| @@ -1,1231 +1,1229 | |||||
| 1 | ''' |
|
1 | ''' | |
| 2 |
|
2 | |||
| 3 | $Author: murco $ |
|
3 | $Author: murco $ | |
| 4 | $Id: JROData.py 173 2012-11-20 15:06:21Z murco $ |
|
4 | $Id: JROData.py 173 2012-11-20 15:06:21Z murco $ | |
| 5 | ''' |
|
5 | ''' | |
| 6 |
|
6 | |||
| 7 | import copy |
|
7 | import copy | |
| 8 | import numpy |
|
8 | import numpy | |
| 9 | import datetime |
|
9 | import datetime | |
| 10 |
|
10 | |||
| 11 | from jroheaderIO import SystemHeader, RadarControllerHeader |
|
11 | from jroheaderIO import SystemHeader, RadarControllerHeader | |
| 12 | from schainpy import cSchain |
|
12 | from schainpy import cSchain | |
| 13 |
|
13 | |||
| 14 |
|
14 | |||
| 15 | def getNumpyDtype(dataTypeCode): |
|
15 | def getNumpyDtype(dataTypeCode): | |
| 16 |
|
16 | |||
| 17 | if dataTypeCode == 0: |
|
17 | if dataTypeCode == 0: | |
| 18 | numpyDtype = numpy.dtype([('real','<i1'),('imag','<i1')]) |
|
18 | numpyDtype = numpy.dtype([('real','<i1'),('imag','<i1')]) | |
| 19 | elif dataTypeCode == 1: |
|
19 | elif dataTypeCode == 1: | |
| 20 | numpyDtype = numpy.dtype([('real','<i2'),('imag','<i2')]) |
|
20 | numpyDtype = numpy.dtype([('real','<i2'),('imag','<i2')]) | |
| 21 | elif dataTypeCode == 2: |
|
21 | elif dataTypeCode == 2: | |
| 22 | numpyDtype = numpy.dtype([('real','<i4'),('imag','<i4')]) |
|
22 | numpyDtype = numpy.dtype([('real','<i4'),('imag','<i4')]) | |
| 23 | elif dataTypeCode == 3: |
|
23 | elif dataTypeCode == 3: | |
| 24 | numpyDtype = numpy.dtype([('real','<i8'),('imag','<i8')]) |
|
24 | numpyDtype = numpy.dtype([('real','<i8'),('imag','<i8')]) | |
| 25 | elif dataTypeCode == 4: |
|
25 | elif dataTypeCode == 4: | |
| 26 | numpyDtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
26 | numpyDtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 27 | elif dataTypeCode == 5: |
|
27 | elif dataTypeCode == 5: | |
| 28 | numpyDtype = numpy.dtype([('real','<f8'),('imag','<f8')]) |
|
28 | numpyDtype = numpy.dtype([('real','<f8'),('imag','<f8')]) | |
| 29 | else: |
|
29 | else: | |
| 30 | raise ValueError, 'dataTypeCode was not defined' |
|
30 | raise ValueError, 'dataTypeCode was not defined' | |
| 31 |
|
31 | |||
| 32 | return numpyDtype |
|
32 | return numpyDtype | |
| 33 |
|
33 | |||
| 34 | def getDataTypeCode(numpyDtype): |
|
34 | def getDataTypeCode(numpyDtype): | |
| 35 |
|
35 | |||
| 36 | if numpyDtype == numpy.dtype([('real','<i1'),('imag','<i1')]): |
|
36 | if numpyDtype == numpy.dtype([('real','<i1'),('imag','<i1')]): | |
| 37 | datatype = 0 |
|
37 | datatype = 0 | |
| 38 | elif numpyDtype == numpy.dtype([('real','<i2'),('imag','<i2')]): |
|
38 | elif numpyDtype == numpy.dtype([('real','<i2'),('imag','<i2')]): | |
| 39 | datatype = 1 |
|
39 | datatype = 1 | |
| 40 | elif numpyDtype == numpy.dtype([('real','<i4'),('imag','<i4')]): |
|
40 | elif numpyDtype == numpy.dtype([('real','<i4'),('imag','<i4')]): | |
| 41 | datatype = 2 |
|
41 | datatype = 2 | |
| 42 | elif numpyDtype == numpy.dtype([('real','<i8'),('imag','<i8')]): |
|
42 | elif numpyDtype == numpy.dtype([('real','<i8'),('imag','<i8')]): | |
| 43 | datatype = 3 |
|
43 | datatype = 3 | |
| 44 | elif numpyDtype == numpy.dtype([('real','<f4'),('imag','<f4')]): |
|
44 | elif numpyDtype == numpy.dtype([('real','<f4'),('imag','<f4')]): | |
| 45 | datatype = 4 |
|
45 | datatype = 4 | |
| 46 | elif numpyDtype == numpy.dtype([('real','<f8'),('imag','<f8')]): |
|
46 | elif numpyDtype == numpy.dtype([('real','<f8'),('imag','<f8')]): | |
| 47 | datatype = 5 |
|
47 | datatype = 5 | |
| 48 | else: |
|
48 | else: | |
| 49 | datatype = None |
|
49 | datatype = None | |
| 50 |
|
50 | |||
| 51 | return datatype |
|
51 | return datatype | |
| 52 |
|
52 | |||
| 53 | def hildebrand_sekhon(data, navg): |
|
53 | def hildebrand_sekhon(data, navg): | |
| 54 | """ |
|
54 | """ | |
| 55 | This method is for the objective determination of the noise level in Doppler spectra. This |
|
55 | This method is for the objective determination of the noise level in Doppler spectra. This | |
| 56 | implementation technique is based on the fact that the standard deviation of the spectral |
|
56 | implementation technique is based on the fact that the standard deviation of the spectral | |
| 57 | densities is equal to the mean spectral density for white Gaussian noise |
|
57 | densities is equal to the mean spectral density for white Gaussian noise | |
| 58 |
|
58 | |||
| 59 | Inputs: |
|
59 | Inputs: | |
| 60 | Data : heights |
|
60 | Data : heights | |
| 61 | navg : numbers of averages |
|
61 | navg : numbers of averages | |
| 62 |
|
62 | |||
| 63 | Return: |
|
63 | Return: | |
| 64 | -1 : any error |
|
64 | -1 : any error | |
| 65 | anoise : noise's level |
|
65 | anoise : noise's level | |
| 66 | """ |
|
66 | """ | |
| 67 |
|
67 | |||
| 68 | sortdata = numpy.sort(data, axis=None) |
|
68 | sortdata = numpy.sort(data, axis=None) | |
| 69 | # lenOfData = len(sortdata) |
|
69 | # lenOfData = len(sortdata) | |
| 70 | # nums_min = lenOfData*0.2 |
|
70 | # nums_min = lenOfData*0.2 | |
| 71 | # |
|
71 | # | |
| 72 | # if nums_min <= 5: |
|
72 | # if nums_min <= 5: | |
| 73 | # nums_min = 5 |
|
73 | # nums_min = 5 | |
| 74 | # |
|
74 | # | |
| 75 | # sump = 0. |
|
75 | # sump = 0. | |
| 76 | # |
|
76 | # | |
| 77 | # sumq = 0. |
|
77 | # sumq = 0. | |
| 78 | # |
|
78 | # | |
| 79 | # j = 0 |
|
79 | # j = 0 | |
| 80 | # |
|
80 | # | |
| 81 | # cont = 1 |
|
81 | # cont = 1 | |
| 82 | # |
|
82 | # | |
| 83 | # while((cont==1)and(j<lenOfData)): |
|
83 | # while((cont==1)and(j<lenOfData)): | |
| 84 | # |
|
84 | # | |
| 85 | # sump += sortdata[j] |
|
85 | # sump += sortdata[j] | |
| 86 | # |
|
86 | # | |
| 87 | # sumq += sortdata[j]**2 |
|
87 | # sumq += sortdata[j]**2 | |
| 88 | # |
|
88 | # | |
| 89 | # if j > nums_min: |
|
89 | # if j > nums_min: | |
| 90 | # rtest = float(j)/(j-1) + 1.0/navg |
|
90 | # rtest = float(j)/(j-1) + 1.0/navg | |
| 91 | # if ((sumq*j) > (rtest*sump**2)): |
|
91 | # if ((sumq*j) > (rtest*sump**2)): | |
| 92 | # j = j - 1 |
|
92 | # j = j - 1 | |
| 93 | # sump = sump - sortdata[j] |
|
93 | # sump = sump - sortdata[j] | |
| 94 | # sumq = sumq - sortdata[j]**2 |
|
94 | # sumq = sumq - sortdata[j]**2 | |
| 95 | # cont = 0 |
|
95 | # cont = 0 | |
| 96 | # |
|
96 | # | |
| 97 | # j += 1 |
|
97 | # j += 1 | |
| 98 | # |
|
98 | # | |
| 99 | # lnoise = sump /j |
|
99 | # lnoise = sump /j | |
| 100 | # |
|
100 | # | |
| 101 | # return lnoise |
|
101 | # return lnoise | |
| 102 |
|
102 | |||
| 103 | return cSchain.hildebrand_sekhon(sortdata, navg) |
|
103 | return cSchain.hildebrand_sekhon(sortdata, navg) | |
| 104 |
|
104 | |||
| 105 |
|
105 | |||
| 106 | class Beam: |
|
106 | class Beam: | |
| 107 |
|
107 | |||
| 108 | def __init__(self): |
|
108 | def __init__(self): | |
| 109 | self.codeList = [] |
|
109 | self.codeList = [] | |
| 110 | self.azimuthList = [] |
|
110 | self.azimuthList = [] | |
| 111 | self.zenithList = [] |
|
111 | self.zenithList = [] | |
| 112 |
|
112 | |||
| 113 | class GenericData(object): |
|
113 | class GenericData(object): | |
| 114 |
|
114 | |||
| 115 | flagNoData = True |
|
115 | flagNoData = True | |
| 116 |
|
116 | |||
| 117 | def copy(self, inputObj=None): |
|
117 | def copy(self, inputObj=None): | |
| 118 |
|
118 | |||
| 119 | if inputObj == None: |
|
119 | if inputObj == None: | |
| 120 | return copy.deepcopy(self) |
|
120 | return copy.deepcopy(self) | |
| 121 |
|
121 | |||
| 122 | for key in inputObj.__dict__.keys(): |
|
122 | for key in inputObj.__dict__.keys(): | |
| 123 |
|
123 | |||
| 124 | attribute = inputObj.__dict__[key] |
|
124 | attribute = inputObj.__dict__[key] | |
| 125 |
|
125 | |||
| 126 | #If this attribute is a tuple or list |
|
126 | #If this attribute is a tuple or list | |
| 127 | if type(inputObj.__dict__[key]) in (tuple, list): |
|
127 | if type(inputObj.__dict__[key]) in (tuple, list): | |
| 128 | self.__dict__[key] = attribute[:] |
|
128 | self.__dict__[key] = attribute[:] | |
| 129 | continue |
|
129 | continue | |
| 130 |
|
130 | |||
| 131 | #If this attribute is another object or instance |
|
131 | #If this attribute is another object or instance | |
| 132 | if hasattr(attribute, '__dict__'): |
|
132 | if hasattr(attribute, '__dict__'): | |
| 133 | self.__dict__[key] = attribute.copy() |
|
133 | self.__dict__[key] = attribute.copy() | |
| 134 | continue |
|
134 | continue | |
| 135 |
|
135 | |||
| 136 | self.__dict__[key] = inputObj.__dict__[key] |
|
136 | self.__dict__[key] = inputObj.__dict__[key] | |
| 137 |
|
137 | |||
| 138 | def deepcopy(self): |
|
138 | def deepcopy(self): | |
| 139 |
|
139 | |||
| 140 | return copy.deepcopy(self) |
|
140 | return copy.deepcopy(self) | |
| 141 |
|
141 | |||
| 142 | def isEmpty(self): |
|
142 | def isEmpty(self): | |
| 143 |
|
143 | |||
| 144 | return self.flagNoData |
|
144 | return self.flagNoData | |
| 145 |
|
145 | |||
| 146 | class JROData(GenericData): |
|
146 | class JROData(GenericData): | |
| 147 |
|
147 | |||
| 148 | # m_BasicHeader = BasicHeader() |
|
148 | # m_BasicHeader = BasicHeader() | |
| 149 | # m_ProcessingHeader = ProcessingHeader() |
|
149 | # m_ProcessingHeader = ProcessingHeader() | |
| 150 |
|
150 | |||
| 151 | systemHeaderObj = SystemHeader() |
|
151 | systemHeaderObj = SystemHeader() | |
| 152 |
|
152 | |||
| 153 | radarControllerHeaderObj = RadarControllerHeader() |
|
153 | radarControllerHeaderObj = RadarControllerHeader() | |
| 154 |
|
154 | |||
| 155 | # data = None |
|
155 | # data = None | |
| 156 |
|
156 | |||
| 157 | type = None |
|
157 | type = None | |
| 158 |
|
158 | |||
| 159 | datatype = None #dtype but in string |
|
159 | datatype = None #dtype but in string | |
| 160 |
|
160 | |||
| 161 | # dtype = None |
|
161 | # dtype = None | |
| 162 |
|
162 | |||
| 163 | # nChannels = None |
|
163 | # nChannels = None | |
| 164 |
|
164 | |||
| 165 | # nHeights = None |
|
165 | # nHeights = None | |
| 166 |
|
166 | |||
| 167 | nProfiles = None |
|
167 | nProfiles = None | |
| 168 |
|
168 | |||
| 169 | heightList = None |
|
169 | heightList = None | |
| 170 |
|
170 | |||
| 171 | channelList = None |
|
171 | channelList = None | |
| 172 |
|
172 | |||
| 173 | flagDiscontinuousBlock = False |
|
173 | flagDiscontinuousBlock = False | |
| 174 |
|
174 | |||
| 175 | useLocalTime = False |
|
175 | useLocalTime = False | |
| 176 |
|
176 | |||
| 177 | utctime = None |
|
177 | utctime = None | |
| 178 |
|
178 | |||
| 179 | timeZone = None |
|
179 | timeZone = None | |
| 180 |
|
180 | |||
| 181 | dstFlag = None |
|
181 | dstFlag = None | |
| 182 |
|
182 | |||
| 183 | errorCount = None |
|
183 | errorCount = None | |
| 184 |
|
184 | |||
| 185 | blocksize = None |
|
185 | blocksize = None | |
| 186 |
|
186 | |||
| 187 | # nCode = None |
|
187 | # nCode = None | |
| 188 | # |
|
188 | # | |
| 189 | # nBaud = None |
|
189 | # nBaud = None | |
| 190 | # |
|
190 | # | |
| 191 | # code = None |
|
191 | # code = None | |
| 192 |
|
192 | |||
| 193 | flagDecodeData = False #asumo q la data no esta decodificada |
|
193 | flagDecodeData = False #asumo q la data no esta decodificada | |
| 194 |
|
194 | |||
| 195 | flagDeflipData = False #asumo q la data no esta sin flip |
|
195 | flagDeflipData = False #asumo q la data no esta sin flip | |
| 196 |
|
196 | |||
| 197 | flagShiftFFT = False |
|
197 | flagShiftFFT = False | |
| 198 |
|
198 | |||
| 199 | # ippSeconds = None |
|
199 | # ippSeconds = None | |
| 200 |
|
200 | |||
| 201 | # timeInterval = None |
|
201 | # timeInterval = None | |
| 202 |
|
202 | |||
| 203 | nCohInt = None |
|
203 | nCohInt = None | |
| 204 |
|
204 | |||
| 205 | # noise = None |
|
205 | # noise = None | |
| 206 |
|
206 | |||
| 207 | windowOfFilter = 1 |
|
207 | windowOfFilter = 1 | |
| 208 |
|
208 | |||
| 209 | #Speed of ligth |
|
209 | #Speed of ligth | |
| 210 | C = 3e8 |
|
210 | C = 3e8 | |
| 211 |
|
211 | |||
| 212 | frequency = 49.92e6 |
|
212 | frequency = 49.92e6 | |
| 213 |
|
213 | |||
| 214 | realtime = False |
|
214 | realtime = False | |
| 215 |
|
215 | |||
| 216 | beacon_heiIndexList = None |
|
216 | beacon_heiIndexList = None | |
| 217 |
|
217 | |||
| 218 | last_block = None |
|
218 | last_block = None | |
| 219 |
|
219 | |||
| 220 | blocknow = None |
|
220 | blocknow = None | |
| 221 |
|
221 | |||
| 222 | azimuth = None |
|
222 | azimuth = None | |
| 223 |
|
223 | |||
| 224 | zenith = None |
|
224 | zenith = None | |
| 225 |
|
225 | |||
| 226 | beam = Beam() |
|
226 | beam = Beam() | |
| 227 |
|
227 | |||
| 228 | profileIndex = None |
|
228 | profileIndex = None | |
| 229 |
|
229 | |||
| 230 | def getNoise(self): |
|
230 | def getNoise(self): | |
| 231 |
|
231 | |||
| 232 | raise NotImplementedError |
|
232 | raise NotImplementedError | |
| 233 |
|
233 | |||
| 234 | def getNChannels(self): |
|
234 | def getNChannels(self): | |
| 235 |
|
235 | |||
| 236 | return len(self.channelList) |
|
236 | return len(self.channelList) | |
| 237 |
|
237 | |||
| 238 | def getChannelIndexList(self): |
|
238 | def getChannelIndexList(self): | |
| 239 |
|
239 | |||
| 240 | return range(self.nChannels) |
|
240 | return range(self.nChannels) | |
| 241 |
|
241 | |||
| 242 | def getNHeights(self): |
|
242 | def getNHeights(self): | |
| 243 |
|
243 | |||
| 244 | return len(self.heightList) |
|
244 | return len(self.heightList) | |
| 245 |
|
245 | |||
| 246 | def getHeiRange(self, extrapoints=0): |
|
246 | def getHeiRange(self, extrapoints=0): | |
| 247 |
|
247 | |||
| 248 | heis = self.heightList |
|
248 | heis = self.heightList | |
| 249 | # deltah = self.heightList[1] - self.heightList[0] |
|
249 | # deltah = self.heightList[1] - self.heightList[0] | |
| 250 | # |
|
250 | # | |
| 251 | # heis.append(self.heightList[-1]) |
|
251 | # heis.append(self.heightList[-1]) | |
| 252 |
|
252 | |||
| 253 | return heis |
|
253 | return heis | |
| 254 |
|
254 | |||
| 255 | def getDeltaH(self): |
|
255 | def getDeltaH(self): | |
| 256 |
|
256 | |||
| 257 | delta = self.heightList[1] - self.heightList[0] |
|
257 | delta = self.heightList[1] - self.heightList[0] | |
| 258 |
|
258 | |||
| 259 | return delta |
|
259 | return delta | |
| 260 |
|
260 | |||
| 261 | def getltctime(self): |
|
261 | def getltctime(self): | |
| 262 |
|
262 | |||
| 263 | if self.useLocalTime: |
|
263 | if self.useLocalTime: | |
| 264 | return self.utctime - self.timeZone*60 |
|
264 | return self.utctime - self.timeZone*60 | |
| 265 |
|
265 | |||
| 266 | return self.utctime |
|
266 | return self.utctime | |
| 267 |
|
267 | |||
| 268 | def getDatatime(self): |
|
268 | def getDatatime(self): | |
| 269 |
|
269 | |||
| 270 | datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
270 | datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime) | |
| 271 | return datatimeValue |
|
271 | return datatimeValue | |
| 272 |
|
272 | |||
| 273 | def getTimeRange(self): |
|
273 | def getTimeRange(self): | |
| 274 |
|
274 | |||
| 275 | datatime = [] |
|
275 | datatime = [] | |
| 276 |
|
276 | |||
| 277 | datatime.append(self.ltctime) |
|
277 | datatime.append(self.ltctime) | |
| 278 | datatime.append(self.ltctime + self.timeInterval+1) |
|
278 | datatime.append(self.ltctime + self.timeInterval+1) | |
| 279 |
|
279 | |||
| 280 | datatime = numpy.array(datatime) |
|
280 | datatime = numpy.array(datatime) | |
| 281 |
|
281 | |||
| 282 | return datatime |
|
282 | return datatime | |
| 283 |
|
283 | |||
| 284 | def getFmaxTimeResponse(self): |
|
284 | def getFmaxTimeResponse(self): | |
| 285 |
|
285 | |||
| 286 | period = (10**-6)*self.getDeltaH()/(0.15) |
|
286 | period = (10**-6)*self.getDeltaH()/(0.15) | |
| 287 |
|
287 | |||
| 288 | PRF = 1./(period * self.nCohInt) |
|
288 | PRF = 1./(period * self.nCohInt) | |
| 289 |
|
289 | |||
| 290 | fmax = PRF |
|
290 | fmax = PRF | |
| 291 |
|
291 | |||
| 292 | return fmax |
|
292 | return fmax | |
| 293 |
|
293 | |||
| 294 | def getFmax(self): |
|
294 | def getFmax(self): | |
| 295 |
|
295 | |||
| 296 | PRF = 1./(self.ippSeconds * self.nCohInt) |
|
296 | PRF = 1./(self.ippSeconds * self.nCohInt) | |
| 297 |
|
297 | |||
| 298 | fmax = PRF |
|
298 | fmax = PRF | |
| 299 |
|
299 | |||
| 300 | return fmax |
|
300 | return fmax | |
| 301 |
|
301 | |||
| 302 | def getVmax(self): |
|
302 | def getVmax(self): | |
| 303 |
|
303 | |||
| 304 | _lambda = self.C/self.frequency |
|
304 | _lambda = self.C/self.frequency | |
| 305 |
|
305 | |||
| 306 | vmax = self.getFmax() * _lambda/2 |
|
306 | vmax = self.getFmax() * _lambda/2 | |
| 307 |
|
307 | |||
| 308 | return vmax |
|
308 | return vmax | |
| 309 |
|
309 | |||
| 310 | def get_ippSeconds(self): |
|
310 | def get_ippSeconds(self): | |
| 311 | ''' |
|
311 | ''' | |
| 312 | ''' |
|
312 | ''' | |
| 313 | return self.radarControllerHeaderObj.ippSeconds |
|
313 | return self.radarControllerHeaderObj.ippSeconds | |
| 314 |
|
314 | |||
| 315 | def set_ippSeconds(self, ippSeconds): |
|
315 | def set_ippSeconds(self, ippSeconds): | |
| 316 | ''' |
|
316 | ''' | |
| 317 | ''' |
|
317 | ''' | |
| 318 |
|
318 | |||
| 319 | self.radarControllerHeaderObj.ippSeconds = ippSeconds |
|
319 | self.radarControllerHeaderObj.ippSeconds = ippSeconds | |
| 320 |
|
320 | |||
| 321 | return |
|
321 | return | |
| 322 |
|
322 | |||
| 323 | def get_dtype(self): |
|
323 | def get_dtype(self): | |
| 324 | ''' |
|
324 | ''' | |
| 325 | ''' |
|
325 | ''' | |
| 326 | return getNumpyDtype(self.datatype) |
|
326 | return getNumpyDtype(self.datatype) | |
| 327 |
|
327 | |||
| 328 | def set_dtype(self, numpyDtype): |
|
328 | def set_dtype(self, numpyDtype): | |
| 329 | ''' |
|
329 | ''' | |
| 330 | ''' |
|
330 | ''' | |
| 331 |
|
331 | |||
| 332 | self.datatype = getDataTypeCode(numpyDtype) |
|
332 | self.datatype = getDataTypeCode(numpyDtype) | |
| 333 |
|
333 | |||
| 334 | def get_code(self): |
|
334 | def get_code(self): | |
| 335 | ''' |
|
335 | ''' | |
| 336 | ''' |
|
336 | ''' | |
| 337 | return self.radarControllerHeaderObj.code |
|
337 | return self.radarControllerHeaderObj.code | |
| 338 |
|
338 | |||
| 339 | def set_code(self, code): |
|
339 | def set_code(self, code): | |
| 340 | ''' |
|
340 | ''' | |
| 341 | ''' |
|
341 | ''' | |
| 342 | self.radarControllerHeaderObj.code = code |
|
342 | self.radarControllerHeaderObj.code = code | |
| 343 |
|
343 | |||
| 344 | return |
|
344 | return | |
| 345 |
|
345 | |||
| 346 | def get_ncode(self): |
|
346 | def get_ncode(self): | |
| 347 | ''' |
|
347 | ''' | |
| 348 | ''' |
|
348 | ''' | |
| 349 | return self.radarControllerHeaderObj.nCode |
|
349 | return self.radarControllerHeaderObj.nCode | |
| 350 |
|
350 | |||
| 351 | def set_ncode(self, nCode): |
|
351 | def set_ncode(self, nCode): | |
| 352 | ''' |
|
352 | ''' | |
| 353 | ''' |
|
353 | ''' | |
| 354 | self.radarControllerHeaderObj.nCode = nCode |
|
354 | self.radarControllerHeaderObj.nCode = nCode | |
| 355 |
|
355 | |||
| 356 | return |
|
356 | return | |
| 357 |
|
357 | |||
| 358 | def get_nbaud(self): |
|
358 | def get_nbaud(self): | |
| 359 | ''' |
|
359 | ''' | |
| 360 | ''' |
|
360 | ''' | |
| 361 | return self.radarControllerHeaderObj.nBaud |
|
361 | return self.radarControllerHeaderObj.nBaud | |
| 362 |
|
362 | |||
| 363 | def set_nbaud(self, nBaud): |
|
363 | def set_nbaud(self, nBaud): | |
| 364 | ''' |
|
364 | ''' | |
| 365 | ''' |
|
365 | ''' | |
| 366 | self.radarControllerHeaderObj.nBaud = nBaud |
|
366 | self.radarControllerHeaderObj.nBaud = nBaud | |
| 367 |
|
367 | |||
| 368 | return |
|
368 | return | |
| 369 |
|
369 | |||
| 370 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
370 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") | |
| 371 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
371 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") | |
| 372 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
372 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") | |
| 373 | #noise = property(getNoise, "I'm the 'nHeights' property.") |
|
373 | #noise = property(getNoise, "I'm the 'nHeights' property.") | |
| 374 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
374 | datatime = property(getDatatime, "I'm the 'datatime' property") | |
| 375 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
375 | ltctime = property(getltctime, "I'm the 'ltctime' property") | |
| 376 | ippSeconds = property(get_ippSeconds, set_ippSeconds) |
|
376 | ippSeconds = property(get_ippSeconds, set_ippSeconds) | |
| 377 | dtype = property(get_dtype, set_dtype) |
|
377 | dtype = property(get_dtype, set_dtype) | |
| 378 | # timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
378 | # timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") | |
| 379 | code = property(get_code, set_code) |
|
379 | code = property(get_code, set_code) | |
| 380 | nCode = property(get_ncode, set_ncode) |
|
380 | nCode = property(get_ncode, set_ncode) | |
| 381 | nBaud = property(get_nbaud, set_nbaud) |
|
381 | nBaud = property(get_nbaud, set_nbaud) | |
| 382 |
|
382 | |||
| 383 | class Voltage(JROData): |
|
383 | class Voltage(JROData): | |
| 384 |
|
384 | |||
| 385 | #data es un numpy array de 2 dmensiones (canales, alturas) |
|
385 | #data es un numpy array de 2 dmensiones (canales, alturas) | |
| 386 | data = None |
|
386 | data = None | |
| 387 |
|
387 | |||
| 388 | def __init__(self): |
|
388 | def __init__(self): | |
| 389 | ''' |
|
389 | ''' | |
| 390 | Constructor |
|
390 | Constructor | |
| 391 | ''' |
|
391 | ''' | |
| 392 |
|
392 | |||
| 393 | self.useLocalTime = True |
|
393 | self.useLocalTime = True | |
| 394 |
|
394 | |||
| 395 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
395 | self.radarControllerHeaderObj = RadarControllerHeader() | |
| 396 |
|
396 | |||
| 397 | self.systemHeaderObj = SystemHeader() |
|
397 | self.systemHeaderObj = SystemHeader() | |
| 398 |
|
398 | |||
| 399 | self.type = "Voltage" |
|
399 | self.type = "Voltage" | |
| 400 |
|
400 | |||
| 401 | self.data = None |
|
401 | self.data = None | |
| 402 |
|
402 | |||
| 403 | # self.dtype = None |
|
403 | # self.dtype = None | |
| 404 |
|
404 | |||
| 405 | # self.nChannels = 0 |
|
405 | # self.nChannels = 0 | |
| 406 |
|
406 | |||
| 407 | # self.nHeights = 0 |
|
407 | # self.nHeights = 0 | |
| 408 |
|
408 | |||
| 409 | self.nProfiles = None |
|
409 | self.nProfiles = None | |
| 410 |
|
410 | |||
| 411 | self.heightList = None |
|
411 | self.heightList = None | |
| 412 |
|
412 | |||
| 413 | self.channelList = None |
|
413 | self.channelList = None | |
| 414 |
|
414 | |||
| 415 | # self.channelIndexList = None |
|
415 | # self.channelIndexList = None | |
| 416 |
|
416 | |||
| 417 | self.flagNoData = True |
|
417 | self.flagNoData = True | |
| 418 |
|
418 | |||
| 419 | self.flagDiscontinuousBlock = False |
|
419 | self.flagDiscontinuousBlock = False | |
| 420 |
|
420 | |||
| 421 | self.utctime = None |
|
421 | self.utctime = None | |
| 422 |
|
422 | |||
| 423 | self.timeZone = None |
|
423 | self.timeZone = None | |
| 424 |
|
424 | |||
| 425 | self.dstFlag = None |
|
425 | self.dstFlag = None | |
| 426 |
|
426 | |||
| 427 | self.errorCount = None |
|
427 | self.errorCount = None | |
| 428 |
|
428 | |||
| 429 | self.nCohInt = None |
|
429 | self.nCohInt = None | |
| 430 |
|
430 | |||
| 431 | self.blocksize = None |
|
431 | self.blocksize = None | |
| 432 |
|
432 | |||
| 433 | self.flagDecodeData = False #asumo q la data no esta decodificada |
|
433 | self.flagDecodeData = False #asumo q la data no esta decodificada | |
| 434 |
|
434 | |||
| 435 | self.flagDeflipData = False #asumo q la data no esta sin flip |
|
435 | self.flagDeflipData = False #asumo q la data no esta sin flip | |
| 436 |
|
436 | |||
| 437 | self.flagShiftFFT = False |
|
437 | self.flagShiftFFT = False | |
| 438 |
|
438 | |||
| 439 | self.flagDataAsBlock = False #Asumo que la data es leida perfil a perfil |
|
439 | self.flagDataAsBlock = False #Asumo que la data es leida perfil a perfil | |
| 440 |
|
440 | |||
| 441 | self.profileIndex = 0 |
|
441 | self.profileIndex = 0 | |
| 442 |
|
442 | |||
| 443 | def getNoisebyHildebrand(self, channel = None): |
|
443 | def getNoisebyHildebrand(self, channel = None): | |
| 444 | """ |
|
444 | """ | |
| 445 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
445 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon | |
| 446 |
|
446 | |||
| 447 | Return: |
|
447 | Return: | |
| 448 | noiselevel |
|
448 | noiselevel | |
| 449 | """ |
|
449 | """ | |
| 450 |
|
450 | |||
| 451 | if channel != None: |
|
451 | if channel != None: | |
| 452 | data = self.data[channel] |
|
452 | data = self.data[channel] | |
| 453 | nChannels = 1 |
|
453 | nChannels = 1 | |
| 454 | else: |
|
454 | else: | |
| 455 | data = self.data |
|
455 | data = self.data | |
| 456 | nChannels = self.nChannels |
|
456 | nChannels = self.nChannels | |
| 457 |
|
457 | |||
| 458 | noise = numpy.zeros(nChannels) |
|
458 | noise = numpy.zeros(nChannels) | |
| 459 | power = data * numpy.conjugate(data) |
|
459 | power = data * numpy.conjugate(data) | |
| 460 |
|
460 | |||
| 461 | for thisChannel in range(nChannels): |
|
461 | for thisChannel in range(nChannels): | |
| 462 | if nChannels == 1: |
|
462 | if nChannels == 1: | |
| 463 | daux = power[:].real |
|
463 | daux = power[:].real | |
| 464 | else: |
|
464 | else: | |
| 465 | daux = power[thisChannel,:].real |
|
465 | daux = power[thisChannel,:].real | |
| 466 | noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt) |
|
466 | noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt) | |
| 467 |
|
467 | |||
| 468 | return noise |
|
468 | return noise | |
| 469 |
|
469 | |||
| 470 | def getNoise(self, type = 1, channel = None): |
|
470 | def getNoise(self, type = 1, channel = None): | |
| 471 |
|
471 | |||
| 472 | if type == 1: |
|
472 | if type == 1: | |
| 473 | noise = self.getNoisebyHildebrand(channel) |
|
473 | noise = self.getNoisebyHildebrand(channel) | |
| 474 |
|
474 | |||
| 475 | return noise |
|
475 | return noise | |
| 476 |
|
476 | |||
| 477 | def getPower(self, channel = None): |
|
477 | def getPower(self, channel = None): | |
| 478 |
|
478 | |||
| 479 | if channel != None: |
|
479 | if channel != None: | |
| 480 | data = self.data[channel] |
|
480 | data = self.data[channel] | |
| 481 | else: |
|
481 | else: | |
| 482 | data = self.data |
|
482 | data = self.data | |
| 483 |
|
483 | |||
| 484 | power = data * numpy.conjugate(data) |
|
484 | power = data * numpy.conjugate(data) | |
| 485 | powerdB = 10*numpy.log10(power.real) |
|
485 | powerdB = 10*numpy.log10(power.real) | |
| 486 | powerdB = numpy.squeeze(powerdB) |
|
486 | powerdB = numpy.squeeze(powerdB) | |
| 487 |
|
487 | |||
| 488 | return powerdB |
|
488 | return powerdB | |
| 489 |
|
489 | |||
| 490 | def getTimeInterval(self): |
|
490 | def getTimeInterval(self): | |
| 491 |
|
491 | |||
| 492 | timeInterval = self.ippSeconds * self.nCohInt |
|
492 | timeInterval = self.ippSeconds * self.nCohInt | |
| 493 |
|
493 | |||
| 494 | return timeInterval |
|
494 | return timeInterval | |
| 495 |
|
495 | |||
| 496 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
496 | noise = property(getNoise, "I'm the 'nHeights' property.") | |
| 497 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
497 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") | |
| 498 |
|
498 | |||
| 499 | class Spectra(JROData): |
|
499 | class Spectra(JROData): | |
| 500 |
|
500 | |||
| 501 | #data spc es un numpy array de 2 dmensiones (canales, perfiles, alturas) |
|
501 | #data spc es un numpy array de 2 dmensiones (canales, perfiles, alturas) | |
| 502 | data_spc = None |
|
502 | data_spc = None | |
| 503 |
|
503 | |||
| 504 | #data cspc es un numpy array de 2 dmensiones (canales, pares, alturas) |
|
504 | #data cspc es un numpy array de 2 dmensiones (canales, pares, alturas) | |
| 505 | data_cspc = None |
|
505 | data_cspc = None | |
| 506 |
|
506 | |||
| 507 | #data dc es un numpy array de 2 dmensiones (canales, alturas) |
|
507 | #data dc es un numpy array de 2 dmensiones (canales, alturas) | |
| 508 | data_dc = None |
|
508 | data_dc = None | |
| 509 |
|
509 | |||
| 510 | #data power |
|
510 | #data power | |
| 511 | data_pwr = None |
|
511 | data_pwr = None | |
| 512 |
|
512 | |||
| 513 | nFFTPoints = None |
|
513 | nFFTPoints = None | |
| 514 |
|
514 | |||
| 515 | # nPairs = None |
|
515 | # nPairs = None | |
| 516 |
|
516 | |||
| 517 | pairsList = None |
|
517 | pairsList = None | |
| 518 |
|
518 | |||
| 519 | nIncohInt = None |
|
519 | nIncohInt = None | |
| 520 |
|
520 | |||
| 521 | wavelength = None #Necesario para cacular el rango de velocidad desde la frecuencia |
|
521 | wavelength = None #Necesario para cacular el rango de velocidad desde la frecuencia | |
| 522 |
|
522 | |||
| 523 | nCohInt = None #se requiere para determinar el valor de timeInterval |
|
523 | nCohInt = None #se requiere para determinar el valor de timeInterval | |
| 524 |
|
524 | |||
| 525 | ippFactor = None |
|
525 | ippFactor = None | |
| 526 |
|
526 | |||
| 527 | profileIndex = 0 |
|
527 | profileIndex = 0 | |
| 528 |
|
528 | |||
| 529 | plotting = "spectra" |
|
529 | plotting = "spectra" | |
| 530 |
|
530 | |||
| 531 | def __init__(self): |
|
531 | def __init__(self): | |
| 532 | ''' |
|
532 | ''' | |
| 533 | Constructor |
|
533 | Constructor | |
| 534 | ''' |
|
534 | ''' | |
| 535 |
|
535 | |||
| 536 | self.useLocalTime = True |
|
536 | self.useLocalTime = True | |
| 537 |
|
537 | |||
| 538 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
538 | self.radarControllerHeaderObj = RadarControllerHeader() | |
| 539 |
|
539 | |||
| 540 | self.systemHeaderObj = SystemHeader() |
|
540 | self.systemHeaderObj = SystemHeader() | |
| 541 |
|
541 | |||
| 542 | self.type = "Spectra" |
|
542 | self.type = "Spectra" | |
| 543 |
|
543 | |||
| 544 | # self.data = None |
|
544 | # self.data = None | |
| 545 |
|
545 | |||
| 546 | # self.dtype = None |
|
546 | # self.dtype = None | |
| 547 |
|
547 | |||
| 548 | # self.nChannels = 0 |
|
548 | # self.nChannels = 0 | |
| 549 |
|
549 | |||
| 550 | # self.nHeights = 0 |
|
550 | # self.nHeights = 0 | |
| 551 |
|
551 | |||
| 552 | self.nProfiles = None |
|
552 | self.nProfiles = None | |
| 553 |
|
553 | |||
| 554 | self.heightList = None |
|
554 | self.heightList = None | |
| 555 |
|
555 | |||
| 556 | self.channelList = None |
|
556 | self.channelList = None | |
| 557 |
|
557 | |||
| 558 | # self.channelIndexList = None |
|
558 | # self.channelIndexList = None | |
| 559 |
|
559 | |||
| 560 | self.pairsList = None |
|
560 | self.pairsList = None | |
| 561 |
|
561 | |||
| 562 | self.flagNoData = True |
|
562 | self.flagNoData = True | |
| 563 |
|
563 | |||
| 564 | self.flagDiscontinuousBlock = False |
|
564 | self.flagDiscontinuousBlock = False | |
| 565 |
|
565 | |||
| 566 | self.utctime = None |
|
566 | self.utctime = None | |
| 567 |
|
567 | |||
| 568 | self.nCohInt = None |
|
568 | self.nCohInt = None | |
| 569 |
|
569 | |||
| 570 | self.nIncohInt = None |
|
570 | self.nIncohInt = None | |
| 571 |
|
571 | |||
| 572 | self.blocksize = None |
|
572 | self.blocksize = None | |
| 573 |
|
573 | |||
| 574 | self.nFFTPoints = None |
|
574 | self.nFFTPoints = None | |
| 575 |
|
575 | |||
| 576 | self.wavelength = None |
|
576 | self.wavelength = None | |
| 577 |
|
577 | |||
| 578 | self.flagDecodeData = False #asumo q la data no esta decodificada |
|
578 | self.flagDecodeData = False #asumo q la data no esta decodificada | |
| 579 |
|
579 | |||
| 580 | self.flagDeflipData = False #asumo q la data no esta sin flip |
|
580 | self.flagDeflipData = False #asumo q la data no esta sin flip | |
| 581 |
|
581 | |||
| 582 | self.flagShiftFFT = False |
|
582 | self.flagShiftFFT = False | |
| 583 |
|
583 | |||
| 584 | self.ippFactor = 1 |
|
584 | self.ippFactor = 1 | |
| 585 |
|
585 | |||
| 586 | #self.noise = None |
|
586 | #self.noise = None | |
| 587 |
|
587 | |||
| 588 | self.beacon_heiIndexList = [] |
|
588 | self.beacon_heiIndexList = [] | |
| 589 |
|
589 | |||
| 590 | self.noise_estimation = None |
|
590 | self.noise_estimation = None | |
| 591 |
|
591 | |||
| 592 |
|
592 | |||
| 593 | def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
593 | def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): | |
| 594 | """ |
|
594 | """ | |
| 595 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon |
|
595 | Determino el nivel de ruido usando el metodo Hildebrand-Sekhon | |
| 596 |
|
596 | |||
| 597 | Return: |
|
597 | Return: | |
| 598 | noiselevel |
|
598 | noiselevel | |
| 599 | """ |
|
599 | """ | |
| 600 |
|
600 | |||
| 601 | noise = numpy.zeros(self.nChannels) |
|
601 | noise = numpy.zeros(self.nChannels) | |
| 602 |
|
602 | |||
| 603 | for channel in range(self.nChannels): |
|
603 | for channel in range(self.nChannels): | |
| 604 | daux = self.data_spc[channel,xmin_index:xmax_index,ymin_index:ymax_index] |
|
604 | daux = self.data_spc[channel,xmin_index:xmax_index,ymin_index:ymax_index] | |
| 605 | noise[channel] = hildebrand_sekhon(daux, self.nIncohInt) |
|
605 | noise[channel] = hildebrand_sekhon(daux, self.nIncohInt) | |
| 606 |
|
606 | |||
| 607 | return noise |
|
607 | return noise | |
| 608 |
|
608 | |||
| 609 | def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): |
|
609 | def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None): | |
| 610 |
|
610 | |||
| 611 | if self.noise_estimation is not None: |
|
611 | if self.noise_estimation is not None: | |
| 612 | return self.noise_estimation #this was estimated by getNoise Operation defined in jroproc_spectra.py |
|
612 | return self.noise_estimation #this was estimated by getNoise Operation defined in jroproc_spectra.py | |
| 613 | else: |
|
613 | else: | |
| 614 | noise = self.getNoisebyHildebrand(xmin_index, xmax_index, ymin_index, ymax_index) |
|
614 | noise = self.getNoisebyHildebrand(xmin_index, xmax_index, ymin_index, ymax_index) | |
| 615 | return noise |
|
615 | return noise | |
| 616 |
|
616 | |||
| 617 | def getFreqRangeTimeResponse(self, extrapoints=0): |
|
617 | def getFreqRangeTimeResponse(self, extrapoints=0): | |
| 618 |
|
618 | |||
| 619 | deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints*self.ippFactor) |
|
619 | deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints*self.ippFactor) | |
| 620 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 |
|
620 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 | |
| 621 |
|
621 | |||
| 622 | return freqrange |
|
622 | return freqrange | |
| 623 |
|
623 | |||
| 624 | def getAcfRange(self, extrapoints=0): |
|
624 | def getAcfRange(self, extrapoints=0): | |
| 625 |
|
625 | |||
| 626 | deltafreq = 10./(self.getFmax() / (self.nFFTPoints*self.ippFactor)) |
|
626 | deltafreq = 10./(self.getFmax() / (self.nFFTPoints*self.ippFactor)) | |
| 627 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 |
|
627 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 | |
| 628 |
|
628 | |||
| 629 | return freqrange |
|
629 | return freqrange | |
| 630 |
|
630 | |||
| 631 | def getFreqRange(self, extrapoints=0): |
|
631 | def getFreqRange(self, extrapoints=0): | |
| 632 |
|
632 | |||
| 633 | deltafreq = self.getFmax() / (self.nFFTPoints*self.ippFactor) |
|
633 | deltafreq = self.getFmax() / (self.nFFTPoints*self.ippFactor) | |
| 634 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 |
|
634 | freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2 | |
| 635 |
|
635 | |||
| 636 | return freqrange |
|
636 | return freqrange | |
| 637 |
|
637 | |||
| 638 | def getVelRange(self, extrapoints=0): |
|
638 | def getVelRange(self, extrapoints=0): | |
| 639 |
|
639 | |||
| 640 | print 'VELMAX', self.getVmax() |
|
|||
| 641 | asdasdasd |
|
|||
| 642 | deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor) |
|
640 | deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor) | |
| 643 | velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) #- deltav/2 |
|
641 | velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) #- deltav/2 | |
| 644 |
|
642 | |||
| 645 | return velrange |
|
643 | return velrange | |
| 646 |
|
644 | |||
| 647 | def getNPairs(self): |
|
645 | def getNPairs(self): | |
| 648 |
|
646 | |||
| 649 | return len(self.pairsList) |
|
647 | return len(self.pairsList) | |
| 650 |
|
648 | |||
| 651 | def getPairsIndexList(self): |
|
649 | def getPairsIndexList(self): | |
| 652 |
|
650 | |||
| 653 | return range(self.nPairs) |
|
651 | return range(self.nPairs) | |
| 654 |
|
652 | |||
| 655 | def getNormFactor(self): |
|
653 | def getNormFactor(self): | |
| 656 |
|
654 | |||
| 657 | pwcode = 1 |
|
655 | pwcode = 1 | |
| 658 |
|
656 | |||
| 659 | if self.flagDecodeData: |
|
657 | if self.flagDecodeData: | |
| 660 | pwcode = numpy.sum(self.code[0]**2) |
|
658 | pwcode = numpy.sum(self.code[0]**2) | |
| 661 | #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
659 | #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter | |
| 662 | normFactor = self.nProfiles*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter |
|
660 | normFactor = self.nProfiles*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter | |
| 663 |
|
661 | |||
| 664 | return normFactor |
|
662 | return normFactor | |
| 665 |
|
663 | |||
| 666 | def getFlagCspc(self): |
|
664 | def getFlagCspc(self): | |
| 667 |
|
665 | |||
| 668 | if self.data_cspc is None: |
|
666 | if self.data_cspc is None: | |
| 669 | return True |
|
667 | return True | |
| 670 |
|
668 | |||
| 671 | return False |
|
669 | return False | |
| 672 |
|
670 | |||
| 673 | def getFlagDc(self): |
|
671 | def getFlagDc(self): | |
| 674 |
|
672 | |||
| 675 | if self.data_dc is None: |
|
673 | if self.data_dc is None: | |
| 676 | return True |
|
674 | return True | |
| 677 |
|
675 | |||
| 678 | return False |
|
676 | return False | |
| 679 |
|
677 | |||
| 680 | def getTimeInterval(self): |
|
678 | def getTimeInterval(self): | |
| 681 |
|
679 | |||
| 682 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles |
|
680 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles | |
| 683 |
|
681 | |||
| 684 | return timeInterval |
|
682 | return timeInterval | |
| 685 |
|
683 | |||
| 686 | def getPower(self): |
|
684 | def getPower(self): | |
| 687 |
|
685 | |||
| 688 | factor = self.normFactor |
|
686 | factor = self.normFactor | |
| 689 | z = self.data_spc/factor |
|
687 | z = self.data_spc/factor | |
| 690 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
688 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 691 | avg = numpy.average(z, axis=1) |
|
689 | avg = numpy.average(z, axis=1) | |
| 692 |
|
690 | |||
| 693 | return 10*numpy.log10(avg) |
|
691 | return 10*numpy.log10(avg) | |
| 694 |
|
692 | |||
| 695 | def getCoherence(self, pairsList=None, phase=False): |
|
693 | def getCoherence(self, pairsList=None, phase=False): | |
| 696 |
|
694 | |||
| 697 | z = [] |
|
695 | z = [] | |
| 698 | if pairsList is None: |
|
696 | if pairsList is None: | |
| 699 | pairsIndexList = self.pairsIndexList |
|
697 | pairsIndexList = self.pairsIndexList | |
| 700 | else: |
|
698 | else: | |
| 701 | pairsIndexList = [] |
|
699 | pairsIndexList = [] | |
| 702 | for pair in pairsList: |
|
700 | for pair in pairsList: | |
| 703 | if pair not in self.pairsList: |
|
701 | if pair not in self.pairsList: | |
| 704 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
702 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) | |
| 705 | pairsIndexList.append(self.pairsList.index(pair)) |
|
703 | pairsIndexList.append(self.pairsList.index(pair)) | |
| 706 | for i in range(len(pairsIndexList)): |
|
704 | for i in range(len(pairsIndexList)): | |
| 707 | pair = self.pairsList[pairsIndexList[i]] |
|
705 | pair = self.pairsList[pairsIndexList[i]] | |
| 708 | ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0) |
|
706 | ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0) | |
| 709 | powa = numpy.average(self.data_spc[pair[0], :, :], axis=0) |
|
707 | powa = numpy.average(self.data_spc[pair[0], :, :], axis=0) | |
| 710 | powb = numpy.average(self.data_spc[pair[1], :, :], axis=0) |
|
708 | powb = numpy.average(self.data_spc[pair[1], :, :], axis=0) | |
| 711 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
709 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 712 | if phase: |
|
710 | if phase: | |
| 713 | data = numpy.arctan2(avgcoherenceComplex.imag, |
|
711 | data = numpy.arctan2(avgcoherenceComplex.imag, | |
| 714 | avgcoherenceComplex.real)*180/numpy.pi |
|
712 | avgcoherenceComplex.real)*180/numpy.pi | |
| 715 | else: |
|
713 | else: | |
| 716 | data = numpy.abs(avgcoherenceComplex) |
|
714 | data = numpy.abs(avgcoherenceComplex) | |
| 717 |
|
715 | |||
| 718 | z.append(data) |
|
716 | z.append(data) | |
| 719 |
|
717 | |||
| 720 | return numpy.array(z) |
|
718 | return numpy.array(z) | |
| 721 |
|
719 | |||
| 722 | def setValue(self, value): |
|
720 | def setValue(self, value): | |
| 723 |
|
721 | |||
| 724 | print "This property should not be initialized" |
|
722 | print "This property should not be initialized" | |
| 725 |
|
723 | |||
| 726 | return |
|
724 | return | |
| 727 |
|
725 | |||
| 728 | nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.") |
|
726 | nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.") | |
| 729 | pairsIndexList = property(getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.") |
|
727 | pairsIndexList = property(getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.") | |
| 730 | normFactor = property(getNormFactor, setValue, "I'm the 'getNormFactor' property.") |
|
728 | normFactor = property(getNormFactor, setValue, "I'm the 'getNormFactor' property.") | |
| 731 | flag_cspc = property(getFlagCspc, setValue) |
|
729 | flag_cspc = property(getFlagCspc, setValue) | |
| 732 | flag_dc = property(getFlagDc, setValue) |
|
730 | flag_dc = property(getFlagDc, setValue) | |
| 733 | noise = property(getNoise, setValue, "I'm the 'nHeights' property.") |
|
731 | noise = property(getNoise, setValue, "I'm the 'nHeights' property.") | |
| 734 | timeInterval = property(getTimeInterval, setValue, "I'm the 'timeInterval' property") |
|
732 | timeInterval = property(getTimeInterval, setValue, "I'm the 'timeInterval' property") | |
| 735 |
|
733 | |||
| 736 | class SpectraHeis(Spectra): |
|
734 | class SpectraHeis(Spectra): | |
| 737 |
|
735 | |||
| 738 | data_spc = None |
|
736 | data_spc = None | |
| 739 |
|
737 | |||
| 740 | data_cspc = None |
|
738 | data_cspc = None | |
| 741 |
|
739 | |||
| 742 | data_dc = None |
|
740 | data_dc = None | |
| 743 |
|
741 | |||
| 744 | nFFTPoints = None |
|
742 | nFFTPoints = None | |
| 745 |
|
743 | |||
| 746 | # nPairs = None |
|
744 | # nPairs = None | |
| 747 |
|
745 | |||
| 748 | pairsList = None |
|
746 | pairsList = None | |
| 749 |
|
747 | |||
| 750 | nCohInt = None |
|
748 | nCohInt = None | |
| 751 |
|
749 | |||
| 752 | nIncohInt = None |
|
750 | nIncohInt = None | |
| 753 |
|
751 | |||
| 754 | def __init__(self): |
|
752 | def __init__(self): | |
| 755 |
|
753 | |||
| 756 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
754 | self.radarControllerHeaderObj = RadarControllerHeader() | |
| 757 |
|
755 | |||
| 758 | self.systemHeaderObj = SystemHeader() |
|
756 | self.systemHeaderObj = SystemHeader() | |
| 759 |
|
757 | |||
| 760 | self.type = "SpectraHeis" |
|
758 | self.type = "SpectraHeis" | |
| 761 |
|
759 | |||
| 762 | # self.dtype = None |
|
760 | # self.dtype = None | |
| 763 |
|
761 | |||
| 764 | # self.nChannels = 0 |
|
762 | # self.nChannels = 0 | |
| 765 |
|
763 | |||
| 766 | # self.nHeights = 0 |
|
764 | # self.nHeights = 0 | |
| 767 |
|
765 | |||
| 768 | self.nProfiles = None |
|
766 | self.nProfiles = None | |
| 769 |
|
767 | |||
| 770 | self.heightList = None |
|
768 | self.heightList = None | |
| 771 |
|
769 | |||
| 772 | self.channelList = None |
|
770 | self.channelList = None | |
| 773 |
|
771 | |||
| 774 | # self.channelIndexList = None |
|
772 | # self.channelIndexList = None | |
| 775 |
|
773 | |||
| 776 | self.flagNoData = True |
|
774 | self.flagNoData = True | |
| 777 |
|
775 | |||
| 778 | self.flagDiscontinuousBlock = False |
|
776 | self.flagDiscontinuousBlock = False | |
| 779 |
|
777 | |||
| 780 | # self.nPairs = 0 |
|
778 | # self.nPairs = 0 | |
| 781 |
|
779 | |||
| 782 | self.utctime = None |
|
780 | self.utctime = None | |
| 783 |
|
781 | |||
| 784 | self.blocksize = None |
|
782 | self.blocksize = None | |
| 785 |
|
783 | |||
| 786 | self.profileIndex = 0 |
|
784 | self.profileIndex = 0 | |
| 787 |
|
785 | |||
| 788 | self.nCohInt = 1 |
|
786 | self.nCohInt = 1 | |
| 789 |
|
787 | |||
| 790 | self.nIncohInt = 1 |
|
788 | self.nIncohInt = 1 | |
| 791 |
|
789 | |||
| 792 | def getNormFactor(self): |
|
790 | def getNormFactor(self): | |
| 793 | pwcode = 1 |
|
791 | pwcode = 1 | |
| 794 | if self.flagDecodeData: |
|
792 | if self.flagDecodeData: | |
| 795 | pwcode = numpy.sum(self.code[0]**2) |
|
793 | pwcode = numpy.sum(self.code[0]**2) | |
| 796 |
|
794 | |||
| 797 | normFactor = self.nIncohInt*self.nCohInt*pwcode |
|
795 | normFactor = self.nIncohInt*self.nCohInt*pwcode | |
| 798 |
|
796 | |||
| 799 | return normFactor |
|
797 | return normFactor | |
| 800 |
|
798 | |||
| 801 | def getTimeInterval(self): |
|
799 | def getTimeInterval(self): | |
| 802 |
|
800 | |||
| 803 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
801 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt | |
| 804 |
|
802 | |||
| 805 | return timeInterval |
|
803 | return timeInterval | |
| 806 |
|
804 | |||
| 807 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") |
|
805 | normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.") | |
| 808 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
806 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") | |
| 809 |
|
807 | |||
| 810 | class Fits(JROData): |
|
808 | class Fits(JROData): | |
| 811 |
|
809 | |||
| 812 | heightList = None |
|
810 | heightList = None | |
| 813 |
|
811 | |||
| 814 | channelList = None |
|
812 | channelList = None | |
| 815 |
|
813 | |||
| 816 | flagNoData = True |
|
814 | flagNoData = True | |
| 817 |
|
815 | |||
| 818 | flagDiscontinuousBlock = False |
|
816 | flagDiscontinuousBlock = False | |
| 819 |
|
817 | |||
| 820 | useLocalTime = False |
|
818 | useLocalTime = False | |
| 821 |
|
819 | |||
| 822 | utctime = None |
|
820 | utctime = None | |
| 823 |
|
821 | |||
| 824 | timeZone = None |
|
822 | timeZone = None | |
| 825 |
|
823 | |||
| 826 | # ippSeconds = None |
|
824 | # ippSeconds = None | |
| 827 |
|
825 | |||
| 828 | # timeInterval = None |
|
826 | # timeInterval = None | |
| 829 |
|
827 | |||
| 830 | nCohInt = None |
|
828 | nCohInt = None | |
| 831 |
|
829 | |||
| 832 | nIncohInt = None |
|
830 | nIncohInt = None | |
| 833 |
|
831 | |||
| 834 | noise = None |
|
832 | noise = None | |
| 835 |
|
833 | |||
| 836 | windowOfFilter = 1 |
|
834 | windowOfFilter = 1 | |
| 837 |
|
835 | |||
| 838 | #Speed of ligth |
|
836 | #Speed of ligth | |
| 839 | C = 3e8 |
|
837 | C = 3e8 | |
| 840 |
|
838 | |||
| 841 | frequency = 49.92e6 |
|
839 | frequency = 49.92e6 | |
| 842 |
|
840 | |||
| 843 | realtime = False |
|
841 | realtime = False | |
| 844 |
|
842 | |||
| 845 |
|
843 | |||
| 846 | def __init__(self): |
|
844 | def __init__(self): | |
| 847 |
|
845 | |||
| 848 | self.type = "Fits" |
|
846 | self.type = "Fits" | |
| 849 |
|
847 | |||
| 850 | self.nProfiles = None |
|
848 | self.nProfiles = None | |
| 851 |
|
849 | |||
| 852 | self.heightList = None |
|
850 | self.heightList = None | |
| 853 |
|
851 | |||
| 854 | self.channelList = None |
|
852 | self.channelList = None | |
| 855 |
|
853 | |||
| 856 | # self.channelIndexList = None |
|
854 | # self.channelIndexList = None | |
| 857 |
|
855 | |||
| 858 | self.flagNoData = True |
|
856 | self.flagNoData = True | |
| 859 |
|
857 | |||
| 860 | self.utctime = None |
|
858 | self.utctime = None | |
| 861 |
|
859 | |||
| 862 | self.nCohInt = 1 |
|
860 | self.nCohInt = 1 | |
| 863 |
|
861 | |||
| 864 | self.nIncohInt = 1 |
|
862 | self.nIncohInt = 1 | |
| 865 |
|
863 | |||
| 866 | self.useLocalTime = True |
|
864 | self.useLocalTime = True | |
| 867 |
|
865 | |||
| 868 | self.profileIndex = 0 |
|
866 | self.profileIndex = 0 | |
| 869 |
|
867 | |||
| 870 | # self.utctime = None |
|
868 | # self.utctime = None | |
| 871 | # self.timeZone = None |
|
869 | # self.timeZone = None | |
| 872 | # self.ltctime = None |
|
870 | # self.ltctime = None | |
| 873 | # self.timeInterval = None |
|
871 | # self.timeInterval = None | |
| 874 | # self.header = None |
|
872 | # self.header = None | |
| 875 | # self.data_header = None |
|
873 | # self.data_header = None | |
| 876 | # self.data = None |
|
874 | # self.data = None | |
| 877 | # self.datatime = None |
|
875 | # self.datatime = None | |
| 878 | # self.flagNoData = False |
|
876 | # self.flagNoData = False | |
| 879 | # self.expName = '' |
|
877 | # self.expName = '' | |
| 880 | # self.nChannels = None |
|
878 | # self.nChannels = None | |
| 881 | # self.nSamples = None |
|
879 | # self.nSamples = None | |
| 882 | # self.dataBlocksPerFile = None |
|
880 | # self.dataBlocksPerFile = None | |
| 883 | # self.comments = '' |
|
881 | # self.comments = '' | |
| 884 | # |
|
882 | # | |
| 885 |
|
883 | |||
| 886 |
|
884 | |||
| 887 | def getltctime(self): |
|
885 | def getltctime(self): | |
| 888 |
|
886 | |||
| 889 | if self.useLocalTime: |
|
887 | if self.useLocalTime: | |
| 890 | return self.utctime - self.timeZone*60 |
|
888 | return self.utctime - self.timeZone*60 | |
| 891 |
|
889 | |||
| 892 | return self.utctime |
|
890 | return self.utctime | |
| 893 |
|
891 | |||
| 894 | def getDatatime(self): |
|
892 | def getDatatime(self): | |
| 895 |
|
893 | |||
| 896 | datatime = datetime.datetime.utcfromtimestamp(self.ltctime) |
|
894 | datatime = datetime.datetime.utcfromtimestamp(self.ltctime) | |
| 897 | return datatime |
|
895 | return datatime | |
| 898 |
|
896 | |||
| 899 | def getTimeRange(self): |
|
897 | def getTimeRange(self): | |
| 900 |
|
898 | |||
| 901 | datatime = [] |
|
899 | datatime = [] | |
| 902 |
|
900 | |||
| 903 | datatime.append(self.ltctime) |
|
901 | datatime.append(self.ltctime) | |
| 904 | datatime.append(self.ltctime + self.timeInterval) |
|
902 | datatime.append(self.ltctime + self.timeInterval) | |
| 905 |
|
903 | |||
| 906 | datatime = numpy.array(datatime) |
|
904 | datatime = numpy.array(datatime) | |
| 907 |
|
905 | |||
| 908 | return datatime |
|
906 | return datatime | |
| 909 |
|
907 | |||
| 910 | def getHeiRange(self): |
|
908 | def getHeiRange(self): | |
| 911 |
|
909 | |||
| 912 | heis = self.heightList |
|
910 | heis = self.heightList | |
| 913 |
|
911 | |||
| 914 | return heis |
|
912 | return heis | |
| 915 |
|
913 | |||
| 916 | def getNHeights(self): |
|
914 | def getNHeights(self): | |
| 917 |
|
915 | |||
| 918 | return len(self.heightList) |
|
916 | return len(self.heightList) | |
| 919 |
|
917 | |||
| 920 | def getNChannels(self): |
|
918 | def getNChannels(self): | |
| 921 |
|
919 | |||
| 922 | return len(self.channelList) |
|
920 | return len(self.channelList) | |
| 923 |
|
921 | |||
| 924 | def getChannelIndexList(self): |
|
922 | def getChannelIndexList(self): | |
| 925 |
|
923 | |||
| 926 | return range(self.nChannels) |
|
924 | return range(self.nChannels) | |
| 927 |
|
925 | |||
| 928 | def getNoise(self, type = 1): |
|
926 | def getNoise(self, type = 1): | |
| 929 |
|
927 | |||
| 930 | #noise = numpy.zeros(self.nChannels) |
|
928 | #noise = numpy.zeros(self.nChannels) | |
| 931 |
|
929 | |||
| 932 | if type == 1: |
|
930 | if type == 1: | |
| 933 | noise = self.getNoisebyHildebrand() |
|
931 | noise = self.getNoisebyHildebrand() | |
| 934 |
|
932 | |||
| 935 | if type == 2: |
|
933 | if type == 2: | |
| 936 | noise = self.getNoisebySort() |
|
934 | noise = self.getNoisebySort() | |
| 937 |
|
935 | |||
| 938 | if type == 3: |
|
936 | if type == 3: | |
| 939 | noise = self.getNoisebyWindow() |
|
937 | noise = self.getNoisebyWindow() | |
| 940 |
|
938 | |||
| 941 | return noise |
|
939 | return noise | |
| 942 |
|
940 | |||
| 943 | def getTimeInterval(self): |
|
941 | def getTimeInterval(self): | |
| 944 |
|
942 | |||
| 945 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt |
|
943 | timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt | |
| 946 |
|
944 | |||
| 947 | return timeInterval |
|
945 | return timeInterval | |
| 948 |
|
946 | |||
| 949 | datatime = property(getDatatime, "I'm the 'datatime' property") |
|
947 | datatime = property(getDatatime, "I'm the 'datatime' property") | |
| 950 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") |
|
948 | nHeights = property(getNHeights, "I'm the 'nHeights' property.") | |
| 951 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") |
|
949 | nChannels = property(getNChannels, "I'm the 'nChannel' property.") | |
| 952 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") |
|
950 | channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.") | |
| 953 | noise = property(getNoise, "I'm the 'nHeights' property.") |
|
951 | noise = property(getNoise, "I'm the 'nHeights' property.") | |
| 954 |
|
952 | |||
| 955 | ltctime = property(getltctime, "I'm the 'ltctime' property") |
|
953 | ltctime = property(getltctime, "I'm the 'ltctime' property") | |
| 956 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
954 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") | |
| 957 |
|
955 | |||
| 958 |
|
956 | |||
| 959 | class Correlation(JROData): |
|
957 | class Correlation(JROData): | |
| 960 |
|
958 | |||
| 961 | noise = None |
|
959 | noise = None | |
| 962 |
|
960 | |||
| 963 | SNR = None |
|
961 | SNR = None | |
| 964 |
|
962 | |||
| 965 | #-------------------------------------------------- |
|
963 | #-------------------------------------------------- | |
| 966 |
|
964 | |||
| 967 | mode = None |
|
965 | mode = None | |
| 968 |
|
966 | |||
| 969 | split = False |
|
967 | split = False | |
| 970 |
|
968 | |||
| 971 | data_cf = None |
|
969 | data_cf = None | |
| 972 |
|
970 | |||
| 973 | lags = None |
|
971 | lags = None | |
| 974 |
|
972 | |||
| 975 | lagRange = None |
|
973 | lagRange = None | |
| 976 |
|
974 | |||
| 977 | pairsList = None |
|
975 | pairsList = None | |
| 978 |
|
976 | |||
| 979 | normFactor = None |
|
977 | normFactor = None | |
| 980 |
|
978 | |||
| 981 | #-------------------------------------------------- |
|
979 | #-------------------------------------------------- | |
| 982 |
|
980 | |||
| 983 | # calculateVelocity = None |
|
981 | # calculateVelocity = None | |
| 984 |
|
982 | |||
| 985 | nLags = None |
|
983 | nLags = None | |
| 986 |
|
984 | |||
| 987 | nPairs = None |
|
985 | nPairs = None | |
| 988 |
|
986 | |||
| 989 | nAvg = None |
|
987 | nAvg = None | |
| 990 |
|
988 | |||
| 991 |
|
989 | |||
| 992 | def __init__(self): |
|
990 | def __init__(self): | |
| 993 | ''' |
|
991 | ''' | |
| 994 | Constructor |
|
992 | Constructor | |
| 995 | ''' |
|
993 | ''' | |
| 996 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
994 | self.radarControllerHeaderObj = RadarControllerHeader() | |
| 997 |
|
995 | |||
| 998 | self.systemHeaderObj = SystemHeader() |
|
996 | self.systemHeaderObj = SystemHeader() | |
| 999 |
|
997 | |||
| 1000 | self.type = "Correlation" |
|
998 | self.type = "Correlation" | |
| 1001 |
|
999 | |||
| 1002 | self.data = None |
|
1000 | self.data = None | |
| 1003 |
|
1001 | |||
| 1004 | self.dtype = None |
|
1002 | self.dtype = None | |
| 1005 |
|
1003 | |||
| 1006 | self.nProfiles = None |
|
1004 | self.nProfiles = None | |
| 1007 |
|
1005 | |||
| 1008 | self.heightList = None |
|
1006 | self.heightList = None | |
| 1009 |
|
1007 | |||
| 1010 | self.channelList = None |
|
1008 | self.channelList = None | |
| 1011 |
|
1009 | |||
| 1012 | self.flagNoData = True |
|
1010 | self.flagNoData = True | |
| 1013 |
|
1011 | |||
| 1014 | self.flagDiscontinuousBlock = False |
|
1012 | self.flagDiscontinuousBlock = False | |
| 1015 |
|
1013 | |||
| 1016 | self.utctime = None |
|
1014 | self.utctime = None | |
| 1017 |
|
1015 | |||
| 1018 | self.timeZone = None |
|
1016 | self.timeZone = None | |
| 1019 |
|
1017 | |||
| 1020 | self.dstFlag = None |
|
1018 | self.dstFlag = None | |
| 1021 |
|
1019 | |||
| 1022 | self.errorCount = None |
|
1020 | self.errorCount = None | |
| 1023 |
|
1021 | |||
| 1024 | self.blocksize = None |
|
1022 | self.blocksize = None | |
| 1025 |
|
1023 | |||
| 1026 | self.flagDecodeData = False #asumo q la data no esta decodificada |
|
1024 | self.flagDecodeData = False #asumo q la data no esta decodificada | |
| 1027 |
|
1025 | |||
| 1028 | self.flagDeflipData = False #asumo q la data no esta sin flip |
|
1026 | self.flagDeflipData = False #asumo q la data no esta sin flip | |
| 1029 |
|
1027 | |||
| 1030 | self.pairsList = None |
|
1028 | self.pairsList = None | |
| 1031 |
|
1029 | |||
| 1032 | self.nPoints = None |
|
1030 | self.nPoints = None | |
| 1033 |
|
1031 | |||
| 1034 | def getPairsList(self): |
|
1032 | def getPairsList(self): | |
| 1035 |
|
1033 | |||
| 1036 | return self.pairsList |
|
1034 | return self.pairsList | |
| 1037 |
|
1035 | |||
| 1038 | def getNoise(self, mode = 2): |
|
1036 | def getNoise(self, mode = 2): | |
| 1039 |
|
1037 | |||
| 1040 | indR = numpy.where(self.lagR == 0)[0][0] |
|
1038 | indR = numpy.where(self.lagR == 0)[0][0] | |
| 1041 | indT = numpy.where(self.lagT == 0)[0][0] |
|
1039 | indT = numpy.where(self.lagT == 0)[0][0] | |
| 1042 |
|
1040 | |||
| 1043 | jspectra0 = self.data_corr[:,:,indR,:] |
|
1041 | jspectra0 = self.data_corr[:,:,indR,:] | |
| 1044 | jspectra = copy.copy(jspectra0) |
|
1042 | jspectra = copy.copy(jspectra0) | |
| 1045 |
|
1043 | |||
| 1046 | num_chan = jspectra.shape[0] |
|
1044 | num_chan = jspectra.shape[0] | |
| 1047 | num_hei = jspectra.shape[2] |
|
1045 | num_hei = jspectra.shape[2] | |
| 1048 |
|
1046 | |||
| 1049 | freq_dc = jspectra.shape[1]/2 |
|
1047 | freq_dc = jspectra.shape[1]/2 | |
| 1050 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
1048 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |
| 1051 |
|
1049 | |||
| 1052 | if ind_vel[0]<0: |
|
1050 | if ind_vel[0]<0: | |
| 1053 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
1051 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |
| 1054 |
|
1052 | |||
| 1055 | if mode == 1: |
|
1053 | if mode == 1: | |
| 1056 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
1054 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
| 1057 |
|
1055 | |||
| 1058 | if mode == 2: |
|
1056 | if mode == 2: | |
| 1059 |
|
1057 | |||
| 1060 | vel = numpy.array([-2,-1,1,2]) |
|
1058 | vel = numpy.array([-2,-1,1,2]) | |
| 1061 | xx = numpy.zeros([4,4]) |
|
1059 | xx = numpy.zeros([4,4]) | |
| 1062 |
|
1060 | |||
| 1063 | for fil in range(4): |
|
1061 | for fil in range(4): | |
| 1064 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
1062 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |
| 1065 |
|
1063 | |||
| 1066 | xx_inv = numpy.linalg.inv(xx) |
|
1064 | xx_inv = numpy.linalg.inv(xx) | |
| 1067 | xx_aux = xx_inv[0,:] |
|
1065 | xx_aux = xx_inv[0,:] | |
| 1068 |
|
1066 | |||
| 1069 | for ich in range(num_chan): |
|
1067 | for ich in range(num_chan): | |
| 1070 | yy = jspectra[ich,ind_vel,:] |
|
1068 | yy = jspectra[ich,ind_vel,:] | |
| 1071 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
1069 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 1072 |
|
1070 | |||
| 1073 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
1071 | junkid = jspectra[ich,freq_dc,:]<=0 | |
| 1074 | cjunkid = sum(junkid) |
|
1072 | cjunkid = sum(junkid) | |
| 1075 |
|
1073 | |||
| 1076 | if cjunkid.any(): |
|
1074 | if cjunkid.any(): | |
| 1077 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
1075 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |
| 1078 |
|
1076 | |||
| 1079 | noise = jspectra0[:,freq_dc,:] - jspectra[:,freq_dc,:] |
|
1077 | noise = jspectra0[:,freq_dc,:] - jspectra[:,freq_dc,:] | |
| 1080 |
|
1078 | |||
| 1081 | return noise |
|
1079 | return noise | |
| 1082 |
|
1080 | |||
| 1083 | def getTimeInterval(self): |
|
1081 | def getTimeInterval(self): | |
| 1084 |
|
1082 | |||
| 1085 | timeInterval = self.ippSeconds * self.nCohInt * self.nProfiles |
|
1083 | timeInterval = self.ippSeconds * self.nCohInt * self.nProfiles | |
| 1086 |
|
1084 | |||
| 1087 | return timeInterval |
|
1085 | return timeInterval | |
| 1088 |
|
1086 | |||
| 1089 | def splitFunctions(self): |
|
1087 | def splitFunctions(self): | |
| 1090 |
|
1088 | |||
| 1091 | pairsList = self.pairsList |
|
1089 | pairsList = self.pairsList | |
| 1092 | ccf_pairs = [] |
|
1090 | ccf_pairs = [] | |
| 1093 | acf_pairs = [] |
|
1091 | acf_pairs = [] | |
| 1094 | ccf_ind = [] |
|
1092 | ccf_ind = [] | |
| 1095 | acf_ind = [] |
|
1093 | acf_ind = [] | |
| 1096 | for l in range(len(pairsList)): |
|
1094 | for l in range(len(pairsList)): | |
| 1097 | chan0 = pairsList[l][0] |
|
1095 | chan0 = pairsList[l][0] | |
| 1098 | chan1 = pairsList[l][1] |
|
1096 | chan1 = pairsList[l][1] | |
| 1099 |
|
1097 | |||
| 1100 | #Obteniendo pares de Autocorrelacion |
|
1098 | #Obteniendo pares de Autocorrelacion | |
| 1101 | if chan0 == chan1: |
|
1099 | if chan0 == chan1: | |
| 1102 | acf_pairs.append(chan0) |
|
1100 | acf_pairs.append(chan0) | |
| 1103 | acf_ind.append(l) |
|
1101 | acf_ind.append(l) | |
| 1104 | else: |
|
1102 | else: | |
| 1105 | ccf_pairs.append(pairsList[l]) |
|
1103 | ccf_pairs.append(pairsList[l]) | |
| 1106 | ccf_ind.append(l) |
|
1104 | ccf_ind.append(l) | |
| 1107 |
|
1105 | |||
| 1108 | data_acf = self.data_cf[acf_ind] |
|
1106 | data_acf = self.data_cf[acf_ind] | |
| 1109 | data_ccf = self.data_cf[ccf_ind] |
|
1107 | data_ccf = self.data_cf[ccf_ind] | |
| 1110 |
|
1108 | |||
| 1111 | return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf |
|
1109 | return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf | |
| 1112 |
|
1110 | |||
| 1113 | def getNormFactor(self): |
|
1111 | def getNormFactor(self): | |
| 1114 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions() |
|
1112 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions() | |
| 1115 | acf_pairs = numpy.array(acf_pairs) |
|
1113 | acf_pairs = numpy.array(acf_pairs) | |
| 1116 | normFactor = numpy.zeros((self.nPairs,self.nHeights)) |
|
1114 | normFactor = numpy.zeros((self.nPairs,self.nHeights)) | |
| 1117 |
|
1115 | |||
| 1118 | for p in range(self.nPairs): |
|
1116 | for p in range(self.nPairs): | |
| 1119 | pair = self.pairsList[p] |
|
1117 | pair = self.pairsList[p] | |
| 1120 |
|
1118 | |||
| 1121 | ch0 = pair[0] |
|
1119 | ch0 = pair[0] | |
| 1122 | ch1 = pair[1] |
|
1120 | ch1 = pair[1] | |
| 1123 |
|
1121 | |||
| 1124 | ch0_max = numpy.max(data_acf[acf_pairs==ch0,:,:], axis=1) |
|
1122 | ch0_max = numpy.max(data_acf[acf_pairs==ch0,:,:], axis=1) | |
| 1125 | ch1_max = numpy.max(data_acf[acf_pairs==ch1,:,:], axis=1) |
|
1123 | ch1_max = numpy.max(data_acf[acf_pairs==ch1,:,:], axis=1) | |
| 1126 | normFactor[p,:] = numpy.sqrt(ch0_max*ch1_max) |
|
1124 | normFactor[p,:] = numpy.sqrt(ch0_max*ch1_max) | |
| 1127 |
|
1125 | |||
| 1128 | return normFactor |
|
1126 | return normFactor | |
| 1129 |
|
1127 | |||
| 1130 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") |
|
1128 | timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property") | |
| 1131 | normFactor = property(getNormFactor, "I'm the 'normFactor property'") |
|
1129 | normFactor = property(getNormFactor, "I'm the 'normFactor property'") | |
| 1132 |
|
1130 | |||
| 1133 | class Parameters(Spectra): |
|
1131 | class Parameters(Spectra): | |
| 1134 |
|
1132 | |||
| 1135 | experimentInfo = None #Information about the experiment |
|
1133 | experimentInfo = None #Information about the experiment | |
| 1136 |
|
1134 | |||
| 1137 | #Information from previous data |
|
1135 | #Information from previous data | |
| 1138 |
|
1136 | |||
| 1139 | inputUnit = None #Type of data to be processed |
|
1137 | inputUnit = None #Type of data to be processed | |
| 1140 |
|
1138 | |||
| 1141 | operation = None #Type of operation to parametrize |
|
1139 | operation = None #Type of operation to parametrize | |
| 1142 |
|
1140 | |||
| 1143 | #normFactor = None #Normalization Factor |
|
1141 | #normFactor = None #Normalization Factor | |
| 1144 |
|
1142 | |||
| 1145 | groupList = None #List of Pairs, Groups, etc |
|
1143 | groupList = None #List of Pairs, Groups, etc | |
| 1146 |
|
1144 | |||
| 1147 | #Parameters |
|
1145 | #Parameters | |
| 1148 |
|
1146 | |||
| 1149 | data_param = None #Parameters obtained |
|
1147 | data_param = None #Parameters obtained | |
| 1150 |
|
1148 | |||
| 1151 | data_pre = None #Data Pre Parametrization |
|
1149 | data_pre = None #Data Pre Parametrization | |
| 1152 |
|
1150 | |||
| 1153 | data_SNR = None #Signal to Noise Ratio |
|
1151 | data_SNR = None #Signal to Noise Ratio | |
| 1154 |
|
1152 | |||
| 1155 | # heightRange = None #Heights |
|
1153 | # heightRange = None #Heights | |
| 1156 |
|
1154 | |||
| 1157 | abscissaList = None #Abscissa, can be velocities, lags or time |
|
1155 | abscissaList = None #Abscissa, can be velocities, lags or time | |
| 1158 |
|
1156 | |||
| 1159 | # noise = None #Noise Potency |
|
1157 | # noise = None #Noise Potency | |
| 1160 |
|
1158 | |||
| 1161 | utctimeInit = None #Initial UTC time |
|
1159 | utctimeInit = None #Initial UTC time | |
| 1162 |
|
1160 | |||
| 1163 | paramInterval = None #Time interval to calculate Parameters in seconds |
|
1161 | paramInterval = None #Time interval to calculate Parameters in seconds | |
| 1164 |
|
1162 | |||
| 1165 | useLocalTime = True |
|
1163 | useLocalTime = True | |
| 1166 |
|
1164 | |||
| 1167 | #Fitting |
|
1165 | #Fitting | |
| 1168 |
|
1166 | |||
| 1169 | data_error = None #Error of the estimation |
|
1167 | data_error = None #Error of the estimation | |
| 1170 |
|
1168 | |||
| 1171 | constants = None |
|
1169 | constants = None | |
| 1172 |
|
1170 | |||
| 1173 | library = None |
|
1171 | library = None | |
| 1174 |
|
1172 | |||
| 1175 | #Output signal |
|
1173 | #Output signal | |
| 1176 |
|
1174 | |||
| 1177 | outputInterval = None #Time interval to calculate output signal in seconds |
|
1175 | outputInterval = None #Time interval to calculate output signal in seconds | |
| 1178 |
|
1176 | |||
| 1179 | data_output = None #Out signal |
|
1177 | data_output = None #Out signal | |
| 1180 |
|
1178 | |||
| 1181 | nAvg = None |
|
1179 | nAvg = None | |
| 1182 |
|
1180 | |||
| 1183 | noise_estimation = None |
|
1181 | noise_estimation = None | |
| 1184 |
|
1182 | |||
| 1185 | GauSPC = None #Fit gaussian SPC |
|
1183 | GauSPC = None #Fit gaussian SPC | |
| 1186 |
|
1184 | |||
| 1187 |
|
1185 | |||
| 1188 | def __init__(self): |
|
1186 | def __init__(self): | |
| 1189 | ''' |
|
1187 | ''' | |
| 1190 | Constructor |
|
1188 | Constructor | |
| 1191 | ''' |
|
1189 | ''' | |
| 1192 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
1190 | self.radarControllerHeaderObj = RadarControllerHeader() | |
| 1193 |
|
1191 | |||
| 1194 | self.systemHeaderObj = SystemHeader() |
|
1192 | self.systemHeaderObj = SystemHeader() | |
| 1195 |
|
1193 | |||
| 1196 | self.type = "Parameters" |
|
1194 | self.type = "Parameters" | |
| 1197 |
|
1195 | |||
| 1198 | def getTimeRange1(self, interval): |
|
1196 | def getTimeRange1(self, interval): | |
| 1199 |
|
1197 | |||
| 1200 | datatime = [] |
|
1198 | datatime = [] | |
| 1201 |
|
1199 | |||
| 1202 | if self.useLocalTime: |
|
1200 | if self.useLocalTime: | |
| 1203 | time1 = self.utctimeInit - self.timeZone*60 |
|
1201 | time1 = self.utctimeInit - self.timeZone*60 | |
| 1204 | else: |
|
1202 | else: | |
| 1205 | time1 = self.utctimeInit |
|
1203 | time1 = self.utctimeInit | |
| 1206 |
|
1204 | |||
| 1207 | datatime.append(time1) |
|
1205 | datatime.append(time1) | |
| 1208 | datatime.append(time1 + interval) |
|
1206 | datatime.append(time1 + interval) | |
| 1209 | datatime = numpy.array(datatime) |
|
1207 | datatime = numpy.array(datatime) | |
| 1210 |
|
1208 | |||
| 1211 | return datatime |
|
1209 | return datatime | |
| 1212 |
|
1210 | |||
| 1213 | def getTimeInterval(self): |
|
1211 | def getTimeInterval(self): | |
| 1214 |
|
1212 | |||
| 1215 | if hasattr(self, 'timeInterval1'): |
|
1213 | if hasattr(self, 'timeInterval1'): | |
| 1216 | return self.timeInterval1 |
|
1214 | return self.timeInterval1 | |
| 1217 | else: |
|
1215 | else: | |
| 1218 | return self.paramInterval |
|
1216 | return self.paramInterval | |
| 1219 |
|
1217 | |||
| 1220 | def setValue(self, value): |
|
1218 | def setValue(self, value): | |
| 1221 |
|
1219 | |||
| 1222 | print "This property should not be initialized" |
|
1220 | print "This property should not be initialized" | |
| 1223 |
|
1221 | |||
| 1224 | return |
|
1222 | return | |
| 1225 |
|
1223 | |||
| 1226 | def getNoise(self): |
|
1224 | def getNoise(self): | |
| 1227 |
|
1225 | |||
| 1228 | return self.spc_noise |
|
1226 | return self.spc_noise | |
| 1229 |
|
1227 | |||
| 1230 | timeInterval = property(getTimeInterval) |
|
1228 | timeInterval = property(getTimeInterval) | |
| 1231 | noise = property(getNoise, setValue, "I'm the 'Noise' property.") |
|
1229 | noise = property(getNoise, setValue, "I'm the 'Noise' property.") | |
| @@ -1,2160 +1,2160 | |||||
| 1 | import os |
|
1 | import os | |
| 2 | import datetime |
|
2 | import datetime | |
| 3 | import numpy |
|
3 | import numpy | |
| 4 | import inspect |
|
4 | import inspect | |
| 5 | from figure import Figure, isRealtime, isTimeInHourRange |
|
5 | from figure import Figure, isRealtime, isTimeInHourRange | |
| 6 | from plotting_codes import * |
|
6 | from plotting_codes import * | |
| 7 |
|
7 | |||
| 8 |
|
8 | |||
| 9 |
class |
|
9 | class SpcParamPlot(Figure): | |
| 10 |
|
10 | |||
| 11 | isConfig = None |
|
11 | isConfig = None | |
| 12 | __nsubplots = None |
|
12 | __nsubplots = None | |
| 13 |
|
13 | |||
| 14 | WIDTHPROF = None |
|
14 | WIDTHPROF = None | |
| 15 | HEIGHTPROF = None |
|
15 | HEIGHTPROF = None | |
| 16 |
PREFIX = ' |
|
16 | PREFIX = 'SpcParam' | |
| 17 |
|
17 | |||
| 18 | def __init__(self, **kwargs): |
|
18 | def __init__(self, **kwargs): | |
| 19 | Figure.__init__(self, **kwargs) |
|
19 | Figure.__init__(self, **kwargs) | |
| 20 | self.isConfig = False |
|
20 | self.isConfig = False | |
| 21 | self.__nsubplots = 1 |
|
21 | self.__nsubplots = 1 | |
| 22 |
|
22 | |||
| 23 | self.WIDTH = 250 |
|
23 | self.WIDTH = 250 | |
| 24 | self.HEIGHT = 250 |
|
24 | self.HEIGHT = 250 | |
| 25 | self.WIDTHPROF = 120 |
|
25 | self.WIDTHPROF = 120 | |
| 26 | self.HEIGHTPROF = 0 |
|
26 | self.HEIGHTPROF = 0 | |
| 27 | self.counter_imagwr = 0 |
|
27 | self.counter_imagwr = 0 | |
| 28 |
|
28 | |||
| 29 | self.PLOT_CODE = SPEC_CODE |
|
29 | self.PLOT_CODE = SPEC_CODE | |
| 30 |
|
30 | |||
| 31 | self.FTP_WEI = None |
|
31 | self.FTP_WEI = None | |
| 32 | self.EXP_CODE = None |
|
32 | self.EXP_CODE = None | |
| 33 | self.SUB_EXP_CODE = None |
|
33 | self.SUB_EXP_CODE = None | |
| 34 | self.PLOT_POS = None |
|
34 | self.PLOT_POS = None | |
| 35 |
|
35 | |||
| 36 | self.__xfilter_ena = False |
|
36 | self.__xfilter_ena = False | |
| 37 | self.__yfilter_ena = False |
|
37 | self.__yfilter_ena = False | |
| 38 |
|
38 | |||
| 39 | def getSubplots(self): |
|
39 | def getSubplots(self): | |
| 40 |
|
40 | |||
| 41 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
41 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 42 | nrow = int(self.nplots*1./ncol + 0.9) |
|
42 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 43 |
|
43 | |||
| 44 | return nrow, ncol |
|
44 | return nrow, ncol | |
| 45 |
|
45 | |||
| 46 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
46 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 47 |
|
47 | |||
| 48 | self.__showprofile = showprofile |
|
48 | self.__showprofile = showprofile | |
| 49 | self.nplots = nplots |
|
49 | self.nplots = nplots | |
| 50 |
|
50 | |||
| 51 | ncolspan = 1 |
|
51 | ncolspan = 1 | |
| 52 | colspan = 1 |
|
52 | colspan = 1 | |
| 53 | if showprofile: |
|
53 | if showprofile: | |
| 54 | ncolspan = 3 |
|
54 | ncolspan = 3 | |
| 55 | colspan = 2 |
|
55 | colspan = 2 | |
| 56 | self.__nsubplots = 2 |
|
56 | self.__nsubplots = 2 | |
| 57 |
|
57 | |||
| 58 | self.createFigure(id = id, |
|
58 | self.createFigure(id = id, | |
| 59 | wintitle = wintitle, |
|
59 | wintitle = wintitle, | |
| 60 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
60 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 61 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
61 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 62 | show=show) |
|
62 | show=show) | |
| 63 |
|
63 | |||
| 64 | nrow, ncol = self.getSubplots() |
|
64 | nrow, ncol = self.getSubplots() | |
| 65 |
|
65 | |||
| 66 | counter = 0 |
|
66 | counter = 0 | |
| 67 | for y in range(nrow): |
|
67 | for y in range(nrow): | |
| 68 | for x in range(ncol): |
|
68 | for x in range(ncol): | |
| 69 |
|
69 | |||
| 70 | if counter >= self.nplots: |
|
70 | if counter >= self.nplots: | |
| 71 | break |
|
71 | break | |
| 72 |
|
72 | |||
| 73 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
73 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 74 |
|
74 | |||
| 75 | if showprofile: |
|
75 | if showprofile: | |
| 76 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
76 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 77 |
|
77 | |||
| 78 | counter += 1 |
|
78 | counter += 1 | |
| 79 |
|
79 | |||
| 80 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
80 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 81 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
81 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 82 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
82 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 83 | server=None, folder=None, username=None, password=None, |
|
83 | server=None, folder=None, username=None, password=None, | |
| 84 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
84 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
| 85 |
xaxis="frequency", colormap='jet', normFactor=None , |
|
85 | xaxis="frequency", colormap='jet', normFactor=None , Selector = 0): | |
| 86 |
|
86 | |||
| 87 | """ |
|
87 | """ | |
| 88 |
|
88 | |||
| 89 | Input: |
|
89 | Input: | |
| 90 | dataOut : |
|
90 | dataOut : | |
| 91 | id : |
|
91 | id : | |
| 92 | wintitle : |
|
92 | wintitle : | |
| 93 | channelList : |
|
93 | channelList : | |
| 94 | showProfile : |
|
94 | showProfile : | |
| 95 | xmin : None, |
|
95 | xmin : None, | |
| 96 | xmax : None, |
|
96 | xmax : None, | |
| 97 | ymin : None, |
|
97 | ymin : None, | |
| 98 | ymax : None, |
|
98 | ymax : None, | |
| 99 | zmin : None, |
|
99 | zmin : None, | |
| 100 | zmax : None |
|
100 | zmax : None | |
| 101 | """ |
|
101 | """ | |
| 102 | if realtime: |
|
102 | if realtime: | |
| 103 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
103 | if not(isRealtime(utcdatatime = dataOut.utctime)): | |
| 104 | print 'Skipping this plot function' |
|
104 | print 'Skipping this plot function' | |
| 105 | return |
|
105 | return | |
| 106 |
|
106 | |||
| 107 | if channelList == None: |
|
107 | if channelList == None: | |
| 108 | channelIndexList = dataOut.channelIndexList |
|
108 | channelIndexList = dataOut.channelIndexList | |
| 109 | else: |
|
109 | else: | |
| 110 | channelIndexList = [] |
|
110 | channelIndexList = [] | |
| 111 | for channel in channelList: |
|
111 | for channel in channelList: | |
| 112 | if channel not in dataOut.channelList: |
|
112 | if channel not in dataOut.channelList: | |
| 113 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel |
|
113 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel | |
| 114 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
114 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 115 |
|
115 | |||
| 116 | # if normFactor is None: |
|
116 | # if normFactor is None: | |
| 117 | # factor = dataOut.normFactor |
|
117 | # factor = dataOut.normFactor | |
| 118 | # else: |
|
118 | # else: | |
| 119 | # factor = normFactor |
|
119 | # factor = normFactor | |
| 120 | if xaxis == "frequency": |
|
120 | if xaxis == "frequency": | |
| 121 | x = dataOut.spc_range[0] |
|
121 | x = dataOut.spcparam_range[0] | |
| 122 | xlabel = "Frequency (kHz)" |
|
122 | xlabel = "Frequency (kHz)" | |
| 123 |
|
123 | |||
| 124 | elif xaxis == "time": |
|
124 | elif xaxis == "time": | |
| 125 | x = dataOut.spc_range[1] |
|
125 | x = dataOut.spcparam_range[1] | |
| 126 | xlabel = "Time (ms)" |
|
126 | xlabel = "Time (ms)" | |
| 127 |
|
127 | |||
| 128 | else: |
|
128 | else: | |
| 129 | x = dataOut.spc_range[2] |
|
129 | x = dataOut.spcparam_range[2] | |
| 130 | xlabel = "Velocity (m/s)" |
|
130 | xlabel = "Velocity (m/s)" | |
| 131 |
|
131 | |||
| 132 | ylabel = "Range (Km)" |
|
132 | ylabel = "Range (Km)" | |
| 133 |
|
133 | |||
| 134 | y = dataOut.getHeiRange() |
|
134 | y = dataOut.getHeiRange() | |
| 135 |
|
135 | |||
| 136 |
z = dataOut. |
|
136 | z = dataOut.SPCparam[Selector] #GauSelector] #dataOut.data_spc/factor | |
| 137 | print 'GausSPC', z[0,32,10:40] |
|
137 | #print 'GausSPC', z[0,32,10:40] | |
| 138 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
138 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 139 | zdB = 10*numpy.log10(z) |
|
139 | zdB = 10*numpy.log10(z) | |
| 140 |
|
140 | |||
| 141 | avg = numpy.average(z, axis=1) |
|
141 | avg = numpy.average(z, axis=1) | |
| 142 | avgdB = 10*numpy.log10(avg) |
|
142 | avgdB = 10*numpy.log10(avg) | |
| 143 |
|
143 | |||
| 144 | noise = dataOut.spc_noise |
|
144 | noise = dataOut.spc_noise | |
| 145 | noisedB = 10*numpy.log10(noise) |
|
145 | noisedB = 10*numpy.log10(noise) | |
| 146 |
|
146 | |||
| 147 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
147 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 148 | title = wintitle + " Spectra" |
|
148 | title = wintitle + " Spectra" | |
| 149 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
149 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 150 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
150 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 151 |
|
151 | |||
| 152 | if not self.isConfig: |
|
152 | if not self.isConfig: | |
| 153 |
|
153 | |||
| 154 | nplots = len(channelIndexList) |
|
154 | nplots = len(channelIndexList) | |
| 155 |
|
155 | |||
| 156 | self.setup(id=id, |
|
156 | self.setup(id=id, | |
| 157 | nplots=nplots, |
|
157 | nplots=nplots, | |
| 158 | wintitle=wintitle, |
|
158 | wintitle=wintitle, | |
| 159 | showprofile=showprofile, |
|
159 | showprofile=showprofile, | |
| 160 | show=show) |
|
160 | show=show) | |
| 161 |
|
161 | |||
| 162 | if xmin == None: xmin = numpy.nanmin(x) |
|
162 | if xmin == None: xmin = numpy.nanmin(x) | |
| 163 | if xmax == None: xmax = numpy.nanmax(x) |
|
163 | if xmax == None: xmax = numpy.nanmax(x) | |
| 164 | if ymin == None: ymin = numpy.nanmin(y) |
|
164 | if ymin == None: ymin = numpy.nanmin(y) | |
| 165 | if ymax == None: ymax = numpy.nanmax(y) |
|
165 | if ymax == None: ymax = numpy.nanmax(y) | |
| 166 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
166 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 167 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
167 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 168 |
|
168 | |||
| 169 | self.FTP_WEI = ftp_wei |
|
169 | self.FTP_WEI = ftp_wei | |
| 170 | self.EXP_CODE = exp_code |
|
170 | self.EXP_CODE = exp_code | |
| 171 | self.SUB_EXP_CODE = sub_exp_code |
|
171 | self.SUB_EXP_CODE = sub_exp_code | |
| 172 | self.PLOT_POS = plot_pos |
|
172 | self.PLOT_POS = plot_pos | |
| 173 |
|
173 | |||
| 174 | self.isConfig = True |
|
174 | self.isConfig = True | |
| 175 |
|
175 | |||
| 176 | self.setWinTitle(title) |
|
176 | self.setWinTitle(title) | |
| 177 |
|
177 | |||
| 178 | for i in range(self.nplots): |
|
178 | for i in range(self.nplots): | |
| 179 | index = channelIndexList[i] |
|
179 | index = channelIndexList[i] | |
| 180 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
180 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 181 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) |
|
181 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) | |
| 182 | if len(dataOut.beam.codeList) != 0: |
|
182 | if len(dataOut.beam.codeList) != 0: | |
| 183 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) |
|
183 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) | |
| 184 |
|
184 | |||
| 185 | axes = self.axesList[i*self.__nsubplots] |
|
185 | axes = self.axesList[i*self.__nsubplots] | |
| 186 | axes.pcolor(x, y, zdB[index,:,:], |
|
186 | axes.pcolor(x, y, zdB[index,:,:], | |
| 187 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
187 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 188 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, |
|
188 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, | |
| 189 | ticksize=9, cblabel='') |
|
189 | ticksize=9, cblabel='') | |
| 190 |
|
190 | |||
| 191 | if self.__showprofile: |
|
191 | if self.__showprofile: | |
| 192 | axes = self.axesList[i*self.__nsubplots +1] |
|
192 | axes = self.axesList[i*self.__nsubplots +1] | |
| 193 | axes.pline(avgdB[index,:], y, |
|
193 | axes.pline(avgdB[index,:], y, | |
| 194 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
194 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 195 | xlabel='dB', ylabel='', title='', |
|
195 | xlabel='dB', ylabel='', title='', | |
| 196 | ytick_visible=False, |
|
196 | ytick_visible=False, | |
| 197 | grid='x') |
|
197 | grid='x') | |
| 198 |
|
198 | |||
| 199 | noiseline = numpy.repeat(noisedB[index], len(y)) |
|
199 | noiseline = numpy.repeat(noisedB[index], len(y)) | |
| 200 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
200 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) | |
| 201 |
|
201 | |||
| 202 | self.draw() |
|
202 | self.draw() | |
| 203 |
|
203 | |||
| 204 | if figfile == None: |
|
204 | if figfile == None: | |
| 205 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
205 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 206 | name = str_datetime |
|
206 | name = str_datetime | |
| 207 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
207 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 208 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
208 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 209 | figfile = self.getFilename(name) |
|
209 | figfile = self.getFilename(name) | |
| 210 |
|
210 | |||
| 211 | self.save(figpath=figpath, |
|
211 | self.save(figpath=figpath, | |
| 212 | figfile=figfile, |
|
212 | figfile=figfile, | |
| 213 | save=save, |
|
213 | save=save, | |
| 214 | ftp=ftp, |
|
214 | ftp=ftp, | |
| 215 | wr_period=wr_period, |
|
215 | wr_period=wr_period, | |
| 216 | thisDatetime=thisDatetime) |
|
216 | thisDatetime=thisDatetime) | |
| 217 |
|
217 | |||
| 218 |
|
218 | |||
| 219 |
|
219 | |||
| 220 | class MomentsPlot(Figure): |
|
220 | class MomentsPlot(Figure): | |
| 221 |
|
221 | |||
| 222 | isConfig = None |
|
222 | isConfig = None | |
| 223 | __nsubplots = None |
|
223 | __nsubplots = None | |
| 224 |
|
224 | |||
| 225 | WIDTHPROF = None |
|
225 | WIDTHPROF = None | |
| 226 | HEIGHTPROF = None |
|
226 | HEIGHTPROF = None | |
| 227 | PREFIX = 'prm' |
|
227 | PREFIX = 'prm' | |
| 228 |
|
228 | |||
| 229 | def __init__(self, **kwargs): |
|
229 | def __init__(self, **kwargs): | |
| 230 | Figure.__init__(self, **kwargs) |
|
230 | Figure.__init__(self, **kwargs) | |
| 231 | self.isConfig = False |
|
231 | self.isConfig = False | |
| 232 | self.__nsubplots = 1 |
|
232 | self.__nsubplots = 1 | |
| 233 |
|
233 | |||
| 234 | self.WIDTH = 280 |
|
234 | self.WIDTH = 280 | |
| 235 | self.HEIGHT = 250 |
|
235 | self.HEIGHT = 250 | |
| 236 | self.WIDTHPROF = 120 |
|
236 | self.WIDTHPROF = 120 | |
| 237 | self.HEIGHTPROF = 0 |
|
237 | self.HEIGHTPROF = 0 | |
| 238 | self.counter_imagwr = 0 |
|
238 | self.counter_imagwr = 0 | |
| 239 |
|
239 | |||
| 240 | self.PLOT_CODE = MOMENTS_CODE |
|
240 | self.PLOT_CODE = MOMENTS_CODE | |
| 241 |
|
241 | |||
| 242 | self.FTP_WEI = None |
|
242 | self.FTP_WEI = None | |
| 243 | self.EXP_CODE = None |
|
243 | self.EXP_CODE = None | |
| 244 | self.SUB_EXP_CODE = None |
|
244 | self.SUB_EXP_CODE = None | |
| 245 | self.PLOT_POS = None |
|
245 | self.PLOT_POS = None | |
| 246 |
|
246 | |||
| 247 | def getSubplots(self): |
|
247 | def getSubplots(self): | |
| 248 |
|
248 | |||
| 249 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
249 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 250 | nrow = int(self.nplots*1./ncol + 0.9) |
|
250 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 251 |
|
251 | |||
| 252 | return nrow, ncol |
|
252 | return nrow, ncol | |
| 253 |
|
253 | |||
| 254 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
254 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 255 |
|
255 | |||
| 256 | self.__showprofile = showprofile |
|
256 | self.__showprofile = showprofile | |
| 257 | self.nplots = nplots |
|
257 | self.nplots = nplots | |
| 258 |
|
258 | |||
| 259 | ncolspan = 1 |
|
259 | ncolspan = 1 | |
| 260 | colspan = 1 |
|
260 | colspan = 1 | |
| 261 | if showprofile: |
|
261 | if showprofile: | |
| 262 | ncolspan = 3 |
|
262 | ncolspan = 3 | |
| 263 | colspan = 2 |
|
263 | colspan = 2 | |
| 264 | self.__nsubplots = 2 |
|
264 | self.__nsubplots = 2 | |
| 265 |
|
265 | |||
| 266 | self.createFigure(id = id, |
|
266 | self.createFigure(id = id, | |
| 267 | wintitle = wintitle, |
|
267 | wintitle = wintitle, | |
| 268 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
268 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 269 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
269 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 270 | show=show) |
|
270 | show=show) | |
| 271 |
|
271 | |||
| 272 | nrow, ncol = self.getSubplots() |
|
272 | nrow, ncol = self.getSubplots() | |
| 273 |
|
273 | |||
| 274 | counter = 0 |
|
274 | counter = 0 | |
| 275 | for y in range(nrow): |
|
275 | for y in range(nrow): | |
| 276 | for x in range(ncol): |
|
276 | for x in range(ncol): | |
| 277 |
|
277 | |||
| 278 | if counter >= self.nplots: |
|
278 | if counter >= self.nplots: | |
| 279 | break |
|
279 | break | |
| 280 |
|
280 | |||
| 281 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
281 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 282 |
|
282 | |||
| 283 | if showprofile: |
|
283 | if showprofile: | |
| 284 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
284 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 285 |
|
285 | |||
| 286 | counter += 1 |
|
286 | counter += 1 | |
| 287 |
|
287 | |||
| 288 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
288 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 289 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
289 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 290 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
290 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 291 | server=None, folder=None, username=None, password=None, |
|
291 | server=None, folder=None, username=None, password=None, | |
| 292 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): |
|
292 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): | |
| 293 |
|
293 | |||
| 294 | """ |
|
294 | """ | |
| 295 |
|
295 | |||
| 296 | Input: |
|
296 | Input: | |
| 297 | dataOut : |
|
297 | dataOut : | |
| 298 | id : |
|
298 | id : | |
| 299 | wintitle : |
|
299 | wintitle : | |
| 300 | channelList : |
|
300 | channelList : | |
| 301 | showProfile : |
|
301 | showProfile : | |
| 302 | xmin : None, |
|
302 | xmin : None, | |
| 303 | xmax : None, |
|
303 | xmax : None, | |
| 304 | ymin : None, |
|
304 | ymin : None, | |
| 305 | ymax : None, |
|
305 | ymax : None, | |
| 306 | zmin : None, |
|
306 | zmin : None, | |
| 307 | zmax : None |
|
307 | zmax : None | |
| 308 | """ |
|
308 | """ | |
| 309 |
|
309 | |||
| 310 | if dataOut.flagNoData: |
|
310 | if dataOut.flagNoData: | |
| 311 | return None |
|
311 | return None | |
| 312 |
|
312 | |||
| 313 | if realtime: |
|
313 | if realtime: | |
| 314 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
314 | if not(isRealtime(utcdatatime = dataOut.utctime)): | |
| 315 | print 'Skipping this plot function' |
|
315 | print 'Skipping this plot function' | |
| 316 | return |
|
316 | return | |
| 317 |
|
317 | |||
| 318 | if channelList == None: |
|
318 | if channelList == None: | |
| 319 | channelIndexList = dataOut.channelIndexList |
|
319 | channelIndexList = dataOut.channelIndexList | |
| 320 | else: |
|
320 | else: | |
| 321 | channelIndexList = [] |
|
321 | channelIndexList = [] | |
| 322 | for channel in channelList: |
|
322 | for channel in channelList: | |
| 323 | if channel not in dataOut.channelList: |
|
323 | if channel not in dataOut.channelList: | |
| 324 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
324 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 325 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
325 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 326 |
|
326 | |||
| 327 | factor = dataOut.normFactor |
|
327 | factor = dataOut.normFactor | |
| 328 | x = dataOut.abscissaList |
|
328 | x = dataOut.abscissaList | |
| 329 | y = dataOut.heightList |
|
329 | y = dataOut.heightList | |
| 330 |
|
330 | |||
| 331 | z = dataOut.data_pre[channelIndexList,:,:]/factor |
|
331 | z = dataOut.data_pre[channelIndexList,:,:]/factor | |
| 332 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
332 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 333 | avg = numpy.average(z, axis=1) |
|
333 | avg = numpy.average(z, axis=1) | |
| 334 | noise = dataOut.noise/factor |
|
334 | noise = dataOut.noise/factor | |
| 335 |
|
335 | |||
| 336 | zdB = 10*numpy.log10(z) |
|
336 | zdB = 10*numpy.log10(z) | |
| 337 | avgdB = 10*numpy.log10(avg) |
|
337 | avgdB = 10*numpy.log10(avg) | |
| 338 | noisedB = 10*numpy.log10(noise) |
|
338 | noisedB = 10*numpy.log10(noise) | |
| 339 |
|
339 | |||
| 340 | #thisDatetime = dataOut.datatime |
|
340 | #thisDatetime = dataOut.datatime | |
| 341 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
341 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 342 | title = wintitle + " Parameters" |
|
342 | title = wintitle + " Parameters" | |
| 343 | xlabel = "Velocity (m/s)" |
|
343 | xlabel = "Velocity (m/s)" | |
| 344 | ylabel = "Range (Km)" |
|
344 | ylabel = "Range (Km)" | |
| 345 |
|
345 | |||
| 346 | update_figfile = False |
|
346 | update_figfile = False | |
| 347 |
|
347 | |||
| 348 | if not self.isConfig: |
|
348 | if not self.isConfig: | |
| 349 |
|
349 | |||
| 350 | nplots = len(channelIndexList) |
|
350 | nplots = len(channelIndexList) | |
| 351 |
|
351 | |||
| 352 | self.setup(id=id, |
|
352 | self.setup(id=id, | |
| 353 | nplots=nplots, |
|
353 | nplots=nplots, | |
| 354 | wintitle=wintitle, |
|
354 | wintitle=wintitle, | |
| 355 | showprofile=showprofile, |
|
355 | showprofile=showprofile, | |
| 356 | show=show) |
|
356 | show=show) | |
| 357 |
|
357 | |||
| 358 | if xmin == None: xmin = numpy.nanmin(x) |
|
358 | if xmin == None: xmin = numpy.nanmin(x) | |
| 359 | if xmax == None: xmax = numpy.nanmax(x) |
|
359 | if xmax == None: xmax = numpy.nanmax(x) | |
| 360 | if ymin == None: ymin = numpy.nanmin(y) |
|
360 | if ymin == None: ymin = numpy.nanmin(y) | |
| 361 | if ymax == None: ymax = numpy.nanmax(y) |
|
361 | if ymax == None: ymax = numpy.nanmax(y) | |
| 362 | if zmin == None: zmin = numpy.nanmin(avgdB)*0.9 |
|
362 | if zmin == None: zmin = numpy.nanmin(avgdB)*0.9 | |
| 363 | if zmax == None: zmax = numpy.nanmax(avgdB)*0.9 |
|
363 | if zmax == None: zmax = numpy.nanmax(avgdB)*0.9 | |
| 364 |
|
364 | |||
| 365 | self.FTP_WEI = ftp_wei |
|
365 | self.FTP_WEI = ftp_wei | |
| 366 | self.EXP_CODE = exp_code |
|
366 | self.EXP_CODE = exp_code | |
| 367 | self.SUB_EXP_CODE = sub_exp_code |
|
367 | self.SUB_EXP_CODE = sub_exp_code | |
| 368 | self.PLOT_POS = plot_pos |
|
368 | self.PLOT_POS = plot_pos | |
| 369 |
|
369 | |||
| 370 | self.isConfig = True |
|
370 | self.isConfig = True | |
| 371 | update_figfile = True |
|
371 | update_figfile = True | |
| 372 |
|
372 | |||
| 373 | self.setWinTitle(title) |
|
373 | self.setWinTitle(title) | |
| 374 |
|
374 | |||
| 375 | for i in range(self.nplots): |
|
375 | for i in range(self.nplots): | |
| 376 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
376 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 377 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime) |
|
377 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime) | |
| 378 | axes = self.axesList[i*self.__nsubplots] |
|
378 | axes = self.axesList[i*self.__nsubplots] | |
| 379 | axes.pcolor(x, y, zdB[i,:,:], |
|
379 | axes.pcolor(x, y, zdB[i,:,:], | |
| 380 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
380 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 381 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
381 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 382 | ticksize=9, cblabel='') |
|
382 | ticksize=9, cblabel='') | |
| 383 | #Mean Line |
|
383 | #Mean Line | |
| 384 | mean = dataOut.data_param[i, 1, :] |
|
384 | mean = dataOut.data_param[i, 1, :] | |
| 385 | axes.addpline(mean, y, idline=0, color="black", linestyle="solid", lw=1) |
|
385 | axes.addpline(mean, y, idline=0, color="black", linestyle="solid", lw=1) | |
| 386 |
|
386 | |||
| 387 | if self.__showprofile: |
|
387 | if self.__showprofile: | |
| 388 | axes = self.axesList[i*self.__nsubplots +1] |
|
388 | axes = self.axesList[i*self.__nsubplots +1] | |
| 389 | axes.pline(avgdB[i], y, |
|
389 | axes.pline(avgdB[i], y, | |
| 390 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
390 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 391 | xlabel='dB', ylabel='', title='', |
|
391 | xlabel='dB', ylabel='', title='', | |
| 392 | ytick_visible=False, |
|
392 | ytick_visible=False, | |
| 393 | grid='x') |
|
393 | grid='x') | |
| 394 |
|
394 | |||
| 395 | noiseline = numpy.repeat(noisedB[i], len(y)) |
|
395 | noiseline = numpy.repeat(noisedB[i], len(y)) | |
| 396 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
396 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) | |
| 397 |
|
397 | |||
| 398 | self.draw() |
|
398 | self.draw() | |
| 399 |
|
399 | |||
| 400 | self.save(figpath=figpath, |
|
400 | self.save(figpath=figpath, | |
| 401 | figfile=figfile, |
|
401 | figfile=figfile, | |
| 402 | save=save, |
|
402 | save=save, | |
| 403 | ftp=ftp, |
|
403 | ftp=ftp, | |
| 404 | wr_period=wr_period, |
|
404 | wr_period=wr_period, | |
| 405 | thisDatetime=thisDatetime) |
|
405 | thisDatetime=thisDatetime) | |
| 406 |
|
406 | |||
| 407 |
|
407 | |||
| 408 |
|
408 | |||
| 409 | class SkyMapPlot(Figure): |
|
409 | class SkyMapPlot(Figure): | |
| 410 |
|
410 | |||
| 411 | __isConfig = None |
|
411 | __isConfig = None | |
| 412 | __nsubplots = None |
|
412 | __nsubplots = None | |
| 413 |
|
413 | |||
| 414 | WIDTHPROF = None |
|
414 | WIDTHPROF = None | |
| 415 | HEIGHTPROF = None |
|
415 | HEIGHTPROF = None | |
| 416 | PREFIX = 'mmap' |
|
416 | PREFIX = 'mmap' | |
| 417 |
|
417 | |||
| 418 | def __init__(self, **kwargs): |
|
418 | def __init__(self, **kwargs): | |
| 419 | Figure.__init__(self, **kwargs) |
|
419 | Figure.__init__(self, **kwargs) | |
| 420 | self.isConfig = False |
|
420 | self.isConfig = False | |
| 421 | self.__nsubplots = 1 |
|
421 | self.__nsubplots = 1 | |
| 422 |
|
422 | |||
| 423 | # self.WIDTH = 280 |
|
423 | # self.WIDTH = 280 | |
| 424 | # self.HEIGHT = 250 |
|
424 | # self.HEIGHT = 250 | |
| 425 | self.WIDTH = 600 |
|
425 | self.WIDTH = 600 | |
| 426 | self.HEIGHT = 600 |
|
426 | self.HEIGHT = 600 | |
| 427 | self.WIDTHPROF = 120 |
|
427 | self.WIDTHPROF = 120 | |
| 428 | self.HEIGHTPROF = 0 |
|
428 | self.HEIGHTPROF = 0 | |
| 429 | self.counter_imagwr = 0 |
|
429 | self.counter_imagwr = 0 | |
| 430 |
|
430 | |||
| 431 | self.PLOT_CODE = MSKYMAP_CODE |
|
431 | self.PLOT_CODE = MSKYMAP_CODE | |
| 432 |
|
432 | |||
| 433 | self.FTP_WEI = None |
|
433 | self.FTP_WEI = None | |
| 434 | self.EXP_CODE = None |
|
434 | self.EXP_CODE = None | |
| 435 | self.SUB_EXP_CODE = None |
|
435 | self.SUB_EXP_CODE = None | |
| 436 | self.PLOT_POS = None |
|
436 | self.PLOT_POS = None | |
| 437 |
|
437 | |||
| 438 | def getSubplots(self): |
|
438 | def getSubplots(self): | |
| 439 |
|
439 | |||
| 440 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
440 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 441 | nrow = int(self.nplots*1./ncol + 0.9) |
|
441 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 442 |
|
442 | |||
| 443 | return nrow, ncol |
|
443 | return nrow, ncol | |
| 444 |
|
444 | |||
| 445 | def setup(self, id, nplots, wintitle, showprofile=False, show=True): |
|
445 | def setup(self, id, nplots, wintitle, showprofile=False, show=True): | |
| 446 |
|
446 | |||
| 447 | self.__showprofile = showprofile |
|
447 | self.__showprofile = showprofile | |
| 448 | self.nplots = nplots |
|
448 | self.nplots = nplots | |
| 449 |
|
449 | |||
| 450 | ncolspan = 1 |
|
450 | ncolspan = 1 | |
| 451 | colspan = 1 |
|
451 | colspan = 1 | |
| 452 |
|
452 | |||
| 453 | self.createFigure(id = id, |
|
453 | self.createFigure(id = id, | |
| 454 | wintitle = wintitle, |
|
454 | wintitle = wintitle, | |
| 455 | widthplot = self.WIDTH, #+ self.WIDTHPROF, |
|
455 | widthplot = self.WIDTH, #+ self.WIDTHPROF, | |
| 456 | heightplot = self.HEIGHT,# + self.HEIGHTPROF, |
|
456 | heightplot = self.HEIGHT,# + self.HEIGHTPROF, | |
| 457 | show=show) |
|
457 | show=show) | |
| 458 |
|
458 | |||
| 459 | nrow, ncol = 1,1 |
|
459 | nrow, ncol = 1,1 | |
| 460 | counter = 0 |
|
460 | counter = 0 | |
| 461 | x = 0 |
|
461 | x = 0 | |
| 462 | y = 0 |
|
462 | y = 0 | |
| 463 | self.addAxes(1, 1, 0, 0, 1, 1, True) |
|
463 | self.addAxes(1, 1, 0, 0, 1, 1, True) | |
| 464 |
|
464 | |||
| 465 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False, |
|
465 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False, | |
| 466 | tmin=0, tmax=24, timerange=None, |
|
466 | tmin=0, tmax=24, timerange=None, | |
| 467 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
467 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 468 | server=None, folder=None, username=None, password=None, |
|
468 | server=None, folder=None, username=None, password=None, | |
| 469 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): |
|
469 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): | |
| 470 |
|
470 | |||
| 471 | """ |
|
471 | """ | |
| 472 |
|
472 | |||
| 473 | Input: |
|
473 | Input: | |
| 474 | dataOut : |
|
474 | dataOut : | |
| 475 | id : |
|
475 | id : | |
| 476 | wintitle : |
|
476 | wintitle : | |
| 477 | channelList : |
|
477 | channelList : | |
| 478 | showProfile : |
|
478 | showProfile : | |
| 479 | xmin : None, |
|
479 | xmin : None, | |
| 480 | xmax : None, |
|
480 | xmax : None, | |
| 481 | ymin : None, |
|
481 | ymin : None, | |
| 482 | ymax : None, |
|
482 | ymax : None, | |
| 483 | zmin : None, |
|
483 | zmin : None, | |
| 484 | zmax : None |
|
484 | zmax : None | |
| 485 | """ |
|
485 | """ | |
| 486 |
|
486 | |||
| 487 | arrayParameters = dataOut.data_param |
|
487 | arrayParameters = dataOut.data_param | |
| 488 | error = arrayParameters[:,-1] |
|
488 | error = arrayParameters[:,-1] | |
| 489 | indValid = numpy.where(error == 0)[0] |
|
489 | indValid = numpy.where(error == 0)[0] | |
| 490 | finalMeteor = arrayParameters[indValid,:] |
|
490 | finalMeteor = arrayParameters[indValid,:] | |
| 491 | finalAzimuth = finalMeteor[:,3] |
|
491 | finalAzimuth = finalMeteor[:,3] | |
| 492 | finalZenith = finalMeteor[:,4] |
|
492 | finalZenith = finalMeteor[:,4] | |
| 493 |
|
493 | |||
| 494 | x = finalAzimuth*numpy.pi/180 |
|
494 | x = finalAzimuth*numpy.pi/180 | |
| 495 | y = finalZenith |
|
495 | y = finalZenith | |
| 496 | x1 = [dataOut.ltctime, dataOut.ltctime] |
|
496 | x1 = [dataOut.ltctime, dataOut.ltctime] | |
| 497 |
|
497 | |||
| 498 | #thisDatetime = dataOut.datatime |
|
498 | #thisDatetime = dataOut.datatime | |
| 499 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) |
|
499 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) | |
| 500 | title = wintitle + " Parameters" |
|
500 | title = wintitle + " Parameters" | |
| 501 | xlabel = "Zonal Zenith Angle (deg) " |
|
501 | xlabel = "Zonal Zenith Angle (deg) " | |
| 502 | ylabel = "Meridional Zenith Angle (deg)" |
|
502 | ylabel = "Meridional Zenith Angle (deg)" | |
| 503 | update_figfile = False |
|
503 | update_figfile = False | |
| 504 |
|
504 | |||
| 505 | if not self.isConfig: |
|
505 | if not self.isConfig: | |
| 506 |
|
506 | |||
| 507 | nplots = 1 |
|
507 | nplots = 1 | |
| 508 |
|
508 | |||
| 509 | self.setup(id=id, |
|
509 | self.setup(id=id, | |
| 510 | nplots=nplots, |
|
510 | nplots=nplots, | |
| 511 | wintitle=wintitle, |
|
511 | wintitle=wintitle, | |
| 512 | showprofile=showprofile, |
|
512 | showprofile=showprofile, | |
| 513 | show=show) |
|
513 | show=show) | |
| 514 |
|
514 | |||
| 515 | if self.xmin is None and self.xmax is None: |
|
515 | if self.xmin is None and self.xmax is None: | |
| 516 | self.xmin, self.xmax = self.getTimeLim(x1, tmin, tmax, timerange) |
|
516 | self.xmin, self.xmax = self.getTimeLim(x1, tmin, tmax, timerange) | |
| 517 |
|
517 | |||
| 518 | if timerange != None: |
|
518 | if timerange != None: | |
| 519 | self.timerange = timerange |
|
519 | self.timerange = timerange | |
| 520 | else: |
|
520 | else: | |
| 521 | self.timerange = self.xmax - self.xmin |
|
521 | self.timerange = self.xmax - self.xmin | |
| 522 |
|
522 | |||
| 523 | self.FTP_WEI = ftp_wei |
|
523 | self.FTP_WEI = ftp_wei | |
| 524 | self.EXP_CODE = exp_code |
|
524 | self.EXP_CODE = exp_code | |
| 525 | self.SUB_EXP_CODE = sub_exp_code |
|
525 | self.SUB_EXP_CODE = sub_exp_code | |
| 526 | self.PLOT_POS = plot_pos |
|
526 | self.PLOT_POS = plot_pos | |
| 527 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
527 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 528 | self.firstdate = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
528 | self.firstdate = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 529 | self.isConfig = True |
|
529 | self.isConfig = True | |
| 530 | update_figfile = True |
|
530 | update_figfile = True | |
| 531 |
|
531 | |||
| 532 | self.setWinTitle(title) |
|
532 | self.setWinTitle(title) | |
| 533 |
|
533 | |||
| 534 | i = 0 |
|
534 | i = 0 | |
| 535 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
535 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 536 |
|
536 | |||
| 537 | axes = self.axesList[i*self.__nsubplots] |
|
537 | axes = self.axesList[i*self.__nsubplots] | |
| 538 | nevents = axes.x_buffer.shape[0] + x.shape[0] |
|
538 | nevents = axes.x_buffer.shape[0] + x.shape[0] | |
| 539 | title = "Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n" %(self.firstdate,str_datetime,nevents) |
|
539 | title = "Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n" %(self.firstdate,str_datetime,nevents) | |
| 540 | axes.polar(x, y, |
|
540 | axes.polar(x, y, | |
| 541 | title=title, xlabel=xlabel, ylabel=ylabel, |
|
541 | title=title, xlabel=xlabel, ylabel=ylabel, | |
| 542 | ticksize=9, cblabel='') |
|
542 | ticksize=9, cblabel='') | |
| 543 |
|
543 | |||
| 544 | self.draw() |
|
544 | self.draw() | |
| 545 |
|
545 | |||
| 546 | self.save(figpath=figpath, |
|
546 | self.save(figpath=figpath, | |
| 547 | figfile=figfile, |
|
547 | figfile=figfile, | |
| 548 | save=save, |
|
548 | save=save, | |
| 549 | ftp=ftp, |
|
549 | ftp=ftp, | |
| 550 | wr_period=wr_period, |
|
550 | wr_period=wr_period, | |
| 551 | thisDatetime=thisDatetime, |
|
551 | thisDatetime=thisDatetime, | |
| 552 | update_figfile=update_figfile) |
|
552 | update_figfile=update_figfile) | |
| 553 |
|
553 | |||
| 554 | if dataOut.ltctime >= self.xmax: |
|
554 | if dataOut.ltctime >= self.xmax: | |
| 555 | self.isConfigmagwr = wr_period |
|
555 | self.isConfigmagwr = wr_period | |
| 556 | self.isConfig = False |
|
556 | self.isConfig = False | |
| 557 | update_figfile = True |
|
557 | update_figfile = True | |
| 558 | axes.__firsttime = True |
|
558 | axes.__firsttime = True | |
| 559 | self.xmin += self.timerange |
|
559 | self.xmin += self.timerange | |
| 560 | self.xmax += self.timerange |
|
560 | self.xmax += self.timerange | |
| 561 |
|
561 | |||
| 562 |
|
562 | |||
| 563 |
|
563 | |||
| 564 |
|
564 | |||
| 565 | class WindProfilerPlot(Figure): |
|
565 | class WindProfilerPlot(Figure): | |
| 566 |
|
566 | |||
| 567 | __isConfig = None |
|
567 | __isConfig = None | |
| 568 | __nsubplots = None |
|
568 | __nsubplots = None | |
| 569 |
|
569 | |||
| 570 | WIDTHPROF = None |
|
570 | WIDTHPROF = None | |
| 571 | HEIGHTPROF = None |
|
571 | HEIGHTPROF = None | |
| 572 | PREFIX = 'wind' |
|
572 | PREFIX = 'wind' | |
| 573 |
|
573 | |||
| 574 | def __init__(self, **kwargs): |
|
574 | def __init__(self, **kwargs): | |
| 575 | Figure.__init__(self, **kwargs) |
|
575 | Figure.__init__(self, **kwargs) | |
| 576 | self.timerange = None |
|
576 | self.timerange = None | |
| 577 | self.isConfig = False |
|
577 | self.isConfig = False | |
| 578 | self.__nsubplots = 1 |
|
578 | self.__nsubplots = 1 | |
| 579 |
|
579 | |||
| 580 | self.WIDTH = 800 |
|
580 | self.WIDTH = 800 | |
| 581 | self.HEIGHT = 300 |
|
581 | self.HEIGHT = 300 | |
| 582 | self.WIDTHPROF = 120 |
|
582 | self.WIDTHPROF = 120 | |
| 583 | self.HEIGHTPROF = 0 |
|
583 | self.HEIGHTPROF = 0 | |
| 584 | self.counter_imagwr = 0 |
|
584 | self.counter_imagwr = 0 | |
| 585 |
|
585 | |||
| 586 | self.PLOT_CODE = WIND_CODE |
|
586 | self.PLOT_CODE = WIND_CODE | |
| 587 |
|
587 | |||
| 588 | self.FTP_WEI = None |
|
588 | self.FTP_WEI = None | |
| 589 | self.EXP_CODE = None |
|
589 | self.EXP_CODE = None | |
| 590 | self.SUB_EXP_CODE = None |
|
590 | self.SUB_EXP_CODE = None | |
| 591 | self.PLOT_POS = None |
|
591 | self.PLOT_POS = None | |
| 592 | self.tmin = None |
|
592 | self.tmin = None | |
| 593 | self.tmax = None |
|
593 | self.tmax = None | |
| 594 |
|
594 | |||
| 595 | self.xmin = None |
|
595 | self.xmin = None | |
| 596 | self.xmax = None |
|
596 | self.xmax = None | |
| 597 |
|
597 | |||
| 598 | self.figfile = None |
|
598 | self.figfile = None | |
| 599 |
|
599 | |||
| 600 | def getSubplots(self): |
|
600 | def getSubplots(self): | |
| 601 |
|
601 | |||
| 602 | ncol = 1 |
|
602 | ncol = 1 | |
| 603 | nrow = self.nplots |
|
603 | nrow = self.nplots | |
| 604 |
|
604 | |||
| 605 | return nrow, ncol |
|
605 | return nrow, ncol | |
| 606 |
|
606 | |||
| 607 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
607 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 608 |
|
608 | |||
| 609 | self.__showprofile = showprofile |
|
609 | self.__showprofile = showprofile | |
| 610 | self.nplots = nplots |
|
610 | self.nplots = nplots | |
| 611 |
|
611 | |||
| 612 | ncolspan = 1 |
|
612 | ncolspan = 1 | |
| 613 | colspan = 1 |
|
613 | colspan = 1 | |
| 614 |
|
614 | |||
| 615 | self.createFigure(id = id, |
|
615 | self.createFigure(id = id, | |
| 616 | wintitle = wintitle, |
|
616 | wintitle = wintitle, | |
| 617 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
617 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 618 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
618 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 619 | show=show) |
|
619 | show=show) | |
| 620 |
|
620 | |||
| 621 | nrow, ncol = self.getSubplots() |
|
621 | nrow, ncol = self.getSubplots() | |
| 622 |
|
622 | |||
| 623 | counter = 0 |
|
623 | counter = 0 | |
| 624 | for y in range(nrow): |
|
624 | for y in range(nrow): | |
| 625 | if counter >= self.nplots: |
|
625 | if counter >= self.nplots: | |
| 626 | break |
|
626 | break | |
| 627 |
|
627 | |||
| 628 | self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1) |
|
628 | self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1) | |
| 629 | counter += 1 |
|
629 | counter += 1 | |
| 630 |
|
630 | |||
| 631 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='False', |
|
631 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='False', | |
| 632 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
632 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 633 | zmax_ver = None, zmin_ver = None, SNRmin = None, SNRmax = None, |
|
633 | zmax_ver = None, zmin_ver = None, SNRmin = None, SNRmax = None, | |
| 634 | timerange=None, SNRthresh = None, |
|
634 | timerange=None, SNRthresh = None, | |
| 635 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
635 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 636 | server=None, folder=None, username=None, password=None, |
|
636 | server=None, folder=None, username=None, password=None, | |
| 637 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
637 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 638 | """ |
|
638 | """ | |
| 639 |
|
639 | |||
| 640 | Input: |
|
640 | Input: | |
| 641 | dataOut : |
|
641 | dataOut : | |
| 642 | id : |
|
642 | id : | |
| 643 | wintitle : |
|
643 | wintitle : | |
| 644 | channelList : |
|
644 | channelList : | |
| 645 | showProfile : |
|
645 | showProfile : | |
| 646 | xmin : None, |
|
646 | xmin : None, | |
| 647 | xmax : None, |
|
647 | xmax : None, | |
| 648 | ymin : None, |
|
648 | ymin : None, | |
| 649 | ymax : None, |
|
649 | ymax : None, | |
| 650 | zmin : None, |
|
650 | zmin : None, | |
| 651 | zmax : None |
|
651 | zmax : None | |
| 652 | """ |
|
652 | """ | |
| 653 |
|
653 | |||
| 654 | # if timerange is not None: |
|
654 | # if timerange is not None: | |
| 655 | # self.timerange = timerange |
|
655 | # self.timerange = timerange | |
| 656 | # |
|
656 | # | |
| 657 | # tmin = None |
|
657 | # tmin = None | |
| 658 | # tmax = None |
|
658 | # tmax = None | |
| 659 |
|
659 | |||
| 660 | x = dataOut.getTimeRange1(dataOut.paramInterval) |
|
660 | x = dataOut.getTimeRange1(dataOut.paramInterval) | |
| 661 | y = dataOut.heightList |
|
661 | y = dataOut.heightList | |
| 662 | z = dataOut.data_output.copy() |
|
662 | z = dataOut.data_output.copy() | |
| 663 | nplots = z.shape[0] #Number of wind dimensions estimated |
|
663 | nplots = z.shape[0] #Number of wind dimensions estimated | |
| 664 | nplotsw = nplots |
|
664 | nplotsw = nplots | |
| 665 |
|
665 | |||
| 666 |
|
666 | |||
| 667 | #If there is a SNR function defined |
|
667 | #If there is a SNR function defined | |
| 668 | if dataOut.data_SNR is not None: |
|
668 | if dataOut.data_SNR is not None: | |
| 669 | nplots += 1 |
|
669 | nplots += 1 | |
| 670 | SNR = dataOut.data_SNR[0] |
|
670 | SNR = dataOut.data_SNR[0] | |
| 671 | SNRavg = SNR#numpy.average(SNR, axis=0) |
|
671 | SNRavg = SNR#numpy.average(SNR, axis=0) | |
| 672 |
|
672 | |||
| 673 | SNRdB = 10*numpy.log10(SNR) |
|
673 | SNRdB = 10*numpy.log10(SNR) | |
| 674 | SNRavgdB = 10*numpy.log10(SNRavg) |
|
674 | SNRavgdB = 10*numpy.log10(SNRavg) | |
| 675 |
|
675 | |||
| 676 | if SNRthresh == None: |
|
676 | if SNRthresh == None: | |
| 677 | SNRthresh = -5.0 |
|
677 | SNRthresh = -5.0 | |
| 678 | ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0] |
|
678 | ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0] | |
| 679 |
|
679 | |||
| 680 | for i in range(nplotsw): |
|
680 | for i in range(nplotsw): | |
| 681 | z[i,ind] = numpy.nan |
|
681 | z[i,ind] = numpy.nan | |
| 682 |
|
682 | |||
| 683 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) |
|
683 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) | |
| 684 | #thisDatetime = datetime.datetime.now() |
|
684 | #thisDatetime = datetime.datetime.now() | |
| 685 | title = wintitle + "Wind" |
|
685 | title = wintitle + "Wind" | |
| 686 | xlabel = "" |
|
686 | xlabel = "" | |
| 687 | ylabel = "Height (km)" |
|
687 | ylabel = "Height (km)" | |
| 688 | update_figfile = False |
|
688 | update_figfile = False | |
| 689 |
|
689 | |||
| 690 | if not self.isConfig: |
|
690 | if not self.isConfig: | |
| 691 |
|
691 | |||
| 692 | self.setup(id=id, |
|
692 | self.setup(id=id, | |
| 693 | nplots=nplots, |
|
693 | nplots=nplots, | |
| 694 | wintitle=wintitle, |
|
694 | wintitle=wintitle, | |
| 695 | showprofile=showprofile, |
|
695 | showprofile=showprofile, | |
| 696 | show=show) |
|
696 | show=show) | |
| 697 |
|
697 | |||
| 698 | if timerange is not None: |
|
698 | if timerange is not None: | |
| 699 | self.timerange = timerange |
|
699 | self.timerange = timerange | |
| 700 |
|
700 | |||
| 701 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
701 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 702 |
|
702 | |||
| 703 | if ymin == None: ymin = numpy.nanmin(y) |
|
703 | if ymin == None: ymin = numpy.nanmin(y) | |
| 704 | if ymax == None: ymax = numpy.nanmax(y) |
|
704 | if ymax == None: ymax = numpy.nanmax(y) | |
| 705 |
|
705 | |||
| 706 | if zmax == None: zmax = numpy.nanmax(abs(z[range(2),:])) |
|
706 | if zmax == None: zmax = numpy.nanmax(abs(z[range(2),:])) | |
| 707 | #if numpy.isnan(zmax): zmax = 50 |
|
707 | #if numpy.isnan(zmax): zmax = 50 | |
| 708 | if zmin == None: zmin = -zmax |
|
708 | if zmin == None: zmin = -zmax | |
| 709 |
|
709 | |||
| 710 | if nplotsw == 3: |
|
710 | if nplotsw == 3: | |
| 711 | if zmax_ver == None: zmax_ver = numpy.nanmax(abs(z[2,:])) |
|
711 | if zmax_ver == None: zmax_ver = numpy.nanmax(abs(z[2,:])) | |
| 712 | if zmin_ver == None: zmin_ver = -zmax_ver |
|
712 | if zmin_ver == None: zmin_ver = -zmax_ver | |
| 713 |
|
713 | |||
| 714 | if dataOut.data_SNR is not None: |
|
714 | if dataOut.data_SNR is not None: | |
| 715 | if SNRmin == None: SNRmin = numpy.nanmin(SNRavgdB) |
|
715 | if SNRmin == None: SNRmin = numpy.nanmin(SNRavgdB) | |
| 716 | if SNRmax == None: SNRmax = numpy.nanmax(SNRavgdB) |
|
716 | if SNRmax == None: SNRmax = numpy.nanmax(SNRavgdB) | |
| 717 |
|
717 | |||
| 718 |
|
718 | |||
| 719 | self.FTP_WEI = ftp_wei |
|
719 | self.FTP_WEI = ftp_wei | |
| 720 | self.EXP_CODE = exp_code |
|
720 | self.EXP_CODE = exp_code | |
| 721 | self.SUB_EXP_CODE = sub_exp_code |
|
721 | self.SUB_EXP_CODE = sub_exp_code | |
| 722 | self.PLOT_POS = plot_pos |
|
722 | self.PLOT_POS = plot_pos | |
| 723 |
|
723 | |||
| 724 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
724 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 725 | self.isConfig = True |
|
725 | self.isConfig = True | |
| 726 | self.figfile = figfile |
|
726 | self.figfile = figfile | |
| 727 | update_figfile = True |
|
727 | update_figfile = True | |
| 728 |
|
728 | |||
| 729 | self.setWinTitle(title) |
|
729 | self.setWinTitle(title) | |
| 730 |
|
730 | |||
| 731 | if ((self.xmax - x[1]) < (x[1]-x[0])): |
|
731 | if ((self.xmax - x[1]) < (x[1]-x[0])): | |
| 732 | x[1] = self.xmax |
|
732 | x[1] = self.xmax | |
| 733 |
|
733 | |||
| 734 | strWind = ['Zonal', 'Meridional', 'Vertical'] |
|
734 | strWind = ['Zonal', 'Meridional', 'Vertical'] | |
| 735 | strCb = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)'] |
|
735 | strCb = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)'] | |
| 736 | zmaxVector = [zmax, zmax, zmax_ver] |
|
736 | zmaxVector = [zmax, zmax, zmax_ver] | |
| 737 | zminVector = [zmin, zmin, zmin_ver] |
|
737 | zminVector = [zmin, zmin, zmin_ver] | |
| 738 | windFactor = [1,1,100] |
|
738 | windFactor = [1,1,100] | |
| 739 |
|
739 | |||
| 740 | for i in range(nplotsw): |
|
740 | for i in range(nplotsw): | |
| 741 |
|
741 | |||
| 742 | title = "%s Wind: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
742 | title = "%s Wind: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 743 | axes = self.axesList[i*self.__nsubplots] |
|
743 | axes = self.axesList[i*self.__nsubplots] | |
| 744 |
|
744 | |||
| 745 | z1 = z[i,:].reshape((1,-1))*windFactor[i] |
|
745 | z1 = z[i,:].reshape((1,-1))*windFactor[i] | |
| 746 |
|
746 | |||
| 747 | print 'x', x |
|
747 | print 'x', x | |
| 748 | print datetime.datetime.utcfromtimestamp(x[0]) |
|
748 | print datetime.datetime.utcfromtimestamp(x[0]) | |
| 749 | print datetime.datetime.utcfromtimestamp(x[1]) |
|
749 | print datetime.datetime.utcfromtimestamp(x[1]) | |
| 750 |
|
750 | |||
| 751 | #z1=numpy.ma.masked_where(z1==0.,z1) |
|
751 | #z1=numpy.ma.masked_where(z1==0.,z1) | |
| 752 |
|
752 | |||
| 753 | axes.pcolorbuffer(x, y, z1, |
|
753 | axes.pcolorbuffer(x, y, z1, | |
| 754 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i], |
|
754 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i], | |
| 755 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
755 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 756 | ticksize=9, cblabel=strCb[i], cbsize="1%", colormap="seismic" ) |
|
756 | ticksize=9, cblabel=strCb[i], cbsize="1%", colormap="seismic" ) | |
| 757 |
|
757 | |||
| 758 | if dataOut.data_SNR is not None: |
|
758 | if dataOut.data_SNR is not None: | |
| 759 | i += 1 |
|
759 | i += 1 | |
| 760 | title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
760 | title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 761 | axes = self.axesList[i*self.__nsubplots] |
|
761 | axes = self.axesList[i*self.__nsubplots] | |
| 762 | SNRavgdB = SNRavgdB.reshape((1,-1)) |
|
762 | SNRavgdB = SNRavgdB.reshape((1,-1)) | |
| 763 | axes.pcolorbuffer(x, y, SNRavgdB, |
|
763 | axes.pcolorbuffer(x, y, SNRavgdB, | |
| 764 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, |
|
764 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, | |
| 765 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
765 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 766 | ticksize=9, cblabel='', cbsize="1%", colormap="jet") |
|
766 | ticksize=9, cblabel='', cbsize="1%", colormap="jet") | |
| 767 |
|
767 | |||
| 768 | self.draw() |
|
768 | self.draw() | |
| 769 |
|
769 | |||
| 770 | self.save(figpath=figpath, |
|
770 | self.save(figpath=figpath, | |
| 771 | figfile=figfile, |
|
771 | figfile=figfile, | |
| 772 | save=save, |
|
772 | save=save, | |
| 773 | ftp=ftp, |
|
773 | ftp=ftp, | |
| 774 | wr_period=wr_period, |
|
774 | wr_period=wr_period, | |
| 775 | thisDatetime=thisDatetime, |
|
775 | thisDatetime=thisDatetime, | |
| 776 | update_figfile=update_figfile) |
|
776 | update_figfile=update_figfile) | |
| 777 |
|
777 | |||
| 778 | if dataOut.ltctime + dataOut.paramInterval >= self.xmax: |
|
778 | if dataOut.ltctime + dataOut.paramInterval >= self.xmax: | |
| 779 | self.counter_imagwr = wr_period |
|
779 | self.counter_imagwr = wr_period | |
| 780 | self.isConfig = False |
|
780 | self.isConfig = False | |
| 781 | update_figfile = True |
|
781 | update_figfile = True | |
| 782 |
|
782 | |||
| 783 |
|
783 | |||
| 784 | class ParametersPlot(Figure): |
|
784 | class ParametersPlot(Figure): | |
| 785 |
|
785 | |||
| 786 | __isConfig = None |
|
786 | __isConfig = None | |
| 787 | __nsubplots = None |
|
787 | __nsubplots = None | |
| 788 |
|
788 | |||
| 789 | WIDTHPROF = None |
|
789 | WIDTHPROF = None | |
| 790 | HEIGHTPROF = None |
|
790 | HEIGHTPROF = None | |
| 791 | PREFIX = 'param' |
|
791 | PREFIX = 'param' | |
| 792 |
|
792 | |||
| 793 | nplots = None |
|
793 | nplots = None | |
| 794 | nchan = None |
|
794 | nchan = None | |
| 795 |
|
795 | |||
| 796 | def __init__(self, **kwargs): |
|
796 | def __init__(self, **kwargs): | |
| 797 | Figure.__init__(self, **kwargs) |
|
797 | Figure.__init__(self, **kwargs) | |
| 798 | self.timerange = None |
|
798 | self.timerange = None | |
| 799 | self.isConfig = False |
|
799 | self.isConfig = False | |
| 800 | self.__nsubplots = 1 |
|
800 | self.__nsubplots = 1 | |
| 801 |
|
801 | |||
| 802 | self.WIDTH = 800 |
|
802 | self.WIDTH = 800 | |
| 803 | self.HEIGHT = 180 |
|
803 | self.HEIGHT = 180 | |
| 804 | self.WIDTHPROF = 120 |
|
804 | self.WIDTHPROF = 120 | |
| 805 | self.HEIGHTPROF = 0 |
|
805 | self.HEIGHTPROF = 0 | |
| 806 | self.counter_imagwr = 0 |
|
806 | self.counter_imagwr = 0 | |
| 807 |
|
807 | |||
| 808 | self.PLOT_CODE = RTI_CODE |
|
808 | self.PLOT_CODE = RTI_CODE | |
| 809 |
|
809 | |||
| 810 | self.FTP_WEI = None |
|
810 | self.FTP_WEI = None | |
| 811 | self.EXP_CODE = None |
|
811 | self.EXP_CODE = None | |
| 812 | self.SUB_EXP_CODE = None |
|
812 | self.SUB_EXP_CODE = None | |
| 813 | self.PLOT_POS = None |
|
813 | self.PLOT_POS = None | |
| 814 | self.tmin = None |
|
814 | self.tmin = None | |
| 815 | self.tmax = None |
|
815 | self.tmax = None | |
| 816 |
|
816 | |||
| 817 | self.xmin = None |
|
817 | self.xmin = None | |
| 818 | self.xmax = None |
|
818 | self.xmax = None | |
| 819 |
|
819 | |||
| 820 | self.figfile = None |
|
820 | self.figfile = None | |
| 821 |
|
821 | |||
| 822 | def getSubplots(self): |
|
822 | def getSubplots(self): | |
| 823 |
|
823 | |||
| 824 | ncol = 1 |
|
824 | ncol = 1 | |
| 825 | nrow = self.nplots |
|
825 | nrow = self.nplots | |
| 826 |
|
826 | |||
| 827 | return nrow, ncol |
|
827 | return nrow, ncol | |
| 828 |
|
828 | |||
| 829 | def setup(self, id, nplots, wintitle, show=True): |
|
829 | def setup(self, id, nplots, wintitle, show=True): | |
| 830 |
|
830 | |||
| 831 | self.nplots = nplots |
|
831 | self.nplots = nplots | |
| 832 |
|
832 | |||
| 833 | ncolspan = 1 |
|
833 | ncolspan = 1 | |
| 834 | colspan = 1 |
|
834 | colspan = 1 | |
| 835 |
|
835 | |||
| 836 | self.createFigure(id = id, |
|
836 | self.createFigure(id = id, | |
| 837 | wintitle = wintitle, |
|
837 | wintitle = wintitle, | |
| 838 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
838 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 839 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
839 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 840 | show=show) |
|
840 | show=show) | |
| 841 |
|
841 | |||
| 842 | nrow, ncol = self.getSubplots() |
|
842 | nrow, ncol = self.getSubplots() | |
| 843 |
|
843 | |||
| 844 | counter = 0 |
|
844 | counter = 0 | |
| 845 | for y in range(nrow): |
|
845 | for y in range(nrow): | |
| 846 | for x in range(ncol): |
|
846 | for x in range(ncol): | |
| 847 |
|
847 | |||
| 848 | if counter >= self.nplots: |
|
848 | if counter >= self.nplots: | |
| 849 | break |
|
849 | break | |
| 850 |
|
850 | |||
| 851 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
851 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 852 |
|
852 | |||
| 853 | counter += 1 |
|
853 | counter += 1 | |
| 854 |
|
854 | |||
| 855 | def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap="jet", |
|
855 | def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap="jet", | |
| 856 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None, |
|
856 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None, | |
| 857 | showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None, |
|
857 | showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None, | |
| 858 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
858 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 859 | server=None, folder=None, username=None, password=None, |
|
859 | server=None, folder=None, username=None, password=None, | |
| 860 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, HEIGHT=None): |
|
860 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, HEIGHT=None): | |
| 861 | """ |
|
861 | """ | |
| 862 |
|
862 | |||
| 863 | Input: |
|
863 | Input: | |
| 864 | dataOut : |
|
864 | dataOut : | |
| 865 | id : |
|
865 | id : | |
| 866 | wintitle : |
|
866 | wintitle : | |
| 867 | channelList : |
|
867 | channelList : | |
| 868 | showProfile : |
|
868 | showProfile : | |
| 869 | xmin : None, |
|
869 | xmin : None, | |
| 870 | xmax : None, |
|
870 | xmax : None, | |
| 871 | ymin : None, |
|
871 | ymin : None, | |
| 872 | ymax : None, |
|
872 | ymax : None, | |
| 873 | zmin : None, |
|
873 | zmin : None, | |
| 874 | zmax : None |
|
874 | zmax : None | |
| 875 | """ |
|
875 | """ | |
| 876 |
|
876 | |||
| 877 | if HEIGHT is not None: |
|
877 | if HEIGHT is not None: | |
| 878 | self.HEIGHT = HEIGHT |
|
878 | self.HEIGHT = HEIGHT | |
| 879 |
|
879 | |||
| 880 |
|
880 | |||
| 881 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
881 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 882 | return |
|
882 | return | |
| 883 |
|
883 | |||
| 884 | if channelList == None: |
|
884 | if channelList == None: | |
| 885 | channelIndexList = range(dataOut.data_param.shape[0]) |
|
885 | channelIndexList = range(dataOut.data_param.shape[0]) | |
| 886 | else: |
|
886 | else: | |
| 887 | channelIndexList = [] |
|
887 | channelIndexList = [] | |
| 888 | for channel in channelList: |
|
888 | for channel in channelList: | |
| 889 | if channel not in dataOut.channelList: |
|
889 | if channel not in dataOut.channelList: | |
| 890 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
890 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 891 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
891 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 892 |
|
892 | |||
| 893 | x = dataOut.getTimeRange1(dataOut.paramInterval) |
|
893 | x = dataOut.getTimeRange1(dataOut.paramInterval) | |
| 894 | y = dataOut.getHeiRange() |
|
894 | y = dataOut.getHeiRange() | |
| 895 |
|
895 | |||
| 896 | if dataOut.data_param.ndim == 3: |
|
896 | if dataOut.data_param.ndim == 3: | |
| 897 | z = dataOut.data_param[channelIndexList,paramIndex,:] |
|
897 | z = dataOut.data_param[channelIndexList,paramIndex,:] | |
| 898 | else: |
|
898 | else: | |
| 899 | z = dataOut.data_param[channelIndexList,:] |
|
899 | z = dataOut.data_param[channelIndexList,:] | |
| 900 |
|
900 | |||
| 901 | if showSNR: |
|
901 | if showSNR: | |
| 902 | #SNR data |
|
902 | #SNR data | |
| 903 | SNRarray = dataOut.data_SNR[channelIndexList,:] |
|
903 | SNRarray = dataOut.data_SNR[channelIndexList,:] | |
| 904 | SNRdB = 10*numpy.log10(SNRarray) |
|
904 | SNRdB = 10*numpy.log10(SNRarray) | |
| 905 | ind = numpy.where(SNRdB < SNRthresh) |
|
905 | ind = numpy.where(SNRdB < SNRthresh) | |
| 906 | z[ind] = numpy.nan |
|
906 | z[ind] = numpy.nan | |
| 907 |
|
907 | |||
| 908 | thisDatetime = dataOut.datatime |
|
908 | thisDatetime = dataOut.datatime | |
| 909 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
909 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 910 | title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
910 | title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 911 | xlabel = "" |
|
911 | xlabel = "" | |
| 912 | ylabel = "Range (Km)" |
|
912 | ylabel = "Range (Km)" | |
| 913 |
|
913 | |||
| 914 | update_figfile = False |
|
914 | update_figfile = False | |
| 915 |
|
915 | |||
| 916 | if not self.isConfig: |
|
916 | if not self.isConfig: | |
| 917 |
|
917 | |||
| 918 | nchan = len(channelIndexList) |
|
918 | nchan = len(channelIndexList) | |
| 919 | self.nchan = nchan |
|
919 | self.nchan = nchan | |
| 920 | self.plotFact = 1 |
|
920 | self.plotFact = 1 | |
| 921 | nplots = nchan |
|
921 | nplots = nchan | |
| 922 |
|
922 | |||
| 923 | if showSNR: |
|
923 | if showSNR: | |
| 924 | nplots = nchan*2 |
|
924 | nplots = nchan*2 | |
| 925 | self.plotFact = 2 |
|
925 | self.plotFact = 2 | |
| 926 | if SNRmin == None: SNRmin = numpy.nanmin(SNRdB) |
|
926 | if SNRmin == None: SNRmin = numpy.nanmin(SNRdB) | |
| 927 | if SNRmax == None: SNRmax = numpy.nanmax(SNRdB) |
|
927 | if SNRmax == None: SNRmax = numpy.nanmax(SNRdB) | |
| 928 |
|
928 | |||
| 929 | self.setup(id=id, |
|
929 | self.setup(id=id, | |
| 930 | nplots=nplots, |
|
930 | nplots=nplots, | |
| 931 | wintitle=wintitle, |
|
931 | wintitle=wintitle, | |
| 932 | show=show) |
|
932 | show=show) | |
| 933 |
|
933 | |||
| 934 | if timerange != None: |
|
934 | if timerange != None: | |
| 935 | self.timerange = timerange |
|
935 | self.timerange = timerange | |
| 936 |
|
936 | |||
| 937 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
937 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 938 |
|
938 | |||
| 939 | if ymin == None: ymin = numpy.nanmin(y) |
|
939 | if ymin == None: ymin = numpy.nanmin(y) | |
| 940 | if ymax == None: ymax = numpy.nanmax(y) |
|
940 | if ymax == None: ymax = numpy.nanmax(y) | |
| 941 | if zmin == None: zmin = numpy.nanmin(z) |
|
941 | if zmin == None: zmin = numpy.nanmin(z) | |
| 942 | if zmax == None: zmax = numpy.nanmax(z) |
|
942 | if zmax == None: zmax = numpy.nanmax(z) | |
| 943 |
|
943 | |||
| 944 | self.FTP_WEI = ftp_wei |
|
944 | self.FTP_WEI = ftp_wei | |
| 945 | self.EXP_CODE = exp_code |
|
945 | self.EXP_CODE = exp_code | |
| 946 | self.SUB_EXP_CODE = sub_exp_code |
|
946 | self.SUB_EXP_CODE = sub_exp_code | |
| 947 | self.PLOT_POS = plot_pos |
|
947 | self.PLOT_POS = plot_pos | |
| 948 |
|
948 | |||
| 949 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
949 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 950 | self.isConfig = True |
|
950 | self.isConfig = True | |
| 951 | self.figfile = figfile |
|
951 | self.figfile = figfile | |
| 952 | update_figfile = True |
|
952 | update_figfile = True | |
| 953 |
|
953 | |||
| 954 | self.setWinTitle(title) |
|
954 | self.setWinTitle(title) | |
| 955 |
|
955 | |||
| 956 | for i in range(self.nchan): |
|
956 | for i in range(self.nchan): | |
| 957 | index = channelIndexList[i] |
|
957 | index = channelIndexList[i] | |
| 958 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
958 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 959 | axes = self.axesList[i*self.plotFact] |
|
959 | axes = self.axesList[i*self.plotFact] | |
| 960 | z1 = z[i,:].reshape((1,-1)) |
|
960 | z1 = z[i,:].reshape((1,-1)) | |
| 961 | axes.pcolorbuffer(x, y, z1, |
|
961 | axes.pcolorbuffer(x, y, z1, | |
| 962 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
962 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 963 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
963 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 964 | ticksize=9, cblabel='', cbsize="1%",colormap=colormap) |
|
964 | ticksize=9, cblabel='', cbsize="1%",colormap=colormap) | |
| 965 |
|
965 | |||
| 966 | if showSNR: |
|
966 | if showSNR: | |
| 967 | title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
967 | title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 968 | axes = self.axesList[i*self.plotFact + 1] |
|
968 | axes = self.axesList[i*self.plotFact + 1] | |
| 969 | SNRdB1 = SNRdB[i,:].reshape((1,-1)) |
|
969 | SNRdB1 = SNRdB[i,:].reshape((1,-1)) | |
| 970 | axes.pcolorbuffer(x, y, SNRdB1, |
|
970 | axes.pcolorbuffer(x, y, SNRdB1, | |
| 971 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, |
|
971 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, | |
| 972 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
972 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 973 | ticksize=9, cblabel='', cbsize="1%",colormap='jet') |
|
973 | ticksize=9, cblabel='', cbsize="1%",colormap='jet') | |
| 974 |
|
974 | |||
| 975 |
|
975 | |||
| 976 | self.draw() |
|
976 | self.draw() | |
| 977 |
|
977 | |||
| 978 | if dataOut.ltctime >= self.xmax: |
|
978 | if dataOut.ltctime >= self.xmax: | |
| 979 | self.counter_imagwr = wr_period |
|
979 | self.counter_imagwr = wr_period | |
| 980 | self.isConfig = False |
|
980 | self.isConfig = False | |
| 981 | update_figfile = True |
|
981 | update_figfile = True | |
| 982 |
|
982 | |||
| 983 | self.save(figpath=figpath, |
|
983 | self.save(figpath=figpath, | |
| 984 | figfile=figfile, |
|
984 | figfile=figfile, | |
| 985 | save=save, |
|
985 | save=save, | |
| 986 | ftp=ftp, |
|
986 | ftp=ftp, | |
| 987 | wr_period=wr_period, |
|
987 | wr_period=wr_period, | |
| 988 | thisDatetime=thisDatetime, |
|
988 | thisDatetime=thisDatetime, | |
| 989 | update_figfile=update_figfile) |
|
989 | update_figfile=update_figfile) | |
| 990 |
|
990 | |||
| 991 |
|
991 | |||
| 992 |
|
992 | |||
| 993 | class Parameters1Plot(Figure): |
|
993 | class Parameters1Plot(Figure): | |
| 994 |
|
994 | |||
| 995 | __isConfig = None |
|
995 | __isConfig = None | |
| 996 | __nsubplots = None |
|
996 | __nsubplots = None | |
| 997 |
|
997 | |||
| 998 | WIDTHPROF = None |
|
998 | WIDTHPROF = None | |
| 999 | HEIGHTPROF = None |
|
999 | HEIGHTPROF = None | |
| 1000 | PREFIX = 'prm' |
|
1000 | PREFIX = 'prm' | |
| 1001 |
|
1001 | |||
| 1002 | def __init__(self, **kwargs): |
|
1002 | def __init__(self, **kwargs): | |
| 1003 | Figure.__init__(self, **kwargs) |
|
1003 | Figure.__init__(self, **kwargs) | |
| 1004 | self.timerange = 2*60*60 |
|
1004 | self.timerange = 2*60*60 | |
| 1005 | self.isConfig = False |
|
1005 | self.isConfig = False | |
| 1006 | self.__nsubplots = 1 |
|
1006 | self.__nsubplots = 1 | |
| 1007 |
|
1007 | |||
| 1008 | self.WIDTH = 800 |
|
1008 | self.WIDTH = 800 | |
| 1009 | self.HEIGHT = 180 |
|
1009 | self.HEIGHT = 180 | |
| 1010 | self.WIDTHPROF = 120 |
|
1010 | self.WIDTHPROF = 120 | |
| 1011 | self.HEIGHTPROF = 0 |
|
1011 | self.HEIGHTPROF = 0 | |
| 1012 | self.counter_imagwr = 0 |
|
1012 | self.counter_imagwr = 0 | |
| 1013 |
|
1013 | |||
| 1014 | self.PLOT_CODE = PARMS_CODE |
|
1014 | self.PLOT_CODE = PARMS_CODE | |
| 1015 |
|
1015 | |||
| 1016 | self.FTP_WEI = None |
|
1016 | self.FTP_WEI = None | |
| 1017 | self.EXP_CODE = None |
|
1017 | self.EXP_CODE = None | |
| 1018 | self.SUB_EXP_CODE = None |
|
1018 | self.SUB_EXP_CODE = None | |
| 1019 | self.PLOT_POS = None |
|
1019 | self.PLOT_POS = None | |
| 1020 | self.tmin = None |
|
1020 | self.tmin = None | |
| 1021 | self.tmax = None |
|
1021 | self.tmax = None | |
| 1022 |
|
1022 | |||
| 1023 | self.xmin = None |
|
1023 | self.xmin = None | |
| 1024 | self.xmax = None |
|
1024 | self.xmax = None | |
| 1025 |
|
1025 | |||
| 1026 | self.figfile = None |
|
1026 | self.figfile = None | |
| 1027 |
|
1027 | |||
| 1028 | def getSubplots(self): |
|
1028 | def getSubplots(self): | |
| 1029 |
|
1029 | |||
| 1030 | ncol = 1 |
|
1030 | ncol = 1 | |
| 1031 | nrow = self.nplots |
|
1031 | nrow = self.nplots | |
| 1032 |
|
1032 | |||
| 1033 | return nrow, ncol |
|
1033 | return nrow, ncol | |
| 1034 |
|
1034 | |||
| 1035 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1035 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1036 |
|
1036 | |||
| 1037 | self.__showprofile = showprofile |
|
1037 | self.__showprofile = showprofile | |
| 1038 | self.nplots = nplots |
|
1038 | self.nplots = nplots | |
| 1039 |
|
1039 | |||
| 1040 | ncolspan = 1 |
|
1040 | ncolspan = 1 | |
| 1041 | colspan = 1 |
|
1041 | colspan = 1 | |
| 1042 |
|
1042 | |||
| 1043 | self.createFigure(id = id, |
|
1043 | self.createFigure(id = id, | |
| 1044 | wintitle = wintitle, |
|
1044 | wintitle = wintitle, | |
| 1045 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
1045 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 1046 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
1046 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 1047 | show=show) |
|
1047 | show=show) | |
| 1048 |
|
1048 | |||
| 1049 | nrow, ncol = self.getSubplots() |
|
1049 | nrow, ncol = self.getSubplots() | |
| 1050 |
|
1050 | |||
| 1051 | counter = 0 |
|
1051 | counter = 0 | |
| 1052 | for y in range(nrow): |
|
1052 | for y in range(nrow): | |
| 1053 | for x in range(ncol): |
|
1053 | for x in range(ncol): | |
| 1054 |
|
1054 | |||
| 1055 | if counter >= self.nplots: |
|
1055 | if counter >= self.nplots: | |
| 1056 | break |
|
1056 | break | |
| 1057 |
|
1057 | |||
| 1058 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1058 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1059 |
|
1059 | |||
| 1060 | if showprofile: |
|
1060 | if showprofile: | |
| 1061 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
1061 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 1062 |
|
1062 | |||
| 1063 | counter += 1 |
|
1063 | counter += 1 | |
| 1064 |
|
1064 | |||
| 1065 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False, |
|
1065 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False, | |
| 1066 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None, |
|
1066 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None, | |
| 1067 | parameterIndex = None, onlyPositive = False, |
|
1067 | parameterIndex = None, onlyPositive = False, | |
| 1068 | SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None, onlySNR = False, |
|
1068 | SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None, onlySNR = False, | |
| 1069 | DOP = True, |
|
1069 | DOP = True, | |
| 1070 | zlabel = "", parameterName = "", parameterObject = "data_param", |
|
1070 | zlabel = "", parameterName = "", parameterObject = "data_param", | |
| 1071 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
1071 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 1072 | server=None, folder=None, username=None, password=None, |
|
1072 | server=None, folder=None, username=None, password=None, | |
| 1073 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1073 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1074 | #print inspect.getargspec(self.run).args |
|
1074 | #print inspect.getargspec(self.run).args | |
| 1075 | """ |
|
1075 | """ | |
| 1076 |
|
1076 | |||
| 1077 | Input: |
|
1077 | Input: | |
| 1078 | dataOut : |
|
1078 | dataOut : | |
| 1079 | id : |
|
1079 | id : | |
| 1080 | wintitle : |
|
1080 | wintitle : | |
| 1081 | channelList : |
|
1081 | channelList : | |
| 1082 | showProfile : |
|
1082 | showProfile : | |
| 1083 | xmin : None, |
|
1083 | xmin : None, | |
| 1084 | xmax : None, |
|
1084 | xmax : None, | |
| 1085 | ymin : None, |
|
1085 | ymin : None, | |
| 1086 | ymax : None, |
|
1086 | ymax : None, | |
| 1087 | zmin : None, |
|
1087 | zmin : None, | |
| 1088 | zmax : None |
|
1088 | zmax : None | |
| 1089 | """ |
|
1089 | """ | |
| 1090 |
|
1090 | |||
| 1091 | data_param = getattr(dataOut, parameterObject) |
|
1091 | data_param = getattr(dataOut, parameterObject) | |
| 1092 |
|
1092 | |||
| 1093 | if channelList == None: |
|
1093 | if channelList == None: | |
| 1094 | channelIndexList = numpy.arange(data_param.shape[0]) |
|
1094 | channelIndexList = numpy.arange(data_param.shape[0]) | |
| 1095 | else: |
|
1095 | else: | |
| 1096 | channelIndexList = numpy.array(channelList) |
|
1096 | channelIndexList = numpy.array(channelList) | |
| 1097 |
|
1097 | |||
| 1098 | nchan = len(channelIndexList) #Number of channels being plotted |
|
1098 | nchan = len(channelIndexList) #Number of channels being plotted | |
| 1099 |
|
1099 | |||
| 1100 | if nchan < 1: |
|
1100 | if nchan < 1: | |
| 1101 | return |
|
1101 | return | |
| 1102 |
|
1102 | |||
| 1103 | nGraphsByChannel = 0 |
|
1103 | nGraphsByChannel = 0 | |
| 1104 |
|
1104 | |||
| 1105 | if SNR: |
|
1105 | if SNR: | |
| 1106 | nGraphsByChannel += 1 |
|
1106 | nGraphsByChannel += 1 | |
| 1107 | if DOP: |
|
1107 | if DOP: | |
| 1108 | nGraphsByChannel += 1 |
|
1108 | nGraphsByChannel += 1 | |
| 1109 |
|
1109 | |||
| 1110 | if nGraphsByChannel < 1: |
|
1110 | if nGraphsByChannel < 1: | |
| 1111 | return |
|
1111 | return | |
| 1112 |
|
1112 | |||
| 1113 | nplots = nGraphsByChannel*nchan |
|
1113 | nplots = nGraphsByChannel*nchan | |
| 1114 |
|
1114 | |||
| 1115 | if timerange is not None: |
|
1115 | if timerange is not None: | |
| 1116 | self.timerange = timerange |
|
1116 | self.timerange = timerange | |
| 1117 |
|
1117 | |||
| 1118 | #tmin = None |
|
1118 | #tmin = None | |
| 1119 | #tmax = None |
|
1119 | #tmax = None | |
| 1120 | if parameterIndex == None: |
|
1120 | if parameterIndex == None: | |
| 1121 | parameterIndex = 1 |
|
1121 | parameterIndex = 1 | |
| 1122 |
|
1122 | |||
| 1123 | x = dataOut.getTimeRange1(dataOut.paramInterval) |
|
1123 | x = dataOut.getTimeRange1(dataOut.paramInterval) | |
| 1124 | y = dataOut.heightList |
|
1124 | y = dataOut.heightList | |
| 1125 | z = data_param[channelIndexList,parameterIndex,:].copy() |
|
1125 | z = data_param[channelIndexList,parameterIndex,:].copy() | |
| 1126 |
|
1126 | |||
| 1127 | zRange = dataOut.abscissaList |
|
1127 | zRange = dataOut.abscissaList | |
| 1128 | # nChannels = z.shape[0] #Number of wind dimensions estimated |
|
1128 | # nChannels = z.shape[0] #Number of wind dimensions estimated | |
| 1129 | # thisDatetime = dataOut.datatime |
|
1129 | # thisDatetime = dataOut.datatime | |
| 1130 |
|
1130 | |||
| 1131 | if dataOut.data_SNR is not None: |
|
1131 | if dataOut.data_SNR is not None: | |
| 1132 | SNRarray = dataOut.data_SNR[channelIndexList,:] |
|
1132 | SNRarray = dataOut.data_SNR[channelIndexList,:] | |
| 1133 | SNRdB = 10*numpy.log10(SNRarray) |
|
1133 | SNRdB = 10*numpy.log10(SNRarray) | |
| 1134 | # SNRavgdB = 10*numpy.log10(SNRavg) |
|
1134 | # SNRavgdB = 10*numpy.log10(SNRavg) | |
| 1135 | ind = numpy.where(SNRdB < 10**(SNRthresh/10)) |
|
1135 | ind = numpy.where(SNRdB < 10**(SNRthresh/10)) | |
| 1136 | z[ind] = numpy.nan |
|
1136 | z[ind] = numpy.nan | |
| 1137 |
|
1137 | |||
| 1138 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1138 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1139 | title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1139 | title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1140 | xlabel = "" |
|
1140 | xlabel = "" | |
| 1141 | ylabel = "Range (Km)" |
|
1141 | ylabel = "Range (Km)" | |
| 1142 |
|
1142 | |||
| 1143 | if (SNR and not onlySNR): nplots = 2*nplots |
|
1143 | if (SNR and not onlySNR): nplots = 2*nplots | |
| 1144 |
|
1144 | |||
| 1145 | if onlyPositive: |
|
1145 | if onlyPositive: | |
| 1146 | colormap = "jet" |
|
1146 | colormap = "jet" | |
| 1147 | zmin = 0 |
|
1147 | zmin = 0 | |
| 1148 | else: colormap = "RdBu_r" |
|
1148 | else: colormap = "RdBu_r" | |
| 1149 |
|
1149 | |||
| 1150 | if not self.isConfig: |
|
1150 | if not self.isConfig: | |
| 1151 |
|
1151 | |||
| 1152 | self.setup(id=id, |
|
1152 | self.setup(id=id, | |
| 1153 | nplots=nplots, |
|
1153 | nplots=nplots, | |
| 1154 | wintitle=wintitle, |
|
1154 | wintitle=wintitle, | |
| 1155 | showprofile=showprofile, |
|
1155 | showprofile=showprofile, | |
| 1156 | show=show) |
|
1156 | show=show) | |
| 1157 |
|
1157 | |||
| 1158 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1158 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1159 |
|
1159 | |||
| 1160 | if ymin == None: ymin = numpy.nanmin(y) |
|
1160 | if ymin == None: ymin = numpy.nanmin(y) | |
| 1161 | if ymax == None: ymax = numpy.nanmax(y) |
|
1161 | if ymax == None: ymax = numpy.nanmax(y) | |
| 1162 | if zmin == None: zmin = numpy.nanmin(zRange) |
|
1162 | if zmin == None: zmin = numpy.nanmin(zRange) | |
| 1163 | if zmax == None: zmax = numpy.nanmax(zRange) |
|
1163 | if zmax == None: zmax = numpy.nanmax(zRange) | |
| 1164 |
|
1164 | |||
| 1165 | if SNR: |
|
1165 | if SNR: | |
| 1166 | if SNRmin == None: SNRmin = numpy.nanmin(SNRdB) |
|
1166 | if SNRmin == None: SNRmin = numpy.nanmin(SNRdB) | |
| 1167 | if SNRmax == None: SNRmax = numpy.nanmax(SNRdB) |
|
1167 | if SNRmax == None: SNRmax = numpy.nanmax(SNRdB) | |
| 1168 |
|
1168 | |||
| 1169 | self.FTP_WEI = ftp_wei |
|
1169 | self.FTP_WEI = ftp_wei | |
| 1170 | self.EXP_CODE = exp_code |
|
1170 | self.EXP_CODE = exp_code | |
| 1171 | self.SUB_EXP_CODE = sub_exp_code |
|
1171 | self.SUB_EXP_CODE = sub_exp_code | |
| 1172 | self.PLOT_POS = plot_pos |
|
1172 | self.PLOT_POS = plot_pos | |
| 1173 |
|
1173 | |||
| 1174 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1174 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1175 | self.isConfig = True |
|
1175 | self.isConfig = True | |
| 1176 | self.figfile = figfile |
|
1176 | self.figfile = figfile | |
| 1177 |
|
1177 | |||
| 1178 | self.setWinTitle(title) |
|
1178 | self.setWinTitle(title) | |
| 1179 |
|
1179 | |||
| 1180 | if ((self.xmax - x[1]) < (x[1]-x[0])): |
|
1180 | if ((self.xmax - x[1]) < (x[1]-x[0])): | |
| 1181 | x[1] = self.xmax |
|
1181 | x[1] = self.xmax | |
| 1182 |
|
1182 | |||
| 1183 | for i in range(nchan): |
|
1183 | for i in range(nchan): | |
| 1184 |
|
1184 | |||
| 1185 | if (SNR and not onlySNR): j = 2*i |
|
1185 | if (SNR and not onlySNR): j = 2*i | |
| 1186 | else: j = i |
|
1186 | else: j = i | |
| 1187 |
|
1187 | |||
| 1188 | j = nGraphsByChannel*i |
|
1188 | j = nGraphsByChannel*i | |
| 1189 |
|
1189 | |||
| 1190 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
1190 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 1191 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
1191 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 1192 |
|
1192 | |||
| 1193 | if not onlySNR: |
|
1193 | if not onlySNR: | |
| 1194 | axes = self.axesList[j*self.__nsubplots] |
|
1194 | axes = self.axesList[j*self.__nsubplots] | |
| 1195 | z1 = z[i,:].reshape((1,-1)) |
|
1195 | z1 = z[i,:].reshape((1,-1)) | |
| 1196 | axes.pcolorbuffer(x, y, z1, |
|
1196 | axes.pcolorbuffer(x, y, z1, | |
| 1197 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
1197 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 1198 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap, |
|
1198 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap, | |
| 1199 | ticksize=9, cblabel=zlabel, cbsize="1%") |
|
1199 | ticksize=9, cblabel=zlabel, cbsize="1%") | |
| 1200 |
|
1200 | |||
| 1201 | if DOP: |
|
1201 | if DOP: | |
| 1202 | title = "%s Channel %d: %s" %(parameterName, channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1202 | title = "%s Channel %d: %s" %(parameterName, channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1203 |
|
1203 | |||
| 1204 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
1204 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 1205 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
1205 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 1206 | axes = self.axesList[j] |
|
1206 | axes = self.axesList[j] | |
| 1207 | z1 = z[i,:].reshape((1,-1)) |
|
1207 | z1 = z[i,:].reshape((1,-1)) | |
| 1208 | axes.pcolorbuffer(x, y, z1, |
|
1208 | axes.pcolorbuffer(x, y, z1, | |
| 1209 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
1209 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 1210 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap, |
|
1210 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap, | |
| 1211 | ticksize=9, cblabel=zlabel, cbsize="1%") |
|
1211 | ticksize=9, cblabel=zlabel, cbsize="1%") | |
| 1212 |
|
1212 | |||
| 1213 | if SNR: |
|
1213 | if SNR: | |
| 1214 | title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1214 | title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1215 | axes = self.axesList[(j)*self.__nsubplots] |
|
1215 | axes = self.axesList[(j)*self.__nsubplots] | |
| 1216 | if not onlySNR: |
|
1216 | if not onlySNR: | |
| 1217 | axes = self.axesList[(j + 1)*self.__nsubplots] |
|
1217 | axes = self.axesList[(j + 1)*self.__nsubplots] | |
| 1218 |
|
1218 | |||
| 1219 | axes = self.axesList[(j + nGraphsByChannel-1)] |
|
1219 | axes = self.axesList[(j + nGraphsByChannel-1)] | |
| 1220 |
|
1220 | |||
| 1221 | z1 = SNRdB[i,:].reshape((1,-1)) |
|
1221 | z1 = SNRdB[i,:].reshape((1,-1)) | |
| 1222 | axes.pcolorbuffer(x, y, z1, |
|
1222 | axes.pcolorbuffer(x, y, z1, | |
| 1223 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, |
|
1223 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, | |
| 1224 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet", |
|
1224 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet", | |
| 1225 | ticksize=9, cblabel=zlabel, cbsize="1%") |
|
1225 | ticksize=9, cblabel=zlabel, cbsize="1%") | |
| 1226 |
|
1226 | |||
| 1227 |
|
1227 | |||
| 1228 |
|
1228 | |||
| 1229 | self.draw() |
|
1229 | self.draw() | |
| 1230 |
|
1230 | |||
| 1231 | if x[1] >= self.axesList[0].xmax: |
|
1231 | if x[1] >= self.axesList[0].xmax: | |
| 1232 | self.counter_imagwr = wr_period |
|
1232 | self.counter_imagwr = wr_period | |
| 1233 | self.isConfig = False |
|
1233 | self.isConfig = False | |
| 1234 | self.figfile = None |
|
1234 | self.figfile = None | |
| 1235 |
|
1235 | |||
| 1236 | self.save(figpath=figpath, |
|
1236 | self.save(figpath=figpath, | |
| 1237 | figfile=figfile, |
|
1237 | figfile=figfile, | |
| 1238 | save=save, |
|
1238 | save=save, | |
| 1239 | ftp=ftp, |
|
1239 | ftp=ftp, | |
| 1240 | wr_period=wr_period, |
|
1240 | wr_period=wr_period, | |
| 1241 | thisDatetime=thisDatetime, |
|
1241 | thisDatetime=thisDatetime, | |
| 1242 | update_figfile=False) |
|
1242 | update_figfile=False) | |
| 1243 |
|
1243 | |||
| 1244 | class SpectralFittingPlot(Figure): |
|
1244 | class SpectralFittingPlot(Figure): | |
| 1245 |
|
1245 | |||
| 1246 | __isConfig = None |
|
1246 | __isConfig = None | |
| 1247 | __nsubplots = None |
|
1247 | __nsubplots = None | |
| 1248 |
|
1248 | |||
| 1249 | WIDTHPROF = None |
|
1249 | WIDTHPROF = None | |
| 1250 | HEIGHTPROF = None |
|
1250 | HEIGHTPROF = None | |
| 1251 | PREFIX = 'prm' |
|
1251 | PREFIX = 'prm' | |
| 1252 |
|
1252 | |||
| 1253 |
|
1253 | |||
| 1254 | N = None |
|
1254 | N = None | |
| 1255 | ippSeconds = None |
|
1255 | ippSeconds = None | |
| 1256 |
|
1256 | |||
| 1257 | def __init__(self, **kwargs): |
|
1257 | def __init__(self, **kwargs): | |
| 1258 | Figure.__init__(self, **kwargs) |
|
1258 | Figure.__init__(self, **kwargs) | |
| 1259 | self.isConfig = False |
|
1259 | self.isConfig = False | |
| 1260 | self.__nsubplots = 1 |
|
1260 | self.__nsubplots = 1 | |
| 1261 |
|
1261 | |||
| 1262 | self.PLOT_CODE = SPECFIT_CODE |
|
1262 | self.PLOT_CODE = SPECFIT_CODE | |
| 1263 |
|
1263 | |||
| 1264 | self.WIDTH = 450 |
|
1264 | self.WIDTH = 450 | |
| 1265 | self.HEIGHT = 250 |
|
1265 | self.HEIGHT = 250 | |
| 1266 | self.WIDTHPROF = 0 |
|
1266 | self.WIDTHPROF = 0 | |
| 1267 | self.HEIGHTPROF = 0 |
|
1267 | self.HEIGHTPROF = 0 | |
| 1268 |
|
1268 | |||
| 1269 | def getSubplots(self): |
|
1269 | def getSubplots(self): | |
| 1270 |
|
1270 | |||
| 1271 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
1271 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 1272 | nrow = int(self.nplots*1./ncol + 0.9) |
|
1272 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 1273 |
|
1273 | |||
| 1274 | return nrow, ncol |
|
1274 | return nrow, ncol | |
| 1275 |
|
1275 | |||
| 1276 | def setup(self, id, nplots, wintitle, showprofile=False, show=True): |
|
1276 | def setup(self, id, nplots, wintitle, showprofile=False, show=True): | |
| 1277 |
|
1277 | |||
| 1278 | showprofile = False |
|
1278 | showprofile = False | |
| 1279 | self.__showprofile = showprofile |
|
1279 | self.__showprofile = showprofile | |
| 1280 | self.nplots = nplots |
|
1280 | self.nplots = nplots | |
| 1281 |
|
1281 | |||
| 1282 | ncolspan = 5 |
|
1282 | ncolspan = 5 | |
| 1283 | colspan = 4 |
|
1283 | colspan = 4 | |
| 1284 | if showprofile: |
|
1284 | if showprofile: | |
| 1285 | ncolspan = 5 |
|
1285 | ncolspan = 5 | |
| 1286 | colspan = 4 |
|
1286 | colspan = 4 | |
| 1287 | self.__nsubplots = 2 |
|
1287 | self.__nsubplots = 2 | |
| 1288 |
|
1288 | |||
| 1289 | self.createFigure(id = id, |
|
1289 | self.createFigure(id = id, | |
| 1290 | wintitle = wintitle, |
|
1290 | wintitle = wintitle, | |
| 1291 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
1291 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 1292 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
1292 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 1293 | show=show) |
|
1293 | show=show) | |
| 1294 |
|
1294 | |||
| 1295 | nrow, ncol = self.getSubplots() |
|
1295 | nrow, ncol = self.getSubplots() | |
| 1296 |
|
1296 | |||
| 1297 | counter = 0 |
|
1297 | counter = 0 | |
| 1298 | for y in range(nrow): |
|
1298 | for y in range(nrow): | |
| 1299 | for x in range(ncol): |
|
1299 | for x in range(ncol): | |
| 1300 |
|
1300 | |||
| 1301 | if counter >= self.nplots: |
|
1301 | if counter >= self.nplots: | |
| 1302 | break |
|
1302 | break | |
| 1303 |
|
1303 | |||
| 1304 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1304 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1305 |
|
1305 | |||
| 1306 | if showprofile: |
|
1306 | if showprofile: | |
| 1307 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
1307 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 1308 |
|
1308 | |||
| 1309 | counter += 1 |
|
1309 | counter += 1 | |
| 1310 |
|
1310 | |||
| 1311 | def run(self, dataOut, id, cutHeight=None, fit=False, wintitle="", channelList=None, showprofile=True, |
|
1311 | def run(self, dataOut, id, cutHeight=None, fit=False, wintitle="", channelList=None, showprofile=True, | |
| 1312 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1312 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1313 | save=False, figpath='./', figfile=None, show=True): |
|
1313 | save=False, figpath='./', figfile=None, show=True): | |
| 1314 |
|
1314 | |||
| 1315 | """ |
|
1315 | """ | |
| 1316 |
|
1316 | |||
| 1317 | Input: |
|
1317 | Input: | |
| 1318 | dataOut : |
|
1318 | dataOut : | |
| 1319 | id : |
|
1319 | id : | |
| 1320 | wintitle : |
|
1320 | wintitle : | |
| 1321 | channelList : |
|
1321 | channelList : | |
| 1322 | showProfile : |
|
1322 | showProfile : | |
| 1323 | xmin : None, |
|
1323 | xmin : None, | |
| 1324 | xmax : None, |
|
1324 | xmax : None, | |
| 1325 | zmin : None, |
|
1325 | zmin : None, | |
| 1326 | zmax : None |
|
1326 | zmax : None | |
| 1327 | """ |
|
1327 | """ | |
| 1328 |
|
1328 | |||
| 1329 | if cutHeight==None: |
|
1329 | if cutHeight==None: | |
| 1330 | h=270 |
|
1330 | h=270 | |
| 1331 | heightindex = numpy.abs(cutHeight - dataOut.heightList).argmin() |
|
1331 | heightindex = numpy.abs(cutHeight - dataOut.heightList).argmin() | |
| 1332 | cutHeight = dataOut.heightList[heightindex] |
|
1332 | cutHeight = dataOut.heightList[heightindex] | |
| 1333 |
|
1333 | |||
| 1334 | factor = dataOut.normFactor |
|
1334 | factor = dataOut.normFactor | |
| 1335 | x = dataOut.abscissaList[:-1] |
|
1335 | x = dataOut.abscissaList[:-1] | |
| 1336 | #y = dataOut.getHeiRange() |
|
1336 | #y = dataOut.getHeiRange() | |
| 1337 |
|
1337 | |||
| 1338 | z = dataOut.data_pre[:,:,heightindex]/factor |
|
1338 | z = dataOut.data_pre[:,:,heightindex]/factor | |
| 1339 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
1339 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 1340 | avg = numpy.average(z, axis=1) |
|
1340 | avg = numpy.average(z, axis=1) | |
| 1341 | listChannels = z.shape[0] |
|
1341 | listChannels = z.shape[0] | |
| 1342 |
|
1342 | |||
| 1343 | #Reconstruct Function |
|
1343 | #Reconstruct Function | |
| 1344 | if fit==True: |
|
1344 | if fit==True: | |
| 1345 | groupArray = dataOut.groupList |
|
1345 | groupArray = dataOut.groupList | |
| 1346 | listChannels = groupArray.reshape((groupArray.size)) |
|
1346 | listChannels = groupArray.reshape((groupArray.size)) | |
| 1347 | listChannels.sort() |
|
1347 | listChannels.sort() | |
| 1348 | spcFitLine = numpy.zeros(z.shape) |
|
1348 | spcFitLine = numpy.zeros(z.shape) | |
| 1349 | constants = dataOut.constants |
|
1349 | constants = dataOut.constants | |
| 1350 |
|
1350 | |||
| 1351 | nGroups = groupArray.shape[0] |
|
1351 | nGroups = groupArray.shape[0] | |
| 1352 | nChannels = groupArray.shape[1] |
|
1352 | nChannels = groupArray.shape[1] | |
| 1353 | nProfiles = z.shape[1] |
|
1353 | nProfiles = z.shape[1] | |
| 1354 |
|
1354 | |||
| 1355 | for f in range(nGroups): |
|
1355 | for f in range(nGroups): | |
| 1356 | groupChann = groupArray[f,:] |
|
1356 | groupChann = groupArray[f,:] | |
| 1357 | p = dataOut.data_param[f,:,heightindex] |
|
1357 | p = dataOut.data_param[f,:,heightindex] | |
| 1358 | # p = numpy.array([ 89.343967,0.14036615,0.17086219,18.89835291,1.58388365,1.55099167]) |
|
1358 | # p = numpy.array([ 89.343967,0.14036615,0.17086219,18.89835291,1.58388365,1.55099167]) | |
| 1359 | fitLineAux = dataOut.library.modelFunction(p, constants)*nProfiles |
|
1359 | fitLineAux = dataOut.library.modelFunction(p, constants)*nProfiles | |
| 1360 | fitLineAux = fitLineAux.reshape((nChannels,nProfiles)) |
|
1360 | fitLineAux = fitLineAux.reshape((nChannels,nProfiles)) | |
| 1361 | spcFitLine[groupChann,:] = fitLineAux |
|
1361 | spcFitLine[groupChann,:] = fitLineAux | |
| 1362 | # spcFitLine = spcFitLine/factor |
|
1362 | # spcFitLine = spcFitLine/factor | |
| 1363 |
|
1363 | |||
| 1364 | z = z[listChannels,:] |
|
1364 | z = z[listChannels,:] | |
| 1365 | spcFitLine = spcFitLine[listChannels,:] |
|
1365 | spcFitLine = spcFitLine[listChannels,:] | |
| 1366 | spcFitLinedB = 10*numpy.log10(spcFitLine) |
|
1366 | spcFitLinedB = 10*numpy.log10(spcFitLine) | |
| 1367 |
|
1367 | |||
| 1368 | zdB = 10*numpy.log10(z) |
|
1368 | zdB = 10*numpy.log10(z) | |
| 1369 | #thisDatetime = dataOut.datatime |
|
1369 | #thisDatetime = dataOut.datatime | |
| 1370 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1370 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1371 | title = wintitle + " Doppler Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1371 | title = wintitle + " Doppler Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1372 | xlabel = "Velocity (m/s)" |
|
1372 | xlabel = "Velocity (m/s)" | |
| 1373 | ylabel = "Spectrum" |
|
1373 | ylabel = "Spectrum" | |
| 1374 |
|
1374 | |||
| 1375 | if not self.isConfig: |
|
1375 | if not self.isConfig: | |
| 1376 |
|
1376 | |||
| 1377 | nplots = listChannels.size |
|
1377 | nplots = listChannels.size | |
| 1378 |
|
1378 | |||
| 1379 | self.setup(id=id, |
|
1379 | self.setup(id=id, | |
| 1380 | nplots=nplots, |
|
1380 | nplots=nplots, | |
| 1381 | wintitle=wintitle, |
|
1381 | wintitle=wintitle, | |
| 1382 | showprofile=showprofile, |
|
1382 | showprofile=showprofile, | |
| 1383 | show=show) |
|
1383 | show=show) | |
| 1384 |
|
1384 | |||
| 1385 | if xmin == None: xmin = numpy.nanmin(x) |
|
1385 | if xmin == None: xmin = numpy.nanmin(x) | |
| 1386 | if xmax == None: xmax = numpy.nanmax(x) |
|
1386 | if xmax == None: xmax = numpy.nanmax(x) | |
| 1387 | if ymin == None: ymin = numpy.nanmin(zdB) |
|
1387 | if ymin == None: ymin = numpy.nanmin(zdB) | |
| 1388 | if ymax == None: ymax = numpy.nanmax(zdB)+2 |
|
1388 | if ymax == None: ymax = numpy.nanmax(zdB)+2 | |
| 1389 |
|
1389 | |||
| 1390 | self.isConfig = True |
|
1390 | self.isConfig = True | |
| 1391 |
|
1391 | |||
| 1392 | self.setWinTitle(title) |
|
1392 | self.setWinTitle(title) | |
| 1393 | for i in range(self.nplots): |
|
1393 | for i in range(self.nplots): | |
| 1394 | # title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i]) |
|
1394 | # title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i]) | |
| 1395 | title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i]) |
|
1395 | title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i]) | |
| 1396 | axes = self.axesList[i*self.__nsubplots] |
|
1396 | axes = self.axesList[i*self.__nsubplots] | |
| 1397 | if fit == False: |
|
1397 | if fit == False: | |
| 1398 | axes.pline(x, zdB[i,:], |
|
1398 | axes.pline(x, zdB[i,:], | |
| 1399 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1399 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1400 | xlabel=xlabel, ylabel=ylabel, title=title |
|
1400 | xlabel=xlabel, ylabel=ylabel, title=title | |
| 1401 | ) |
|
1401 | ) | |
| 1402 | if fit == True: |
|
1402 | if fit == True: | |
| 1403 | fitline=spcFitLinedB[i,:] |
|
1403 | fitline=spcFitLinedB[i,:] | |
| 1404 | y=numpy.vstack([zdB[i,:],fitline] ) |
|
1404 | y=numpy.vstack([zdB[i,:],fitline] ) | |
| 1405 | legendlabels=['Data','Fitting'] |
|
1405 | legendlabels=['Data','Fitting'] | |
| 1406 | axes.pmultilineyaxis(x, y, |
|
1406 | axes.pmultilineyaxis(x, y, | |
| 1407 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1407 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1408 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
1408 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 1409 | legendlabels=legendlabels, marker=None, |
|
1409 | legendlabels=legendlabels, marker=None, | |
| 1410 | linestyle='solid', grid='both') |
|
1410 | linestyle='solid', grid='both') | |
| 1411 |
|
1411 | |||
| 1412 | self.draw() |
|
1412 | self.draw() | |
| 1413 |
|
1413 | |||
| 1414 | self.save(figpath=figpath, |
|
1414 | self.save(figpath=figpath, | |
| 1415 | figfile=figfile, |
|
1415 | figfile=figfile, | |
| 1416 | save=save, |
|
1416 | save=save, | |
| 1417 | ftp=ftp, |
|
1417 | ftp=ftp, | |
| 1418 | wr_period=wr_period, |
|
1418 | wr_period=wr_period, | |
| 1419 | thisDatetime=thisDatetime) |
|
1419 | thisDatetime=thisDatetime) | |
| 1420 |
|
1420 | |||
| 1421 |
|
1421 | |||
| 1422 | class EWDriftsPlot(Figure): |
|
1422 | class EWDriftsPlot(Figure): | |
| 1423 |
|
1423 | |||
| 1424 | __isConfig = None |
|
1424 | __isConfig = None | |
| 1425 | __nsubplots = None |
|
1425 | __nsubplots = None | |
| 1426 |
|
1426 | |||
| 1427 | WIDTHPROF = None |
|
1427 | WIDTHPROF = None | |
| 1428 | HEIGHTPROF = None |
|
1428 | HEIGHTPROF = None | |
| 1429 | PREFIX = 'drift' |
|
1429 | PREFIX = 'drift' | |
| 1430 |
|
1430 | |||
| 1431 | def __init__(self, **kwargs): |
|
1431 | def __init__(self, **kwargs): | |
| 1432 | Figure.__init__(self, **kwargs) |
|
1432 | Figure.__init__(self, **kwargs) | |
| 1433 | self.timerange = 2*60*60 |
|
1433 | self.timerange = 2*60*60 | |
| 1434 | self.isConfig = False |
|
1434 | self.isConfig = False | |
| 1435 | self.__nsubplots = 1 |
|
1435 | self.__nsubplots = 1 | |
| 1436 |
|
1436 | |||
| 1437 | self.WIDTH = 800 |
|
1437 | self.WIDTH = 800 | |
| 1438 | self.HEIGHT = 150 |
|
1438 | self.HEIGHT = 150 | |
| 1439 | self.WIDTHPROF = 120 |
|
1439 | self.WIDTHPROF = 120 | |
| 1440 | self.HEIGHTPROF = 0 |
|
1440 | self.HEIGHTPROF = 0 | |
| 1441 | self.counter_imagwr = 0 |
|
1441 | self.counter_imagwr = 0 | |
| 1442 |
|
1442 | |||
| 1443 | self.PLOT_CODE = EWDRIFT_CODE |
|
1443 | self.PLOT_CODE = EWDRIFT_CODE | |
| 1444 |
|
1444 | |||
| 1445 | self.FTP_WEI = None |
|
1445 | self.FTP_WEI = None | |
| 1446 | self.EXP_CODE = None |
|
1446 | self.EXP_CODE = None | |
| 1447 | self.SUB_EXP_CODE = None |
|
1447 | self.SUB_EXP_CODE = None | |
| 1448 | self.PLOT_POS = None |
|
1448 | self.PLOT_POS = None | |
| 1449 | self.tmin = None |
|
1449 | self.tmin = None | |
| 1450 | self.tmax = None |
|
1450 | self.tmax = None | |
| 1451 |
|
1451 | |||
| 1452 | self.xmin = None |
|
1452 | self.xmin = None | |
| 1453 | self.xmax = None |
|
1453 | self.xmax = None | |
| 1454 |
|
1454 | |||
| 1455 | self.figfile = None |
|
1455 | self.figfile = None | |
| 1456 |
|
1456 | |||
| 1457 | def getSubplots(self): |
|
1457 | def getSubplots(self): | |
| 1458 |
|
1458 | |||
| 1459 | ncol = 1 |
|
1459 | ncol = 1 | |
| 1460 | nrow = self.nplots |
|
1460 | nrow = self.nplots | |
| 1461 |
|
1461 | |||
| 1462 | return nrow, ncol |
|
1462 | return nrow, ncol | |
| 1463 |
|
1463 | |||
| 1464 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1464 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1465 |
|
1465 | |||
| 1466 | self.__showprofile = showprofile |
|
1466 | self.__showprofile = showprofile | |
| 1467 | self.nplots = nplots |
|
1467 | self.nplots = nplots | |
| 1468 |
|
1468 | |||
| 1469 | ncolspan = 1 |
|
1469 | ncolspan = 1 | |
| 1470 | colspan = 1 |
|
1470 | colspan = 1 | |
| 1471 |
|
1471 | |||
| 1472 | self.createFigure(id = id, |
|
1472 | self.createFigure(id = id, | |
| 1473 | wintitle = wintitle, |
|
1473 | wintitle = wintitle, | |
| 1474 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
1474 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 1475 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
1475 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 1476 | show=show) |
|
1476 | show=show) | |
| 1477 |
|
1477 | |||
| 1478 | nrow, ncol = self.getSubplots() |
|
1478 | nrow, ncol = self.getSubplots() | |
| 1479 |
|
1479 | |||
| 1480 | counter = 0 |
|
1480 | counter = 0 | |
| 1481 | for y in range(nrow): |
|
1481 | for y in range(nrow): | |
| 1482 | if counter >= self.nplots: |
|
1482 | if counter >= self.nplots: | |
| 1483 | break |
|
1483 | break | |
| 1484 |
|
1484 | |||
| 1485 | self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1) |
|
1485 | self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1) | |
| 1486 | counter += 1 |
|
1486 | counter += 1 | |
| 1487 |
|
1487 | |||
| 1488 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
1488 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 1489 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
1489 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 1490 | zmaxVertical = None, zminVertical = None, zmaxZonal = None, zminZonal = None, |
|
1490 | zmaxVertical = None, zminVertical = None, zmaxZonal = None, zminZonal = None, | |
| 1491 | timerange=None, SNRthresh = -numpy.inf, SNRmin = None, SNRmax = None, SNR_1 = False, |
|
1491 | timerange=None, SNRthresh = -numpy.inf, SNRmin = None, SNRmax = None, SNR_1 = False, | |
| 1492 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
1492 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 1493 | server=None, folder=None, username=None, password=None, |
|
1493 | server=None, folder=None, username=None, password=None, | |
| 1494 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1494 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1495 | """ |
|
1495 | """ | |
| 1496 |
|
1496 | |||
| 1497 | Input: |
|
1497 | Input: | |
| 1498 | dataOut : |
|
1498 | dataOut : | |
| 1499 | id : |
|
1499 | id : | |
| 1500 | wintitle : |
|
1500 | wintitle : | |
| 1501 | channelList : |
|
1501 | channelList : | |
| 1502 | showProfile : |
|
1502 | showProfile : | |
| 1503 | xmin : None, |
|
1503 | xmin : None, | |
| 1504 | xmax : None, |
|
1504 | xmax : None, | |
| 1505 | ymin : None, |
|
1505 | ymin : None, | |
| 1506 | ymax : None, |
|
1506 | ymax : None, | |
| 1507 | zmin : None, |
|
1507 | zmin : None, | |
| 1508 | zmax : None |
|
1508 | zmax : None | |
| 1509 | """ |
|
1509 | """ | |
| 1510 |
|
1510 | |||
| 1511 | if timerange is not None: |
|
1511 | if timerange is not None: | |
| 1512 | self.timerange = timerange |
|
1512 | self.timerange = timerange | |
| 1513 |
|
1513 | |||
| 1514 | tmin = None |
|
1514 | tmin = None | |
| 1515 | tmax = None |
|
1515 | tmax = None | |
| 1516 |
|
1516 | |||
| 1517 | x = dataOut.getTimeRange1(dataOut.outputInterval) |
|
1517 | x = dataOut.getTimeRange1(dataOut.outputInterval) | |
| 1518 | # y = dataOut.heightList |
|
1518 | # y = dataOut.heightList | |
| 1519 | y = dataOut.heightList |
|
1519 | y = dataOut.heightList | |
| 1520 |
|
1520 | |||
| 1521 | z = dataOut.data_output |
|
1521 | z = dataOut.data_output | |
| 1522 | nplots = z.shape[0] #Number of wind dimensions estimated |
|
1522 | nplots = z.shape[0] #Number of wind dimensions estimated | |
| 1523 | nplotsw = nplots |
|
1523 | nplotsw = nplots | |
| 1524 |
|
1524 | |||
| 1525 | #If there is a SNR function defined |
|
1525 | #If there is a SNR function defined | |
| 1526 | if dataOut.data_SNR is not None: |
|
1526 | if dataOut.data_SNR is not None: | |
| 1527 | nplots += 1 |
|
1527 | nplots += 1 | |
| 1528 | SNR = dataOut.data_SNR |
|
1528 | SNR = dataOut.data_SNR | |
| 1529 |
|
1529 | |||
| 1530 | if SNR_1: |
|
1530 | if SNR_1: | |
| 1531 | SNR += 1 |
|
1531 | SNR += 1 | |
| 1532 |
|
1532 | |||
| 1533 | SNRavg = numpy.average(SNR, axis=0) |
|
1533 | SNRavg = numpy.average(SNR, axis=0) | |
| 1534 |
|
1534 | |||
| 1535 | SNRdB = 10*numpy.log10(SNR) |
|
1535 | SNRdB = 10*numpy.log10(SNR) | |
| 1536 | SNRavgdB = 10*numpy.log10(SNRavg) |
|
1536 | SNRavgdB = 10*numpy.log10(SNRavg) | |
| 1537 |
|
1537 | |||
| 1538 | ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0] |
|
1538 | ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0] | |
| 1539 |
|
1539 | |||
| 1540 | for i in range(nplotsw): |
|
1540 | for i in range(nplotsw): | |
| 1541 | z[i,ind] = numpy.nan |
|
1541 | z[i,ind] = numpy.nan | |
| 1542 |
|
1542 | |||
| 1543 |
|
1543 | |||
| 1544 | showprofile = False |
|
1544 | showprofile = False | |
| 1545 | # thisDatetime = dataOut.datatime |
|
1545 | # thisDatetime = dataOut.datatime | |
| 1546 | thisDatetime = datetime.datetime.utcfromtimestamp(x[1]) |
|
1546 | thisDatetime = datetime.datetime.utcfromtimestamp(x[1]) | |
| 1547 | title = wintitle + " EW Drifts" |
|
1547 | title = wintitle + " EW Drifts" | |
| 1548 | xlabel = "" |
|
1548 | xlabel = "" | |
| 1549 | ylabel = "Height (Km)" |
|
1549 | ylabel = "Height (Km)" | |
| 1550 |
|
1550 | |||
| 1551 | if not self.isConfig: |
|
1551 | if not self.isConfig: | |
| 1552 |
|
1552 | |||
| 1553 | self.setup(id=id, |
|
1553 | self.setup(id=id, | |
| 1554 | nplots=nplots, |
|
1554 | nplots=nplots, | |
| 1555 | wintitle=wintitle, |
|
1555 | wintitle=wintitle, | |
| 1556 | showprofile=showprofile, |
|
1556 | showprofile=showprofile, | |
| 1557 | show=show) |
|
1557 | show=show) | |
| 1558 |
|
1558 | |||
| 1559 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1559 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1560 |
|
1560 | |||
| 1561 | if ymin == None: ymin = numpy.nanmin(y) |
|
1561 | if ymin == None: ymin = numpy.nanmin(y) | |
| 1562 | if ymax == None: ymax = numpy.nanmax(y) |
|
1562 | if ymax == None: ymax = numpy.nanmax(y) | |
| 1563 |
|
1563 | |||
| 1564 | if zmaxZonal == None: zmaxZonal = numpy.nanmax(abs(z[0,:])) |
|
1564 | if zmaxZonal == None: zmaxZonal = numpy.nanmax(abs(z[0,:])) | |
| 1565 | if zminZonal == None: zminZonal = -zmaxZonal |
|
1565 | if zminZonal == None: zminZonal = -zmaxZonal | |
| 1566 | if zmaxVertical == None: zmaxVertical = numpy.nanmax(abs(z[1,:])) |
|
1566 | if zmaxVertical == None: zmaxVertical = numpy.nanmax(abs(z[1,:])) | |
| 1567 | if zminVertical == None: zminVertical = -zmaxVertical |
|
1567 | if zminVertical == None: zminVertical = -zmaxVertical | |
| 1568 |
|
1568 | |||
| 1569 | if dataOut.data_SNR is not None: |
|
1569 | if dataOut.data_SNR is not None: | |
| 1570 | if SNRmin == None: SNRmin = numpy.nanmin(SNRavgdB) |
|
1570 | if SNRmin == None: SNRmin = numpy.nanmin(SNRavgdB) | |
| 1571 | if SNRmax == None: SNRmax = numpy.nanmax(SNRavgdB) |
|
1571 | if SNRmax == None: SNRmax = numpy.nanmax(SNRavgdB) | |
| 1572 |
|
1572 | |||
| 1573 | self.FTP_WEI = ftp_wei |
|
1573 | self.FTP_WEI = ftp_wei | |
| 1574 | self.EXP_CODE = exp_code |
|
1574 | self.EXP_CODE = exp_code | |
| 1575 | self.SUB_EXP_CODE = sub_exp_code |
|
1575 | self.SUB_EXP_CODE = sub_exp_code | |
| 1576 | self.PLOT_POS = plot_pos |
|
1576 | self.PLOT_POS = plot_pos | |
| 1577 |
|
1577 | |||
| 1578 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1578 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1579 | self.isConfig = True |
|
1579 | self.isConfig = True | |
| 1580 |
|
1580 | |||
| 1581 |
|
1581 | |||
| 1582 | self.setWinTitle(title) |
|
1582 | self.setWinTitle(title) | |
| 1583 |
|
1583 | |||
| 1584 | if ((self.xmax - x[1]) < (x[1]-x[0])): |
|
1584 | if ((self.xmax - x[1]) < (x[1]-x[0])): | |
| 1585 | x[1] = self.xmax |
|
1585 | x[1] = self.xmax | |
| 1586 |
|
1586 | |||
| 1587 | strWind = ['Zonal','Vertical'] |
|
1587 | strWind = ['Zonal','Vertical'] | |
| 1588 | strCb = 'Velocity (m/s)' |
|
1588 | strCb = 'Velocity (m/s)' | |
| 1589 | zmaxVector = [zmaxZonal, zmaxVertical] |
|
1589 | zmaxVector = [zmaxZonal, zmaxVertical] | |
| 1590 | zminVector = [zminZonal, zminVertical] |
|
1590 | zminVector = [zminZonal, zminVertical] | |
| 1591 |
|
1591 | |||
| 1592 | for i in range(nplotsw): |
|
1592 | for i in range(nplotsw): | |
| 1593 |
|
1593 | |||
| 1594 | title = "%s Drifts: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1594 | title = "%s Drifts: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1595 | axes = self.axesList[i*self.__nsubplots] |
|
1595 | axes = self.axesList[i*self.__nsubplots] | |
| 1596 |
|
1596 | |||
| 1597 | z1 = z[i,:].reshape((1,-1)) |
|
1597 | z1 = z[i,:].reshape((1,-1)) | |
| 1598 |
|
1598 | |||
| 1599 | axes.pcolorbuffer(x, y, z1, |
|
1599 | axes.pcolorbuffer(x, y, z1, | |
| 1600 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i], |
|
1600 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i], | |
| 1601 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
1601 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 1602 | ticksize=9, cblabel=strCb, cbsize="1%", colormap="RdBu_r") |
|
1602 | ticksize=9, cblabel=strCb, cbsize="1%", colormap="RdBu_r") | |
| 1603 |
|
1603 | |||
| 1604 | if dataOut.data_SNR is not None: |
|
1604 | if dataOut.data_SNR is not None: | |
| 1605 | i += 1 |
|
1605 | i += 1 | |
| 1606 | if SNR_1: |
|
1606 | if SNR_1: | |
| 1607 | title = "Signal Noise Ratio + 1 (SNR+1): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1607 | title = "Signal Noise Ratio + 1 (SNR+1): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1608 | else: |
|
1608 | else: | |
| 1609 | title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1609 | title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1610 | axes = self.axesList[i*self.__nsubplots] |
|
1610 | axes = self.axesList[i*self.__nsubplots] | |
| 1611 | SNRavgdB = SNRavgdB.reshape((1,-1)) |
|
1611 | SNRavgdB = SNRavgdB.reshape((1,-1)) | |
| 1612 |
|
1612 | |||
| 1613 | axes.pcolorbuffer(x, y, SNRavgdB, |
|
1613 | axes.pcolorbuffer(x, y, SNRavgdB, | |
| 1614 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, |
|
1614 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax, | |
| 1615 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
1615 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 1616 | ticksize=9, cblabel='', cbsize="1%", colormap="jet") |
|
1616 | ticksize=9, cblabel='', cbsize="1%", colormap="jet") | |
| 1617 |
|
1617 | |||
| 1618 | self.draw() |
|
1618 | self.draw() | |
| 1619 |
|
1619 | |||
| 1620 | if x[1] >= self.axesList[0].xmax: |
|
1620 | if x[1] >= self.axesList[0].xmax: | |
| 1621 | self.counter_imagwr = wr_period |
|
1621 | self.counter_imagwr = wr_period | |
| 1622 | self.isConfig = False |
|
1622 | self.isConfig = False | |
| 1623 | self.figfile = None |
|
1623 | self.figfile = None | |
| 1624 |
|
1624 | |||
| 1625 |
|
1625 | |||
| 1626 |
|
1626 | |||
| 1627 |
|
1627 | |||
| 1628 | class PhasePlot(Figure): |
|
1628 | class PhasePlot(Figure): | |
| 1629 |
|
1629 | |||
| 1630 | __isConfig = None |
|
1630 | __isConfig = None | |
| 1631 | __nsubplots = None |
|
1631 | __nsubplots = None | |
| 1632 |
|
1632 | |||
| 1633 | PREFIX = 'mphase' |
|
1633 | PREFIX = 'mphase' | |
| 1634 |
|
1634 | |||
| 1635 | def __init__(self, **kwargs): |
|
1635 | def __init__(self, **kwargs): | |
| 1636 | Figure.__init__(self, **kwargs) |
|
1636 | Figure.__init__(self, **kwargs) | |
| 1637 | self.timerange = 24*60*60 |
|
1637 | self.timerange = 24*60*60 | |
| 1638 | self.isConfig = False |
|
1638 | self.isConfig = False | |
| 1639 | self.__nsubplots = 1 |
|
1639 | self.__nsubplots = 1 | |
| 1640 | self.counter_imagwr = 0 |
|
1640 | self.counter_imagwr = 0 | |
| 1641 | self.WIDTH = 600 |
|
1641 | self.WIDTH = 600 | |
| 1642 | self.HEIGHT = 300 |
|
1642 | self.HEIGHT = 300 | |
| 1643 | self.WIDTHPROF = 120 |
|
1643 | self.WIDTHPROF = 120 | |
| 1644 | self.HEIGHTPROF = 0 |
|
1644 | self.HEIGHTPROF = 0 | |
| 1645 | self.xdata = None |
|
1645 | self.xdata = None | |
| 1646 | self.ydata = None |
|
1646 | self.ydata = None | |
| 1647 |
|
1647 | |||
| 1648 | self.PLOT_CODE = MPHASE_CODE |
|
1648 | self.PLOT_CODE = MPHASE_CODE | |
| 1649 |
|
1649 | |||
| 1650 | self.FTP_WEI = None |
|
1650 | self.FTP_WEI = None | |
| 1651 | self.EXP_CODE = None |
|
1651 | self.EXP_CODE = None | |
| 1652 | self.SUB_EXP_CODE = None |
|
1652 | self.SUB_EXP_CODE = None | |
| 1653 | self.PLOT_POS = None |
|
1653 | self.PLOT_POS = None | |
| 1654 |
|
1654 | |||
| 1655 |
|
1655 | |||
| 1656 | self.filename_phase = None |
|
1656 | self.filename_phase = None | |
| 1657 |
|
1657 | |||
| 1658 | self.figfile = None |
|
1658 | self.figfile = None | |
| 1659 |
|
1659 | |||
| 1660 | def getSubplots(self): |
|
1660 | def getSubplots(self): | |
| 1661 |
|
1661 | |||
| 1662 | ncol = 1 |
|
1662 | ncol = 1 | |
| 1663 | nrow = 1 |
|
1663 | nrow = 1 | |
| 1664 |
|
1664 | |||
| 1665 | return nrow, ncol |
|
1665 | return nrow, ncol | |
| 1666 |
|
1666 | |||
| 1667 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1667 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1668 |
|
1668 | |||
| 1669 | self.__showprofile = showprofile |
|
1669 | self.__showprofile = showprofile | |
| 1670 | self.nplots = nplots |
|
1670 | self.nplots = nplots | |
| 1671 |
|
1671 | |||
| 1672 | ncolspan = 7 |
|
1672 | ncolspan = 7 | |
| 1673 | colspan = 6 |
|
1673 | colspan = 6 | |
| 1674 | self.__nsubplots = 2 |
|
1674 | self.__nsubplots = 2 | |
| 1675 |
|
1675 | |||
| 1676 | self.createFigure(id = id, |
|
1676 | self.createFigure(id = id, | |
| 1677 | wintitle = wintitle, |
|
1677 | wintitle = wintitle, | |
| 1678 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1678 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1679 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1679 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1680 | show=show) |
|
1680 | show=show) | |
| 1681 |
|
1681 | |||
| 1682 | nrow, ncol = self.getSubplots() |
|
1682 | nrow, ncol = self.getSubplots() | |
| 1683 |
|
1683 | |||
| 1684 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1684 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1685 |
|
1685 | |||
| 1686 |
|
1686 | |||
| 1687 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
1687 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 1688 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1688 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1689 | timerange=None, |
|
1689 | timerange=None, | |
| 1690 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1690 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1691 | server=None, folder=None, username=None, password=None, |
|
1691 | server=None, folder=None, username=None, password=None, | |
| 1692 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1692 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1693 |
|
1693 | |||
| 1694 |
|
1694 | |||
| 1695 | tmin = None |
|
1695 | tmin = None | |
| 1696 | tmax = None |
|
1696 | tmax = None | |
| 1697 | x = dataOut.getTimeRange1(dataOut.outputInterval) |
|
1697 | x = dataOut.getTimeRange1(dataOut.outputInterval) | |
| 1698 | y = dataOut.getHeiRange() |
|
1698 | y = dataOut.getHeiRange() | |
| 1699 |
|
1699 | |||
| 1700 |
|
1700 | |||
| 1701 | #thisDatetime = dataOut.datatime |
|
1701 | #thisDatetime = dataOut.datatime | |
| 1702 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) |
|
1702 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) | |
| 1703 | title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1703 | title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1704 | xlabel = "Local Time" |
|
1704 | xlabel = "Local Time" | |
| 1705 | ylabel = "Phase" |
|
1705 | ylabel = "Phase" | |
| 1706 |
|
1706 | |||
| 1707 |
|
1707 | |||
| 1708 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
1708 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) | |
| 1709 | phase_beacon = dataOut.data_output |
|
1709 | phase_beacon = dataOut.data_output | |
| 1710 | update_figfile = False |
|
1710 | update_figfile = False | |
| 1711 |
|
1711 | |||
| 1712 | if not self.isConfig: |
|
1712 | if not self.isConfig: | |
| 1713 |
|
1713 | |||
| 1714 | self.nplots = phase_beacon.size |
|
1714 | self.nplots = phase_beacon.size | |
| 1715 |
|
1715 | |||
| 1716 | self.setup(id=id, |
|
1716 | self.setup(id=id, | |
| 1717 | nplots=self.nplots, |
|
1717 | nplots=self.nplots, | |
| 1718 | wintitle=wintitle, |
|
1718 | wintitle=wintitle, | |
| 1719 | showprofile=showprofile, |
|
1719 | showprofile=showprofile, | |
| 1720 | show=show) |
|
1720 | show=show) | |
| 1721 |
|
1721 | |||
| 1722 | if timerange is not None: |
|
1722 | if timerange is not None: | |
| 1723 | self.timerange = timerange |
|
1723 | self.timerange = timerange | |
| 1724 |
|
1724 | |||
| 1725 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1725 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1726 |
|
1726 | |||
| 1727 | if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0 |
|
1727 | if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0 | |
| 1728 | if ymax == None: ymax = numpy.nanmax(phase_beacon) + 10.0 |
|
1728 | if ymax == None: ymax = numpy.nanmax(phase_beacon) + 10.0 | |
| 1729 |
|
1729 | |||
| 1730 | self.FTP_WEI = ftp_wei |
|
1730 | self.FTP_WEI = ftp_wei | |
| 1731 | self.EXP_CODE = exp_code |
|
1731 | self.EXP_CODE = exp_code | |
| 1732 | self.SUB_EXP_CODE = sub_exp_code |
|
1732 | self.SUB_EXP_CODE = sub_exp_code | |
| 1733 | self.PLOT_POS = plot_pos |
|
1733 | self.PLOT_POS = plot_pos | |
| 1734 |
|
1734 | |||
| 1735 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1735 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1736 | self.isConfig = True |
|
1736 | self.isConfig = True | |
| 1737 | self.figfile = figfile |
|
1737 | self.figfile = figfile | |
| 1738 | self.xdata = numpy.array([]) |
|
1738 | self.xdata = numpy.array([]) | |
| 1739 | self.ydata = numpy.array([]) |
|
1739 | self.ydata = numpy.array([]) | |
| 1740 |
|
1740 | |||
| 1741 | #open file beacon phase |
|
1741 | #open file beacon phase | |
| 1742 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1742 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1743 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
1743 | beacon_file = os.path.join(path,'%s.txt'%self.name) | |
| 1744 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
1744 | self.filename_phase = os.path.join(figpath,beacon_file) | |
| 1745 | update_figfile = True |
|
1745 | update_figfile = True | |
| 1746 |
|
1746 | |||
| 1747 |
|
1747 | |||
| 1748 | #store data beacon phase |
|
1748 | #store data beacon phase | |
| 1749 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
1749 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) | |
| 1750 |
|
1750 | |||
| 1751 | self.setWinTitle(title) |
|
1751 | self.setWinTitle(title) | |
| 1752 |
|
1752 | |||
| 1753 |
|
1753 | |||
| 1754 | title = "Phase Offset %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1754 | title = "Phase Offset %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1755 |
|
1755 | |||
| 1756 | legendlabels = ["phase %d"%(chan) for chan in numpy.arange(self.nplots)] |
|
1756 | legendlabels = ["phase %d"%(chan) for chan in numpy.arange(self.nplots)] | |
| 1757 |
|
1757 | |||
| 1758 | axes = self.axesList[0] |
|
1758 | axes = self.axesList[0] | |
| 1759 |
|
1759 | |||
| 1760 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1760 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1761 |
|
1761 | |||
| 1762 | if len(self.ydata)==0: |
|
1762 | if len(self.ydata)==0: | |
| 1763 | self.ydata = phase_beacon.reshape(-1,1) |
|
1763 | self.ydata = phase_beacon.reshape(-1,1) | |
| 1764 | else: |
|
1764 | else: | |
| 1765 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
1765 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |
| 1766 |
|
1766 | |||
| 1767 |
|
1767 | |||
| 1768 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1768 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1769 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1769 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1770 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1770 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1771 | XAxisAsTime=True, grid='both' |
|
1771 | XAxisAsTime=True, grid='both' | |
| 1772 | ) |
|
1772 | ) | |
| 1773 |
|
1773 | |||
| 1774 | self.draw() |
|
1774 | self.draw() | |
| 1775 |
|
1775 | |||
| 1776 | self.save(figpath=figpath, |
|
1776 | self.save(figpath=figpath, | |
| 1777 | figfile=figfile, |
|
1777 | figfile=figfile, | |
| 1778 | save=save, |
|
1778 | save=save, | |
| 1779 | ftp=ftp, |
|
1779 | ftp=ftp, | |
| 1780 | wr_period=wr_period, |
|
1780 | wr_period=wr_period, | |
| 1781 | thisDatetime=thisDatetime, |
|
1781 | thisDatetime=thisDatetime, | |
| 1782 | update_figfile=update_figfile) |
|
1782 | update_figfile=update_figfile) | |
| 1783 |
|
1783 | |||
| 1784 | if dataOut.ltctime + dataOut.outputInterval >= self.xmax: |
|
1784 | if dataOut.ltctime + dataOut.outputInterval >= self.xmax: | |
| 1785 | self.counter_imagwr = wr_period |
|
1785 | self.counter_imagwr = wr_period | |
| 1786 | self.isConfig = False |
|
1786 | self.isConfig = False | |
| 1787 | update_figfile = True |
|
1787 | update_figfile = True | |
| 1788 |
|
1788 | |||
| 1789 |
|
1789 | |||
| 1790 |
|
1790 | |||
| 1791 | class NSMeteorDetection1Plot(Figure): |
|
1791 | class NSMeteorDetection1Plot(Figure): | |
| 1792 |
|
1792 | |||
| 1793 | isConfig = None |
|
1793 | isConfig = None | |
| 1794 | __nsubplots = None |
|
1794 | __nsubplots = None | |
| 1795 |
|
1795 | |||
| 1796 | WIDTHPROF = None |
|
1796 | WIDTHPROF = None | |
| 1797 | HEIGHTPROF = None |
|
1797 | HEIGHTPROF = None | |
| 1798 | PREFIX = 'nsm' |
|
1798 | PREFIX = 'nsm' | |
| 1799 |
|
1799 | |||
| 1800 | zminList = None |
|
1800 | zminList = None | |
| 1801 | zmaxList = None |
|
1801 | zmaxList = None | |
| 1802 | cmapList = None |
|
1802 | cmapList = None | |
| 1803 | titleList = None |
|
1803 | titleList = None | |
| 1804 | nPairs = None |
|
1804 | nPairs = None | |
| 1805 | nChannels = None |
|
1805 | nChannels = None | |
| 1806 | nParam = None |
|
1806 | nParam = None | |
| 1807 |
|
1807 | |||
| 1808 | def __init__(self, **kwargs): |
|
1808 | def __init__(self, **kwargs): | |
| 1809 | Figure.__init__(self, **kwargs) |
|
1809 | Figure.__init__(self, **kwargs) | |
| 1810 | self.isConfig = False |
|
1810 | self.isConfig = False | |
| 1811 | self.__nsubplots = 1 |
|
1811 | self.__nsubplots = 1 | |
| 1812 |
|
1812 | |||
| 1813 | self.WIDTH = 750 |
|
1813 | self.WIDTH = 750 | |
| 1814 | self.HEIGHT = 250 |
|
1814 | self.HEIGHT = 250 | |
| 1815 | self.WIDTHPROF = 120 |
|
1815 | self.WIDTHPROF = 120 | |
| 1816 | self.HEIGHTPROF = 0 |
|
1816 | self.HEIGHTPROF = 0 | |
| 1817 | self.counter_imagwr = 0 |
|
1817 | self.counter_imagwr = 0 | |
| 1818 |
|
1818 | |||
| 1819 | self.PLOT_CODE = SPEC_CODE |
|
1819 | self.PLOT_CODE = SPEC_CODE | |
| 1820 |
|
1820 | |||
| 1821 | self.FTP_WEI = None |
|
1821 | self.FTP_WEI = None | |
| 1822 | self.EXP_CODE = None |
|
1822 | self.EXP_CODE = None | |
| 1823 | self.SUB_EXP_CODE = None |
|
1823 | self.SUB_EXP_CODE = None | |
| 1824 | self.PLOT_POS = None |
|
1824 | self.PLOT_POS = None | |
| 1825 |
|
1825 | |||
| 1826 | self.__xfilter_ena = False |
|
1826 | self.__xfilter_ena = False | |
| 1827 | self.__yfilter_ena = False |
|
1827 | self.__yfilter_ena = False | |
| 1828 |
|
1828 | |||
| 1829 | def getSubplots(self): |
|
1829 | def getSubplots(self): | |
| 1830 |
|
1830 | |||
| 1831 | ncol = 3 |
|
1831 | ncol = 3 | |
| 1832 | nrow = int(numpy.ceil(self.nplots/3.0)) |
|
1832 | nrow = int(numpy.ceil(self.nplots/3.0)) | |
| 1833 |
|
1833 | |||
| 1834 | return nrow, ncol |
|
1834 | return nrow, ncol | |
| 1835 |
|
1835 | |||
| 1836 | def setup(self, id, nplots, wintitle, show=True): |
|
1836 | def setup(self, id, nplots, wintitle, show=True): | |
| 1837 |
|
1837 | |||
| 1838 | self.nplots = nplots |
|
1838 | self.nplots = nplots | |
| 1839 |
|
1839 | |||
| 1840 | ncolspan = 1 |
|
1840 | ncolspan = 1 | |
| 1841 | colspan = 1 |
|
1841 | colspan = 1 | |
| 1842 |
|
1842 | |||
| 1843 | self.createFigure(id = id, |
|
1843 | self.createFigure(id = id, | |
| 1844 | wintitle = wintitle, |
|
1844 | wintitle = wintitle, | |
| 1845 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
1845 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 1846 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
1846 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 1847 | show=show) |
|
1847 | show=show) | |
| 1848 |
|
1848 | |||
| 1849 | nrow, ncol = self.getSubplots() |
|
1849 | nrow, ncol = self.getSubplots() | |
| 1850 |
|
1850 | |||
| 1851 | counter = 0 |
|
1851 | counter = 0 | |
| 1852 | for y in range(nrow): |
|
1852 | for y in range(nrow): | |
| 1853 | for x in range(ncol): |
|
1853 | for x in range(ncol): | |
| 1854 |
|
1854 | |||
| 1855 | if counter >= self.nplots: |
|
1855 | if counter >= self.nplots: | |
| 1856 | break |
|
1856 | break | |
| 1857 |
|
1857 | |||
| 1858 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1858 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1859 |
|
1859 | |||
| 1860 | counter += 1 |
|
1860 | counter += 1 | |
| 1861 |
|
1861 | |||
| 1862 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
1862 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 1863 | xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None, |
|
1863 | xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None, | |
| 1864 | vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA', |
|
1864 | vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA', | |
| 1865 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1865 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1866 | server=None, folder=None, username=None, password=None, |
|
1866 | server=None, folder=None, username=None, password=None, | |
| 1867 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
1867 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
| 1868 | xaxis="frequency"): |
|
1868 | xaxis="frequency"): | |
| 1869 |
|
1869 | |||
| 1870 | """ |
|
1870 | """ | |
| 1871 |
|
1871 | |||
| 1872 | Input: |
|
1872 | Input: | |
| 1873 | dataOut : |
|
1873 | dataOut : | |
| 1874 | id : |
|
1874 | id : | |
| 1875 | wintitle : |
|
1875 | wintitle : | |
| 1876 | channelList : |
|
1876 | channelList : | |
| 1877 | showProfile : |
|
1877 | showProfile : | |
| 1878 | xmin : None, |
|
1878 | xmin : None, | |
| 1879 | xmax : None, |
|
1879 | xmax : None, | |
| 1880 | ymin : None, |
|
1880 | ymin : None, | |
| 1881 | ymax : None, |
|
1881 | ymax : None, | |
| 1882 | zmin : None, |
|
1882 | zmin : None, | |
| 1883 | zmax : None |
|
1883 | zmax : None | |
| 1884 | """ |
|
1884 | """ | |
| 1885 | #SEPARAR EN DOS PLOTS |
|
1885 | #SEPARAR EN DOS PLOTS | |
| 1886 | nParam = dataOut.data_param.shape[1] - 3 |
|
1886 | nParam = dataOut.data_param.shape[1] - 3 | |
| 1887 |
|
1887 | |||
| 1888 | utctime = dataOut.data_param[0,0] |
|
1888 | utctime = dataOut.data_param[0,0] | |
| 1889 | tmet = dataOut.data_param[:,1].astype(int) |
|
1889 | tmet = dataOut.data_param[:,1].astype(int) | |
| 1890 | hmet = dataOut.data_param[:,2].astype(int) |
|
1890 | hmet = dataOut.data_param[:,2].astype(int) | |
| 1891 |
|
1891 | |||
| 1892 | x = dataOut.abscissaList |
|
1892 | x = dataOut.abscissaList | |
| 1893 | y = dataOut.heightList |
|
1893 | y = dataOut.heightList | |
| 1894 |
|
1894 | |||
| 1895 | z = numpy.zeros((nParam, y.size, x.size - 1)) |
|
1895 | z = numpy.zeros((nParam, y.size, x.size - 1)) | |
| 1896 | z[:,:] = numpy.nan |
|
1896 | z[:,:] = numpy.nan | |
| 1897 | z[:,hmet,tmet] = dataOut.data_param[:,3:].T |
|
1897 | z[:,hmet,tmet] = dataOut.data_param[:,3:].T | |
| 1898 | z[0,:,:] = 10*numpy.log10(z[0,:,:]) |
|
1898 | z[0,:,:] = 10*numpy.log10(z[0,:,:]) | |
| 1899 |
|
1899 | |||
| 1900 | xlabel = "Time (s)" |
|
1900 | xlabel = "Time (s)" | |
| 1901 | ylabel = "Range (km)" |
|
1901 | ylabel = "Range (km)" | |
| 1902 |
|
1902 | |||
| 1903 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) |
|
1903 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) | |
| 1904 |
|
1904 | |||
| 1905 | if not self.isConfig: |
|
1905 | if not self.isConfig: | |
| 1906 |
|
1906 | |||
| 1907 | nplots = nParam |
|
1907 | nplots = nParam | |
| 1908 |
|
1908 | |||
| 1909 | self.setup(id=id, |
|
1909 | self.setup(id=id, | |
| 1910 | nplots=nplots, |
|
1910 | nplots=nplots, | |
| 1911 | wintitle=wintitle, |
|
1911 | wintitle=wintitle, | |
| 1912 | show=show) |
|
1912 | show=show) | |
| 1913 |
|
1913 | |||
| 1914 | if xmin is None: xmin = numpy.nanmin(x) |
|
1914 | if xmin is None: xmin = numpy.nanmin(x) | |
| 1915 | if xmax is None: xmax = numpy.nanmax(x) |
|
1915 | if xmax is None: xmax = numpy.nanmax(x) | |
| 1916 | if ymin is None: ymin = numpy.nanmin(y) |
|
1916 | if ymin is None: ymin = numpy.nanmin(y) | |
| 1917 | if ymax is None: ymax = numpy.nanmax(y) |
|
1917 | if ymax is None: ymax = numpy.nanmax(y) | |
| 1918 | if SNRmin is None: SNRmin = numpy.nanmin(z[0,:]) |
|
1918 | if SNRmin is None: SNRmin = numpy.nanmin(z[0,:]) | |
| 1919 | if SNRmax is None: SNRmax = numpy.nanmax(z[0,:]) |
|
1919 | if SNRmax is None: SNRmax = numpy.nanmax(z[0,:]) | |
| 1920 | if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:])) |
|
1920 | if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:])) | |
| 1921 | if vmin is None: vmin = -vmax |
|
1921 | if vmin is None: vmin = -vmax | |
| 1922 | if wmin is None: wmin = 0 |
|
1922 | if wmin is None: wmin = 0 | |
| 1923 | if wmax is None: wmax = 50 |
|
1923 | if wmax is None: wmax = 50 | |
| 1924 |
|
1924 | |||
| 1925 | pairsList = dataOut.groupList |
|
1925 | pairsList = dataOut.groupList | |
| 1926 | self.nPairs = len(dataOut.groupList) |
|
1926 | self.nPairs = len(dataOut.groupList) | |
| 1927 |
|
1927 | |||
| 1928 | zminList = [SNRmin, vmin, cmin] + [pmin]*self.nPairs |
|
1928 | zminList = [SNRmin, vmin, cmin] + [pmin]*self.nPairs | |
| 1929 | zmaxList = [SNRmax, vmax, cmax] + [pmax]*self.nPairs |
|
1929 | zmaxList = [SNRmax, vmax, cmax] + [pmax]*self.nPairs | |
| 1930 | titleList = ["SNR","Radial Velocity","Coherence"] |
|
1930 | titleList = ["SNR","Radial Velocity","Coherence"] | |
| 1931 | cmapList = ["jet","RdBu_r","jet"] |
|
1931 | cmapList = ["jet","RdBu_r","jet"] | |
| 1932 |
|
1932 | |||
| 1933 | for i in range(self.nPairs): |
|
1933 | for i in range(self.nPairs): | |
| 1934 | strAux1 = "Phase Difference "+ str(pairsList[i][0]) + str(pairsList[i][1]) |
|
1934 | strAux1 = "Phase Difference "+ str(pairsList[i][0]) + str(pairsList[i][1]) | |
| 1935 | titleList = titleList + [strAux1] |
|
1935 | titleList = titleList + [strAux1] | |
| 1936 | cmapList = cmapList + ["RdBu_r"] |
|
1936 | cmapList = cmapList + ["RdBu_r"] | |
| 1937 |
|
1937 | |||
| 1938 | self.zminList = zminList |
|
1938 | self.zminList = zminList | |
| 1939 | self.zmaxList = zmaxList |
|
1939 | self.zmaxList = zmaxList | |
| 1940 | self.cmapList = cmapList |
|
1940 | self.cmapList = cmapList | |
| 1941 | self.titleList = titleList |
|
1941 | self.titleList = titleList | |
| 1942 |
|
1942 | |||
| 1943 | self.FTP_WEI = ftp_wei |
|
1943 | self.FTP_WEI = ftp_wei | |
| 1944 | self.EXP_CODE = exp_code |
|
1944 | self.EXP_CODE = exp_code | |
| 1945 | self.SUB_EXP_CODE = sub_exp_code |
|
1945 | self.SUB_EXP_CODE = sub_exp_code | |
| 1946 | self.PLOT_POS = plot_pos |
|
1946 | self.PLOT_POS = plot_pos | |
| 1947 |
|
1947 | |||
| 1948 | self.isConfig = True |
|
1948 | self.isConfig = True | |
| 1949 |
|
1949 | |||
| 1950 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
1950 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 1951 |
|
1951 | |||
| 1952 | for i in range(nParam): |
|
1952 | for i in range(nParam): | |
| 1953 | title = self.titleList[i] + ": " +str_datetime |
|
1953 | title = self.titleList[i] + ": " +str_datetime | |
| 1954 | axes = self.axesList[i] |
|
1954 | axes = self.axesList[i] | |
| 1955 | axes.pcolor(x, y, z[i,:].T, |
|
1955 | axes.pcolor(x, y, z[i,:].T, | |
| 1956 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i], |
|
1956 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i], | |
| 1957 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='') |
|
1957 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='') | |
| 1958 | self.draw() |
|
1958 | self.draw() | |
| 1959 |
|
1959 | |||
| 1960 | if figfile == None: |
|
1960 | if figfile == None: | |
| 1961 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1961 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1962 | name = str_datetime |
|
1962 | name = str_datetime | |
| 1963 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
1963 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 1964 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
1964 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 1965 | figfile = self.getFilename(name) |
|
1965 | figfile = self.getFilename(name) | |
| 1966 |
|
1966 | |||
| 1967 | self.save(figpath=figpath, |
|
1967 | self.save(figpath=figpath, | |
| 1968 | figfile=figfile, |
|
1968 | figfile=figfile, | |
| 1969 | save=save, |
|
1969 | save=save, | |
| 1970 | ftp=ftp, |
|
1970 | ftp=ftp, | |
| 1971 | wr_period=wr_period, |
|
1971 | wr_period=wr_period, | |
| 1972 | thisDatetime=thisDatetime) |
|
1972 | thisDatetime=thisDatetime) | |
| 1973 |
|
1973 | |||
| 1974 |
|
1974 | |||
| 1975 | class NSMeteorDetection2Plot(Figure): |
|
1975 | class NSMeteorDetection2Plot(Figure): | |
| 1976 |
|
1976 | |||
| 1977 | isConfig = None |
|
1977 | isConfig = None | |
| 1978 | __nsubplots = None |
|
1978 | __nsubplots = None | |
| 1979 |
|
1979 | |||
| 1980 | WIDTHPROF = None |
|
1980 | WIDTHPROF = None | |
| 1981 | HEIGHTPROF = None |
|
1981 | HEIGHTPROF = None | |
| 1982 | PREFIX = 'nsm' |
|
1982 | PREFIX = 'nsm' | |
| 1983 |
|
1983 | |||
| 1984 | zminList = None |
|
1984 | zminList = None | |
| 1985 | zmaxList = None |
|
1985 | zmaxList = None | |
| 1986 | cmapList = None |
|
1986 | cmapList = None | |
| 1987 | titleList = None |
|
1987 | titleList = None | |
| 1988 | nPairs = None |
|
1988 | nPairs = None | |
| 1989 | nChannels = None |
|
1989 | nChannels = None | |
| 1990 | nParam = None |
|
1990 | nParam = None | |
| 1991 |
|
1991 | |||
| 1992 | def __init__(self, **kwargs): |
|
1992 | def __init__(self, **kwargs): | |
| 1993 | Figure.__init__(self, **kwargs) |
|
1993 | Figure.__init__(self, **kwargs) | |
| 1994 | self.isConfig = False |
|
1994 | self.isConfig = False | |
| 1995 | self.__nsubplots = 1 |
|
1995 | self.__nsubplots = 1 | |
| 1996 |
|
1996 | |||
| 1997 | self.WIDTH = 750 |
|
1997 | self.WIDTH = 750 | |
| 1998 | self.HEIGHT = 250 |
|
1998 | self.HEIGHT = 250 | |
| 1999 | self.WIDTHPROF = 120 |
|
1999 | self.WIDTHPROF = 120 | |
| 2000 | self.HEIGHTPROF = 0 |
|
2000 | self.HEIGHTPROF = 0 | |
| 2001 | self.counter_imagwr = 0 |
|
2001 | self.counter_imagwr = 0 | |
| 2002 |
|
2002 | |||
| 2003 | self.PLOT_CODE = SPEC_CODE |
|
2003 | self.PLOT_CODE = SPEC_CODE | |
| 2004 |
|
2004 | |||
| 2005 | self.FTP_WEI = None |
|
2005 | self.FTP_WEI = None | |
| 2006 | self.EXP_CODE = None |
|
2006 | self.EXP_CODE = None | |
| 2007 | self.SUB_EXP_CODE = None |
|
2007 | self.SUB_EXP_CODE = None | |
| 2008 | self.PLOT_POS = None |
|
2008 | self.PLOT_POS = None | |
| 2009 |
|
2009 | |||
| 2010 | self.__xfilter_ena = False |
|
2010 | self.__xfilter_ena = False | |
| 2011 | self.__yfilter_ena = False |
|
2011 | self.__yfilter_ena = False | |
| 2012 |
|
2012 | |||
| 2013 | def getSubplots(self): |
|
2013 | def getSubplots(self): | |
| 2014 |
|
2014 | |||
| 2015 | ncol = 3 |
|
2015 | ncol = 3 | |
| 2016 | nrow = int(numpy.ceil(self.nplots/3.0)) |
|
2016 | nrow = int(numpy.ceil(self.nplots/3.0)) | |
| 2017 |
|
2017 | |||
| 2018 | return nrow, ncol |
|
2018 | return nrow, ncol | |
| 2019 |
|
2019 | |||
| 2020 | def setup(self, id, nplots, wintitle, show=True): |
|
2020 | def setup(self, id, nplots, wintitle, show=True): | |
| 2021 |
|
2021 | |||
| 2022 | self.nplots = nplots |
|
2022 | self.nplots = nplots | |
| 2023 |
|
2023 | |||
| 2024 | ncolspan = 1 |
|
2024 | ncolspan = 1 | |
| 2025 | colspan = 1 |
|
2025 | colspan = 1 | |
| 2026 |
|
2026 | |||
| 2027 | self.createFigure(id = id, |
|
2027 | self.createFigure(id = id, | |
| 2028 | wintitle = wintitle, |
|
2028 | wintitle = wintitle, | |
| 2029 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
2029 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 2030 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
2030 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 2031 | show=show) |
|
2031 | show=show) | |
| 2032 |
|
2032 | |||
| 2033 | nrow, ncol = self.getSubplots() |
|
2033 | nrow, ncol = self.getSubplots() | |
| 2034 |
|
2034 | |||
| 2035 | counter = 0 |
|
2035 | counter = 0 | |
| 2036 | for y in range(nrow): |
|
2036 | for y in range(nrow): | |
| 2037 | for x in range(ncol): |
|
2037 | for x in range(ncol): | |
| 2038 |
|
2038 | |||
| 2039 | if counter >= self.nplots: |
|
2039 | if counter >= self.nplots: | |
| 2040 | break |
|
2040 | break | |
| 2041 |
|
2041 | |||
| 2042 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
2042 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 2043 |
|
2043 | |||
| 2044 | counter += 1 |
|
2044 | counter += 1 | |
| 2045 |
|
2045 | |||
| 2046 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
2046 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 2047 | xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None, |
|
2047 | xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None, | |
| 2048 | vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA', |
|
2048 | vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA', | |
| 2049 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
2049 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 2050 | server=None, folder=None, username=None, password=None, |
|
2050 | server=None, folder=None, username=None, password=None, | |
| 2051 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
2051 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
| 2052 | xaxis="frequency"): |
|
2052 | xaxis="frequency"): | |
| 2053 |
|
2053 | |||
| 2054 | """ |
|
2054 | """ | |
| 2055 |
|
2055 | |||
| 2056 | Input: |
|
2056 | Input: | |
| 2057 | dataOut : |
|
2057 | dataOut : | |
| 2058 | id : |
|
2058 | id : | |
| 2059 | wintitle : |
|
2059 | wintitle : | |
| 2060 | channelList : |
|
2060 | channelList : | |
| 2061 | showProfile : |
|
2061 | showProfile : | |
| 2062 | xmin : None, |
|
2062 | xmin : None, | |
| 2063 | xmax : None, |
|
2063 | xmax : None, | |
| 2064 | ymin : None, |
|
2064 | ymin : None, | |
| 2065 | ymax : None, |
|
2065 | ymax : None, | |
| 2066 | zmin : None, |
|
2066 | zmin : None, | |
| 2067 | zmax : None |
|
2067 | zmax : None | |
| 2068 | """ |
|
2068 | """ | |
| 2069 | #Rebuild matrix |
|
2069 | #Rebuild matrix | |
| 2070 | utctime = dataOut.data_param[0,0] |
|
2070 | utctime = dataOut.data_param[0,0] | |
| 2071 | cmet = dataOut.data_param[:,1].astype(int) |
|
2071 | cmet = dataOut.data_param[:,1].astype(int) | |
| 2072 | tmet = dataOut.data_param[:,2].astype(int) |
|
2072 | tmet = dataOut.data_param[:,2].astype(int) | |
| 2073 | hmet = dataOut.data_param[:,3].astype(int) |
|
2073 | hmet = dataOut.data_param[:,3].astype(int) | |
| 2074 |
|
2074 | |||
| 2075 | nParam = 3 |
|
2075 | nParam = 3 | |
| 2076 | nChan = len(dataOut.groupList) |
|
2076 | nChan = len(dataOut.groupList) | |
| 2077 | x = dataOut.abscissaList |
|
2077 | x = dataOut.abscissaList | |
| 2078 | y = dataOut.heightList |
|
2078 | y = dataOut.heightList | |
| 2079 |
|
2079 | |||
| 2080 | z = numpy.full((nChan, nParam, y.size, x.size - 1),numpy.nan) |
|
2080 | z = numpy.full((nChan, nParam, y.size, x.size - 1),numpy.nan) | |
| 2081 | z[cmet,:,hmet,tmet] = dataOut.data_param[:,4:] |
|
2081 | z[cmet,:,hmet,tmet] = dataOut.data_param[:,4:] | |
| 2082 | z[:,0,:,:] = 10*numpy.log10(z[:,0,:,:]) #logarithmic scale |
|
2082 | z[:,0,:,:] = 10*numpy.log10(z[:,0,:,:]) #logarithmic scale | |
| 2083 | z = numpy.reshape(z, (nChan*nParam, y.size, x.size-1)) |
|
2083 | z = numpy.reshape(z, (nChan*nParam, y.size, x.size-1)) | |
| 2084 |
|
2084 | |||
| 2085 | xlabel = "Time (s)" |
|
2085 | xlabel = "Time (s)" | |
| 2086 | ylabel = "Range (km)" |
|
2086 | ylabel = "Range (km)" | |
| 2087 |
|
2087 | |||
| 2088 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) |
|
2088 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime) | |
| 2089 |
|
2089 | |||
| 2090 | if not self.isConfig: |
|
2090 | if not self.isConfig: | |
| 2091 |
|
2091 | |||
| 2092 | nplots = nParam*nChan |
|
2092 | nplots = nParam*nChan | |
| 2093 |
|
2093 | |||
| 2094 | self.setup(id=id, |
|
2094 | self.setup(id=id, | |
| 2095 | nplots=nplots, |
|
2095 | nplots=nplots, | |
| 2096 | wintitle=wintitle, |
|
2096 | wintitle=wintitle, | |
| 2097 | show=show) |
|
2097 | show=show) | |
| 2098 |
|
2098 | |||
| 2099 | if xmin is None: xmin = numpy.nanmin(x) |
|
2099 | if xmin is None: xmin = numpy.nanmin(x) | |
| 2100 | if xmax is None: xmax = numpy.nanmax(x) |
|
2100 | if xmax is None: xmax = numpy.nanmax(x) | |
| 2101 | if ymin is None: ymin = numpy.nanmin(y) |
|
2101 | if ymin is None: ymin = numpy.nanmin(y) | |
| 2102 | if ymax is None: ymax = numpy.nanmax(y) |
|
2102 | if ymax is None: ymax = numpy.nanmax(y) | |
| 2103 | if SNRmin is None: SNRmin = numpy.nanmin(z[0,:]) |
|
2103 | if SNRmin is None: SNRmin = numpy.nanmin(z[0,:]) | |
| 2104 | if SNRmax is None: SNRmax = numpy.nanmax(z[0,:]) |
|
2104 | if SNRmax is None: SNRmax = numpy.nanmax(z[0,:]) | |
| 2105 | if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:])) |
|
2105 | if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:])) | |
| 2106 | if vmin is None: vmin = -vmax |
|
2106 | if vmin is None: vmin = -vmax | |
| 2107 | if wmin is None: wmin = 0 |
|
2107 | if wmin is None: wmin = 0 | |
| 2108 | if wmax is None: wmax = 50 |
|
2108 | if wmax is None: wmax = 50 | |
| 2109 |
|
2109 | |||
| 2110 | self.nChannels = nChan |
|
2110 | self.nChannels = nChan | |
| 2111 |
|
2111 | |||
| 2112 | zminList = [] |
|
2112 | zminList = [] | |
| 2113 | zmaxList = [] |
|
2113 | zmaxList = [] | |
| 2114 | titleList = [] |
|
2114 | titleList = [] | |
| 2115 | cmapList = [] |
|
2115 | cmapList = [] | |
| 2116 | for i in range(self.nChannels): |
|
2116 | for i in range(self.nChannels): | |
| 2117 | strAux1 = "SNR Channel "+ str(i) |
|
2117 | strAux1 = "SNR Channel "+ str(i) | |
| 2118 | strAux2 = "Radial Velocity Channel "+ str(i) |
|
2118 | strAux2 = "Radial Velocity Channel "+ str(i) | |
| 2119 | strAux3 = "Spectral Width Channel "+ str(i) |
|
2119 | strAux3 = "Spectral Width Channel "+ str(i) | |
| 2120 |
|
2120 | |||
| 2121 | titleList = titleList + [strAux1,strAux2,strAux3] |
|
2121 | titleList = titleList + [strAux1,strAux2,strAux3] | |
| 2122 | cmapList = cmapList + ["jet","RdBu_r","jet"] |
|
2122 | cmapList = cmapList + ["jet","RdBu_r","jet"] | |
| 2123 | zminList = zminList + [SNRmin,vmin,wmin] |
|
2123 | zminList = zminList + [SNRmin,vmin,wmin] | |
| 2124 | zmaxList = zmaxList + [SNRmax,vmax,wmax] |
|
2124 | zmaxList = zmaxList + [SNRmax,vmax,wmax] | |
| 2125 |
|
2125 | |||
| 2126 | self.zminList = zminList |
|
2126 | self.zminList = zminList | |
| 2127 | self.zmaxList = zmaxList |
|
2127 | self.zmaxList = zmaxList | |
| 2128 | self.cmapList = cmapList |
|
2128 | self.cmapList = cmapList | |
| 2129 | self.titleList = titleList |
|
2129 | self.titleList = titleList | |
| 2130 |
|
2130 | |||
| 2131 | self.FTP_WEI = ftp_wei |
|
2131 | self.FTP_WEI = ftp_wei | |
| 2132 | self.EXP_CODE = exp_code |
|
2132 | self.EXP_CODE = exp_code | |
| 2133 | self.SUB_EXP_CODE = sub_exp_code |
|
2133 | self.SUB_EXP_CODE = sub_exp_code | |
| 2134 | self.PLOT_POS = plot_pos |
|
2134 | self.PLOT_POS = plot_pos | |
| 2135 |
|
2135 | |||
| 2136 | self.isConfig = True |
|
2136 | self.isConfig = True | |
| 2137 |
|
2137 | |||
| 2138 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
2138 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 2139 |
|
2139 | |||
| 2140 | for i in range(self.nplots): |
|
2140 | for i in range(self.nplots): | |
| 2141 | title = self.titleList[i] + ": " +str_datetime |
|
2141 | title = self.titleList[i] + ": " +str_datetime | |
| 2142 | axes = self.axesList[i] |
|
2142 | axes = self.axesList[i] | |
| 2143 | axes.pcolor(x, y, z[i,:].T, |
|
2143 | axes.pcolor(x, y, z[i,:].T, | |
| 2144 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i], |
|
2144 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i], | |
| 2145 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='') |
|
2145 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='') | |
| 2146 | self.draw() |
|
2146 | self.draw() | |
| 2147 |
|
2147 | |||
| 2148 | if figfile == None: |
|
2148 | if figfile == None: | |
| 2149 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
2149 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 2150 | name = str_datetime |
|
2150 | name = str_datetime | |
| 2151 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
2151 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 2152 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
2152 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 2153 | figfile = self.getFilename(name) |
|
2153 | figfile = self.getFilename(name) | |
| 2154 |
|
2154 | |||
| 2155 | self.save(figpath=figpath, |
|
2155 | self.save(figpath=figpath, | |
| 2156 | figfile=figfile, |
|
2156 | figfile=figfile, | |
| 2157 | save=save, |
|
2157 | save=save, | |
| 2158 | ftp=ftp, |
|
2158 | ftp=ftp, | |
| 2159 | wr_period=wr_period, |
|
2159 | wr_period=wr_period, | |
| 2160 | thisDatetime=thisDatetime) |
|
2160 | thisDatetime=thisDatetime) | |
| @@ -1,1611 +1,1605 | |||||
| 1 | ''' |
|
1 | ''' | |
| 2 | Created on Jul 9, 2014 |
|
2 | Created on Jul 9, 2014 | |
| 3 |
|
3 | |||
| 4 | @author: roj-idl71 |
|
4 | @author: roj-idl71 | |
| 5 | ''' |
|
5 | ''' | |
| 6 | import os |
|
6 | import os | |
| 7 | import datetime |
|
7 | import datetime | |
| 8 | import numpy |
|
8 | import numpy | |
| 9 |
|
9 | |||
| 10 | import matplotlib.pyplot as plt |
|
10 | import matplotlib.pyplot as plt | |
| 11 |
|
11 | |||
| 12 | from figure import Figure, isRealtime, isTimeInHourRange |
|
12 | from figure import Figure, isRealtime, isTimeInHourRange | |
| 13 | from plotting_codes import * |
|
13 | from plotting_codes import * | |
| 14 | from matplotlib.pyplot import savefig |
|
14 | from matplotlib.pyplot import savefig | |
| 15 |
|
15 | |||
| 16 | class SpectraPlot(Figure): |
|
16 | class SpectraPlot(Figure): | |
| 17 |
|
17 | |||
| 18 | isConfig = None |
|
18 | isConfig = None | |
| 19 | __nsubplots = None |
|
19 | __nsubplots = None | |
| 20 |
|
20 | |||
| 21 | WIDTHPROF = None |
|
21 | WIDTHPROF = None | |
| 22 | HEIGHTPROF = None |
|
22 | HEIGHTPROF = None | |
| 23 | PREFIX = 'spc' |
|
23 | PREFIX = 'spc' | |
| 24 |
|
24 | |||
| 25 | def __init__(self, **kwargs): |
|
25 | def __init__(self, **kwargs): | |
| 26 | Figure.__init__(self, **kwargs) |
|
26 | Figure.__init__(self, **kwargs) | |
| 27 | self.isConfig = False |
|
27 | self.isConfig = False | |
| 28 | self.__nsubplots = 1 |
|
28 | self.__nsubplots = 1 | |
| 29 |
|
29 | |||
| 30 | self.WIDTH = 300 |
|
30 | self.WIDTH = 300 | |
| 31 | self.HEIGHT = 300 |
|
31 | self.HEIGHT = 300 | |
| 32 | self.WIDTHPROF = 120 |
|
32 | self.WIDTHPROF = 120 | |
| 33 | self.HEIGHTPROF = 0 |
|
33 | self.HEIGHTPROF = 0 | |
| 34 | self.counter_imagwr = 0 |
|
34 | self.counter_imagwr = 0 | |
| 35 |
|
35 | |||
| 36 | self.PLOT_CODE = SPEC_CODE |
|
36 | self.PLOT_CODE = SPEC_CODE | |
| 37 |
|
37 | |||
| 38 | self.FTP_WEI = None |
|
38 | self.FTP_WEI = None | |
| 39 | self.EXP_CODE = None |
|
39 | self.EXP_CODE = None | |
| 40 | self.SUB_EXP_CODE = None |
|
40 | self.SUB_EXP_CODE = None | |
| 41 | self.PLOT_POS = None |
|
41 | self.PLOT_POS = None | |
| 42 |
|
42 | |||
| 43 | self.__xfilter_ena = False |
|
43 | self.__xfilter_ena = False | |
| 44 | self.__yfilter_ena = False |
|
44 | self.__yfilter_ena = False | |
| 45 |
|
45 | |||
| 46 | self.indice=1 |
|
46 | self.indice=1 | |
| 47 |
|
47 | |||
| 48 | def getSubplots(self): |
|
48 | def getSubplots(self): | |
| 49 |
|
49 | |||
| 50 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
50 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
| 51 | nrow = int(self.nplots*1./ncol + 0.9) |
|
51 | nrow = int(self.nplots*1./ncol + 0.9) | |
| 52 |
|
52 | |||
| 53 | return nrow, ncol |
|
53 | return nrow, ncol | |
| 54 |
|
54 | |||
| 55 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
55 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 56 |
|
56 | |||
| 57 | self.__showprofile = showprofile |
|
57 | self.__showprofile = showprofile | |
| 58 | self.nplots = nplots |
|
58 | self.nplots = nplots | |
| 59 |
|
59 | |||
| 60 | ncolspan = 1 |
|
60 | ncolspan = 1 | |
| 61 | colspan = 1 |
|
61 | colspan = 1 | |
| 62 | if showprofile: |
|
62 | if showprofile: | |
| 63 | ncolspan = 3 |
|
63 | ncolspan = 3 | |
| 64 | colspan = 2 |
|
64 | colspan = 2 | |
| 65 | self.__nsubplots = 2 |
|
65 | self.__nsubplots = 2 | |
| 66 |
|
66 | |||
| 67 | self.createFigure(id = id, |
|
67 | self.createFigure(id = id, | |
| 68 | wintitle = wintitle, |
|
68 | wintitle = wintitle, | |
| 69 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
69 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 70 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
70 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 71 | show=show) |
|
71 | show=show) | |
| 72 |
|
72 | |||
| 73 | nrow, ncol = self.getSubplots() |
|
73 | nrow, ncol = self.getSubplots() | |
| 74 |
|
74 | |||
| 75 | counter = 0 |
|
75 | counter = 0 | |
| 76 | for y in range(nrow): |
|
76 | for y in range(nrow): | |
| 77 | for x in range(ncol): |
|
77 | for x in range(ncol): | |
| 78 |
|
78 | |||
| 79 | if counter >= self.nplots: |
|
79 | if counter >= self.nplots: | |
| 80 | break |
|
80 | break | |
| 81 |
|
81 | |||
| 82 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
82 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 83 |
|
83 | |||
| 84 | if showprofile: |
|
84 | if showprofile: | |
| 85 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
85 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 86 |
|
86 | |||
| 87 | counter += 1 |
|
87 | counter += 1 | |
| 88 |
|
88 | |||
| 89 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, |
|
89 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
| 90 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
90 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 91 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
91 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 92 | server=None, folder=None, username=None, password=None, |
|
92 | server=None, folder=None, username=None, password=None, | |
| 93 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
93 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
| 94 | xaxis="frequency", colormap='jet', normFactor=None): |
|
94 | xaxis="frequency", colormap='jet', normFactor=None): | |
| 95 |
|
95 | |||
| 96 | """ |
|
96 | """ | |
| 97 |
|
97 | |||
| 98 | Input: |
|
98 | Input: | |
| 99 | dataOut : |
|
99 | dataOut : | |
| 100 | id : |
|
100 | id : | |
| 101 | wintitle : |
|
101 | wintitle : | |
| 102 | channelList : |
|
102 | channelList : | |
| 103 | showProfile : |
|
103 | showProfile : | |
| 104 | xmin : None, |
|
104 | xmin : None, | |
| 105 | xmax : None, |
|
105 | xmax : None, | |
| 106 | ymin : None, |
|
106 | ymin : None, | |
| 107 | ymax : None, |
|
107 | ymax : None, | |
| 108 | zmin : None, |
|
108 | zmin : None, | |
| 109 | zmax : None |
|
109 | zmax : None | |
| 110 | """ |
|
110 | """ | |
| 111 | if realtime: |
|
111 | if realtime: | |
| 112 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
112 | if not(isRealtime(utcdatatime = dataOut.utctime)): | |
| 113 | print 'Skipping this plot function' |
|
113 | print 'Skipping this plot function' | |
| 114 | return |
|
114 | return | |
| 115 |
|
115 | |||
| 116 | if channelList == None: |
|
116 | if channelList == None: | |
| 117 | channelIndexList = dataOut.channelIndexList |
|
117 | channelIndexList = dataOut.channelIndexList | |
| 118 | else: |
|
118 | else: | |
| 119 | channelIndexList = [] |
|
119 | channelIndexList = [] | |
| 120 | for channel in channelList: |
|
120 | for channel in channelList: | |
| 121 | if channel not in dataOut.channelList: |
|
121 | if channel not in dataOut.channelList: | |
| 122 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel |
|
122 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel | |
| 123 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
123 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 124 |
|
124 | |||
| 125 | if normFactor is None: |
|
125 | if normFactor is None: | |
| 126 | factor = dataOut.normFactor |
|
126 | factor = dataOut.normFactor | |
| 127 | else: |
|
127 | else: | |
| 128 | factor = normFactor |
|
128 | factor = normFactor | |
| 129 | if xaxis == "frequency": |
|
129 | if xaxis == "frequency": | |
| 130 | x = dataOut.getFreqRange(1)/1000. |
|
130 | x = dataOut.getFreqRange(1)/1000. | |
| 131 | print 'FRECUENCIA MAXIMA', numpy.amax(x) |
|
|||
| 132 | asfasfasdfaf |
|
|||
| 133 | print '#######################################################' |
|
|||
| 134 | print 'xlen', len(x) |
|
|||
| 135 | print x |
|
|||
| 136 | print '#######################################################' |
|
|||
| 137 | xlabel = "Frequency (kHz)" |
|
131 | xlabel = "Frequency (kHz)" | |
| 138 |
|
132 | |||
| 139 | elif xaxis == "time": |
|
133 | elif xaxis == "time": | |
| 140 | x = dataOut.getAcfRange(1) |
|
134 | x = dataOut.getAcfRange(1) | |
| 141 | xlabel = "Time (ms)" |
|
135 | xlabel = "Time (ms)" | |
| 142 |
|
136 | |||
| 143 | else: |
|
137 | else: | |
| 144 | x = dataOut.getVelRange(1) |
|
138 | x = dataOut.getVelRange(1) | |
| 145 | xlabel = "Velocity (m/s)" |
|
139 | xlabel = "Velocity (m/s)" | |
| 146 |
|
140 | |||
| 147 | ylabel = "Range (Km)" |
|
141 | ylabel = "Range (Km)" | |
| 148 |
|
142 | |||
| 149 | y = dataOut.getHeiRange() |
|
143 | y = dataOut.getHeiRange() | |
| 150 |
|
144 | |||
| 151 | z = dataOut.data_spc/factor |
|
145 | z = dataOut.data_spc/factor | |
| 152 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
146 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 153 | zdB = 10*numpy.log10(z) |
|
147 | zdB = 10*numpy.log10(z) | |
| 154 |
|
148 | |||
| 155 | avg = numpy.average(z, axis=1) |
|
149 | avg = numpy.average(z, axis=1) | |
| 156 | avgdB = 10*numpy.log10(avg) |
|
150 | avgdB = 10*numpy.log10(avg) | |
| 157 |
|
151 | |||
| 158 | noise = dataOut.getNoise()/factor |
|
152 | noise = dataOut.getNoise()/factor | |
| 159 | noisedB = 10*numpy.log10(noise) |
|
153 | noisedB = 10*numpy.log10(noise) | |
| 160 |
|
154 | |||
| 161 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
155 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 162 | title = wintitle + " Spectra" |
|
156 | title = wintitle + " Spectra" | |
| 163 |
|
157 | |||
| 164 |
|
158 | |||
| 165 |
|
159 | |||
| 166 | print 'len de X',len(x), numpy.shape(x), 'len de spc line',len(dataOut.data_spc[1,:,15]), numpy.shape(dataOut.data_spc) |
|
160 | print 'len de X',len(x), numpy.shape(x), 'len de spc line',len(dataOut.data_spc[1,:,15]), numpy.shape(dataOut.data_spc) | |
| 167 | print 'Altura:', y[0], y[1], y[13], y[14], y[10] |
|
161 | print 'Altura:', y[0], y[1], y[13], y[14], y[10] | |
| 168 | #a=z[1,:,15] |
|
162 | #a=z[1,:,15] | |
| 169 |
|
163 | |||
| 170 | # fig = plt.figure(10+self.indice) |
|
164 | # fig = plt.figure(10+self.indice) | |
| 171 | # plt.plot( x[0:128], zdB[0,:,10] ) |
|
165 | # plt.plot( x[0:128], zdB[0,:,10] ) | |
| 172 | # plt.axis([-12, 12, 15, 50]) |
|
166 | # plt.axis([-12, 12, 15, 50]) | |
| 173 | # plt.title(" %s" %( '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))) ) |
|
167 | # plt.title(" %s" %( '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))) ) | |
| 174 | # plt.ylabel('Intensidad [dB]') |
|
168 | # plt.ylabel('Intensidad [dB]') | |
| 175 | # plt.xlabel('Velocidad [m/s]') |
|
169 | # plt.xlabel('Velocidad [m/s]') | |
| 176 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) |
|
170 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) | |
| 177 | # |
|
171 | # | |
| 178 | # plt.show() |
|
172 | # plt.show() | |
| 179 | # |
|
173 | # | |
| 180 | # self.indice=self.indice+1 |
|
174 | # self.indice=self.indice+1 | |
| 181 |
|
175 | |||
| 182 |
|
176 | |||
| 183 |
|
177 | |||
| 184 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
178 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 185 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
179 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 186 |
|
180 | |||
| 187 | if not self.isConfig: |
|
181 | if not self.isConfig: | |
| 188 |
|
182 | |||
| 189 | nplots = len(channelIndexList) |
|
183 | nplots = len(channelIndexList) | |
| 190 |
|
184 | |||
| 191 | self.setup(id=id, |
|
185 | self.setup(id=id, | |
| 192 | nplots=nplots, |
|
186 | nplots=nplots, | |
| 193 | wintitle=wintitle, |
|
187 | wintitle=wintitle, | |
| 194 | showprofile=showprofile, |
|
188 | showprofile=showprofile, | |
| 195 | show=show) |
|
189 | show=show) | |
| 196 |
|
190 | |||
| 197 | if xmin == None: xmin = numpy.nanmin(x) |
|
191 | if xmin == None: xmin = numpy.nanmin(x) | |
| 198 | if xmax == None: xmax = numpy.nanmax(x) |
|
192 | if xmax == None: xmax = numpy.nanmax(x) | |
| 199 | if ymin == None: ymin = numpy.nanmin(y) |
|
193 | if ymin == None: ymin = numpy.nanmin(y) | |
| 200 | if ymax == None: ymax = numpy.nanmax(y) |
|
194 | if ymax == None: ymax = numpy.nanmax(y) | |
| 201 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
195 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 202 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
196 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 203 |
|
197 | |||
| 204 | self.FTP_WEI = ftp_wei |
|
198 | self.FTP_WEI = ftp_wei | |
| 205 | self.EXP_CODE = exp_code |
|
199 | self.EXP_CODE = exp_code | |
| 206 | self.SUB_EXP_CODE = sub_exp_code |
|
200 | self.SUB_EXP_CODE = sub_exp_code | |
| 207 | self.PLOT_POS = plot_pos |
|
201 | self.PLOT_POS = plot_pos | |
| 208 |
|
202 | |||
| 209 | self.isConfig = True |
|
203 | self.isConfig = True | |
| 210 |
|
204 | |||
| 211 | self.setWinTitle(title) |
|
205 | self.setWinTitle(title) | |
| 212 |
|
206 | |||
| 213 | for i in range(self.nplots): |
|
207 | for i in range(self.nplots): | |
| 214 | index = channelIndexList[i] |
|
208 | index = channelIndexList[i] | |
| 215 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
209 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 216 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) |
|
210 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) | |
| 217 | if len(dataOut.beam.codeList) != 0: |
|
211 | if len(dataOut.beam.codeList) != 0: | |
| 218 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) |
|
212 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) | |
| 219 |
|
213 | |||
| 220 | axes = self.axesList[i*self.__nsubplots] |
|
214 | axes = self.axesList[i*self.__nsubplots] | |
| 221 | axes.pcolor(x, y, zdB[index,:,:], |
|
215 | axes.pcolor(x, y, zdB[index,:,:], | |
| 222 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
216 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 223 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, |
|
217 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, | |
| 224 | ticksize=9, cblabel='') |
|
218 | ticksize=9, cblabel='') | |
| 225 |
|
219 | |||
| 226 | if self.__showprofile: |
|
220 | if self.__showprofile: | |
| 227 | axes = self.axesList[i*self.__nsubplots +1] |
|
221 | axes = self.axesList[i*self.__nsubplots +1] | |
| 228 | axes.pline(avgdB[index,:], y, |
|
222 | axes.pline(avgdB[index,:], y, | |
| 229 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
223 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 230 | xlabel='dB', ylabel='', title='', |
|
224 | xlabel='dB', ylabel='', title='', | |
| 231 | ytick_visible=False, |
|
225 | ytick_visible=False, | |
| 232 | grid='x') |
|
226 | grid='x') | |
| 233 |
|
227 | |||
| 234 | noiseline = numpy.repeat(noisedB[index], len(y)) |
|
228 | noiseline = numpy.repeat(noisedB[index], len(y)) | |
| 235 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
229 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) | |
| 236 |
|
230 | |||
| 237 | self.draw() |
|
231 | self.draw() | |
| 238 |
|
232 | |||
| 239 | if figfile == None: |
|
233 | if figfile == None: | |
| 240 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
234 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 241 | name = str_datetime |
|
235 | name = str_datetime | |
| 242 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
236 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 243 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) |
|
237 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
| 244 | figfile = self.getFilename(name) |
|
238 | figfile = self.getFilename(name) | |
| 245 |
|
239 | |||
| 246 | self.save(figpath=figpath, |
|
240 | self.save(figpath=figpath, | |
| 247 | figfile=figfile, |
|
241 | figfile=figfile, | |
| 248 | save=save, |
|
242 | save=save, | |
| 249 | ftp=ftp, |
|
243 | ftp=ftp, | |
| 250 | wr_period=wr_period, |
|
244 | wr_period=wr_period, | |
| 251 | thisDatetime=thisDatetime) |
|
245 | thisDatetime=thisDatetime) | |
| 252 |
|
246 | |||
| 253 |
|
247 | |||
| 254 | class CrossSpectraPlot(Figure): |
|
248 | class CrossSpectraPlot(Figure): | |
| 255 |
|
249 | |||
| 256 | isConfig = None |
|
250 | isConfig = None | |
| 257 | __nsubplots = None |
|
251 | __nsubplots = None | |
| 258 |
|
252 | |||
| 259 | WIDTH = None |
|
253 | WIDTH = None | |
| 260 | HEIGHT = None |
|
254 | HEIGHT = None | |
| 261 | WIDTHPROF = None |
|
255 | WIDTHPROF = None | |
| 262 | HEIGHTPROF = None |
|
256 | HEIGHTPROF = None | |
| 263 | PREFIX = 'cspc' |
|
257 | PREFIX = 'cspc' | |
| 264 |
|
258 | |||
| 265 | def __init__(self, **kwargs): |
|
259 | def __init__(self, **kwargs): | |
| 266 | Figure.__init__(self, **kwargs) |
|
260 | Figure.__init__(self, **kwargs) | |
| 267 | self.isConfig = False |
|
261 | self.isConfig = False | |
| 268 | self.__nsubplots = 4 |
|
262 | self.__nsubplots = 4 | |
| 269 | self.counter_imagwr = 0 |
|
263 | self.counter_imagwr = 0 | |
| 270 | self.WIDTH = 250 |
|
264 | self.WIDTH = 250 | |
| 271 | self.HEIGHT = 250 |
|
265 | self.HEIGHT = 250 | |
| 272 | self.WIDTHPROF = 0 |
|
266 | self.WIDTHPROF = 0 | |
| 273 | self.HEIGHTPROF = 0 |
|
267 | self.HEIGHTPROF = 0 | |
| 274 |
|
268 | |||
| 275 | self.PLOT_CODE = CROSS_CODE |
|
269 | self.PLOT_CODE = CROSS_CODE | |
| 276 | self.FTP_WEI = None |
|
270 | self.FTP_WEI = None | |
| 277 | self.EXP_CODE = None |
|
271 | self.EXP_CODE = None | |
| 278 | self.SUB_EXP_CODE = None |
|
272 | self.SUB_EXP_CODE = None | |
| 279 | self.PLOT_POS = None |
|
273 | self.PLOT_POS = None | |
| 280 |
|
274 | |||
| 281 | self.indice=0 |
|
275 | self.indice=0 | |
| 282 |
|
276 | |||
| 283 | def getSubplots(self): |
|
277 | def getSubplots(self): | |
| 284 |
|
278 | |||
| 285 | ncol = 4 |
|
279 | ncol = 4 | |
| 286 | nrow = self.nplots |
|
280 | nrow = self.nplots | |
| 287 |
|
281 | |||
| 288 | return nrow, ncol |
|
282 | return nrow, ncol | |
| 289 |
|
283 | |||
| 290 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
284 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 291 |
|
285 | |||
| 292 | self.__showprofile = showprofile |
|
286 | self.__showprofile = showprofile | |
| 293 | self.nplots = nplots |
|
287 | self.nplots = nplots | |
| 294 |
|
288 | |||
| 295 | ncolspan = 1 |
|
289 | ncolspan = 1 | |
| 296 | colspan = 1 |
|
290 | colspan = 1 | |
| 297 |
|
291 | |||
| 298 | self.createFigure(id = id, |
|
292 | self.createFigure(id = id, | |
| 299 | wintitle = wintitle, |
|
293 | wintitle = wintitle, | |
| 300 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
294 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 301 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
295 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 302 | show=True) |
|
296 | show=True) | |
| 303 |
|
297 | |||
| 304 | nrow, ncol = self.getSubplots() |
|
298 | nrow, ncol = self.getSubplots() | |
| 305 |
|
299 | |||
| 306 | counter = 0 |
|
300 | counter = 0 | |
| 307 | for y in range(nrow): |
|
301 | for y in range(nrow): | |
| 308 | for x in range(ncol): |
|
302 | for x in range(ncol): | |
| 309 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
303 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 310 |
|
304 | |||
| 311 | counter += 1 |
|
305 | counter += 1 | |
| 312 |
|
306 | |||
| 313 | def run(self, dataOut, id, wintitle="", pairsList=None, |
|
307 | def run(self, dataOut, id, wintitle="", pairsList=None, | |
| 314 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
308 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 315 | coh_min=None, coh_max=None, phase_min=None, phase_max=None, |
|
309 | coh_min=None, coh_max=None, phase_min=None, phase_max=None, | |
| 316 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, |
|
310 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, | |
| 317 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
311 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, | |
| 318 | server=None, folder=None, username=None, password=None, |
|
312 | server=None, folder=None, username=None, password=None, | |
| 319 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, |
|
313 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, | |
| 320 | xaxis='frequency'): |
|
314 | xaxis='frequency'): | |
| 321 |
|
315 | |||
| 322 | """ |
|
316 | """ | |
| 323 |
|
317 | |||
| 324 | Input: |
|
318 | Input: | |
| 325 | dataOut : |
|
319 | dataOut : | |
| 326 | id : |
|
320 | id : | |
| 327 | wintitle : |
|
321 | wintitle : | |
| 328 | channelList : |
|
322 | channelList : | |
| 329 | showProfile : |
|
323 | showProfile : | |
| 330 | xmin : None, |
|
324 | xmin : None, | |
| 331 | xmax : None, |
|
325 | xmax : None, | |
| 332 | ymin : None, |
|
326 | ymin : None, | |
| 333 | ymax : None, |
|
327 | ymax : None, | |
| 334 | zmin : None, |
|
328 | zmin : None, | |
| 335 | zmax : None |
|
329 | zmax : None | |
| 336 | """ |
|
330 | """ | |
| 337 |
|
331 | |||
| 338 | if pairsList == None: |
|
332 | if pairsList == None: | |
| 339 | pairsIndexList = dataOut.pairsIndexList |
|
333 | pairsIndexList = dataOut.pairsIndexList | |
| 340 | else: |
|
334 | else: | |
| 341 | pairsIndexList = [] |
|
335 | pairsIndexList = [] | |
| 342 | for pair in pairsList: |
|
336 | for pair in pairsList: | |
| 343 | if pair not in dataOut.pairsList: |
|
337 | if pair not in dataOut.pairsList: | |
| 344 | raise ValueError, "Pair %s is not in dataOut.pairsList" %str(pair) |
|
338 | raise ValueError, "Pair %s is not in dataOut.pairsList" %str(pair) | |
| 345 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
339 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 346 |
|
340 | |||
| 347 | if not pairsIndexList: |
|
341 | if not pairsIndexList: | |
| 348 | return |
|
342 | return | |
| 349 |
|
343 | |||
| 350 | if len(pairsIndexList) > 4: |
|
344 | if len(pairsIndexList) > 4: | |
| 351 | pairsIndexList = pairsIndexList[0:4] |
|
345 | pairsIndexList = pairsIndexList[0:4] | |
| 352 |
|
346 | |||
| 353 | if normFactor is None: |
|
347 | if normFactor is None: | |
| 354 | factor = dataOut.normFactor |
|
348 | factor = dataOut.normFactor | |
| 355 | else: |
|
349 | else: | |
| 356 | factor = normFactor |
|
350 | factor = normFactor | |
| 357 | x = dataOut.getVelRange(1) |
|
351 | x = dataOut.getVelRange(1) | |
| 358 | y = dataOut.getHeiRange() |
|
352 | y = dataOut.getHeiRange() | |
| 359 | z = dataOut.data_spc[:,:,:]/factor |
|
353 | z = dataOut.data_spc[:,:,:]/factor | |
| 360 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
354 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 361 |
|
355 | |||
| 362 | noise = dataOut.noise/factor |
|
356 | noise = dataOut.noise/factor | |
| 363 |
|
357 | |||
| 364 | zdB = 10*numpy.log10(z) |
|
358 | zdB = 10*numpy.log10(z) | |
| 365 | noisedB = 10*numpy.log10(noise) |
|
359 | noisedB = 10*numpy.log10(noise) | |
| 366 |
|
360 | |||
| 367 | if coh_min == None: |
|
361 | if coh_min == None: | |
| 368 | coh_min = 0.0 |
|
362 | coh_min = 0.0 | |
| 369 | if coh_max == None: |
|
363 | if coh_max == None: | |
| 370 | coh_max = 1.0 |
|
364 | coh_max = 1.0 | |
| 371 |
|
365 | |||
| 372 | if phase_min == None: |
|
366 | if phase_min == None: | |
| 373 | phase_min = -180 |
|
367 | phase_min = -180 | |
| 374 | if phase_max == None: |
|
368 | if phase_max == None: | |
| 375 | phase_max = 180 |
|
369 | phase_max = 180 | |
| 376 |
|
370 | |||
| 377 | #thisDatetime = dataOut.datatime |
|
371 | #thisDatetime = dataOut.datatime | |
| 378 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
372 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 379 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
373 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 380 | # xlabel = "Velocity (m/s)" |
|
374 | # xlabel = "Velocity (m/s)" | |
| 381 | ylabel = "Range (Km)" |
|
375 | ylabel = "Range (Km)" | |
| 382 |
|
376 | |||
| 383 | if xaxis == "frequency": |
|
377 | if xaxis == "frequency": | |
| 384 | x = dataOut.getFreqRange(1)/1000. |
|
378 | x = dataOut.getFreqRange(1)/1000. | |
| 385 | xlabel = "Frequency (kHz)" |
|
379 | xlabel = "Frequency (kHz)" | |
| 386 |
|
380 | |||
| 387 | elif xaxis == "time": |
|
381 | elif xaxis == "time": | |
| 388 | x = dataOut.getAcfRange(1) |
|
382 | x = dataOut.getAcfRange(1) | |
| 389 | xlabel = "Time (ms)" |
|
383 | xlabel = "Time (ms)" | |
| 390 |
|
384 | |||
| 391 | else: |
|
385 | else: | |
| 392 | x = dataOut.getVelRange(1) |
|
386 | x = dataOut.getVelRange(1) | |
| 393 | xlabel = "Velocity (m/s)" |
|
387 | xlabel = "Velocity (m/s)" | |
| 394 |
|
388 | |||
| 395 | if not self.isConfig: |
|
389 | if not self.isConfig: | |
| 396 |
|
390 | |||
| 397 | nplots = len(pairsIndexList) |
|
391 | nplots = len(pairsIndexList) | |
| 398 |
|
392 | |||
| 399 | self.setup(id=id, |
|
393 | self.setup(id=id, | |
| 400 | nplots=nplots, |
|
394 | nplots=nplots, | |
| 401 | wintitle=wintitle, |
|
395 | wintitle=wintitle, | |
| 402 | showprofile=False, |
|
396 | showprofile=False, | |
| 403 | show=show) |
|
397 | show=show) | |
| 404 |
|
398 | |||
| 405 | avg = numpy.abs(numpy.average(z, axis=1)) |
|
399 | avg = numpy.abs(numpy.average(z, axis=1)) | |
| 406 | avgdB = 10*numpy.log10(avg) |
|
400 | avgdB = 10*numpy.log10(avg) | |
| 407 |
|
401 | |||
| 408 | if xmin == None: xmin = numpy.nanmin(x) |
|
402 | if xmin == None: xmin = numpy.nanmin(x) | |
| 409 | if xmax == None: xmax = numpy.nanmax(x) |
|
403 | if xmax == None: xmax = numpy.nanmax(x) | |
| 410 | if ymin == None: ymin = numpy.nanmin(y) |
|
404 | if ymin == None: ymin = numpy.nanmin(y) | |
| 411 | if ymax == None: ymax = numpy.nanmax(y) |
|
405 | if ymax == None: ymax = numpy.nanmax(y) | |
| 412 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
406 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 413 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
407 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 414 |
|
408 | |||
| 415 | self.FTP_WEI = ftp_wei |
|
409 | self.FTP_WEI = ftp_wei | |
| 416 | self.EXP_CODE = exp_code |
|
410 | self.EXP_CODE = exp_code | |
| 417 | self.SUB_EXP_CODE = sub_exp_code |
|
411 | self.SUB_EXP_CODE = sub_exp_code | |
| 418 | self.PLOT_POS = plot_pos |
|
412 | self.PLOT_POS = plot_pos | |
| 419 |
|
413 | |||
| 420 | self.isConfig = True |
|
414 | self.isConfig = True | |
| 421 |
|
415 | |||
| 422 | self.setWinTitle(title) |
|
416 | self.setWinTitle(title) | |
| 423 |
|
417 | |||
| 424 |
|
418 | |||
| 425 | for i in range(self.nplots): |
|
419 | for i in range(self.nplots): | |
| 426 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
420 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 427 |
|
421 | |||
| 428 | chan_index0 = dataOut.channelList.index(pair[0]) |
|
422 | chan_index0 = dataOut.channelList.index(pair[0]) | |
| 429 | chan_index1 = dataOut.channelList.index(pair[1]) |
|
423 | chan_index1 = dataOut.channelList.index(pair[1]) | |
| 430 |
|
424 | |||
| 431 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
425 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
| 432 | title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime) |
|
426 | title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime) | |
| 433 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor) |
|
427 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor) | |
| 434 | axes0 = self.axesList[i*self.__nsubplots] |
|
428 | axes0 = self.axesList[i*self.__nsubplots] | |
| 435 | axes0.pcolor(x, y, zdB, |
|
429 | axes0.pcolor(x, y, zdB, | |
| 436 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
430 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 437 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
431 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 438 | ticksize=9, colormap=power_cmap, cblabel='') |
|
432 | ticksize=9, colormap=power_cmap, cblabel='') | |
| 439 |
|
433 | |||
| 440 | title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime) |
|
434 | title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime) | |
| 441 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor) |
|
435 | zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor) | |
| 442 | axes0 = self.axesList[i*self.__nsubplots+1] |
|
436 | axes0 = self.axesList[i*self.__nsubplots+1] | |
| 443 | axes0.pcolor(x, y, zdB, |
|
437 | axes0.pcolor(x, y, zdB, | |
| 444 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
438 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 445 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
439 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 446 | ticksize=9, colormap=power_cmap, cblabel='') |
|
440 | ticksize=9, colormap=power_cmap, cblabel='') | |
| 447 |
|
441 | |||
| 448 | coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:] / numpy.sqrt( dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:] ) |
|
442 | coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:] / numpy.sqrt( dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:] ) | |
| 449 | coherence = numpy.abs(coherenceComplex) |
|
443 | coherence = numpy.abs(coherenceComplex) | |
| 450 | # phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi |
|
444 | # phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi | |
| 451 | phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi |
|
445 | phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi | |
| 452 |
|
446 | |||
| 453 |
|
447 | |||
| 454 |
|
448 | |||
| 455 |
|
449 | |||
| 456 | # #print 'FASE', numpy.shape(phase), y[25] |
|
450 | # #print 'FASE', numpy.shape(phase), y[25] | |
| 457 | # fig = plt.figure(10+self.indice) |
|
451 | # fig = plt.figure(10+self.indice) | |
| 458 | # #plt.plot( x[0:256],coherence[:,25] ) |
|
452 | # #plt.plot( x[0:256],coherence[:,25] ) | |
| 459 | # cohAv = numpy.average(coherence,1) |
|
453 | # cohAv = numpy.average(coherence,1) | |
| 460 | # |
|
454 | # | |
| 461 | # plt.plot( x[0:256],cohAv ) |
|
455 | # plt.plot( x[0:256],cohAv ) | |
| 462 | # #plt.axis([-12, 12, 15, 50]) |
|
456 | # #plt.axis([-12, 12, 15, 50]) | |
| 463 | # plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) |
|
457 | # plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) | |
| 464 | # plt.ylabel('Desfase [grados]') |
|
458 | # plt.ylabel('Desfase [grados]') | |
| 465 | # plt.xlabel('Velocidad [m/s]') |
|
459 | # plt.xlabel('Velocidad [m/s]') | |
| 466 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) |
|
460 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) | |
| 467 | # |
|
461 | # | |
| 468 | # plt.show() |
|
462 | # plt.show() | |
| 469 | # self.indice=self.indice+1 |
|
463 | # self.indice=self.indice+1 | |
| 470 |
|
464 | |||
| 471 |
|
465 | |||
| 472 | # print 'FASE', numpy.shape(phase), y[25] |
|
466 | # print 'FASE', numpy.shape(phase), y[25] | |
| 473 | # fig = plt.figure(10+self.indice) |
|
467 | # fig = plt.figure(10+self.indice) | |
| 474 | # plt.plot( x[0:256],phase[:,25] ) |
|
468 | # plt.plot( x[0:256],phase[:,25] ) | |
| 475 | # #plt.axis([-12, 12, 15, 50]) |
|
469 | # #plt.axis([-12, 12, 15, 50]) | |
| 476 | # plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) |
|
470 | # plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) | |
| 477 | # plt.ylabel('Desfase [grados]') |
|
471 | # plt.ylabel('Desfase [grados]') | |
| 478 | # plt.xlabel('Velocidad [m/s]') |
|
472 | # plt.xlabel('Velocidad [m/s]') | |
| 479 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) |
|
473 | # fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) | |
| 480 | # |
|
474 | # | |
| 481 | # plt.show() |
|
475 | # plt.show() | |
| 482 | # self.indice=self.indice+1 |
|
476 | # self.indice=self.indice+1 | |
| 483 |
|
477 | |||
| 484 |
|
478 | |||
| 485 |
|
479 | |||
| 486 |
|
480 | |||
| 487 | title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1]) |
|
481 | title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1]) | |
| 488 | axes0 = self.axesList[i*self.__nsubplots+2] |
|
482 | axes0 = self.axesList[i*self.__nsubplots+2] | |
| 489 | axes0.pcolor(x, y, coherence, |
|
483 | axes0.pcolor(x, y, coherence, | |
| 490 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max, |
|
484 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max, | |
| 491 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
485 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 492 | ticksize=9, colormap=coherence_cmap, cblabel='') |
|
486 | ticksize=9, colormap=coherence_cmap, cblabel='') | |
| 493 |
|
487 | |||
| 494 | title = "Phase Ch%d * Ch%d" %(pair[0], pair[1]) |
|
488 | title = "Phase Ch%d * Ch%d" %(pair[0], pair[1]) | |
| 495 | axes0 = self.axesList[i*self.__nsubplots+3] |
|
489 | axes0 = self.axesList[i*self.__nsubplots+3] | |
| 496 | axes0.pcolor(x, y, phase, |
|
490 | axes0.pcolor(x, y, phase, | |
| 497 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, |
|
491 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, | |
| 498 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
492 | xlabel=xlabel, ylabel=ylabel, title=title, | |
| 499 | ticksize=9, colormap=phase_cmap, cblabel='') |
|
493 | ticksize=9, colormap=phase_cmap, cblabel='') | |
| 500 |
|
494 | |||
| 501 |
|
495 | |||
| 502 |
|
496 | |||
| 503 | self.draw() |
|
497 | self.draw() | |
| 504 |
|
498 | |||
| 505 | self.save(figpath=figpath, |
|
499 | self.save(figpath=figpath, | |
| 506 | figfile=figfile, |
|
500 | figfile=figfile, | |
| 507 | save=save, |
|
501 | save=save, | |
| 508 | ftp=ftp, |
|
502 | ftp=ftp, | |
| 509 | wr_period=wr_period, |
|
503 | wr_period=wr_period, | |
| 510 | thisDatetime=thisDatetime) |
|
504 | thisDatetime=thisDatetime) | |
| 511 |
|
505 | |||
| 512 |
|
506 | |||
| 513 | class RTIPlot(Figure): |
|
507 | class RTIPlot(Figure): | |
| 514 |
|
508 | |||
| 515 | __isConfig = None |
|
509 | __isConfig = None | |
| 516 | __nsubplots = None |
|
510 | __nsubplots = None | |
| 517 |
|
511 | |||
| 518 | WIDTHPROF = None |
|
512 | WIDTHPROF = None | |
| 519 | HEIGHTPROF = None |
|
513 | HEIGHTPROF = None | |
| 520 | PREFIX = 'rti' |
|
514 | PREFIX = 'rti' | |
| 521 |
|
515 | |||
| 522 | def __init__(self, **kwargs): |
|
516 | def __init__(self, **kwargs): | |
| 523 |
|
517 | |||
| 524 | Figure.__init__(self, **kwargs) |
|
518 | Figure.__init__(self, **kwargs) | |
| 525 | self.timerange = None |
|
519 | self.timerange = None | |
| 526 | self.isConfig = False |
|
520 | self.isConfig = False | |
| 527 | self.__nsubplots = 1 |
|
521 | self.__nsubplots = 1 | |
| 528 |
|
522 | |||
| 529 | self.WIDTH = 800 |
|
523 | self.WIDTH = 800 | |
| 530 | self.HEIGHT = 250 |
|
524 | self.HEIGHT = 250 | |
| 531 | self.WIDTHPROF = 120 |
|
525 | self.WIDTHPROF = 120 | |
| 532 | self.HEIGHTPROF = 0 |
|
526 | self.HEIGHTPROF = 0 | |
| 533 | self.counter_imagwr = 0 |
|
527 | self.counter_imagwr = 0 | |
| 534 |
|
528 | |||
| 535 | self.PLOT_CODE = RTI_CODE |
|
529 | self.PLOT_CODE = RTI_CODE | |
| 536 |
|
530 | |||
| 537 | self.FTP_WEI = None |
|
531 | self.FTP_WEI = None | |
| 538 | self.EXP_CODE = None |
|
532 | self.EXP_CODE = None | |
| 539 | self.SUB_EXP_CODE = None |
|
533 | self.SUB_EXP_CODE = None | |
| 540 | self.PLOT_POS = None |
|
534 | self.PLOT_POS = None | |
| 541 | self.tmin = None |
|
535 | self.tmin = None | |
| 542 | self.tmax = None |
|
536 | self.tmax = None | |
| 543 |
|
537 | |||
| 544 | self.xmin = None |
|
538 | self.xmin = None | |
| 545 | self.xmax = None |
|
539 | self.xmax = None | |
| 546 |
|
540 | |||
| 547 | self.figfile = None |
|
541 | self.figfile = None | |
| 548 |
|
542 | |||
| 549 | def getSubplots(self): |
|
543 | def getSubplots(self): | |
| 550 |
|
544 | |||
| 551 | ncol = 1 |
|
545 | ncol = 1 | |
| 552 | nrow = self.nplots |
|
546 | nrow = self.nplots | |
| 553 |
|
547 | |||
| 554 | return nrow, ncol |
|
548 | return nrow, ncol | |
| 555 |
|
549 | |||
| 556 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
550 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 557 |
|
551 | |||
| 558 | self.__showprofile = showprofile |
|
552 | self.__showprofile = showprofile | |
| 559 | self.nplots = nplots |
|
553 | self.nplots = nplots | |
| 560 |
|
554 | |||
| 561 | ncolspan = 1 |
|
555 | ncolspan = 1 | |
| 562 | colspan = 1 |
|
556 | colspan = 1 | |
| 563 | if showprofile: |
|
557 | if showprofile: | |
| 564 | ncolspan = 7 |
|
558 | ncolspan = 7 | |
| 565 | colspan = 6 |
|
559 | colspan = 6 | |
| 566 | self.__nsubplots = 2 |
|
560 | self.__nsubplots = 2 | |
| 567 |
|
561 | |||
| 568 | self.createFigure(id = id, |
|
562 | self.createFigure(id = id, | |
| 569 | wintitle = wintitle, |
|
563 | wintitle = wintitle, | |
| 570 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
564 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 571 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
565 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 572 | show=show) |
|
566 | show=show) | |
| 573 |
|
567 | |||
| 574 | nrow, ncol = self.getSubplots() |
|
568 | nrow, ncol = self.getSubplots() | |
| 575 |
|
569 | |||
| 576 | counter = 0 |
|
570 | counter = 0 | |
| 577 | for y in range(nrow): |
|
571 | for y in range(nrow): | |
| 578 | for x in range(ncol): |
|
572 | for x in range(ncol): | |
| 579 |
|
573 | |||
| 580 | if counter >= self.nplots: |
|
574 | if counter >= self.nplots: | |
| 581 | break |
|
575 | break | |
| 582 |
|
576 | |||
| 583 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
577 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 584 |
|
578 | |||
| 585 | if showprofile: |
|
579 | if showprofile: | |
| 586 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
580 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 587 |
|
581 | |||
| 588 | counter += 1 |
|
582 | counter += 1 | |
| 589 |
|
583 | |||
| 590 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
584 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', | |
| 591 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
585 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 592 | timerange=None, colormap='jet', |
|
586 | timerange=None, colormap='jet', | |
| 593 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
587 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, | |
| 594 | server=None, folder=None, username=None, password=None, |
|
588 | server=None, folder=None, username=None, password=None, | |
| 595 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None): |
|
589 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None): | |
| 596 |
|
590 | |||
| 597 | """ |
|
591 | """ | |
| 598 |
|
592 | |||
| 599 | Input: |
|
593 | Input: | |
| 600 | dataOut : |
|
594 | dataOut : | |
| 601 | id : |
|
595 | id : | |
| 602 | wintitle : |
|
596 | wintitle : | |
| 603 | channelList : |
|
597 | channelList : | |
| 604 | showProfile : |
|
598 | showProfile : | |
| 605 | xmin : None, |
|
599 | xmin : None, | |
| 606 | xmax : None, |
|
600 | xmax : None, | |
| 607 | ymin : None, |
|
601 | ymin : None, | |
| 608 | ymax : None, |
|
602 | ymax : None, | |
| 609 | zmin : None, |
|
603 | zmin : None, | |
| 610 | zmax : None |
|
604 | zmax : None | |
| 611 | """ |
|
605 | """ | |
| 612 |
|
606 | |||
| 613 | #colormap = kwargs.get('colormap', 'jet') |
|
607 | #colormap = kwargs.get('colormap', 'jet') | |
| 614 | if HEIGHT is not None: |
|
608 | if HEIGHT is not None: | |
| 615 | self.HEIGHT = HEIGHT |
|
609 | self.HEIGHT = HEIGHT | |
| 616 |
|
610 | |||
| 617 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
611 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 618 | return |
|
612 | return | |
| 619 |
|
613 | |||
| 620 | if channelList == None: |
|
614 | if channelList == None: | |
| 621 | channelIndexList = dataOut.channelIndexList |
|
615 | channelIndexList = dataOut.channelIndexList | |
| 622 | else: |
|
616 | else: | |
| 623 | channelIndexList = [] |
|
617 | channelIndexList = [] | |
| 624 | for channel in channelList: |
|
618 | for channel in channelList: | |
| 625 | if channel not in dataOut.channelList: |
|
619 | if channel not in dataOut.channelList: | |
| 626 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
620 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 627 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
621 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 628 |
|
622 | |||
| 629 | if normFactor is None: |
|
623 | if normFactor is None: | |
| 630 | factor = dataOut.normFactor |
|
624 | factor = dataOut.normFactor | |
| 631 | else: |
|
625 | else: | |
| 632 | factor = normFactor |
|
626 | factor = normFactor | |
| 633 |
|
627 | |||
| 634 | # factor = dataOut.normFactor |
|
628 | # factor = dataOut.normFactor | |
| 635 | x = dataOut.getTimeRange() |
|
629 | x = dataOut.getTimeRange() | |
| 636 | y = dataOut.getHeiRange() |
|
630 | y = dataOut.getHeiRange() | |
| 637 |
|
631 | |||
| 638 | z = dataOut.data_spc/factor |
|
632 | z = dataOut.data_spc/factor | |
| 639 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
633 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 640 | avg = numpy.average(z, axis=1) |
|
634 | avg = numpy.average(z, axis=1) | |
| 641 | avgdB = 10.*numpy.log10(avg) |
|
635 | avgdB = 10.*numpy.log10(avg) | |
| 642 | # avgdB = dataOut.getPower() |
|
636 | # avgdB = dataOut.getPower() | |
| 643 |
|
637 | |||
| 644 |
|
638 | |||
| 645 | thisDatetime = dataOut.datatime |
|
639 | thisDatetime = dataOut.datatime | |
| 646 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
640 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 647 | title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
641 | title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 648 | xlabel = "" |
|
642 | xlabel = "" | |
| 649 | ylabel = "Range (Km)" |
|
643 | ylabel = "Range (Km)" | |
| 650 |
|
644 | |||
| 651 | update_figfile = False |
|
645 | update_figfile = False | |
| 652 |
|
646 | |||
| 653 | if dataOut.ltctime >= self.xmax: |
|
647 | if dataOut.ltctime >= self.xmax: | |
| 654 | self.counter_imagwr = wr_period |
|
648 | self.counter_imagwr = wr_period | |
| 655 | self.isConfig = False |
|
649 | self.isConfig = False | |
| 656 | update_figfile = True |
|
650 | update_figfile = True | |
| 657 |
|
651 | |||
| 658 | if not self.isConfig: |
|
652 | if not self.isConfig: | |
| 659 |
|
653 | |||
| 660 | nplots = len(channelIndexList) |
|
654 | nplots = len(channelIndexList) | |
| 661 |
|
655 | |||
| 662 | self.setup(id=id, |
|
656 | self.setup(id=id, | |
| 663 | nplots=nplots, |
|
657 | nplots=nplots, | |
| 664 | wintitle=wintitle, |
|
658 | wintitle=wintitle, | |
| 665 | showprofile=showprofile, |
|
659 | showprofile=showprofile, | |
| 666 | show=show) |
|
660 | show=show) | |
| 667 |
|
661 | |||
| 668 | if timerange != None: |
|
662 | if timerange != None: | |
| 669 | self.timerange = timerange |
|
663 | self.timerange = timerange | |
| 670 |
|
664 | |||
| 671 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
665 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 672 |
|
666 | |||
| 673 | noise = dataOut.noise/factor |
|
667 | noise = dataOut.noise/factor | |
| 674 | noisedB = 10*numpy.log10(noise) |
|
668 | noisedB = 10*numpy.log10(noise) | |
| 675 |
|
669 | |||
| 676 | if ymin == None: ymin = numpy.nanmin(y) |
|
670 | if ymin == None: ymin = numpy.nanmin(y) | |
| 677 | if ymax == None: ymax = numpy.nanmax(y) |
|
671 | if ymax == None: ymax = numpy.nanmax(y) | |
| 678 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 |
|
672 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
| 679 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 |
|
673 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
| 680 |
|
674 | |||
| 681 | self.FTP_WEI = ftp_wei |
|
675 | self.FTP_WEI = ftp_wei | |
| 682 | self.EXP_CODE = exp_code |
|
676 | self.EXP_CODE = exp_code | |
| 683 | self.SUB_EXP_CODE = sub_exp_code |
|
677 | self.SUB_EXP_CODE = sub_exp_code | |
| 684 | self.PLOT_POS = plot_pos |
|
678 | self.PLOT_POS = plot_pos | |
| 685 |
|
679 | |||
| 686 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
680 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 687 | self.isConfig = True |
|
681 | self.isConfig = True | |
| 688 | self.figfile = figfile |
|
682 | self.figfile = figfile | |
| 689 | update_figfile = True |
|
683 | update_figfile = True | |
| 690 |
|
684 | |||
| 691 | self.setWinTitle(title) |
|
685 | self.setWinTitle(title) | |
| 692 |
|
686 | |||
| 693 | for i in range(self.nplots): |
|
687 | for i in range(self.nplots): | |
| 694 | index = channelIndexList[i] |
|
688 | index = channelIndexList[i] | |
| 695 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
689 | title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 696 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
|
690 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
| 697 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
|
691 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
| 698 | axes = self.axesList[i*self.__nsubplots] |
|
692 | axes = self.axesList[i*self.__nsubplots] | |
| 699 | zdB = avgdB[index].reshape((1,-1)) |
|
693 | zdB = avgdB[index].reshape((1,-1)) | |
| 700 | axes.pcolorbuffer(x, y, zdB, |
|
694 | axes.pcolorbuffer(x, y, zdB, | |
| 701 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
695 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 702 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
696 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 703 | ticksize=9, cblabel='', cbsize="1%", colormap=colormap) |
|
697 | ticksize=9, cblabel='', cbsize="1%", colormap=colormap) | |
| 704 |
|
698 | |||
| 705 | if self.__showprofile: |
|
699 | if self.__showprofile: | |
| 706 | axes = self.axesList[i*self.__nsubplots +1] |
|
700 | axes = self.axesList[i*self.__nsubplots +1] | |
| 707 | axes.pline(avgdB[index], y, |
|
701 | axes.pline(avgdB[index], y, | |
| 708 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
702 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 709 | xlabel='dB', ylabel='', title='', |
|
703 | xlabel='dB', ylabel='', title='', | |
| 710 | ytick_visible=False, |
|
704 | ytick_visible=False, | |
| 711 | grid='x') |
|
705 | grid='x') | |
| 712 |
|
706 | |||
| 713 | self.draw() |
|
707 | self.draw() | |
| 714 |
|
708 | |||
| 715 | self.save(figpath=figpath, |
|
709 | self.save(figpath=figpath, | |
| 716 | figfile=figfile, |
|
710 | figfile=figfile, | |
| 717 | save=save, |
|
711 | save=save, | |
| 718 | ftp=ftp, |
|
712 | ftp=ftp, | |
| 719 | wr_period=wr_period, |
|
713 | wr_period=wr_period, | |
| 720 | thisDatetime=thisDatetime, |
|
714 | thisDatetime=thisDatetime, | |
| 721 | update_figfile=update_figfile) |
|
715 | update_figfile=update_figfile) | |
| 722 |
|
716 | |||
| 723 | class CoherenceMap(Figure): |
|
717 | class CoherenceMap(Figure): | |
| 724 | isConfig = None |
|
718 | isConfig = None | |
| 725 | __nsubplots = None |
|
719 | __nsubplots = None | |
| 726 |
|
720 | |||
| 727 | WIDTHPROF = None |
|
721 | WIDTHPROF = None | |
| 728 | HEIGHTPROF = None |
|
722 | HEIGHTPROF = None | |
| 729 | PREFIX = 'cmap' |
|
723 | PREFIX = 'cmap' | |
| 730 |
|
724 | |||
| 731 | def __init__(self, **kwargs): |
|
725 | def __init__(self, **kwargs): | |
| 732 | Figure.__init__(self, **kwargs) |
|
726 | Figure.__init__(self, **kwargs) | |
| 733 | self.timerange = 2*60*60 |
|
727 | self.timerange = 2*60*60 | |
| 734 | self.isConfig = False |
|
728 | self.isConfig = False | |
| 735 | self.__nsubplots = 1 |
|
729 | self.__nsubplots = 1 | |
| 736 |
|
730 | |||
| 737 | self.WIDTH = 800 |
|
731 | self.WIDTH = 800 | |
| 738 | self.HEIGHT = 180 |
|
732 | self.HEIGHT = 180 | |
| 739 | self.WIDTHPROF = 120 |
|
733 | self.WIDTHPROF = 120 | |
| 740 | self.HEIGHTPROF = 0 |
|
734 | self.HEIGHTPROF = 0 | |
| 741 | self.counter_imagwr = 0 |
|
735 | self.counter_imagwr = 0 | |
| 742 |
|
736 | |||
| 743 | self.PLOT_CODE = COH_CODE |
|
737 | self.PLOT_CODE = COH_CODE | |
| 744 |
|
738 | |||
| 745 | self.FTP_WEI = None |
|
739 | self.FTP_WEI = None | |
| 746 | self.EXP_CODE = None |
|
740 | self.EXP_CODE = None | |
| 747 | self.SUB_EXP_CODE = None |
|
741 | self.SUB_EXP_CODE = None | |
| 748 | self.PLOT_POS = None |
|
742 | self.PLOT_POS = None | |
| 749 | self.counter_imagwr = 0 |
|
743 | self.counter_imagwr = 0 | |
| 750 |
|
744 | |||
| 751 | self.xmin = None |
|
745 | self.xmin = None | |
| 752 | self.xmax = None |
|
746 | self.xmax = None | |
| 753 |
|
747 | |||
| 754 | def getSubplots(self): |
|
748 | def getSubplots(self): | |
| 755 | ncol = 1 |
|
749 | ncol = 1 | |
| 756 | nrow = self.nplots*2 |
|
750 | nrow = self.nplots*2 | |
| 757 |
|
751 | |||
| 758 | return nrow, ncol |
|
752 | return nrow, ncol | |
| 759 |
|
753 | |||
| 760 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
754 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 761 | self.__showprofile = showprofile |
|
755 | self.__showprofile = showprofile | |
| 762 | self.nplots = nplots |
|
756 | self.nplots = nplots | |
| 763 |
|
757 | |||
| 764 | ncolspan = 1 |
|
758 | ncolspan = 1 | |
| 765 | colspan = 1 |
|
759 | colspan = 1 | |
| 766 | if showprofile: |
|
760 | if showprofile: | |
| 767 | ncolspan = 7 |
|
761 | ncolspan = 7 | |
| 768 | colspan = 6 |
|
762 | colspan = 6 | |
| 769 | self.__nsubplots = 2 |
|
763 | self.__nsubplots = 2 | |
| 770 |
|
764 | |||
| 771 | self.createFigure(id = id, |
|
765 | self.createFigure(id = id, | |
| 772 | wintitle = wintitle, |
|
766 | wintitle = wintitle, | |
| 773 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
767 | widthplot = self.WIDTH + self.WIDTHPROF, | |
| 774 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
768 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
| 775 | show=True) |
|
769 | show=True) | |
| 776 |
|
770 | |||
| 777 | nrow, ncol = self.getSubplots() |
|
771 | nrow, ncol = self.getSubplots() | |
| 778 |
|
772 | |||
| 779 | for y in range(nrow): |
|
773 | for y in range(nrow): | |
| 780 | for x in range(ncol): |
|
774 | for x in range(ncol): | |
| 781 |
|
775 | |||
| 782 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
776 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 783 |
|
777 | |||
| 784 | if showprofile: |
|
778 | if showprofile: | |
| 785 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
779 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
| 786 |
|
780 | |||
| 787 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
781 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 788 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
782 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
| 789 | timerange=None, phase_min=None, phase_max=None, |
|
783 | timerange=None, phase_min=None, phase_max=None, | |
| 790 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, |
|
784 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, | |
| 791 | coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
785 | coherence_cmap='jet', phase_cmap='RdBu_r', show=True, | |
| 792 | server=None, folder=None, username=None, password=None, |
|
786 | server=None, folder=None, username=None, password=None, | |
| 793 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
787 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 794 |
|
788 | |||
| 795 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
789 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 796 | return |
|
790 | return | |
| 797 |
|
791 | |||
| 798 | if pairsList == None: |
|
792 | if pairsList == None: | |
| 799 | pairsIndexList = dataOut.pairsIndexList |
|
793 | pairsIndexList = dataOut.pairsIndexList | |
| 800 | else: |
|
794 | else: | |
| 801 | pairsIndexList = [] |
|
795 | pairsIndexList = [] | |
| 802 | for pair in pairsList: |
|
796 | for pair in pairsList: | |
| 803 | if pair not in dataOut.pairsList: |
|
797 | if pair not in dataOut.pairsList: | |
| 804 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
798 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) | |
| 805 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
799 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 806 |
|
800 | |||
| 807 | if pairsIndexList == []: |
|
801 | if pairsIndexList == []: | |
| 808 | return |
|
802 | return | |
| 809 |
|
803 | |||
| 810 | if len(pairsIndexList) > 4: |
|
804 | if len(pairsIndexList) > 4: | |
| 811 | pairsIndexList = pairsIndexList[0:4] |
|
805 | pairsIndexList = pairsIndexList[0:4] | |
| 812 |
|
806 | |||
| 813 | if phase_min == None: |
|
807 | if phase_min == None: | |
| 814 | phase_min = -180 |
|
808 | phase_min = -180 | |
| 815 | if phase_max == None: |
|
809 | if phase_max == None: | |
| 816 | phase_max = 180 |
|
810 | phase_max = 180 | |
| 817 |
|
811 | |||
| 818 | x = dataOut.getTimeRange() |
|
812 | x = dataOut.getTimeRange() | |
| 819 | y = dataOut.getHeiRange() |
|
813 | y = dataOut.getHeiRange() | |
| 820 |
|
814 | |||
| 821 | thisDatetime = dataOut.datatime |
|
815 | thisDatetime = dataOut.datatime | |
| 822 |
|
816 | |||
| 823 | title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
817 | title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 824 | xlabel = "" |
|
818 | xlabel = "" | |
| 825 | ylabel = "Range (Km)" |
|
819 | ylabel = "Range (Km)" | |
| 826 | update_figfile = False |
|
820 | update_figfile = False | |
| 827 |
|
821 | |||
| 828 | if not self.isConfig: |
|
822 | if not self.isConfig: | |
| 829 | nplots = len(pairsIndexList) |
|
823 | nplots = len(pairsIndexList) | |
| 830 | self.setup(id=id, |
|
824 | self.setup(id=id, | |
| 831 | nplots=nplots, |
|
825 | nplots=nplots, | |
| 832 | wintitle=wintitle, |
|
826 | wintitle=wintitle, | |
| 833 | showprofile=showprofile, |
|
827 | showprofile=showprofile, | |
| 834 | show=show) |
|
828 | show=show) | |
| 835 |
|
829 | |||
| 836 | if timerange != None: |
|
830 | if timerange != None: | |
| 837 | self.timerange = timerange |
|
831 | self.timerange = timerange | |
| 838 |
|
832 | |||
| 839 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
833 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 840 |
|
834 | |||
| 841 | if ymin == None: ymin = numpy.nanmin(y) |
|
835 | if ymin == None: ymin = numpy.nanmin(y) | |
| 842 | if ymax == None: ymax = numpy.nanmax(y) |
|
836 | if ymax == None: ymax = numpy.nanmax(y) | |
| 843 | if zmin == None: zmin = 0. |
|
837 | if zmin == None: zmin = 0. | |
| 844 | if zmax == None: zmax = 1. |
|
838 | if zmax == None: zmax = 1. | |
| 845 |
|
839 | |||
| 846 | self.FTP_WEI = ftp_wei |
|
840 | self.FTP_WEI = ftp_wei | |
| 847 | self.EXP_CODE = exp_code |
|
841 | self.EXP_CODE = exp_code | |
| 848 | self.SUB_EXP_CODE = sub_exp_code |
|
842 | self.SUB_EXP_CODE = sub_exp_code | |
| 849 | self.PLOT_POS = plot_pos |
|
843 | self.PLOT_POS = plot_pos | |
| 850 |
|
844 | |||
| 851 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
845 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 852 |
|
846 | |||
| 853 | self.isConfig = True |
|
847 | self.isConfig = True | |
| 854 | update_figfile = True |
|
848 | update_figfile = True | |
| 855 |
|
849 | |||
| 856 | self.setWinTitle(title) |
|
850 | self.setWinTitle(title) | |
| 857 |
|
851 | |||
| 858 | for i in range(self.nplots): |
|
852 | for i in range(self.nplots): | |
| 859 |
|
853 | |||
| 860 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
854 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 861 |
|
855 | |||
| 862 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) |
|
856 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0) | |
| 863 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) |
|
857 | powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0) | |
| 864 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) |
|
858 | powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0) | |
| 865 |
|
859 | |||
| 866 |
|
860 | |||
| 867 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
861 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 868 | coherence = numpy.abs(avgcoherenceComplex) |
|
862 | coherence = numpy.abs(avgcoherenceComplex) | |
| 869 |
|
863 | |||
| 870 | z = coherence.reshape((1,-1)) |
|
864 | z = coherence.reshape((1,-1)) | |
| 871 |
|
865 | |||
| 872 | counter = 0 |
|
866 | counter = 0 | |
| 873 |
|
867 | |||
| 874 | title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
868 | title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 875 | axes = self.axesList[i*self.__nsubplots*2] |
|
869 | axes = self.axesList[i*self.__nsubplots*2] | |
| 876 | axes.pcolorbuffer(x, y, z, |
|
870 | axes.pcolorbuffer(x, y, z, | |
| 877 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
871 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
| 878 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
872 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 879 | ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%") |
|
873 | ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%") | |
| 880 |
|
874 | |||
| 881 | if self.__showprofile: |
|
875 | if self.__showprofile: | |
| 882 | counter += 1 |
|
876 | counter += 1 | |
| 883 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
877 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 884 | axes.pline(coherence, y, |
|
878 | axes.pline(coherence, y, | |
| 885 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, |
|
879 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
| 886 | xlabel='', ylabel='', title='', ticksize=7, |
|
880 | xlabel='', ylabel='', title='', ticksize=7, | |
| 887 | ytick_visible=False, nxticks=5, |
|
881 | ytick_visible=False, nxticks=5, | |
| 888 | grid='x') |
|
882 | grid='x') | |
| 889 |
|
883 | |||
| 890 | counter += 1 |
|
884 | counter += 1 | |
| 891 |
|
885 | |||
| 892 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
886 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 893 |
|
887 | |||
| 894 | z = phase.reshape((1,-1)) |
|
888 | z = phase.reshape((1,-1)) | |
| 895 |
|
889 | |||
| 896 | title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
890 | title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 897 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
891 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 898 | axes.pcolorbuffer(x, y, z, |
|
892 | axes.pcolorbuffer(x, y, z, | |
| 899 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, |
|
893 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max, | |
| 900 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, |
|
894 | xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True, | |
| 901 | ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%") |
|
895 | ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%") | |
| 902 |
|
896 | |||
| 903 | if self.__showprofile: |
|
897 | if self.__showprofile: | |
| 904 | counter += 1 |
|
898 | counter += 1 | |
| 905 | axes = self.axesList[i*self.__nsubplots*2 + counter] |
|
899 | axes = self.axesList[i*self.__nsubplots*2 + counter] | |
| 906 | axes.pline(phase, y, |
|
900 | axes.pline(phase, y, | |
| 907 | xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax, |
|
901 | xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax, | |
| 908 | xlabel='', ylabel='', title='', ticksize=7, |
|
902 | xlabel='', ylabel='', title='', ticksize=7, | |
| 909 | ytick_visible=False, nxticks=4, |
|
903 | ytick_visible=False, nxticks=4, | |
| 910 | grid='x') |
|
904 | grid='x') | |
| 911 |
|
905 | |||
| 912 | self.draw() |
|
906 | self.draw() | |
| 913 |
|
907 | |||
| 914 | if dataOut.ltctime >= self.xmax: |
|
908 | if dataOut.ltctime >= self.xmax: | |
| 915 | self.counter_imagwr = wr_period |
|
909 | self.counter_imagwr = wr_period | |
| 916 | self.isConfig = False |
|
910 | self.isConfig = False | |
| 917 | update_figfile = True |
|
911 | update_figfile = True | |
| 918 |
|
912 | |||
| 919 | self.save(figpath=figpath, |
|
913 | self.save(figpath=figpath, | |
| 920 | figfile=figfile, |
|
914 | figfile=figfile, | |
| 921 | save=save, |
|
915 | save=save, | |
| 922 | ftp=ftp, |
|
916 | ftp=ftp, | |
| 923 | wr_period=wr_period, |
|
917 | wr_period=wr_period, | |
| 924 | thisDatetime=thisDatetime, |
|
918 | thisDatetime=thisDatetime, | |
| 925 | update_figfile=update_figfile) |
|
919 | update_figfile=update_figfile) | |
| 926 |
|
920 | |||
| 927 | class PowerProfilePlot(Figure): |
|
921 | class PowerProfilePlot(Figure): | |
| 928 |
|
922 | |||
| 929 | isConfig = None |
|
923 | isConfig = None | |
| 930 | __nsubplots = None |
|
924 | __nsubplots = None | |
| 931 |
|
925 | |||
| 932 | WIDTHPROF = None |
|
926 | WIDTHPROF = None | |
| 933 | HEIGHTPROF = None |
|
927 | HEIGHTPROF = None | |
| 934 | PREFIX = 'spcprofile' |
|
928 | PREFIX = 'spcprofile' | |
| 935 |
|
929 | |||
| 936 | def __init__(self, **kwargs): |
|
930 | def __init__(self, **kwargs): | |
| 937 | Figure.__init__(self, **kwargs) |
|
931 | Figure.__init__(self, **kwargs) | |
| 938 | self.isConfig = False |
|
932 | self.isConfig = False | |
| 939 | self.__nsubplots = 1 |
|
933 | self.__nsubplots = 1 | |
| 940 |
|
934 | |||
| 941 | self.PLOT_CODE = POWER_CODE |
|
935 | self.PLOT_CODE = POWER_CODE | |
| 942 |
|
936 | |||
| 943 | self.WIDTH = 300 |
|
937 | self.WIDTH = 300 | |
| 944 | self.HEIGHT = 500 |
|
938 | self.HEIGHT = 500 | |
| 945 | self.counter_imagwr = 0 |
|
939 | self.counter_imagwr = 0 | |
| 946 |
|
940 | |||
| 947 | def getSubplots(self): |
|
941 | def getSubplots(self): | |
| 948 | ncol = 1 |
|
942 | ncol = 1 | |
| 949 | nrow = 1 |
|
943 | nrow = 1 | |
| 950 |
|
944 | |||
| 951 | return nrow, ncol |
|
945 | return nrow, ncol | |
| 952 |
|
946 | |||
| 953 | def setup(self, id, nplots, wintitle, show): |
|
947 | def setup(self, id, nplots, wintitle, show): | |
| 954 |
|
948 | |||
| 955 | self.nplots = nplots |
|
949 | self.nplots = nplots | |
| 956 |
|
950 | |||
| 957 | ncolspan = 1 |
|
951 | ncolspan = 1 | |
| 958 | colspan = 1 |
|
952 | colspan = 1 | |
| 959 |
|
953 | |||
| 960 | self.createFigure(id = id, |
|
954 | self.createFigure(id = id, | |
| 961 | wintitle = wintitle, |
|
955 | wintitle = wintitle, | |
| 962 | widthplot = self.WIDTH, |
|
956 | widthplot = self.WIDTH, | |
| 963 | heightplot = self.HEIGHT, |
|
957 | heightplot = self.HEIGHT, | |
| 964 | show=show) |
|
958 | show=show) | |
| 965 |
|
959 | |||
| 966 | nrow, ncol = self.getSubplots() |
|
960 | nrow, ncol = self.getSubplots() | |
| 967 |
|
961 | |||
| 968 | counter = 0 |
|
962 | counter = 0 | |
| 969 | for y in range(nrow): |
|
963 | for y in range(nrow): | |
| 970 | for x in range(ncol): |
|
964 | for x in range(ncol): | |
| 971 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
965 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 972 |
|
966 | |||
| 973 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
967 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 974 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
968 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 975 | save=False, figpath='./', figfile=None, show=True, |
|
969 | save=False, figpath='./', figfile=None, show=True, | |
| 976 | ftp=False, wr_period=1, server=None, |
|
970 | ftp=False, wr_period=1, server=None, | |
| 977 | folder=None, username=None, password=None): |
|
971 | folder=None, username=None, password=None): | |
| 978 |
|
972 | |||
| 979 |
|
973 | |||
| 980 | if channelList == None: |
|
974 | if channelList == None: | |
| 981 | channelIndexList = dataOut.channelIndexList |
|
975 | channelIndexList = dataOut.channelIndexList | |
| 982 | channelList = dataOut.channelList |
|
976 | channelList = dataOut.channelList | |
| 983 | else: |
|
977 | else: | |
| 984 | channelIndexList = [] |
|
978 | channelIndexList = [] | |
| 985 | for channel in channelList: |
|
979 | for channel in channelList: | |
| 986 | if channel not in dataOut.channelList: |
|
980 | if channel not in dataOut.channelList: | |
| 987 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
981 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 988 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
982 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 989 |
|
983 | |||
| 990 | factor = dataOut.normFactor |
|
984 | factor = dataOut.normFactor | |
| 991 |
|
985 | |||
| 992 | y = dataOut.getHeiRange() |
|
986 | y = dataOut.getHeiRange() | |
| 993 |
|
987 | |||
| 994 | #for voltage |
|
988 | #for voltage | |
| 995 | if dataOut.type == 'Voltage': |
|
989 | if dataOut.type == 'Voltage': | |
| 996 | x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) |
|
990 | x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) | |
| 997 | x = x.real |
|
991 | x = x.real | |
| 998 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
992 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) | |
| 999 |
|
993 | |||
| 1000 | #for spectra |
|
994 | #for spectra | |
| 1001 | if dataOut.type == 'Spectra': |
|
995 | if dataOut.type == 'Spectra': | |
| 1002 | x = dataOut.data_spc[channelIndexList,:,:]/factor |
|
996 | x = dataOut.data_spc[channelIndexList,:,:]/factor | |
| 1003 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) |
|
997 | x = numpy.where(numpy.isfinite(x), x, numpy.NAN) | |
| 1004 | x = numpy.average(x, axis=1) |
|
998 | x = numpy.average(x, axis=1) | |
| 1005 |
|
999 | |||
| 1006 |
|
1000 | |||
| 1007 | xdB = 10*numpy.log10(x) |
|
1001 | xdB = 10*numpy.log10(x) | |
| 1008 |
|
1002 | |||
| 1009 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1003 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1010 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1004 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1011 | xlabel = "dB" |
|
1005 | xlabel = "dB" | |
| 1012 | ylabel = "Range (Km)" |
|
1006 | ylabel = "Range (Km)" | |
| 1013 |
|
1007 | |||
| 1014 | if not self.isConfig: |
|
1008 | if not self.isConfig: | |
| 1015 |
|
1009 | |||
| 1016 | nplots = 1 |
|
1010 | nplots = 1 | |
| 1017 |
|
1011 | |||
| 1018 | self.setup(id=id, |
|
1012 | self.setup(id=id, | |
| 1019 | nplots=nplots, |
|
1013 | nplots=nplots, | |
| 1020 | wintitle=wintitle, |
|
1014 | wintitle=wintitle, | |
| 1021 | show=show) |
|
1015 | show=show) | |
| 1022 |
|
1016 | |||
| 1023 | if ymin == None: ymin = numpy.nanmin(y) |
|
1017 | if ymin == None: ymin = numpy.nanmin(y) | |
| 1024 | if ymax == None: ymax = numpy.nanmax(y) |
|
1018 | if ymax == None: ymax = numpy.nanmax(y) | |
| 1025 | if xmin == None: xmin = numpy.nanmin(xdB)*0.9 |
|
1019 | if xmin == None: xmin = numpy.nanmin(xdB)*0.9 | |
| 1026 | if xmax == None: xmax = numpy.nanmax(xdB)*1.1 |
|
1020 | if xmax == None: xmax = numpy.nanmax(xdB)*1.1 | |
| 1027 |
|
1021 | |||
| 1028 | self.isConfig = True |
|
1022 | self.isConfig = True | |
| 1029 |
|
1023 | |||
| 1030 | self.setWinTitle(title) |
|
1024 | self.setWinTitle(title) | |
| 1031 |
|
1025 | |||
| 1032 | title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1026 | title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1033 | axes = self.axesList[0] |
|
1027 | axes = self.axesList[0] | |
| 1034 |
|
1028 | |||
| 1035 | legendlabels = ["channel %d"%x for x in channelList] |
|
1029 | legendlabels = ["channel %d"%x for x in channelList] | |
| 1036 | axes.pmultiline(xdB, y, |
|
1030 | axes.pmultiline(xdB, y, | |
| 1037 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1031 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1038 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
1032 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 1039 | ytick_visible=True, nxticks=5, |
|
1033 | ytick_visible=True, nxticks=5, | |
| 1040 | grid='x') |
|
1034 | grid='x') | |
| 1041 |
|
1035 | |||
| 1042 | self.draw() |
|
1036 | self.draw() | |
| 1043 |
|
1037 | |||
| 1044 | self.save(figpath=figpath, |
|
1038 | self.save(figpath=figpath, | |
| 1045 | figfile=figfile, |
|
1039 | figfile=figfile, | |
| 1046 | save=save, |
|
1040 | save=save, | |
| 1047 | ftp=ftp, |
|
1041 | ftp=ftp, | |
| 1048 | wr_period=wr_period, |
|
1042 | wr_period=wr_period, | |
| 1049 | thisDatetime=thisDatetime) |
|
1043 | thisDatetime=thisDatetime) | |
| 1050 |
|
1044 | |||
| 1051 | class SpectraCutPlot(Figure): |
|
1045 | class SpectraCutPlot(Figure): | |
| 1052 |
|
1046 | |||
| 1053 | isConfig = None |
|
1047 | isConfig = None | |
| 1054 | __nsubplots = None |
|
1048 | __nsubplots = None | |
| 1055 |
|
1049 | |||
| 1056 | WIDTHPROF = None |
|
1050 | WIDTHPROF = None | |
| 1057 | HEIGHTPROF = None |
|
1051 | HEIGHTPROF = None | |
| 1058 | PREFIX = 'spc_cut' |
|
1052 | PREFIX = 'spc_cut' | |
| 1059 |
|
1053 | |||
| 1060 | def __init__(self, **kwargs): |
|
1054 | def __init__(self, **kwargs): | |
| 1061 | Figure.__init__(self, **kwargs) |
|
1055 | Figure.__init__(self, **kwargs) | |
| 1062 | self.isConfig = False |
|
1056 | self.isConfig = False | |
| 1063 | self.__nsubplots = 1 |
|
1057 | self.__nsubplots = 1 | |
| 1064 |
|
1058 | |||
| 1065 | self.PLOT_CODE = POWER_CODE |
|
1059 | self.PLOT_CODE = POWER_CODE | |
| 1066 |
|
1060 | |||
| 1067 | self.WIDTH = 700 |
|
1061 | self.WIDTH = 700 | |
| 1068 | self.HEIGHT = 500 |
|
1062 | self.HEIGHT = 500 | |
| 1069 | self.counter_imagwr = 0 |
|
1063 | self.counter_imagwr = 0 | |
| 1070 |
|
1064 | |||
| 1071 | def getSubplots(self): |
|
1065 | def getSubplots(self): | |
| 1072 | ncol = 1 |
|
1066 | ncol = 1 | |
| 1073 | nrow = 1 |
|
1067 | nrow = 1 | |
| 1074 |
|
1068 | |||
| 1075 | return nrow, ncol |
|
1069 | return nrow, ncol | |
| 1076 |
|
1070 | |||
| 1077 | def setup(self, id, nplots, wintitle, show): |
|
1071 | def setup(self, id, nplots, wintitle, show): | |
| 1078 |
|
1072 | |||
| 1079 | self.nplots = nplots |
|
1073 | self.nplots = nplots | |
| 1080 |
|
1074 | |||
| 1081 | ncolspan = 1 |
|
1075 | ncolspan = 1 | |
| 1082 | colspan = 1 |
|
1076 | colspan = 1 | |
| 1083 |
|
1077 | |||
| 1084 | self.createFigure(id = id, |
|
1078 | self.createFigure(id = id, | |
| 1085 | wintitle = wintitle, |
|
1079 | wintitle = wintitle, | |
| 1086 | widthplot = self.WIDTH, |
|
1080 | widthplot = self.WIDTH, | |
| 1087 | heightplot = self.HEIGHT, |
|
1081 | heightplot = self.HEIGHT, | |
| 1088 | show=show) |
|
1082 | show=show) | |
| 1089 |
|
1083 | |||
| 1090 | nrow, ncol = self.getSubplots() |
|
1084 | nrow, ncol = self.getSubplots() | |
| 1091 |
|
1085 | |||
| 1092 | counter = 0 |
|
1086 | counter = 0 | |
| 1093 | for y in range(nrow): |
|
1087 | for y in range(nrow): | |
| 1094 | for x in range(ncol): |
|
1088 | for x in range(ncol): | |
| 1095 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
1089 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
| 1096 |
|
1090 | |||
| 1097 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
1091 | def run(self, dataOut, id, wintitle="", channelList=None, | |
| 1098 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1092 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1099 | save=False, figpath='./', figfile=None, show=True, |
|
1093 | save=False, figpath='./', figfile=None, show=True, | |
| 1100 | ftp=False, wr_period=1, server=None, |
|
1094 | ftp=False, wr_period=1, server=None, | |
| 1101 | folder=None, username=None, password=None, |
|
1095 | folder=None, username=None, password=None, | |
| 1102 | xaxis="frequency"): |
|
1096 | xaxis="frequency"): | |
| 1103 |
|
1097 | |||
| 1104 |
|
1098 | |||
| 1105 | if channelList == None: |
|
1099 | if channelList == None: | |
| 1106 | channelIndexList = dataOut.channelIndexList |
|
1100 | channelIndexList = dataOut.channelIndexList | |
| 1107 | channelList = dataOut.channelList |
|
1101 | channelList = dataOut.channelList | |
| 1108 | else: |
|
1102 | else: | |
| 1109 | channelIndexList = [] |
|
1103 | channelIndexList = [] | |
| 1110 | for channel in channelList: |
|
1104 | for channel in channelList: | |
| 1111 | if channel not in dataOut.channelList: |
|
1105 | if channel not in dataOut.channelList: | |
| 1112 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
1106 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 1113 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
1107 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 1114 |
|
1108 | |||
| 1115 | factor = dataOut.normFactor |
|
1109 | factor = dataOut.normFactor | |
| 1116 |
|
1110 | |||
| 1117 | y = dataOut.getHeiRange() |
|
1111 | y = dataOut.getHeiRange() | |
| 1118 |
|
1112 | |||
| 1119 | z = dataOut.data_spc/factor |
|
1113 | z = dataOut.data_spc/factor | |
| 1120 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
1114 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 1121 |
|
1115 | |||
| 1122 | hei_index = numpy.arange(25)*3 + 20 |
|
1116 | hei_index = numpy.arange(25)*3 + 20 | |
| 1123 |
|
1117 | |||
| 1124 | if xaxis == "frequency": |
|
1118 | if xaxis == "frequency": | |
| 1125 | x = dataOut.getFreqRange()/1000. |
|
1119 | x = dataOut.getFreqRange()/1000. | |
| 1126 | zdB = 10*numpy.log10(z[0,:,hei_index]) |
|
1120 | zdB = 10*numpy.log10(z[0,:,hei_index]) | |
| 1127 | xlabel = "Frequency (kHz)" |
|
1121 | xlabel = "Frequency (kHz)" | |
| 1128 | ylabel = "Power (dB)" |
|
1122 | ylabel = "Power (dB)" | |
| 1129 |
|
1123 | |||
| 1130 | elif xaxis == "time": |
|
1124 | elif xaxis == "time": | |
| 1131 | x = dataOut.getAcfRange() |
|
1125 | x = dataOut.getAcfRange() | |
| 1132 | zdB = z[0,:,hei_index] |
|
1126 | zdB = z[0,:,hei_index] | |
| 1133 | xlabel = "Time (ms)" |
|
1127 | xlabel = "Time (ms)" | |
| 1134 | ylabel = "ACF" |
|
1128 | ylabel = "ACF" | |
| 1135 |
|
1129 | |||
| 1136 | else: |
|
1130 | else: | |
| 1137 | x = dataOut.getVelRange() |
|
1131 | x = dataOut.getVelRange() | |
| 1138 | zdB = 10*numpy.log10(z[0,:,hei_index]) |
|
1132 | zdB = 10*numpy.log10(z[0,:,hei_index]) | |
| 1139 | xlabel = "Velocity (m/s)" |
|
1133 | xlabel = "Velocity (m/s)" | |
| 1140 | ylabel = "Power (dB)" |
|
1134 | ylabel = "Power (dB)" | |
| 1141 |
|
1135 | |||
| 1142 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
1136 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
| 1143 | title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1137 | title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1144 |
|
1138 | |||
| 1145 | if not self.isConfig: |
|
1139 | if not self.isConfig: | |
| 1146 |
|
1140 | |||
| 1147 | nplots = 1 |
|
1141 | nplots = 1 | |
| 1148 |
|
1142 | |||
| 1149 | self.setup(id=id, |
|
1143 | self.setup(id=id, | |
| 1150 | nplots=nplots, |
|
1144 | nplots=nplots, | |
| 1151 | wintitle=wintitle, |
|
1145 | wintitle=wintitle, | |
| 1152 | show=show) |
|
1146 | show=show) | |
| 1153 |
|
1147 | |||
| 1154 | if xmin == None: xmin = numpy.nanmin(x)*0.9 |
|
1148 | if xmin == None: xmin = numpy.nanmin(x)*0.9 | |
| 1155 | if xmax == None: xmax = numpy.nanmax(x)*1.1 |
|
1149 | if xmax == None: xmax = numpy.nanmax(x)*1.1 | |
| 1156 | if ymin == None: ymin = numpy.nanmin(zdB) |
|
1150 | if ymin == None: ymin = numpy.nanmin(zdB) | |
| 1157 | if ymax == None: ymax = numpy.nanmax(zdB) |
|
1151 | if ymax == None: ymax = numpy.nanmax(zdB) | |
| 1158 |
|
1152 | |||
| 1159 | self.isConfig = True |
|
1153 | self.isConfig = True | |
| 1160 |
|
1154 | |||
| 1161 | self.setWinTitle(title) |
|
1155 | self.setWinTitle(title) | |
| 1162 |
|
1156 | |||
| 1163 | title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
1157 | title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
| 1164 | axes = self.axesList[0] |
|
1158 | axes = self.axesList[0] | |
| 1165 |
|
1159 | |||
| 1166 | legendlabels = ["Range = %dKm" %y[i] for i in hei_index] |
|
1160 | legendlabels = ["Range = %dKm" %y[i] for i in hei_index] | |
| 1167 |
|
1161 | |||
| 1168 | axes.pmultilineyaxis( x, zdB, |
|
1162 | axes.pmultilineyaxis( x, zdB, | |
| 1169 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
1163 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, | |
| 1170 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, |
|
1164 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, | |
| 1171 | ytick_visible=True, nxticks=5, |
|
1165 | ytick_visible=True, nxticks=5, | |
| 1172 | grid='x') |
|
1166 | grid='x') | |
| 1173 |
|
1167 | |||
| 1174 | self.draw() |
|
1168 | self.draw() | |
| 1175 |
|
1169 | |||
| 1176 | self.save(figpath=figpath, |
|
1170 | self.save(figpath=figpath, | |
| 1177 | figfile=figfile, |
|
1171 | figfile=figfile, | |
| 1178 | save=save, |
|
1172 | save=save, | |
| 1179 | ftp=ftp, |
|
1173 | ftp=ftp, | |
| 1180 | wr_period=wr_period, |
|
1174 | wr_period=wr_period, | |
| 1181 | thisDatetime=thisDatetime) |
|
1175 | thisDatetime=thisDatetime) | |
| 1182 |
|
1176 | |||
| 1183 | class Noise(Figure): |
|
1177 | class Noise(Figure): | |
| 1184 |
|
1178 | |||
| 1185 | isConfig = None |
|
1179 | isConfig = None | |
| 1186 | __nsubplots = None |
|
1180 | __nsubplots = None | |
| 1187 |
|
1181 | |||
| 1188 | PREFIX = 'noise' |
|
1182 | PREFIX = 'noise' | |
| 1189 |
|
1183 | |||
| 1190 |
|
1184 | |||
| 1191 | def __init__(self, **kwargs): |
|
1185 | def __init__(self, **kwargs): | |
| 1192 | Figure.__init__(self, **kwargs) |
|
1186 | Figure.__init__(self, **kwargs) | |
| 1193 | self.timerange = 24*60*60 |
|
1187 | self.timerange = 24*60*60 | |
| 1194 | self.isConfig = False |
|
1188 | self.isConfig = False | |
| 1195 | self.__nsubplots = 1 |
|
1189 | self.__nsubplots = 1 | |
| 1196 | self.counter_imagwr = 0 |
|
1190 | self.counter_imagwr = 0 | |
| 1197 | self.WIDTH = 800 |
|
1191 | self.WIDTH = 800 | |
| 1198 | self.HEIGHT = 400 |
|
1192 | self.HEIGHT = 400 | |
| 1199 | self.WIDTHPROF = 120 |
|
1193 | self.WIDTHPROF = 120 | |
| 1200 | self.HEIGHTPROF = 0 |
|
1194 | self.HEIGHTPROF = 0 | |
| 1201 | self.xdata = None |
|
1195 | self.xdata = None | |
| 1202 | self.ydata = None |
|
1196 | self.ydata = None | |
| 1203 |
|
1197 | |||
| 1204 | self.PLOT_CODE = NOISE_CODE |
|
1198 | self.PLOT_CODE = NOISE_CODE | |
| 1205 |
|
1199 | |||
| 1206 | self.FTP_WEI = None |
|
1200 | self.FTP_WEI = None | |
| 1207 | self.EXP_CODE = None |
|
1201 | self.EXP_CODE = None | |
| 1208 | self.SUB_EXP_CODE = None |
|
1202 | self.SUB_EXP_CODE = None | |
| 1209 | self.PLOT_POS = None |
|
1203 | self.PLOT_POS = None | |
| 1210 | self.figfile = None |
|
1204 | self.figfile = None | |
| 1211 |
|
1205 | |||
| 1212 | self.xmin = None |
|
1206 | self.xmin = None | |
| 1213 | self.xmax = None |
|
1207 | self.xmax = None | |
| 1214 |
|
1208 | |||
| 1215 | def getSubplots(self): |
|
1209 | def getSubplots(self): | |
| 1216 |
|
1210 | |||
| 1217 | ncol = 1 |
|
1211 | ncol = 1 | |
| 1218 | nrow = 1 |
|
1212 | nrow = 1 | |
| 1219 |
|
1213 | |||
| 1220 | return nrow, ncol |
|
1214 | return nrow, ncol | |
| 1221 |
|
1215 | |||
| 1222 | def openfile(self, filename): |
|
1216 | def openfile(self, filename): | |
| 1223 | dirname = os.path.dirname(filename) |
|
1217 | dirname = os.path.dirname(filename) | |
| 1224 |
|
1218 | |||
| 1225 | if not os.path.exists(dirname): |
|
1219 | if not os.path.exists(dirname): | |
| 1226 | os.mkdir(dirname) |
|
1220 | os.mkdir(dirname) | |
| 1227 |
|
1221 | |||
| 1228 | f = open(filename,'w+') |
|
1222 | f = open(filename,'w+') | |
| 1229 | f.write('\n\n') |
|
1223 | f.write('\n\n') | |
| 1230 | f.write('JICAMARCA RADIO OBSERVATORY - Noise \n') |
|
1224 | f.write('JICAMARCA RADIO OBSERVATORY - Noise \n') | |
| 1231 | f.write('DD MM YYYY HH MM SS Channel0 Channel1 Channel2 Channel3\n\n' ) |
|
1225 | f.write('DD MM YYYY HH MM SS Channel0 Channel1 Channel2 Channel3\n\n' ) | |
| 1232 | f.close() |
|
1226 | f.close() | |
| 1233 |
|
1227 | |||
| 1234 | def save_data(self, filename_phase, data, data_datetime): |
|
1228 | def save_data(self, filename_phase, data, data_datetime): | |
| 1235 |
|
1229 | |||
| 1236 | f=open(filename_phase,'a') |
|
1230 | f=open(filename_phase,'a') | |
| 1237 |
|
1231 | |||
| 1238 | timetuple_data = data_datetime.timetuple() |
|
1232 | timetuple_data = data_datetime.timetuple() | |
| 1239 | day = str(timetuple_data.tm_mday) |
|
1233 | day = str(timetuple_data.tm_mday) | |
| 1240 | month = str(timetuple_data.tm_mon) |
|
1234 | month = str(timetuple_data.tm_mon) | |
| 1241 | year = str(timetuple_data.tm_year) |
|
1235 | year = str(timetuple_data.tm_year) | |
| 1242 | hour = str(timetuple_data.tm_hour) |
|
1236 | hour = str(timetuple_data.tm_hour) | |
| 1243 | minute = str(timetuple_data.tm_min) |
|
1237 | minute = str(timetuple_data.tm_min) | |
| 1244 | second = str(timetuple_data.tm_sec) |
|
1238 | second = str(timetuple_data.tm_sec) | |
| 1245 |
|
1239 | |||
| 1246 | data_msg = '' |
|
1240 | data_msg = '' | |
| 1247 | for i in range(len(data)): |
|
1241 | for i in range(len(data)): | |
| 1248 | data_msg += str(data[i]) + ' ' |
|
1242 | data_msg += str(data[i]) + ' ' | |
| 1249 |
|
1243 | |||
| 1250 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' ' + data_msg + '\n') |
|
1244 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' ' + data_msg + '\n') | |
| 1251 | f.close() |
|
1245 | f.close() | |
| 1252 |
|
1246 | |||
| 1253 |
|
1247 | |||
| 1254 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1248 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1255 |
|
1249 | |||
| 1256 | self.__showprofile = showprofile |
|
1250 | self.__showprofile = showprofile | |
| 1257 | self.nplots = nplots |
|
1251 | self.nplots = nplots | |
| 1258 |
|
1252 | |||
| 1259 | ncolspan = 7 |
|
1253 | ncolspan = 7 | |
| 1260 | colspan = 6 |
|
1254 | colspan = 6 | |
| 1261 | self.__nsubplots = 2 |
|
1255 | self.__nsubplots = 2 | |
| 1262 |
|
1256 | |||
| 1263 | self.createFigure(id = id, |
|
1257 | self.createFigure(id = id, | |
| 1264 | wintitle = wintitle, |
|
1258 | wintitle = wintitle, | |
| 1265 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1259 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1266 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1260 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1267 | show=show) |
|
1261 | show=show) | |
| 1268 |
|
1262 | |||
| 1269 | nrow, ncol = self.getSubplots() |
|
1263 | nrow, ncol = self.getSubplots() | |
| 1270 |
|
1264 | |||
| 1271 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1265 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1272 |
|
1266 | |||
| 1273 |
|
1267 | |||
| 1274 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
1268 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', | |
| 1275 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
1269 | xmin=None, xmax=None, ymin=None, ymax=None, | |
| 1276 | timerange=None, |
|
1270 | timerange=None, | |
| 1277 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1271 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1278 | server=None, folder=None, username=None, password=None, |
|
1272 | server=None, folder=None, username=None, password=None, | |
| 1279 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1273 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1280 |
|
1274 | |||
| 1281 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
1275 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 1282 | return |
|
1276 | return | |
| 1283 |
|
1277 | |||
| 1284 | if channelList == None: |
|
1278 | if channelList == None: | |
| 1285 | channelIndexList = dataOut.channelIndexList |
|
1279 | channelIndexList = dataOut.channelIndexList | |
| 1286 | channelList = dataOut.channelList |
|
1280 | channelList = dataOut.channelList | |
| 1287 | else: |
|
1281 | else: | |
| 1288 | channelIndexList = [] |
|
1282 | channelIndexList = [] | |
| 1289 | for channel in channelList: |
|
1283 | for channel in channelList: | |
| 1290 | if channel not in dataOut.channelList: |
|
1284 | if channel not in dataOut.channelList: | |
| 1291 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
1285 | raise ValueError, "Channel %d is not in dataOut.channelList" | |
| 1292 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
1286 | channelIndexList.append(dataOut.channelList.index(channel)) | |
| 1293 |
|
1287 | |||
| 1294 | x = dataOut.getTimeRange() |
|
1288 | x = dataOut.getTimeRange() | |
| 1295 | #y = dataOut.getHeiRange() |
|
1289 | #y = dataOut.getHeiRange() | |
| 1296 | factor = dataOut.normFactor |
|
1290 | factor = dataOut.normFactor | |
| 1297 | noise = dataOut.noise[channelIndexList]/factor |
|
1291 | noise = dataOut.noise[channelIndexList]/factor | |
| 1298 | noisedB = 10*numpy.log10(noise) |
|
1292 | noisedB = 10*numpy.log10(noise) | |
| 1299 |
|
1293 | |||
| 1300 | thisDatetime = dataOut.datatime |
|
1294 | thisDatetime = dataOut.datatime | |
| 1301 |
|
1295 | |||
| 1302 | title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1296 | title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1303 | xlabel = "" |
|
1297 | xlabel = "" | |
| 1304 | ylabel = "Intensity (dB)" |
|
1298 | ylabel = "Intensity (dB)" | |
| 1305 | update_figfile = False |
|
1299 | update_figfile = False | |
| 1306 |
|
1300 | |||
| 1307 | if not self.isConfig: |
|
1301 | if not self.isConfig: | |
| 1308 |
|
1302 | |||
| 1309 | nplots = 1 |
|
1303 | nplots = 1 | |
| 1310 |
|
1304 | |||
| 1311 | self.setup(id=id, |
|
1305 | self.setup(id=id, | |
| 1312 | nplots=nplots, |
|
1306 | nplots=nplots, | |
| 1313 | wintitle=wintitle, |
|
1307 | wintitle=wintitle, | |
| 1314 | showprofile=showprofile, |
|
1308 | showprofile=showprofile, | |
| 1315 | show=show) |
|
1309 | show=show) | |
| 1316 |
|
1310 | |||
| 1317 | if timerange != None: |
|
1311 | if timerange != None: | |
| 1318 | self.timerange = timerange |
|
1312 | self.timerange = timerange | |
| 1319 |
|
1313 | |||
| 1320 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1314 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1321 |
|
1315 | |||
| 1322 | if ymin == None: ymin = numpy.floor(numpy.nanmin(noisedB)) - 10.0 |
|
1316 | if ymin == None: ymin = numpy.floor(numpy.nanmin(noisedB)) - 10.0 | |
| 1323 | if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0 |
|
1317 | if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0 | |
| 1324 |
|
1318 | |||
| 1325 | self.FTP_WEI = ftp_wei |
|
1319 | self.FTP_WEI = ftp_wei | |
| 1326 | self.EXP_CODE = exp_code |
|
1320 | self.EXP_CODE = exp_code | |
| 1327 | self.SUB_EXP_CODE = sub_exp_code |
|
1321 | self.SUB_EXP_CODE = sub_exp_code | |
| 1328 | self.PLOT_POS = plot_pos |
|
1322 | self.PLOT_POS = plot_pos | |
| 1329 |
|
1323 | |||
| 1330 |
|
1324 | |||
| 1331 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1325 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1332 | self.isConfig = True |
|
1326 | self.isConfig = True | |
| 1333 | self.figfile = figfile |
|
1327 | self.figfile = figfile | |
| 1334 | self.xdata = numpy.array([]) |
|
1328 | self.xdata = numpy.array([]) | |
| 1335 | self.ydata = numpy.array([]) |
|
1329 | self.ydata = numpy.array([]) | |
| 1336 |
|
1330 | |||
| 1337 | update_figfile = True |
|
1331 | update_figfile = True | |
| 1338 |
|
1332 | |||
| 1339 | #open file beacon phase |
|
1333 | #open file beacon phase | |
| 1340 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1334 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1341 | noise_file = os.path.join(path,'%s.txt'%self.name) |
|
1335 | noise_file = os.path.join(path,'%s.txt'%self.name) | |
| 1342 | self.filename_noise = os.path.join(figpath,noise_file) |
|
1336 | self.filename_noise = os.path.join(figpath,noise_file) | |
| 1343 |
|
1337 | |||
| 1344 | self.setWinTitle(title) |
|
1338 | self.setWinTitle(title) | |
| 1345 |
|
1339 | |||
| 1346 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1340 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1347 |
|
1341 | |||
| 1348 | legendlabels = ["channel %d"%(idchannel) for idchannel in channelList] |
|
1342 | legendlabels = ["channel %d"%(idchannel) for idchannel in channelList] | |
| 1349 | axes = self.axesList[0] |
|
1343 | axes = self.axesList[0] | |
| 1350 |
|
1344 | |||
| 1351 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1345 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1352 |
|
1346 | |||
| 1353 | if len(self.ydata)==0: |
|
1347 | if len(self.ydata)==0: | |
| 1354 | self.ydata = noisedB.reshape(-1,1) |
|
1348 | self.ydata = noisedB.reshape(-1,1) | |
| 1355 | else: |
|
1349 | else: | |
| 1356 | self.ydata = numpy.hstack((self.ydata, noisedB.reshape(-1,1))) |
|
1350 | self.ydata = numpy.hstack((self.ydata, noisedB.reshape(-1,1))) | |
| 1357 |
|
1351 | |||
| 1358 |
|
1352 | |||
| 1359 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1353 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1360 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1354 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1361 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1355 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1362 | XAxisAsTime=True, grid='both' |
|
1356 | XAxisAsTime=True, grid='both' | |
| 1363 | ) |
|
1357 | ) | |
| 1364 |
|
1358 | |||
| 1365 | self.draw() |
|
1359 | self.draw() | |
| 1366 |
|
1360 | |||
| 1367 | if dataOut.ltctime >= self.xmax: |
|
1361 | if dataOut.ltctime >= self.xmax: | |
| 1368 | self.counter_imagwr = wr_period |
|
1362 | self.counter_imagwr = wr_period | |
| 1369 | self.isConfig = False |
|
1363 | self.isConfig = False | |
| 1370 | update_figfile = True |
|
1364 | update_figfile = True | |
| 1371 |
|
1365 | |||
| 1372 | self.save(figpath=figpath, |
|
1366 | self.save(figpath=figpath, | |
| 1373 | figfile=figfile, |
|
1367 | figfile=figfile, | |
| 1374 | save=save, |
|
1368 | save=save, | |
| 1375 | ftp=ftp, |
|
1369 | ftp=ftp, | |
| 1376 | wr_period=wr_period, |
|
1370 | wr_period=wr_period, | |
| 1377 | thisDatetime=thisDatetime, |
|
1371 | thisDatetime=thisDatetime, | |
| 1378 | update_figfile=update_figfile) |
|
1372 | update_figfile=update_figfile) | |
| 1379 |
|
1373 | |||
| 1380 | #store data beacon phase |
|
1374 | #store data beacon phase | |
| 1381 | if save: |
|
1375 | if save: | |
| 1382 | self.save_data(self.filename_noise, noisedB, thisDatetime) |
|
1376 | self.save_data(self.filename_noise, noisedB, thisDatetime) | |
| 1383 |
|
1377 | |||
| 1384 | class BeaconPhase(Figure): |
|
1378 | class BeaconPhase(Figure): | |
| 1385 |
|
1379 | |||
| 1386 | __isConfig = None |
|
1380 | __isConfig = None | |
| 1387 | __nsubplots = None |
|
1381 | __nsubplots = None | |
| 1388 |
|
1382 | |||
| 1389 | PREFIX = 'beacon_phase' |
|
1383 | PREFIX = 'beacon_phase' | |
| 1390 |
|
1384 | |||
| 1391 | def __init__(self, **kwargs): |
|
1385 | def __init__(self, **kwargs): | |
| 1392 | Figure.__init__(self, **kwargs) |
|
1386 | Figure.__init__(self, **kwargs) | |
| 1393 | self.timerange = 24*60*60 |
|
1387 | self.timerange = 24*60*60 | |
| 1394 | self.isConfig = False |
|
1388 | self.isConfig = False | |
| 1395 | self.__nsubplots = 1 |
|
1389 | self.__nsubplots = 1 | |
| 1396 | self.counter_imagwr = 0 |
|
1390 | self.counter_imagwr = 0 | |
| 1397 | self.WIDTH = 800 |
|
1391 | self.WIDTH = 800 | |
| 1398 | self.HEIGHT = 400 |
|
1392 | self.HEIGHT = 400 | |
| 1399 | self.WIDTHPROF = 120 |
|
1393 | self.WIDTHPROF = 120 | |
| 1400 | self.HEIGHTPROF = 0 |
|
1394 | self.HEIGHTPROF = 0 | |
| 1401 | self.xdata = None |
|
1395 | self.xdata = None | |
| 1402 | self.ydata = None |
|
1396 | self.ydata = None | |
| 1403 |
|
1397 | |||
| 1404 | self.PLOT_CODE = BEACON_CODE |
|
1398 | self.PLOT_CODE = BEACON_CODE | |
| 1405 |
|
1399 | |||
| 1406 | self.FTP_WEI = None |
|
1400 | self.FTP_WEI = None | |
| 1407 | self.EXP_CODE = None |
|
1401 | self.EXP_CODE = None | |
| 1408 | self.SUB_EXP_CODE = None |
|
1402 | self.SUB_EXP_CODE = None | |
| 1409 | self.PLOT_POS = None |
|
1403 | self.PLOT_POS = None | |
| 1410 |
|
1404 | |||
| 1411 | self.filename_phase = None |
|
1405 | self.filename_phase = None | |
| 1412 |
|
1406 | |||
| 1413 | self.figfile = None |
|
1407 | self.figfile = None | |
| 1414 |
|
1408 | |||
| 1415 | self.xmin = None |
|
1409 | self.xmin = None | |
| 1416 | self.xmax = None |
|
1410 | self.xmax = None | |
| 1417 |
|
1411 | |||
| 1418 | def getSubplots(self): |
|
1412 | def getSubplots(self): | |
| 1419 |
|
1413 | |||
| 1420 | ncol = 1 |
|
1414 | ncol = 1 | |
| 1421 | nrow = 1 |
|
1415 | nrow = 1 | |
| 1422 |
|
1416 | |||
| 1423 | return nrow, ncol |
|
1417 | return nrow, ncol | |
| 1424 |
|
1418 | |||
| 1425 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
1419 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
| 1426 |
|
1420 | |||
| 1427 | self.__showprofile = showprofile |
|
1421 | self.__showprofile = showprofile | |
| 1428 | self.nplots = nplots |
|
1422 | self.nplots = nplots | |
| 1429 |
|
1423 | |||
| 1430 | ncolspan = 7 |
|
1424 | ncolspan = 7 | |
| 1431 | colspan = 6 |
|
1425 | colspan = 6 | |
| 1432 | self.__nsubplots = 2 |
|
1426 | self.__nsubplots = 2 | |
| 1433 |
|
1427 | |||
| 1434 | self.createFigure(id = id, |
|
1428 | self.createFigure(id = id, | |
| 1435 | wintitle = wintitle, |
|
1429 | wintitle = wintitle, | |
| 1436 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
1430 | widthplot = self.WIDTH+self.WIDTHPROF, | |
| 1437 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
1431 | heightplot = self.HEIGHT+self.HEIGHTPROF, | |
| 1438 | show=show) |
|
1432 | show=show) | |
| 1439 |
|
1433 | |||
| 1440 | nrow, ncol = self.getSubplots() |
|
1434 | nrow, ncol = self.getSubplots() | |
| 1441 |
|
1435 | |||
| 1442 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
1436 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) | |
| 1443 |
|
1437 | |||
| 1444 | def save_phase(self, filename_phase): |
|
1438 | def save_phase(self, filename_phase): | |
| 1445 | f = open(filename_phase,'w+') |
|
1439 | f = open(filename_phase,'w+') | |
| 1446 | f.write('\n\n') |
|
1440 | f.write('\n\n') | |
| 1447 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') |
|
1441 | f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n') | |
| 1448 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) |
|
1442 | f.write('DD MM YYYY HH MM SS pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' ) | |
| 1449 | f.close() |
|
1443 | f.close() | |
| 1450 |
|
1444 | |||
| 1451 | def save_data(self, filename_phase, data, data_datetime): |
|
1445 | def save_data(self, filename_phase, data, data_datetime): | |
| 1452 | f=open(filename_phase,'a') |
|
1446 | f=open(filename_phase,'a') | |
| 1453 | timetuple_data = data_datetime.timetuple() |
|
1447 | timetuple_data = data_datetime.timetuple() | |
| 1454 | day = str(timetuple_data.tm_mday) |
|
1448 | day = str(timetuple_data.tm_mday) | |
| 1455 | month = str(timetuple_data.tm_mon) |
|
1449 | month = str(timetuple_data.tm_mon) | |
| 1456 | year = str(timetuple_data.tm_year) |
|
1450 | year = str(timetuple_data.tm_year) | |
| 1457 | hour = str(timetuple_data.tm_hour) |
|
1451 | hour = str(timetuple_data.tm_hour) | |
| 1458 | minute = str(timetuple_data.tm_min) |
|
1452 | minute = str(timetuple_data.tm_min) | |
| 1459 | second = str(timetuple_data.tm_sec) |
|
1453 | second = str(timetuple_data.tm_sec) | |
| 1460 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') |
|
1454 | f.write(day+' '+month+' '+year+' '+hour+' '+minute+' '+second+' '+str(data[0])+' '+str(data[1])+' '+str(data[2])+' '+str(data[3])+'\n') | |
| 1461 | f.close() |
|
1455 | f.close() | |
| 1462 |
|
1456 | |||
| 1463 |
|
1457 | |||
| 1464 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', |
|
1458 | def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True', | |
| 1465 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, |
|
1459 | xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None, | |
| 1466 | timerange=None, |
|
1460 | timerange=None, | |
| 1467 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
1461 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
| 1468 | server=None, folder=None, username=None, password=None, |
|
1462 | server=None, folder=None, username=None, password=None, | |
| 1469 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
1463 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
| 1470 |
|
1464 | |||
| 1471 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
1465 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): | |
| 1472 | return |
|
1466 | return | |
| 1473 |
|
1467 | |||
| 1474 | if pairsList == None: |
|
1468 | if pairsList == None: | |
| 1475 | pairsIndexList = dataOut.pairsIndexList[:10] |
|
1469 | pairsIndexList = dataOut.pairsIndexList[:10] | |
| 1476 | else: |
|
1470 | else: | |
| 1477 | pairsIndexList = [] |
|
1471 | pairsIndexList = [] | |
| 1478 | for pair in pairsList: |
|
1472 | for pair in pairsList: | |
| 1479 | if pair not in dataOut.pairsList: |
|
1473 | if pair not in dataOut.pairsList: | |
| 1480 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) |
|
1474 | raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair) | |
| 1481 | pairsIndexList.append(dataOut.pairsList.index(pair)) |
|
1475 | pairsIndexList.append(dataOut.pairsList.index(pair)) | |
| 1482 |
|
1476 | |||
| 1483 | if pairsIndexList == []: |
|
1477 | if pairsIndexList == []: | |
| 1484 | return |
|
1478 | return | |
| 1485 |
|
1479 | |||
| 1486 | # if len(pairsIndexList) > 4: |
|
1480 | # if len(pairsIndexList) > 4: | |
| 1487 | # pairsIndexList = pairsIndexList[0:4] |
|
1481 | # pairsIndexList = pairsIndexList[0:4] | |
| 1488 |
|
1482 | |||
| 1489 | hmin_index = None |
|
1483 | hmin_index = None | |
| 1490 | hmax_index = None |
|
1484 | hmax_index = None | |
| 1491 |
|
1485 | |||
| 1492 | if hmin != None and hmax != None: |
|
1486 | if hmin != None and hmax != None: | |
| 1493 | indexes = numpy.arange(dataOut.nHeights) |
|
1487 | indexes = numpy.arange(dataOut.nHeights) | |
| 1494 | hmin_list = indexes[dataOut.heightList >= hmin] |
|
1488 | hmin_list = indexes[dataOut.heightList >= hmin] | |
| 1495 | hmax_list = indexes[dataOut.heightList <= hmax] |
|
1489 | hmax_list = indexes[dataOut.heightList <= hmax] | |
| 1496 |
|
1490 | |||
| 1497 | if hmin_list.any(): |
|
1491 | if hmin_list.any(): | |
| 1498 | hmin_index = hmin_list[0] |
|
1492 | hmin_index = hmin_list[0] | |
| 1499 |
|
1493 | |||
| 1500 | if hmax_list.any(): |
|
1494 | if hmax_list.any(): | |
| 1501 | hmax_index = hmax_list[-1]+1 |
|
1495 | hmax_index = hmax_list[-1]+1 | |
| 1502 |
|
1496 | |||
| 1503 | x = dataOut.getTimeRange() |
|
1497 | x = dataOut.getTimeRange() | |
| 1504 | #y = dataOut.getHeiRange() |
|
1498 | #y = dataOut.getHeiRange() | |
| 1505 |
|
1499 | |||
| 1506 |
|
1500 | |||
| 1507 | thisDatetime = dataOut.datatime |
|
1501 | thisDatetime = dataOut.datatime | |
| 1508 |
|
1502 | |||
| 1509 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
1503 | title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
| 1510 | xlabel = "Local Time" |
|
1504 | xlabel = "Local Time" | |
| 1511 | ylabel = "Phase (degrees)" |
|
1505 | ylabel = "Phase (degrees)" | |
| 1512 |
|
1506 | |||
| 1513 | update_figfile = False |
|
1507 | update_figfile = False | |
| 1514 |
|
1508 | |||
| 1515 | nplots = len(pairsIndexList) |
|
1509 | nplots = len(pairsIndexList) | |
| 1516 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) |
|
1510 | #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList))) | |
| 1517 | phase_beacon = numpy.zeros(len(pairsIndexList)) |
|
1511 | phase_beacon = numpy.zeros(len(pairsIndexList)) | |
| 1518 | for i in range(nplots): |
|
1512 | for i in range(nplots): | |
| 1519 | pair = dataOut.pairsList[pairsIndexList[i]] |
|
1513 | pair = dataOut.pairsList[pairsIndexList[i]] | |
| 1520 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) |
|
1514 | ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0) | |
| 1521 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) |
|
1515 | powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0) | |
| 1522 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) |
|
1516 | powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0) | |
| 1523 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) |
|
1517 | avgcoherenceComplex = ccf/numpy.sqrt(powa*powb) | |
| 1524 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi |
|
1518 | phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi | |
| 1525 |
|
1519 | |||
| 1526 | #print "Phase %d%d" %(pair[0], pair[1]) |
|
1520 | #print "Phase %d%d" %(pair[0], pair[1]) | |
| 1527 | #print phase[dataOut.beacon_heiIndexList] |
|
1521 | #print phase[dataOut.beacon_heiIndexList] | |
| 1528 |
|
1522 | |||
| 1529 | if dataOut.beacon_heiIndexList: |
|
1523 | if dataOut.beacon_heiIndexList: | |
| 1530 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) |
|
1524 | phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList]) | |
| 1531 | else: |
|
1525 | else: | |
| 1532 | phase_beacon[i] = numpy.average(phase) |
|
1526 | phase_beacon[i] = numpy.average(phase) | |
| 1533 |
|
1527 | |||
| 1534 | if not self.isConfig: |
|
1528 | if not self.isConfig: | |
| 1535 |
|
1529 | |||
| 1536 | nplots = len(pairsIndexList) |
|
1530 | nplots = len(pairsIndexList) | |
| 1537 |
|
1531 | |||
| 1538 | self.setup(id=id, |
|
1532 | self.setup(id=id, | |
| 1539 | nplots=nplots, |
|
1533 | nplots=nplots, | |
| 1540 | wintitle=wintitle, |
|
1534 | wintitle=wintitle, | |
| 1541 | showprofile=showprofile, |
|
1535 | showprofile=showprofile, | |
| 1542 | show=show) |
|
1536 | show=show) | |
| 1543 |
|
1537 | |||
| 1544 | if timerange != None: |
|
1538 | if timerange != None: | |
| 1545 | self.timerange = timerange |
|
1539 | self.timerange = timerange | |
| 1546 |
|
1540 | |||
| 1547 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) |
|
1541 | self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange) | |
| 1548 |
|
1542 | |||
| 1549 | if ymin == None: ymin = 0 |
|
1543 | if ymin == None: ymin = 0 | |
| 1550 | if ymax == None: ymax = 360 |
|
1544 | if ymax == None: ymax = 360 | |
| 1551 |
|
1545 | |||
| 1552 | self.FTP_WEI = ftp_wei |
|
1546 | self.FTP_WEI = ftp_wei | |
| 1553 | self.EXP_CODE = exp_code |
|
1547 | self.EXP_CODE = exp_code | |
| 1554 | self.SUB_EXP_CODE = sub_exp_code |
|
1548 | self.SUB_EXP_CODE = sub_exp_code | |
| 1555 | self.PLOT_POS = plot_pos |
|
1549 | self.PLOT_POS = plot_pos | |
| 1556 |
|
1550 | |||
| 1557 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
1551 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
| 1558 | self.isConfig = True |
|
1552 | self.isConfig = True | |
| 1559 | self.figfile = figfile |
|
1553 | self.figfile = figfile | |
| 1560 | self.xdata = numpy.array([]) |
|
1554 | self.xdata = numpy.array([]) | |
| 1561 | self.ydata = numpy.array([]) |
|
1555 | self.ydata = numpy.array([]) | |
| 1562 |
|
1556 | |||
| 1563 | update_figfile = True |
|
1557 | update_figfile = True | |
| 1564 |
|
1558 | |||
| 1565 | #open file beacon phase |
|
1559 | #open file beacon phase | |
| 1566 | path = '%s%03d' %(self.PREFIX, self.id) |
|
1560 | path = '%s%03d' %(self.PREFIX, self.id) | |
| 1567 | beacon_file = os.path.join(path,'%s.txt'%self.name) |
|
1561 | beacon_file = os.path.join(path,'%s.txt'%self.name) | |
| 1568 | self.filename_phase = os.path.join(figpath,beacon_file) |
|
1562 | self.filename_phase = os.path.join(figpath,beacon_file) | |
| 1569 | #self.save_phase(self.filename_phase) |
|
1563 | #self.save_phase(self.filename_phase) | |
| 1570 |
|
1564 | |||
| 1571 |
|
1565 | |||
| 1572 | #store data beacon phase |
|
1566 | #store data beacon phase | |
| 1573 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) |
|
1567 | #self.save_data(self.filename_phase, phase_beacon, thisDatetime) | |
| 1574 |
|
1568 | |||
| 1575 | self.setWinTitle(title) |
|
1569 | self.setWinTitle(title) | |
| 1576 |
|
1570 | |||
| 1577 |
|
1571 | |||
| 1578 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
|
1572 | title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
| 1579 |
|
1573 | |||
| 1580 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] |
|
1574 | legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList] | |
| 1581 |
|
1575 | |||
| 1582 | axes = self.axesList[0] |
|
1576 | axes = self.axesList[0] | |
| 1583 |
|
1577 | |||
| 1584 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
1578 | self.xdata = numpy.hstack((self.xdata, x[0:1])) | |
| 1585 |
|
1579 | |||
| 1586 | if len(self.ydata)==0: |
|
1580 | if len(self.ydata)==0: | |
| 1587 | self.ydata = phase_beacon.reshape(-1,1) |
|
1581 | self.ydata = phase_beacon.reshape(-1,1) | |
| 1588 | else: |
|
1582 | else: | |
| 1589 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) |
|
1583 | self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1))) | |
| 1590 |
|
1584 | |||
| 1591 |
|
1585 | |||
| 1592 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
1586 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, | |
| 1593 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, |
|
1587 | xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, | |
| 1594 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", |
|
1588 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid", | |
| 1595 | XAxisAsTime=True, grid='both' |
|
1589 | XAxisAsTime=True, grid='both' | |
| 1596 | ) |
|
1590 | ) | |
| 1597 |
|
1591 | |||
| 1598 | self.draw() |
|
1592 | self.draw() | |
| 1599 |
|
1593 | |||
| 1600 | if dataOut.ltctime >= self.xmax: |
|
1594 | if dataOut.ltctime >= self.xmax: | |
| 1601 | self.counter_imagwr = wr_period |
|
1595 | self.counter_imagwr = wr_period | |
| 1602 | self.isConfig = False |
|
1596 | self.isConfig = False | |
| 1603 | update_figfile = True |
|
1597 | update_figfile = True | |
| 1604 |
|
1598 | |||
| 1605 | self.save(figpath=figpath, |
|
1599 | self.save(figpath=figpath, | |
| 1606 | figfile=figfile, |
|
1600 | figfile=figfile, | |
| 1607 | save=save, |
|
1601 | save=save, | |
| 1608 | ftp=ftp, |
|
1602 | ftp=ftp, | |
| 1609 | wr_period=wr_period, |
|
1603 | wr_period=wr_period, | |
| 1610 | thisDatetime=thisDatetime, |
|
1604 | thisDatetime=thisDatetime, | |
| 1611 | update_figfile=update_figfile) |
|
1605 | update_figfile=update_figfile) | |
| @@ -1,3863 +1,3982 | |||||
| 1 | import numpy |
|
1 | import numpy | |
| 2 | import math |
|
2 | import math | |
| 3 | from scipy import optimize, interpolate, signal, stats, ndimage |
|
3 | from scipy import optimize, interpolate, signal, stats, ndimage | |
| 4 | import scipy |
|
4 | import scipy | |
| 5 | import re |
|
5 | import re | |
| 6 | import datetime |
|
6 | import datetime | |
| 7 | import copy |
|
7 | import copy | |
| 8 | import sys |
|
8 | import sys | |
| 9 | import importlib |
|
9 | import importlib | |
| 10 | import itertools |
|
10 | import itertools | |
| 11 | from multiprocessing import Pool, TimeoutError |
|
11 | from multiprocessing import Pool, TimeoutError | |
| 12 | from multiprocessing.pool import ThreadPool |
|
12 | from multiprocessing.pool import ThreadPool | |
| 13 | import copy_reg |
|
13 | import copy_reg | |
| 14 | import cPickle |
|
14 | import cPickle | |
| 15 | import types |
|
15 | import types | |
| 16 | from functools import partial |
|
16 | from functools import partial | |
| 17 | import time |
|
17 | import time | |
| 18 | #from sklearn.cluster import KMeans |
|
18 | #from sklearn.cluster import KMeans | |
| 19 |
|
19 | |||
| 20 | import matplotlib.pyplot as plt |
|
20 | import matplotlib.pyplot as plt | |
| 21 |
|
21 | |||
| 22 | from scipy.optimize import fmin_l_bfgs_b #optimize with bounds on state papameters |
|
22 | from scipy.optimize import fmin_l_bfgs_b #optimize with bounds on state papameters | |
| 23 | from jroproc_base import ProcessingUnit, Operation |
|
23 | from jroproc_base import ProcessingUnit, Operation | |
| 24 | from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon |
|
24 | from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon | |
| 25 | from scipy import asarray as ar,exp |
|
25 | from scipy import asarray as ar,exp | |
| 26 | from scipy.optimize import curve_fit |
|
26 | from scipy.optimize import curve_fit | |
| 27 |
|
27 | |||
| 28 | import warnings |
|
28 | import warnings | |
| 29 | from numpy import NaN |
|
29 | from numpy import NaN | |
| 30 | from scipy.optimize.optimize import OptimizeWarning |
|
30 | from scipy.optimize.optimize import OptimizeWarning | |
|
|
31 | from IPython.parallel.controller.scheduler import numpy | |||
| 31 | warnings.filterwarnings('ignore') |
|
32 | warnings.filterwarnings('ignore') | |
| 32 |
|
33 | |||
| 33 |
|
34 | |||
| 34 | SPEED_OF_LIGHT = 299792458 |
|
35 | SPEED_OF_LIGHT = 299792458 | |
| 35 |
|
36 | |||
| 36 |
|
37 | |||
| 37 | '''solving pickling issue''' |
|
38 | '''solving pickling issue''' | |
| 38 |
|
39 | |||
| 39 | def _pickle_method(method): |
|
40 | def _pickle_method(method): | |
| 40 | func_name = method.im_func.__name__ |
|
41 | func_name = method.im_func.__name__ | |
| 41 | obj = method.im_self |
|
42 | obj = method.im_self | |
| 42 | cls = method.im_class |
|
43 | cls = method.im_class | |
| 43 | return _unpickle_method, (func_name, obj, cls) |
|
44 | return _unpickle_method, (func_name, obj, cls) | |
| 44 |
|
45 | |||
| 45 | def _unpickle_method(func_name, obj, cls): |
|
46 | def _unpickle_method(func_name, obj, cls): | |
| 46 | for cls in cls.mro(): |
|
47 | for cls in cls.mro(): | |
| 47 | try: |
|
48 | try: | |
| 48 | func = cls.__dict__[func_name] |
|
49 | func = cls.__dict__[func_name] | |
| 49 | except KeyError: |
|
50 | except KeyError: | |
| 50 | pass |
|
51 | pass | |
| 51 | else: |
|
52 | else: | |
| 52 | break |
|
53 | break | |
| 53 | return func.__get__(obj, cls) |
|
54 | return func.__get__(obj, cls) | |
| 54 |
|
55 | |||
| 55 | class ParametersProc(ProcessingUnit): |
|
56 | class ParametersProc(ProcessingUnit): | |
| 56 |
|
57 | |||
| 57 | nSeconds = None |
|
58 | nSeconds = None | |
| 58 |
|
59 | |||
| 59 | def __init__(self): |
|
60 | def __init__(self): | |
| 60 | ProcessingUnit.__init__(self) |
|
61 | ProcessingUnit.__init__(self) | |
| 61 |
|
62 | |||
| 62 | # self.objectDict = {} |
|
63 | # self.objectDict = {} | |
| 63 | self.buffer = None |
|
64 | self.buffer = None | |
| 64 | self.firstdatatime = None |
|
65 | self.firstdatatime = None | |
| 65 | self.profIndex = 0 |
|
66 | self.profIndex = 0 | |
| 66 | self.dataOut = Parameters() |
|
67 | self.dataOut = Parameters() | |
| 67 |
|
68 | |||
| 68 | def __updateObjFromInput(self): |
|
69 | def __updateObjFromInput(self): | |
| 69 |
|
70 | |||
| 70 | self.dataOut.inputUnit = self.dataIn.type |
|
71 | self.dataOut.inputUnit = self.dataIn.type | |
| 71 |
|
72 | |||
| 72 | self.dataOut.timeZone = self.dataIn.timeZone |
|
73 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 73 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
74 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 74 | self.dataOut.errorCount = self.dataIn.errorCount |
|
75 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 75 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
76 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 76 |
|
77 | |||
| 77 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
78 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 78 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
79 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 79 | self.dataOut.channelList = self.dataIn.channelList |
|
80 | self.dataOut.channelList = self.dataIn.channelList | |
| 80 | self.dataOut.heightList = self.dataIn.heightList |
|
81 | self.dataOut.heightList = self.dataIn.heightList | |
| 81 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
82 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 82 | # self.dataOut.nHeights = self.dataIn.nHeights |
|
83 | # self.dataOut.nHeights = self.dataIn.nHeights | |
| 83 | # self.dataOut.nChannels = self.dataIn.nChannels |
|
84 | # self.dataOut.nChannels = self.dataIn.nChannels | |
| 84 | self.dataOut.nBaud = self.dataIn.nBaud |
|
85 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 85 | self.dataOut.nCode = self.dataIn.nCode |
|
86 | self.dataOut.nCode = self.dataIn.nCode | |
| 86 | self.dataOut.code = self.dataIn.code |
|
87 | self.dataOut.code = self.dataIn.code | |
| 87 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
88 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 88 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
89 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 89 | # self.dataOut.utctime = self.firstdatatime |
|
90 | # self.dataOut.utctime = self.firstdatatime | |
| 90 | self.dataOut.utctime = self.dataIn.utctime |
|
91 | self.dataOut.utctime = self.dataIn.utctime | |
| 91 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
92 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |
| 92 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
93 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |
| 93 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
94 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 94 | # self.dataOut.nIncohInt = 1 |
|
95 | # self.dataOut.nIncohInt = 1 | |
| 95 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
96 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 96 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
97 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 97 | self.dataOut.timeInterval1 = self.dataIn.timeInterval |
|
98 | self.dataOut.timeInterval1 = self.dataIn.timeInterval | |
| 98 | self.dataOut.heightList = self.dataIn.getHeiRange() |
|
99 | self.dataOut.heightList = self.dataIn.getHeiRange() | |
| 99 | self.dataOut.frequency = self.dataIn.frequency |
|
100 | self.dataOut.frequency = self.dataIn.frequency | |
| 100 | self.dataOut.noise = self.dataIn.noise |
|
101 | self.dataOut.noise = self.dataIn.noise | |
| 101 |
|
102 | |||
| 102 |
|
103 | |||
| 103 |
|
104 | |||
| 104 | def run(self): |
|
105 | def run(self): | |
| 105 |
|
106 | |||
| 106 | #---------------------- Voltage Data --------------------------- |
|
107 | #---------------------- Voltage Data --------------------------- | |
| 107 |
|
108 | |||
| 108 | if self.dataIn.type == "Voltage": |
|
109 | if self.dataIn.type == "Voltage": | |
| 109 |
|
110 | |||
| 110 | self.__updateObjFromInput() |
|
111 | self.__updateObjFromInput() | |
| 111 | self.dataOut.data_pre = self.dataIn.data.copy() |
|
112 | self.dataOut.data_pre = self.dataIn.data.copy() | |
| 112 | self.dataOut.flagNoData = False |
|
113 | self.dataOut.flagNoData = False | |
| 113 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
114 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 114 | self.dataOut.paramInterval = self.dataIn.nProfiles*self.dataIn.nCohInt*self.dataIn.ippSeconds |
|
115 | self.dataOut.paramInterval = self.dataIn.nProfiles*self.dataIn.nCohInt*self.dataIn.ippSeconds | |
| 115 | return |
|
116 | return | |
| 116 |
|
117 | |||
| 117 | #---------------------- Spectra Data --------------------------- |
|
118 | #---------------------- Spectra Data --------------------------- | |
| 118 |
|
119 | |||
| 119 | if self.dataIn.type == "Spectra": |
|
120 | if self.dataIn.type == "Spectra": | |
| 120 |
|
121 | |||
| 121 | self.dataOut.data_pre = (self.dataIn.data_spc , self.dataIn.data_cspc) |
|
122 | self.dataOut.data_pre = (self.dataIn.data_spc , self.dataIn.data_cspc) | |
| 122 | print 'self.dataIn.data_spc', self.dataIn.data_spc.shape |
|
123 | print 'self.dataIn.data_spc', self.dataIn.data_spc.shape | |
| 123 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) |
|
124 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) | |
| 124 | self.dataOut.spc_noise = self.dataIn.getNoise() |
|
125 | self.dataOut.spc_noise = self.dataIn.getNoise() | |
| 125 | self.dataOut.spc_range = (self.dataIn.getFreqRange(1) , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1) ) |
|
126 | self.dataOut.spc_range = numpy.asanyarray((self.dataIn.getFreqRange(1) , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1) )) | |
| 126 |
|
127 | |||
| 127 | self.dataOut.normFactor = self.dataIn.normFactor |
|
128 | self.dataOut.normFactor = self.dataIn.normFactor | |
| 128 | #self.dataOut.outputInterval = self.dataIn.outputInterval |
|
129 | #self.dataOut.outputInterval = self.dataIn.outputInterval | |
| 129 | self.dataOut.groupList = self.dataIn.pairsList |
|
130 | self.dataOut.groupList = self.dataIn.pairsList | |
| 130 | self.dataOut.flagNoData = False |
|
131 | self.dataOut.flagNoData = False | |
| 131 | #print 'datain chandist ',self.dataIn.ChanDist |
|
132 | #print 'datain chandist ',self.dataIn.ChanDist | |
| 132 | if hasattr(self.dataIn, 'ChanDist'): #Distances of receiver channels |
|
133 | if hasattr(self.dataIn, 'ChanDist'): #Distances of receiver channels | |
| 133 | self.dataOut.ChanDist = self.dataIn.ChanDist |
|
134 | self.dataOut.ChanDist = self.dataIn.ChanDist | |
| 134 | else: self.dataOut.ChanDist = None |
|
135 | else: self.dataOut.ChanDist = None | |
| 135 |
|
136 | |||
| 136 | print 'datain chandist ',self.dataOut.ChanDist |
|
137 | print 'datain chandist ',self.dataOut.ChanDist | |
| 137 |
|
138 | |||
| 138 | #if hasattr(self.dataIn, 'VelRange'): #Velocities range |
|
139 | #if hasattr(self.dataIn, 'VelRange'): #Velocities range | |
| 139 | # self.dataOut.VelRange = self.dataIn.VelRange |
|
140 | # self.dataOut.VelRange = self.dataIn.VelRange | |
| 140 | #else: self.dataOut.VelRange = None |
|
141 | #else: self.dataOut.VelRange = None | |
| 141 |
|
142 | |||
| 142 | if hasattr(self.dataIn, 'RadarConst'): #Radar Constant |
|
143 | if hasattr(self.dataIn, 'RadarConst'): #Radar Constant | |
| 143 | self.dataOut.RadarConst = self.dataIn.RadarConst |
|
144 | self.dataOut.RadarConst = self.dataIn.RadarConst | |
| 144 |
|
145 | |||
| 145 | if hasattr(self.dataIn, 'NPW'): #NPW |
|
146 | if hasattr(self.dataIn, 'NPW'): #NPW | |
| 146 | self.dataOut.NPW = self.dataIn.NPW |
|
147 | self.dataOut.NPW = self.dataIn.NPW | |
| 147 |
|
148 | |||
| 148 | if hasattr(self.dataIn, 'COFA'): #COFA |
|
149 | if hasattr(self.dataIn, 'COFA'): #COFA | |
| 149 | self.dataOut.COFA = self.dataIn.COFA |
|
150 | self.dataOut.COFA = self.dataIn.COFA | |
| 150 |
|
151 | |||
| 151 |
|
152 | |||
| 152 |
|
153 | |||
| 153 | #---------------------- Correlation Data --------------------------- |
|
154 | #---------------------- Correlation Data --------------------------- | |
| 154 |
|
155 | |||
| 155 | if self.dataIn.type == "Correlation": |
|
156 | if self.dataIn.type == "Correlation": | |
| 156 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.dataIn.splitFunctions() |
|
157 | acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.dataIn.splitFunctions() | |
| 157 |
|
158 | |||
| 158 | self.dataOut.data_pre = (self.dataIn.data_cf[acf_ind,:], self.dataIn.data_cf[ccf_ind,:,:]) |
|
159 | self.dataOut.data_pre = (self.dataIn.data_cf[acf_ind,:], self.dataIn.data_cf[ccf_ind,:,:]) | |
| 159 | self.dataOut.normFactor = (self.dataIn.normFactor[acf_ind,:], self.dataIn.normFactor[ccf_ind,:]) |
|
160 | self.dataOut.normFactor = (self.dataIn.normFactor[acf_ind,:], self.dataIn.normFactor[ccf_ind,:]) | |
| 160 | self.dataOut.groupList = (acf_pairs, ccf_pairs) |
|
161 | self.dataOut.groupList = (acf_pairs, ccf_pairs) | |
| 161 |
|
162 | |||
| 162 | self.dataOut.abscissaList = self.dataIn.lagRange |
|
163 | self.dataOut.abscissaList = self.dataIn.lagRange | |
| 163 | self.dataOut.noise = self.dataIn.noise |
|
164 | self.dataOut.noise = self.dataIn.noise | |
| 164 | self.dataOut.data_SNR = self.dataIn.SNR |
|
165 | self.dataOut.data_SNR = self.dataIn.SNR | |
| 165 | self.dataOut.flagNoData = False |
|
166 | self.dataOut.flagNoData = False | |
| 166 | self.dataOut.nAvg = self.dataIn.nAvg |
|
167 | self.dataOut.nAvg = self.dataIn.nAvg | |
| 167 |
|
168 | |||
| 168 | #---------------------- Parameters Data --------------------------- |
|
169 | #---------------------- Parameters Data --------------------------- | |
| 169 |
|
170 | |||
| 170 | if self.dataIn.type == "Parameters": |
|
171 | if self.dataIn.type == "Parameters": | |
| 171 | self.dataOut.copy(self.dataIn) |
|
172 | self.dataOut.copy(self.dataIn) | |
| 172 | self.dataOut.flagNoData = False |
|
173 | self.dataOut.flagNoData = False | |
| 173 |
|
174 | |||
| 174 | return True |
|
175 | return True | |
| 175 |
|
176 | |||
| 176 | self.__updateObjFromInput() |
|
177 | self.__updateObjFromInput() | |
| 177 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
178 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 178 | self.dataOut.paramInterval = self.dataIn.timeInterval |
|
179 | self.dataOut.paramInterval = self.dataIn.timeInterval | |
| 179 |
|
180 | |||
| 180 | return |
|
181 | return | |
| 181 |
|
182 | |||
| 182 |
|
183 | |||
| 183 | def target(tups): |
|
184 | def target(tups): | |
| 184 |
|
185 | |||
| 185 | obj, args = tups |
|
186 | obj, args = tups | |
| 186 | #print 'TARGETTT', obj, args |
|
187 | #print 'TARGETTT', obj, args | |
| 187 | return obj.FitGau(args) |
|
188 | return obj.FitGau(args) | |
| 188 |
|
189 | |||
| 189 |
|
190 | |||
|
|
191 | class SpectralFilters(Operation): | |||
|
|
192 | ||||
|
|
193 | '''This class allows the Rainfall / Wind Selection for CLAIRE RADAR | |||
|
|
194 | ||||
|
|
195 | LimitR : It is the limit in m/s of Rainfall | |||
|
|
196 | LimitW : It is the limit in m/s for Winds | |||
|
|
197 | ||||
|
|
198 | Input: | |||
|
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199 | ||||
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200 | self.dataOut.data_pre : SPC and CSPC | |||
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201 | self.dataOut.spc_range : To select wind and rainfall velocities | |||
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202 | ||||
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203 | Affected: | |||
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204 | ||||
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205 | self.dataOut.data_pre : It is used for the new SPC and CSPC ranges of wind | |||
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206 | self.dataOut.spcparam_range : Used in SpcParamPlot | |||
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207 | self.dataOut.SPCparam : Used in PrecipitationProc | |||
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208 | ||||
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209 | ||||
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210 | ''' | |||
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211 | ||||
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212 | def __init__(self, **kwargs): | |||
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213 | Operation.__init__(self, **kwargs) | |||
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214 | self.i=0 | |||
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215 | ||||
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216 | def run(self, dataOut, Rain_Velocity_Limit=1.5, Wind_Velocity_Limit=2.5): | |||
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217 | ||||
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218 | #Limite de vientos | |||
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219 | LimitR = Rain_Velocity_Limit | |||
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220 | LimitW = Wind_Velocity_Limit | |||
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221 | ||||
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222 | self.spc = dataOut.data_pre[0].copy() | |||
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223 | self.cspc = dataOut.data_pre[1].copy() | |||
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224 | ||||
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225 | self.Num_Hei = self.spc.shape[2] | |||
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226 | self.Num_Bin = self.spc.shape[1] | |||
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227 | self.Num_Chn = self.spc.shape[0] | |||
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228 | ||||
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229 | VelRange = dataOut.spc_range[2] | |||
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230 | TimeRange = dataOut.spc_range[1] | |||
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231 | FrecRange = dataOut.spc_range[0] | |||
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232 | ||||
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233 | Vmax= 2*numpy.max(dataOut.spc_range[2]) | |||
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234 | Tmax= 2*numpy.max(dataOut.spc_range[1]) | |||
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235 | Fmax= 2*numpy.max(dataOut.spc_range[0]) | |||
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236 | ||||
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237 | Breaker1R=VelRange[numpy.abs(VelRange-(-LimitR)).argmin()] | |||
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238 | Breaker1R=numpy.where(VelRange == Breaker1R) | |||
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239 | ||||
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240 | Breaker1W=VelRange[numpy.abs(VelRange-(-LimitW)).argmin()] | |||
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241 | Breaker1W=numpy.where(VelRange == Breaker1W) | |||
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242 | ||||
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243 | Breaker2W=VelRange[numpy.abs(VelRange-(LimitW)).argmin()] | |||
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244 | Breaker2W=numpy.where(VelRange == Breaker2W) | |||
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245 | ||||
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246 | ||||
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247 | '''Reacomodando SPCrange''' | |||
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248 | ||||
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249 | VelRange=numpy.roll(VelRange,-Breaker1R[0],axis=0) | |||
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250 | ||||
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251 | VelRange[-int(Breaker1R[0]):]+= Vmax | |||
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252 | ||||
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253 | FrecRange=numpy.roll(FrecRange,-Breaker1R[0],axis=0) | |||
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254 | ||||
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255 | FrecRange[-int(Breaker1R[0]):]+= Fmax | |||
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256 | ||||
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257 | TimeRange=numpy.roll(TimeRange,-Breaker1R[0],axis=0) | |||
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258 | ||||
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259 | TimeRange[-int(Breaker1R[0]):]+= Tmax | |||
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260 | ||||
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261 | ''' ------------------ ''' | |||
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262 | ||||
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263 | Breaker2R=VelRange[numpy.abs(VelRange-(LimitR)).argmin()] | |||
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264 | Breaker2R=numpy.where(VelRange == Breaker2R) | |||
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265 | ||||
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266 | ||||
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267 | ||||
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268 | ||||
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269 | SPCroll = numpy.roll(self.spc,-Breaker1R[0],axis=1) | |||
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270 | ||||
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271 | SPCcut = SPCroll.copy() | |||
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272 | for i in range(self.Num_Chn): | |||
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273 | SPCcut[i,0:int(Breaker2R[0]),:] = dataOut.noise[i] | |||
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274 | ||||
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275 | self.spc[i, 0:int(Breaker1W[0]) ,:] = dataOut.noise[i] | |||
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276 | self.spc[i, int(Breaker2W[0]):self.Num_Bin ,:] = dataOut.noise[i] | |||
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277 | ||||
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278 | self.cspc[i, 0:int(Breaker1W[0]) ,:] = dataOut.noise[i] | |||
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279 | self.cspc[i, int(Breaker2W[0]):self.Num_Bin ,:] = dataOut.noise[i] | |||
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280 | ||||
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281 | ||||
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282 | SPC_ch1 = SPCroll | |||
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283 | ||||
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284 | SPC_ch2 = SPCcut | |||
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285 | ||||
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286 | SPCparam = (SPC_ch1, SPC_ch2, self.spc) | |||
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287 | dataOut.SPCparam = numpy.asarray(SPCparam) | |||
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288 | ||||
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289 | dataOut.data_pre= (self.spc , self.cspc) | |||
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290 | ||||
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291 | #dataOut.data_preParam = (self.spc , self.cspc) | |||
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292 | ||||
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293 | dataOut.spcparam_range=numpy.zeros([self.Num_Chn,self.Num_Bin+1]) | |||
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294 | ||||
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295 | dataOut.spcparam_range[2]=VelRange | |||
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296 | dataOut.spcparam_range[1]=TimeRange | |||
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297 | dataOut.spcparam_range[0]=FrecRange | |||
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298 | ||||
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299 | ||||
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300 | ||||
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301 | ||||
| 190 | class GaussianFit(Operation): |
|
302 | class GaussianFit(Operation): | |
| 191 |
|
303 | |||
| 192 | ''' |
|
304 | ''' | |
| 193 | Function that fit of one and two generalized gaussians (gg) based |
|
305 | Function that fit of one and two generalized gaussians (gg) based | |
| 194 | on the PSD shape across an "power band" identified from a cumsum of |
|
306 | on the PSD shape across an "power band" identified from a cumsum of | |
| 195 | the measured spectrum - noise. |
|
307 | the measured spectrum - noise. | |
| 196 |
|
308 | |||
| 197 | Input: |
|
309 | Input: | |
| 198 | self.dataOut.data_pre : SelfSpectra |
|
310 | self.dataOut.data_pre : SelfSpectra | |
| 199 |
|
311 | |||
| 200 | Output: |
|
312 | Output: | |
| 201 |
self.dataOut. |
|
313 | self.dataOut.SPCparam : SPC_ch1, SPC_ch2 | |
| 202 |
|
314 | |||
| 203 | ''' |
|
315 | ''' | |
| 204 | def __init__(self, **kwargs): |
|
316 | def __init__(self, **kwargs): | |
| 205 | Operation.__init__(self, **kwargs) |
|
317 | Operation.__init__(self, **kwargs) | |
| 206 | self.i=0 |
|
318 | self.i=0 | |
| 207 |
|
319 | |||
| 208 |
|
320 | |||
| 209 | def run(self, dataOut, num_intg=7, pnoise=1., SNRlimit=-9): #num_intg: Incoherent integrations, pnoise: Noise, vel_arr: range of velocities, similar to the ftt points |
|
321 | def run(self, dataOut, num_intg=7, pnoise=1., SNRlimit=-9): #num_intg: Incoherent integrations, pnoise: Noise, vel_arr: range of velocities, similar to the ftt points | |
| 210 | """This routine will find a couple of generalized Gaussians to a power spectrum |
|
322 | """This routine will find a couple of generalized Gaussians to a power spectrum | |
| 211 | input: spc |
|
323 | input: spc | |
| 212 | output: |
|
324 | output: | |
| 213 | Amplitude0,shift0,width0,p0,Amplitude1,shift1,width1,p1,noise |
|
325 | Amplitude0,shift0,width0,p0,Amplitude1,shift1,width1,p1,noise | |
| 214 | """ |
|
326 | """ | |
| 215 |
|
327 | |||
| 216 | self.spc = dataOut.data_pre[0].copy() |
|
328 | self.spc = dataOut.data_pre[0].copy() | |
| 217 |
|
329 | |||
| 218 |
|
330 | |||
| 219 | print 'SelfSpectra Shape', numpy.asarray(self.spc).shape |
|
331 | print 'SelfSpectra Shape', numpy.asarray(self.spc).shape | |
| 220 |
|
332 | |||
| 221 |
|
333 | |||
| 222 | #plt.figure(50) |
|
334 | #plt.figure(50) | |
| 223 | #plt.subplot(121) |
|
335 | #plt.subplot(121) | |
| 224 | #plt.plot(self.spc,'k',label='spc(66)') |
|
336 | #plt.plot(self.spc,'k',label='spc(66)') | |
| 225 | #plt.plot(xFrec,ySamples[1],'g',label='Ch1') |
|
337 | #plt.plot(xFrec,ySamples[1],'g',label='Ch1') | |
| 226 | #plt.plot(xFrec,ySamples[2],'r',label='Ch2') |
|
338 | #plt.plot(xFrec,ySamples[2],'r',label='Ch2') | |
| 227 | #plt.plot(xFrec,FitGauss,'yo:',label='fit') |
|
339 | #plt.plot(xFrec,FitGauss,'yo:',label='fit') | |
| 228 | #plt.legend() |
|
340 | #plt.legend() | |
| 229 | #plt.title('DATOS A ALTURA DE 7500 METROS') |
|
341 | #plt.title('DATOS A ALTURA DE 7500 METROS') | |
| 230 | #plt.show() |
|
342 | #plt.show() | |
| 231 |
|
343 | |||
| 232 | self.Num_Hei = self.spc.shape[2] |
|
344 | self.Num_Hei = self.spc.shape[2] | |
| 233 | #self.Num_Bin = len(self.spc) |
|
345 | #self.Num_Bin = len(self.spc) | |
| 234 | self.Num_Bin = self.spc.shape[1] |
|
346 | self.Num_Bin = self.spc.shape[1] | |
| 235 | self.Num_Chn = self.spc.shape[0] |
|
347 | self.Num_Chn = self.spc.shape[0] | |
| 236 | Vrange = dataOut.abscissaList |
|
348 | Vrange = dataOut.abscissaList | |
| 237 |
|
349 | |||
| 238 | GauSPC = numpy.empty([self.Num_Chn,self.Num_Bin,self.Num_Hei]) |
|
350 | GauSPC = numpy.empty([self.Num_Chn,self.Num_Bin,self.Num_Hei]) | |
| 239 | SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei]) |
|
351 | SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei]) | |
| 240 | SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei]) |
|
352 | SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei]) | |
| 241 | SPC_ch1[:] = numpy.NaN |
|
353 | SPC_ch1[:] = numpy.NaN | |
| 242 | SPC_ch2[:] = numpy.NaN |
|
354 | SPC_ch2[:] = numpy.NaN | |
| 243 |
|
355 | |||
| 244 |
|
356 | |||
| 245 | start_time = time.time() |
|
357 | start_time = time.time() | |
| 246 |
|
358 | |||
| 247 | noise_ = dataOut.spc_noise[0].copy() |
|
359 | noise_ = dataOut.spc_noise[0].copy() | |
| 248 |
|
360 | |||
| 249 |
|
361 | |||
| 250 | pool = Pool(processes=self.Num_Chn) |
|
362 | pool = Pool(processes=self.Num_Chn) | |
| 251 | args = [(Vrange, Ch, pnoise, noise_, num_intg, SNRlimit) for Ch in range(self.Num_Chn)] |
|
363 | args = [(Vrange, Ch, pnoise, noise_, num_intg, SNRlimit) for Ch in range(self.Num_Chn)] | |
| 252 | objs = [self for __ in range(self.Num_Chn)] |
|
364 | objs = [self for __ in range(self.Num_Chn)] | |
| 253 | attrs = zip(objs, args) |
|
365 | attrs = zip(objs, args) | |
| 254 | gauSPC = pool.map(target, attrs) |
|
366 | gauSPC = pool.map(target, attrs) | |
| 255 |
dataOut. |
|
367 | dataOut.SPCparam = numpy.asarray(SPCparam) | |
| 256 |
|
368 | |||
| 257 |
|
369 | |||
| 258 |
|
370 | |||
| 259 | print '========================================================' |
|
371 | print '========================================================' | |
| 260 | print 'total_time: ', time.time()-start_time |
|
372 | print 'total_time: ', time.time()-start_time | |
| 261 |
|
373 | |||
| 262 | # re-normalizing spc and noise |
|
374 | # re-normalizing spc and noise | |
| 263 | # This part differs from gg1 |
|
375 | # This part differs from gg1 | |
| 264 |
|
376 | |||
| 265 |
|
377 | |||
| 266 |
|
378 | |||
| 267 | ''' Parameters: |
|
379 | ''' Parameters: | |
| 268 | 1. Amplitude |
|
380 | 1. Amplitude | |
| 269 | 2. Shift |
|
381 | 2. Shift | |
| 270 | 3. Width |
|
382 | 3. Width | |
| 271 | 4. Power |
|
383 | 4. Power | |
| 272 | ''' |
|
384 | ''' | |
| 273 |
|
385 | |||
| 274 |
|
386 | |||
| 275 | ############################################################################### |
|
387 | ############################################################################### | |
| 276 | def FitGau(self, X): |
|
388 | def FitGau(self, X): | |
| 277 |
|
389 | |||
| 278 | Vrange, ch, pnoise, noise_, num_intg, SNRlimit = X |
|
390 | Vrange, ch, pnoise, noise_, num_intg, SNRlimit = X | |
| 279 | #print 'VARSSSS', ch, pnoise, noise, num_intg |
|
391 | #print 'VARSSSS', ch, pnoise, noise, num_intg | |
| 280 |
|
392 | |||
| 281 | #print 'HEIGHTS', self.Num_Hei |
|
393 | #print 'HEIGHTS', self.Num_Hei | |
| 282 |
|
394 | |||
| 283 |
|
|
395 | SPCparam = [] | |
| 284 | SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei]) |
|
396 | SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei]) | |
| 285 | SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei]) |
|
397 | SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei]) | |
| 286 | SPC_ch1[:] = 0#numpy.NaN |
|
398 | SPC_ch1[:] = 0#numpy.NaN | |
| 287 | SPC_ch2[:] = 0#numpy.NaN |
|
399 | SPC_ch2[:] = 0#numpy.NaN | |
| 288 |
|
400 | |||
| 289 |
|
401 | |||
| 290 |
|
402 | |||
| 291 | for ht in range(self.Num_Hei): |
|
403 | for ht in range(self.Num_Hei): | |
| 292 | #print (numpy.asarray(self.spc).shape) |
|
404 | #print (numpy.asarray(self.spc).shape) | |
| 293 |
|
405 | |||
| 294 | #print 'TTTTT', ch , ht |
|
406 | #print 'TTTTT', ch , ht | |
| 295 | #print self.spc.shape |
|
407 | #print self.spc.shape | |
| 296 |
|
408 | |||
| 297 |
|
409 | |||
| 298 | spc = numpy.asarray(self.spc)[ch,:,ht] |
|
410 | spc = numpy.asarray(self.spc)[ch,:,ht] | |
| 299 |
|
411 | |||
| 300 | ############################################# |
|
412 | ############################################# | |
| 301 | # normalizing spc and noise |
|
413 | # normalizing spc and noise | |
| 302 | # This part differs from gg1 |
|
414 | # This part differs from gg1 | |
| 303 | spc_norm_max = max(spc) |
|
415 | spc_norm_max = max(spc) | |
| 304 | #spc = spc / spc_norm_max |
|
416 | #spc = spc / spc_norm_max | |
| 305 | pnoise = pnoise #/ spc_norm_max |
|
417 | pnoise = pnoise #/ spc_norm_max | |
| 306 | ############################################# |
|
418 | ############################################# | |
| 307 |
|
419 | |||
| 308 | fatspectra=1.0 |
|
420 | fatspectra=1.0 | |
| 309 |
|
421 | |||
| 310 | wnoise = noise_ #/ spc_norm_max |
|
422 | wnoise = noise_ #/ spc_norm_max | |
| 311 | #wnoise,stdv,i_max,index =enoise(spc,num_intg) #noise estimate using Hildebrand Sekhon, only wnoise is used |
|
423 | #wnoise,stdv,i_max,index =enoise(spc,num_intg) #noise estimate using Hildebrand Sekhon, only wnoise is used | |
| 312 | #if wnoise>1.1*pnoise: # to be tested later |
|
424 | #if wnoise>1.1*pnoise: # to be tested later | |
| 313 | # wnoise=pnoise |
|
425 | # wnoise=pnoise | |
| 314 | noisebl=wnoise*0.9; |
|
426 | noisebl=wnoise*0.9; | |
| 315 | noisebh=wnoise*1.1 |
|
427 | noisebh=wnoise*1.1 | |
| 316 | spc=spc-wnoise |
|
428 | spc=spc-wnoise | |
| 317 | # print 'wnoise', noise_[0], spc_norm_max, wnoise |
|
429 | # print 'wnoise', noise_[0], spc_norm_max, wnoise | |
| 318 | minx=numpy.argmin(spc) |
|
430 | minx=numpy.argmin(spc) | |
| 319 | #spcs=spc.copy() |
|
431 | #spcs=spc.copy() | |
| 320 | spcs=numpy.roll(spc,-minx) |
|
432 | spcs=numpy.roll(spc,-minx) | |
| 321 | cum=numpy.cumsum(spcs) |
|
433 | cum=numpy.cumsum(spcs) | |
| 322 | tot_noise=wnoise * self.Num_Bin #64; |
|
434 | tot_noise=wnoise * self.Num_Bin #64; | |
| 323 | #print 'spc' , spcs[5:8] , 'tot_noise', tot_noise |
|
435 | #print 'spc' , spcs[5:8] , 'tot_noise', tot_noise | |
| 324 | #tot_signal=sum(cum[-5:])/5.; ''' How does this line work? ''' |
|
436 | #tot_signal=sum(cum[-5:])/5.; ''' How does this line work? ''' | |
| 325 | #snr=tot_signal/tot_noise |
|
437 | #snr=tot_signal/tot_noise | |
| 326 | #snr=cum[-1]/tot_noise |
|
438 | #snr=cum[-1]/tot_noise | |
| 327 | snr = sum(spcs)/tot_noise |
|
439 | snr = sum(spcs)/tot_noise | |
| 328 | snrdB=10.*numpy.log10(snr) |
|
440 | snrdB=10.*numpy.log10(snr) | |
| 329 |
|
441 | |||
| 330 | if snrdB < SNRlimit : |
|
442 | if snrdB < SNRlimit : | |
| 331 | snr = numpy.NaN |
|
443 | snr = numpy.NaN | |
| 332 | SPC_ch1[:,ht] = 0#numpy.NaN |
|
444 | SPC_ch1[:,ht] = 0#numpy.NaN | |
| 333 | SPC_ch1[:,ht] = 0#numpy.NaN |
|
445 | SPC_ch1[:,ht] = 0#numpy.NaN | |
| 334 |
|
|
446 | SPCparam = (SPC_ch1,SPC_ch2) | |
| 335 | continue |
|
447 | continue | |
| 336 | #print 'snr',snrdB #, sum(spcs) , tot_noise |
|
448 | #print 'snr',snrdB #, sum(spcs) , tot_noise | |
| 337 |
|
449 | |||
| 338 |
|
450 | |||
| 339 |
|
451 | |||
| 340 | #if snrdB<-18 or numpy.isnan(snrdB) or num_intg<4: |
|
452 | #if snrdB<-18 or numpy.isnan(snrdB) or num_intg<4: | |
| 341 | # return [None,]*4,[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None |
|
453 | # return [None,]*4,[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None | |
| 342 |
|
454 | |||
| 343 | cummax=max(cum); |
|
455 | cummax=max(cum); | |
| 344 | epsi=0.08*fatspectra # cumsum to narrow down the energy region |
|
456 | epsi=0.08*fatspectra # cumsum to narrow down the energy region | |
| 345 | cumlo=cummax*epsi; |
|
457 | cumlo=cummax*epsi; | |
| 346 | cumhi=cummax*(1-epsi) |
|
458 | cumhi=cummax*(1-epsi) | |
| 347 | powerindex=numpy.array(numpy.where(numpy.logical_and(cum>cumlo, cum<cumhi))[0]) |
|
459 | powerindex=numpy.array(numpy.where(numpy.logical_and(cum>cumlo, cum<cumhi))[0]) | |
| 348 |
|
460 | |||
| 349 |
|
461 | |||
| 350 | if len(powerindex) < 1:# case for powerindex 0 |
|
462 | if len(powerindex) < 1:# case for powerindex 0 | |
| 351 | continue |
|
463 | continue | |
| 352 | powerlo=powerindex[0] |
|
464 | powerlo=powerindex[0] | |
| 353 | powerhi=powerindex[-1] |
|
465 | powerhi=powerindex[-1] | |
| 354 | powerwidth=powerhi-powerlo |
|
466 | powerwidth=powerhi-powerlo | |
| 355 |
|
467 | |||
| 356 | firstpeak=powerlo+powerwidth/10.# first gaussian energy location |
|
468 | firstpeak=powerlo+powerwidth/10.# first gaussian energy location | |
| 357 | secondpeak=powerhi-powerwidth/10.#second gaussian energy location |
|
469 | secondpeak=powerhi-powerwidth/10.#second gaussian energy location | |
| 358 | midpeak=(firstpeak+secondpeak)/2. |
|
470 | midpeak=(firstpeak+secondpeak)/2. | |
| 359 | firstamp=spcs[int(firstpeak)] |
|
471 | firstamp=spcs[int(firstpeak)] | |
| 360 | secondamp=spcs[int(secondpeak)] |
|
472 | secondamp=spcs[int(secondpeak)] | |
| 361 | midamp=spcs[int(midpeak)] |
|
473 | midamp=spcs[int(midpeak)] | |
| 362 |
|
474 | |||
| 363 | x=numpy.arange( self.Num_Bin ) |
|
475 | x=numpy.arange( self.Num_Bin ) | |
| 364 | y_data=spc+wnoise |
|
476 | y_data=spc+wnoise | |
| 365 |
|
477 | |||
| 366 | ''' single Gaussian ''' |
|
478 | ''' single Gaussian ''' | |
| 367 | shift0=numpy.mod(midpeak+minx, self.Num_Bin ) |
|
479 | shift0=numpy.mod(midpeak+minx, self.Num_Bin ) | |
| 368 | width0=powerwidth/4.#Initialization entire power of spectrum divided by 4 |
|
480 | width0=powerwidth/4.#Initialization entire power of spectrum divided by 4 | |
| 369 | power0=2. |
|
481 | power0=2. | |
| 370 | amplitude0=midamp |
|
482 | amplitude0=midamp | |
| 371 | state0=[shift0,width0,amplitude0,power0,wnoise] |
|
483 | state0=[shift0,width0,amplitude0,power0,wnoise] | |
| 372 | bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth),(0,None),(0.5,3.),(noisebl,noisebh)) |
|
484 | bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth),(0,None),(0.5,3.),(noisebl,noisebh)) | |
| 373 | lsq1=fmin_l_bfgs_b(self.misfit1,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True) |
|
485 | lsq1=fmin_l_bfgs_b(self.misfit1,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True) | |
| 374 |
|
486 | |||
| 375 | chiSq1=lsq1[1]; |
|
487 | chiSq1=lsq1[1]; | |
| 376 |
|
488 | |||
| 377 |
|
489 | |||
| 378 | if fatspectra<1.0 and powerwidth<4: |
|
490 | if fatspectra<1.0 and powerwidth<4: | |
| 379 | choice=0 |
|
491 | choice=0 | |
| 380 | Amplitude0=lsq1[0][2] |
|
492 | Amplitude0=lsq1[0][2] | |
| 381 | shift0=lsq1[0][0] |
|
493 | shift0=lsq1[0][0] | |
| 382 | width0=lsq1[0][1] |
|
494 | width0=lsq1[0][1] | |
| 383 | p0=lsq1[0][3] |
|
495 | p0=lsq1[0][3] | |
| 384 | Amplitude1=0. |
|
496 | Amplitude1=0. | |
| 385 | shift1=0. |
|
497 | shift1=0. | |
| 386 | width1=0. |
|
498 | width1=0. | |
| 387 | p1=0. |
|
499 | p1=0. | |
| 388 | noise=lsq1[0][4] |
|
500 | noise=lsq1[0][4] | |
| 389 | #return (numpy.array([shift0,width0,Amplitude0,p0]), |
|
501 | #return (numpy.array([shift0,width0,Amplitude0,p0]), | |
| 390 | # numpy.array([shift1,width1,Amplitude1,p1]),noise,snrdB,chiSq1,6.,sigmas1,[None,]*9,choice) |
|
502 | # numpy.array([shift1,width1,Amplitude1,p1]),noise,snrdB,chiSq1,6.,sigmas1,[None,]*9,choice) | |
| 391 |
|
503 | |||
| 392 | ''' two gaussians ''' |
|
504 | ''' two gaussians ''' | |
| 393 | #shift0=numpy.mod(firstpeak+minx,64); shift1=numpy.mod(secondpeak+minx,64) |
|
505 | #shift0=numpy.mod(firstpeak+minx,64); shift1=numpy.mod(secondpeak+minx,64) | |
| 394 | shift0=numpy.mod(firstpeak+minx, self.Num_Bin ); |
|
506 | shift0=numpy.mod(firstpeak+minx, self.Num_Bin ); | |
| 395 | shift1=numpy.mod(secondpeak+minx, self.Num_Bin ) |
|
507 | shift1=numpy.mod(secondpeak+minx, self.Num_Bin ) | |
| 396 | width0=powerwidth/6.; |
|
508 | width0=powerwidth/6.; | |
| 397 | width1=width0 |
|
509 | width1=width0 | |
| 398 | power0=2.; |
|
510 | power0=2.; | |
| 399 | power1=power0 |
|
511 | power1=power0 | |
| 400 | amplitude0=firstamp; |
|
512 | amplitude0=firstamp; | |
| 401 | amplitude1=secondamp |
|
513 | amplitude1=secondamp | |
| 402 | state0=[shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,wnoise] |
|
514 | state0=[shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,wnoise] | |
| 403 | #bnds=((0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh)) |
|
515 | #bnds=((0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh)) | |
| 404 | bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh)) |
|
516 | bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh)) | |
| 405 | #bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(0.1,0.5)) |
|
517 | #bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(0.1,0.5)) | |
| 406 |
|
518 | |||
| 407 | lsq2 = fmin_l_bfgs_b( self.misfit2 , state0 , args=(y_data,x,num_intg) , bounds=bnds , approx_grad=True ) |
|
519 | lsq2 = fmin_l_bfgs_b( self.misfit2 , state0 , args=(y_data,x,num_intg) , bounds=bnds , approx_grad=True ) | |
| 408 |
|
520 | |||
| 409 |
|
521 | |||
| 410 | chiSq2=lsq2[1]; |
|
522 | chiSq2=lsq2[1]; | |
| 411 |
|
523 | |||
| 412 |
|
524 | |||
| 413 |
|
525 | |||
| 414 | oneG=(chiSq1<5 and chiSq1/chiSq2<2.0) and (abs(lsq2[0][0]-lsq2[0][4])<(lsq2[0][1]+lsq2[0][5])/3. or abs(lsq2[0][0]-lsq2[0][4])<10) |
|
526 | oneG=(chiSq1<5 and chiSq1/chiSq2<2.0) and (abs(lsq2[0][0]-lsq2[0][4])<(lsq2[0][1]+lsq2[0][5])/3. or abs(lsq2[0][0]-lsq2[0][4])<10) | |
| 415 |
|
527 | |||
| 416 | if snrdB>-12: # when SNR is strong pick the peak with least shift (LOS velocity) error |
|
528 | if snrdB>-12: # when SNR is strong pick the peak with least shift (LOS velocity) error | |
| 417 | if oneG: |
|
529 | if oneG: | |
| 418 | choice=0 |
|
530 | choice=0 | |
| 419 | else: |
|
531 | else: | |
| 420 | w1=lsq2[0][1]; w2=lsq2[0][5] |
|
532 | w1=lsq2[0][1]; w2=lsq2[0][5] | |
| 421 | a1=lsq2[0][2]; a2=lsq2[0][6] |
|
533 | a1=lsq2[0][2]; a2=lsq2[0][6] | |
| 422 | p1=lsq2[0][3]; p2=lsq2[0][7] |
|
534 | p1=lsq2[0][3]; p2=lsq2[0][7] | |
| 423 | s1=(2**(1+1./p1))*scipy.special.gamma(1./p1)/p1; |
|
535 | s1=(2**(1+1./p1))*scipy.special.gamma(1./p1)/p1; | |
| 424 | s2=(2**(1+1./p2))*scipy.special.gamma(1./p2)/p2; |
|
536 | s2=(2**(1+1./p2))*scipy.special.gamma(1./p2)/p2; | |
| 425 | gp1=a1*w1*s1; gp2=a2*w2*s2 # power content of each ggaussian with proper p scaling |
|
537 | gp1=a1*w1*s1; gp2=a2*w2*s2 # power content of each ggaussian with proper p scaling | |
| 426 |
|
538 | |||
| 427 | if gp1>gp2: |
|
539 | if gp1>gp2: | |
| 428 | if a1>0.7*a2: |
|
540 | if a1>0.7*a2: | |
| 429 | choice=1 |
|
541 | choice=1 | |
| 430 | else: |
|
542 | else: | |
| 431 | choice=2 |
|
543 | choice=2 | |
| 432 | elif gp2>gp1: |
|
544 | elif gp2>gp1: | |
| 433 | if a2>0.7*a1: |
|
545 | if a2>0.7*a1: | |
| 434 | choice=2 |
|
546 | choice=2 | |
| 435 | else: |
|
547 | else: | |
| 436 | choice=1 |
|
548 | choice=1 | |
| 437 | else: |
|
549 | else: | |
| 438 | choice=numpy.argmax([a1,a2])+1 |
|
550 | choice=numpy.argmax([a1,a2])+1 | |
| 439 | #else: |
|
551 | #else: | |
| 440 | #choice=argmin([std2a,std2b])+1 |
|
552 | #choice=argmin([std2a,std2b])+1 | |
| 441 |
|
553 | |||
| 442 | else: # with low SNR go to the most energetic peak |
|
554 | else: # with low SNR go to the most energetic peak | |
| 443 | choice=numpy.argmax([lsq1[0][2]*lsq1[0][1],lsq2[0][2]*lsq2[0][1],lsq2[0][6]*lsq2[0][5]]) |
|
555 | choice=numpy.argmax([lsq1[0][2]*lsq1[0][1],lsq2[0][2]*lsq2[0][1],lsq2[0][6]*lsq2[0][5]]) | |
| 444 |
|
556 | |||
| 445 |
|
557 | |||
| 446 | shift0=lsq2[0][0]; |
|
558 | shift0=lsq2[0][0]; | |
| 447 | vel0=Vrange[0] + shift0*(Vrange[1]-Vrange[0]) |
|
559 | vel0=Vrange[0] + shift0*(Vrange[1]-Vrange[0]) | |
| 448 | shift1=lsq2[0][4]; |
|
560 | shift1=lsq2[0][4]; | |
| 449 | vel1=Vrange[0] + shift1*(Vrange[1]-Vrange[0]) |
|
561 | vel1=Vrange[0] + shift1*(Vrange[1]-Vrange[0]) | |
| 450 |
|
562 | |||
| 451 | max_vel = 1.0 |
|
563 | max_vel = 1.0 | |
| 452 |
|
564 | |||
| 453 | #first peak will be 0, second peak will be 1 |
|
565 | #first peak will be 0, second peak will be 1 | |
| 454 | if vel0 > -1.0 and vel0 < max_vel : #first peak is in the correct range |
|
566 | if vel0 > -1.0 and vel0 < max_vel : #first peak is in the correct range | |
| 455 | shift0=lsq2[0][0] |
|
567 | shift0=lsq2[0][0] | |
| 456 | width0=lsq2[0][1] |
|
568 | width0=lsq2[0][1] | |
| 457 | Amplitude0=lsq2[0][2] |
|
569 | Amplitude0=lsq2[0][2] | |
| 458 | p0=lsq2[0][3] |
|
570 | p0=lsq2[0][3] | |
| 459 |
|
571 | |||
| 460 | shift1=lsq2[0][4] |
|
572 | shift1=lsq2[0][4] | |
| 461 | width1=lsq2[0][5] |
|
573 | width1=lsq2[0][5] | |
| 462 | Amplitude1=lsq2[0][6] |
|
574 | Amplitude1=lsq2[0][6] | |
| 463 | p1=lsq2[0][7] |
|
575 | p1=lsq2[0][7] | |
| 464 | noise=lsq2[0][8] |
|
576 | noise=lsq2[0][8] | |
| 465 | else: |
|
577 | else: | |
| 466 | shift1=lsq2[0][0] |
|
578 | shift1=lsq2[0][0] | |
| 467 | width1=lsq2[0][1] |
|
579 | width1=lsq2[0][1] | |
| 468 | Amplitude1=lsq2[0][2] |
|
580 | Amplitude1=lsq2[0][2] | |
| 469 | p1=lsq2[0][3] |
|
581 | p1=lsq2[0][3] | |
| 470 |
|
582 | |||
| 471 | shift0=lsq2[0][4] |
|
583 | shift0=lsq2[0][4] | |
| 472 | width0=lsq2[0][5] |
|
584 | width0=lsq2[0][5] | |
| 473 | Amplitude0=lsq2[0][6] |
|
585 | Amplitude0=lsq2[0][6] | |
| 474 | p0=lsq2[0][7] |
|
586 | p0=lsq2[0][7] | |
| 475 | noise=lsq2[0][8] |
|
587 | noise=lsq2[0][8] | |
| 476 |
|
588 | |||
| 477 | if Amplitude0<0.05: # in case the peak is noise |
|
589 | if Amplitude0<0.05: # in case the peak is noise | |
| 478 | shift0,width0,Amplitude0,p0 = [0,0,0,0]#4*[numpy.NaN] |
|
590 | shift0,width0,Amplitude0,p0 = [0,0,0,0]#4*[numpy.NaN] | |
| 479 | if Amplitude1<0.05: |
|
591 | if Amplitude1<0.05: | |
| 480 | shift1,width1,Amplitude1,p1 = [0,0,0,0]#4*[numpy.NaN] |
|
592 | shift1,width1,Amplitude1,p1 = [0,0,0,0]#4*[numpy.NaN] | |
| 481 |
|
593 | |||
| 482 |
|
594 | |||
| 483 | # if choice==0: # pick the single gaussian fit |
|
595 | # if choice==0: # pick the single gaussian fit | |
| 484 | # Amplitude0=lsq1[0][2] |
|
596 | # Amplitude0=lsq1[0][2] | |
| 485 | # shift0=lsq1[0][0] |
|
597 | # shift0=lsq1[0][0] | |
| 486 | # width0=lsq1[0][1] |
|
598 | # width0=lsq1[0][1] | |
| 487 | # p0=lsq1[0][3] |
|
599 | # p0=lsq1[0][3] | |
| 488 | # Amplitude1=0. |
|
600 | # Amplitude1=0. | |
| 489 | # shift1=0. |
|
601 | # shift1=0. | |
| 490 | # width1=0. |
|
602 | # width1=0. | |
| 491 | # p1=0. |
|
603 | # p1=0. | |
| 492 | # noise=lsq1[0][4] |
|
604 | # noise=lsq1[0][4] | |
| 493 | # elif choice==1: # take the first one of the 2 gaussians fitted |
|
605 | # elif choice==1: # take the first one of the 2 gaussians fitted | |
| 494 | # Amplitude0 = lsq2[0][2] |
|
606 | # Amplitude0 = lsq2[0][2] | |
| 495 | # shift0 = lsq2[0][0] |
|
607 | # shift0 = lsq2[0][0] | |
| 496 | # width0 = lsq2[0][1] |
|
608 | # width0 = lsq2[0][1] | |
| 497 | # p0 = lsq2[0][3] |
|
609 | # p0 = lsq2[0][3] | |
| 498 | # Amplitude1 = lsq2[0][6] # This is 0 in gg1 |
|
610 | # Amplitude1 = lsq2[0][6] # This is 0 in gg1 | |
| 499 | # shift1 = lsq2[0][4] # This is 0 in gg1 |
|
611 | # shift1 = lsq2[0][4] # This is 0 in gg1 | |
| 500 | # width1 = lsq2[0][5] # This is 0 in gg1 |
|
612 | # width1 = lsq2[0][5] # This is 0 in gg1 | |
| 501 | # p1 = lsq2[0][7] # This is 0 in gg1 |
|
613 | # p1 = lsq2[0][7] # This is 0 in gg1 | |
| 502 | # noise = lsq2[0][8] |
|
614 | # noise = lsq2[0][8] | |
| 503 | # else: # the second one |
|
615 | # else: # the second one | |
| 504 | # Amplitude0 = lsq2[0][6] |
|
616 | # Amplitude0 = lsq2[0][6] | |
| 505 | # shift0 = lsq2[0][4] |
|
617 | # shift0 = lsq2[0][4] | |
| 506 | # width0 = lsq2[0][5] |
|
618 | # width0 = lsq2[0][5] | |
| 507 | # p0 = lsq2[0][7] |
|
619 | # p0 = lsq2[0][7] | |
| 508 | # Amplitude1 = lsq2[0][2] # This is 0 in gg1 |
|
620 | # Amplitude1 = lsq2[0][2] # This is 0 in gg1 | |
| 509 | # shift1 = lsq2[0][0] # This is 0 in gg1 |
|
621 | # shift1 = lsq2[0][0] # This is 0 in gg1 | |
| 510 | # width1 = lsq2[0][1] # This is 0 in gg1 |
|
622 | # width1 = lsq2[0][1] # This is 0 in gg1 | |
| 511 | # p1 = lsq2[0][3] # This is 0 in gg1 |
|
623 | # p1 = lsq2[0][3] # This is 0 in gg1 | |
| 512 | # noise = lsq2[0][8] |
|
624 | # noise = lsq2[0][8] | |
| 513 |
|
625 | |||
| 514 | #print len(noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0) |
|
626 | #print len(noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0) | |
| 515 | SPC_ch1[:,ht] = noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0 |
|
627 | SPC_ch1[:,ht] = noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0 | |
| 516 | SPC_ch2[:,ht] = noise + Amplitude1*numpy.exp(-0.5*(abs(x-shift1))/width1)**p1 |
|
628 | SPC_ch2[:,ht] = noise + Amplitude1*numpy.exp(-0.5*(abs(x-shift1))/width1)**p1 | |
| 517 | #print 'SPC_ch1.shape',SPC_ch1.shape |
|
629 | #print 'SPC_ch1.shape',SPC_ch1.shape | |
| 518 | #print 'SPC_ch2.shape',SPC_ch2.shape |
|
630 | #print 'SPC_ch2.shape',SPC_ch2.shape | |
| 519 | #dataOut.data_param = SPC_ch1 |
|
631 | #dataOut.data_param = SPC_ch1 | |
| 520 |
|
|
632 | SPCparam = (SPC_ch1,SPC_ch2) | |
| 521 | #GauSPC[1] = SPC_ch2 |
|
633 | #GauSPC[1] = SPC_ch2 | |
| 522 |
|
634 | |||
| 523 | # print 'shift0', shift0 |
|
635 | # print 'shift0', shift0 | |
| 524 | # print 'Amplitude0', Amplitude0 |
|
636 | # print 'Amplitude0', Amplitude0 | |
| 525 | # print 'width0', width0 |
|
637 | # print 'width0', width0 | |
| 526 | # print 'p0', p0 |
|
638 | # print 'p0', p0 | |
| 527 | # print '========================' |
|
639 | # print '========================' | |
| 528 | # print 'shift1', shift1 |
|
640 | # print 'shift1', shift1 | |
| 529 | # print 'Amplitude1', Amplitude1 |
|
641 | # print 'Amplitude1', Amplitude1 | |
| 530 | # print 'width1', width1 |
|
642 | # print 'width1', width1 | |
| 531 | # print 'p1', p1 |
|
643 | # print 'p1', p1 | |
| 532 | # print 'noise', noise |
|
644 | # print 'noise', noise | |
| 533 | # print 's_noise', wnoise |
|
645 | # print 's_noise', wnoise | |
| 534 |
|
646 | |||
| 535 | return GauSPC |
|
647 | return GauSPC | |
| 536 |
|
648 | |||
| 537 | def y_model1(self,x,state): |
|
649 | def y_model1(self,x,state): | |
| 538 | shift0,width0,amplitude0,power0,noise=state |
|
650 | shift0,width0,amplitude0,power0,noise=state | |
| 539 | model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0) |
|
651 | model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0) | |
| 540 |
|
652 | |||
| 541 | model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0) |
|
653 | model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0) | |
| 542 |
|
654 | |||
| 543 | model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0) |
|
655 | model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0) | |
| 544 | return model0+model0u+model0d+noise |
|
656 | return model0+model0u+model0d+noise | |
| 545 |
|
657 | |||
| 546 | def y_model2(self,x,state): #Equation for two generalized Gaussians with Nyquist |
|
658 | def y_model2(self,x,state): #Equation for two generalized Gaussians with Nyquist | |
| 547 | shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,noise=state |
|
659 | shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,noise=state | |
| 548 | model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0) |
|
660 | model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0) | |
| 549 |
|
661 | |||
| 550 | model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0) |
|
662 | model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0) | |
| 551 |
|
663 | |||
| 552 | model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0) |
|
664 | model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0) | |
| 553 | model1=amplitude1*numpy.exp(-0.5*abs((x-shift1)/width1)**power1) |
|
665 | model1=amplitude1*numpy.exp(-0.5*abs((x-shift1)/width1)**power1) | |
| 554 |
|
666 | |||
| 555 | model1u=amplitude1*numpy.exp(-0.5*abs((x-shift1- self.Num_Bin )/width1)**power1) |
|
667 | model1u=amplitude1*numpy.exp(-0.5*abs((x-shift1- self.Num_Bin )/width1)**power1) | |
| 556 |
|
668 | |||
| 557 | model1d=amplitude1*numpy.exp(-0.5*abs((x-shift1+ self.Num_Bin )/width1)**power1) |
|
669 | model1d=amplitude1*numpy.exp(-0.5*abs((x-shift1+ self.Num_Bin )/width1)**power1) | |
| 558 | return model0+model0u+model0d+model1+model1u+model1d+noise |
|
670 | return model0+model0u+model0d+model1+model1u+model1d+noise | |
| 559 |
|
671 | |||
| 560 | def misfit1(self,state,y_data,x,num_intg): # This function compares how close real data is with the model data, the close it is, the better it is. |
|
672 | def misfit1(self,state,y_data,x,num_intg): # This function compares how close real data is with the model data, the close it is, the better it is. | |
| 561 |
|
673 | |||
| 562 | return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model1(x,state)))**2)#/(64-5.) # /(64-5.) can be commented |
|
674 | return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model1(x,state)))**2)#/(64-5.) # /(64-5.) can be commented | |
| 563 |
|
675 | |||
| 564 | def misfit2(self,state,y_data,x,num_intg): |
|
676 | def misfit2(self,state,y_data,x,num_intg): | |
| 565 | return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model2(x,state)))**2)#/(64-9.) |
|
677 | return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model2(x,state)))**2)#/(64-9.) | |
| 566 |
|
678 | |||
| 567 |
|
679 | |||
| 568 |
|
680 | |||
| 569 | class PrecipitationProc(Operation): |
|
681 | class PrecipitationProc(Operation): | |
| 570 |
|
682 | |||
| 571 | ''' |
|
683 | ''' | |
| 572 | Operator that estimates Reflectivity factor (Z), and estimates rainfall Rate (R) |
|
684 | Operator that estimates Reflectivity factor (Z), and estimates rainfall Rate (R) | |
| 573 |
|
685 | |||
| 574 | Input: |
|
686 | Input: | |
| 575 | self.dataOut.data_pre : SelfSpectra |
|
687 | self.dataOut.data_pre : SelfSpectra | |
| 576 |
|
688 | |||
| 577 | Output: |
|
689 | Output: | |
| 578 |
|
690 | |||
| 579 | self.dataOut.data_output : Reflectivity factor, rainfall Rate |
|
691 | self.dataOut.data_output : Reflectivity factor, rainfall Rate | |
| 580 |
|
692 | |||
| 581 |
|
693 | |||
| 582 | Parameters affected: |
|
694 | Parameters affected: | |
| 583 | ''' |
|
695 | ''' | |
| 584 |
|
696 | def gaus(self,xSamples,Amp,Mu,Sigma): | ||
|
|
697 | return ( Amp / ((2*numpy.pi)**0.5 * Sigma) ) * numpy.exp( -( xSamples - Mu )**2 / ( 2 * (Sigma**2) )) | |||
|
|
698 | ||||
|
|
699 | ||||
|
|
700 | ||||
|
|
701 | def Moments(self, ySamples, xSamples): | |||
|
|
702 | Pot = numpy.nansum( ySamples ) # Potencia, momento 0 | |||
|
|
703 | yNorm = ySamples / Pot | |||
|
|
704 | ||||
|
|
705 | Vr = numpy.nansum( yNorm * xSamples ) # Velocidad radial, mu, corrimiento doppler, primer momento | |||
|
|
706 | Sigma2 = abs(numpy.nansum( yNorm * ( xSamples - Vr )**2 )) # Segundo Momento | |||
|
|
707 | Desv = Sigma2**0.5 # Desv. Estandar, Ancho espectral | |||
|
|
708 | ||||
|
|
709 | return numpy.array([Pot, Vr, Desv]) | |||
| 585 |
|
710 | |||
| 586 | def run(self, dataOut, radar=None, Pt=5000, Gt=295.1209, Gr=70.7945, Lambda=0.6741, aL=2.5118, |
|
711 | def run(self, dataOut, radar=None, Pt=5000, Gt=295.1209, Gr=70.7945, Lambda=0.6741, aL=2.5118, | |
| 587 | tauW=4e-06, ThetaT=0.1656317, ThetaR=0.36774087, Km = 0.93, Altitude=3350): |
|
712 | tauW=4e-06, ThetaT=0.1656317, ThetaR=0.36774087, Km = 0.93, Altitude=3350): | |
| 588 |
|
713 | |||
| 589 |
|
714 | |||
| 590 |
Velrange = dataOut. |
|
715 | Velrange = dataOut.spc_range[2] | |
|
|
716 | FrecRange = dataOut.spc_range[0] | |||
|
|
717 | ||||
|
|
718 | dV= Velrange[1]-Velrange[0] | |||
|
|
719 | dF= FrecRange[1]-FrecRange[0] | |||
| 591 |
|
720 | |||
| 592 | if radar == "MIRA35C" : |
|
721 | if radar == "MIRA35C" : | |
| 593 |
|
722 | |||
| 594 | self.spc = dataOut.data_pre[0].copy() |
|
723 | self.spc = dataOut.data_pre[0].copy() | |
| 595 | self.Num_Hei = self.spc.shape[2] |
|
724 | self.Num_Hei = self.spc.shape[2] | |
| 596 | self.Num_Bin = self.spc.shape[1] |
|
725 | self.Num_Bin = self.spc.shape[1] | |
| 597 | self.Num_Chn = self.spc.shape[0] |
|
726 | self.Num_Chn = self.spc.shape[0] | |
| 598 | Ze = self.dBZeMODE2(dataOut) |
|
727 | Ze = self.dBZeMODE2(dataOut) | |
| 599 |
|
728 | |||
| 600 | else: |
|
729 | else: | |
| 601 |
|
730 | |||
| 602 |
self.spc = dataOut. |
|
731 | self.spc = dataOut.SPCparam[1] #dataOut.data_pre[0].copy() # | |
| 603 | self.Num_Hei = self.spc.shape[2] |
|
732 | self.Num_Hei = self.spc.shape[2] | |
| 604 | self.Num_Bin = self.spc.shape[1] |
|
733 | self.Num_Bin = self.spc.shape[1] | |
| 605 | self.Num_Chn = self.spc.shape[0] |
|
734 | self.Num_Chn = self.spc.shape[0] | |
| 606 | print '==================== SPC SHAPE',numpy.shape(self.spc) |
|
735 | print '==================== SPC SHAPE',numpy.shape(self.spc) | |
| 607 |
|
736 | |||
| 608 |
|
737 | |||
| 609 | ''' Se obtiene la constante del RADAR ''' |
|
738 | ''' Se obtiene la constante del RADAR ''' | |
| 610 |
|
739 | |||
| 611 | self.Pt = Pt |
|
740 | self.Pt = Pt | |
| 612 | self.Gt = Gt |
|
741 | self.Gt = Gt | |
| 613 | self.Gr = Gr |
|
742 | self.Gr = Gr | |
| 614 | self.Lambda = Lambda |
|
743 | self.Lambda = Lambda | |
| 615 | self.aL = aL |
|
744 | self.aL = aL | |
| 616 | self.tauW = tauW |
|
745 | self.tauW = tauW | |
| 617 | self.ThetaT = ThetaT |
|
746 | self.ThetaT = ThetaT | |
| 618 | self.ThetaR = ThetaR |
|
747 | self.ThetaR = ThetaR | |
| 619 |
|
748 | |||
| 620 | Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) ) |
|
749 | Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) ) | |
| 621 | Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * tauW * numpy.pi * ThetaT * ThetaR) |
|
750 | Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * tauW * numpy.pi * ThetaT * ThetaR) | |
| 622 |
RadarConstant = |
|
751 | RadarConstant = 4.1396e+08# Numerator / Denominator | |
| 623 | print '***' |
|
752 | print '***' | |
| 624 | print '*** RadarConstant' , RadarConstant, '****' |
|
753 | print '*** RadarConstant' , RadarConstant, '****' | |
| 625 | print '***' |
|
754 | print '***' | |
| 626 | ''' ============================= ''' |
|
755 | ''' ============================= ''' | |
| 627 |
|
756 | |||
| 628 | SPCmean = numpy.mean(self.spc,0) |
|
757 | SPCmean = numpy.mean(self.spc,0) | |
| 629 |
ETA = numpy.zeros(self.Num_Hei |
|
758 | ETAf = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |
|
|
759 | ETAv = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |||
|
|
760 | ETAd = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |||
|
|
761 | ||||
| 630 | Pr = self.spc[0,:,:] |
|
762 | Pr = self.spc[0,:,:] | |
| 631 |
|
763 | |||
| 632 | VelMeteoro = numpy.mean(SPCmean,axis=0) |
|
764 | VelMeteoro = numpy.mean(SPCmean,axis=0) | |
| 633 | print '==================== Vel SHAPE',VelMeteoro |
|
|||
| 634 |
|
765 | |||
| 635 | D_range = numpy.zeros(self.Num_Hei) |
|
766 | #print '==================== Vel SHAPE',VelMeteoro | |
| 636 | SIGMA = numpy.zeros(self.Num_Hei) |
|
767 | ||
| 637 |
|
|
768 | D_range = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |
| 638 |
|
|
769 | SIGMA = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |
|
|
770 | N_dist = numpy.zeros([self.Num_Bin,self.Num_Hei]) | |||
|
|
771 | D_mean = numpy.zeros(self.Num_Hei) | |||
| 639 | del_V = numpy.zeros(self.Num_Hei) |
|
772 | del_V = numpy.zeros(self.Num_Hei) | |
|
|
773 | Z = numpy.zeros(self.Num_Hei) | |||
|
|
774 | Ze = numpy.zeros(self.Num_Hei) | |||
|
|
775 | RR = numpy.zeros(self.Num_Hei) | |||
| 640 |
|
776 | |||
| 641 |
|
777 | |||
| 642 | for R in range(self.Num_Hei): |
|
778 | for R in range(self.Num_Hei): | |
| 643 | ETA[:,R] = RadarConstant * Pr[:,R] * R**2 #Reflectivity (ETA) |
|
|||
| 644 |
|
779 | |||
| 645 | h = R + Altitude #Range from ground to radar pulse altitude |
|
780 | h = R*75 + Altitude #Range from ground to radar pulse altitude | |
| 646 | del_V[R] = 1 + 3.68 * 10**-5 * h + 1.71 * 10**-9 * h**2 #Density change correction for velocity |
|
781 | del_V[R] = 1 + 3.68 * 10**-5 * h + 1.71 * 10**-9 * h**2 #Density change correction for velocity | |
| 647 |
|
782 | |||
| 648 |
D_range[R] = numpy.log( (9.65 - (Vel |
|
783 | D_range[:,R] = numpy.log( (9.65 - (Velrange[0:self.Num_Bin] / del_V[R])) / 10.3 ) / -0.6 #Range of Diameter of drops related to velocity | |
| 649 | SIGMA[R] = numpy.pi**5 / Lambda**4 * Km * D_range[R]**6 #Equivalent Section of drops (sigma) |
|
784 | ||
| 650 | #print '******* D_range ********', self.Num_Hei |
|
785 | ETAf[:,R] = 1/RadarConstant * Pr[:,R] * (R*0.075)**2 #Reflectivity (ETA) | |
| 651 |
|
|
786 | ||
| 652 | N_dist[R] = ETA[R] / SIGMA[R] |
|
787 | ETAv[:,R]=ETAf[:,R]*dF/dV | |
|
|
788 | ||||
|
|
789 | ETAd[:,R]=ETAv[:,R]*6.18*exp(-0.6*D_range[:,R]) | |||
|
|
790 | ||||
|
|
791 | SIGMA[:,R] = numpy.pi**5 / Lambda**4 * Km * D_range[:,R]**6 #Equivalent Section of drops (sigma) | |||
|
|
792 | ||||
|
|
793 | N_dist[:,R] = ETAd[:,R] / SIGMA[:,R] | |||
|
|
794 | ||||
|
|
795 | DMoments = self.Moments(Pr[:,R], D_range[:,R]) | |||
| 653 |
|
796 | |||
|
|
797 | try: | |||
|
|
798 | popt01,pcov = curve_fit(self.gaus, D_range[:,R] , Pr[:,R] , p0=DMoments) | |||
|
|
799 | except: | |||
|
|
800 | popt01=numpy.zeros(3) | |||
|
|
801 | popt01[1]= DMoments[1] | |||
|
|
802 | D_mean[R]=popt01[1] | |||
|
|
803 | ||||
|
|
804 | Z[R] = numpy.nansum( N_dist[:,R] * D_range[:,R]**6 ) | |||
| 654 |
|
805 | |||
|
|
806 | RR[R] = 6*10**-4.*numpy.pi * numpy.nansum( D_range[:,R]**3 * N_dist[:,R] * Velrange[0:self.Num_Bin] ) #Rainfall rate | |||
| 655 |
|
807 | |||
| 656 | Ze = (ETA * Lambda**4) / (numpy.pi * Km) |
|
808 | Ze[R] = (numpy.nansum(ETAd[:,R]) * Lambda**4) / (numpy.pi * Km) | |
| 657 | Z = numpy.sum( N_dist * D_range**6 ) |
|
|||
| 658 | #print 'Velrange',len(Velrange), 'D_range', len(D_range) |
|
|||
| 659 | RR = 6*10**-4*numpy.pi * numpy.sum( D_range[R]**3 * N_dist[R] * VelMeteoro[R] ) #Rainfall rate |
|
|||
| 660 |
|
809 | |||
| 661 |
|
810 | |||
| 662 |
|
811 | |||
| 663 |
RR2 = (Z |
|
812 | RR2 = (Z/200)**(1/1.6) | |
| 664 | dBRR = 10*numpy.log10(RR) |
|
813 | dBRR = 10*numpy.log10(RR) | |
|
|
814 | dBRR2 = 10*numpy.log10(RR2) | |||
| 665 |
|
815 | |||
| 666 | dBZe = 10*numpy.log10(Ze) |
|
816 | dBZe = 10*numpy.log10(Ze) | |
| 667 | dataOut.data_output = Ze |
|
817 | dBZ = 10*numpy.log10(Z) | |
|
|
818 | ||||
|
|
819 | dataOut.data_output = Z | |||
| 668 | dataOut.data_param = numpy.ones([3,self.Num_Hei]) |
|
820 | dataOut.data_param = numpy.ones([3,self.Num_Hei]) | |
| 669 | dataOut.channelList = [0,1,2] |
|
821 | dataOut.channelList = [0,1,2] | |
| 670 | print 'channelList', dataOut.channelList |
|
822 | ||
| 671 |
dataOut.data_param[0]=dBZ |
|
823 | dataOut.data_param[0]=dBZ | |
| 672 |
dataOut.data_param[1]=dB |
|
824 | dataOut.data_param[1]=dBZe | |
|
|
825 | dataOut.data_param[2]=dBRR2 | |||
|
|
826 | ||||
| 673 | print 'RR SHAPE', dBRR.shape |
|
827 | print 'RR SHAPE', dBRR.shape | |
| 674 |
print 'Ze |
|
828 | #print 'Ze ', dBZe | |
| 675 | print 'dataOut.data_param SHAPE', dataOut.data_param.shape |
|
829 | print 'Z ', dBZ | |
|
|
830 | print 'RR ', dBRR | |||
|
|
831 | #print 'RR2 ', dBRR2 | |||
|
|
832 | #print 'D_mean', D_mean | |||
|
|
833 | #print 'del_V', del_V | |||
|
|
834 | #print 'D_range',D_range.shape, D_range[:,30] | |||
|
|
835 | #print 'Velrange', Velrange | |||
|
|
836 | #print 'numpy.nansum( N_dist[:,R]', numpy.nansum( N_dist, axis=0) | |||
|
|
837 | #print 'dataOut.data_param SHAPE', dataOut.data_param.shape | |||
| 676 |
|
838 | |||
| 677 |
|
839 | |||
| 678 | def dBZeMODE2(self, dataOut): # Processing for MIRA35C |
|
840 | def dBZeMODE2(self, dataOut): # Processing for MIRA35C | |
| 679 |
|
841 | |||
| 680 | NPW = dataOut.NPW |
|
842 | NPW = dataOut.NPW | |
| 681 | COFA = dataOut.COFA |
|
843 | COFA = dataOut.COFA | |
| 682 |
|
844 | |||
| 683 | SNR = numpy.array([self.spc[0,:,:] / NPW[0]]) #, self.spc[1,:,:] / NPW[1]]) |
|
845 | SNR = numpy.array([self.spc[0,:,:] / NPW[0]]) #, self.spc[1,:,:] / NPW[1]]) | |
| 684 | RadarConst = dataOut.RadarConst |
|
846 | RadarConst = dataOut.RadarConst | |
| 685 | #frequency = 34.85*10**9 |
|
847 | #frequency = 34.85*10**9 | |
| 686 |
|
848 | |||
| 687 | ETA = numpy.zeros(([self.Num_Chn ,self.Num_Hei])) |
|
849 | ETA = numpy.zeros(([self.Num_Chn ,self.Num_Hei])) | |
| 688 | data_output = numpy.ones([self.Num_Chn , self.Num_Hei])*numpy.NaN |
|
850 | data_output = numpy.ones([self.Num_Chn , self.Num_Hei])*numpy.NaN | |
| 689 |
|
851 | |||
| 690 | ETA = numpy.sum(SNR,1) |
|
852 | ETA = numpy.sum(SNR,1) | |
| 691 | print 'ETA' , ETA |
|
853 | print 'ETA' , ETA | |
| 692 | ETA = numpy.where(ETA is not 0. , ETA, numpy.NaN) |
|
854 | ETA = numpy.where(ETA is not 0. , ETA, numpy.NaN) | |
| 693 |
|
855 | |||
| 694 | Ze = numpy.ones([self.Num_Chn, self.Num_Hei] ) |
|
856 | Ze = numpy.ones([self.Num_Chn, self.Num_Hei] ) | |
| 695 |
|
857 | |||
| 696 | for r in range(self.Num_Hei): |
|
858 | for r in range(self.Num_Hei): | |
| 697 |
|
859 | |||
| 698 | Ze[0,r] = ( ETA[0,r] ) * COFA[0,r][0] * RadarConst * ((r/5000.)**2) |
|
860 | Ze[0,r] = ( ETA[0,r] ) * COFA[0,r][0] * RadarConst * ((r/5000.)**2) | |
| 699 | #Ze[1,r] = ( ETA[1,r] ) * COFA[1,r][0] * RadarConst * ((r/5000.)**2) |
|
861 | #Ze[1,r] = ( ETA[1,r] ) * COFA[1,r][0] * RadarConst * ((r/5000.)**2) | |
| 700 |
|
862 | |||
| 701 | return Ze |
|
863 | return Ze | |
| 702 |
|
864 | |||
| 703 | # def GetRadarConstant(self): |
|
865 | # def GetRadarConstant(self): | |
| 704 | # |
|
866 | # | |
| 705 | # """ |
|
867 | # """ | |
| 706 | # Constants: |
|
868 | # Constants: | |
| 707 | # |
|
869 | # | |
| 708 | # Pt: Transmission Power dB 5kW 5000 |
|
870 | # Pt: Transmission Power dB 5kW 5000 | |
| 709 | # Gt: Transmission Gain dB 24.7 dB 295.1209 |
|
871 | # Gt: Transmission Gain dB 24.7 dB 295.1209 | |
| 710 | # Gr: Reception Gain dB 18.5 dB 70.7945 |
|
872 | # Gr: Reception Gain dB 18.5 dB 70.7945 | |
| 711 | # Lambda: Wavelenght m 0.6741 m 0.6741 |
|
873 | # Lambda: Wavelenght m 0.6741 m 0.6741 | |
| 712 | # aL: Attenuation loses dB 4dB 2.5118 |
|
874 | # aL: Attenuation loses dB 4dB 2.5118 | |
| 713 | # tauW: Width of transmission pulse s 4us 4e-6 |
|
875 | # tauW: Width of transmission pulse s 4us 4e-6 | |
| 714 | # ThetaT: Transmission antenna bean angle rad 0.1656317 rad 0.1656317 |
|
876 | # ThetaT: Transmission antenna bean angle rad 0.1656317 rad 0.1656317 | |
| 715 | # ThetaR: Reception antenna beam angle rad 0.36774087 rad 0.36774087 |
|
877 | # ThetaR: Reception antenna beam angle rad 0.36774087 rad 0.36774087 | |
| 716 | # |
|
878 | # | |
| 717 | # """ |
|
879 | # """ | |
| 718 | # |
|
880 | # | |
| 719 | # Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) ) |
|
881 | # Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) ) | |
| 720 | # Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * TauW * numpy.pi * ThetaT * TheraR) |
|
882 | # Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * TauW * numpy.pi * ThetaT * TheraR) | |
| 721 | # RadarConstant = Numerator / Denominator |
|
883 | # RadarConstant = Numerator / Denominator | |
| 722 | # |
|
884 | # | |
| 723 | # return RadarConstant |
|
885 | # return RadarConstant | |
| 724 |
|
886 | |||
| 725 |
|
887 | |||
| 726 |
|
888 | |||
| 727 | class FullSpectralAnalysis(Operation): |
|
889 | class FullSpectralAnalysis(Operation): | |
| 728 |
|
890 | |||
| 729 | """ |
|
891 | """ | |
| 730 | Function that implements Full Spectral Analisys technique. |
|
892 | Function that implements Full Spectral Analisys technique. | |
| 731 |
|
893 | |||
| 732 | Input: |
|
894 | Input: | |
| 733 | self.dataOut.data_pre : SelfSpectra and CrossSPectra data |
|
895 | self.dataOut.data_pre : SelfSpectra and CrossSPectra data | |
| 734 | self.dataOut.groupList : Pairlist of channels |
|
896 | self.dataOut.groupList : Pairlist of channels | |
| 735 | self.dataOut.ChanDist : Physical distance between receivers |
|
897 | self.dataOut.ChanDist : Physical distance between receivers | |
| 736 |
|
898 | |||
| 737 |
|
899 | |||
| 738 | Output: |
|
900 | Output: | |
| 739 |
|
901 | |||
| 740 | self.dataOut.data_output : Zonal wind, Meridional wind and Vertical wind |
|
902 | self.dataOut.data_output : Zonal wind, Meridional wind and Vertical wind | |
| 741 |
|
903 | |||
| 742 |
|
904 | |||
| 743 | Parameters affected: Winds, height range, SNR |
|
905 | Parameters affected: Winds, height range, SNR | |
| 744 |
|
906 | |||
| 745 | """ |
|
907 | """ | |
| 746 | def run(self, dataOut, E01=None, E02=None, E12=None, N01=None, N02=None, N12=None, SNRlimit=7): |
|
908 | def run(self, dataOut, E01=None, E02=None, E12=None, N01=None, N02=None, N12=None, SNRlimit=7): | |
| 747 |
|
909 | |||
| 748 | self.indice=int(numpy.random.rand()*1000) |
|
910 | self.indice=int(numpy.random.rand()*1000) | |
| 749 |
|
911 | |||
| 750 | spc = dataOut.data_pre[0] |
|
912 | spc = dataOut.data_pre[0].copy() | |
| 751 | cspc = dataOut.data_pre[1] |
|
913 | cspc = dataOut.data_pre[1] | |
| 752 |
|
914 | |||
| 753 | nChannel = spc.shape[0] |
|
915 | nChannel = spc.shape[0] | |
| 754 | nProfiles = spc.shape[1] |
|
916 | nProfiles = spc.shape[1] | |
| 755 | nHeights = spc.shape[2] |
|
917 | nHeights = spc.shape[2] | |
| 756 |
|
918 | |||
| 757 | pairsList = dataOut.groupList |
|
919 | pairsList = dataOut.groupList | |
| 758 | if dataOut.ChanDist is not None : |
|
920 | if dataOut.ChanDist is not None : | |
| 759 | ChanDist = dataOut.ChanDist |
|
921 | ChanDist = dataOut.ChanDist | |
| 760 | else: |
|
922 | else: | |
| 761 | ChanDist = numpy.array([[E01, N01],[E02,N02],[E12,N12]]) |
|
923 | ChanDist = numpy.array([[E01, N01],[E02,N02],[E12,N12]]) | |
| 762 |
|
924 | |||
| 763 | #print 'ChanDist', ChanDist |
|
925 | FrecRange = dataOut.spc_range[0] | |
| 764 |
|
||||
| 765 | #if dataOut.VelRange is not None: |
|
|||
| 766 | AbbsisaRange= dataOut.spc_range#dataOut.VelRange |
|
|||
| 767 | #else: |
|
|||
| 768 | # AbbsisaRange= dataOut.spc_range#dataOut.abscissaList |
|
|||
| 769 |
|
926 | |||
| 770 | ySamples=numpy.ones([nChannel,nProfiles]) |
|
927 | ySamples=numpy.ones([nChannel,nProfiles]) | |
| 771 | phase=numpy.ones([nChannel,nProfiles]) |
|
928 | phase=numpy.ones([nChannel,nProfiles]) | |
| 772 | CSPCSamples=numpy.ones([nChannel,nProfiles],dtype=numpy.complex_) |
|
929 | CSPCSamples=numpy.ones([nChannel,nProfiles],dtype=numpy.complex_) | |
| 773 | coherence=numpy.ones([nChannel,nProfiles]) |
|
930 | coherence=numpy.ones([nChannel,nProfiles]) | |
| 774 | PhaseSlope=numpy.ones(nChannel) |
|
931 | PhaseSlope=numpy.ones(nChannel) | |
| 775 | PhaseInter=numpy.ones(nChannel) |
|
932 | PhaseInter=numpy.ones(nChannel) | |
| 776 | dataSNR = dataOut.data_SNR |
|
933 | data_SNR=numpy.zeros([nProfiles]) | |
| 777 |
|
||||
| 778 |
|
||||
| 779 |
|
934 | |||
| 780 | data = dataOut.data_pre |
|
935 | data = dataOut.data_pre | |
| 781 | noise = dataOut.noise |
|
936 | noise = dataOut.noise | |
| 782 | #print 'noise',noise |
|
|||
| 783 | #SNRdB = 10*numpy.log10(dataOut.data_SNR) |
|
|||
| 784 |
|
937 | |||
| 785 | FirstMoment = dataOut.data_param[0,1,:]#numpy.average(dataOut.data_param[:,1,:],0) |
|
938 | dataOut.data_SNR = (numpy.mean(spc,axis=1)- noise[0]) / noise[0] | |
| 786 | SecondMoment = numpy.average(dataOut.data_param[:,2,:],0) |
|
|||
| 787 |
|
939 | |||
| 788 | #SNRdBMean = [] |
|
|||
| 789 |
|
||||
| 790 |
|
940 | |||
| 791 | #for j in range(nHeights): |
|
|||
| 792 | # FirstMoment = numpy.append(FirstMoment,numpy.mean([dataOut.data_param[0,1,j],dataOut.data_param[1,1,j],dataOut.data_param[2,1,j]])) |
|
|||
| 793 | # SNRdBMean = numpy.append(SNRdBMean,numpy.mean([SNRdB[0,j],SNRdB[1,j],SNRdB[2,j]])) |
|
|||
| 794 |
|
941 | |||
| 795 | data_output=numpy.ones([3,spc.shape[2]])*numpy.NaN |
|
942 | print dataOut.data_SNR.shape | |
|
|
943 | #FirstMoment = dataOut.moments[0,1,:]#numpy.average(dataOut.data_param[:,1,:],0) | |||
|
|
944 | #SecondMoment = numpy.average(dataOut.moments[:,2,:],0) | |||
|
|
945 | ||||
|
|
946 | #SNRdBMean = [] | |||
|
|
947 | ||||
|
|
948 | data_output=numpy.ones([spc.shape[0],spc.shape[2]])*numpy.NaN | |||
| 796 |
|
949 | |||
| 797 | velocityX=[] |
|
950 | velocityX=[] | |
| 798 | velocityY=[] |
|
951 | velocityY=[] | |
| 799 | velocityV=[] |
|
952 | velocityV=[] | |
| 800 | PhaseLine=[] |
|
953 | PhaseLine=[] | |
| 801 |
|
954 | |||
| 802 | dbSNR = 10*numpy.log10(dataSNR) |
|
955 | dbSNR = 10*numpy.log10(dataOut.data_SNR) | |
| 803 | dbSNR = numpy.average(dbSNR,0) |
|
956 | dbSNR = numpy.average(dbSNR,0) | |
| 804 |
|
957 | |||
| 805 | for Height in range(nHeights): |
|
958 | for Height in range(nHeights): | |
| 806 |
|
959 | |||
| 807 |
[Vzon,Vmer,Vver, GaussCenter, PhaseSlope, FitGaussCSPC]= self.WindEstimation( |
|
960 | [Vzon,Vmer,Vver, GaussCenter, PhaseSlope, FitGaussCSPC]= self.WindEstimation(spc, cspc, pairsList, ChanDist, Height, noise, dataOut.spc_range.copy(), dbSNR[Height], SNRlimit) | |
| 808 | PhaseLine = numpy.append(PhaseLine, PhaseSlope) |
|
961 | PhaseLine = numpy.append(PhaseLine, PhaseSlope) | |
| 809 |
|
962 | |||
| 810 | if abs(Vzon)<100. and abs(Vzon)> 0.: |
|
963 | if abs(Vzon)<100. and abs(Vzon)> 0.: | |
| 811 | velocityX=numpy.append(velocityX, -Vzon)#Vmag |
|
964 | velocityX=numpy.append(velocityX, -Vzon)#Vmag | |
| 812 |
|
965 | |||
| 813 | else: |
|
966 | else: | |
| 814 | #print 'Vzon',Vzon |
|
967 | #print 'Vzon',Vzon | |
| 815 | velocityX=numpy.append(velocityX, numpy.NaN) |
|
968 | velocityX=numpy.append(velocityX, numpy.NaN) | |
| 816 |
|
969 | |||
| 817 | if abs(Vmer)<100. and abs(Vmer) > 0.: |
|
970 | if abs(Vmer)<100. and abs(Vmer) > 0.: | |
| 818 | velocityY=numpy.append(velocityY, -Vmer)#Vang |
|
971 | velocityY=numpy.append(velocityY, -Vmer)#Vang | |
| 819 |
|
972 | |||
| 820 | else: |
|
973 | else: | |
| 821 | #print 'Vmer',Vmer |
|
974 | #print 'Vmer',Vmer | |
| 822 | velocityY=numpy.append(velocityY, numpy.NaN) |
|
975 | velocityY=numpy.append(velocityY, numpy.NaN) | |
| 823 |
|
976 | |||
| 824 | if dbSNR[Height] > SNRlimit: |
|
977 | if dbSNR[Height] > SNRlimit: | |
| 825 |
velocityV=numpy.append(velocityV, |
|
978 | velocityV=numpy.append(velocityV, -Vver)#FirstMoment[Height]) | |
| 826 | else: |
|
979 | else: | |
| 827 | velocityV=numpy.append(velocityV, numpy.NaN) |
|
980 | velocityV=numpy.append(velocityV, numpy.NaN) | |
| 828 | #FirstMoment[Height]= numpy.NaN |
|
981 | #FirstMoment[Height]= numpy.NaN | |
| 829 | # if SNRdBMean[Height] <12: |
|
982 | # if SNRdBMean[Height] <12: | |
| 830 | # FirstMoment[Height] = numpy.NaN |
|
983 | # FirstMoment[Height] = numpy.NaN | |
| 831 | # velocityX[Height] = numpy.NaN |
|
984 | # velocityX[Height] = numpy.NaN | |
| 832 | # velocityY[Height] = numpy.NaN |
|
985 | # velocityY[Height] = numpy.NaN | |
| 833 |
|
986 | |||
| 834 |
|
987 | |||
| 835 |
|
988 | |||
| 836 | data_output[0] = numpy.array(velocityX) #self.moving_average(numpy.array(velocityX) , N=1) |
|
989 | data_output[0] = numpy.array(velocityX) #self.moving_average(numpy.array(velocityX) , N=1) | |
| 837 | data_output[1] = numpy.array(velocityY) #self.moving_average(numpy.array(velocityY) , N=1) |
|
990 | data_output[1] = numpy.array(velocityY) #self.moving_average(numpy.array(velocityY) , N=1) | |
| 838 | data_output[2] = -velocityV#FirstMoment |
|
991 | data_output[2] = -velocityV#FirstMoment | |
| 839 |
|
|
992 | ||
| 840 | print ' ' |
|
993 | print 'FirstMoment', data_output[2] | |
| 841 | #print 'FirstMoment' |
|
|||
| 842 | #print FirstMoment |
|
994 | #print FirstMoment | |
| 843 | print 'velocityX',numpy.shape(data_output[0]) |
|
995 | # print 'velocityX',numpy.shape(data_output[0]) | |
| 844 | print 'velocityX',data_output[0] |
|
996 | # print 'velocityX',data_output[0] | |
| 845 | print ' ' |
|
997 | # print ' ' | |
| 846 | print 'velocityY',numpy.shape(data_output[1]) |
|
998 | # print 'velocityY',numpy.shape(data_output[1]) | |
| 847 | print 'velocityY',data_output[1] |
|
999 | # print 'velocityY',data_output[1] | |
| 848 | print 'velocityV',data_output[2] |
|
1000 | # print 'velocityV',data_output[2] | |
| 849 | print 'PhaseLine',PhaseLine |
|
1001 | # print 'PhaseLine',PhaseLine | |
| 850 | #print numpy.array(velocityY) |
|
1002 | #print numpy.array(velocityY) | |
| 851 | #print 'SNR' |
|
1003 | #print 'SNR' | |
| 852 | #print 10*numpy.log10(dataOut.data_SNR) |
|
1004 | #print 10*numpy.log10(dataOut.data_SNR) | |
| 853 | #print numpy.shape(10*numpy.log10(dataOut.data_SNR)) |
|
1005 | #print numpy.shape(10*numpy.log10(dataOut.data_SNR)) | |
| 854 | print ' ' |
|
1006 | print ' ' | |
| 855 |
|
1007 | |||
| 856 |
xFrec= |
|
1008 | xFrec=FrecRange[0:spc.shape[1]] | |
| 857 |
|
1009 | |||
| 858 | dataOut.data_output=data_output |
|
1010 | dataOut.data_output=data_output | |
| 859 |
|
1011 | |||
| 860 | return |
|
1012 | return | |
| 861 |
|
1013 | |||
| 862 |
|
1014 | |||
| 863 | def moving_average(self,x, N=2): |
|
1015 | def moving_average(self,x, N=2): | |
| 864 | return numpy.convolve(x, numpy.ones((N,))/N)[(N-1):] |
|
1016 | return numpy.convolve(x, numpy.ones((N,))/N)[(N-1):] | |
| 865 |
|
1017 | |||
| 866 | def gaus(self,xSamples,Amp,Mu,Sigma): |
|
1018 | def gaus(self,xSamples,Amp,Mu,Sigma): | |
| 867 | return ( Amp / ((2*numpy.pi)**0.5 * Sigma) ) * numpy.exp( -( xSamples - Mu )**2 / ( 2 * (Sigma**2) )) |
|
1019 | return ( Amp / ((2*numpy.pi)**0.5 * Sigma) ) * numpy.exp( -( xSamples - Mu )**2 / ( 2 * (Sigma**2) )) | |
| 868 |
|
1020 | |||
| 869 |
|
1021 | |||
| 870 |
|
1022 | |||
| 871 | def Moments(self, ySamples, xSamples): |
|
1023 | def Moments(self, ySamples, xSamples): | |
| 872 | Pot = numpy.nansum( ySamples ) # Potencia, momento 0 |
|
1024 | Pot = numpy.nansum( ySamples ) # Potencia, momento 0 | |
| 873 | yNorm = ySamples / Pot |
|
1025 | yNorm = ySamples / Pot | |
| 874 |
|
1026 | |||
| 875 | Vr = numpy.nansum( yNorm * xSamples ) # Velocidad radial, mu, corrimiento doppler, primer momento |
|
1027 | Vr = numpy.nansum( yNorm * xSamples ) # Velocidad radial, mu, corrimiento doppler, primer momento | |
| 876 | Sigma2 = abs(numpy.nansum( yNorm * ( xSamples - Vr )**2 )) # Segundo Momento |
|
1028 | Sigma2 = abs(numpy.nansum( yNorm * ( xSamples - Vr )**2 )) # Segundo Momento | |
| 877 | Desv = Sigma2**0.5 # Desv. Estandar, Ancho espectral |
|
1029 | Desv = Sigma2**0.5 # Desv. Estandar, Ancho espectral | |
| 878 |
|
1030 | |||
| 879 | return numpy.array([Pot, Vr, Desv]) |
|
1031 | return numpy.array([Pot, Vr, Desv]) | |
| 880 |
|
1032 | |||
| 881 |
def WindEstimation(self |
|
1033 | def WindEstimation(self, spc, cspc, pairsList, ChanDist, Height, noise, AbbsisaRange, dbSNR, SNRlimit): | |
| 882 |
|
1034 | |||
| 883 | print ' ' |
|
1035 | # print ' ' | |
| 884 | print '######################## Height',Height, (1000 + 75*Height), '##############################' |
|
1036 | # print '######################## Height',Height, (1000 + 75*Height), '##############################' | |
| 885 | print ' ' |
|
1037 | # print ' ' | |
| 886 |
|
1038 | |||
| 887 | ySamples=numpy.ones([spc.shape[0],spc.shape[1]]) |
|
1039 | ySamples=numpy.ones([spc.shape[0],spc.shape[1]]) | |
| 888 | phase=numpy.ones([spc.shape[0],spc.shape[1]]) |
|
1040 | phase=numpy.ones([spc.shape[0],spc.shape[1]]) | |
| 889 | CSPCSamples=numpy.ones([spc.shape[0],spc.shape[1]],dtype=numpy.complex_) |
|
1041 | CSPCSamples=numpy.ones([spc.shape[0],spc.shape[1]],dtype=numpy.complex_) | |
| 890 | coherence=numpy.ones([spc.shape[0],spc.shape[1]]) |
|
1042 | coherence=numpy.ones([spc.shape[0],spc.shape[1]]) | |
| 891 | PhaseSlope=numpy.zeros(spc.shape[0]) |
|
1043 | PhaseSlope=numpy.zeros(spc.shape[0]) | |
| 892 | PhaseInter=numpy.ones(spc.shape[0]) |
|
1044 | PhaseInter=numpy.ones(spc.shape[0]) | |
| 893 | xFrec=AbbsisaRange[0][0:spc.shape[1]] |
|
1045 | xFrec=AbbsisaRange[0][0:spc.shape[1]] | |
| 894 | xVel =AbbsisaRange[2][0:spc.shape[1]] |
|
1046 | xVel =AbbsisaRange[2][0:spc.shape[1]] | |
| 895 | Vv=numpy.empty(spc.shape[2])*0 |
|
1047 | Vv=numpy.empty(spc.shape[2])*0 | |
| 896 | SPCav = numpy.average(spc, axis=0)-numpy.average(noise) #spc[0]-noise[0]# |
|
1048 | SPCav = numpy.average(spc, axis=0)-numpy.average(noise) #spc[0]-noise[0]# | |
| 897 |
|
1049 | |||
| 898 | SPCmoments = self.Moments(SPCav[:,Height], xVel ) |
|
1050 | SPCmoments = self.Moments(SPCav[:,Height], xVel ) | |
| 899 | CSPCmoments = [] |
|
1051 | CSPCmoments = [] | |
| 900 | cspcNoise = numpy.empty(3) |
|
1052 | cspcNoise = numpy.empty(3) | |
| 901 |
|
1053 | |||
| 902 | '''Getting Eij and Nij''' |
|
1054 | '''Getting Eij and Nij''' | |
| 903 |
|
1055 | |||
| 904 | E01=ChanDist[0][0] |
|
1056 | E01=ChanDist[0][0] | |
| 905 | N01=ChanDist[0][1] |
|
1057 | N01=ChanDist[0][1] | |
| 906 |
|
1058 | |||
| 907 | E02=ChanDist[1][0] |
|
1059 | E02=ChanDist[1][0] | |
| 908 | N02=ChanDist[1][1] |
|
1060 | N02=ChanDist[1][1] | |
| 909 |
|
1061 | |||
| 910 | E12=ChanDist[2][0] |
|
1062 | E12=ChanDist[2][0] | |
| 911 | N12=ChanDist[2][1] |
|
1063 | N12=ChanDist[2][1] | |
| 912 |
|
1064 | |||
| 913 | z = spc.copy() |
|
1065 | z = spc.copy() | |
| 914 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
|
1066 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
| 915 |
|
1067 | |||
| 916 | for i in range(spc.shape[0]): |
|
1068 | for i in range(spc.shape[0]): | |
| 917 |
|
1069 | |||
| 918 | '''****** Line of Data SPC ******''' |
|
1070 | '''****** Line of Data SPC ******''' | |
| 919 | zline=z[i,:,Height].copy() - noise[i] # Se resta ruido |
|
1071 | zline=z[i,:,Height].copy() - noise[i] # Se resta ruido | |
| 920 |
|
1072 | |||
| 921 | '''****** SPC is normalized ******''' |
|
1073 | '''****** SPC is normalized ******''' | |
| 922 | SmoothSPC =self.moving_average(zline.copy(),N=1) # Se suaviza el ruido |
|
1074 | SmoothSPC =self.moving_average(zline.copy(),N=1) # Se suaviza el ruido | |
| 923 | FactNorm = SmoothSPC/numpy.nansum(SmoothSPC) # SPC Normalizado y suavizado |
|
1075 | FactNorm = SmoothSPC/numpy.nansum(SmoothSPC) # SPC Normalizado y suavizado | |
| 924 |
|
1076 | |||
| 925 | xSamples = xFrec # Se toma el rango de frecuncias |
|
1077 | xSamples = xFrec # Se toma el rango de frecuncias | |
| 926 | ySamples[i] = FactNorm # Se toman los valores de SPC normalizado |
|
1078 | ySamples[i] = FactNorm # Se toman los valores de SPC normalizado | |
| 927 |
|
1079 | |||
| 928 | for i in range(spc.shape[0]): |
|
1080 | for i in range(spc.shape[0]): | |
| 929 |
|
1081 | |||
| 930 | '''****** Line of Data CSPC ******''' |
|
1082 | '''****** Line of Data CSPC ******''' | |
| 931 | cspcLine = ( cspc[i,:,Height].copy())# - noise[i] ) # no! Se resta el ruido |
|
1083 | cspcLine = ( cspc[i,:,Height].copy())# - noise[i] ) # no! Se resta el ruido | |
| 932 | SmoothCSPC =self.moving_average(cspcLine,N=1) # Se suaviza el ruido |
|
1084 | SmoothCSPC =self.moving_average(cspcLine,N=1) # Se suaviza el ruido | |
| 933 | cspcNorm = SmoothCSPC/numpy.nansum(SmoothCSPC) # CSPC normalizado y suavizado |
|
1085 | cspcNorm = SmoothCSPC/numpy.nansum(SmoothCSPC) # CSPC normalizado y suavizado | |
| 934 |
|
1086 | |||
| 935 | '''****** CSPC is normalized with respect to Briggs and Vincent ******''' |
|
1087 | '''****** CSPC is normalized with respect to Briggs and Vincent ******''' | |
| 936 | chan_index0 = pairsList[i][0] |
|
1088 | chan_index0 = pairsList[i][0] | |
| 937 | chan_index1 = pairsList[i][1] |
|
1089 | chan_index1 = pairsList[i][1] | |
| 938 |
|
1090 | |||
| 939 | CSPCFactor= numpy.abs(numpy.nansum(ySamples[chan_index0]))**2 * numpy.abs(numpy.nansum(ySamples[chan_index1]))**2 |
|
1091 | CSPCFactor= numpy.abs(numpy.nansum(ySamples[chan_index0]))**2 * numpy.abs(numpy.nansum(ySamples[chan_index1]))**2 | |
| 940 | CSPCNorm = cspcNorm / numpy.sqrt(CSPCFactor) |
|
1092 | CSPCNorm = cspcNorm / numpy.sqrt(CSPCFactor) | |
| 941 |
|
1093 | |||
| 942 | CSPCSamples[i] = CSPCNorm |
|
1094 | CSPCSamples[i] = CSPCNorm | |
| 943 |
|
1095 | |||
| 944 | coherence[i] = numpy.abs(CSPCSamples[i]) / numpy.sqrt(CSPCFactor) |
|
1096 | coherence[i] = numpy.abs(CSPCSamples[i]) / numpy.sqrt(CSPCFactor) | |
| 945 |
|
1097 | |||
| 946 | #coherence[i]= self.moving_average(coherence[i],N=1) |
|
1098 | #coherence[i]= self.moving_average(coherence[i],N=1) | |
| 947 |
|
1099 | |||
| 948 | phase[i] = self.moving_average( numpy.arctan2(CSPCSamples[i].imag, CSPCSamples[i].real),N=1)#*180/numpy.pi |
|
1100 | phase[i] = self.moving_average( numpy.arctan2(CSPCSamples[i].imag, CSPCSamples[i].real),N=1)#*180/numpy.pi | |
| 949 |
|
1101 | |||
| 950 | CSPCmoments = numpy.vstack([self.Moments(numpy.abs(CSPCSamples[0]), xSamples), |
|
1102 | CSPCmoments = numpy.vstack([self.Moments(numpy.abs(CSPCSamples[0]), xSamples), | |
| 951 | self.Moments(numpy.abs(CSPCSamples[1]), xSamples), |
|
1103 | self.Moments(numpy.abs(CSPCSamples[1]), xSamples), | |
| 952 | self.Moments(numpy.abs(CSPCSamples[2]), xSamples)]) |
|
1104 | self.Moments(numpy.abs(CSPCSamples[2]), xSamples)]) | |
| 953 |
|
1105 | |||
| 954 | #print '##### SUMA de SPC #####', len(ySamples) |
|
1106 | #print '##### SUMA de SPC #####', len(ySamples) | |
| 955 | #print numpy.sum(ySamples[0]) |
|
1107 | #print numpy.sum(ySamples[0]) | |
| 956 | #print '##### SUMA de CSPC #####', len(coherence) |
|
1108 | #print '##### SUMA de CSPC #####', len(coherence) | |
| 957 | #print numpy.sum(numpy.abs(CSPCNorm)) |
|
1109 | #print numpy.sum(numpy.abs(CSPCNorm)) | |
| 958 | #print numpy.sum(coherence[0]) |
|
1110 | #print numpy.sum(coherence[0]) | |
| 959 | print 'len',len(xSamples) |
|
1111 | # print 'len',len(xSamples) | |
| 960 | print 'CSPCmoments', numpy.shape(CSPCmoments) |
|
1112 | # print 'CSPCmoments', numpy.shape(CSPCmoments) | |
| 961 | print CSPCmoments |
|
1113 | # print CSPCmoments | |
| 962 | print '#######################' |
|
1114 | # print '#######################' | |
| 963 |
|
1115 | |||
| 964 | popt=[1e-10,1e-10,1e-10] |
|
1116 | popt=[1e-10,1e-10,1e-10] | |
| 965 | popt01, popt02, popt12 = [1e-10,1e-10,1e-10], [1e-10,1e-10,1e-10] ,[1e-10,1e-10,1e-10] |
|
1117 | popt01, popt02, popt12 = [1e-10,1e-10,1e-10], [1e-10,1e-10,1e-10] ,[1e-10,1e-10,1e-10] | |
| 966 | FitGauss01, FitGauss02, FitGauss12 = numpy.empty(len(xSamples))*0, numpy.empty(len(xSamples))*0, numpy.empty(len(xSamples))*0 |
|
1118 | FitGauss01, FitGauss02, FitGauss12 = numpy.empty(len(xSamples))*0, numpy.empty(len(xSamples))*0, numpy.empty(len(xSamples))*0 | |
| 967 |
|
1119 | |||
| 968 | CSPCMask01 = numpy.abs(CSPCSamples[0]) |
|
1120 | CSPCMask01 = numpy.abs(CSPCSamples[0]) | |
| 969 | CSPCMask02 = numpy.abs(CSPCSamples[1]) |
|
1121 | CSPCMask02 = numpy.abs(CSPCSamples[1]) | |
| 970 | CSPCMask12 = numpy.abs(CSPCSamples[2]) |
|
1122 | CSPCMask12 = numpy.abs(CSPCSamples[2]) | |
| 971 |
|
1123 | |||
| 972 | mask01 = ~numpy.isnan(CSPCMask01) |
|
1124 | mask01 = ~numpy.isnan(CSPCMask01) | |
| 973 | mask02 = ~numpy.isnan(CSPCMask02) |
|
1125 | mask02 = ~numpy.isnan(CSPCMask02) | |
| 974 | mask12 = ~numpy.isnan(CSPCMask12) |
|
1126 | mask12 = ~numpy.isnan(CSPCMask12) | |
| 975 |
|
1127 | |||
| 976 | #mask = ~numpy.isnan(CSPCMask01) |
|
1128 | #mask = ~numpy.isnan(CSPCMask01) | |
| 977 | CSPCMask01 = CSPCMask01[mask01] |
|
1129 | CSPCMask01 = CSPCMask01[mask01] | |
| 978 | CSPCMask02 = CSPCMask02[mask02] |
|
1130 | CSPCMask02 = CSPCMask02[mask02] | |
| 979 | CSPCMask12 = CSPCMask12[mask12] |
|
1131 | CSPCMask12 = CSPCMask12[mask12] | |
| 980 | #CSPCMask01 = numpy.ma.masked_invalid(CSPCMask01) |
|
1132 | #CSPCMask01 = numpy.ma.masked_invalid(CSPCMask01) | |
| 981 |
|
1133 | |||
| 982 |
|
1134 | |||
| 983 |
|
1135 | |||
| 984 |
|
||||
| 985 |
|
||||
| 986 | '''***Fit Gauss CSPC01***''' |
|
1136 | '''***Fit Gauss CSPC01***''' | |
| 987 | if dbSNR > SNRlimit: |
|
1137 | if dbSNR > SNRlimit: | |
| 988 | try: |
|
1138 | try: | |
| 989 | popt01,pcov = curve_fit(self.gaus,xSamples[mask01],numpy.abs(CSPCMask01),p0=CSPCmoments[0]) |
|
1139 | popt01,pcov = curve_fit(self.gaus,xSamples[mask01],numpy.abs(CSPCMask01),p0=CSPCmoments[0]) | |
| 990 | popt02,pcov = curve_fit(self.gaus,xSamples[mask02],numpy.abs(CSPCMask02),p0=CSPCmoments[1]) |
|
1140 | popt02,pcov = curve_fit(self.gaus,xSamples[mask02],numpy.abs(CSPCMask02),p0=CSPCmoments[1]) | |
| 991 | popt12,pcov = curve_fit(self.gaus,xSamples[mask12],numpy.abs(CSPCMask12),p0=CSPCmoments[2]) |
|
1141 | popt12,pcov = curve_fit(self.gaus,xSamples[mask12],numpy.abs(CSPCMask12),p0=CSPCmoments[2]) | |
| 992 | FitGauss01 = self.gaus(xSamples,*popt01) |
|
1142 | FitGauss01 = self.gaus(xSamples,*popt01) | |
| 993 | FitGauss02 = self.gaus(xSamples,*popt02) |
|
1143 | FitGauss02 = self.gaus(xSamples,*popt02) | |
| 994 | FitGauss12 = self.gaus(xSamples,*popt12) |
|
1144 | FitGauss12 = self.gaus(xSamples,*popt12) | |
| 995 | except: |
|
1145 | except: | |
| 996 | FitGauss01=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[0])) |
|
1146 | FitGauss01=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[0])) | |
| 997 | FitGauss02=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[1])) |
|
1147 | FitGauss02=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[1])) | |
| 998 | FitGauss12=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[2])) |
|
1148 | FitGauss12=numpy.ones(len(xSamples))*numpy.mean(numpy.abs(CSPCSamples[2])) | |
| 999 |
|
1149 | |||
| 1000 |
|
1150 | |||
| 1001 | CSPCopt = numpy.vstack([popt01,popt02,popt12]) |
|
1151 | CSPCopt = numpy.vstack([popt01,popt02,popt12]) | |
| 1002 |
|
1152 | |||
| 1003 | '''****** Getting fij width ******''' |
|
1153 | '''****** Getting fij width ******''' | |
| 1004 |
|
1154 | |||
| 1005 | yMean = numpy.average(ySamples, axis=0) # ySamples[0] |
|
1155 | yMean = numpy.average(ySamples, axis=0) # ySamples[0] | |
| 1006 |
|
1156 | |||
| 1007 | '''******* Getting fitting Gaussian *******''' |
|
1157 | '''******* Getting fitting Gaussian *******''' | |
| 1008 | meanGauss = sum(xSamples*yMean) / len(xSamples) # Mu, velocidad radial (frecuencia) |
|
1158 | meanGauss = sum(xSamples*yMean) / len(xSamples) # Mu, velocidad radial (frecuencia) | |
| 1009 | sigma2 = sum(yMean*(xSamples-meanGauss)**2) / len(xSamples) # Varianza, Ancho espectral (frecuencia) |
|
1159 | sigma2 = sum(yMean*(xSamples-meanGauss)**2) / len(xSamples) # Varianza, Ancho espectral (frecuencia) | |
| 1010 |
|
1160 | |||
| 1011 | yMoments = self.Moments(yMean, xSamples) |
|
1161 | yMoments = self.Moments(yMean, xSamples) | |
| 1012 |
|
1162 | |||
| 1013 | if dbSNR > SNRlimit: # and abs(meanGauss/sigma2) > 0.00001: |
|
1163 | if dbSNR > SNRlimit: # and abs(meanGauss/sigma2) > 0.00001: | |
| 1014 | try: |
|
1164 | try: | |
| 1015 | popt,pcov = curve_fit(self.gaus,xSamples,yMean,p0=yMoments) |
|
1165 | popt,pcov = curve_fit(self.gaus,xSamples,yMean,p0=yMoments) | |
| 1016 | FitGauss=self.gaus(xSamples,*popt) |
|
1166 | FitGauss=self.gaus(xSamples,*popt) | |
| 1017 |
|
1167 | |||
| 1018 | except :#RuntimeError: |
|
1168 | except :#RuntimeError: | |
| 1019 | FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) |
|
1169 | FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) | |
| 1020 |
|
1170 | |||
| 1021 |
|
1171 | |||
| 1022 | else: |
|
1172 | else: | |
| 1023 | FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) |
|
1173 | FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) | |
| 1024 |
|
1174 | |||
| 1025 |
|
1175 | |||
| 1026 |
|
1176 | |||
| 1027 | '''****** Getting Fij ******''' |
|
1177 | '''****** Getting Fij ******''' | |
| 1028 | Fijcspc = CSPCopt[:,2]/2*3 |
|
1178 | Fijcspc = CSPCopt[:,2]/2*3 | |
| 1029 |
|
1179 | |||
| 1030 | #GauWidth = (popt[2]/2)*3 |
|
1180 | #GauWidth = (popt[2]/2)*3 | |
| 1031 | GaussCenter = popt[1] #xFrec[GCpos] |
|
1181 | GaussCenter = popt[1] #xFrec[GCpos] | |
| 1032 | #Punto en Eje X de la Gaussiana donde se encuentra el centro |
|
1182 | #Punto en Eje X de la Gaussiana donde se encuentra el centro | |
| 1033 | ClosestCenter = xSamples[numpy.abs(xSamples-GaussCenter).argmin()] |
|
1183 | ClosestCenter = xSamples[numpy.abs(xSamples-GaussCenter).argmin()] | |
| 1034 | PointGauCenter = numpy.where(xSamples==ClosestCenter)[0][0] |
|
1184 | PointGauCenter = numpy.where(xSamples==ClosestCenter)[0][0] | |
| 1035 |
|
1185 | |||
| 1036 | #Punto e^-1 hubicado en la Gaussiana |
|
1186 | #Punto e^-1 hubicado en la Gaussiana | |
| 1037 | PeMinus1 = numpy.max(FitGauss)* numpy.exp(-1) |
|
1187 | PeMinus1 = numpy.max(FitGauss)* numpy.exp(-1) | |
| 1038 | FijClosest = FitGauss[numpy.abs(FitGauss-PeMinus1).argmin()] # El punto mas cercano a "Peminus1" dentro de "FitGauss" |
|
1188 | FijClosest = FitGauss[numpy.abs(FitGauss-PeMinus1).argmin()] # El punto mas cercano a "Peminus1" dentro de "FitGauss" | |
| 1039 | PointFij = numpy.where(FitGauss==FijClosest)[0][0] |
|
1189 | PointFij = numpy.where(FitGauss==FijClosest)[0][0] | |
| 1040 |
|
1190 | |||
| 1041 | if xSamples[PointFij] > xSamples[PointGauCenter]: |
|
1191 | if xSamples[PointFij] > xSamples[PointGauCenter]: | |
| 1042 | Fij = xSamples[PointFij] - xSamples[PointGauCenter] |
|
1192 | Fij = xSamples[PointFij] - xSamples[PointGauCenter] | |
| 1043 |
|
1193 | |||
| 1044 | else: |
|
1194 | else: | |
| 1045 | Fij = xSamples[PointGauCenter] - xSamples[PointFij] |
|
1195 | Fij = xSamples[PointGauCenter] - xSamples[PointFij] | |
| 1046 |
|
1196 | |||
| 1047 | print 'CSPCopt' |
|
1197 | # print 'CSPCopt' | |
| 1048 | print CSPCopt |
|
1198 | # print CSPCopt | |
| 1049 | print 'popt' |
|
1199 | # print 'popt' | |
| 1050 | print popt |
|
1200 | # print popt | |
| 1051 | print '#######################################' |
|
1201 | # print '#######################################' | |
| 1052 | #print 'dataOut.data_param', numpy.shape(data_param) |
|
1202 | #print 'dataOut.data_param', numpy.shape(data_param) | |
| 1053 | #print 'dataOut.data_param0', data_param[0,0,Height] |
|
1203 | #print 'dataOut.data_param0', data_param[0,0,Height] | |
| 1054 | #print 'dataOut.data_param1', data_param[0,1,Height] |
|
1204 | #print 'dataOut.data_param1', data_param[0,1,Height] | |
| 1055 | #print 'dataOut.data_param2', data_param[0,2,Height] |
|
1205 | #print 'dataOut.data_param2', data_param[0,2,Height] | |
| 1056 |
|
1206 | |||
| 1057 |
|
1207 | |||
| 1058 | print 'yMoments', yMoments |
|
1208 | # print 'yMoments', yMoments | |
| 1059 | print 'Moments', SPCmoments |
|
1209 | # print 'Moments', SPCmoments | |
| 1060 | print 'Fij2 Moment', Fij |
|
1210 | # print 'Fij2 Moment', Fij | |
| 1061 | #print 'Fij', Fij, 'popt[2]/2',popt[2]/2 |
|
1211 | # #print 'Fij', Fij, 'popt[2]/2',popt[2]/2 | |
| 1062 | print 'Fijcspc',Fijcspc |
|
1212 | # print 'Fijcspc',Fijcspc | |
| 1063 | print '#######################################' |
|
1213 | # print '#######################################' | |
| 1064 |
|
||||
| 1065 |
|
||||
| 1066 | # Range = numpy.empty([3,2]) |
|
|||
| 1067 | # GaussCenter = numpy.empty(3) |
|
|||
| 1068 | # FrecRange, VelRange = [[],[],[]],[[],[],[]] |
|
|||
| 1069 | # FrecRange01, FrecRange02, FrecRange12 = numpy.empty(3), numpy.empty(3), numpy.empty(3) |
|
|||
| 1070 | # VelRange01, VelRange02, VelRange12 = numpy.empty(3), numpy.empty(3), numpy.empty(3) |
|
|||
| 1071 | # |
|
|||
| 1072 | # GauWidth = numpy.empty(3) |
|
|||
| 1073 | # ClosRangeMin, ClosRangeMax = numpy.empty(3), numpy.empty(3) |
|
|||
| 1074 | # PointRangeMin, PointRangeMax = numpy.empty(3), numpy.empty(3) |
|
|||
| 1075 | # '''****** Taking frequency ranges from CSPCs ******''' |
|
|||
| 1076 | # for i in range(spc.shape[0]): |
|
|||
| 1077 | # |
|
|||
| 1078 | # GaussCenter[i] = CSPCopt[i][1] #Primer momento 01 |
|
|||
| 1079 | # GauWidth[i] = CSPCopt[i][2]*2/2 #Ancho de banda de Gau01 |
|
|||
| 1080 | # |
|
|||
| 1081 | # Range[i][0] = GaussCenter[i] - GauWidth[i] |
|
|||
| 1082 | # Range[i][1] = GaussCenter[i] + GauWidth[i] |
|
|||
| 1083 | # #Punto en Eje X de la Gaussiana donde se encuentra ancho de banda (min:max) |
|
|||
| 1084 | # ClosRangeMin[i] = xSamples[numpy.abs(xSamples-Range[i][0]).argmin()] |
|
|||
| 1085 | # ClosRangeMax[i] = xSamples[numpy.abs(xSamples-Range[i][1]).argmin()] |
|
|||
| 1086 | # |
|
|||
| 1087 | # PointRangeMin[i] = numpy.where(xSamples==ClosRangeMin[i])[0][0] |
|
|||
| 1088 | # PointRangeMax[i] = numpy.where(xSamples==ClosRangeMax[i])[0][0] |
|
|||
| 1089 | # |
|
|||
| 1090 | # Range[i]=numpy.array([ PointRangeMin[i], PointRangeMax[i] ]) |
|
|||
| 1091 | # |
|
|||
| 1092 | # FrecRange[i] = xFrec[ Range[i][0] : Range[i][1] ] |
|
|||
| 1093 | # VelRange[i] = xVel[ Range[i][0] : Range[i][1] ] |
|
|||
| 1094 |
|
||||
| 1095 |
|
||||
| 1096 |
|
1214 | |||
|
|
1215 | ||||
| 1097 | '''****** Taking frequency ranges from SPCs ******''' |
|
1216 | '''****** Taking frequency ranges from SPCs ******''' | |
| 1098 |
|
1217 | |||
| 1099 |
|
1218 | |||
| 1100 | #GaussCenter = popt[1] #Primer momento 01 |
|
1219 | #GaussCenter = popt[1] #Primer momento 01 | |
| 1101 | GauWidth = popt[2] *3/2 #Ancho de banda de Gau01 |
|
1220 | GauWidth = popt[2] *3/2 #Ancho de banda de Gau01 | |
| 1102 | Range = numpy.empty(2) |
|
1221 | Range = numpy.empty(2) | |
| 1103 | Range[0] = GaussCenter - GauWidth |
|
1222 | Range[0] = GaussCenter - GauWidth | |
| 1104 | Range[1] = GaussCenter + GauWidth |
|
1223 | Range[1] = GaussCenter + GauWidth | |
| 1105 | #Punto en Eje X de la Gaussiana donde se encuentra ancho de banda (min:max) |
|
1224 | #Punto en Eje X de la Gaussiana donde se encuentra ancho de banda (min:max) | |
| 1106 | ClosRangeMin = xSamples[numpy.abs(xSamples-Range[0]).argmin()] |
|
1225 | ClosRangeMin = xSamples[numpy.abs(xSamples-Range[0]).argmin()] | |
| 1107 | ClosRangeMax = xSamples[numpy.abs(xSamples-Range[1]).argmin()] |
|
1226 | ClosRangeMax = xSamples[numpy.abs(xSamples-Range[1]).argmin()] | |
| 1108 |
|
1227 | |||
| 1109 | PointRangeMin = numpy.where(xSamples==ClosRangeMin)[0][0] |
|
1228 | PointRangeMin = numpy.where(xSamples==ClosRangeMin)[0][0] | |
| 1110 | PointRangeMax = numpy.where(xSamples==ClosRangeMax)[0][0] |
|
1229 | PointRangeMax = numpy.where(xSamples==ClosRangeMax)[0][0] | |
| 1111 |
|
1230 | |||
| 1112 | Range=numpy.array([ PointRangeMin, PointRangeMax ]) |
|
1231 | Range=numpy.array([ PointRangeMin, PointRangeMax ]) | |
| 1113 |
|
1232 | |||
| 1114 | FrecRange = xFrec[ Range[0] : Range[1] ] |
|
1233 | FrecRange = xFrec[ Range[0] : Range[1] ] | |
| 1115 | VelRange = xVel[ Range[0] : Range[1] ] |
|
1234 | VelRange = xVel[ Range[0] : Range[1] ] | |
| 1116 |
|
1235 | |||
| 1117 |
|
1236 | |||
| 1118 | #print 'RANGE: ', Range |
|
1237 | #print 'RANGE: ', Range | |
| 1119 | #print 'FrecRange', numpy.shape(FrecRange)#,FrecRange |
|
1238 | #print 'FrecRange', numpy.shape(FrecRange)#,FrecRange | |
| 1120 | #print 'len: ', len(FrecRange) |
|
1239 | #print 'len: ', len(FrecRange) | |
| 1121 |
|
1240 | |||
| 1122 | '''****** Getting SCPC Slope ******''' |
|
1241 | '''****** Getting SCPC Slope ******''' | |
| 1123 |
|
1242 | |||
| 1124 | for i in range(spc.shape[0]): |
|
1243 | for i in range(spc.shape[0]): | |
| 1125 |
|
1244 | |||
| 1126 | if len(FrecRange)>5 and len(FrecRange)<spc.shape[1]*0.6: |
|
1245 | if len(FrecRange)>5 and len(FrecRange)<spc.shape[1]*0.6: | |
| 1127 | PhaseRange=self.moving_average(phase[i,Range[0]:Range[1]],N=3) |
|
1246 | PhaseRange=self.moving_average(phase[i,Range[0]:Range[1]],N=3) | |
| 1128 |
|
1247 | |||
| 1129 | #print 'Ancho espectral Frecuencias', FrecRange[-1]-FrecRange[0], 'Hz' |
|
1248 | #print 'Ancho espectral Frecuencias', FrecRange[-1]-FrecRange[0], 'Hz' | |
| 1130 | #print 'Ancho espectral Velocidades', VelRange[-1]-VelRange[0], 'm/s' |
|
1249 | #print 'Ancho espectral Velocidades', VelRange[-1]-VelRange[0], 'm/s' | |
| 1131 | #print 'FrecRange', len(FrecRange) , FrecRange |
|
1250 | #print 'FrecRange', len(FrecRange) , FrecRange | |
| 1132 | #print 'VelRange', len(VelRange) , VelRange |
|
1251 | #print 'VelRange', len(VelRange) , VelRange | |
| 1133 | #print 'PhaseRange', numpy.shape(PhaseRange), PhaseRange |
|
1252 | #print 'PhaseRange', numpy.shape(PhaseRange), PhaseRange | |
| 1134 | #print ' ' |
|
1253 | #print ' ' | |
| 1135 |
|
1254 | |||
| 1136 | '''***********************VelRange******************''' |
|
1255 | '''***********************VelRange******************''' | |
| 1137 |
|
1256 | |||
| 1138 | mask = ~numpy.isnan(FrecRange) & ~numpy.isnan(PhaseRange) |
|
1257 | mask = ~numpy.isnan(FrecRange) & ~numpy.isnan(PhaseRange) | |
| 1139 |
|
1258 | |||
| 1140 | if len(FrecRange) == len(PhaseRange): |
|
1259 | if len(FrecRange) == len(PhaseRange): | |
| 1141 | try: |
|
1260 | try: | |
| 1142 | slope, intercept, r_value, p_value, std_err = stats.linregress(FrecRange[mask], PhaseRange[mask]) |
|
1261 | slope, intercept, r_value, p_value, std_err = stats.linregress(FrecRange[mask], PhaseRange[mask]) | |
| 1143 | PhaseSlope[i]=slope |
|
1262 | PhaseSlope[i]=slope | |
| 1144 | PhaseInter[i]=intercept |
|
1263 | PhaseInter[i]=intercept | |
| 1145 | except: |
|
1264 | except: | |
| 1146 | PhaseSlope[i]=0 |
|
1265 | PhaseSlope[i]=0 | |
| 1147 | PhaseInter[i]=0 |
|
1266 | PhaseInter[i]=0 | |
| 1148 | else: |
|
1267 | else: | |
| 1149 | PhaseSlope[i]=0 |
|
1268 | PhaseSlope[i]=0 | |
| 1150 | PhaseInter[i]=0 |
|
1269 | PhaseInter[i]=0 | |
| 1151 | else: |
|
1270 | else: | |
| 1152 | PhaseSlope[i]=0 |
|
1271 | PhaseSlope[i]=0 | |
| 1153 | PhaseInter[i]=0 |
|
1272 | PhaseInter[i]=0 | |
| 1154 |
|
1273 | |||
| 1155 |
|
1274 | |||
| 1156 | '''Getting constant C''' |
|
1275 | '''Getting constant C''' | |
| 1157 | cC=(Fij*numpy.pi)**2 |
|
1276 | cC=(Fij*numpy.pi)**2 | |
| 1158 |
|
1277 | |||
| 1159 | '''****** Getting constants F and G ******''' |
|
1278 | '''****** Getting constants F and G ******''' | |
| 1160 | MijEijNij=numpy.array([[E02,N02], [E12,N12]]) |
|
1279 | MijEijNij=numpy.array([[E02,N02], [E12,N12]]) | |
| 1161 | MijResult0=(-PhaseSlope[1]*cC) / (2*numpy.pi) |
|
1280 | MijResult0=(-PhaseSlope[1]*cC) / (2*numpy.pi) | |
| 1162 | MijResult1=(-PhaseSlope[2]*cC) / (2*numpy.pi) |
|
1281 | MijResult1=(-PhaseSlope[2]*cC) / (2*numpy.pi) | |
| 1163 | MijResults=numpy.array([MijResult0,MijResult1]) |
|
1282 | MijResults=numpy.array([MijResult0,MijResult1]) | |
| 1164 | (cF,cG) = numpy.linalg.solve(MijEijNij, MijResults) |
|
1283 | (cF,cG) = numpy.linalg.solve(MijEijNij, MijResults) | |
| 1165 |
|
1284 | |||
| 1166 | '''****** Getting constants A, B and H ******''' |
|
1285 | '''****** Getting constants A, B and H ******''' | |
| 1167 | W01=numpy.nanmax( FitGauss01 ) #numpy.abs(CSPCSamples[0])) |
|
1286 | W01=numpy.nanmax( FitGauss01 ) #numpy.abs(CSPCSamples[0])) | |
| 1168 | W02=numpy.nanmax( FitGauss02 ) #numpy.abs(CSPCSamples[1])) |
|
1287 | W02=numpy.nanmax( FitGauss02 ) #numpy.abs(CSPCSamples[1])) | |
| 1169 | W12=numpy.nanmax( FitGauss12 ) #numpy.abs(CSPCSamples[2])) |
|
1288 | W12=numpy.nanmax( FitGauss12 ) #numpy.abs(CSPCSamples[2])) | |
| 1170 |
|
1289 | |||
| 1171 | WijResult0=((cF*E01+cG*N01)**2)/cC - numpy.log(W01 / numpy.sqrt(numpy.pi/cC)) |
|
1290 | WijResult0=((cF*E01+cG*N01)**2)/cC - numpy.log(W01 / numpy.sqrt(numpy.pi/cC)) | |
| 1172 | WijResult1=((cF*E02+cG*N02)**2)/cC - numpy.log(W02 / numpy.sqrt(numpy.pi/cC)) |
|
1291 | WijResult1=((cF*E02+cG*N02)**2)/cC - numpy.log(W02 / numpy.sqrt(numpy.pi/cC)) | |
| 1173 | WijResult2=((cF*E12+cG*N12)**2)/cC - numpy.log(W12 / numpy.sqrt(numpy.pi/cC)) |
|
1292 | WijResult2=((cF*E12+cG*N12)**2)/cC - numpy.log(W12 / numpy.sqrt(numpy.pi/cC)) | |
| 1174 |
|
1293 | |||
| 1175 | WijResults=numpy.array([WijResult0, WijResult1, WijResult2]) |
|
1294 | WijResults=numpy.array([WijResult0, WijResult1, WijResult2]) | |
| 1176 |
|
1295 | |||
| 1177 | WijEijNij=numpy.array([ [E01**2, N01**2, 2*E01*N01] , [E02**2, N02**2, 2*E02*N02] , [E12**2, N12**2, 2*E12*N12] ]) |
|
1296 | WijEijNij=numpy.array([ [E01**2, N01**2, 2*E01*N01] , [E02**2, N02**2, 2*E02*N02] , [E12**2, N12**2, 2*E12*N12] ]) | |
| 1178 | (cA,cB,cH) = numpy.linalg.solve(WijEijNij, WijResults) |
|
1297 | (cA,cB,cH) = numpy.linalg.solve(WijEijNij, WijResults) | |
| 1179 |
|
1298 | |||
| 1180 | VxVy=numpy.array([[cA,cH],[cH,cB]]) |
|
1299 | VxVy=numpy.array([[cA,cH],[cH,cB]]) | |
| 1181 |
|
||||
| 1182 | VxVyResults=numpy.array([-cF,-cG]) |
|
1300 | VxVyResults=numpy.array([-cF,-cG]) | |
| 1183 | (Vx,Vy) = numpy.linalg.solve(VxVy, VxVyResults) |
|
1301 | (Vx,Vy) = numpy.linalg.solve(VxVy, VxVyResults) | |
|
|
1302 | ||||
| 1184 | #print 'MijResults, cC, PhaseSlope', MijResults, cC, PhaseSlope |
|
1303 | #print 'MijResults, cC, PhaseSlope', MijResults, cC, PhaseSlope | |
| 1185 | #print 'W01,02,12', W01, W02, W12 |
|
1304 | #print 'W01,02,12', W01, W02, W12 | |
| 1186 | #print 'WijResult0,1,2',WijResult0, WijResult1, WijResult2, 'Results', WijResults |
|
1305 | #print 'WijResult0,1,2',WijResult0, WijResult1, WijResult2, 'Results', WijResults | |
| 1187 | #print 'cA,cB,cH, cF, cG', cA, cB, cH, cF, cG |
|
1306 | #print 'cA,cB,cH, cF, cG', cA, cB, cH, cF, cG | |
| 1188 | #print 'VxVy', VxVyResults |
|
1307 | #print 'VxVy', VxVyResults | |
| 1189 | #print '###########################****************************************' |
|
1308 | #print '###########################****************************************' | |
| 1190 | Vzon = Vy |
|
1309 | Vzon = Vy | |
| 1191 | Vmer = Vx |
|
1310 | Vmer = Vx | |
| 1192 | Vmag=numpy.sqrt(Vzon**2+Vmer**2) |
|
1311 | Vmag=numpy.sqrt(Vzon**2+Vmer**2) | |
| 1193 | Vang=numpy.arctan2(Vmer,Vzon) |
|
1312 | Vang=numpy.arctan2(Vmer,Vzon) | |
| 1194 | Vver=SPCmoments[1] |
|
1313 | Vver=SPCmoments[1] | |
| 1195 | FitGaussCSPC = numpy.array([FitGauss01,FitGauss02,FitGauss12]) |
|
1314 | FitGaussCSPC = numpy.array([FitGauss01,FitGauss02,FitGauss12]) | |
| 1196 |
|
1315 | |||
| 1197 |
|
1316 | |||
| 1198 | # ''' Ploteo por altura ''' |
|
1317 | # ''' Ploteo por altura ''' | |
| 1199 | # if Height == 28: |
|
1318 | # if Height == 28: | |
| 1200 | # for i in range(3): |
|
1319 | # for i in range(3): | |
| 1201 | # #print 'FASE', numpy.shape(phase), y[25] |
|
1320 | # #print 'FASE', numpy.shape(phase), y[25] | |
| 1202 | # #print numpy.shape(coherence) |
|
1321 | # #print numpy.shape(coherence) | |
| 1203 | # fig = plt.figure(10+self.indice) |
|
1322 | # fig = plt.figure(10+self.indice) | |
| 1204 | # #plt.plot( x[0:256],coherence[:,25] ) |
|
1323 | # #plt.plot( x[0:256],coherence[:,25] ) | |
| 1205 | # #cohAv = numpy.average(coherence[i],1) |
|
1324 | # #cohAv = numpy.average(coherence[i],1) | |
| 1206 | # Pendiente = FrecRange * PhaseSlope[i] |
|
1325 | # Pendiente = FrecRange * PhaseSlope[i] | |
| 1207 | # plt.plot( FrecRange, Pendiente) |
|
1326 | # plt.plot( FrecRange, Pendiente) | |
| 1208 | # plt.plot( xFrec,phase[i]) |
|
1327 | # plt.plot( xFrec,phase[i]) | |
| 1209 | # |
|
1328 | # | |
| 1210 | # CSPCmean = numpy.mean(numpy.abs(CSPCSamples),0) |
|
1329 | # CSPCmean = numpy.mean(numpy.abs(CSPCSamples),0) | |
| 1211 | # #plt.plot(xFrec, FitGauss01) |
|
1330 | # #plt.plot(xFrec, FitGauss01) | |
| 1212 | # #plt.plot(xFrec, CSPCmean) |
|
1331 | # #plt.plot(xFrec, CSPCmean) | |
| 1213 | # #plt.plot(xFrec, numpy.abs(CSPCSamples[0])) |
|
1332 | # #plt.plot(xFrec, numpy.abs(CSPCSamples[0])) | |
| 1214 | # #plt.plot(xFrec, FitGauss) |
|
1333 | # #plt.plot(xFrec, FitGauss) | |
| 1215 | # #plt.plot(xFrec, yMean) |
|
1334 | # #plt.plot(xFrec, yMean) | |
| 1216 | # #plt.plot(xFrec, numpy.abs(coherence[0])) |
|
1335 | # #plt.plot(xFrec, numpy.abs(coherence[0])) | |
| 1217 | # |
|
1336 | # | |
| 1218 | # #plt.axis([-12, 12, 15, 50]) |
|
1337 | # #plt.axis([-12, 12, 15, 50]) | |
| 1219 | # #plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) |
|
1338 | # #plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) | |
| 1220 | # plt.ylabel('Desfase [rad]') |
|
1339 | # plt.ylabel('Desfase [rad]') | |
| 1221 | # #plt.ylabel('CSPC normalizado') |
|
1340 | # #plt.ylabel('CSPC normalizado') | |
| 1222 | # plt.xlabel('Frec range [Hz]') |
|
1341 | # plt.xlabel('Frec range [Hz]') | |
| 1223 |
|
1342 | |||
| 1224 | #fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) |
|
1343 | #fig.savefig('/home/erick/Documents/Pics/to{}.png'.format(self.indice)) | |
| 1225 |
|
1344 | |||
| 1226 | # plt.show() |
|
1345 | # plt.show() | |
| 1227 | # self.indice=self.indice+1 |
|
1346 | # self.indice=self.indice+1 | |
| 1228 |
|
1347 | |||
| 1229 |
|
1348 | |||
| 1230 |
|
1349 | |||
| 1231 |
|
1350 | |||
| 1232 |
|
1351 | |||
| 1233 | print 'vzon y vmer', Vzon, Vmer |
|
1352 | # print 'vzon y vmer', Vzon, Vmer | |
| 1234 | return Vzon, Vmer, Vver, GaussCenter, PhaseSlope, FitGaussCSPC |
|
1353 | return Vzon, Vmer, Vver, GaussCenter, PhaseSlope, FitGaussCSPC | |
| 1235 |
|
1354 | |||
| 1236 | class SpectralMoments(Operation): |
|
1355 | class SpectralMoments(Operation): | |
| 1237 |
|
1356 | |||
| 1238 | ''' |
|
1357 | ''' | |
| 1239 | Function SpectralMoments() |
|
1358 | Function SpectralMoments() | |
| 1240 |
|
1359 | |||
| 1241 | Calculates moments (power, mean, standard deviation) and SNR of the signal |
|
1360 | Calculates moments (power, mean, standard deviation) and SNR of the signal | |
| 1242 |
|
1361 | |||
| 1243 | Type of dataIn: Spectra |
|
1362 | Type of dataIn: Spectra | |
| 1244 |
|
1363 | |||
| 1245 | Configuration Parameters: |
|
1364 | Configuration Parameters: | |
| 1246 |
|
1365 | |||
| 1247 | dirCosx : Cosine director in X axis |
|
1366 | dirCosx : Cosine director in X axis | |
| 1248 | dirCosy : Cosine director in Y axis |
|
1367 | dirCosy : Cosine director in Y axis | |
| 1249 |
|
1368 | |||
| 1250 | elevation : |
|
1369 | elevation : | |
| 1251 | azimuth : |
|
1370 | azimuth : | |
| 1252 |
|
1371 | |||
| 1253 | Input: |
|
1372 | Input: | |
| 1254 | channelList : simple channel list to select e.g. [2,3,7] |
|
1373 | channelList : simple channel list to select e.g. [2,3,7] | |
| 1255 | self.dataOut.data_pre : Spectral data |
|
1374 | self.dataOut.data_pre : Spectral data | |
| 1256 | self.dataOut.abscissaList : List of frequencies |
|
1375 | self.dataOut.abscissaList : List of frequencies | |
| 1257 | self.dataOut.noise : Noise level per channel |
|
1376 | self.dataOut.noise : Noise level per channel | |
| 1258 |
|
1377 | |||
| 1259 | Affected: |
|
1378 | Affected: | |
| 1260 |
self.dataOut. |
|
1379 | self.dataOut.moments : Parameters per channel | |
| 1261 | self.dataOut.data_SNR : SNR per channel |
|
1380 | self.dataOut.data_SNR : SNR per channel | |
| 1262 |
|
1381 | |||
| 1263 | ''' |
|
1382 | ''' | |
| 1264 |
|
1383 | |||
| 1265 | def run(self, dataOut): |
|
1384 | def run(self, dataOut): | |
| 1266 |
|
1385 | |||
| 1267 | #dataOut.data_pre = dataOut.data_pre[0] |
|
1386 | #dataOut.data_pre = dataOut.data_pre[0] | |
| 1268 | data = dataOut.data_pre[0] |
|
1387 | data = dataOut.data_pre[0] | |
| 1269 | absc = dataOut.abscissaList[:-1] |
|
1388 | absc = dataOut.abscissaList[:-1] | |
| 1270 | noise = dataOut.noise |
|
1389 | noise = dataOut.noise | |
| 1271 | nChannel = data.shape[0] |
|
1390 | nChannel = data.shape[0] | |
| 1272 | data_param = numpy.zeros((nChannel, 4, data.shape[2])) |
|
1391 | data_param = numpy.zeros((nChannel, 4, data.shape[2])) | |
| 1273 |
|
1392 | |||
| 1274 | for ind in range(nChannel): |
|
1393 | for ind in range(nChannel): | |
| 1275 | data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind] ) |
|
1394 | data_param[ind,:,:] = self.__calculateMoments( data[ind,:,:] , absc , noise[ind] ) | |
| 1276 |
|
1395 | |||
| 1277 |
dataOut. |
|
1396 | dataOut.moments = data_param[:,1:,:] | |
| 1278 | dataOut.data_SNR = data_param[:,0] |
|
1397 | dataOut.data_SNR = data_param[:,0] | |
| 1279 | return |
|
1398 | return | |
| 1280 |
|
1399 | |||
| 1281 | def __calculateMoments(self, oldspec, oldfreq, n0, |
|
1400 | def __calculateMoments(self, oldspec, oldfreq, n0, | |
| 1282 | nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None): |
|
1401 | nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None): | |
| 1283 |
|
1402 | |||
| 1284 | if (nicoh == None): nicoh = 1 |
|
1403 | if (nicoh == None): nicoh = 1 | |
| 1285 | if (graph == None): graph = 0 |
|
1404 | if (graph == None): graph = 0 | |
| 1286 | if (smooth == None): smooth = 0 |
|
1405 | if (smooth == None): smooth = 0 | |
| 1287 | elif (self.smooth < 3): smooth = 0 |
|
1406 | elif (self.smooth < 3): smooth = 0 | |
| 1288 |
|
1407 | |||
| 1289 | if (type1 == None): type1 = 0 |
|
1408 | if (type1 == None): type1 = 0 | |
| 1290 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 |
|
1409 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 | |
| 1291 | if (snrth == None): snrth = -3 |
|
1410 | if (snrth == None): snrth = -3 | |
| 1292 | if (dc == None): dc = 0 |
|
1411 | if (dc == None): dc = 0 | |
| 1293 | if (aliasing == None): aliasing = 0 |
|
1412 | if (aliasing == None): aliasing = 0 | |
| 1294 | if (oldfd == None): oldfd = 0 |
|
1413 | if (oldfd == None): oldfd = 0 | |
| 1295 | if (wwauto == None): wwauto = 0 |
|
1414 | if (wwauto == None): wwauto = 0 | |
| 1296 |
|
1415 | |||
| 1297 | if (n0 < 1.e-20): n0 = 1.e-20 |
|
1416 | if (n0 < 1.e-20): n0 = 1.e-20 | |
| 1298 |
|
1417 | |||
| 1299 | freq = oldfreq |
|
1418 | freq = oldfreq | |
| 1300 | vec_power = numpy.zeros(oldspec.shape[1]) |
|
1419 | vec_power = numpy.zeros(oldspec.shape[1]) | |
| 1301 | vec_fd = numpy.zeros(oldspec.shape[1]) |
|
1420 | vec_fd = numpy.zeros(oldspec.shape[1]) | |
| 1302 | vec_w = numpy.zeros(oldspec.shape[1]) |
|
1421 | vec_w = numpy.zeros(oldspec.shape[1]) | |
| 1303 | vec_snr = numpy.zeros(oldspec.shape[1]) |
|
1422 | vec_snr = numpy.zeros(oldspec.shape[1]) | |
| 1304 |
|
1423 | |||
| 1305 | oldspec = numpy.ma.masked_invalid(oldspec) |
|
1424 | oldspec = numpy.ma.masked_invalid(oldspec) | |
| 1306 |
|
1425 | |||
| 1307 | for ind in range(oldspec.shape[1]): |
|
1426 | for ind in range(oldspec.shape[1]): | |
| 1308 |
|
1427 | |||
| 1309 | spec = oldspec[:,ind] |
|
1428 | spec = oldspec[:,ind] | |
| 1310 | aux = spec*fwindow |
|
1429 | aux = spec*fwindow | |
| 1311 | max_spec = aux.max() |
|
1430 | max_spec = aux.max() | |
| 1312 | m = list(aux).index(max_spec) |
|
1431 | m = list(aux).index(max_spec) | |
| 1313 |
|
1432 | |||
| 1314 | #Smooth |
|
1433 | #Smooth | |
| 1315 | if (smooth == 0): spec2 = spec |
|
1434 | if (smooth == 0): spec2 = spec | |
| 1316 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) |
|
1435 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) | |
| 1317 |
|
1436 | |||
| 1318 | # Calculo de Momentos |
|
1437 | # Calculo de Momentos | |
| 1319 | bb = spec2[range(m,spec2.size)] |
|
1438 | bb = spec2[range(m,spec2.size)] | |
| 1320 | bb = (bb<n0).nonzero() |
|
1439 | bb = (bb<n0).nonzero() | |
| 1321 | bb = bb[0] |
|
1440 | bb = bb[0] | |
| 1322 |
|
1441 | |||
| 1323 | ss = spec2[range(0,m + 1)] |
|
1442 | ss = spec2[range(0,m + 1)] | |
| 1324 | ss = (ss<n0).nonzero() |
|
1443 | ss = (ss<n0).nonzero() | |
| 1325 | ss = ss[0] |
|
1444 | ss = ss[0] | |
| 1326 |
|
1445 | |||
| 1327 | if (bb.size == 0): |
|
1446 | if (bb.size == 0): | |
| 1328 | bb0 = spec.size - 1 - m |
|
1447 | bb0 = spec.size - 1 - m | |
| 1329 | else: |
|
1448 | else: | |
| 1330 | bb0 = bb[0] - 1 |
|
1449 | bb0 = bb[0] - 1 | |
| 1331 | if (bb0 < 0): |
|
1450 | if (bb0 < 0): | |
| 1332 | bb0 = 0 |
|
1451 | bb0 = 0 | |
| 1333 |
|
1452 | |||
| 1334 | if (ss.size == 0): ss1 = 1 |
|
1453 | if (ss.size == 0): ss1 = 1 | |
| 1335 | else: ss1 = max(ss) + 1 |
|
1454 | else: ss1 = max(ss) + 1 | |
| 1336 |
|
1455 | |||
| 1337 | if (ss1 > m): ss1 = m |
|
1456 | if (ss1 > m): ss1 = m | |
| 1338 |
|
1457 | |||
| 1339 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 |
|
1458 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 | |
| 1340 | power = ( (spec2[valid] - n0) * fwindow[valid] ).sum() |
|
1459 | power = ( (spec2[valid] - n0) * fwindow[valid] ).sum() | |
| 1341 | fd = ( (spec2[valid]- n0) * freq[valid] * fwindow[valid] ).sum() / power |
|
1460 | fd = ( (spec2[valid]- n0) * freq[valid] * fwindow[valid] ).sum() / power | |
| 1342 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) |
|
1461 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) | |
| 1343 | snr = (spec2.mean()-n0)/n0 |
|
1462 | snr = (spec2.mean()-n0)/n0 | |
| 1344 |
|
1463 | |||
| 1345 | if (snr < 1.e-20) : |
|
1464 | if (snr < 1.e-20) : | |
| 1346 | snr = 1.e-20 |
|
1465 | snr = 1.e-20 | |
| 1347 |
|
1466 | |||
| 1348 | vec_power[ind] = power |
|
1467 | vec_power[ind] = power | |
| 1349 | vec_fd[ind] = fd |
|
1468 | vec_fd[ind] = fd | |
| 1350 | vec_w[ind] = w |
|
1469 | vec_w[ind] = w | |
| 1351 | vec_snr[ind] = snr |
|
1470 | vec_snr[ind] = snr | |
| 1352 |
|
1471 | |||
| 1353 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) |
|
1472 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) | |
| 1354 | return moments |
|
1473 | return moments | |
| 1355 |
|
1474 | |||
| 1356 | #------------------ Get SA Parameters -------------------------- |
|
1475 | #------------------ Get SA Parameters -------------------------- | |
| 1357 |
|
1476 | |||
| 1358 | def GetSAParameters(self): |
|
1477 | def GetSAParameters(self): | |
| 1359 | #SA en frecuencia |
|
1478 | #SA en frecuencia | |
| 1360 | pairslist = self.dataOut.groupList |
|
1479 | pairslist = self.dataOut.groupList | |
| 1361 | num_pairs = len(pairslist) |
|
1480 | num_pairs = len(pairslist) | |
| 1362 |
|
1481 | |||
| 1363 | vel = self.dataOut.abscissaList |
|
1482 | vel = self.dataOut.abscissaList | |
| 1364 | spectra = self.dataOut.data_pre |
|
1483 | spectra = self.dataOut.data_pre | |
| 1365 | cspectra = self.dataIn.data_cspc |
|
1484 | cspectra = self.dataIn.data_cspc | |
| 1366 | delta_v = vel[1] - vel[0] |
|
1485 | delta_v = vel[1] - vel[0] | |
| 1367 |
|
1486 | |||
| 1368 | #Calculating the power spectrum |
|
1487 | #Calculating the power spectrum | |
| 1369 | spc_pow = numpy.sum(spectra, 3)*delta_v |
|
1488 | spc_pow = numpy.sum(spectra, 3)*delta_v | |
| 1370 | #Normalizing Spectra |
|
1489 | #Normalizing Spectra | |
| 1371 | norm_spectra = spectra/spc_pow |
|
1490 | norm_spectra = spectra/spc_pow | |
| 1372 | #Calculating the norm_spectra at peak |
|
1491 | #Calculating the norm_spectra at peak | |
| 1373 | max_spectra = numpy.max(norm_spectra, 3) |
|
1492 | max_spectra = numpy.max(norm_spectra, 3) | |
| 1374 |
|
1493 | |||
| 1375 | #Normalizing Cross Spectra |
|
1494 | #Normalizing Cross Spectra | |
| 1376 | norm_cspectra = numpy.zeros(cspectra.shape) |
|
1495 | norm_cspectra = numpy.zeros(cspectra.shape) | |
| 1377 |
|
1496 | |||
| 1378 | for i in range(num_chan): |
|
1497 | for i in range(num_chan): | |
| 1379 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) |
|
1498 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) | |
| 1380 |
|
1499 | |||
| 1381 | max_cspectra = numpy.max(norm_cspectra,2) |
|
1500 | max_cspectra = numpy.max(norm_cspectra,2) | |
| 1382 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) |
|
1501 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) | |
| 1383 |
|
1502 | |||
| 1384 | for i in range(num_pairs): |
|
1503 | for i in range(num_pairs): | |
| 1385 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) |
|
1504 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) | |
| 1386 | #------------------- Get Lags ---------------------------------- |
|
1505 | #------------------- Get Lags ---------------------------------- | |
| 1387 |
|
1506 | |||
| 1388 | class SALags(Operation): |
|
1507 | class SALags(Operation): | |
| 1389 | ''' |
|
1508 | ''' | |
| 1390 | Function GetMoments() |
|
1509 | Function GetMoments() | |
| 1391 |
|
1510 | |||
| 1392 | Input: |
|
1511 | Input: | |
| 1393 | self.dataOut.data_pre |
|
1512 | self.dataOut.data_pre | |
| 1394 | self.dataOut.abscissaList |
|
1513 | self.dataOut.abscissaList | |
| 1395 | self.dataOut.noise |
|
1514 | self.dataOut.noise | |
| 1396 | self.dataOut.normFactor |
|
1515 | self.dataOut.normFactor | |
| 1397 | self.dataOut.data_SNR |
|
1516 | self.dataOut.data_SNR | |
| 1398 | self.dataOut.groupList |
|
1517 | self.dataOut.groupList | |
| 1399 | self.dataOut.nChannels |
|
1518 | self.dataOut.nChannels | |
| 1400 |
|
1519 | |||
| 1401 | Affected: |
|
1520 | Affected: | |
| 1402 | self.dataOut.data_param |
|
1521 | self.dataOut.data_param | |
| 1403 |
|
1522 | |||
| 1404 | ''' |
|
1523 | ''' | |
| 1405 | def run(self, dataOut): |
|
1524 | def run(self, dataOut): | |
| 1406 | data_acf = dataOut.data_pre[0] |
|
1525 | data_acf = dataOut.data_pre[0] | |
| 1407 | data_ccf = dataOut.data_pre[1] |
|
1526 | data_ccf = dataOut.data_pre[1] | |
| 1408 | normFactor_acf = dataOut.normFactor[0] |
|
1527 | normFactor_acf = dataOut.normFactor[0] | |
| 1409 | normFactor_ccf = dataOut.normFactor[1] |
|
1528 | normFactor_ccf = dataOut.normFactor[1] | |
| 1410 | pairs_acf = dataOut.groupList[0] |
|
1529 | pairs_acf = dataOut.groupList[0] | |
| 1411 | pairs_ccf = dataOut.groupList[1] |
|
1530 | pairs_ccf = dataOut.groupList[1] | |
| 1412 |
|
1531 | |||
| 1413 | nHeights = dataOut.nHeights |
|
1532 | nHeights = dataOut.nHeights | |
| 1414 | absc = dataOut.abscissaList |
|
1533 | absc = dataOut.abscissaList | |
| 1415 | noise = dataOut.noise |
|
1534 | noise = dataOut.noise | |
| 1416 | SNR = dataOut.data_SNR |
|
1535 | SNR = dataOut.data_SNR | |
| 1417 | nChannels = dataOut.nChannels |
|
1536 | nChannels = dataOut.nChannels | |
| 1418 | # pairsList = dataOut.groupList |
|
1537 | # pairsList = dataOut.groupList | |
| 1419 | # pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) |
|
1538 | # pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) | |
| 1420 |
|
1539 | |||
| 1421 | for l in range(len(pairs_acf)): |
|
1540 | for l in range(len(pairs_acf)): | |
| 1422 | data_acf[l,:,:] = data_acf[l,:,:]/normFactor_acf[l,:] |
|
1541 | data_acf[l,:,:] = data_acf[l,:,:]/normFactor_acf[l,:] | |
| 1423 |
|
1542 | |||
| 1424 | for l in range(len(pairs_ccf)): |
|
1543 | for l in range(len(pairs_ccf)): | |
| 1425 | data_ccf[l,:,:] = data_ccf[l,:,:]/normFactor_ccf[l,:] |
|
1544 | data_ccf[l,:,:] = data_ccf[l,:,:]/normFactor_ccf[l,:] | |
| 1426 |
|
1545 | |||
| 1427 | dataOut.data_param = numpy.zeros((len(pairs_ccf)*2 + 1, nHeights)) |
|
1546 | dataOut.data_param = numpy.zeros((len(pairs_ccf)*2 + 1, nHeights)) | |
| 1428 | dataOut.data_param[:-1,:] = self.__calculateTaus(data_acf, data_ccf, absc) |
|
1547 | dataOut.data_param[:-1,:] = self.__calculateTaus(data_acf, data_ccf, absc) | |
| 1429 | dataOut.data_param[-1,:] = self.__calculateLag1Phase(data_acf, absc) |
|
1548 | dataOut.data_param[-1,:] = self.__calculateLag1Phase(data_acf, absc) | |
| 1430 | return |
|
1549 | return | |
| 1431 |
|
1550 | |||
| 1432 | # def __getPairsAutoCorr(self, pairsList, nChannels): |
|
1551 | # def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 1433 | # |
|
1552 | # | |
| 1434 | # pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
1553 | # pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 1435 | # |
|
1554 | # | |
| 1436 | # for l in range(len(pairsList)): |
|
1555 | # for l in range(len(pairsList)): | |
| 1437 | # firstChannel = pairsList[l][0] |
|
1556 | # firstChannel = pairsList[l][0] | |
| 1438 | # secondChannel = pairsList[l][1] |
|
1557 | # secondChannel = pairsList[l][1] | |
| 1439 | # |
|
1558 | # | |
| 1440 | # #Obteniendo pares de Autocorrelacion |
|
1559 | # #Obteniendo pares de Autocorrelacion | |
| 1441 | # if firstChannel == secondChannel: |
|
1560 | # if firstChannel == secondChannel: | |
| 1442 | # pairsAutoCorr[firstChannel] = int(l) |
|
1561 | # pairsAutoCorr[firstChannel] = int(l) | |
| 1443 | # |
|
1562 | # | |
| 1444 | # pairsAutoCorr = pairsAutoCorr.astype(int) |
|
1563 | # pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 1445 | # |
|
1564 | # | |
| 1446 | # pairsCrossCorr = range(len(pairsList)) |
|
1565 | # pairsCrossCorr = range(len(pairsList)) | |
| 1447 | # pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
1566 | # pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 1448 | # |
|
1567 | # | |
| 1449 | # return pairsAutoCorr, pairsCrossCorr |
|
1568 | # return pairsAutoCorr, pairsCrossCorr | |
| 1450 |
|
1569 | |||
| 1451 | def __calculateTaus(self, data_acf, data_ccf, lagRange): |
|
1570 | def __calculateTaus(self, data_acf, data_ccf, lagRange): | |
| 1452 |
|
1571 | |||
| 1453 | lag0 = data_acf.shape[1]/2 |
|
1572 | lag0 = data_acf.shape[1]/2 | |
| 1454 | #Funcion de Autocorrelacion |
|
1573 | #Funcion de Autocorrelacion | |
| 1455 | mean_acf = stats.nanmean(data_acf, axis = 0) |
|
1574 | mean_acf = stats.nanmean(data_acf, axis = 0) | |
| 1456 |
|
1575 | |||
| 1457 | #Obtencion Indice de TauCross |
|
1576 | #Obtencion Indice de TauCross | |
| 1458 | ind_ccf = data_ccf.argmax(axis = 1) |
|
1577 | ind_ccf = data_ccf.argmax(axis = 1) | |
| 1459 | #Obtencion Indice de TauAuto |
|
1578 | #Obtencion Indice de TauAuto | |
| 1460 | ind_acf = numpy.zeros(ind_ccf.shape,dtype = 'int') |
|
1579 | ind_acf = numpy.zeros(ind_ccf.shape,dtype = 'int') | |
| 1461 | ccf_lag0 = data_ccf[:,lag0,:] |
|
1580 | ccf_lag0 = data_ccf[:,lag0,:] | |
| 1462 |
|
1581 | |||
| 1463 | for i in range(ccf_lag0.shape[0]): |
|
1582 | for i in range(ccf_lag0.shape[0]): | |
| 1464 | ind_acf[i,:] = numpy.abs(mean_acf - ccf_lag0[i,:]).argmin(axis = 0) |
|
1583 | ind_acf[i,:] = numpy.abs(mean_acf - ccf_lag0[i,:]).argmin(axis = 0) | |
| 1465 |
|
1584 | |||
| 1466 | #Obtencion de TauCross y TauAuto |
|
1585 | #Obtencion de TauCross y TauAuto | |
| 1467 | tau_ccf = lagRange[ind_ccf] |
|
1586 | tau_ccf = lagRange[ind_ccf] | |
| 1468 | tau_acf = lagRange[ind_acf] |
|
1587 | tau_acf = lagRange[ind_acf] | |
| 1469 |
|
1588 | |||
| 1470 | Nan1, Nan2 = numpy.where(tau_ccf == lagRange[0]) |
|
1589 | Nan1, Nan2 = numpy.where(tau_ccf == lagRange[0]) | |
| 1471 |
|
1590 | |||
| 1472 | tau_ccf[Nan1,Nan2] = numpy.nan |
|
1591 | tau_ccf[Nan1,Nan2] = numpy.nan | |
| 1473 | tau_acf[Nan1,Nan2] = numpy.nan |
|
1592 | tau_acf[Nan1,Nan2] = numpy.nan | |
| 1474 | tau = numpy.vstack((tau_ccf,tau_acf)) |
|
1593 | tau = numpy.vstack((tau_ccf,tau_acf)) | |
| 1475 |
|
1594 | |||
| 1476 | return tau |
|
1595 | return tau | |
| 1477 |
|
1596 | |||
| 1478 | def __calculateLag1Phase(self, data, lagTRange): |
|
1597 | def __calculateLag1Phase(self, data, lagTRange): | |
| 1479 | data1 = stats.nanmean(data, axis = 0) |
|
1598 | data1 = stats.nanmean(data, axis = 0) | |
| 1480 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 |
|
1599 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 | |
| 1481 |
|
1600 | |||
| 1482 | phase = numpy.angle(data1[lag1,:]) |
|
1601 | phase = numpy.angle(data1[lag1,:]) | |
| 1483 |
|
1602 | |||
| 1484 | return phase |
|
1603 | return phase | |
| 1485 |
|
1604 | |||
| 1486 | class SpectralFitting(Operation): |
|
1605 | class SpectralFitting(Operation): | |
| 1487 | ''' |
|
1606 | ''' | |
| 1488 | Function GetMoments() |
|
1607 | Function GetMoments() | |
| 1489 |
|
1608 | |||
| 1490 | Input: |
|
1609 | Input: | |
| 1491 | Output: |
|
1610 | Output: | |
| 1492 | Variables modified: |
|
1611 | Variables modified: | |
| 1493 | ''' |
|
1612 | ''' | |
| 1494 |
|
1613 | |||
| 1495 | def run(self, dataOut, getSNR = True, path=None, file=None, groupList=None): |
|
1614 | def run(self, dataOut, getSNR = True, path=None, file=None, groupList=None): | |
| 1496 |
|
1615 | |||
| 1497 |
|
1616 | |||
| 1498 | if path != None: |
|
1617 | if path != None: | |
| 1499 | sys.path.append(path) |
|
1618 | sys.path.append(path) | |
| 1500 | self.dataOut.library = importlib.import_module(file) |
|
1619 | self.dataOut.library = importlib.import_module(file) | |
| 1501 |
|
1620 | |||
| 1502 | #To be inserted as a parameter |
|
1621 | #To be inserted as a parameter | |
| 1503 | groupArray = numpy.array(groupList) |
|
1622 | groupArray = numpy.array(groupList) | |
| 1504 | # groupArray = numpy.array([[0,1],[2,3]]) |
|
1623 | # groupArray = numpy.array([[0,1],[2,3]]) | |
| 1505 | self.dataOut.groupList = groupArray |
|
1624 | self.dataOut.groupList = groupArray | |
| 1506 |
|
1625 | |||
| 1507 | nGroups = groupArray.shape[0] |
|
1626 | nGroups = groupArray.shape[0] | |
| 1508 | nChannels = self.dataIn.nChannels |
|
1627 | nChannels = self.dataIn.nChannels | |
| 1509 | nHeights=self.dataIn.heightList.size |
|
1628 | nHeights=self.dataIn.heightList.size | |
| 1510 |
|
1629 | |||
| 1511 | #Parameters Array |
|
1630 | #Parameters Array | |
| 1512 | self.dataOut.data_param = None |
|
1631 | self.dataOut.data_param = None | |
| 1513 |
|
1632 | |||
| 1514 | #Set constants |
|
1633 | #Set constants | |
| 1515 | constants = self.dataOut.library.setConstants(self.dataIn) |
|
1634 | constants = self.dataOut.library.setConstants(self.dataIn) | |
| 1516 | self.dataOut.constants = constants |
|
1635 | self.dataOut.constants = constants | |
| 1517 | M = self.dataIn.normFactor |
|
1636 | M = self.dataIn.normFactor | |
| 1518 | N = self.dataIn.nFFTPoints |
|
1637 | N = self.dataIn.nFFTPoints | |
| 1519 | ippSeconds = self.dataIn.ippSeconds |
|
1638 | ippSeconds = self.dataIn.ippSeconds | |
| 1520 | K = self.dataIn.nIncohInt |
|
1639 | K = self.dataIn.nIncohInt | |
| 1521 | pairsArray = numpy.array(self.dataIn.pairsList) |
|
1640 | pairsArray = numpy.array(self.dataIn.pairsList) | |
| 1522 |
|
1641 | |||
| 1523 | #List of possible combinations |
|
1642 | #List of possible combinations | |
| 1524 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) |
|
1643 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) | |
| 1525 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') |
|
1644 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') | |
| 1526 |
|
1645 | |||
| 1527 | if getSNR: |
|
1646 | if getSNR: | |
| 1528 | listChannels = groupArray.reshape((groupArray.size)) |
|
1647 | listChannels = groupArray.reshape((groupArray.size)) | |
| 1529 | listChannels.sort() |
|
1648 | listChannels.sort() | |
| 1530 | noise = self.dataIn.getNoise() |
|
1649 | noise = self.dataIn.getNoise() | |
| 1531 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) |
|
1650 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) | |
| 1532 |
|
1651 | |||
| 1533 | for i in range(nGroups): |
|
1652 | for i in range(nGroups): | |
| 1534 | coord = groupArray[i,:] |
|
1653 | coord = groupArray[i,:] | |
| 1535 |
|
1654 | |||
| 1536 | #Input data array |
|
1655 | #Input data array | |
| 1537 | data = self.dataIn.data_spc[coord,:,:]/(M*N) |
|
1656 | data = self.dataIn.data_spc[coord,:,:]/(M*N) | |
| 1538 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) |
|
1657 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) | |
| 1539 |
|
1658 | |||
| 1540 | #Cross Spectra data array for Covariance Matrixes |
|
1659 | #Cross Spectra data array for Covariance Matrixes | |
| 1541 | ind = 0 |
|
1660 | ind = 0 | |
| 1542 | for pairs in listComb: |
|
1661 | for pairs in listComb: | |
| 1543 | pairsSel = numpy.array([coord[x],coord[y]]) |
|
1662 | pairsSel = numpy.array([coord[x],coord[y]]) | |
| 1544 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) |
|
1663 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) | |
| 1545 | ind += 1 |
|
1664 | ind += 1 | |
| 1546 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) |
|
1665 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) | |
| 1547 | dataCross = dataCross**2/K |
|
1666 | dataCross = dataCross**2/K | |
| 1548 |
|
1667 | |||
| 1549 | for h in range(nHeights): |
|
1668 | for h in range(nHeights): | |
| 1550 | # print self.dataOut.heightList[h] |
|
1669 | # print self.dataOut.heightList[h] | |
| 1551 |
|
1670 | |||
| 1552 | #Input |
|
1671 | #Input | |
| 1553 | d = data[:,h] |
|
1672 | d = data[:,h] | |
| 1554 |
|
1673 | |||
| 1555 | #Covariance Matrix |
|
1674 | #Covariance Matrix | |
| 1556 | D = numpy.diag(d**2/K) |
|
1675 | D = numpy.diag(d**2/K) | |
| 1557 | ind = 0 |
|
1676 | ind = 0 | |
| 1558 | for pairs in listComb: |
|
1677 | for pairs in listComb: | |
| 1559 | #Coordinates in Covariance Matrix |
|
1678 | #Coordinates in Covariance Matrix | |
| 1560 | x = pairs[0] |
|
1679 | x = pairs[0] | |
| 1561 | y = pairs[1] |
|
1680 | y = pairs[1] | |
| 1562 | #Channel Index |
|
1681 | #Channel Index | |
| 1563 | S12 = dataCross[ind,:,h] |
|
1682 | S12 = dataCross[ind,:,h] | |
| 1564 | D12 = numpy.diag(S12) |
|
1683 | D12 = numpy.diag(S12) | |
| 1565 | #Completing Covariance Matrix with Cross Spectras |
|
1684 | #Completing Covariance Matrix with Cross Spectras | |
| 1566 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 |
|
1685 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 | |
| 1567 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 |
|
1686 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 | |
| 1568 | ind += 1 |
|
1687 | ind += 1 | |
| 1569 | Dinv=numpy.linalg.inv(D) |
|
1688 | Dinv=numpy.linalg.inv(D) | |
| 1570 | L=numpy.linalg.cholesky(Dinv) |
|
1689 | L=numpy.linalg.cholesky(Dinv) | |
| 1571 | LT=L.T |
|
1690 | LT=L.T | |
| 1572 |
|
1691 | |||
| 1573 | dp = numpy.dot(LT,d) |
|
1692 | dp = numpy.dot(LT,d) | |
| 1574 |
|
1693 | |||
| 1575 | #Initial values |
|
1694 | #Initial values | |
| 1576 | data_spc = self.dataIn.data_spc[coord,:,h] |
|
1695 | data_spc = self.dataIn.data_spc[coord,:,h] | |
| 1577 |
|
1696 | |||
| 1578 | if (h>0)and(error1[3]<5): |
|
1697 | if (h>0)and(error1[3]<5): | |
| 1579 | p0 = self.dataOut.data_param[i,:,h-1] |
|
1698 | p0 = self.dataOut.data_param[i,:,h-1] | |
| 1580 | else: |
|
1699 | else: | |
| 1581 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) |
|
1700 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) | |
| 1582 |
|
1701 | |||
| 1583 | try: |
|
1702 | try: | |
| 1584 | #Least Squares |
|
1703 | #Least Squares | |
| 1585 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) |
|
1704 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) | |
| 1586 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) |
|
1705 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) | |
| 1587 | #Chi square error |
|
1706 | #Chi square error | |
| 1588 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) |
|
1707 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) | |
| 1589 | #Error with Jacobian |
|
1708 | #Error with Jacobian | |
| 1590 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) |
|
1709 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) | |
| 1591 | except: |
|
1710 | except: | |
| 1592 | minp = p0*numpy.nan |
|
1711 | minp = p0*numpy.nan | |
| 1593 | error0 = numpy.nan |
|
1712 | error0 = numpy.nan | |
| 1594 | error1 = p0*numpy.nan |
|
1713 | error1 = p0*numpy.nan | |
| 1595 |
|
1714 | |||
| 1596 | #Save |
|
1715 | #Save | |
| 1597 | if self.dataOut.data_param == None: |
|
1716 | if self.dataOut.data_param == None: | |
| 1598 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan |
|
1717 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan | |
| 1599 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan |
|
1718 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan | |
| 1600 |
|
1719 | |||
| 1601 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) |
|
1720 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) | |
| 1602 | self.dataOut.data_param[i,:,h] = minp |
|
1721 | self.dataOut.data_param[i,:,h] = minp | |
| 1603 | return |
|
1722 | return | |
| 1604 |
|
1723 | |||
| 1605 | def __residFunction(self, p, dp, LT, constants): |
|
1724 | def __residFunction(self, p, dp, LT, constants): | |
| 1606 |
|
1725 | |||
| 1607 | fm = self.dataOut.library.modelFunction(p, constants) |
|
1726 | fm = self.dataOut.library.modelFunction(p, constants) | |
| 1608 | fmp=numpy.dot(LT,fm) |
|
1727 | fmp=numpy.dot(LT,fm) | |
| 1609 |
|
1728 | |||
| 1610 | return dp-fmp |
|
1729 | return dp-fmp | |
| 1611 |
|
1730 | |||
| 1612 | def __getSNR(self, z, noise): |
|
1731 | def __getSNR(self, z, noise): | |
| 1613 |
|
1732 | |||
| 1614 | avg = numpy.average(z, axis=1) |
|
1733 | avg = numpy.average(z, axis=1) | |
| 1615 | SNR = (avg.T-noise)/noise |
|
1734 | SNR = (avg.T-noise)/noise | |
| 1616 | SNR = SNR.T |
|
1735 | SNR = SNR.T | |
| 1617 | return SNR |
|
1736 | return SNR | |
| 1618 |
|
1737 | |||
| 1619 | def __chisq(p,chindex,hindex): |
|
1738 | def __chisq(p,chindex,hindex): | |
| 1620 | #similar to Resid but calculates CHI**2 |
|
1739 | #similar to Resid but calculates CHI**2 | |
| 1621 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) |
|
1740 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) | |
| 1622 | dp=numpy.dot(LT,d) |
|
1741 | dp=numpy.dot(LT,d) | |
| 1623 | fmp=numpy.dot(LT,fm) |
|
1742 | fmp=numpy.dot(LT,fm) | |
| 1624 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) |
|
1743 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) | |
| 1625 | return chisq |
|
1744 | return chisq | |
| 1626 |
|
1745 | |||
| 1627 | class WindProfiler(Operation): |
|
1746 | class WindProfiler(Operation): | |
| 1628 |
|
1747 | |||
| 1629 | __isConfig = False |
|
1748 | __isConfig = False | |
| 1630 |
|
1749 | |||
| 1631 | __initime = None |
|
1750 | __initime = None | |
| 1632 | __lastdatatime = None |
|
1751 | __lastdatatime = None | |
| 1633 | __integrationtime = None |
|
1752 | __integrationtime = None | |
| 1634 |
|
1753 | |||
| 1635 | __buffer = None |
|
1754 | __buffer = None | |
| 1636 |
|
1755 | |||
| 1637 | __dataReady = False |
|
1756 | __dataReady = False | |
| 1638 |
|
1757 | |||
| 1639 | __firstdata = None |
|
1758 | __firstdata = None | |
| 1640 |
|
1759 | |||
| 1641 | n = None |
|
1760 | n = None | |
| 1642 |
|
1761 | |||
| 1643 | def __init__(self, **kwargs): |
|
1762 | def __init__(self, **kwargs): | |
| 1644 | Operation.__init__(self, **kwargs) |
|
1763 | Operation.__init__(self, **kwargs) | |
| 1645 |
|
1764 | |||
| 1646 | def __calculateCosDir(self, elev, azim): |
|
1765 | def __calculateCosDir(self, elev, azim): | |
| 1647 | zen = (90 - elev)*numpy.pi/180 |
|
1766 | zen = (90 - elev)*numpy.pi/180 | |
| 1648 | azim = azim*numpy.pi/180 |
|
1767 | azim = azim*numpy.pi/180 | |
| 1649 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) |
|
1768 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) | |
| 1650 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) |
|
1769 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) | |
| 1651 |
|
1770 | |||
| 1652 | signX = numpy.sign(numpy.cos(azim)) |
|
1771 | signX = numpy.sign(numpy.cos(azim)) | |
| 1653 | signY = numpy.sign(numpy.sin(azim)) |
|
1772 | signY = numpy.sign(numpy.sin(azim)) | |
| 1654 |
|
1773 | |||
| 1655 | cosDirX = numpy.copysign(cosDirX, signX) |
|
1774 | cosDirX = numpy.copysign(cosDirX, signX) | |
| 1656 | cosDirY = numpy.copysign(cosDirY, signY) |
|
1775 | cosDirY = numpy.copysign(cosDirY, signY) | |
| 1657 | return cosDirX, cosDirY |
|
1776 | return cosDirX, cosDirY | |
| 1658 |
|
1777 | |||
| 1659 | def __calculateAngles(self, theta_x, theta_y, azimuth): |
|
1778 | def __calculateAngles(self, theta_x, theta_y, azimuth): | |
| 1660 |
|
1779 | |||
| 1661 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) |
|
1780 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) | |
| 1662 | zenith_arr = numpy.arccos(dir_cosw) |
|
1781 | zenith_arr = numpy.arccos(dir_cosw) | |
| 1663 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 |
|
1782 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 | |
| 1664 |
|
1783 | |||
| 1665 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) |
|
1784 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) | |
| 1666 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) |
|
1785 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) | |
| 1667 |
|
1786 | |||
| 1668 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw |
|
1787 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw | |
| 1669 |
|
1788 | |||
| 1670 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): |
|
1789 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): | |
| 1671 |
|
1790 | |||
| 1672 | # |
|
1791 | # | |
| 1673 | if horOnly: |
|
1792 | if horOnly: | |
| 1674 | A = numpy.c_[dir_cosu,dir_cosv] |
|
1793 | A = numpy.c_[dir_cosu,dir_cosv] | |
| 1675 | else: |
|
1794 | else: | |
| 1676 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] |
|
1795 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] | |
| 1677 | A = numpy.asmatrix(A) |
|
1796 | A = numpy.asmatrix(A) | |
| 1678 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() |
|
1797 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() | |
| 1679 |
|
1798 | |||
| 1680 | return A1 |
|
1799 | return A1 | |
| 1681 |
|
1800 | |||
| 1682 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
1801 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
| 1683 | listPhi = phi.tolist() |
|
1802 | listPhi = phi.tolist() | |
| 1684 | maxid = listPhi.index(max(listPhi)) |
|
1803 | maxid = listPhi.index(max(listPhi)) | |
| 1685 | minid = listPhi.index(min(listPhi)) |
|
1804 | minid = listPhi.index(min(listPhi)) | |
| 1686 |
|
1805 | |||
| 1687 | rango = range(len(phi)) |
|
1806 | rango = range(len(phi)) | |
| 1688 | # rango = numpy.delete(rango,maxid) |
|
1807 | # rango = numpy.delete(rango,maxid) | |
| 1689 |
|
1808 | |||
| 1690 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
1809 | heiRang1 = heiRang*math.cos(phi[maxid]) | |
| 1691 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
1810 | heiRangAux = heiRang*math.cos(phi[minid]) | |
| 1692 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
1811 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |
| 1693 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
1812 | heiRang1 = numpy.delete(heiRang1,indOut) | |
| 1694 |
|
1813 | |||
| 1695 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1814 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1696 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1815 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1697 |
|
1816 | |||
| 1698 | for i in rango: |
|
1817 | for i in rango: | |
| 1699 | x = heiRang*math.cos(phi[i]) |
|
1818 | x = heiRang*math.cos(phi[i]) | |
| 1700 | y1 = velRadial[i,:] |
|
1819 | y1 = velRadial[i,:] | |
| 1701 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
1820 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |
| 1702 |
|
1821 | |||
| 1703 | x1 = heiRang1 |
|
1822 | x1 = heiRang1 | |
| 1704 | y11 = f1(x1) |
|
1823 | y11 = f1(x1) | |
| 1705 |
|
1824 | |||
| 1706 | y2 = SNR[i,:] |
|
1825 | y2 = SNR[i,:] | |
| 1707 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
1826 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |
| 1708 | y21 = f2(x1) |
|
1827 | y21 = f2(x1) | |
| 1709 |
|
1828 | |||
| 1710 | velRadial1[i,:] = y11 |
|
1829 | velRadial1[i,:] = y11 | |
| 1711 | SNR1[i,:] = y21 |
|
1830 | SNR1[i,:] = y21 | |
| 1712 |
|
1831 | |||
| 1713 | return heiRang1, velRadial1, SNR1 |
|
1832 | return heiRang1, velRadial1, SNR1 | |
| 1714 |
|
1833 | |||
| 1715 | def __calculateVelUVW(self, A, velRadial): |
|
1834 | def __calculateVelUVW(self, A, velRadial): | |
| 1716 |
|
1835 | |||
| 1717 | #Operacion Matricial |
|
1836 | #Operacion Matricial | |
| 1718 | # velUVW = numpy.zeros((velRadial.shape[1],3)) |
|
1837 | # velUVW = numpy.zeros((velRadial.shape[1],3)) | |
| 1719 | # for ind in range(velRadial.shape[1]): |
|
1838 | # for ind in range(velRadial.shape[1]): | |
| 1720 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) |
|
1839 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) | |
| 1721 | # velUVW = velUVW.transpose() |
|
1840 | # velUVW = velUVW.transpose() | |
| 1722 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) |
|
1841 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) | |
| 1723 | velUVW[:,:] = numpy.dot(A,velRadial) |
|
1842 | velUVW[:,:] = numpy.dot(A,velRadial) | |
| 1724 |
|
1843 | |||
| 1725 |
|
1844 | |||
| 1726 | return velUVW |
|
1845 | return velUVW | |
| 1727 |
|
1846 | |||
| 1728 | # def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): |
|
1847 | # def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): | |
| 1729 |
|
1848 | |||
| 1730 | def techniqueDBS(self, kwargs): |
|
1849 | def techniqueDBS(self, kwargs): | |
| 1731 | """ |
|
1850 | """ | |
| 1732 | Function that implements Doppler Beam Swinging (DBS) technique. |
|
1851 | Function that implements Doppler Beam Swinging (DBS) technique. | |
| 1733 |
|
1852 | |||
| 1734 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1853 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
| 1735 | Direction correction (if necessary), Ranges and SNR |
|
1854 | Direction correction (if necessary), Ranges and SNR | |
| 1736 |
|
1855 | |||
| 1737 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1856 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 1738 |
|
1857 | |||
| 1739 | Parameters affected: Winds, height range, SNR |
|
1858 | Parameters affected: Winds, height range, SNR | |
| 1740 | """ |
|
1859 | """ | |
| 1741 | velRadial0 = kwargs['velRadial'] |
|
1860 | velRadial0 = kwargs['velRadial'] | |
| 1742 | heiRang = kwargs['heightList'] |
|
1861 | heiRang = kwargs['heightList'] | |
| 1743 | SNR0 = kwargs['SNR'] |
|
1862 | SNR0 = kwargs['SNR'] | |
| 1744 |
|
1863 | |||
| 1745 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): |
|
1864 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): | |
| 1746 | theta_x = numpy.array(kwargs['dirCosx']) |
|
1865 | theta_x = numpy.array(kwargs['dirCosx']) | |
| 1747 | theta_y = numpy.array(kwargs['dirCosy']) |
|
1866 | theta_y = numpy.array(kwargs['dirCosy']) | |
| 1748 | else: |
|
1867 | else: | |
| 1749 | elev = numpy.array(kwargs['elevation']) |
|
1868 | elev = numpy.array(kwargs['elevation']) | |
| 1750 | azim = numpy.array(kwargs['azimuth']) |
|
1869 | azim = numpy.array(kwargs['azimuth']) | |
| 1751 | theta_x, theta_y = self.__calculateCosDir(elev, azim) |
|
1870 | theta_x, theta_y = self.__calculateCosDir(elev, azim) | |
| 1752 | azimuth = kwargs['correctAzimuth'] |
|
1871 | azimuth = kwargs['correctAzimuth'] | |
| 1753 | if kwargs.has_key('horizontalOnly'): |
|
1872 | if kwargs.has_key('horizontalOnly'): | |
| 1754 | horizontalOnly = kwargs['horizontalOnly'] |
|
1873 | horizontalOnly = kwargs['horizontalOnly'] | |
| 1755 | else: horizontalOnly = False |
|
1874 | else: horizontalOnly = False | |
| 1756 | if kwargs.has_key('correctFactor'): |
|
1875 | if kwargs.has_key('correctFactor'): | |
| 1757 | correctFactor = kwargs['correctFactor'] |
|
1876 | correctFactor = kwargs['correctFactor'] | |
| 1758 | else: correctFactor = 1 |
|
1877 | else: correctFactor = 1 | |
| 1759 | if kwargs.has_key('channelList'): |
|
1878 | if kwargs.has_key('channelList'): | |
| 1760 | channelList = kwargs['channelList'] |
|
1879 | channelList = kwargs['channelList'] | |
| 1761 | if len(channelList) == 2: |
|
1880 | if len(channelList) == 2: | |
| 1762 | horizontalOnly = True |
|
1881 | horizontalOnly = True | |
| 1763 | arrayChannel = numpy.array(channelList) |
|
1882 | arrayChannel = numpy.array(channelList) | |
| 1764 | param = param[arrayChannel,:,:] |
|
1883 | param = param[arrayChannel,:,:] | |
| 1765 | theta_x = theta_x[arrayChannel] |
|
1884 | theta_x = theta_x[arrayChannel] | |
| 1766 | theta_y = theta_y[arrayChannel] |
|
1885 | theta_y = theta_y[arrayChannel] | |
| 1767 |
|
1886 | |||
| 1768 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(theta_x, theta_y, azimuth) |
|
1887 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(theta_x, theta_y, azimuth) | |
| 1769 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correctFactor*velRadial0, SNR0) |
|
1888 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correctFactor*velRadial0, SNR0) | |
| 1770 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) |
|
1889 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) | |
| 1771 |
|
1890 | |||
| 1772 | #Calculo de Componentes de la velocidad con DBS |
|
1891 | #Calculo de Componentes de la velocidad con DBS | |
| 1773 | winds = self.__calculateVelUVW(A,velRadial1) |
|
1892 | winds = self.__calculateVelUVW(A,velRadial1) | |
| 1774 |
|
1893 | |||
| 1775 | return winds, heiRang1, SNR1 |
|
1894 | return winds, heiRang1, SNR1 | |
| 1776 |
|
1895 | |||
| 1777 | def __calculateDistance(self, posx, posy, pairs_ccf, azimuth = None): |
|
1896 | def __calculateDistance(self, posx, posy, pairs_ccf, azimuth = None): | |
| 1778 |
|
1897 | |||
| 1779 | nPairs = len(pairs_ccf) |
|
1898 | nPairs = len(pairs_ccf) | |
| 1780 | posx = numpy.asarray(posx) |
|
1899 | posx = numpy.asarray(posx) | |
| 1781 | posy = numpy.asarray(posy) |
|
1900 | posy = numpy.asarray(posy) | |
| 1782 |
|
1901 | |||
| 1783 | #Rotacion Inversa para alinear con el azimuth |
|
1902 | #Rotacion Inversa para alinear con el azimuth | |
| 1784 | if azimuth!= None: |
|
1903 | if azimuth!= None: | |
| 1785 | azimuth = azimuth*math.pi/180 |
|
1904 | azimuth = azimuth*math.pi/180 | |
| 1786 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) |
|
1905 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) | |
| 1787 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) |
|
1906 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) | |
| 1788 | else: |
|
1907 | else: | |
| 1789 | posx1 = posx |
|
1908 | posx1 = posx | |
| 1790 | posy1 = posy |
|
1909 | posy1 = posy | |
| 1791 |
|
1910 | |||
| 1792 | #Calculo de Distancias |
|
1911 | #Calculo de Distancias | |
| 1793 | distx = numpy.zeros(nPairs) |
|
1912 | distx = numpy.zeros(nPairs) | |
| 1794 | disty = numpy.zeros(nPairs) |
|
1913 | disty = numpy.zeros(nPairs) | |
| 1795 | dist = numpy.zeros(nPairs) |
|
1914 | dist = numpy.zeros(nPairs) | |
| 1796 | ang = numpy.zeros(nPairs) |
|
1915 | ang = numpy.zeros(nPairs) | |
| 1797 |
|
1916 | |||
| 1798 | for i in range(nPairs): |
|
1917 | for i in range(nPairs): | |
| 1799 | distx[i] = posx1[pairs_ccf[i][1]] - posx1[pairs_ccf[i][0]] |
|
1918 | distx[i] = posx1[pairs_ccf[i][1]] - posx1[pairs_ccf[i][0]] | |
| 1800 | disty[i] = posy1[pairs_ccf[i][1]] - posy1[pairs_ccf[i][0]] |
|
1919 | disty[i] = posy1[pairs_ccf[i][1]] - posy1[pairs_ccf[i][0]] | |
| 1801 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) |
|
1920 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) | |
| 1802 | ang[i] = numpy.arctan2(disty[i],distx[i]) |
|
1921 | ang[i] = numpy.arctan2(disty[i],distx[i]) | |
| 1803 |
|
1922 | |||
| 1804 | return distx, disty, dist, ang |
|
1923 | return distx, disty, dist, ang | |
| 1805 | #Calculo de Matrices |
|
1924 | #Calculo de Matrices | |
| 1806 | # nPairs = len(pairs) |
|
1925 | # nPairs = len(pairs) | |
| 1807 | # ang1 = numpy.zeros((nPairs, 2, 1)) |
|
1926 | # ang1 = numpy.zeros((nPairs, 2, 1)) | |
| 1808 | # dist1 = numpy.zeros((nPairs, 2, 1)) |
|
1927 | # dist1 = numpy.zeros((nPairs, 2, 1)) | |
| 1809 | # |
|
1928 | # | |
| 1810 | # for j in range(nPairs): |
|
1929 | # for j in range(nPairs): | |
| 1811 | # dist1[j,0,0] = dist[pairs[j][0]] |
|
1930 | # dist1[j,0,0] = dist[pairs[j][0]] | |
| 1812 | # dist1[j,1,0] = dist[pairs[j][1]] |
|
1931 | # dist1[j,1,0] = dist[pairs[j][1]] | |
| 1813 | # ang1[j,0,0] = ang[pairs[j][0]] |
|
1932 | # ang1[j,0,0] = ang[pairs[j][0]] | |
| 1814 | # ang1[j,1,0] = ang[pairs[j][1]] |
|
1933 | # ang1[j,1,0] = ang[pairs[j][1]] | |
| 1815 | # |
|
1934 | # | |
| 1816 | # return distx,disty, dist1,ang1 |
|
1935 | # return distx,disty, dist1,ang1 | |
| 1817 |
|
1936 | |||
| 1818 |
|
1937 | |||
| 1819 | def __calculateVelVer(self, phase, lagTRange, _lambda): |
|
1938 | def __calculateVelVer(self, phase, lagTRange, _lambda): | |
| 1820 |
|
1939 | |||
| 1821 | Ts = lagTRange[1] - lagTRange[0] |
|
1940 | Ts = lagTRange[1] - lagTRange[0] | |
| 1822 | velW = -_lambda*phase/(4*math.pi*Ts) |
|
1941 | velW = -_lambda*phase/(4*math.pi*Ts) | |
| 1823 |
|
1942 | |||
| 1824 | return velW |
|
1943 | return velW | |
| 1825 |
|
1944 | |||
| 1826 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): |
|
1945 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): | |
| 1827 | nPairs = tau1.shape[0] |
|
1946 | nPairs = tau1.shape[0] | |
| 1828 | nHeights = tau1.shape[1] |
|
1947 | nHeights = tau1.shape[1] | |
| 1829 | vel = numpy.zeros((nPairs,3,nHeights)) |
|
1948 | vel = numpy.zeros((nPairs,3,nHeights)) | |
| 1830 | dist1 = numpy.reshape(dist, (dist.size,1)) |
|
1949 | dist1 = numpy.reshape(dist, (dist.size,1)) | |
| 1831 |
|
1950 | |||
| 1832 | angCos = numpy.cos(ang) |
|
1951 | angCos = numpy.cos(ang) | |
| 1833 | angSin = numpy.sin(ang) |
|
1952 | angSin = numpy.sin(ang) | |
| 1834 |
|
1953 | |||
| 1835 | vel0 = dist1*tau1/(2*tau2**2) |
|
1954 | vel0 = dist1*tau1/(2*tau2**2) | |
| 1836 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) |
|
1955 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) | |
| 1837 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) |
|
1956 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) | |
| 1838 |
|
1957 | |||
| 1839 | ind = numpy.where(numpy.isinf(vel)) |
|
1958 | ind = numpy.where(numpy.isinf(vel)) | |
| 1840 | vel[ind] = numpy.nan |
|
1959 | vel[ind] = numpy.nan | |
| 1841 |
|
1960 | |||
| 1842 | return vel |
|
1961 | return vel | |
| 1843 |
|
1962 | |||
| 1844 | # def __getPairsAutoCorr(self, pairsList, nChannels): |
|
1963 | # def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 1845 | # |
|
1964 | # | |
| 1846 | # pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
1965 | # pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 1847 | # |
|
1966 | # | |
| 1848 | # for l in range(len(pairsList)): |
|
1967 | # for l in range(len(pairsList)): | |
| 1849 | # firstChannel = pairsList[l][0] |
|
1968 | # firstChannel = pairsList[l][0] | |
| 1850 | # secondChannel = pairsList[l][1] |
|
1969 | # secondChannel = pairsList[l][1] | |
| 1851 | # |
|
1970 | # | |
| 1852 | # #Obteniendo pares de Autocorrelacion |
|
1971 | # #Obteniendo pares de Autocorrelacion | |
| 1853 | # if firstChannel == secondChannel: |
|
1972 | # if firstChannel == secondChannel: | |
| 1854 | # pairsAutoCorr[firstChannel] = int(l) |
|
1973 | # pairsAutoCorr[firstChannel] = int(l) | |
| 1855 | # |
|
1974 | # | |
| 1856 | # pairsAutoCorr = pairsAutoCorr.astype(int) |
|
1975 | # pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 1857 | # |
|
1976 | # | |
| 1858 | # pairsCrossCorr = range(len(pairsList)) |
|
1977 | # pairsCrossCorr = range(len(pairsList)) | |
| 1859 | # pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
1978 | # pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 1860 | # |
|
1979 | # | |
| 1861 | # return pairsAutoCorr, pairsCrossCorr |
|
1980 | # return pairsAutoCorr, pairsCrossCorr | |
| 1862 |
|
1981 | |||
| 1863 | # def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): |
|
1982 | # def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): | |
| 1864 | def techniqueSA(self, kwargs): |
|
1983 | def techniqueSA(self, kwargs): | |
| 1865 |
|
1984 | |||
| 1866 | """ |
|
1985 | """ | |
| 1867 | Function that implements Spaced Antenna (SA) technique. |
|
1986 | Function that implements Spaced Antenna (SA) technique. | |
| 1868 |
|
1987 | |||
| 1869 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1988 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
| 1870 | Direction correction (if necessary), Ranges and SNR |
|
1989 | Direction correction (if necessary), Ranges and SNR | |
| 1871 |
|
1990 | |||
| 1872 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1991 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 1873 |
|
1992 | |||
| 1874 | Parameters affected: Winds |
|
1993 | Parameters affected: Winds | |
| 1875 | """ |
|
1994 | """ | |
| 1876 | position_x = kwargs['positionX'] |
|
1995 | position_x = kwargs['positionX'] | |
| 1877 | position_y = kwargs['positionY'] |
|
1996 | position_y = kwargs['positionY'] | |
| 1878 | azimuth = kwargs['azimuth'] |
|
1997 | azimuth = kwargs['azimuth'] | |
| 1879 |
|
1998 | |||
| 1880 | if kwargs.has_key('correctFactor'): |
|
1999 | if kwargs.has_key('correctFactor'): | |
| 1881 | correctFactor = kwargs['correctFactor'] |
|
2000 | correctFactor = kwargs['correctFactor'] | |
| 1882 | else: |
|
2001 | else: | |
| 1883 | correctFactor = 1 |
|
2002 | correctFactor = 1 | |
| 1884 |
|
2003 | |||
| 1885 | groupList = kwargs['groupList'] |
|
2004 | groupList = kwargs['groupList'] | |
| 1886 | pairs_ccf = groupList[1] |
|
2005 | pairs_ccf = groupList[1] | |
| 1887 | tau = kwargs['tau'] |
|
2006 | tau = kwargs['tau'] | |
| 1888 | _lambda = kwargs['_lambda'] |
|
2007 | _lambda = kwargs['_lambda'] | |
| 1889 |
|
2008 | |||
| 1890 | #Cross Correlation pairs obtained |
|
2009 | #Cross Correlation pairs obtained | |
| 1891 | # pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairssList, nChannels) |
|
2010 | # pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairssList, nChannels) | |
| 1892 | # pairsArray = numpy.array(pairsList)[pairsCrossCorr] |
|
2011 | # pairsArray = numpy.array(pairsList)[pairsCrossCorr] | |
| 1893 | # pairsSelArray = numpy.array(pairsSelected) |
|
2012 | # pairsSelArray = numpy.array(pairsSelected) | |
| 1894 | # pairs = [] |
|
2013 | # pairs = [] | |
| 1895 | # |
|
2014 | # | |
| 1896 | # #Wind estimation pairs obtained |
|
2015 | # #Wind estimation pairs obtained | |
| 1897 | # for i in range(pairsSelArray.shape[0]/2): |
|
2016 | # for i in range(pairsSelArray.shape[0]/2): | |
| 1898 | # ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] |
|
2017 | # ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] | |
| 1899 | # ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] |
|
2018 | # ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] | |
| 1900 | # pairs.append((ind1,ind2)) |
|
2019 | # pairs.append((ind1,ind2)) | |
| 1901 |
|
2020 | |||
| 1902 | indtau = tau.shape[0]/2 |
|
2021 | indtau = tau.shape[0]/2 | |
| 1903 | tau1 = tau[:indtau,:] |
|
2022 | tau1 = tau[:indtau,:] | |
| 1904 | tau2 = tau[indtau:-1,:] |
|
2023 | tau2 = tau[indtau:-1,:] | |
| 1905 | # tau1 = tau1[pairs,:] |
|
2024 | # tau1 = tau1[pairs,:] | |
| 1906 | # tau2 = tau2[pairs,:] |
|
2025 | # tau2 = tau2[pairs,:] | |
| 1907 | phase1 = tau[-1,:] |
|
2026 | phase1 = tau[-1,:] | |
| 1908 |
|
2027 | |||
| 1909 | #--------------------------------------------------------------------- |
|
2028 | #--------------------------------------------------------------------- | |
| 1910 | #Metodo Directo |
|
2029 | #Metodo Directo | |
| 1911 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairs_ccf,azimuth) |
|
2030 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairs_ccf,azimuth) | |
| 1912 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) |
|
2031 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) | |
| 1913 | winds = stats.nanmean(winds, axis=0) |
|
2032 | winds = stats.nanmean(winds, axis=0) | |
| 1914 | #--------------------------------------------------------------------- |
|
2033 | #--------------------------------------------------------------------- | |
| 1915 | #Metodo General |
|
2034 | #Metodo General | |
| 1916 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) |
|
2035 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) | |
| 1917 | # #Calculo Coeficientes de Funcion de Correlacion |
|
2036 | # #Calculo Coeficientes de Funcion de Correlacion | |
| 1918 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) |
|
2037 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) | |
| 1919 | # #Calculo de Velocidades |
|
2038 | # #Calculo de Velocidades | |
| 1920 | # winds = self.calculateVelUV(F,G,A,B,H) |
|
2039 | # winds = self.calculateVelUV(F,G,A,B,H) | |
| 1921 |
|
2040 | |||
| 1922 | #--------------------------------------------------------------------- |
|
2041 | #--------------------------------------------------------------------- | |
| 1923 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) |
|
2042 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) | |
| 1924 | winds = correctFactor*winds |
|
2043 | winds = correctFactor*winds | |
| 1925 | return winds |
|
2044 | return winds | |
| 1926 |
|
2045 | |||
| 1927 | def __checkTime(self, currentTime, paramInterval, outputInterval): |
|
2046 | def __checkTime(self, currentTime, paramInterval, outputInterval): | |
| 1928 |
|
2047 | |||
| 1929 | dataTime = currentTime + paramInterval |
|
2048 | dataTime = currentTime + paramInterval | |
| 1930 | deltaTime = dataTime - self.__initime |
|
2049 | deltaTime = dataTime - self.__initime | |
| 1931 |
|
2050 | |||
| 1932 | if deltaTime >= outputInterval or deltaTime < 0: |
|
2051 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 1933 | self.__dataReady = True |
|
2052 | self.__dataReady = True | |
| 1934 | return |
|
2053 | return | |
| 1935 |
|
2054 | |||
| 1936 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): |
|
2055 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): | |
| 1937 | ''' |
|
2056 | ''' | |
| 1938 | Function that implements winds estimation technique with detected meteors. |
|
2057 | Function that implements winds estimation technique with detected meteors. | |
| 1939 |
|
2058 | |||
| 1940 | Input: Detected meteors, Minimum meteor quantity to wind estimation |
|
2059 | Input: Detected meteors, Minimum meteor quantity to wind estimation | |
| 1941 |
|
2060 | |||
| 1942 | Output: Winds estimation (Zonal and Meridional) |
|
2061 | Output: Winds estimation (Zonal and Meridional) | |
| 1943 |
|
2062 | |||
| 1944 | Parameters affected: Winds |
|
2063 | Parameters affected: Winds | |
| 1945 | ''' |
|
2064 | ''' | |
| 1946 | # print arrayMeteor.shape |
|
2065 | # print arrayMeteor.shape | |
| 1947 | #Settings |
|
2066 | #Settings | |
| 1948 | nInt = (heightMax - heightMin)/2 |
|
2067 | nInt = (heightMax - heightMin)/2 | |
| 1949 | # print nInt |
|
2068 | # print nInt | |
| 1950 | nInt = int(nInt) |
|
2069 | nInt = int(nInt) | |
| 1951 | # print nInt |
|
2070 | # print nInt | |
| 1952 | winds = numpy.zeros((2,nInt))*numpy.nan |
|
2071 | winds = numpy.zeros((2,nInt))*numpy.nan | |
| 1953 |
|
2072 | |||
| 1954 | #Filter errors |
|
2073 | #Filter errors | |
| 1955 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] |
|
2074 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] | |
| 1956 | finalMeteor = arrayMeteor[error,:] |
|
2075 | finalMeteor = arrayMeteor[error,:] | |
| 1957 |
|
2076 | |||
| 1958 | #Meteor Histogram |
|
2077 | #Meteor Histogram | |
| 1959 | finalHeights = finalMeteor[:,2] |
|
2078 | finalHeights = finalMeteor[:,2] | |
| 1960 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) |
|
2079 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) | |
| 1961 | nMeteorsPerI = hist[0] |
|
2080 | nMeteorsPerI = hist[0] | |
| 1962 | heightPerI = hist[1] |
|
2081 | heightPerI = hist[1] | |
| 1963 |
|
2082 | |||
| 1964 | #Sort of meteors |
|
2083 | #Sort of meteors | |
| 1965 | indSort = finalHeights.argsort() |
|
2084 | indSort = finalHeights.argsort() | |
| 1966 | finalMeteor2 = finalMeteor[indSort,:] |
|
2085 | finalMeteor2 = finalMeteor[indSort,:] | |
| 1967 |
|
2086 | |||
| 1968 | # Calculating winds |
|
2087 | # Calculating winds | |
| 1969 | ind1 = 0 |
|
2088 | ind1 = 0 | |
| 1970 | ind2 = 0 |
|
2089 | ind2 = 0 | |
| 1971 |
|
2090 | |||
| 1972 | for i in range(nInt): |
|
2091 | for i in range(nInt): | |
| 1973 | nMet = nMeteorsPerI[i] |
|
2092 | nMet = nMeteorsPerI[i] | |
| 1974 | ind1 = ind2 |
|
2093 | ind1 = ind2 | |
| 1975 | ind2 = ind1 + nMet |
|
2094 | ind2 = ind1 + nMet | |
| 1976 |
|
2095 | |||
| 1977 | meteorAux = finalMeteor2[ind1:ind2,:] |
|
2096 | meteorAux = finalMeteor2[ind1:ind2,:] | |
| 1978 |
|
2097 | |||
| 1979 | if meteorAux.shape[0] >= meteorThresh: |
|
2098 | if meteorAux.shape[0] >= meteorThresh: | |
| 1980 | vel = meteorAux[:, 6] |
|
2099 | vel = meteorAux[:, 6] | |
| 1981 | zen = meteorAux[:, 4]*numpy.pi/180 |
|
2100 | zen = meteorAux[:, 4]*numpy.pi/180 | |
| 1982 | azim = meteorAux[:, 3]*numpy.pi/180 |
|
2101 | azim = meteorAux[:, 3]*numpy.pi/180 | |
| 1983 |
|
2102 | |||
| 1984 | n = numpy.cos(zen) |
|
2103 | n = numpy.cos(zen) | |
| 1985 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) |
|
2104 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) | |
| 1986 | # l = m*numpy.tan(azim) |
|
2105 | # l = m*numpy.tan(azim) | |
| 1987 | l = numpy.sin(zen)*numpy.sin(azim) |
|
2106 | l = numpy.sin(zen)*numpy.sin(azim) | |
| 1988 | m = numpy.sin(zen)*numpy.cos(azim) |
|
2107 | m = numpy.sin(zen)*numpy.cos(azim) | |
| 1989 |
|
2108 | |||
| 1990 | A = numpy.vstack((l, m)).transpose() |
|
2109 | A = numpy.vstack((l, m)).transpose() | |
| 1991 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) |
|
2110 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) | |
| 1992 | windsAux = numpy.dot(A1, vel) |
|
2111 | windsAux = numpy.dot(A1, vel) | |
| 1993 |
|
2112 | |||
| 1994 | winds[0,i] = windsAux[0] |
|
2113 | winds[0,i] = windsAux[0] | |
| 1995 | winds[1,i] = windsAux[1] |
|
2114 | winds[1,i] = windsAux[1] | |
| 1996 |
|
2115 | |||
| 1997 | return winds, heightPerI[:-1] |
|
2116 | return winds, heightPerI[:-1] | |
| 1998 |
|
2117 | |||
| 1999 | def techniqueNSM_SA(self, **kwargs): |
|
2118 | def techniqueNSM_SA(self, **kwargs): | |
| 2000 | metArray = kwargs['metArray'] |
|
2119 | metArray = kwargs['metArray'] | |
| 2001 | heightList = kwargs['heightList'] |
|
2120 | heightList = kwargs['heightList'] | |
| 2002 | timeList = kwargs['timeList'] |
|
2121 | timeList = kwargs['timeList'] | |
| 2003 |
|
2122 | |||
| 2004 | rx_location = kwargs['rx_location'] |
|
2123 | rx_location = kwargs['rx_location'] | |
| 2005 | groupList = kwargs['groupList'] |
|
2124 | groupList = kwargs['groupList'] | |
| 2006 | azimuth = kwargs['azimuth'] |
|
2125 | azimuth = kwargs['azimuth'] | |
| 2007 | dfactor = kwargs['dfactor'] |
|
2126 | dfactor = kwargs['dfactor'] | |
| 2008 | k = kwargs['k'] |
|
2127 | k = kwargs['k'] | |
| 2009 |
|
2128 | |||
| 2010 | azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth) |
|
2129 | azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth) | |
| 2011 | d = dist*dfactor |
|
2130 | d = dist*dfactor | |
| 2012 | #Phase calculation |
|
2131 | #Phase calculation | |
| 2013 | metArray1 = self.__getPhaseSlope(metArray, heightList, timeList) |
|
2132 | metArray1 = self.__getPhaseSlope(metArray, heightList, timeList) | |
| 2014 |
|
2133 | |||
| 2015 | metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities |
|
2134 | metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities | |
| 2016 |
|
2135 | |||
| 2017 | velEst = numpy.zeros((heightList.size,2))*numpy.nan |
|
2136 | velEst = numpy.zeros((heightList.size,2))*numpy.nan | |
| 2018 | azimuth1 = azimuth1*numpy.pi/180 |
|
2137 | azimuth1 = azimuth1*numpy.pi/180 | |
| 2019 |
|
2138 | |||
| 2020 | for i in range(heightList.size): |
|
2139 | for i in range(heightList.size): | |
| 2021 | h = heightList[i] |
|
2140 | h = heightList[i] | |
| 2022 | indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0] |
|
2141 | indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0] | |
| 2023 | metHeight = metArray1[indH,:] |
|
2142 | metHeight = metArray1[indH,:] | |
| 2024 | if metHeight.shape[0] >= 2: |
|
2143 | if metHeight.shape[0] >= 2: | |
| 2025 | velAux = numpy.asmatrix(metHeight[:,-2]).T #Radial Velocities |
|
2144 | velAux = numpy.asmatrix(metHeight[:,-2]).T #Radial Velocities | |
| 2026 | iazim = metHeight[:,1].astype(int) |
|
2145 | iazim = metHeight[:,1].astype(int) | |
| 2027 | azimAux = numpy.asmatrix(azimuth1[iazim]).T #Azimuths |
|
2146 | azimAux = numpy.asmatrix(azimuth1[iazim]).T #Azimuths | |
| 2028 | A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux))) |
|
2147 | A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux))) | |
| 2029 | A = numpy.asmatrix(A) |
|
2148 | A = numpy.asmatrix(A) | |
| 2030 | A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose() |
|
2149 | A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose() | |
| 2031 | velHor = numpy.dot(A1,velAux) |
|
2150 | velHor = numpy.dot(A1,velAux) | |
| 2032 |
|
2151 | |||
| 2033 | velEst[i,:] = numpy.squeeze(velHor) |
|
2152 | velEst[i,:] = numpy.squeeze(velHor) | |
| 2034 | return velEst |
|
2153 | return velEst | |
| 2035 |
|
2154 | |||
| 2036 | def __getPhaseSlope(self, metArray, heightList, timeList): |
|
2155 | def __getPhaseSlope(self, metArray, heightList, timeList): | |
| 2037 | meteorList = [] |
|
2156 | meteorList = [] | |
| 2038 | #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2 |
|
2157 | #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2 | |
| 2039 | #Putting back together the meteor matrix |
|
2158 | #Putting back together the meteor matrix | |
| 2040 | utctime = metArray[:,0] |
|
2159 | utctime = metArray[:,0] | |
| 2041 | uniqueTime = numpy.unique(utctime) |
|
2160 | uniqueTime = numpy.unique(utctime) | |
| 2042 |
|
2161 | |||
| 2043 | phaseDerThresh = 0.5 |
|
2162 | phaseDerThresh = 0.5 | |
| 2044 | ippSeconds = timeList[1] - timeList[0] |
|
2163 | ippSeconds = timeList[1] - timeList[0] | |
| 2045 | sec = numpy.where(timeList>1)[0][0] |
|
2164 | sec = numpy.where(timeList>1)[0][0] | |
| 2046 | nPairs = metArray.shape[1] - 6 |
|
2165 | nPairs = metArray.shape[1] - 6 | |
| 2047 | nHeights = len(heightList) |
|
2166 | nHeights = len(heightList) | |
| 2048 |
|
2167 | |||
| 2049 | for t in uniqueTime: |
|
2168 | for t in uniqueTime: | |
| 2050 | metArray1 = metArray[utctime==t,:] |
|
2169 | metArray1 = metArray[utctime==t,:] | |
| 2051 | # phaseDerThresh = numpy.pi/4 #reducir Phase thresh |
|
2170 | # phaseDerThresh = numpy.pi/4 #reducir Phase thresh | |
| 2052 | tmet = metArray1[:,1].astype(int) |
|
2171 | tmet = metArray1[:,1].astype(int) | |
| 2053 | hmet = metArray1[:,2].astype(int) |
|
2172 | hmet = metArray1[:,2].astype(int) | |
| 2054 |
|
2173 | |||
| 2055 | metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1)) |
|
2174 | metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1)) | |
| 2056 | metPhase[:,:] = numpy.nan |
|
2175 | metPhase[:,:] = numpy.nan | |
| 2057 | metPhase[:,hmet,tmet] = metArray1[:,6:].T |
|
2176 | metPhase[:,hmet,tmet] = metArray1[:,6:].T | |
| 2058 |
|
2177 | |||
| 2059 | #Delete short trails |
|
2178 | #Delete short trails | |
| 2060 | metBool = ~numpy.isnan(metPhase[0,:,:]) |
|
2179 | metBool = ~numpy.isnan(metPhase[0,:,:]) | |
| 2061 | heightVect = numpy.sum(metBool, axis = 1) |
|
2180 | heightVect = numpy.sum(metBool, axis = 1) | |
| 2062 | metBool[heightVect<sec,:] = False |
|
2181 | metBool[heightVect<sec,:] = False | |
| 2063 | metPhase[:,heightVect<sec,:] = numpy.nan |
|
2182 | metPhase[:,heightVect<sec,:] = numpy.nan | |
| 2064 |
|
2183 | |||
| 2065 | #Derivative |
|
2184 | #Derivative | |
| 2066 | metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1]) |
|
2185 | metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1]) | |
| 2067 | phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh)) |
|
2186 | phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh)) | |
| 2068 | metPhase[phDerAux] = numpy.nan |
|
2187 | metPhase[phDerAux] = numpy.nan | |
| 2069 |
|
2188 | |||
| 2070 | #--------------------------METEOR DETECTION ----------------------------------------- |
|
2189 | #--------------------------METEOR DETECTION ----------------------------------------- | |
| 2071 | indMet = numpy.where(numpy.any(metBool,axis=1))[0] |
|
2190 | indMet = numpy.where(numpy.any(metBool,axis=1))[0] | |
| 2072 |
|
2191 | |||
| 2073 | for p in numpy.arange(nPairs): |
|
2192 | for p in numpy.arange(nPairs): | |
| 2074 | phase = metPhase[p,:,:] |
|
2193 | phase = metPhase[p,:,:] | |
| 2075 | phDer = metDer[p,:,:] |
|
2194 | phDer = metDer[p,:,:] | |
| 2076 |
|
2195 | |||
| 2077 | for h in indMet: |
|
2196 | for h in indMet: | |
| 2078 | height = heightList[h] |
|
2197 | height = heightList[h] | |
| 2079 | phase1 = phase[h,:] #82 |
|
2198 | phase1 = phase[h,:] #82 | |
| 2080 | phDer1 = phDer[h,:] |
|
2199 | phDer1 = phDer[h,:] | |
| 2081 |
|
2200 | |||
| 2082 | phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)]) #Unwrap |
|
2201 | phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)]) #Unwrap | |
| 2083 |
|
2202 | |||
| 2084 | indValid = numpy.where(~numpy.isnan(phase1))[0] |
|
2203 | indValid = numpy.where(~numpy.isnan(phase1))[0] | |
| 2085 | initMet = indValid[0] |
|
2204 | initMet = indValid[0] | |
| 2086 | endMet = 0 |
|
2205 | endMet = 0 | |
| 2087 |
|
2206 | |||
| 2088 | for i in range(len(indValid)-1): |
|
2207 | for i in range(len(indValid)-1): | |
| 2089 |
|
2208 | |||
| 2090 | #Time difference |
|
2209 | #Time difference | |
| 2091 | inow = indValid[i] |
|
2210 | inow = indValid[i] | |
| 2092 | inext = indValid[i+1] |
|
2211 | inext = indValid[i+1] | |
| 2093 | idiff = inext - inow |
|
2212 | idiff = inext - inow | |
| 2094 | #Phase difference |
|
2213 | #Phase difference | |
| 2095 | phDiff = numpy.abs(phase1[inext] - phase1[inow]) |
|
2214 | phDiff = numpy.abs(phase1[inext] - phase1[inow]) | |
| 2096 |
|
2215 | |||
| 2097 | if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]: #End of Meteor |
|
2216 | if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]: #End of Meteor | |
| 2098 | sizeTrail = inow - initMet + 1 |
|
2217 | sizeTrail = inow - initMet + 1 | |
| 2099 | if sizeTrail>3*sec: #Too short meteors |
|
2218 | if sizeTrail>3*sec: #Too short meteors | |
| 2100 | x = numpy.arange(initMet,inow+1)*ippSeconds |
|
2219 | x = numpy.arange(initMet,inow+1)*ippSeconds | |
| 2101 | y = phase1[initMet:inow+1] |
|
2220 | y = phase1[initMet:inow+1] | |
| 2102 | ynnan = ~numpy.isnan(y) |
|
2221 | ynnan = ~numpy.isnan(y) | |
| 2103 | x = x[ynnan] |
|
2222 | x = x[ynnan] | |
| 2104 | y = y[ynnan] |
|
2223 | y = y[ynnan] | |
| 2105 | slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) |
|
2224 | slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) | |
| 2106 | ylin = x*slope + intercept |
|
2225 | ylin = x*slope + intercept | |
| 2107 | rsq = r_value**2 |
|
2226 | rsq = r_value**2 | |
| 2108 | if rsq > 0.5: |
|
2227 | if rsq > 0.5: | |
| 2109 | vel = slope#*height*1000/(k*d) |
|
2228 | vel = slope#*height*1000/(k*d) | |
| 2110 | estAux = numpy.array([utctime,p,height, vel, rsq]) |
|
2229 | estAux = numpy.array([utctime,p,height, vel, rsq]) | |
| 2111 | meteorList.append(estAux) |
|
2230 | meteorList.append(estAux) | |
| 2112 | initMet = inext |
|
2231 | initMet = inext | |
| 2113 | metArray2 = numpy.array(meteorList) |
|
2232 | metArray2 = numpy.array(meteorList) | |
| 2114 |
|
2233 | |||
| 2115 | return metArray2 |
|
2234 | return metArray2 | |
| 2116 |
|
2235 | |||
| 2117 | def __calculateAzimuth1(self, rx_location, pairslist, azimuth0): |
|
2236 | def __calculateAzimuth1(self, rx_location, pairslist, azimuth0): | |
| 2118 |
|
2237 | |||
| 2119 | azimuth1 = numpy.zeros(len(pairslist)) |
|
2238 | azimuth1 = numpy.zeros(len(pairslist)) | |
| 2120 | dist = numpy.zeros(len(pairslist)) |
|
2239 | dist = numpy.zeros(len(pairslist)) | |
| 2121 |
|
2240 | |||
| 2122 | for i in range(len(rx_location)): |
|
2241 | for i in range(len(rx_location)): | |
| 2123 | ch0 = pairslist[i][0] |
|
2242 | ch0 = pairslist[i][0] | |
| 2124 | ch1 = pairslist[i][1] |
|
2243 | ch1 = pairslist[i][1] | |
| 2125 |
|
2244 | |||
| 2126 | diffX = rx_location[ch0][0] - rx_location[ch1][0] |
|
2245 | diffX = rx_location[ch0][0] - rx_location[ch1][0] | |
| 2127 | diffY = rx_location[ch0][1] - rx_location[ch1][1] |
|
2246 | diffY = rx_location[ch0][1] - rx_location[ch1][1] | |
| 2128 | azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi |
|
2247 | azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi | |
| 2129 | dist[i] = numpy.sqrt(diffX**2 + diffY**2) |
|
2248 | dist[i] = numpy.sqrt(diffX**2 + diffY**2) | |
| 2130 |
|
2249 | |||
| 2131 | azimuth1 -= azimuth0 |
|
2250 | azimuth1 -= azimuth0 | |
| 2132 | return azimuth1, dist |
|
2251 | return azimuth1, dist | |
| 2133 |
|
2252 | |||
| 2134 | def techniqueNSM_DBS(self, **kwargs): |
|
2253 | def techniqueNSM_DBS(self, **kwargs): | |
| 2135 | metArray = kwargs['metArray'] |
|
2254 | metArray = kwargs['metArray'] | |
| 2136 | heightList = kwargs['heightList'] |
|
2255 | heightList = kwargs['heightList'] | |
| 2137 | timeList = kwargs['timeList'] |
|
2256 | timeList = kwargs['timeList'] | |
| 2138 | zenithList = kwargs['zenithList'] |
|
2257 | zenithList = kwargs['zenithList'] | |
| 2139 | nChan = numpy.max(cmet) + 1 |
|
2258 | nChan = numpy.max(cmet) + 1 | |
| 2140 | nHeights = len(heightList) |
|
2259 | nHeights = len(heightList) | |
| 2141 |
|
2260 | |||
| 2142 | utctime = metArray[:,0] |
|
2261 | utctime = metArray[:,0] | |
| 2143 | cmet = metArray[:,1] |
|
2262 | cmet = metArray[:,1] | |
| 2144 | hmet = metArray1[:,3].astype(int) |
|
2263 | hmet = metArray1[:,3].astype(int) | |
| 2145 | h1met = heightList[hmet]*zenithList[cmet] |
|
2264 | h1met = heightList[hmet]*zenithList[cmet] | |
| 2146 | vmet = metArray1[:,5] |
|
2265 | vmet = metArray1[:,5] | |
| 2147 |
|
2266 | |||
| 2148 | for i in range(nHeights - 1): |
|
2267 | for i in range(nHeights - 1): | |
| 2149 | hmin = heightList[i] |
|
2268 | hmin = heightList[i] | |
| 2150 | hmax = heightList[i + 1] |
|
2269 | hmax = heightList[i + 1] | |
| 2151 |
|
2270 | |||
| 2152 | vthisH = vmet[(h1met>=hmin) & (h1met<hmax)] |
|
2271 | vthisH = vmet[(h1met>=hmin) & (h1met<hmax)] | |
| 2153 |
|
2272 | |||
| 2154 |
|
2273 | |||
| 2155 |
|
2274 | |||
| 2156 | return data_output |
|
2275 | return data_output | |
| 2157 |
|
2276 | |||
| 2158 | def run(self, dataOut, technique, positionY, positionX, azimuth, **kwargs): |
|
2277 | def run(self, dataOut, technique, positionY, positionX, azimuth, **kwargs): | |
| 2159 |
|
2278 | |||
| 2160 | param = dataOut.data_param |
|
2279 | param = dataOut.data_param | |
| 2161 | if dataOut.abscissaList != None: |
|
2280 | if dataOut.abscissaList != None: | |
| 2162 | absc = dataOut.abscissaList[:-1] |
|
2281 | absc = dataOut.abscissaList[:-1] | |
| 2163 | noise = dataOut.noise |
|
2282 | noise = dataOut.noise | |
| 2164 | heightList = dataOut.heightList |
|
2283 | heightList = dataOut.heightList | |
| 2165 | SNR = dataOut.data_SNR |
|
2284 | SNR = dataOut.data_SNR | |
| 2166 |
|
2285 | |||
| 2167 | if technique == 'DBS': |
|
2286 | if technique == 'DBS': | |
| 2168 |
|
2287 | |||
| 2169 | kwargs['velRadial'] = param[:,1,:] #Radial velocity |
|
2288 | kwargs['velRadial'] = param[:,1,:] #Radial velocity | |
| 2170 | kwargs['heightList'] = heightList |
|
2289 | kwargs['heightList'] = heightList | |
| 2171 | kwargs['SNR'] = SNR |
|
2290 | kwargs['SNR'] = SNR | |
| 2172 |
|
2291 | |||
| 2173 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(kwargs) #DBS Function |
|
2292 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(kwargs) #DBS Function | |
| 2174 | dataOut.utctimeInit = dataOut.utctime |
|
2293 | dataOut.utctimeInit = dataOut.utctime | |
| 2175 | dataOut.outputInterval = dataOut.paramInterval |
|
2294 | dataOut.outputInterval = dataOut.paramInterval | |
| 2176 |
|
2295 | |||
| 2177 | elif technique == 'SA': |
|
2296 | elif technique == 'SA': | |
| 2178 |
|
2297 | |||
| 2179 | #Parameters |
|
2298 | #Parameters | |
| 2180 | # position_x = kwargs['positionX'] |
|
2299 | # position_x = kwargs['positionX'] | |
| 2181 | # position_y = kwargs['positionY'] |
|
2300 | # position_y = kwargs['positionY'] | |
| 2182 | # azimuth = kwargs['azimuth'] |
|
2301 | # azimuth = kwargs['azimuth'] | |
| 2183 | # |
|
2302 | # | |
| 2184 | # if kwargs.has_key('crosspairsList'): |
|
2303 | # if kwargs.has_key('crosspairsList'): | |
| 2185 | # pairs = kwargs['crosspairsList'] |
|
2304 | # pairs = kwargs['crosspairsList'] | |
| 2186 | # else: |
|
2305 | # else: | |
| 2187 | # pairs = None |
|
2306 | # pairs = None | |
| 2188 | # |
|
2307 | # | |
| 2189 | # if kwargs.has_key('correctFactor'): |
|
2308 | # if kwargs.has_key('correctFactor'): | |
| 2190 | # correctFactor = kwargs['correctFactor'] |
|
2309 | # correctFactor = kwargs['correctFactor'] | |
| 2191 | # else: |
|
2310 | # else: | |
| 2192 | # correctFactor = 1 |
|
2311 | # correctFactor = 1 | |
| 2193 |
|
2312 | |||
| 2194 | # tau = dataOut.data_param |
|
2313 | # tau = dataOut.data_param | |
| 2195 | # _lambda = dataOut.C/dataOut.frequency |
|
2314 | # _lambda = dataOut.C/dataOut.frequency | |
| 2196 | # pairsList = dataOut.groupList |
|
2315 | # pairsList = dataOut.groupList | |
| 2197 | # nChannels = dataOut.nChannels |
|
2316 | # nChannels = dataOut.nChannels | |
| 2198 |
|
2317 | |||
| 2199 | kwargs['groupList'] = dataOut.groupList |
|
2318 | kwargs['groupList'] = dataOut.groupList | |
| 2200 | kwargs['tau'] = dataOut.data_param |
|
2319 | kwargs['tau'] = dataOut.data_param | |
| 2201 | kwargs['_lambda'] = dataOut.C/dataOut.frequency |
|
2320 | kwargs['_lambda'] = dataOut.C/dataOut.frequency | |
| 2202 | # dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) |
|
2321 | # dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) | |
| 2203 | dataOut.data_output = self.techniqueSA(kwargs) |
|
2322 | dataOut.data_output = self.techniqueSA(kwargs) | |
| 2204 | dataOut.utctimeInit = dataOut.utctime |
|
2323 | dataOut.utctimeInit = dataOut.utctime | |
| 2205 | dataOut.outputInterval = dataOut.timeInterval |
|
2324 | dataOut.outputInterval = dataOut.timeInterval | |
| 2206 |
|
2325 | |||
| 2207 | elif technique == 'Meteors': |
|
2326 | elif technique == 'Meteors': | |
| 2208 | dataOut.flagNoData = True |
|
2327 | dataOut.flagNoData = True | |
| 2209 | self.__dataReady = False |
|
2328 | self.__dataReady = False | |
| 2210 |
|
2329 | |||
| 2211 | if kwargs.has_key('nHours'): |
|
2330 | if kwargs.has_key('nHours'): | |
| 2212 | nHours = kwargs['nHours'] |
|
2331 | nHours = kwargs['nHours'] | |
| 2213 | else: |
|
2332 | else: | |
| 2214 | nHours = 1 |
|
2333 | nHours = 1 | |
| 2215 |
|
2334 | |||
| 2216 | if kwargs.has_key('meteorsPerBin'): |
|
2335 | if kwargs.has_key('meteorsPerBin'): | |
| 2217 | meteorThresh = kwargs['meteorsPerBin'] |
|
2336 | meteorThresh = kwargs['meteorsPerBin'] | |
| 2218 | else: |
|
2337 | else: | |
| 2219 | meteorThresh = 6 |
|
2338 | meteorThresh = 6 | |
| 2220 |
|
2339 | |||
| 2221 | if kwargs.has_key('hmin'): |
|
2340 | if kwargs.has_key('hmin'): | |
| 2222 | hmin = kwargs['hmin'] |
|
2341 | hmin = kwargs['hmin'] | |
| 2223 | else: hmin = 70 |
|
2342 | else: hmin = 70 | |
| 2224 | if kwargs.has_key('hmax'): |
|
2343 | if kwargs.has_key('hmax'): | |
| 2225 | hmax = kwargs['hmax'] |
|
2344 | hmax = kwargs['hmax'] | |
| 2226 | else: hmax = 110 |
|
2345 | else: hmax = 110 | |
| 2227 |
|
2346 | |||
| 2228 | dataOut.outputInterval = nHours*3600 |
|
2347 | dataOut.outputInterval = nHours*3600 | |
| 2229 |
|
2348 | |||
| 2230 | if self.__isConfig == False: |
|
2349 | if self.__isConfig == False: | |
| 2231 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2350 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 2232 | #Get Initial LTC time |
|
2351 | #Get Initial LTC time | |
| 2233 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2352 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 2234 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2353 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 2235 |
|
2354 | |||
| 2236 | self.__isConfig = True |
|
2355 | self.__isConfig = True | |
| 2237 |
|
2356 | |||
| 2238 | if self.__buffer == None: |
|
2357 | if self.__buffer == None: | |
| 2239 | self.__buffer = dataOut.data_param |
|
2358 | self.__buffer = dataOut.data_param | |
| 2240 | self.__firstdata = copy.copy(dataOut) |
|
2359 | self.__firstdata = copy.copy(dataOut) | |
| 2241 |
|
2360 | |||
| 2242 | else: |
|
2361 | else: | |
| 2243 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2362 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 2244 |
|
2363 | |||
| 2245 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2364 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 2246 |
|
2365 | |||
| 2247 | if self.__dataReady: |
|
2366 | if self.__dataReady: | |
| 2248 | dataOut.utctimeInit = self.__initime |
|
2367 | dataOut.utctimeInit = self.__initime | |
| 2249 |
|
2368 | |||
| 2250 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2369 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 2251 |
|
2370 | |||
| 2252 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) |
|
2371 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) | |
| 2253 | dataOut.flagNoData = False |
|
2372 | dataOut.flagNoData = False | |
| 2254 | self.__buffer = None |
|
2373 | self.__buffer = None | |
| 2255 |
|
2374 | |||
| 2256 | elif technique == 'Meteors1': |
|
2375 | elif technique == 'Meteors1': | |
| 2257 | dataOut.flagNoData = True |
|
2376 | dataOut.flagNoData = True | |
| 2258 | self.__dataReady = False |
|
2377 | self.__dataReady = False | |
| 2259 |
|
2378 | |||
| 2260 | if kwargs.has_key('nMins'): |
|
2379 | if kwargs.has_key('nMins'): | |
| 2261 | nMins = kwargs['nMins'] |
|
2380 | nMins = kwargs['nMins'] | |
| 2262 | else: nMins = 20 |
|
2381 | else: nMins = 20 | |
| 2263 | if kwargs.has_key('rx_location'): |
|
2382 | if kwargs.has_key('rx_location'): | |
| 2264 | rx_location = kwargs['rx_location'] |
|
2383 | rx_location = kwargs['rx_location'] | |
| 2265 | else: rx_location = [(0,1),(1,1),(1,0)] |
|
2384 | else: rx_location = [(0,1),(1,1),(1,0)] | |
| 2266 | if kwargs.has_key('azimuth'): |
|
2385 | if kwargs.has_key('azimuth'): | |
| 2267 | azimuth = kwargs['azimuth'] |
|
2386 | azimuth = kwargs['azimuth'] | |
| 2268 | else: azimuth = 51 |
|
2387 | else: azimuth = 51 | |
| 2269 | if kwargs.has_key('dfactor'): |
|
2388 | if kwargs.has_key('dfactor'): | |
| 2270 | dfactor = kwargs['dfactor'] |
|
2389 | dfactor = kwargs['dfactor'] | |
| 2271 | if kwargs.has_key('mode'): |
|
2390 | if kwargs.has_key('mode'): | |
| 2272 | mode = kwargs['mode'] |
|
2391 | mode = kwargs['mode'] | |
| 2273 | else: mode = 'SA' |
|
2392 | else: mode = 'SA' | |
| 2274 |
|
2393 | |||
| 2275 | #Borrar luego esto |
|
2394 | #Borrar luego esto | |
| 2276 | if dataOut.groupList == None: |
|
2395 | if dataOut.groupList == None: | |
| 2277 | dataOut.groupList = [(0,1),(0,2),(1,2)] |
|
2396 | dataOut.groupList = [(0,1),(0,2),(1,2)] | |
| 2278 | groupList = dataOut.groupList |
|
2397 | groupList = dataOut.groupList | |
| 2279 | C = 3e8 |
|
2398 | C = 3e8 | |
| 2280 | freq = 50e6 |
|
2399 | freq = 50e6 | |
| 2281 | lamb = C/freq |
|
2400 | lamb = C/freq | |
| 2282 | k = 2*numpy.pi/lamb |
|
2401 | k = 2*numpy.pi/lamb | |
| 2283 |
|
2402 | |||
| 2284 | timeList = dataOut.abscissaList |
|
2403 | timeList = dataOut.abscissaList | |
| 2285 | heightList = dataOut.heightList |
|
2404 | heightList = dataOut.heightList | |
| 2286 |
|
2405 | |||
| 2287 | if self.__isConfig == False: |
|
2406 | if self.__isConfig == False: | |
| 2288 | dataOut.outputInterval = nMins*60 |
|
2407 | dataOut.outputInterval = nMins*60 | |
| 2289 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2408 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 2290 | #Get Initial LTC time |
|
2409 | #Get Initial LTC time | |
| 2291 | initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2410 | initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 2292 | minuteAux = initime.minute |
|
2411 | minuteAux = initime.minute | |
| 2293 | minuteNew = int(numpy.floor(minuteAux/nMins)*nMins) |
|
2412 | minuteNew = int(numpy.floor(minuteAux/nMins)*nMins) | |
| 2294 | self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2413 | self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 2295 |
|
2414 | |||
| 2296 | self.__isConfig = True |
|
2415 | self.__isConfig = True | |
| 2297 |
|
2416 | |||
| 2298 | if self.__buffer == None: |
|
2417 | if self.__buffer == None: | |
| 2299 | self.__buffer = dataOut.data_param |
|
2418 | self.__buffer = dataOut.data_param | |
| 2300 | self.__firstdata = copy.copy(dataOut) |
|
2419 | self.__firstdata = copy.copy(dataOut) | |
| 2301 |
|
2420 | |||
| 2302 | else: |
|
2421 | else: | |
| 2303 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2422 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 2304 |
|
2423 | |||
| 2305 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2424 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 2306 |
|
2425 | |||
| 2307 | if self.__dataReady: |
|
2426 | if self.__dataReady: | |
| 2308 | dataOut.utctimeInit = self.__initime |
|
2427 | dataOut.utctimeInit = self.__initime | |
| 2309 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2428 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 2310 |
|
2429 | |||
| 2311 | metArray = self.__buffer |
|
2430 | metArray = self.__buffer | |
| 2312 | if mode == 'SA': |
|
2431 | if mode == 'SA': | |
| 2313 | dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList) |
|
2432 | dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList) | |
| 2314 | elif mode == 'DBS': |
|
2433 | elif mode == 'DBS': | |
| 2315 | dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList) |
|
2434 | dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList) | |
| 2316 | dataOut.data_output = dataOut.data_output.T |
|
2435 | dataOut.data_output = dataOut.data_output.T | |
| 2317 | dataOut.flagNoData = False |
|
2436 | dataOut.flagNoData = False | |
| 2318 | self.__buffer = None |
|
2437 | self.__buffer = None | |
| 2319 |
|
2438 | |||
| 2320 | return |
|
2439 | return | |
| 2321 |
|
2440 | |||
| 2322 | class EWDriftsEstimation(Operation): |
|
2441 | class EWDriftsEstimation(Operation): | |
| 2323 |
|
2442 | |||
| 2324 | def __init__(self): |
|
2443 | def __init__(self): | |
| 2325 | Operation.__init__(self) |
|
2444 | Operation.__init__(self) | |
| 2326 |
|
2445 | |||
| 2327 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
2446 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
| 2328 | listPhi = phi.tolist() |
|
2447 | listPhi = phi.tolist() | |
| 2329 | maxid = listPhi.index(max(listPhi)) |
|
2448 | maxid = listPhi.index(max(listPhi)) | |
| 2330 | minid = listPhi.index(min(listPhi)) |
|
2449 | minid = listPhi.index(min(listPhi)) | |
| 2331 |
|
2450 | |||
| 2332 | rango = range(len(phi)) |
|
2451 | rango = range(len(phi)) | |
| 2333 | # rango = numpy.delete(rango,maxid) |
|
2452 | # rango = numpy.delete(rango,maxid) | |
| 2334 |
|
2453 | |||
| 2335 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
2454 | heiRang1 = heiRang*math.cos(phi[maxid]) | |
| 2336 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
2455 | heiRangAux = heiRang*math.cos(phi[minid]) | |
| 2337 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
2456 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |
| 2338 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
2457 | heiRang1 = numpy.delete(heiRang1,indOut) | |
| 2339 |
|
2458 | |||
| 2340 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
2459 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 2341 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
2460 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 2342 |
|
2461 | |||
| 2343 | for i in rango: |
|
2462 | for i in rango: | |
| 2344 | x = heiRang*math.cos(phi[i]) |
|
2463 | x = heiRang*math.cos(phi[i]) | |
| 2345 | y1 = velRadial[i,:] |
|
2464 | y1 = velRadial[i,:] | |
| 2346 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
2465 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |
| 2347 |
|
2466 | |||
| 2348 | x1 = heiRang1 |
|
2467 | x1 = heiRang1 | |
| 2349 | y11 = f1(x1) |
|
2468 | y11 = f1(x1) | |
| 2350 |
|
2469 | |||
| 2351 | y2 = SNR[i,:] |
|
2470 | y2 = SNR[i,:] | |
| 2352 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
2471 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |
| 2353 | y21 = f2(x1) |
|
2472 | y21 = f2(x1) | |
| 2354 |
|
2473 | |||
| 2355 | velRadial1[i,:] = y11 |
|
2474 | velRadial1[i,:] = y11 | |
| 2356 | SNR1[i,:] = y21 |
|
2475 | SNR1[i,:] = y21 | |
| 2357 |
|
2476 | |||
| 2358 | return heiRang1, velRadial1, SNR1 |
|
2477 | return heiRang1, velRadial1, SNR1 | |
| 2359 |
|
2478 | |||
| 2360 | def run(self, dataOut, zenith, zenithCorrection): |
|
2479 | def run(self, dataOut, zenith, zenithCorrection): | |
| 2361 | heiRang = dataOut.heightList |
|
2480 | heiRang = dataOut.heightList | |
| 2362 | velRadial = dataOut.data_param[:,3,:] |
|
2481 | velRadial = dataOut.data_param[:,3,:] | |
| 2363 | SNR = dataOut.data_SNR |
|
2482 | SNR = dataOut.data_SNR | |
| 2364 |
|
2483 | |||
| 2365 | zenith = numpy.array(zenith) |
|
2484 | zenith = numpy.array(zenith) | |
| 2366 | zenith -= zenithCorrection |
|
2485 | zenith -= zenithCorrection | |
| 2367 | zenith *= numpy.pi/180 |
|
2486 | zenith *= numpy.pi/180 | |
| 2368 |
|
2487 | |||
| 2369 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) |
|
2488 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) | |
| 2370 |
|
2489 | |||
| 2371 | alp = zenith[0] |
|
2490 | alp = zenith[0] | |
| 2372 | bet = zenith[1] |
|
2491 | bet = zenith[1] | |
| 2373 |
|
2492 | |||
| 2374 | w_w = velRadial1[0,:] |
|
2493 | w_w = velRadial1[0,:] | |
| 2375 | w_e = velRadial1[1,:] |
|
2494 | w_e = velRadial1[1,:] | |
| 2376 |
|
2495 | |||
| 2377 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) |
|
2496 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) | |
| 2378 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) |
|
2497 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) | |
| 2379 |
|
2498 | |||
| 2380 | winds = numpy.vstack((u,w)) |
|
2499 | winds = numpy.vstack((u,w)) | |
| 2381 |
|
2500 | |||
| 2382 | dataOut.heightList = heiRang1 |
|
2501 | dataOut.heightList = heiRang1 | |
| 2383 | dataOut.data_output = winds |
|
2502 | dataOut.data_output = winds | |
| 2384 | dataOut.data_SNR = SNR1 |
|
2503 | dataOut.data_SNR = SNR1 | |
| 2385 |
|
2504 | |||
| 2386 | dataOut.utctimeInit = dataOut.utctime |
|
2505 | dataOut.utctimeInit = dataOut.utctime | |
| 2387 | dataOut.outputInterval = dataOut.timeInterval |
|
2506 | dataOut.outputInterval = dataOut.timeInterval | |
| 2388 | return |
|
2507 | return | |
| 2389 |
|
2508 | |||
| 2390 | #--------------- Non Specular Meteor ---------------- |
|
2509 | #--------------- Non Specular Meteor ---------------- | |
| 2391 |
|
2510 | |||
| 2392 | class NonSpecularMeteorDetection(Operation): |
|
2511 | class NonSpecularMeteorDetection(Operation): | |
| 2393 |
|
2512 | |||
| 2394 | def run(self, mode, SNRthresh=8, phaseDerThresh=0.5, cohThresh=0.8, allData = False): |
|
2513 | def run(self, mode, SNRthresh=8, phaseDerThresh=0.5, cohThresh=0.8, allData = False): | |
| 2395 | data_acf = self.dataOut.data_pre[0] |
|
2514 | data_acf = self.dataOut.data_pre[0] | |
| 2396 | data_ccf = self.dataOut.data_pre[1] |
|
2515 | data_ccf = self.dataOut.data_pre[1] | |
| 2397 |
|
2516 | |||
| 2398 | lamb = self.dataOut.C/self.dataOut.frequency |
|
2517 | lamb = self.dataOut.C/self.dataOut.frequency | |
| 2399 | tSamp = self.dataOut.ippSeconds*self.dataOut.nCohInt |
|
2518 | tSamp = self.dataOut.ippSeconds*self.dataOut.nCohInt | |
| 2400 | paramInterval = self.dataOut.paramInterval |
|
2519 | paramInterval = self.dataOut.paramInterval | |
| 2401 |
|
2520 | |||
| 2402 | nChannels = data_acf.shape[0] |
|
2521 | nChannels = data_acf.shape[0] | |
| 2403 | nLags = data_acf.shape[1] |
|
2522 | nLags = data_acf.shape[1] | |
| 2404 | nProfiles = data_acf.shape[2] |
|
2523 | nProfiles = data_acf.shape[2] | |
| 2405 | nHeights = self.dataOut.nHeights |
|
2524 | nHeights = self.dataOut.nHeights | |
| 2406 | nCohInt = self.dataOut.nCohInt |
|
2525 | nCohInt = self.dataOut.nCohInt | |
| 2407 | sec = numpy.round(nProfiles/self.dataOut.paramInterval) |
|
2526 | sec = numpy.round(nProfiles/self.dataOut.paramInterval) | |
| 2408 | heightList = self.dataOut.heightList |
|
2527 | heightList = self.dataOut.heightList | |
| 2409 | ippSeconds = self.dataOut.ippSeconds*self.dataOut.nCohInt*self.dataOut.nAvg |
|
2528 | ippSeconds = self.dataOut.ippSeconds*self.dataOut.nCohInt*self.dataOut.nAvg | |
| 2410 | utctime = self.dataOut.utctime |
|
2529 | utctime = self.dataOut.utctime | |
| 2411 |
|
2530 | |||
| 2412 | self.dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds) |
|
2531 | self.dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds) | |
| 2413 |
|
2532 | |||
| 2414 | #------------------------ SNR -------------------------------------- |
|
2533 | #------------------------ SNR -------------------------------------- | |
| 2415 | power = data_acf[:,0,:,:].real |
|
2534 | power = data_acf[:,0,:,:].real | |
| 2416 | noise = numpy.zeros(nChannels) |
|
2535 | noise = numpy.zeros(nChannels) | |
| 2417 | SNR = numpy.zeros(power.shape) |
|
2536 | SNR = numpy.zeros(power.shape) | |
| 2418 | for i in range(nChannels): |
|
2537 | for i in range(nChannels): | |
| 2419 | noise[i] = hildebrand_sekhon(power[i,:], nCohInt) |
|
2538 | noise[i] = hildebrand_sekhon(power[i,:], nCohInt) | |
| 2420 | SNR[i] = (power[i]-noise[i])/noise[i] |
|
2539 | SNR[i] = (power[i]-noise[i])/noise[i] | |
| 2421 | SNRm = numpy.nanmean(SNR, axis = 0) |
|
2540 | SNRm = numpy.nanmean(SNR, axis = 0) | |
| 2422 | SNRdB = 10*numpy.log10(SNR) |
|
2541 | SNRdB = 10*numpy.log10(SNR) | |
| 2423 |
|
2542 | |||
| 2424 | if mode == 'SA': |
|
2543 | if mode == 'SA': | |
| 2425 | nPairs = data_ccf.shape[0] |
|
2544 | nPairs = data_ccf.shape[0] | |
| 2426 | #---------------------- Coherence and Phase -------------------------- |
|
2545 | #---------------------- Coherence and Phase -------------------------- | |
| 2427 | phase = numpy.zeros(data_ccf[:,0,:,:].shape) |
|
2546 | phase = numpy.zeros(data_ccf[:,0,:,:].shape) | |
| 2428 | # phase1 = numpy.copy(phase) |
|
2547 | # phase1 = numpy.copy(phase) | |
| 2429 | coh1 = numpy.zeros(data_ccf[:,0,:,:].shape) |
|
2548 | coh1 = numpy.zeros(data_ccf[:,0,:,:].shape) | |
| 2430 |
|
2549 | |||
| 2431 | for p in range(nPairs): |
|
2550 | for p in range(nPairs): | |
| 2432 | ch0 = self.dataOut.groupList[p][0] |
|
2551 | ch0 = self.dataOut.groupList[p][0] | |
| 2433 | ch1 = self.dataOut.groupList[p][1] |
|
2552 | ch1 = self.dataOut.groupList[p][1] | |
| 2434 | ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:]) |
|
2553 | ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:]) | |
| 2435 | phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter |
|
2554 | phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter | |
| 2436 | # phase1[p,:,:] = numpy.angle(ccf) #median filter |
|
2555 | # phase1[p,:,:] = numpy.angle(ccf) #median filter | |
| 2437 | coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter |
|
2556 | coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter | |
| 2438 | # coh1[p,:,:] = numpy.abs(ccf) #median filter |
|
2557 | # coh1[p,:,:] = numpy.abs(ccf) #median filter | |
| 2439 | coh = numpy.nanmax(coh1, axis = 0) |
|
2558 | coh = numpy.nanmax(coh1, axis = 0) | |
| 2440 | # struc = numpy.ones((5,1)) |
|
2559 | # struc = numpy.ones((5,1)) | |
| 2441 | # coh = ndimage.morphology.grey_dilation(coh, size=(10,1)) |
|
2560 | # coh = ndimage.morphology.grey_dilation(coh, size=(10,1)) | |
| 2442 | #---------------------- Radial Velocity ---------------------------- |
|
2561 | #---------------------- Radial Velocity ---------------------------- | |
| 2443 | phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0) |
|
2562 | phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0) | |
| 2444 | velRad = phaseAux*lamb/(4*numpy.pi*tSamp) |
|
2563 | velRad = phaseAux*lamb/(4*numpy.pi*tSamp) | |
| 2445 |
|
2564 | |||
| 2446 | if allData: |
|
2565 | if allData: | |
| 2447 | boolMetFin = ~numpy.isnan(SNRm) |
|
2566 | boolMetFin = ~numpy.isnan(SNRm) | |
| 2448 | # coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) |
|
2567 | # coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |
| 2449 | else: |
|
2568 | else: | |
| 2450 | #------------------------ Meteor mask --------------------------------- |
|
2569 | #------------------------ Meteor mask --------------------------------- | |
| 2451 | # #SNR mask |
|
2570 | # #SNR mask | |
| 2452 | # boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB)) |
|
2571 | # boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB)) | |
| 2453 | # |
|
2572 | # | |
| 2454 | # #Erase small objects |
|
2573 | # #Erase small objects | |
| 2455 | # boolMet1 = self.__erase_small(boolMet, 2*sec, 5) |
|
2574 | # boolMet1 = self.__erase_small(boolMet, 2*sec, 5) | |
| 2456 | # |
|
2575 | # | |
| 2457 | # auxEEJ = numpy.sum(boolMet1,axis=0) |
|
2576 | # auxEEJ = numpy.sum(boolMet1,axis=0) | |
| 2458 | # indOver = auxEEJ>nProfiles*0.8 #Use this later |
|
2577 | # indOver = auxEEJ>nProfiles*0.8 #Use this later | |
| 2459 | # indEEJ = numpy.where(indOver)[0] |
|
2578 | # indEEJ = numpy.where(indOver)[0] | |
| 2460 | # indNEEJ = numpy.where(~indOver)[0] |
|
2579 | # indNEEJ = numpy.where(~indOver)[0] | |
| 2461 | # |
|
2580 | # | |
| 2462 | # boolMetFin = boolMet1 |
|
2581 | # boolMetFin = boolMet1 | |
| 2463 | # |
|
2582 | # | |
| 2464 | # if indEEJ.size > 0: |
|
2583 | # if indEEJ.size > 0: | |
| 2465 | # boolMet1[:,indEEJ] = False #Erase heights with EEJ |
|
2584 | # boolMet1[:,indEEJ] = False #Erase heights with EEJ | |
| 2466 | # |
|
2585 | # | |
| 2467 | # boolMet2 = coh > cohThresh |
|
2586 | # boolMet2 = coh > cohThresh | |
| 2468 | # boolMet2 = self.__erase_small(boolMet2, 2*sec,5) |
|
2587 | # boolMet2 = self.__erase_small(boolMet2, 2*sec,5) | |
| 2469 | # |
|
2588 | # | |
| 2470 | # #Final Meteor mask |
|
2589 | # #Final Meteor mask | |
| 2471 | # boolMetFin = boolMet1|boolMet2 |
|
2590 | # boolMetFin = boolMet1|boolMet2 | |
| 2472 |
|
2591 | |||
| 2473 | #Coherence mask |
|
2592 | #Coherence mask | |
| 2474 | boolMet1 = coh > 0.75 |
|
2593 | boolMet1 = coh > 0.75 | |
| 2475 | struc = numpy.ones((30,1)) |
|
2594 | struc = numpy.ones((30,1)) | |
| 2476 | boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc) |
|
2595 | boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc) | |
| 2477 |
|
2596 | |||
| 2478 | #Derivative mask |
|
2597 | #Derivative mask | |
| 2479 | derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) |
|
2598 | derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |
| 2480 | boolMet2 = derPhase < 0.2 |
|
2599 | boolMet2 = derPhase < 0.2 | |
| 2481 | # boolMet2 = ndimage.morphology.binary_opening(boolMet2) |
|
2600 | # boolMet2 = ndimage.morphology.binary_opening(boolMet2) | |
| 2482 | # boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1))) |
|
2601 | # boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1))) | |
| 2483 | boolMet2 = ndimage.median_filter(boolMet2,size=5) |
|
2602 | boolMet2 = ndimage.median_filter(boolMet2,size=5) | |
| 2484 | boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool))) |
|
2603 | boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool))) | |
| 2485 | # #Final mask |
|
2604 | # #Final mask | |
| 2486 | # boolMetFin = boolMet2 |
|
2605 | # boolMetFin = boolMet2 | |
| 2487 | boolMetFin = boolMet1&boolMet2 |
|
2606 | boolMetFin = boolMet1&boolMet2 | |
| 2488 | # boolMetFin = ndimage.morphology.binary_dilation(boolMetFin) |
|
2607 | # boolMetFin = ndimage.morphology.binary_dilation(boolMetFin) | |
| 2489 | #Creating data_param |
|
2608 | #Creating data_param | |
| 2490 | coordMet = numpy.where(boolMetFin) |
|
2609 | coordMet = numpy.where(boolMetFin) | |
| 2491 |
|
2610 | |||
| 2492 | tmet = coordMet[0] |
|
2611 | tmet = coordMet[0] | |
| 2493 | hmet = coordMet[1] |
|
2612 | hmet = coordMet[1] | |
| 2494 |
|
2613 | |||
| 2495 | data_param = numpy.zeros((tmet.size, 6 + nPairs)) |
|
2614 | data_param = numpy.zeros((tmet.size, 6 + nPairs)) | |
| 2496 | data_param[:,0] = utctime |
|
2615 | data_param[:,0] = utctime | |
| 2497 | data_param[:,1] = tmet |
|
2616 | data_param[:,1] = tmet | |
| 2498 | data_param[:,2] = hmet |
|
2617 | data_param[:,2] = hmet | |
| 2499 | data_param[:,3] = SNRm[tmet,hmet] |
|
2618 | data_param[:,3] = SNRm[tmet,hmet] | |
| 2500 | data_param[:,4] = velRad[tmet,hmet] |
|
2619 | data_param[:,4] = velRad[tmet,hmet] | |
| 2501 | data_param[:,5] = coh[tmet,hmet] |
|
2620 | data_param[:,5] = coh[tmet,hmet] | |
| 2502 | data_param[:,6:] = phase[:,tmet,hmet].T |
|
2621 | data_param[:,6:] = phase[:,tmet,hmet].T | |
| 2503 |
|
2622 | |||
| 2504 | elif mode == 'DBS': |
|
2623 | elif mode == 'DBS': | |
| 2505 | self.dataOut.groupList = numpy.arange(nChannels) |
|
2624 | self.dataOut.groupList = numpy.arange(nChannels) | |
| 2506 |
|
2625 | |||
| 2507 | #Radial Velocities |
|
2626 | #Radial Velocities | |
| 2508 | # phase = numpy.angle(data_acf[:,1,:,:]) |
|
2627 | # phase = numpy.angle(data_acf[:,1,:,:]) | |
| 2509 | phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1)) |
|
2628 | phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1)) | |
| 2510 | velRad = phase*lamb/(4*numpy.pi*tSamp) |
|
2629 | velRad = phase*lamb/(4*numpy.pi*tSamp) | |
| 2511 |
|
2630 | |||
| 2512 | #Spectral width |
|
2631 | #Spectral width | |
| 2513 | acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1)) |
|
2632 | acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1)) | |
| 2514 | acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1)) |
|
2633 | acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1)) | |
| 2515 |
|
2634 | |||
| 2516 | spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2)) |
|
2635 | spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2)) | |
| 2517 | # velRad = ndimage.median_filter(velRad, size = (1,5,1)) |
|
2636 | # velRad = ndimage.median_filter(velRad, size = (1,5,1)) | |
| 2518 | if allData: |
|
2637 | if allData: | |
| 2519 | boolMetFin = ~numpy.isnan(SNRdB) |
|
2638 | boolMetFin = ~numpy.isnan(SNRdB) | |
| 2520 | else: |
|
2639 | else: | |
| 2521 | #SNR |
|
2640 | #SNR | |
| 2522 | boolMet1 = (SNRdB>SNRthresh) #SNR mask |
|
2641 | boolMet1 = (SNRdB>SNRthresh) #SNR mask | |
| 2523 | boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5)) |
|
2642 | boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5)) | |
| 2524 |
|
2643 | |||
| 2525 | #Radial velocity |
|
2644 | #Radial velocity | |
| 2526 | boolMet2 = numpy.abs(velRad) < 30 |
|
2645 | boolMet2 = numpy.abs(velRad) < 30 | |
| 2527 | boolMet2 = ndimage.median_filter(boolMet2, (1,5,5)) |
|
2646 | boolMet2 = ndimage.median_filter(boolMet2, (1,5,5)) | |
| 2528 |
|
2647 | |||
| 2529 | #Spectral Width |
|
2648 | #Spectral Width | |
| 2530 | boolMet3 = spcWidth < 30 |
|
2649 | boolMet3 = spcWidth < 30 | |
| 2531 | boolMet3 = ndimage.median_filter(boolMet3, (1,5,5)) |
|
2650 | boolMet3 = ndimage.median_filter(boolMet3, (1,5,5)) | |
| 2532 | # boolMetFin = self.__erase_small(boolMet1, 10,5) |
|
2651 | # boolMetFin = self.__erase_small(boolMet1, 10,5) | |
| 2533 | boolMetFin = boolMet1&boolMet2&boolMet3 |
|
2652 | boolMetFin = boolMet1&boolMet2&boolMet3 | |
| 2534 |
|
2653 | |||
| 2535 | #Creating data_param |
|
2654 | #Creating data_param | |
| 2536 | coordMet = numpy.where(boolMetFin) |
|
2655 | coordMet = numpy.where(boolMetFin) | |
| 2537 |
|
2656 | |||
| 2538 | cmet = coordMet[0] |
|
2657 | cmet = coordMet[0] | |
| 2539 | tmet = coordMet[1] |
|
2658 | tmet = coordMet[1] | |
| 2540 | hmet = coordMet[2] |
|
2659 | hmet = coordMet[2] | |
| 2541 |
|
2660 | |||
| 2542 | data_param = numpy.zeros((tmet.size, 7)) |
|
2661 | data_param = numpy.zeros((tmet.size, 7)) | |
| 2543 | data_param[:,0] = utctime |
|
2662 | data_param[:,0] = utctime | |
| 2544 | data_param[:,1] = cmet |
|
2663 | data_param[:,1] = cmet | |
| 2545 | data_param[:,2] = tmet |
|
2664 | data_param[:,2] = tmet | |
| 2546 | data_param[:,3] = hmet |
|
2665 | data_param[:,3] = hmet | |
| 2547 | data_param[:,4] = SNR[cmet,tmet,hmet].T |
|
2666 | data_param[:,4] = SNR[cmet,tmet,hmet].T | |
| 2548 | data_param[:,5] = velRad[cmet,tmet,hmet].T |
|
2667 | data_param[:,5] = velRad[cmet,tmet,hmet].T | |
| 2549 | data_param[:,6] = spcWidth[cmet,tmet,hmet].T |
|
2668 | data_param[:,6] = spcWidth[cmet,tmet,hmet].T | |
| 2550 |
|
2669 | |||
| 2551 | # self.dataOut.data_param = data_int |
|
2670 | # self.dataOut.data_param = data_int | |
| 2552 | if len(data_param) == 0: |
|
2671 | if len(data_param) == 0: | |
| 2553 | self.dataOut.flagNoData = True |
|
2672 | self.dataOut.flagNoData = True | |
| 2554 | else: |
|
2673 | else: | |
| 2555 | self.dataOut.data_param = data_param |
|
2674 | self.dataOut.data_param = data_param | |
| 2556 |
|
2675 | |||
| 2557 | def __erase_small(self, binArray, threshX, threshY): |
|
2676 | def __erase_small(self, binArray, threshX, threshY): | |
| 2558 | labarray, numfeat = ndimage.measurements.label(binArray) |
|
2677 | labarray, numfeat = ndimage.measurements.label(binArray) | |
| 2559 | binArray1 = numpy.copy(binArray) |
|
2678 | binArray1 = numpy.copy(binArray) | |
| 2560 |
|
2679 | |||
| 2561 | for i in range(1,numfeat + 1): |
|
2680 | for i in range(1,numfeat + 1): | |
| 2562 | auxBin = (labarray==i) |
|
2681 | auxBin = (labarray==i) | |
| 2563 | auxSize = auxBin.sum() |
|
2682 | auxSize = auxBin.sum() | |
| 2564 |
|
2683 | |||
| 2565 | x,y = numpy.where(auxBin) |
|
2684 | x,y = numpy.where(auxBin) | |
| 2566 | widthX = x.max() - x.min() |
|
2685 | widthX = x.max() - x.min() | |
| 2567 | widthY = y.max() - y.min() |
|
2686 | widthY = y.max() - y.min() | |
| 2568 |
|
2687 | |||
| 2569 | #width X: 3 seg -> 12.5*3 |
|
2688 | #width X: 3 seg -> 12.5*3 | |
| 2570 | #width Y: |
|
2689 | #width Y: | |
| 2571 |
|
2690 | |||
| 2572 | if (auxSize < 50) or (widthX < threshX) or (widthY < threshY): |
|
2691 | if (auxSize < 50) or (widthX < threshX) or (widthY < threshY): | |
| 2573 | binArray1[auxBin] = False |
|
2692 | binArray1[auxBin] = False | |
| 2574 |
|
2693 | |||
| 2575 | return binArray1 |
|
2694 | return binArray1 | |
| 2576 |
|
2695 | |||
| 2577 | #--------------- Specular Meteor ---------------- |
|
2696 | #--------------- Specular Meteor ---------------- | |
| 2578 |
|
2697 | |||
| 2579 | class SMDetection(Operation): |
|
2698 | class SMDetection(Operation): | |
| 2580 | ''' |
|
2699 | ''' | |
| 2581 | Function DetectMeteors() |
|
2700 | Function DetectMeteors() | |
| 2582 | Project developed with paper: |
|
2701 | Project developed with paper: | |
| 2583 | HOLDSWORTH ET AL. 2004 |
|
2702 | HOLDSWORTH ET AL. 2004 | |
| 2584 |
|
2703 | |||
| 2585 | Input: |
|
2704 | Input: | |
| 2586 | self.dataOut.data_pre |
|
2705 | self.dataOut.data_pre | |
| 2587 |
|
2706 | |||
| 2588 | centerReceiverIndex: From the channels, which is the center receiver |
|
2707 | centerReceiverIndex: From the channels, which is the center receiver | |
| 2589 |
|
2708 | |||
| 2590 | hei_ref: Height reference for the Beacon signal extraction |
|
2709 | hei_ref: Height reference for the Beacon signal extraction | |
| 2591 | tauindex: |
|
2710 | tauindex: | |
| 2592 | predefinedPhaseShifts: Predefined phase offset for the voltge signals |
|
2711 | predefinedPhaseShifts: Predefined phase offset for the voltge signals | |
| 2593 |
|
2712 | |||
| 2594 | cohDetection: Whether to user Coherent detection or not |
|
2713 | cohDetection: Whether to user Coherent detection or not | |
| 2595 | cohDet_timeStep: Coherent Detection calculation time step |
|
2714 | cohDet_timeStep: Coherent Detection calculation time step | |
| 2596 | cohDet_thresh: Coherent Detection phase threshold to correct phases |
|
2715 | cohDet_thresh: Coherent Detection phase threshold to correct phases | |
| 2597 |
|
2716 | |||
| 2598 | noise_timeStep: Noise calculation time step |
|
2717 | noise_timeStep: Noise calculation time step | |
| 2599 | noise_multiple: Noise multiple to define signal threshold |
|
2718 | noise_multiple: Noise multiple to define signal threshold | |
| 2600 |
|
2719 | |||
| 2601 | multDet_timeLimit: Multiple Detection Removal time limit in seconds |
|
2720 | multDet_timeLimit: Multiple Detection Removal time limit in seconds | |
| 2602 | multDet_rangeLimit: Multiple Detection Removal range limit in km |
|
2721 | multDet_rangeLimit: Multiple Detection Removal range limit in km | |
| 2603 |
|
2722 | |||
| 2604 | phaseThresh: Maximum phase difference between receiver to be consider a meteor |
|
2723 | phaseThresh: Maximum phase difference between receiver to be consider a meteor | |
| 2605 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor |
|
2724 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor | |
| 2606 |
|
2725 | |||
| 2607 | hmin: Minimum Height of the meteor to use it in the further wind estimations |
|
2726 | hmin: Minimum Height of the meteor to use it in the further wind estimations | |
| 2608 | hmax: Maximum Height of the meteor to use it in the further wind estimations |
|
2727 | hmax: Maximum Height of the meteor to use it in the further wind estimations | |
| 2609 | azimuth: Azimuth angle correction |
|
2728 | azimuth: Azimuth angle correction | |
| 2610 |
|
2729 | |||
| 2611 | Affected: |
|
2730 | Affected: | |
| 2612 | self.dataOut.data_param |
|
2731 | self.dataOut.data_param | |
| 2613 |
|
2732 | |||
| 2614 | Rejection Criteria (Errors): |
|
2733 | Rejection Criteria (Errors): | |
| 2615 | 0: No error; analysis OK |
|
2734 | 0: No error; analysis OK | |
| 2616 | 1: SNR < SNR threshold |
|
2735 | 1: SNR < SNR threshold | |
| 2617 | 2: angle of arrival (AOA) ambiguously determined |
|
2736 | 2: angle of arrival (AOA) ambiguously determined | |
| 2618 | 3: AOA estimate not feasible |
|
2737 | 3: AOA estimate not feasible | |
| 2619 | 4: Large difference in AOAs obtained from different antenna baselines |
|
2738 | 4: Large difference in AOAs obtained from different antenna baselines | |
| 2620 | 5: echo at start or end of time series |
|
2739 | 5: echo at start or end of time series | |
| 2621 | 6: echo less than 5 examples long; too short for analysis |
|
2740 | 6: echo less than 5 examples long; too short for analysis | |
| 2622 | 7: echo rise exceeds 0.3s |
|
2741 | 7: echo rise exceeds 0.3s | |
| 2623 | 8: echo decay time less than twice rise time |
|
2742 | 8: echo decay time less than twice rise time | |
| 2624 | 9: large power level before echo |
|
2743 | 9: large power level before echo | |
| 2625 | 10: large power level after echo |
|
2744 | 10: large power level after echo | |
| 2626 | 11: poor fit to amplitude for estimation of decay time |
|
2745 | 11: poor fit to amplitude for estimation of decay time | |
| 2627 | 12: poor fit to CCF phase variation for estimation of radial drift velocity |
|
2746 | 12: poor fit to CCF phase variation for estimation of radial drift velocity | |
| 2628 | 13: height unresolvable echo: not valid height within 70 to 110 km |
|
2747 | 13: height unresolvable echo: not valid height within 70 to 110 km | |
| 2629 | 14: height ambiguous echo: more then one possible height within 70 to 110 km |
|
2748 | 14: height ambiguous echo: more then one possible height within 70 to 110 km | |
| 2630 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s |
|
2749 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s | |
| 2631 | 16: oscilatory echo, indicating event most likely not an underdense echo |
|
2750 | 16: oscilatory echo, indicating event most likely not an underdense echo | |
| 2632 |
|
2751 | |||
| 2633 | 17: phase difference in meteor Reestimation |
|
2752 | 17: phase difference in meteor Reestimation | |
| 2634 |
|
2753 | |||
| 2635 | Data Storage: |
|
2754 | Data Storage: | |
| 2636 | Meteors for Wind Estimation (8): |
|
2755 | Meteors for Wind Estimation (8): | |
| 2637 | Utc Time | Range Height |
|
2756 | Utc Time | Range Height | |
| 2638 | Azimuth Zenith errorCosDir |
|
2757 | Azimuth Zenith errorCosDir | |
| 2639 | VelRad errorVelRad |
|
2758 | VelRad errorVelRad | |
| 2640 | Phase0 Phase1 Phase2 Phase3 |
|
2759 | Phase0 Phase1 Phase2 Phase3 | |
| 2641 | TypeError |
|
2760 | TypeError | |
| 2642 |
|
2761 | |||
| 2643 | ''' |
|
2762 | ''' | |
| 2644 |
|
2763 | |||
| 2645 | def run(self, dataOut, hei_ref = None, tauindex = 0, |
|
2764 | def run(self, dataOut, hei_ref = None, tauindex = 0, | |
| 2646 | phaseOffsets = None, |
|
2765 | phaseOffsets = None, | |
| 2647 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, |
|
2766 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, | |
| 2648 | noise_timeStep = 4, noise_multiple = 4, |
|
2767 | noise_timeStep = 4, noise_multiple = 4, | |
| 2649 | multDet_timeLimit = 1, multDet_rangeLimit = 3, |
|
2768 | multDet_timeLimit = 1, multDet_rangeLimit = 3, | |
| 2650 | phaseThresh = 20, SNRThresh = 5, |
|
2769 | phaseThresh = 20, SNRThresh = 5, | |
| 2651 | hmin = 50, hmax=150, azimuth = 0, |
|
2770 | hmin = 50, hmax=150, azimuth = 0, | |
| 2652 | channelPositions = None) : |
|
2771 | channelPositions = None) : | |
| 2653 |
|
2772 | |||
| 2654 |
|
2773 | |||
| 2655 | #Getting Pairslist |
|
2774 | #Getting Pairslist | |
| 2656 | if channelPositions == None: |
|
2775 | if channelPositions == None: | |
| 2657 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
2776 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |
| 2658 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
2777 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |
| 2659 | meteorOps = SMOperations() |
|
2778 | meteorOps = SMOperations() | |
| 2660 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
2779 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |
| 2661 | heiRang = dataOut.getHeiRange() |
|
2780 | heiRang = dataOut.getHeiRange() | |
| 2662 | #Get Beacon signal - No Beacon signal anymore |
|
2781 | #Get Beacon signal - No Beacon signal anymore | |
| 2663 | # newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
2782 | # newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 2664 | # |
|
2783 | # | |
| 2665 | # if hei_ref != None: |
|
2784 | # if hei_ref != None: | |
| 2666 | # newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
2785 | # newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 2667 | # |
|
2786 | # | |
| 2668 |
|
2787 | |||
| 2669 |
|
2788 | |||
| 2670 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** |
|
2789 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** | |
| 2671 | # see if the user put in pre defined phase shifts |
|
2790 | # see if the user put in pre defined phase shifts | |
| 2672 | voltsPShift = dataOut.data_pre.copy() |
|
2791 | voltsPShift = dataOut.data_pre.copy() | |
| 2673 |
|
2792 | |||
| 2674 | # if predefinedPhaseShifts != None: |
|
2793 | # if predefinedPhaseShifts != None: | |
| 2675 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 |
|
2794 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 | |
| 2676 | # |
|
2795 | # | |
| 2677 | # # elif beaconPhaseShifts: |
|
2796 | # # elif beaconPhaseShifts: | |
| 2678 | # # #get hardware phase shifts using beacon signal |
|
2797 | # # #get hardware phase shifts using beacon signal | |
| 2679 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) |
|
2798 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) | |
| 2680 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) |
|
2799 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) | |
| 2681 | # |
|
2800 | # | |
| 2682 | # else: |
|
2801 | # else: | |
| 2683 | # hardwarePhaseShifts = numpy.zeros(5) |
|
2802 | # hardwarePhaseShifts = numpy.zeros(5) | |
| 2684 | # |
|
2803 | # | |
| 2685 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') |
|
2804 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') | |
| 2686 | # for i in range(self.dataOut.data_pre.shape[0]): |
|
2805 | # for i in range(self.dataOut.data_pre.shape[0]): | |
| 2687 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) |
|
2806 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) | |
| 2688 |
|
2807 | |||
| 2689 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* |
|
2808 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* | |
| 2690 |
|
2809 | |||
| 2691 | #Remove DC |
|
2810 | #Remove DC | |
| 2692 | voltsDC = numpy.mean(voltsPShift,1) |
|
2811 | voltsDC = numpy.mean(voltsPShift,1) | |
| 2693 | voltsDC = numpy.mean(voltsDC,1) |
|
2812 | voltsDC = numpy.mean(voltsDC,1) | |
| 2694 | for i in range(voltsDC.shape[0]): |
|
2813 | for i in range(voltsDC.shape[0]): | |
| 2695 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] |
|
2814 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] | |
| 2696 |
|
2815 | |||
| 2697 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift |
|
2816 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift | |
| 2698 | # voltsPShift = voltsPShift[:,:,:newheis[0][0]] |
|
2817 | # voltsPShift = voltsPShift[:,:,:newheis[0][0]] | |
| 2699 |
|
2818 | |||
| 2700 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** |
|
2819 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** | |
| 2701 | #Coherent Detection |
|
2820 | #Coherent Detection | |
| 2702 | if cohDetection: |
|
2821 | if cohDetection: | |
| 2703 | #use coherent detection to get the net power |
|
2822 | #use coherent detection to get the net power | |
| 2704 | cohDet_thresh = cohDet_thresh*numpy.pi/180 |
|
2823 | cohDet_thresh = cohDet_thresh*numpy.pi/180 | |
| 2705 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, dataOut.timeInterval, pairslist0, cohDet_thresh) |
|
2824 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, dataOut.timeInterval, pairslist0, cohDet_thresh) | |
| 2706 |
|
2825 | |||
| 2707 | #Non-coherent detection! |
|
2826 | #Non-coherent detection! | |
| 2708 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) |
|
2827 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) | |
| 2709 | #********** END OF COH/NON-COH POWER CALCULATION********************** |
|
2828 | #********** END OF COH/NON-COH POWER CALCULATION********************** | |
| 2710 |
|
2829 | |||
| 2711 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** |
|
2830 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** | |
| 2712 | #Get noise |
|
2831 | #Get noise | |
| 2713 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, dataOut.timeInterval) |
|
2832 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, dataOut.timeInterval) | |
| 2714 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) |
|
2833 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) | |
| 2715 | #Get signal threshold |
|
2834 | #Get signal threshold | |
| 2716 | signalThresh = noise_multiple*noise |
|
2835 | signalThresh = noise_multiple*noise | |
| 2717 | #Meteor echoes detection |
|
2836 | #Meteor echoes detection | |
| 2718 | listMeteors = self.__findMeteors(powerNet, signalThresh) |
|
2837 | listMeteors = self.__findMeteors(powerNet, signalThresh) | |
| 2719 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** |
|
2838 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** | |
| 2720 |
|
2839 | |||
| 2721 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** |
|
2840 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** | |
| 2722 | #Parameters |
|
2841 | #Parameters | |
| 2723 | heiRange = dataOut.getHeiRange() |
|
2842 | heiRange = dataOut.getHeiRange() | |
| 2724 | rangeInterval = heiRange[1] - heiRange[0] |
|
2843 | rangeInterval = heiRange[1] - heiRange[0] | |
| 2725 | rangeLimit = multDet_rangeLimit/rangeInterval |
|
2844 | rangeLimit = multDet_rangeLimit/rangeInterval | |
| 2726 | timeLimit = multDet_timeLimit/dataOut.timeInterval |
|
2845 | timeLimit = multDet_timeLimit/dataOut.timeInterval | |
| 2727 | #Multiple detection removals |
|
2846 | #Multiple detection removals | |
| 2728 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) |
|
2847 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) | |
| 2729 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** |
|
2848 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** | |
| 2730 |
|
2849 | |||
| 2731 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** |
|
2850 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** | |
| 2732 | #Parameters |
|
2851 | #Parameters | |
| 2733 | phaseThresh = phaseThresh*numpy.pi/180 |
|
2852 | phaseThresh = phaseThresh*numpy.pi/180 | |
| 2734 | thresh = [phaseThresh, noise_multiple, SNRThresh] |
|
2853 | thresh = [phaseThresh, noise_multiple, SNRThresh] | |
| 2735 | #Meteor reestimation (Errors N 1, 6, 12, 17) |
|
2854 | #Meteor reestimation (Errors N 1, 6, 12, 17) | |
| 2736 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist0, thresh, noise, dataOut.timeInterval, dataOut.frequency) |
|
2855 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist0, thresh, noise, dataOut.timeInterval, dataOut.frequency) | |
| 2737 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) |
|
2856 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) | |
| 2738 | #Estimation of decay times (Errors N 7, 8, 11) |
|
2857 | #Estimation of decay times (Errors N 7, 8, 11) | |
| 2739 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, dataOut.timeInterval, dataOut.frequency) |
|
2858 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, dataOut.timeInterval, dataOut.frequency) | |
| 2740 | #******************* END OF METEOR REESTIMATION ******************* |
|
2859 | #******************* END OF METEOR REESTIMATION ******************* | |
| 2741 |
|
2860 | |||
| 2742 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** |
|
2861 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** | |
| 2743 | #Calculating Radial Velocity (Error N 15) |
|
2862 | #Calculating Radial Velocity (Error N 15) | |
| 2744 | radialStdThresh = 10 |
|
2863 | radialStdThresh = 10 | |
| 2745 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist0, dataOut.timeInterval) |
|
2864 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist0, dataOut.timeInterval) | |
| 2746 |
|
2865 | |||
| 2747 | if len(listMeteors4) > 0: |
|
2866 | if len(listMeteors4) > 0: | |
| 2748 | #Setting New Array |
|
2867 | #Setting New Array | |
| 2749 | date = dataOut.utctime |
|
2868 | date = dataOut.utctime | |
| 2750 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) |
|
2869 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) | |
| 2751 |
|
2870 | |||
| 2752 | #Correcting phase offset |
|
2871 | #Correcting phase offset | |
| 2753 | if phaseOffsets != None: |
|
2872 | if phaseOffsets != None: | |
| 2754 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
2873 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |
| 2755 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
2874 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |
| 2756 |
|
2875 | |||
| 2757 | #Second Pairslist |
|
2876 | #Second Pairslist | |
| 2758 | pairsList = [] |
|
2877 | pairsList = [] | |
| 2759 | pairx = (0,1) |
|
2878 | pairx = (0,1) | |
| 2760 | pairy = (2,3) |
|
2879 | pairy = (2,3) | |
| 2761 | pairsList.append(pairx) |
|
2880 | pairsList.append(pairx) | |
| 2762 | pairsList.append(pairy) |
|
2881 | pairsList.append(pairy) | |
| 2763 |
|
2882 | |||
| 2764 | jph = numpy.array([0,0,0,0]) |
|
2883 | jph = numpy.array([0,0,0,0]) | |
| 2765 | h = (hmin,hmax) |
|
2884 | h = (hmin,hmax) | |
| 2766 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) |
|
2885 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) | |
| 2767 |
|
2886 | |||
| 2768 | # #Calculate AOA (Error N 3, 4) |
|
2887 | # #Calculate AOA (Error N 3, 4) | |
| 2769 | # #JONES ET AL. 1998 |
|
2888 | # #JONES ET AL. 1998 | |
| 2770 | # error = arrayParameters[:,-1] |
|
2889 | # error = arrayParameters[:,-1] | |
| 2771 | # AOAthresh = numpy.pi/8 |
|
2890 | # AOAthresh = numpy.pi/8 | |
| 2772 | # phases = -arrayParameters[:,9:13] |
|
2891 | # phases = -arrayParameters[:,9:13] | |
| 2773 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) |
|
2892 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) | |
| 2774 | # |
|
2893 | # | |
| 2775 | # #Calculate Heights (Error N 13 and 14) |
|
2894 | # #Calculate Heights (Error N 13 and 14) | |
| 2776 | # error = arrayParameters[:,-1] |
|
2895 | # error = arrayParameters[:,-1] | |
| 2777 | # Ranges = arrayParameters[:,2] |
|
2896 | # Ranges = arrayParameters[:,2] | |
| 2778 | # zenith = arrayParameters[:,5] |
|
2897 | # zenith = arrayParameters[:,5] | |
| 2779 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) |
|
2898 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) | |
| 2780 | # error = arrayParameters[:,-1] |
|
2899 | # error = arrayParameters[:,-1] | |
| 2781 | #********************* END OF PARAMETERS CALCULATION ************************** |
|
2900 | #********************* END OF PARAMETERS CALCULATION ************************** | |
| 2782 |
|
2901 | |||
| 2783 | #***************************+ PASS DATA TO NEXT STEP ********************** |
|
2902 | #***************************+ PASS DATA TO NEXT STEP ********************** | |
| 2784 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) |
|
2903 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) | |
| 2785 | dataOut.data_param = arrayParameters |
|
2904 | dataOut.data_param = arrayParameters | |
| 2786 |
|
2905 | |||
| 2787 | if arrayParameters == None: |
|
2906 | if arrayParameters == None: | |
| 2788 | dataOut.flagNoData = True |
|
2907 | dataOut.flagNoData = True | |
| 2789 | else: |
|
2908 | else: | |
| 2790 | dataOut.flagNoData = True |
|
2909 | dataOut.flagNoData = True | |
| 2791 |
|
2910 | |||
| 2792 | return |
|
2911 | return | |
| 2793 |
|
2912 | |||
| 2794 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): |
|
2913 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): | |
| 2795 |
|
2914 | |||
| 2796 | minIndex = min(newheis[0]) |
|
2915 | minIndex = min(newheis[0]) | |
| 2797 | maxIndex = max(newheis[0]) |
|
2916 | maxIndex = max(newheis[0]) | |
| 2798 |
|
2917 | |||
| 2799 | voltage = voltage0[:,:,minIndex:maxIndex+1] |
|
2918 | voltage = voltage0[:,:,minIndex:maxIndex+1] | |
| 2800 | nLength = voltage.shape[1]/n |
|
2919 | nLength = voltage.shape[1]/n | |
| 2801 | nMin = 0 |
|
2920 | nMin = 0 | |
| 2802 | nMax = 0 |
|
2921 | nMax = 0 | |
| 2803 | phaseOffset = numpy.zeros((len(pairslist),n)) |
|
2922 | phaseOffset = numpy.zeros((len(pairslist),n)) | |
| 2804 |
|
2923 | |||
| 2805 | for i in range(n): |
|
2924 | for i in range(n): | |
| 2806 | nMax += nLength |
|
2925 | nMax += nLength | |
| 2807 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) |
|
2926 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) | |
| 2808 | phaseCCF = numpy.mean(phaseCCF, axis = 2) |
|
2927 | phaseCCF = numpy.mean(phaseCCF, axis = 2) | |
| 2809 | phaseOffset[:,i] = phaseCCF.transpose() |
|
2928 | phaseOffset[:,i] = phaseCCF.transpose() | |
| 2810 | nMin = nMax |
|
2929 | nMin = nMax | |
| 2811 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) |
|
2930 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) | |
| 2812 |
|
2931 | |||
| 2813 | #Remove Outliers |
|
2932 | #Remove Outliers | |
| 2814 | factor = 2 |
|
2933 | factor = 2 | |
| 2815 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) |
|
2934 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) | |
| 2816 | dw = numpy.std(wt,axis = 1) |
|
2935 | dw = numpy.std(wt,axis = 1) | |
| 2817 | dw = dw.reshape((dw.size,1)) |
|
2936 | dw = dw.reshape((dw.size,1)) | |
| 2818 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) |
|
2937 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) | |
| 2819 | phaseOffset[ind] = numpy.nan |
|
2938 | phaseOffset[ind] = numpy.nan | |
| 2820 | phaseOffset = stats.nanmean(phaseOffset, axis=1) |
|
2939 | phaseOffset = stats.nanmean(phaseOffset, axis=1) | |
| 2821 |
|
2940 | |||
| 2822 | return phaseOffset |
|
2941 | return phaseOffset | |
| 2823 |
|
2942 | |||
| 2824 | def __shiftPhase(self, data, phaseShift): |
|
2943 | def __shiftPhase(self, data, phaseShift): | |
| 2825 | #this will shift the phase of a complex number |
|
2944 | #this will shift the phase of a complex number | |
| 2826 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) |
|
2945 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) | |
| 2827 | return dataShifted |
|
2946 | return dataShifted | |
| 2828 |
|
2947 | |||
| 2829 | def __estimatePhaseDifference(self, array, pairslist): |
|
2948 | def __estimatePhaseDifference(self, array, pairslist): | |
| 2830 | nChannel = array.shape[0] |
|
2949 | nChannel = array.shape[0] | |
| 2831 | nHeights = array.shape[2] |
|
2950 | nHeights = array.shape[2] | |
| 2832 | numPairs = len(pairslist) |
|
2951 | numPairs = len(pairslist) | |
| 2833 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) |
|
2952 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) | |
| 2834 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) |
|
2953 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) | |
| 2835 |
|
2954 | |||
| 2836 | #Correct phases |
|
2955 | #Correct phases | |
| 2837 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] |
|
2956 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] | |
| 2838 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
2957 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |
| 2839 |
|
2958 | |||
| 2840 | if indDer[0].shape[0] > 0: |
|
2959 | if indDer[0].shape[0] > 0: | |
| 2841 | for i in range(indDer[0].shape[0]): |
|
2960 | for i in range(indDer[0].shape[0]): | |
| 2842 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) |
|
2961 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) | |
| 2843 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi |
|
2962 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi | |
| 2844 |
|
2963 | |||
| 2845 | # for j in range(numSides): |
|
2964 | # for j in range(numSides): | |
| 2846 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) |
|
2965 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) | |
| 2847 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) |
|
2966 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) | |
| 2848 | # |
|
2967 | # | |
| 2849 | #Linear |
|
2968 | #Linear | |
| 2850 | phaseInt = numpy.zeros((numPairs,1)) |
|
2969 | phaseInt = numpy.zeros((numPairs,1)) | |
| 2851 | angAllCCF = phaseCCF[:,[0,1,3,4],0] |
|
2970 | angAllCCF = phaseCCF[:,[0,1,3,4],0] | |
| 2852 | for j in range(numPairs): |
|
2971 | for j in range(numPairs): | |
| 2853 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) |
|
2972 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) | |
| 2854 | phaseInt[j] = fit[1] |
|
2973 | phaseInt[j] = fit[1] | |
| 2855 | #Phase Differences |
|
2974 | #Phase Differences | |
| 2856 | phaseDiff = phaseInt - phaseCCF[:,2,:] |
|
2975 | phaseDiff = phaseInt - phaseCCF[:,2,:] | |
| 2857 | phaseArrival = phaseInt.reshape(phaseInt.size) |
|
2976 | phaseArrival = phaseInt.reshape(phaseInt.size) | |
| 2858 |
|
2977 | |||
| 2859 | #Dealias |
|
2978 | #Dealias | |
| 2860 | phaseArrival = numpy.angle(numpy.exp(1j*phaseArrival)) |
|
2979 | phaseArrival = numpy.angle(numpy.exp(1j*phaseArrival)) | |
| 2861 | # indAlias = numpy.where(phaseArrival > numpy.pi) |
|
2980 | # indAlias = numpy.where(phaseArrival > numpy.pi) | |
| 2862 | # phaseArrival[indAlias] -= 2*numpy.pi |
|
2981 | # phaseArrival[indAlias] -= 2*numpy.pi | |
| 2863 | # indAlias = numpy.where(phaseArrival < -numpy.pi) |
|
2982 | # indAlias = numpy.where(phaseArrival < -numpy.pi) | |
| 2864 | # phaseArrival[indAlias] += 2*numpy.pi |
|
2983 | # phaseArrival[indAlias] += 2*numpy.pi | |
| 2865 |
|
2984 | |||
| 2866 | return phaseDiff, phaseArrival |
|
2985 | return phaseDiff, phaseArrival | |
| 2867 |
|
2986 | |||
| 2868 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): |
|
2987 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): | |
| 2869 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power |
|
2988 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power | |
| 2870 | #find the phase shifts of each channel over 1 second intervals |
|
2989 | #find the phase shifts of each channel over 1 second intervals | |
| 2871 | #only look at ranges below the beacon signal |
|
2990 | #only look at ranges below the beacon signal | |
| 2872 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
2991 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |
| 2873 | numBlocks = int(volts.shape[1]/numProfPerBlock) |
|
2992 | numBlocks = int(volts.shape[1]/numProfPerBlock) | |
| 2874 | numHeights = volts.shape[2] |
|
2993 | numHeights = volts.shape[2] | |
| 2875 | nChannel = volts.shape[0] |
|
2994 | nChannel = volts.shape[0] | |
| 2876 | voltsCohDet = volts.copy() |
|
2995 | voltsCohDet = volts.copy() | |
| 2877 |
|
2996 | |||
| 2878 | pairsarray = numpy.array(pairslist) |
|
2997 | pairsarray = numpy.array(pairslist) | |
| 2879 | indSides = pairsarray[:,1] |
|
2998 | indSides = pairsarray[:,1] | |
| 2880 | # indSides = numpy.array(range(nChannel)) |
|
2999 | # indSides = numpy.array(range(nChannel)) | |
| 2881 | # indSides = numpy.delete(indSides, indCenter) |
|
3000 | # indSides = numpy.delete(indSides, indCenter) | |
| 2882 | # |
|
3001 | # | |
| 2883 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) |
|
3002 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) | |
| 2884 | listBlocks = numpy.array_split(volts, numBlocks, 1) |
|
3003 | listBlocks = numpy.array_split(volts, numBlocks, 1) | |
| 2885 |
|
3004 | |||
| 2886 | startInd = 0 |
|
3005 | startInd = 0 | |
| 2887 | endInd = 0 |
|
3006 | endInd = 0 | |
| 2888 |
|
3007 | |||
| 2889 | for i in range(numBlocks): |
|
3008 | for i in range(numBlocks): | |
| 2890 | startInd = endInd |
|
3009 | startInd = endInd | |
| 2891 | endInd = endInd + listBlocks[i].shape[1] |
|
3010 | endInd = endInd + listBlocks[i].shape[1] | |
| 2892 |
|
3011 | |||
| 2893 | arrayBlock = listBlocks[i] |
|
3012 | arrayBlock = listBlocks[i] | |
| 2894 | # arrayBlockCenter = listCenter[i] |
|
3013 | # arrayBlockCenter = listCenter[i] | |
| 2895 |
|
3014 | |||
| 2896 | #Estimate the Phase Difference |
|
3015 | #Estimate the Phase Difference | |
| 2897 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) |
|
3016 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) | |
| 2898 | #Phase Difference RMS |
|
3017 | #Phase Difference RMS | |
| 2899 | arrayPhaseRMS = numpy.abs(phaseDiff) |
|
3018 | arrayPhaseRMS = numpy.abs(phaseDiff) | |
| 2900 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) |
|
3019 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) | |
| 2901 | indPhase = numpy.where(phaseRMSaux==4) |
|
3020 | indPhase = numpy.where(phaseRMSaux==4) | |
| 2902 | #Shifting |
|
3021 | #Shifting | |
| 2903 | if indPhase[0].shape[0] > 0: |
|
3022 | if indPhase[0].shape[0] > 0: | |
| 2904 | for j in range(indSides.size): |
|
3023 | for j in range(indSides.size): | |
| 2905 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) |
|
3024 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) | |
| 2906 | voltsCohDet[:,startInd:endInd,:] = arrayBlock |
|
3025 | voltsCohDet[:,startInd:endInd,:] = arrayBlock | |
| 2907 |
|
3026 | |||
| 2908 | return voltsCohDet |
|
3027 | return voltsCohDet | |
| 2909 |
|
3028 | |||
| 2910 | def __calculateCCF(self, volts, pairslist ,laglist): |
|
3029 | def __calculateCCF(self, volts, pairslist ,laglist): | |
| 2911 |
|
3030 | |||
| 2912 | nHeights = volts.shape[2] |
|
3031 | nHeights = volts.shape[2] | |
| 2913 | nPoints = volts.shape[1] |
|
3032 | nPoints = volts.shape[1] | |
| 2914 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') |
|
3033 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') | |
| 2915 |
|
3034 | |||
| 2916 | for i in range(len(pairslist)): |
|
3035 | for i in range(len(pairslist)): | |
| 2917 | volts1 = volts[pairslist[i][0]] |
|
3036 | volts1 = volts[pairslist[i][0]] | |
| 2918 | volts2 = volts[pairslist[i][1]] |
|
3037 | volts2 = volts[pairslist[i][1]] | |
| 2919 |
|
3038 | |||
| 2920 | for t in range(len(laglist)): |
|
3039 | for t in range(len(laglist)): | |
| 2921 | idxT = laglist[t] |
|
3040 | idxT = laglist[t] | |
| 2922 | if idxT >= 0: |
|
3041 | if idxT >= 0: | |
| 2923 | vStacked = numpy.vstack((volts2[idxT:,:], |
|
3042 | vStacked = numpy.vstack((volts2[idxT:,:], | |
| 2924 | numpy.zeros((idxT, nHeights),dtype='complex'))) |
|
3043 | numpy.zeros((idxT, nHeights),dtype='complex'))) | |
| 2925 | else: |
|
3044 | else: | |
| 2926 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), |
|
3045 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), | |
| 2927 | volts2[:(nPoints + idxT),:])) |
|
3046 | volts2[:(nPoints + idxT),:])) | |
| 2928 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) |
|
3047 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) | |
| 2929 |
|
3048 | |||
| 2930 | vStacked = None |
|
3049 | vStacked = None | |
| 2931 | return voltsCCF |
|
3050 | return voltsCCF | |
| 2932 |
|
3051 | |||
| 2933 | def __getNoise(self, power, timeSegment, timeInterval): |
|
3052 | def __getNoise(self, power, timeSegment, timeInterval): | |
| 2934 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
3053 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |
| 2935 | numBlocks = int(power.shape[0]/numProfPerBlock) |
|
3054 | numBlocks = int(power.shape[0]/numProfPerBlock) | |
| 2936 | numHeights = power.shape[1] |
|
3055 | numHeights = power.shape[1] | |
| 2937 |
|
3056 | |||
| 2938 | listPower = numpy.array_split(power, numBlocks, 0) |
|
3057 | listPower = numpy.array_split(power, numBlocks, 0) | |
| 2939 | noise = numpy.zeros((power.shape[0], power.shape[1])) |
|
3058 | noise = numpy.zeros((power.shape[0], power.shape[1])) | |
| 2940 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) |
|
3059 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) | |
| 2941 |
|
3060 | |||
| 2942 | startInd = 0 |
|
3061 | startInd = 0 | |
| 2943 | endInd = 0 |
|
3062 | endInd = 0 | |
| 2944 |
|
3063 | |||
| 2945 | for i in range(numBlocks): #split por canal |
|
3064 | for i in range(numBlocks): #split por canal | |
| 2946 | startInd = endInd |
|
3065 | startInd = endInd | |
| 2947 | endInd = endInd + listPower[i].shape[0] |
|
3066 | endInd = endInd + listPower[i].shape[0] | |
| 2948 |
|
3067 | |||
| 2949 | arrayBlock = listPower[i] |
|
3068 | arrayBlock = listPower[i] | |
| 2950 | noiseAux = numpy.mean(arrayBlock, 0) |
|
3069 | noiseAux = numpy.mean(arrayBlock, 0) | |
| 2951 | # noiseAux = numpy.median(noiseAux) |
|
3070 | # noiseAux = numpy.median(noiseAux) | |
| 2952 | # noiseAux = numpy.mean(arrayBlock) |
|
3071 | # noiseAux = numpy.mean(arrayBlock) | |
| 2953 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux |
|
3072 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux | |
| 2954 |
|
3073 | |||
| 2955 | noiseAux1 = numpy.mean(arrayBlock) |
|
3074 | noiseAux1 = numpy.mean(arrayBlock) | |
| 2956 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 |
|
3075 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 | |
| 2957 |
|
3076 | |||
| 2958 | return noise, noise1 |
|
3077 | return noise, noise1 | |
| 2959 |
|
3078 | |||
| 2960 | def __findMeteors(self, power, thresh): |
|
3079 | def __findMeteors(self, power, thresh): | |
| 2961 | nProf = power.shape[0] |
|
3080 | nProf = power.shape[0] | |
| 2962 | nHeights = power.shape[1] |
|
3081 | nHeights = power.shape[1] | |
| 2963 | listMeteors = [] |
|
3082 | listMeteors = [] | |
| 2964 |
|
3083 | |||
| 2965 | for i in range(nHeights): |
|
3084 | for i in range(nHeights): | |
| 2966 | powerAux = power[:,i] |
|
3085 | powerAux = power[:,i] | |
| 2967 | threshAux = thresh[:,i] |
|
3086 | threshAux = thresh[:,i] | |
| 2968 |
|
3087 | |||
| 2969 | indUPthresh = numpy.where(powerAux > threshAux)[0] |
|
3088 | indUPthresh = numpy.where(powerAux > threshAux)[0] | |
| 2970 | indDNthresh = numpy.where(powerAux <= threshAux)[0] |
|
3089 | indDNthresh = numpy.where(powerAux <= threshAux)[0] | |
| 2971 |
|
3090 | |||
| 2972 | j = 0 |
|
3091 | j = 0 | |
| 2973 |
|
3092 | |||
| 2974 | while (j < indUPthresh.size - 2): |
|
3093 | while (j < indUPthresh.size - 2): | |
| 2975 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): |
|
3094 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): | |
| 2976 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) |
|
3095 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) | |
| 2977 | indDNthresh = indDNthresh[indDNAux] |
|
3096 | indDNthresh = indDNthresh[indDNAux] | |
| 2978 |
|
3097 | |||
| 2979 | if (indDNthresh.size > 0): |
|
3098 | if (indDNthresh.size > 0): | |
| 2980 | indEnd = indDNthresh[0] - 1 |
|
3099 | indEnd = indDNthresh[0] - 1 | |
| 2981 | indInit = indUPthresh[j] |
|
3100 | indInit = indUPthresh[j] | |
| 2982 |
|
3101 | |||
| 2983 | meteor = powerAux[indInit:indEnd + 1] |
|
3102 | meteor = powerAux[indInit:indEnd + 1] | |
| 2984 | indPeak = meteor.argmax() + indInit |
|
3103 | indPeak = meteor.argmax() + indInit | |
| 2985 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) |
|
3104 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) | |
| 2986 |
|
3105 | |||
| 2987 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! |
|
3106 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! | |
| 2988 | j = numpy.where(indUPthresh == indEnd)[0] + 1 |
|
3107 | j = numpy.where(indUPthresh == indEnd)[0] + 1 | |
| 2989 | else: j+=1 |
|
3108 | else: j+=1 | |
| 2990 | else: j+=1 |
|
3109 | else: j+=1 | |
| 2991 |
|
3110 | |||
| 2992 | return listMeteors |
|
3111 | return listMeteors | |
| 2993 |
|
3112 | |||
| 2994 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): |
|
3113 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): | |
| 2995 |
|
3114 | |||
| 2996 | arrayMeteors = numpy.asarray(listMeteors) |
|
3115 | arrayMeteors = numpy.asarray(listMeteors) | |
| 2997 | listMeteors1 = [] |
|
3116 | listMeteors1 = [] | |
| 2998 |
|
3117 | |||
| 2999 | while arrayMeteors.shape[0] > 0: |
|
3118 | while arrayMeteors.shape[0] > 0: | |
| 3000 | FLAs = arrayMeteors[:,4] |
|
3119 | FLAs = arrayMeteors[:,4] | |
| 3001 | maxFLA = FLAs.argmax() |
|
3120 | maxFLA = FLAs.argmax() | |
| 3002 | listMeteors1.append(arrayMeteors[maxFLA,:]) |
|
3121 | listMeteors1.append(arrayMeteors[maxFLA,:]) | |
| 3003 |
|
3122 | |||
| 3004 | MeteorInitTime = arrayMeteors[maxFLA,1] |
|
3123 | MeteorInitTime = arrayMeteors[maxFLA,1] | |
| 3005 | MeteorEndTime = arrayMeteors[maxFLA,3] |
|
3124 | MeteorEndTime = arrayMeteors[maxFLA,3] | |
| 3006 | MeteorHeight = arrayMeteors[maxFLA,0] |
|
3125 | MeteorHeight = arrayMeteors[maxFLA,0] | |
| 3007 |
|
3126 | |||
| 3008 | #Check neighborhood |
|
3127 | #Check neighborhood | |
| 3009 | maxHeightIndex = MeteorHeight + rangeLimit |
|
3128 | maxHeightIndex = MeteorHeight + rangeLimit | |
| 3010 | minHeightIndex = MeteorHeight - rangeLimit |
|
3129 | minHeightIndex = MeteorHeight - rangeLimit | |
| 3011 | minTimeIndex = MeteorInitTime - timeLimit |
|
3130 | minTimeIndex = MeteorInitTime - timeLimit | |
| 3012 | maxTimeIndex = MeteorEndTime + timeLimit |
|
3131 | maxTimeIndex = MeteorEndTime + timeLimit | |
| 3013 |
|
3132 | |||
| 3014 | #Check Heights |
|
3133 | #Check Heights | |
| 3015 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) |
|
3134 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) | |
| 3016 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) |
|
3135 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) | |
| 3017 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) |
|
3136 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) | |
| 3018 |
|
3137 | |||
| 3019 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) |
|
3138 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) | |
| 3020 |
|
3139 | |||
| 3021 | return listMeteors1 |
|
3140 | return listMeteors1 | |
| 3022 |
|
3141 | |||
| 3023 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): |
|
3142 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): | |
| 3024 | numHeights = volts.shape[2] |
|
3143 | numHeights = volts.shape[2] | |
| 3025 | nChannel = volts.shape[0] |
|
3144 | nChannel = volts.shape[0] | |
| 3026 |
|
3145 | |||
| 3027 | thresholdPhase = thresh[0] |
|
3146 | thresholdPhase = thresh[0] | |
| 3028 | thresholdNoise = thresh[1] |
|
3147 | thresholdNoise = thresh[1] | |
| 3029 | thresholdDB = float(thresh[2]) |
|
3148 | thresholdDB = float(thresh[2]) | |
| 3030 |
|
3149 | |||
| 3031 | thresholdDB1 = 10**(thresholdDB/10) |
|
3150 | thresholdDB1 = 10**(thresholdDB/10) | |
| 3032 | pairsarray = numpy.array(pairslist) |
|
3151 | pairsarray = numpy.array(pairslist) | |
| 3033 | indSides = pairsarray[:,1] |
|
3152 | indSides = pairsarray[:,1] | |
| 3034 |
|
3153 | |||
| 3035 | pairslist1 = list(pairslist) |
|
3154 | pairslist1 = list(pairslist) | |
| 3036 | pairslist1.append((0,1)) |
|
3155 | pairslist1.append((0,1)) | |
| 3037 | pairslist1.append((3,4)) |
|
3156 | pairslist1.append((3,4)) | |
| 3038 |
|
3157 | |||
| 3039 | listMeteors1 = [] |
|
3158 | listMeteors1 = [] | |
| 3040 | listPowerSeries = [] |
|
3159 | listPowerSeries = [] | |
| 3041 | listVoltageSeries = [] |
|
3160 | listVoltageSeries = [] | |
| 3042 | #volts has the war data |
|
3161 | #volts has the war data | |
| 3043 |
|
3162 | |||
| 3044 | if frequency == 30e6: |
|
3163 | if frequency == 30e6: | |
| 3045 | timeLag = 45*10**-3 |
|
3164 | timeLag = 45*10**-3 | |
| 3046 | else: |
|
3165 | else: | |
| 3047 | timeLag = 15*10**-3 |
|
3166 | timeLag = 15*10**-3 | |
| 3048 | lag = numpy.ceil(timeLag/timeInterval) |
|
3167 | lag = numpy.ceil(timeLag/timeInterval) | |
| 3049 |
|
3168 | |||
| 3050 | for i in range(len(listMeteors)): |
|
3169 | for i in range(len(listMeteors)): | |
| 3051 |
|
3170 | |||
| 3052 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### |
|
3171 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### | |
| 3053 | meteorAux = numpy.zeros(16) |
|
3172 | meteorAux = numpy.zeros(16) | |
| 3054 |
|
3173 | |||
| 3055 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) |
|
3174 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) | |
| 3056 | mHeight = listMeteors[i][0] |
|
3175 | mHeight = listMeteors[i][0] | |
| 3057 | mStart = listMeteors[i][1] |
|
3176 | mStart = listMeteors[i][1] | |
| 3058 | mPeak = listMeteors[i][2] |
|
3177 | mPeak = listMeteors[i][2] | |
| 3059 | mEnd = listMeteors[i][3] |
|
3178 | mEnd = listMeteors[i][3] | |
| 3060 |
|
3179 | |||
| 3061 | #get the volt data between the start and end times of the meteor |
|
3180 | #get the volt data between the start and end times of the meteor | |
| 3062 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] |
|
3181 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] | |
| 3063 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
3182 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |
| 3064 |
|
3183 | |||
| 3065 | #3.6. Phase Difference estimation |
|
3184 | #3.6. Phase Difference estimation | |
| 3066 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) |
|
3185 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) | |
| 3067 |
|
3186 | |||
| 3068 | #3.7. Phase difference removal & meteor start, peak and end times reestimated |
|
3187 | #3.7. Phase difference removal & meteor start, peak and end times reestimated | |
| 3069 | #meteorVolts0.- all Channels, all Profiles |
|
3188 | #meteorVolts0.- all Channels, all Profiles | |
| 3070 | meteorVolts0 = volts[:,:,mHeight] |
|
3189 | meteorVolts0 = volts[:,:,mHeight] | |
| 3071 | meteorThresh = noise[:,mHeight]*thresholdNoise |
|
3190 | meteorThresh = noise[:,mHeight]*thresholdNoise | |
| 3072 | meteorNoise = noise[:,mHeight] |
|
3191 | meteorNoise = noise[:,mHeight] | |
| 3073 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting |
|
3192 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting | |
| 3074 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power |
|
3193 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power | |
| 3075 |
|
3194 | |||
| 3076 | #Times reestimation |
|
3195 | #Times reestimation | |
| 3077 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] |
|
3196 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] | |
| 3078 | if mStart1.size > 0: |
|
3197 | if mStart1.size > 0: | |
| 3079 | mStart1 = mStart1[-1] + 1 |
|
3198 | mStart1 = mStart1[-1] + 1 | |
| 3080 |
|
3199 | |||
| 3081 | else: |
|
3200 | else: | |
| 3082 | mStart1 = mPeak |
|
3201 | mStart1 = mPeak | |
| 3083 |
|
3202 | |||
| 3084 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 |
|
3203 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 | |
| 3085 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] |
|
3204 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] | |
| 3086 | if mEndDecayTime1.size == 0: |
|
3205 | if mEndDecayTime1.size == 0: | |
| 3087 | mEndDecayTime1 = powerNet0.size |
|
3206 | mEndDecayTime1 = powerNet0.size | |
| 3088 | else: |
|
3207 | else: | |
| 3089 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 |
|
3208 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 | |
| 3090 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() |
|
3209 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() | |
| 3091 |
|
3210 | |||
| 3092 | #meteorVolts1.- all Channels, from start to end |
|
3211 | #meteorVolts1.- all Channels, from start to end | |
| 3093 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] |
|
3212 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] | |
| 3094 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] |
|
3213 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] | |
| 3095 | if meteorVolts2.shape[1] == 0: |
|
3214 | if meteorVolts2.shape[1] == 0: | |
| 3096 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] |
|
3215 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] | |
| 3097 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) |
|
3216 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) | |
| 3098 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) |
|
3217 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) | |
| 3099 | ##################### END PARAMETERS REESTIMATION ######################### |
|
3218 | ##################### END PARAMETERS REESTIMATION ######################### | |
| 3100 |
|
3219 | |||
| 3101 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## |
|
3220 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## | |
| 3102 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis |
|
3221 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis | |
| 3103 | if meteorVolts2.shape[1] > 0: |
|
3222 | if meteorVolts2.shape[1] > 0: | |
| 3104 | #Phase Difference re-estimation |
|
3223 | #Phase Difference re-estimation | |
| 3105 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation |
|
3224 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation | |
| 3106 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) |
|
3225 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) | |
| 3107 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) |
|
3226 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) | |
| 3108 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) |
|
3227 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) | |
| 3109 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting |
|
3228 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting | |
| 3110 |
|
3229 | |||
| 3111 | #Phase Difference RMS |
|
3230 | #Phase Difference RMS | |
| 3112 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) |
|
3231 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) | |
| 3113 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) |
|
3232 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) | |
| 3114 | #Data from Meteor |
|
3233 | #Data from Meteor | |
| 3115 | mPeak1 = powerNet1.argmax() + mStart1 |
|
3234 | mPeak1 = powerNet1.argmax() + mStart1 | |
| 3116 | mPeakPower1 = powerNet1.max() |
|
3235 | mPeakPower1 = powerNet1.max() | |
| 3117 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) |
|
3236 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) | |
| 3118 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux |
|
3237 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux | |
| 3119 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) |
|
3238 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) | |
| 3120 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) |
|
3239 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) | |
| 3121 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] |
|
3240 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] | |
| 3122 | #Vectorize |
|
3241 | #Vectorize | |
| 3123 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] |
|
3242 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] | |
| 3124 | meteorAux[7:11] = phaseDiffint[0:4] |
|
3243 | meteorAux[7:11] = phaseDiffint[0:4] | |
| 3125 |
|
3244 | |||
| 3126 | #Rejection Criterions |
|
3245 | #Rejection Criterions | |
| 3127 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation |
|
3246 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation | |
| 3128 | meteorAux[-1] = 17 |
|
3247 | meteorAux[-1] = 17 | |
| 3129 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB |
|
3248 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB | |
| 3130 | meteorAux[-1] = 1 |
|
3249 | meteorAux[-1] = 1 | |
| 3131 |
|
3250 | |||
| 3132 |
|
3251 | |||
| 3133 | else: |
|
3252 | else: | |
| 3134 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] |
|
3253 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] | |
| 3135 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis |
|
3254 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis | |
| 3136 | PowerSeries = 0 |
|
3255 | PowerSeries = 0 | |
| 3137 |
|
3256 | |||
| 3138 | listMeteors1.append(meteorAux) |
|
3257 | listMeteors1.append(meteorAux) | |
| 3139 | listPowerSeries.append(PowerSeries) |
|
3258 | listPowerSeries.append(PowerSeries) | |
| 3140 | listVoltageSeries.append(meteorVolts1) |
|
3259 | listVoltageSeries.append(meteorVolts1) | |
| 3141 |
|
3260 | |||
| 3142 | return listMeteors1, listPowerSeries, listVoltageSeries |
|
3261 | return listMeteors1, listPowerSeries, listVoltageSeries | |
| 3143 |
|
3262 | |||
| 3144 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): |
|
3263 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): | |
| 3145 |
|
3264 | |||
| 3146 | threshError = 10 |
|
3265 | threshError = 10 | |
| 3147 | #Depending if it is 30 or 50 MHz |
|
3266 | #Depending if it is 30 or 50 MHz | |
| 3148 | if frequency == 30e6: |
|
3267 | if frequency == 30e6: | |
| 3149 | timeLag = 45*10**-3 |
|
3268 | timeLag = 45*10**-3 | |
| 3150 | else: |
|
3269 | else: | |
| 3151 | timeLag = 15*10**-3 |
|
3270 | timeLag = 15*10**-3 | |
| 3152 | lag = numpy.ceil(timeLag/timeInterval) |
|
3271 | lag = numpy.ceil(timeLag/timeInterval) | |
| 3153 |
|
3272 | |||
| 3154 | listMeteors1 = [] |
|
3273 | listMeteors1 = [] | |
| 3155 |
|
3274 | |||
| 3156 | for i in range(len(listMeteors)): |
|
3275 | for i in range(len(listMeteors)): | |
| 3157 | meteorPower = listPower[i] |
|
3276 | meteorPower = listPower[i] | |
| 3158 | meteorAux = listMeteors[i] |
|
3277 | meteorAux = listMeteors[i] | |
| 3159 |
|
3278 | |||
| 3160 | if meteorAux[-1] == 0: |
|
3279 | if meteorAux[-1] == 0: | |
| 3161 |
|
3280 | |||
| 3162 | try: |
|
3281 | try: | |
| 3163 | indmax = meteorPower.argmax() |
|
3282 | indmax = meteorPower.argmax() | |
| 3164 | indlag = indmax + lag |
|
3283 | indlag = indmax + lag | |
| 3165 |
|
3284 | |||
| 3166 | y = meteorPower[indlag:] |
|
3285 | y = meteorPower[indlag:] | |
| 3167 | x = numpy.arange(0, y.size)*timeLag |
|
3286 | x = numpy.arange(0, y.size)*timeLag | |
| 3168 |
|
3287 | |||
| 3169 | #first guess |
|
3288 | #first guess | |
| 3170 | a = y[0] |
|
3289 | a = y[0] | |
| 3171 | tau = timeLag |
|
3290 | tau = timeLag | |
| 3172 | #exponential fit |
|
3291 | #exponential fit | |
| 3173 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) |
|
3292 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) | |
| 3174 | y1 = self.__exponential_function(x, *popt) |
|
3293 | y1 = self.__exponential_function(x, *popt) | |
| 3175 | #error estimation |
|
3294 | #error estimation | |
| 3176 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) |
|
3295 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) | |
| 3177 |
|
3296 | |||
| 3178 | decayTime = popt[1] |
|
3297 | decayTime = popt[1] | |
| 3179 | riseTime = indmax*timeInterval |
|
3298 | riseTime = indmax*timeInterval | |
| 3180 | meteorAux[11:13] = [decayTime, error] |
|
3299 | meteorAux[11:13] = [decayTime, error] | |
| 3181 |
|
3300 | |||
| 3182 | #Table items 7, 8 and 11 |
|
3301 | #Table items 7, 8 and 11 | |
| 3183 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s |
|
3302 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s | |
| 3184 | meteorAux[-1] = 7 |
|
3303 | meteorAux[-1] = 7 | |
| 3185 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time |
|
3304 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time | |
| 3186 | meteorAux[-1] = 8 |
|
3305 | meteorAux[-1] = 8 | |
| 3187 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time |
|
3306 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time | |
| 3188 | meteorAux[-1] = 11 |
|
3307 | meteorAux[-1] = 11 | |
| 3189 |
|
3308 | |||
| 3190 |
|
3309 | |||
| 3191 | except: |
|
3310 | except: | |
| 3192 | meteorAux[-1] = 11 |
|
3311 | meteorAux[-1] = 11 | |
| 3193 |
|
3312 | |||
| 3194 |
|
3313 | |||
| 3195 | listMeteors1.append(meteorAux) |
|
3314 | listMeteors1.append(meteorAux) | |
| 3196 |
|
3315 | |||
| 3197 | return listMeteors1 |
|
3316 | return listMeteors1 | |
| 3198 |
|
3317 | |||
| 3199 | #Exponential Function |
|
3318 | #Exponential Function | |
| 3200 |
|
3319 | |||
| 3201 | def __exponential_function(self, x, a, tau): |
|
3320 | def __exponential_function(self, x, a, tau): | |
| 3202 | y = a*numpy.exp(-x/tau) |
|
3321 | y = a*numpy.exp(-x/tau) | |
| 3203 | return y |
|
3322 | return y | |
| 3204 |
|
3323 | |||
| 3205 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): |
|
3324 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): | |
| 3206 |
|
3325 | |||
| 3207 | pairslist1 = list(pairslist) |
|
3326 | pairslist1 = list(pairslist) | |
| 3208 | pairslist1.append((0,1)) |
|
3327 | pairslist1.append((0,1)) | |
| 3209 | pairslist1.append((3,4)) |
|
3328 | pairslist1.append((3,4)) | |
| 3210 | numPairs = len(pairslist1) |
|
3329 | numPairs = len(pairslist1) | |
| 3211 | #Time Lag |
|
3330 | #Time Lag | |
| 3212 | timeLag = 45*10**-3 |
|
3331 | timeLag = 45*10**-3 | |
| 3213 | c = 3e8 |
|
3332 | c = 3e8 | |
| 3214 | lag = numpy.ceil(timeLag/timeInterval) |
|
3333 | lag = numpy.ceil(timeLag/timeInterval) | |
| 3215 | freq = 30e6 |
|
3334 | freq = 30e6 | |
| 3216 |
|
3335 | |||
| 3217 | listMeteors1 = [] |
|
3336 | listMeteors1 = [] | |
| 3218 |
|
3337 | |||
| 3219 | for i in range(len(listMeteors)): |
|
3338 | for i in range(len(listMeteors)): | |
| 3220 | meteorAux = listMeteors[i] |
|
3339 | meteorAux = listMeteors[i] | |
| 3221 | if meteorAux[-1] == 0: |
|
3340 | if meteorAux[-1] == 0: | |
| 3222 | mStart = listMeteors[i][1] |
|
3341 | mStart = listMeteors[i][1] | |
| 3223 | mPeak = listMeteors[i][2] |
|
3342 | mPeak = listMeteors[i][2] | |
| 3224 | mLag = mPeak - mStart + lag |
|
3343 | mLag = mPeak - mStart + lag | |
| 3225 |
|
3344 | |||
| 3226 | #get the volt data between the start and end times of the meteor |
|
3345 | #get the volt data between the start and end times of the meteor | |
| 3227 | meteorVolts = listVolts[i] |
|
3346 | meteorVolts = listVolts[i] | |
| 3228 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
3347 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |
| 3229 |
|
3348 | |||
| 3230 | #Get CCF |
|
3349 | #Get CCF | |
| 3231 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) |
|
3350 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) | |
| 3232 |
|
3351 | |||
| 3233 | #Method 2 |
|
3352 | #Method 2 | |
| 3234 | slopes = numpy.zeros(numPairs) |
|
3353 | slopes = numpy.zeros(numPairs) | |
| 3235 | time = numpy.array([-2,-1,1,2])*timeInterval |
|
3354 | time = numpy.array([-2,-1,1,2])*timeInterval | |
| 3236 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) |
|
3355 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) | |
| 3237 |
|
3356 | |||
| 3238 | #Correct phases |
|
3357 | #Correct phases | |
| 3239 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] |
|
3358 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] | |
| 3240 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
3359 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |
| 3241 |
|
3360 | |||
| 3242 | if indDer[0].shape[0] > 0: |
|
3361 | if indDer[0].shape[0] > 0: | |
| 3243 | for i in range(indDer[0].shape[0]): |
|
3362 | for i in range(indDer[0].shape[0]): | |
| 3244 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) |
|
3363 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) | |
| 3245 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi |
|
3364 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi | |
| 3246 |
|
3365 | |||
| 3247 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) |
|
3366 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) | |
| 3248 | for j in range(numPairs): |
|
3367 | for j in range(numPairs): | |
| 3249 | fit = stats.linregress(time, angAllCCF[j,:]) |
|
3368 | fit = stats.linregress(time, angAllCCF[j,:]) | |
| 3250 | slopes[j] = fit[0] |
|
3369 | slopes[j] = fit[0] | |
| 3251 |
|
3370 | |||
| 3252 | #Remove Outlier |
|
3371 | #Remove Outlier | |
| 3253 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
3372 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |
| 3254 | # slopes = numpy.delete(slopes,indOut) |
|
3373 | # slopes = numpy.delete(slopes,indOut) | |
| 3255 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
3374 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |
| 3256 | # slopes = numpy.delete(slopes,indOut) |
|
3375 | # slopes = numpy.delete(slopes,indOut) | |
| 3257 |
|
3376 | |||
| 3258 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) |
|
3377 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 3259 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) |
|
3378 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 3260 | meteorAux[-2] = radialError |
|
3379 | meteorAux[-2] = radialError | |
| 3261 | meteorAux[-3] = radialVelocity |
|
3380 | meteorAux[-3] = radialVelocity | |
| 3262 |
|
3381 | |||
| 3263 | #Setting Error |
|
3382 | #Setting Error | |
| 3264 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s |
|
3383 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s | |
| 3265 | if numpy.abs(radialVelocity) > 200: |
|
3384 | if numpy.abs(radialVelocity) > 200: | |
| 3266 | meteorAux[-1] = 15 |
|
3385 | meteorAux[-1] = 15 | |
| 3267 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity |
|
3386 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity | |
| 3268 | elif radialError > radialStdThresh: |
|
3387 | elif radialError > radialStdThresh: | |
| 3269 | meteorAux[-1] = 12 |
|
3388 | meteorAux[-1] = 12 | |
| 3270 |
|
3389 | |||
| 3271 | listMeteors1.append(meteorAux) |
|
3390 | listMeteors1.append(meteorAux) | |
| 3272 | return listMeteors1 |
|
3391 | return listMeteors1 | |
| 3273 |
|
3392 | |||
| 3274 | def __setNewArrays(self, listMeteors, date, heiRang): |
|
3393 | def __setNewArrays(self, listMeteors, date, heiRang): | |
| 3275 |
|
3394 | |||
| 3276 | #New arrays |
|
3395 | #New arrays | |
| 3277 | arrayMeteors = numpy.array(listMeteors) |
|
3396 | arrayMeteors = numpy.array(listMeteors) | |
| 3278 | arrayParameters = numpy.zeros((len(listMeteors), 13)) |
|
3397 | arrayParameters = numpy.zeros((len(listMeteors), 13)) | |
| 3279 |
|
3398 | |||
| 3280 | #Date inclusion |
|
3399 | #Date inclusion | |
| 3281 | # date = re.findall(r'\((.*?)\)', date) |
|
3400 | # date = re.findall(r'\((.*?)\)', date) | |
| 3282 | # date = date[0].split(',') |
|
3401 | # date = date[0].split(',') | |
| 3283 | # date = map(int, date) |
|
3402 | # date = map(int, date) | |
| 3284 | # |
|
3403 | # | |
| 3285 | # if len(date)<6: |
|
3404 | # if len(date)<6: | |
| 3286 | # date.append(0) |
|
3405 | # date.append(0) | |
| 3287 | # |
|
3406 | # | |
| 3288 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] |
|
3407 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] | |
| 3289 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) |
|
3408 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) | |
| 3290 | arrayDate = numpy.tile(date, (len(listMeteors))) |
|
3409 | arrayDate = numpy.tile(date, (len(listMeteors))) | |
| 3291 |
|
3410 | |||
| 3292 | #Meteor array |
|
3411 | #Meteor array | |
| 3293 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] |
|
3412 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] | |
| 3294 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) |
|
3413 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) | |
| 3295 |
|
3414 | |||
| 3296 | #Parameters Array |
|
3415 | #Parameters Array | |
| 3297 | arrayParameters[:,0] = arrayDate #Date |
|
3416 | arrayParameters[:,0] = arrayDate #Date | |
| 3298 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range |
|
3417 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range | |
| 3299 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error |
|
3418 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error | |
| 3300 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases |
|
3419 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases | |
| 3301 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error |
|
3420 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error | |
| 3302 |
|
3421 | |||
| 3303 |
|
3422 | |||
| 3304 | return arrayParameters |
|
3423 | return arrayParameters | |
| 3305 |
|
3424 | |||
| 3306 | class CorrectSMPhases(Operation): |
|
3425 | class CorrectSMPhases(Operation): | |
| 3307 |
|
3426 | |||
| 3308 | def run(self, dataOut, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45, channelPositions = None): |
|
3427 | def run(self, dataOut, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45, channelPositions = None): | |
| 3309 |
|
3428 | |||
| 3310 | arrayParameters = dataOut.data_param |
|
3429 | arrayParameters = dataOut.data_param | |
| 3311 | pairsList = [] |
|
3430 | pairsList = [] | |
| 3312 | pairx = (0,1) |
|
3431 | pairx = (0,1) | |
| 3313 | pairy = (2,3) |
|
3432 | pairy = (2,3) | |
| 3314 | pairsList.append(pairx) |
|
3433 | pairsList.append(pairx) | |
| 3315 | pairsList.append(pairy) |
|
3434 | pairsList.append(pairy) | |
| 3316 | jph = numpy.zeros(4) |
|
3435 | jph = numpy.zeros(4) | |
| 3317 |
|
3436 | |||
| 3318 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
3437 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |
| 3319 | # arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
3438 | # arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |
| 3320 | arrayParameters[:,8:12] = numpy.angle(numpy.exp(1j*(arrayParameters[:,8:12] + phaseOffsets))) |
|
3439 | arrayParameters[:,8:12] = numpy.angle(numpy.exp(1j*(arrayParameters[:,8:12] + phaseOffsets))) | |
| 3321 |
|
3440 | |||
| 3322 | meteorOps = SMOperations() |
|
3441 | meteorOps = SMOperations() | |
| 3323 | if channelPositions == None: |
|
3442 | if channelPositions == None: | |
| 3324 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
3443 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |
| 3325 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
3444 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |
| 3326 |
|
3445 | |||
| 3327 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
3446 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |
| 3328 | h = (hmin,hmax) |
|
3447 | h = (hmin,hmax) | |
| 3329 |
|
3448 | |||
| 3330 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) |
|
3449 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) | |
| 3331 |
|
3450 | |||
| 3332 | dataOut.data_param = arrayParameters |
|
3451 | dataOut.data_param = arrayParameters | |
| 3333 | return |
|
3452 | return | |
| 3334 |
|
3453 | |||
| 3335 | class SMPhaseCalibration(Operation): |
|
3454 | class SMPhaseCalibration(Operation): | |
| 3336 |
|
3455 | |||
| 3337 | __buffer = None |
|
3456 | __buffer = None | |
| 3338 |
|
3457 | |||
| 3339 | __initime = None |
|
3458 | __initime = None | |
| 3340 |
|
3459 | |||
| 3341 | __dataReady = False |
|
3460 | __dataReady = False | |
| 3342 |
|
3461 | |||
| 3343 | __isConfig = False |
|
3462 | __isConfig = False | |
| 3344 |
|
3463 | |||
| 3345 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): |
|
3464 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): | |
| 3346 |
|
3465 | |||
| 3347 | dataTime = currentTime + paramInterval |
|
3466 | dataTime = currentTime + paramInterval | |
| 3348 | deltaTime = dataTime - initTime |
|
3467 | deltaTime = dataTime - initTime | |
| 3349 |
|
3468 | |||
| 3350 | if deltaTime >= outputInterval or deltaTime < 0: |
|
3469 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 3351 | return True |
|
3470 | return True | |
| 3352 |
|
3471 | |||
| 3353 | return False |
|
3472 | return False | |
| 3354 |
|
3473 | |||
| 3355 | def __getGammas(self, pairs, d, phases): |
|
3474 | def __getGammas(self, pairs, d, phases): | |
| 3356 | gammas = numpy.zeros(2) |
|
3475 | gammas = numpy.zeros(2) | |
| 3357 |
|
3476 | |||
| 3358 | for i in range(len(pairs)): |
|
3477 | for i in range(len(pairs)): | |
| 3359 |
|
3478 | |||
| 3360 | pairi = pairs[i] |
|
3479 | pairi = pairs[i] | |
| 3361 |
|
3480 | |||
| 3362 | phip3 = phases[:,pairi[1]] |
|
3481 | phip3 = phases[:,pairi[1]] | |
| 3363 | d3 = d[pairi[1]] |
|
3482 | d3 = d[pairi[1]] | |
| 3364 | phip2 = phases[:,pairi[0]] |
|
3483 | phip2 = phases[:,pairi[0]] | |
| 3365 | d2 = d[pairi[0]] |
|
3484 | d2 = d[pairi[0]] | |
| 3366 | #Calculating gamma |
|
3485 | #Calculating gamma | |
| 3367 | # jdcos = alp1/(k*d1) |
|
3486 | # jdcos = alp1/(k*d1) | |
| 3368 | # jgamma = numpy.angle(numpy.exp(1j*(d0*alp1/d1 - alp0))) |
|
3487 | # jgamma = numpy.angle(numpy.exp(1j*(d0*alp1/d1 - alp0))) | |
| 3369 | jgamma = -phip2*d3/d2 - phip3 |
|
3488 | jgamma = -phip2*d3/d2 - phip3 | |
| 3370 | jgamma = numpy.angle(numpy.exp(1j*jgamma)) |
|
3489 | jgamma = numpy.angle(numpy.exp(1j*jgamma)) | |
| 3371 | # jgamma[jgamma>numpy.pi] -= 2*numpy.pi |
|
3490 | # jgamma[jgamma>numpy.pi] -= 2*numpy.pi | |
| 3372 | # jgamma[jgamma<-numpy.pi] += 2*numpy.pi |
|
3491 | # jgamma[jgamma<-numpy.pi] += 2*numpy.pi | |
| 3373 |
|
3492 | |||
| 3374 | #Revised distribution |
|
3493 | #Revised distribution | |
| 3375 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) |
|
3494 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) | |
| 3376 |
|
3495 | |||
| 3377 | #Histogram |
|
3496 | #Histogram | |
| 3378 | nBins = 64.0 |
|
3497 | nBins = 64.0 | |
| 3379 | rmin = -0.5*numpy.pi |
|
3498 | rmin = -0.5*numpy.pi | |
| 3380 | rmax = 0.5*numpy.pi |
|
3499 | rmax = 0.5*numpy.pi | |
| 3381 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) |
|
3500 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) | |
| 3382 |
|
3501 | |||
| 3383 | meteorsY = phaseHisto[0] |
|
3502 | meteorsY = phaseHisto[0] | |
| 3384 | phasesX = phaseHisto[1][:-1] |
|
3503 | phasesX = phaseHisto[1][:-1] | |
| 3385 | width = phasesX[1] - phasesX[0] |
|
3504 | width = phasesX[1] - phasesX[0] | |
| 3386 | phasesX += width/2 |
|
3505 | phasesX += width/2 | |
| 3387 |
|
3506 | |||
| 3388 | #Gaussian aproximation |
|
3507 | #Gaussian aproximation | |
| 3389 | bpeak = meteorsY.argmax() |
|
3508 | bpeak = meteorsY.argmax() | |
| 3390 | peak = meteorsY.max() |
|
3509 | peak = meteorsY.max() | |
| 3391 | jmin = bpeak - 5 |
|
3510 | jmin = bpeak - 5 | |
| 3392 | jmax = bpeak + 5 + 1 |
|
3511 | jmax = bpeak + 5 + 1 | |
| 3393 |
|
3512 | |||
| 3394 | if jmin<0: |
|
3513 | if jmin<0: | |
| 3395 | jmin = 0 |
|
3514 | jmin = 0 | |
| 3396 | jmax = 6 |
|
3515 | jmax = 6 | |
| 3397 | elif jmax > meteorsY.size: |
|
3516 | elif jmax > meteorsY.size: | |
| 3398 | jmin = meteorsY.size - 6 |
|
3517 | jmin = meteorsY.size - 6 | |
| 3399 | jmax = meteorsY.size |
|
3518 | jmax = meteorsY.size | |
| 3400 |
|
3519 | |||
| 3401 | x0 = numpy.array([peak,bpeak,50]) |
|
3520 | x0 = numpy.array([peak,bpeak,50]) | |
| 3402 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) |
|
3521 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) | |
| 3403 |
|
3522 | |||
| 3404 | #Gammas |
|
3523 | #Gammas | |
| 3405 | gammas[i] = coeff[0][1] |
|
3524 | gammas[i] = coeff[0][1] | |
| 3406 |
|
3525 | |||
| 3407 | return gammas |
|
3526 | return gammas | |
| 3408 |
|
3527 | |||
| 3409 | def __residualFunction(self, coeffs, y, t): |
|
3528 | def __residualFunction(self, coeffs, y, t): | |
| 3410 |
|
3529 | |||
| 3411 | return y - self.__gauss_function(t, coeffs) |
|
3530 | return y - self.__gauss_function(t, coeffs) | |
| 3412 |
|
3531 | |||
| 3413 | def __gauss_function(self, t, coeffs): |
|
3532 | def __gauss_function(self, t, coeffs): | |
| 3414 |
|
3533 | |||
| 3415 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) |
|
3534 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) | |
| 3416 |
|
3535 | |||
| 3417 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): |
|
3536 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): | |
| 3418 | meteorOps = SMOperations() |
|
3537 | meteorOps = SMOperations() | |
| 3419 | nchan = 4 |
|
3538 | nchan = 4 | |
| 3420 | pairx = pairsList[0] |
|
3539 | pairx = pairsList[0] | |
| 3421 | pairy = pairsList[1] |
|
3540 | pairy = pairsList[1] | |
| 3422 | center_xangle = 0 |
|
3541 | center_xangle = 0 | |
| 3423 | center_yangle = 0 |
|
3542 | center_yangle = 0 | |
| 3424 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) |
|
3543 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) | |
| 3425 | ntimes = len(range_angle) |
|
3544 | ntimes = len(range_angle) | |
| 3426 |
|
3545 | |||
| 3427 | nstepsx = 20.0 |
|
3546 | nstepsx = 20.0 | |
| 3428 | nstepsy = 20.0 |
|
3547 | nstepsy = 20.0 | |
| 3429 |
|
3548 | |||
| 3430 | for iz in range(ntimes): |
|
3549 | for iz in range(ntimes): | |
| 3431 | min_xangle = -range_angle[iz]/2 + center_xangle |
|
3550 | min_xangle = -range_angle[iz]/2 + center_xangle | |
| 3432 | max_xangle = range_angle[iz]/2 + center_xangle |
|
3551 | max_xangle = range_angle[iz]/2 + center_xangle | |
| 3433 | min_yangle = -range_angle[iz]/2 + center_yangle |
|
3552 | min_yangle = -range_angle[iz]/2 + center_yangle | |
| 3434 | max_yangle = range_angle[iz]/2 + center_yangle |
|
3553 | max_yangle = range_angle[iz]/2 + center_yangle | |
| 3435 |
|
3554 | |||
| 3436 | inc_x = (max_xangle-min_xangle)/nstepsx |
|
3555 | inc_x = (max_xangle-min_xangle)/nstepsx | |
| 3437 | inc_y = (max_yangle-min_yangle)/nstepsy |
|
3556 | inc_y = (max_yangle-min_yangle)/nstepsy | |
| 3438 |
|
3557 | |||
| 3439 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle |
|
3558 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle | |
| 3440 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle |
|
3559 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle | |
| 3441 | penalty = numpy.zeros((nstepsx,nstepsy)) |
|
3560 | penalty = numpy.zeros((nstepsx,nstepsy)) | |
| 3442 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) |
|
3561 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) | |
| 3443 | jph = numpy.zeros(nchan) |
|
3562 | jph = numpy.zeros(nchan) | |
| 3444 |
|
3563 | |||
| 3445 | # Iterations looking for the offset |
|
3564 | # Iterations looking for the offset | |
| 3446 | for iy in range(int(nstepsy)): |
|
3565 | for iy in range(int(nstepsy)): | |
| 3447 | for ix in range(int(nstepsx)): |
|
3566 | for ix in range(int(nstepsx)): | |
| 3448 | jph[pairy[1]] = alpha_y[iy] |
|
3567 | jph[pairy[1]] = alpha_y[iy] | |
| 3449 | jph[pairy[0]] = -gammas[1] - alpha_y[iy]*d[pairy[1]]/d[pairy[0]] |
|
3568 | jph[pairy[0]] = -gammas[1] - alpha_y[iy]*d[pairy[1]]/d[pairy[0]] | |
| 3450 |
|
3569 | |||
| 3451 | jph[pairx[1]] = alpha_x[ix] |
|
3570 | jph[pairx[1]] = alpha_x[ix] | |
| 3452 | jph[pairx[0]] = -gammas[0] - alpha_x[ix]*d[pairx[1]]/d[pairx[0]] |
|
3571 | jph[pairx[0]] = -gammas[0] - alpha_x[ix]*d[pairx[1]]/d[pairx[0]] | |
| 3453 |
|
3572 | |||
| 3454 | jph_array[:,ix,iy] = jph |
|
3573 | jph_array[:,ix,iy] = jph | |
| 3455 |
|
3574 | |||
| 3456 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, d, jph) |
|
3575 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, d, jph) | |
| 3457 | error = meteorsArray1[:,-1] |
|
3576 | error = meteorsArray1[:,-1] | |
| 3458 | ind1 = numpy.where(error==0)[0] |
|
3577 | ind1 = numpy.where(error==0)[0] | |
| 3459 | penalty[ix,iy] = ind1.size |
|
3578 | penalty[ix,iy] = ind1.size | |
| 3460 |
|
3579 | |||
| 3461 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) |
|
3580 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) | |
| 3462 | phOffset = jph_array[:,i,j] |
|
3581 | phOffset = jph_array[:,i,j] | |
| 3463 |
|
3582 | |||
| 3464 | center_xangle = phOffset[pairx[1]] |
|
3583 | center_xangle = phOffset[pairx[1]] | |
| 3465 | center_yangle = phOffset[pairy[1]] |
|
3584 | center_yangle = phOffset[pairy[1]] | |
| 3466 |
|
3585 | |||
| 3467 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) |
|
3586 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) | |
| 3468 | phOffset = phOffset*180/numpy.pi |
|
3587 | phOffset = phOffset*180/numpy.pi | |
| 3469 | return phOffset |
|
3588 | return phOffset | |
| 3470 |
|
3589 | |||
| 3471 |
|
3590 | |||
| 3472 | def run(self, dataOut, hmin, hmax, channelPositions=None, nHours = 1): |
|
3591 | def run(self, dataOut, hmin, hmax, channelPositions=None, nHours = 1): | |
| 3473 |
|
3592 | |||
| 3474 | dataOut.flagNoData = True |
|
3593 | dataOut.flagNoData = True | |
| 3475 | self.__dataReady = False |
|
3594 | self.__dataReady = False | |
| 3476 | dataOut.outputInterval = nHours*3600 |
|
3595 | dataOut.outputInterval = nHours*3600 | |
| 3477 |
|
3596 | |||
| 3478 | if self.__isConfig == False: |
|
3597 | if self.__isConfig == False: | |
| 3479 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
3598 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 3480 | #Get Initial LTC time |
|
3599 | #Get Initial LTC time | |
| 3481 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
3600 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 3482 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
3601 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 3483 |
|
3602 | |||
| 3484 | self.__isConfig = True |
|
3603 | self.__isConfig = True | |
| 3485 |
|
3604 | |||
| 3486 | if self.__buffer == None: |
|
3605 | if self.__buffer == None: | |
| 3487 | self.__buffer = dataOut.data_param.copy() |
|
3606 | self.__buffer = dataOut.data_param.copy() | |
| 3488 |
|
3607 | |||
| 3489 | else: |
|
3608 | else: | |
| 3490 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
3609 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 3491 |
|
3610 | |||
| 3492 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
3611 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 3493 |
|
3612 | |||
| 3494 | if self.__dataReady: |
|
3613 | if self.__dataReady: | |
| 3495 | dataOut.utctimeInit = self.__initime |
|
3614 | dataOut.utctimeInit = self.__initime | |
| 3496 | self.__initime += dataOut.outputInterval #to erase time offset |
|
3615 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 3497 |
|
3616 | |||
| 3498 | freq = dataOut.frequency |
|
3617 | freq = dataOut.frequency | |
| 3499 | c = dataOut.C #m/s |
|
3618 | c = dataOut.C #m/s | |
| 3500 | lamb = c/freq |
|
3619 | lamb = c/freq | |
| 3501 | k = 2*numpy.pi/lamb |
|
3620 | k = 2*numpy.pi/lamb | |
| 3502 | azimuth = 0 |
|
3621 | azimuth = 0 | |
| 3503 | h = (hmin, hmax) |
|
3622 | h = (hmin, hmax) | |
| 3504 | pairs = ((0,1),(2,3)) |
|
3623 | pairs = ((0,1),(2,3)) | |
| 3505 |
|
3624 | |||
| 3506 | if channelPositions == None: |
|
3625 | if channelPositions == None: | |
| 3507 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
3626 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |
| 3508 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
3627 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |
| 3509 | meteorOps = SMOperations() |
|
3628 | meteorOps = SMOperations() | |
| 3510 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
3629 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |
| 3511 |
|
3630 | |||
| 3512 | # distances1 = [-distances[0]*lamb, distances[1]*lamb, -distances[2]*lamb, distances[3]*lamb] |
|
3631 | # distances1 = [-distances[0]*lamb, distances[1]*lamb, -distances[2]*lamb, distances[3]*lamb] | |
| 3513 |
|
3632 | |||
| 3514 | meteorsArray = self.__buffer |
|
3633 | meteorsArray = self.__buffer | |
| 3515 | error = meteorsArray[:,-1] |
|
3634 | error = meteorsArray[:,-1] | |
| 3516 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) |
|
3635 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) | |
| 3517 | ind1 = numpy.where(boolError)[0] |
|
3636 | ind1 = numpy.where(boolError)[0] | |
| 3518 | meteorsArray = meteorsArray[ind1,:] |
|
3637 | meteorsArray = meteorsArray[ind1,:] | |
| 3519 | meteorsArray[:,-1] = 0 |
|
3638 | meteorsArray[:,-1] = 0 | |
| 3520 | phases = meteorsArray[:,8:12] |
|
3639 | phases = meteorsArray[:,8:12] | |
| 3521 |
|
3640 | |||
| 3522 | #Calculate Gammas |
|
3641 | #Calculate Gammas | |
| 3523 | gammas = self.__getGammas(pairs, distances, phases) |
|
3642 | gammas = self.__getGammas(pairs, distances, phases) | |
| 3524 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 |
|
3643 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 | |
| 3525 | #Calculate Phases |
|
3644 | #Calculate Phases | |
| 3526 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) |
|
3645 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) | |
| 3527 | phasesOff = phasesOff.reshape((1,phasesOff.size)) |
|
3646 | phasesOff = phasesOff.reshape((1,phasesOff.size)) | |
| 3528 | dataOut.data_output = -phasesOff |
|
3647 | dataOut.data_output = -phasesOff | |
| 3529 | dataOut.flagNoData = False |
|
3648 | dataOut.flagNoData = False | |
| 3530 | self.__buffer = None |
|
3649 | self.__buffer = None | |
| 3531 |
|
3650 | |||
| 3532 |
|
3651 | |||
| 3533 | return |
|
3652 | return | |
| 3534 |
|
3653 | |||
| 3535 | class SMOperations(): |
|
3654 | class SMOperations(): | |
| 3536 |
|
3655 | |||
| 3537 | def __init__(self): |
|
3656 | def __init__(self): | |
| 3538 |
|
3657 | |||
| 3539 | return |
|
3658 | return | |
| 3540 |
|
3659 | |||
| 3541 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, distances, jph): |
|
3660 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, distances, jph): | |
| 3542 |
|
3661 | |||
| 3543 | arrayParameters = arrayParameters0.copy() |
|
3662 | arrayParameters = arrayParameters0.copy() | |
| 3544 | hmin = h[0] |
|
3663 | hmin = h[0] | |
| 3545 | hmax = h[1] |
|
3664 | hmax = h[1] | |
| 3546 |
|
3665 | |||
| 3547 | #Calculate AOA (Error N 3, 4) |
|
3666 | #Calculate AOA (Error N 3, 4) | |
| 3548 | #JONES ET AL. 1998 |
|
3667 | #JONES ET AL. 1998 | |
| 3549 | AOAthresh = numpy.pi/8 |
|
3668 | AOAthresh = numpy.pi/8 | |
| 3550 | error = arrayParameters[:,-1] |
|
3669 | error = arrayParameters[:,-1] | |
| 3551 | phases = -arrayParameters[:,8:12] + jph |
|
3670 | phases = -arrayParameters[:,8:12] + jph | |
| 3552 | # phases = numpy.unwrap(phases) |
|
3671 | # phases = numpy.unwrap(phases) | |
| 3553 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, distances, error, AOAthresh, azimuth) |
|
3672 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, distances, error, AOAthresh, azimuth) | |
| 3554 |
|
3673 | |||
| 3555 | #Calculate Heights (Error N 13 and 14) |
|
3674 | #Calculate Heights (Error N 13 and 14) | |
| 3556 | error = arrayParameters[:,-1] |
|
3675 | error = arrayParameters[:,-1] | |
| 3557 | Ranges = arrayParameters[:,1] |
|
3676 | Ranges = arrayParameters[:,1] | |
| 3558 | zenith = arrayParameters[:,4] |
|
3677 | zenith = arrayParameters[:,4] | |
| 3559 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) |
|
3678 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) | |
| 3560 |
|
3679 | |||
| 3561 | #----------------------- Get Final data ------------------------------------ |
|
3680 | #----------------------- Get Final data ------------------------------------ | |
| 3562 | # error = arrayParameters[:,-1] |
|
3681 | # error = arrayParameters[:,-1] | |
| 3563 | # ind1 = numpy.where(error==0)[0] |
|
3682 | # ind1 = numpy.where(error==0)[0] | |
| 3564 | # arrayParameters = arrayParameters[ind1,:] |
|
3683 | # arrayParameters = arrayParameters[ind1,:] | |
| 3565 |
|
3684 | |||
| 3566 | return arrayParameters |
|
3685 | return arrayParameters | |
| 3567 |
|
3686 | |||
| 3568 | def __getAOA(self, phases, pairsList, directions, error, AOAthresh, azimuth): |
|
3687 | def __getAOA(self, phases, pairsList, directions, error, AOAthresh, azimuth): | |
| 3569 |
|
3688 | |||
| 3570 | arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
3689 | arrayAOA = numpy.zeros((phases.shape[0],3)) | |
| 3571 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList,directions) |
|
3690 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList,directions) | |
| 3572 |
|
3691 | |||
| 3573 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
3692 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |
| 3574 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
3693 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |
| 3575 | arrayAOA[:,2] = cosDirError |
|
3694 | arrayAOA[:,2] = cosDirError | |
| 3576 |
|
3695 | |||
| 3577 | azimuthAngle = arrayAOA[:,0] |
|
3696 | azimuthAngle = arrayAOA[:,0] | |
| 3578 | zenithAngle = arrayAOA[:,1] |
|
3697 | zenithAngle = arrayAOA[:,1] | |
| 3579 |
|
3698 | |||
| 3580 | #Setting Error |
|
3699 | #Setting Error | |
| 3581 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] |
|
3700 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] | |
| 3582 | error[indError] = 0 |
|
3701 | error[indError] = 0 | |
| 3583 | #Number 3: AOA not fesible |
|
3702 | #Number 3: AOA not fesible | |
| 3584 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
3703 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |
| 3585 | error[indInvalid] = 3 |
|
3704 | error[indInvalid] = 3 | |
| 3586 | #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
3705 | #Number 4: Large difference in AOAs obtained from different antenna baselines | |
| 3587 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
3706 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |
| 3588 | error[indInvalid] = 4 |
|
3707 | error[indInvalid] = 4 | |
| 3589 | return arrayAOA, error |
|
3708 | return arrayAOA, error | |
| 3590 |
|
3709 | |||
| 3591 | def __getDirectionCosines(self, arrayPhase, pairsList, distances): |
|
3710 | def __getDirectionCosines(self, arrayPhase, pairsList, distances): | |
| 3592 |
|
3711 | |||
| 3593 | #Initializing some variables |
|
3712 | #Initializing some variables | |
| 3594 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
3713 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |
| 3595 | ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
3714 | ang_aux = ang_aux.reshape(1,ang_aux.size) | |
| 3596 |
|
3715 | |||
| 3597 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
3716 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |
| 3598 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
3717 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |
| 3599 |
|
3718 | |||
| 3600 |
|
3719 | |||
| 3601 | for i in range(2): |
|
3720 | for i in range(2): | |
| 3602 | ph0 = arrayPhase[:,pairsList[i][0]] |
|
3721 | ph0 = arrayPhase[:,pairsList[i][0]] | |
| 3603 | ph1 = arrayPhase[:,pairsList[i][1]] |
|
3722 | ph1 = arrayPhase[:,pairsList[i][1]] | |
| 3604 | d0 = distances[pairsList[i][0]] |
|
3723 | d0 = distances[pairsList[i][0]] | |
| 3605 | d1 = distances[pairsList[i][1]] |
|
3724 | d1 = distances[pairsList[i][1]] | |
| 3606 |
|
3725 | |||
| 3607 | ph0_aux = ph0 + ph1 |
|
3726 | ph0_aux = ph0 + ph1 | |
| 3608 | ph0_aux = numpy.angle(numpy.exp(1j*ph0_aux)) |
|
3727 | ph0_aux = numpy.angle(numpy.exp(1j*ph0_aux)) | |
| 3609 | # ph0_aux[ph0_aux > numpy.pi] -= 2*numpy.pi |
|
3728 | # ph0_aux[ph0_aux > numpy.pi] -= 2*numpy.pi | |
| 3610 | # ph0_aux[ph0_aux < -numpy.pi] += 2*numpy.pi |
|
3729 | # ph0_aux[ph0_aux < -numpy.pi] += 2*numpy.pi | |
| 3611 | #First Estimation |
|
3730 | #First Estimation | |
| 3612 | cosdir0[:,i] = (ph0_aux)/(2*numpy.pi*(d0 - d1)) |
|
3731 | cosdir0[:,i] = (ph0_aux)/(2*numpy.pi*(d0 - d1)) | |
| 3613 |
|
3732 | |||
| 3614 | #Most-Accurate Second Estimation |
|
3733 | #Most-Accurate Second Estimation | |
| 3615 | phi1_aux = ph0 - ph1 |
|
3734 | phi1_aux = ph0 - ph1 | |
| 3616 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
3735 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |
| 3617 | #Direction Cosine 1 |
|
3736 | #Direction Cosine 1 | |
| 3618 | cosdir1 = (phi1_aux + ang_aux)/(2*numpy.pi*(d0 + d1)) |
|
3737 | cosdir1 = (phi1_aux + ang_aux)/(2*numpy.pi*(d0 + d1)) | |
| 3619 |
|
3738 | |||
| 3620 | #Searching the correct Direction Cosine |
|
3739 | #Searching the correct Direction Cosine | |
| 3621 | cosdir0_aux = cosdir0[:,i] |
|
3740 | cosdir0_aux = cosdir0[:,i] | |
| 3622 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
3741 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |
| 3623 | #Minimum Distance |
|
3742 | #Minimum Distance | |
| 3624 | cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
3743 | cosDiff = (cosdir1 - cosdir0_aux)**2 | |
| 3625 | indcos = cosDiff.argmin(axis = 1) |
|
3744 | indcos = cosDiff.argmin(axis = 1) | |
| 3626 | #Saving Value obtained |
|
3745 | #Saving Value obtained | |
| 3627 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
3746 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |
| 3628 |
|
3747 | |||
| 3629 | return cosdir0, cosdir |
|
3748 | return cosdir0, cosdir | |
| 3630 |
|
3749 | |||
| 3631 | def __calculateAOA(self, cosdir, azimuth): |
|
3750 | def __calculateAOA(self, cosdir, azimuth): | |
| 3632 | cosdirX = cosdir[:,0] |
|
3751 | cosdirX = cosdir[:,0] | |
| 3633 | cosdirY = cosdir[:,1] |
|
3752 | cosdirY = cosdir[:,1] | |
| 3634 |
|
3753 | |||
| 3635 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
3754 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |
| 3636 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth#0 deg north, 90 deg east |
|
3755 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth#0 deg north, 90 deg east | |
| 3637 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
3756 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |
| 3638 |
|
3757 | |||
| 3639 | return angles |
|
3758 | return angles | |
| 3640 |
|
3759 | |||
| 3641 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
3760 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |
| 3642 |
|
3761 | |||
| 3643 | Ramb = 375 #Ramb = c/(2*PRF) |
|
3762 | Ramb = 375 #Ramb = c/(2*PRF) | |
| 3644 | Re = 6371 #Earth Radius |
|
3763 | Re = 6371 #Earth Radius | |
| 3645 | heights = numpy.zeros(Ranges.shape) |
|
3764 | heights = numpy.zeros(Ranges.shape) | |
| 3646 |
|
3765 | |||
| 3647 | R_aux = numpy.array([0,1,2])*Ramb |
|
3766 | R_aux = numpy.array([0,1,2])*Ramb | |
| 3648 | R_aux = R_aux.reshape(1,R_aux.size) |
|
3767 | R_aux = R_aux.reshape(1,R_aux.size) | |
| 3649 |
|
3768 | |||
| 3650 | Ranges = Ranges.reshape(Ranges.size,1) |
|
3769 | Ranges = Ranges.reshape(Ranges.size,1) | |
| 3651 |
|
3770 | |||
| 3652 | Ri = Ranges + R_aux |
|
3771 | Ri = Ranges + R_aux | |
| 3653 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
3772 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |
| 3654 |
|
3773 | |||
| 3655 | #Check if there is a height between 70 and 110 km |
|
3774 | #Check if there is a height between 70 and 110 km | |
| 3656 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
3775 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |
| 3657 | ind_h = numpy.where(h_bool == 1)[0] |
|
3776 | ind_h = numpy.where(h_bool == 1)[0] | |
| 3658 |
|
3777 | |||
| 3659 | hCorr = hi[ind_h, :] |
|
3778 | hCorr = hi[ind_h, :] | |
| 3660 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
3779 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |
| 3661 |
|
3780 | |||
| 3662 | hCorr = hi[ind_hCorr] |
|
3781 | hCorr = hi[ind_hCorr] | |
| 3663 | heights[ind_h] = hCorr |
|
3782 | heights[ind_h] = hCorr | |
| 3664 |
|
3783 | |||
| 3665 | #Setting Error |
|
3784 | #Setting Error | |
| 3666 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
3785 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |
| 3667 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
3786 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |
| 3668 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] |
|
3787 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] | |
| 3669 | error[indError] = 0 |
|
3788 | error[indError] = 0 | |
| 3670 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
3789 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |
| 3671 | error[indInvalid2] = 14 |
|
3790 | error[indInvalid2] = 14 | |
| 3672 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
3791 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |
| 3673 | error[indInvalid1] = 13 |
|
3792 | error[indInvalid1] = 13 | |
| 3674 |
|
3793 | |||
| 3675 | return heights, error |
|
3794 | return heights, error | |
| 3676 |
|
3795 | |||
| 3677 | def getPhasePairs(self, channelPositions): |
|
3796 | def getPhasePairs(self, channelPositions): | |
| 3678 | chanPos = numpy.array(channelPositions) |
|
3797 | chanPos = numpy.array(channelPositions) | |
| 3679 | listOper = list(itertools.combinations(range(5),2)) |
|
3798 | listOper = list(itertools.combinations(range(5),2)) | |
| 3680 |
|
3799 | |||
| 3681 | distances = numpy.zeros(4) |
|
3800 | distances = numpy.zeros(4) | |
| 3682 | axisX = [] |
|
3801 | axisX = [] | |
| 3683 | axisY = [] |
|
3802 | axisY = [] | |
| 3684 | distX = numpy.zeros(3) |
|
3803 | distX = numpy.zeros(3) | |
| 3685 | distY = numpy.zeros(3) |
|
3804 | distY = numpy.zeros(3) | |
| 3686 | ix = 0 |
|
3805 | ix = 0 | |
| 3687 | iy = 0 |
|
3806 | iy = 0 | |
| 3688 |
|
3807 | |||
| 3689 | pairX = numpy.zeros((2,2)) |
|
3808 | pairX = numpy.zeros((2,2)) | |
| 3690 | pairY = numpy.zeros((2,2)) |
|
3809 | pairY = numpy.zeros((2,2)) | |
| 3691 |
|
3810 | |||
| 3692 | for i in range(len(listOper)): |
|
3811 | for i in range(len(listOper)): | |
| 3693 | pairi = listOper[i] |
|
3812 | pairi = listOper[i] | |
| 3694 |
|
3813 | |||
| 3695 | posDif = numpy.abs(chanPos[pairi[0],:] - chanPos[pairi[1],:]) |
|
3814 | posDif = numpy.abs(chanPos[pairi[0],:] - chanPos[pairi[1],:]) | |
| 3696 |
|
3815 | |||
| 3697 | if posDif[0] == 0: |
|
3816 | if posDif[0] == 0: | |
| 3698 | axisY.append(pairi) |
|
3817 | axisY.append(pairi) | |
| 3699 | distY[iy] = posDif[1] |
|
3818 | distY[iy] = posDif[1] | |
| 3700 | iy += 1 |
|
3819 | iy += 1 | |
| 3701 | elif posDif[1] == 0: |
|
3820 | elif posDif[1] == 0: | |
| 3702 | axisX.append(pairi) |
|
3821 | axisX.append(pairi) | |
| 3703 | distX[ix] = posDif[0] |
|
3822 | distX[ix] = posDif[0] | |
| 3704 | ix += 1 |
|
3823 | ix += 1 | |
| 3705 |
|
3824 | |||
| 3706 | for i in range(2): |
|
3825 | for i in range(2): | |
| 3707 | if i==0: |
|
3826 | if i==0: | |
| 3708 | dist0 = distX |
|
3827 | dist0 = distX | |
| 3709 | axis0 = axisX |
|
3828 | axis0 = axisX | |
| 3710 | else: |
|
3829 | else: | |
| 3711 | dist0 = distY |
|
3830 | dist0 = distY | |
| 3712 | axis0 = axisY |
|
3831 | axis0 = axisY | |
| 3713 |
|
3832 | |||
| 3714 | side = numpy.argsort(dist0)[:-1] |
|
3833 | side = numpy.argsort(dist0)[:-1] | |
| 3715 | axis0 = numpy.array(axis0)[side,:] |
|
3834 | axis0 = numpy.array(axis0)[side,:] | |
| 3716 | chanC = int(numpy.intersect1d(axis0[0,:], axis0[1,:])[0]) |
|
3835 | chanC = int(numpy.intersect1d(axis0[0,:], axis0[1,:])[0]) | |
| 3717 | axis1 = numpy.unique(numpy.reshape(axis0,4)) |
|
3836 | axis1 = numpy.unique(numpy.reshape(axis0,4)) | |
| 3718 | side = axis1[axis1 != chanC] |
|
3837 | side = axis1[axis1 != chanC] | |
| 3719 | diff1 = chanPos[chanC,i] - chanPos[side[0],i] |
|
3838 | diff1 = chanPos[chanC,i] - chanPos[side[0],i] | |
| 3720 | diff2 = chanPos[chanC,i] - chanPos[side[1],i] |
|
3839 | diff2 = chanPos[chanC,i] - chanPos[side[1],i] | |
| 3721 | if diff1<0: |
|
3840 | if diff1<0: | |
| 3722 | chan2 = side[0] |
|
3841 | chan2 = side[0] | |
| 3723 | d2 = numpy.abs(diff1) |
|
3842 | d2 = numpy.abs(diff1) | |
| 3724 | chan1 = side[1] |
|
3843 | chan1 = side[1] | |
| 3725 | d1 = numpy.abs(diff2) |
|
3844 | d1 = numpy.abs(diff2) | |
| 3726 | else: |
|
3845 | else: | |
| 3727 | chan2 = side[1] |
|
3846 | chan2 = side[1] | |
| 3728 | d2 = numpy.abs(diff2) |
|
3847 | d2 = numpy.abs(diff2) | |
| 3729 | chan1 = side[0] |
|
3848 | chan1 = side[0] | |
| 3730 | d1 = numpy.abs(diff1) |
|
3849 | d1 = numpy.abs(diff1) | |
| 3731 |
|
3850 | |||
| 3732 | if i==0: |
|
3851 | if i==0: | |
| 3733 | chanCX = chanC |
|
3852 | chanCX = chanC | |
| 3734 | chan1X = chan1 |
|
3853 | chan1X = chan1 | |
| 3735 | chan2X = chan2 |
|
3854 | chan2X = chan2 | |
| 3736 | distances[0:2] = numpy.array([d1,d2]) |
|
3855 | distances[0:2] = numpy.array([d1,d2]) | |
| 3737 | else: |
|
3856 | else: | |
| 3738 | chanCY = chanC |
|
3857 | chanCY = chanC | |
| 3739 | chan1Y = chan1 |
|
3858 | chan1Y = chan1 | |
| 3740 | chan2Y = chan2 |
|
3859 | chan2Y = chan2 | |
| 3741 | distances[2:4] = numpy.array([d1,d2]) |
|
3860 | distances[2:4] = numpy.array([d1,d2]) | |
| 3742 | # axisXsides = numpy.reshape(axisX[ix,:],4) |
|
3861 | # axisXsides = numpy.reshape(axisX[ix,:],4) | |
| 3743 | # |
|
3862 | # | |
| 3744 | # channelCentX = int(numpy.intersect1d(pairX[0,:], pairX[1,:])[0]) |
|
3863 | # channelCentX = int(numpy.intersect1d(pairX[0,:], pairX[1,:])[0]) | |
| 3745 | # channelCentY = int(numpy.intersect1d(pairY[0,:], pairY[1,:])[0]) |
|
3864 | # channelCentY = int(numpy.intersect1d(pairY[0,:], pairY[1,:])[0]) | |
| 3746 | # |
|
3865 | # | |
| 3747 | # ind25X = numpy.where(pairX[0,:] != channelCentX)[0][0] |
|
3866 | # ind25X = numpy.where(pairX[0,:] != channelCentX)[0][0] | |
| 3748 | # ind20X = numpy.where(pairX[1,:] != channelCentX)[0][0] |
|
3867 | # ind20X = numpy.where(pairX[1,:] != channelCentX)[0][0] | |
| 3749 | # channel25X = int(pairX[0,ind25X]) |
|
3868 | # channel25X = int(pairX[0,ind25X]) | |
| 3750 | # channel20X = int(pairX[1,ind20X]) |
|
3869 | # channel20X = int(pairX[1,ind20X]) | |
| 3751 | # ind25Y = numpy.where(pairY[0,:] != channelCentY)[0][0] |
|
3870 | # ind25Y = numpy.where(pairY[0,:] != channelCentY)[0][0] | |
| 3752 | # ind20Y = numpy.where(pairY[1,:] != channelCentY)[0][0] |
|
3871 | # ind20Y = numpy.where(pairY[1,:] != channelCentY)[0][0] | |
| 3753 | # channel25Y = int(pairY[0,ind25Y]) |
|
3872 | # channel25Y = int(pairY[0,ind25Y]) | |
| 3754 | # channel20Y = int(pairY[1,ind20Y]) |
|
3873 | # channel20Y = int(pairY[1,ind20Y]) | |
| 3755 |
|
3874 | |||
| 3756 | # pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] |
|
3875 | # pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] | |
| 3757 | pairslist = [(chanCX, chan1X),(chanCX, chan2X),(chanCY,chan1Y),(chanCY, chan2Y)] |
|
3876 | pairslist = [(chanCX, chan1X),(chanCX, chan2X),(chanCY,chan1Y),(chanCY, chan2Y)] | |
| 3758 |
|
3877 | |||
| 3759 | return pairslist, distances |
|
3878 | return pairslist, distances | |
| 3760 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): |
|
3879 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): | |
| 3761 | # |
|
3880 | # | |
| 3762 | # arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
3881 | # arrayAOA = numpy.zeros((phases.shape[0],3)) | |
| 3763 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) |
|
3882 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) | |
| 3764 | # |
|
3883 | # | |
| 3765 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
3884 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |
| 3766 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
3885 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |
| 3767 | # arrayAOA[:,2] = cosDirError |
|
3886 | # arrayAOA[:,2] = cosDirError | |
| 3768 | # |
|
3887 | # | |
| 3769 | # azimuthAngle = arrayAOA[:,0] |
|
3888 | # azimuthAngle = arrayAOA[:,0] | |
| 3770 | # zenithAngle = arrayAOA[:,1] |
|
3889 | # zenithAngle = arrayAOA[:,1] | |
| 3771 | # |
|
3890 | # | |
| 3772 | # #Setting Error |
|
3891 | # #Setting Error | |
| 3773 | # #Number 3: AOA not fesible |
|
3892 | # #Number 3: AOA not fesible | |
| 3774 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
3893 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |
| 3775 | # error[indInvalid] = 3 |
|
3894 | # error[indInvalid] = 3 | |
| 3776 | # #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
3895 | # #Number 4: Large difference in AOAs obtained from different antenna baselines | |
| 3777 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
3896 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |
| 3778 | # error[indInvalid] = 4 |
|
3897 | # error[indInvalid] = 4 | |
| 3779 | # return arrayAOA, error |
|
3898 | # return arrayAOA, error | |
| 3780 | # |
|
3899 | # | |
| 3781 | # def __getDirectionCosines(self, arrayPhase, pairsList): |
|
3900 | # def __getDirectionCosines(self, arrayPhase, pairsList): | |
| 3782 | # |
|
3901 | # | |
| 3783 | # #Initializing some variables |
|
3902 | # #Initializing some variables | |
| 3784 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
3903 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |
| 3785 | # ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
3904 | # ang_aux = ang_aux.reshape(1,ang_aux.size) | |
| 3786 | # |
|
3905 | # | |
| 3787 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
3906 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |
| 3788 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
3907 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |
| 3789 | # |
|
3908 | # | |
| 3790 | # |
|
3909 | # | |
| 3791 | # for i in range(2): |
|
3910 | # for i in range(2): | |
| 3792 | # #First Estimation |
|
3911 | # #First Estimation | |
| 3793 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] |
|
3912 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] | |
| 3794 | # #Dealias |
|
3913 | # #Dealias | |
| 3795 | # indcsi = numpy.where(phi0_aux > numpy.pi) |
|
3914 | # indcsi = numpy.where(phi0_aux > numpy.pi) | |
| 3796 | # phi0_aux[indcsi] -= 2*numpy.pi |
|
3915 | # phi0_aux[indcsi] -= 2*numpy.pi | |
| 3797 | # indcsi = numpy.where(phi0_aux < -numpy.pi) |
|
3916 | # indcsi = numpy.where(phi0_aux < -numpy.pi) | |
| 3798 | # phi0_aux[indcsi] += 2*numpy.pi |
|
3917 | # phi0_aux[indcsi] += 2*numpy.pi | |
| 3799 | # #Direction Cosine 0 |
|
3918 | # #Direction Cosine 0 | |
| 3800 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) |
|
3919 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) | |
| 3801 | # |
|
3920 | # | |
| 3802 | # #Most-Accurate Second Estimation |
|
3921 | # #Most-Accurate Second Estimation | |
| 3803 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] |
|
3922 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] | |
| 3804 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
3923 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |
| 3805 | # #Direction Cosine 1 |
|
3924 | # #Direction Cosine 1 | |
| 3806 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) |
|
3925 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) | |
| 3807 | # |
|
3926 | # | |
| 3808 | # #Searching the correct Direction Cosine |
|
3927 | # #Searching the correct Direction Cosine | |
| 3809 | # cosdir0_aux = cosdir0[:,i] |
|
3928 | # cosdir0_aux = cosdir0[:,i] | |
| 3810 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
3929 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |
| 3811 | # #Minimum Distance |
|
3930 | # #Minimum Distance | |
| 3812 | # cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
3931 | # cosDiff = (cosdir1 - cosdir0_aux)**2 | |
| 3813 | # indcos = cosDiff.argmin(axis = 1) |
|
3932 | # indcos = cosDiff.argmin(axis = 1) | |
| 3814 | # #Saving Value obtained |
|
3933 | # #Saving Value obtained | |
| 3815 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
3934 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |
| 3816 | # |
|
3935 | # | |
| 3817 | # return cosdir0, cosdir |
|
3936 | # return cosdir0, cosdir | |
| 3818 | # |
|
3937 | # | |
| 3819 | # def __calculateAOA(self, cosdir, azimuth): |
|
3938 | # def __calculateAOA(self, cosdir, azimuth): | |
| 3820 | # cosdirX = cosdir[:,0] |
|
3939 | # cosdirX = cosdir[:,0] | |
| 3821 | # cosdirY = cosdir[:,1] |
|
3940 | # cosdirY = cosdir[:,1] | |
| 3822 | # |
|
3941 | # | |
| 3823 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
3942 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |
| 3824 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east |
|
3943 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east | |
| 3825 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
3944 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |
| 3826 | # |
|
3945 | # | |
| 3827 | # return angles |
|
3946 | # return angles | |
| 3828 | # |
|
3947 | # | |
| 3829 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
3948 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |
| 3830 | # |
|
3949 | # | |
| 3831 | # Ramb = 375 #Ramb = c/(2*PRF) |
|
3950 | # Ramb = 375 #Ramb = c/(2*PRF) | |
| 3832 | # Re = 6371 #Earth Radius |
|
3951 | # Re = 6371 #Earth Radius | |
| 3833 | # heights = numpy.zeros(Ranges.shape) |
|
3952 | # heights = numpy.zeros(Ranges.shape) | |
| 3834 | # |
|
3953 | # | |
| 3835 | # R_aux = numpy.array([0,1,2])*Ramb |
|
3954 | # R_aux = numpy.array([0,1,2])*Ramb | |
| 3836 | # R_aux = R_aux.reshape(1,R_aux.size) |
|
3955 | # R_aux = R_aux.reshape(1,R_aux.size) | |
| 3837 | # |
|
3956 | # | |
| 3838 | # Ranges = Ranges.reshape(Ranges.size,1) |
|
3957 | # Ranges = Ranges.reshape(Ranges.size,1) | |
| 3839 | # |
|
3958 | # | |
| 3840 | # Ri = Ranges + R_aux |
|
3959 | # Ri = Ranges + R_aux | |
| 3841 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
3960 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |
| 3842 | # |
|
3961 | # | |
| 3843 | # #Check if there is a height between 70 and 110 km |
|
3962 | # #Check if there is a height between 70 and 110 km | |
| 3844 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
3963 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |
| 3845 | # ind_h = numpy.where(h_bool == 1)[0] |
|
3964 | # ind_h = numpy.where(h_bool == 1)[0] | |
| 3846 | # |
|
3965 | # | |
| 3847 | # hCorr = hi[ind_h, :] |
|
3966 | # hCorr = hi[ind_h, :] | |
| 3848 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
3967 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |
| 3849 | # |
|
3968 | # | |
| 3850 | # hCorr = hi[ind_hCorr] |
|
3969 | # hCorr = hi[ind_hCorr] | |
| 3851 | # heights[ind_h] = hCorr |
|
3970 | # heights[ind_h] = hCorr | |
| 3852 | # |
|
3971 | # | |
| 3853 | # #Setting Error |
|
3972 | # #Setting Error | |
| 3854 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
3973 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |
| 3855 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
3974 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |
| 3856 | # |
|
3975 | # | |
| 3857 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
3976 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |
| 3858 | # error[indInvalid2] = 14 |
|
3977 | # error[indInvalid2] = 14 | |
| 3859 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
3978 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |
| 3860 | # error[indInvalid1] = 13 |
|
3979 | # error[indInvalid1] = 13 | |
| 3861 | # |
|
3980 | # | |
| 3862 | # return heights, error |
|
3981 | # return heights, error | |
| 3863 | No newline at end of file |
|
3982 | ||
| @@ -1,1068 +1,1067 | |||||
| 1 | import numpy |
|
1 | import numpy | |
| 2 |
|
2 | |||
| 3 | from jroproc_base import ProcessingUnit, Operation |
|
3 | from jroproc_base import ProcessingUnit, Operation | |
| 4 | from schainpy.model.data.jrodata import Spectra |
|
4 | from schainpy.model.data.jrodata import Spectra | |
| 5 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
5 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 6 |
|
6 | |||
| 7 | import matplotlib.pyplot as plt |
|
7 | import matplotlib.pyplot as plt | |
| 8 |
|
8 | |||
| 9 | class SpectraProc(ProcessingUnit): |
|
9 | class SpectraProc(ProcessingUnit): | |
| 10 |
|
10 | |||
| 11 | def __init__(self, **kwargs): |
|
11 | def __init__(self, **kwargs): | |
| 12 |
|
12 | |||
| 13 | ProcessingUnit.__init__(self, **kwargs) |
|
13 | ProcessingUnit.__init__(self, **kwargs) | |
| 14 |
|
14 | |||
| 15 | self.buffer = None |
|
15 | self.buffer = None | |
| 16 | self.firstdatatime = None |
|
16 | self.firstdatatime = None | |
| 17 | self.profIndex = 0 |
|
17 | self.profIndex = 0 | |
| 18 | self.dataOut = Spectra() |
|
18 | self.dataOut = Spectra() | |
| 19 | self.id_min = None |
|
19 | self.id_min = None | |
| 20 | self.id_max = None |
|
20 | self.id_max = None | |
| 21 |
|
21 | |||
| 22 | def __updateSpecFromVoltage(self): |
|
22 | def __updateSpecFromVoltage(self): | |
| 23 |
|
23 | |||
| 24 | self.dataOut.timeZone = self.dataIn.timeZone |
|
24 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 25 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
25 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 26 | self.dataOut.errorCount = self.dataIn.errorCount |
|
26 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 27 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
27 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 28 |
|
28 | |||
| 29 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
29 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 30 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
30 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 31 | self.dataOut.channelList = self.dataIn.channelList |
|
31 | self.dataOut.channelList = self.dataIn.channelList | |
| 32 | self.dataOut.heightList = self.dataIn.heightList |
|
32 | self.dataOut.heightList = self.dataIn.heightList | |
| 33 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
33 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 34 |
|
34 | |||
| 35 | self.dataOut.nBaud = self.dataIn.nBaud |
|
35 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 36 | self.dataOut.nCode = self.dataIn.nCode |
|
36 | self.dataOut.nCode = self.dataIn.nCode | |
| 37 | self.dataOut.code = self.dataIn.code |
|
37 | self.dataOut.code = self.dataIn.code | |
| 38 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
38 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 39 |
|
39 | |||
| 40 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
40 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 41 | self.dataOut.utctime = self.firstdatatime |
|
41 | self.dataOut.utctime = self.firstdatatime | |
| 42 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
42 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |
| 43 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
43 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |
| 44 | self.dataOut.flagShiftFFT = False |
|
44 | self.dataOut.flagShiftFFT = False | |
| 45 |
|
45 | |||
| 46 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
46 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 47 | self.dataOut.nIncohInt = 1 |
|
47 | self.dataOut.nIncohInt = 1 | |
| 48 |
|
48 | |||
| 49 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
49 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 50 |
|
50 | |||
| 51 | self.dataOut.frequency = self.dataIn.frequency |
|
51 | self.dataOut.frequency = self.dataIn.frequency | |
| 52 | self.dataOut.realtime = self.dataIn.realtime |
|
52 | self.dataOut.realtime = self.dataIn.realtime | |
| 53 |
|
53 | |||
| 54 | self.dataOut.azimuth = self.dataIn.azimuth |
|
54 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 55 | self.dataOut.zenith = self.dataIn.zenith |
|
55 | self.dataOut.zenith = self.dataIn.zenith | |
| 56 |
|
56 | |||
| 57 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
57 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 58 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
58 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 59 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
59 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 60 |
|
60 | |||
| 61 | def __getFft(self): |
|
61 | def __getFft(self): | |
| 62 | """ |
|
62 | """ | |
| 63 | Convierte valores de Voltaje a Spectra |
|
63 | Convierte valores de Voltaje a Spectra | |
| 64 |
|
64 | |||
| 65 | Affected: |
|
65 | Affected: | |
| 66 | self.dataOut.data_spc |
|
66 | self.dataOut.data_spc | |
| 67 | self.dataOut.data_cspc |
|
67 | self.dataOut.data_cspc | |
| 68 | self.dataOut.data_dc |
|
68 | self.dataOut.data_dc | |
| 69 | self.dataOut.heightList |
|
69 | self.dataOut.heightList | |
| 70 | self.profIndex |
|
70 | self.profIndex | |
| 71 | self.buffer |
|
71 | self.buffer | |
| 72 | self.dataOut.flagNoData |
|
72 | self.dataOut.flagNoData | |
| 73 | """ |
|
73 | """ | |
| 74 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) |
|
74 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) | |
| 75 |
|
75 | |||
| 76 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
76 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 77 | dc = fft_volt[:,0,:] |
|
77 | dc = fft_volt[:,0,:] | |
| 78 |
|
78 | |||
| 79 | #calculo de self-spectra |
|
79 | #calculo de self-spectra | |
| 80 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) |
|
80 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) | |
| 81 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
81 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 82 | spc = spc.real |
|
82 | spc = spc.real | |
| 83 |
|
83 | |||
| 84 | blocksize = 0 |
|
84 | blocksize = 0 | |
| 85 | blocksize += dc.size |
|
85 | blocksize += dc.size | |
| 86 | blocksize += spc.size |
|
86 | blocksize += spc.size | |
| 87 |
|
87 | |||
| 88 | cspc = None |
|
88 | cspc = None | |
| 89 | pairIndex = 0 |
|
89 | pairIndex = 0 | |
| 90 | if self.dataOut.pairsList != None: |
|
90 | if self.dataOut.pairsList != None: | |
| 91 | #calculo de cross-spectra |
|
91 | #calculo de cross-spectra | |
| 92 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
92 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 93 | for pair in self.dataOut.pairsList: |
|
93 | for pair in self.dataOut.pairsList: | |
| 94 | if pair[0] not in self.dataOut.channelList: |
|
94 | if pair[0] not in self.dataOut.channelList: | |
| 95 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
95 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 96 | if pair[1] not in self.dataOut.channelList: |
|
96 | if pair[1] not in self.dataOut.channelList: | |
| 97 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
97 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 98 |
|
98 | |||
| 99 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) |
|
99 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) | |
| 100 | pairIndex += 1 |
|
100 | pairIndex += 1 | |
| 101 | blocksize += cspc.size |
|
101 | blocksize += cspc.size | |
| 102 |
|
102 | |||
| 103 | self.dataOut.data_spc = spc |
|
103 | self.dataOut.data_spc = spc | |
| 104 | self.dataOut.data_cspc = cspc |
|
104 | self.dataOut.data_cspc = cspc | |
| 105 | self.dataOut.data_dc = dc |
|
105 | self.dataOut.data_dc = dc | |
| 106 | self.dataOut.blockSize = blocksize |
|
106 | self.dataOut.blockSize = blocksize | |
| 107 | self.dataOut.flagShiftFFT = True |
|
107 | self.dataOut.flagShiftFFT = True | |
| 108 |
|
108 | |||
| 109 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): |
|
109 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): | |
| 110 |
|
110 | |||
| 111 | self.dataOut.flagNoData = True |
|
111 | self.dataOut.flagNoData = True | |
| 112 |
|
112 | |||
| 113 | if self.dataIn.type == "Spectra": |
|
113 | if self.dataIn.type == "Spectra": | |
| 114 | self.dataOut.copy(self.dataIn) |
|
114 | self.dataOut.copy(self.dataIn) | |
| 115 | # self.__selectPairs(pairsList) |
|
115 | # self.__selectPairs(pairsList) | |
| 116 | return True |
|
116 | return True | |
| 117 |
|
117 | |||
| 118 | if self.dataIn.type == "Voltage": |
|
118 | if self.dataIn.type == "Voltage": | |
| 119 |
|
119 | |||
| 120 | if nFFTPoints == None: |
|
120 | if nFFTPoints == None: | |
| 121 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" |
|
121 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" | |
| 122 |
|
122 | |||
| 123 | if nProfiles == None: |
|
123 | if nProfiles == None: | |
| 124 | nProfiles = nFFTPoints |
|
124 | nProfiles = nFFTPoints | |
| 125 |
|
125 | |||
| 126 | if ippFactor == None: |
|
126 | if ippFactor == None: | |
| 127 | ippFactor = 1 |
|
127 | ippFactor = 1 | |
| 128 |
|
128 | |||
| 129 | self.dataOut.ippFactor = ippFactor |
|
129 | self.dataOut.ippFactor = ippFactor | |
| 130 |
|
130 | |||
| 131 | self.dataOut.nFFTPoints = nFFTPoints |
|
131 | self.dataOut.nFFTPoints = nFFTPoints | |
| 132 | self.dataOut.pairsList = pairsList |
|
132 | self.dataOut.pairsList = pairsList | |
| 133 |
|
133 | |||
| 134 | if self.buffer is None: |
|
134 | if self.buffer is None: | |
| 135 | self.buffer = numpy.zeros( (self.dataIn.nChannels, |
|
135 | self.buffer = numpy.zeros( (self.dataIn.nChannels, | |
| 136 | nProfiles, |
|
136 | nProfiles, | |
| 137 | self.dataIn.nHeights), |
|
137 | self.dataIn.nHeights), | |
| 138 | dtype='complex') |
|
138 | dtype='complex') | |
| 139 |
|
139 | |||
| 140 | if self.dataIn.flagDataAsBlock: |
|
140 | if self.dataIn.flagDataAsBlock: | |
| 141 | #data dimension: [nChannels, nProfiles, nSamples] |
|
141 | #data dimension: [nChannels, nProfiles, nSamples] | |
| 142 |
|
142 | |||
| 143 | nVoltProfiles = self.dataIn.data.shape[1] |
|
143 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 144 | # nVoltProfiles = self.dataIn.nProfiles |
|
144 | # nVoltProfiles = self.dataIn.nProfiles | |
| 145 |
|
145 | |||
| 146 | if nVoltProfiles == nProfiles: |
|
146 | if nVoltProfiles == nProfiles: | |
| 147 | self.buffer = self.dataIn.data.copy() |
|
147 | self.buffer = self.dataIn.data.copy() | |
| 148 | self.profIndex = nVoltProfiles |
|
148 | self.profIndex = nVoltProfiles | |
| 149 |
|
149 | |||
| 150 | elif nVoltProfiles < nProfiles: |
|
150 | elif nVoltProfiles < nProfiles: | |
| 151 |
|
151 | |||
| 152 | if self.profIndex == 0: |
|
152 | if self.profIndex == 0: | |
| 153 | self.id_min = 0 |
|
153 | self.id_min = 0 | |
| 154 | self.id_max = nVoltProfiles |
|
154 | self.id_max = nVoltProfiles | |
| 155 |
|
155 | |||
| 156 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data |
|
156 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data | |
| 157 | self.profIndex += nVoltProfiles |
|
157 | self.profIndex += nVoltProfiles | |
| 158 | self.id_min += nVoltProfiles |
|
158 | self.id_min += nVoltProfiles | |
| 159 | self.id_max += nVoltProfiles |
|
159 | self.id_max += nVoltProfiles | |
| 160 | else: |
|
160 | else: | |
| 161 | raise ValueError, "The type object %s has %d profiles, it should just has %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) |
|
161 | raise ValueError, "The type object %s has %d profiles, it should just has %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) | |
| 162 | self.dataOut.flagNoData = True |
|
162 | self.dataOut.flagNoData = True | |
| 163 | return 0 |
|
163 | return 0 | |
| 164 | else: |
|
164 | else: | |
| 165 | print 'DATA shape', self.dataIn.data.shape |
|
165 | ||
| 166 | sadsdf |
|
|||
| 167 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() |
|
166 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() | |
| 168 | self.profIndex += 1 |
|
167 | self.profIndex += 1 | |
| 169 |
|
168 | |||
| 170 | if self.firstdatatime == None: |
|
169 | if self.firstdatatime == None: | |
| 171 | self.firstdatatime = self.dataIn.utctime |
|
170 | self.firstdatatime = self.dataIn.utctime | |
| 172 |
|
171 | |||
| 173 | if self.profIndex == nProfiles: |
|
172 | if self.profIndex == nProfiles: | |
| 174 | self.__updateSpecFromVoltage() |
|
173 | self.__updateSpecFromVoltage() | |
| 175 | self.__getFft() |
|
174 | self.__getFft() | |
| 176 |
|
175 | |||
| 177 | self.dataOut.flagNoData = False |
|
176 | self.dataOut.flagNoData = False | |
| 178 | self.firstdatatime = None |
|
177 | self.firstdatatime = None | |
| 179 | self.profIndex = 0 |
|
178 | self.profIndex = 0 | |
| 180 |
|
179 | |||
| 181 | return True |
|
180 | return True | |
| 182 |
|
181 | |||
| 183 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) |
|
182 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) | |
| 184 |
|
183 | |||
| 185 | def __selectPairs(self, pairsList): |
|
184 | def __selectPairs(self, pairsList): | |
| 186 |
|
185 | |||
| 187 | if channelList == None: |
|
186 | if channelList == None: | |
| 188 | return |
|
187 | return | |
| 189 |
|
188 | |||
| 190 | pairsIndexListSelected = [] |
|
189 | pairsIndexListSelected = [] | |
| 191 |
|
190 | |||
| 192 | for thisPair in pairsList: |
|
191 | for thisPair in pairsList: | |
| 193 |
|
192 | |||
| 194 | if thisPair not in self.dataOut.pairsList: |
|
193 | if thisPair not in self.dataOut.pairsList: | |
| 195 | continue |
|
194 | continue | |
| 196 |
|
195 | |||
| 197 | pairIndex = self.dataOut.pairsList.index(thisPair) |
|
196 | pairIndex = self.dataOut.pairsList.index(thisPair) | |
| 198 |
|
197 | |||
| 199 | pairsIndexListSelected.append(pairIndex) |
|
198 | pairsIndexListSelected.append(pairIndex) | |
| 200 |
|
199 | |||
| 201 | if not pairsIndexListSelected: |
|
200 | if not pairsIndexListSelected: | |
| 202 | self.dataOut.data_cspc = None |
|
201 | self.dataOut.data_cspc = None | |
| 203 | self.dataOut.pairsList = [] |
|
202 | self.dataOut.pairsList = [] | |
| 204 | return |
|
203 | return | |
| 205 |
|
204 | |||
| 206 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
205 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 207 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
206 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 208 |
|
207 | |||
| 209 | return |
|
208 | return | |
| 210 |
|
209 | |||
| 211 | def __selectPairsByChannel(self, channelList=None): |
|
210 | def __selectPairsByChannel(self, channelList=None): | |
| 212 |
|
211 | |||
| 213 | if channelList == None: |
|
212 | if channelList == None: | |
| 214 | return |
|
213 | return | |
| 215 |
|
214 | |||
| 216 | pairsIndexListSelected = [] |
|
215 | pairsIndexListSelected = [] | |
| 217 | for pairIndex in self.dataOut.pairsIndexList: |
|
216 | for pairIndex in self.dataOut.pairsIndexList: | |
| 218 | #First pair |
|
217 | #First pair | |
| 219 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
218 | if self.dataOut.pairsList[pairIndex][0] not in channelList: | |
| 220 | continue |
|
219 | continue | |
| 221 | #Second pair |
|
220 | #Second pair | |
| 222 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
221 | if self.dataOut.pairsList[pairIndex][1] not in channelList: | |
| 223 | continue |
|
222 | continue | |
| 224 |
|
223 | |||
| 225 | pairsIndexListSelected.append(pairIndex) |
|
224 | pairsIndexListSelected.append(pairIndex) | |
| 226 |
|
225 | |||
| 227 | if not pairsIndexListSelected: |
|
226 | if not pairsIndexListSelected: | |
| 228 | self.dataOut.data_cspc = None |
|
227 | self.dataOut.data_cspc = None | |
| 229 | self.dataOut.pairsList = [] |
|
228 | self.dataOut.pairsList = [] | |
| 230 | return |
|
229 | return | |
| 231 |
|
230 | |||
| 232 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
231 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 233 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
232 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 234 |
|
233 | |||
| 235 | return |
|
234 | return | |
| 236 |
|
235 | |||
| 237 | def selectChannels(self, channelList): |
|
236 | def selectChannels(self, channelList): | |
| 238 |
|
237 | |||
| 239 | channelIndexList = [] |
|
238 | channelIndexList = [] | |
| 240 |
|
239 | |||
| 241 | for channel in channelList: |
|
240 | for channel in channelList: | |
| 242 | if channel not in self.dataOut.channelList: |
|
241 | if channel not in self.dataOut.channelList: | |
| 243 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) |
|
242 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) | |
| 244 |
|
243 | |||
| 245 | index = self.dataOut.channelList.index(channel) |
|
244 | index = self.dataOut.channelList.index(channel) | |
| 246 | channelIndexList.append(index) |
|
245 | channelIndexList.append(index) | |
| 247 |
|
246 | |||
| 248 | self.selectChannelsByIndex(channelIndexList) |
|
247 | self.selectChannelsByIndex(channelIndexList) | |
| 249 |
|
248 | |||
| 250 | def selectChannelsByIndex(self, channelIndexList): |
|
249 | def selectChannelsByIndex(self, channelIndexList): | |
| 251 | """ |
|
250 | """ | |
| 252 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
251 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 253 |
|
252 | |||
| 254 | Input: |
|
253 | Input: | |
| 255 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
254 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 256 |
|
255 | |||
| 257 | Affected: |
|
256 | Affected: | |
| 258 | self.dataOut.data_spc |
|
257 | self.dataOut.data_spc | |
| 259 | self.dataOut.channelIndexList |
|
258 | self.dataOut.channelIndexList | |
| 260 | self.dataOut.nChannels |
|
259 | self.dataOut.nChannels | |
| 261 |
|
260 | |||
| 262 | Return: |
|
261 | Return: | |
| 263 | None |
|
262 | None | |
| 264 | """ |
|
263 | """ | |
| 265 |
|
264 | |||
| 266 | for channelIndex in channelIndexList: |
|
265 | for channelIndex in channelIndexList: | |
| 267 | if channelIndex not in self.dataOut.channelIndexList: |
|
266 | if channelIndex not in self.dataOut.channelIndexList: | |
| 268 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) |
|
267 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) | |
| 269 |
|
268 | |||
| 270 | # nChannels = len(channelIndexList) |
|
269 | # nChannels = len(channelIndexList) | |
| 271 |
|
270 | |||
| 272 | data_spc = self.dataOut.data_spc[channelIndexList,:] |
|
271 | data_spc = self.dataOut.data_spc[channelIndexList,:] | |
| 273 | data_dc = self.dataOut.data_dc[channelIndexList,:] |
|
272 | data_dc = self.dataOut.data_dc[channelIndexList,:] | |
| 274 |
|
273 | |||
| 275 | self.dataOut.data_spc = data_spc |
|
274 | self.dataOut.data_spc = data_spc | |
| 276 | self.dataOut.data_dc = data_dc |
|
275 | self.dataOut.data_dc = data_dc | |
| 277 |
|
276 | |||
| 278 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
277 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 279 | # self.dataOut.nChannels = nChannels |
|
278 | # self.dataOut.nChannels = nChannels | |
| 280 |
|
279 | |||
| 281 | self.__selectPairsByChannel(self.dataOut.channelList) |
|
280 | self.__selectPairsByChannel(self.dataOut.channelList) | |
| 282 |
|
281 | |||
| 283 | return 1 |
|
282 | return 1 | |
| 284 |
|
283 | |||
| 285 |
|
284 | |||
| 286 | def selectFFTs(self, minFFT, maxFFT ): |
|
285 | def selectFFTs(self, minFFT, maxFFT ): | |
| 287 | """ |
|
286 | """ | |
| 288 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango |
|
287 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango | |
| 289 | minFFT<= FFT <= maxFFT |
|
288 | minFFT<= FFT <= maxFFT | |
| 290 | """ |
|
289 | """ | |
| 291 |
|
290 | |||
| 292 | if (minFFT > maxFFT): |
|
291 | if (minFFT > maxFFT): | |
| 293 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT) |
|
292 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT) | |
| 294 |
|
293 | |||
| 295 | if (minFFT < self.dataOut.getFreqRange()[0]): |
|
294 | if (minFFT < self.dataOut.getFreqRange()[0]): | |
| 296 | minFFT = self.dataOut.getFreqRange()[0] |
|
295 | minFFT = self.dataOut.getFreqRange()[0] | |
| 297 |
|
296 | |||
| 298 | if (maxFFT > self.dataOut.getFreqRange()[-1]): |
|
297 | if (maxFFT > self.dataOut.getFreqRange()[-1]): | |
| 299 | maxFFT = self.dataOut.getFreqRange()[-1] |
|
298 | maxFFT = self.dataOut.getFreqRange()[-1] | |
| 300 |
|
299 | |||
| 301 | minIndex = 0 |
|
300 | minIndex = 0 | |
| 302 | maxIndex = 0 |
|
301 | maxIndex = 0 | |
| 303 | FFTs = self.dataOut.getFreqRange() |
|
302 | FFTs = self.dataOut.getFreqRange() | |
| 304 |
|
303 | |||
| 305 | inda = numpy.where(FFTs >= minFFT) |
|
304 | inda = numpy.where(FFTs >= minFFT) | |
| 306 | indb = numpy.where(FFTs <= maxFFT) |
|
305 | indb = numpy.where(FFTs <= maxFFT) | |
| 307 |
|
306 | |||
| 308 | try: |
|
307 | try: | |
| 309 | minIndex = inda[0][0] |
|
308 | minIndex = inda[0][0] | |
| 310 | except: |
|
309 | except: | |
| 311 | minIndex = 0 |
|
310 | minIndex = 0 | |
| 312 |
|
311 | |||
| 313 | try: |
|
312 | try: | |
| 314 | maxIndex = indb[0][-1] |
|
313 | maxIndex = indb[0][-1] | |
| 315 | except: |
|
314 | except: | |
| 316 | maxIndex = len(FFTs) |
|
315 | maxIndex = len(FFTs) | |
| 317 |
|
316 | |||
| 318 | self.selectFFTsByIndex(minIndex, maxIndex) |
|
317 | self.selectFFTsByIndex(minIndex, maxIndex) | |
| 319 |
|
318 | |||
| 320 | return 1 |
|
319 | return 1 | |
| 321 |
|
320 | |||
| 322 |
|
321 | |||
| 323 |
|
322 | |||
| 324 | def selectHeights(self, minHei, maxHei): |
|
323 | def selectHeights(self, minHei, maxHei): | |
| 325 | """ |
|
324 | """ | |
| 326 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
325 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 327 | minHei <= height <= maxHei |
|
326 | minHei <= height <= maxHei | |
| 328 |
|
327 | |||
| 329 | Input: |
|
328 | Input: | |
| 330 | minHei : valor minimo de altura a considerar |
|
329 | minHei : valor minimo de altura a considerar | |
| 331 | maxHei : valor maximo de altura a considerar |
|
330 | maxHei : valor maximo de altura a considerar | |
| 332 |
|
331 | |||
| 333 | Affected: |
|
332 | Affected: | |
| 334 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
333 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 335 |
|
334 | |||
| 336 | Return: |
|
335 | Return: | |
| 337 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
336 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 338 | """ |
|
337 | """ | |
| 339 |
|
338 | |||
| 340 |
|
339 | |||
| 341 | if (minHei > maxHei): |
|
340 | if (minHei > maxHei): | |
| 342 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) |
|
341 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) | |
| 343 |
|
342 | |||
| 344 | if (minHei < self.dataOut.heightList[0]): |
|
343 | if (minHei < self.dataOut.heightList[0]): | |
| 345 | minHei = self.dataOut.heightList[0] |
|
344 | minHei = self.dataOut.heightList[0] | |
| 346 |
|
345 | |||
| 347 | if (maxHei > self.dataOut.heightList[-1]): |
|
346 | if (maxHei > self.dataOut.heightList[-1]): | |
| 348 | maxHei = self.dataOut.heightList[-1] |
|
347 | maxHei = self.dataOut.heightList[-1] | |
| 349 |
|
348 | |||
| 350 | minIndex = 0 |
|
349 | minIndex = 0 | |
| 351 | maxIndex = 0 |
|
350 | maxIndex = 0 | |
| 352 | heights = self.dataOut.heightList |
|
351 | heights = self.dataOut.heightList | |
| 353 |
|
352 | |||
| 354 | inda = numpy.where(heights >= minHei) |
|
353 | inda = numpy.where(heights >= minHei) | |
| 355 | indb = numpy.where(heights <= maxHei) |
|
354 | indb = numpy.where(heights <= maxHei) | |
| 356 |
|
355 | |||
| 357 | try: |
|
356 | try: | |
| 358 | minIndex = inda[0][0] |
|
357 | minIndex = inda[0][0] | |
| 359 | except: |
|
358 | except: | |
| 360 | minIndex = 0 |
|
359 | minIndex = 0 | |
| 361 |
|
360 | |||
| 362 | try: |
|
361 | try: | |
| 363 | maxIndex = indb[0][-1] |
|
362 | maxIndex = indb[0][-1] | |
| 364 | except: |
|
363 | except: | |
| 365 | maxIndex = len(heights) |
|
364 | maxIndex = len(heights) | |
| 366 |
|
365 | |||
| 367 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
366 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 368 |
|
367 | |||
| 369 |
|
368 | |||
| 370 | return 1 |
|
369 | return 1 | |
| 371 |
|
370 | |||
| 372 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): |
|
371 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): | |
| 373 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
372 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 374 |
|
373 | |||
| 375 | if hei_ref != None: |
|
374 | if hei_ref != None: | |
| 376 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
375 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 377 |
|
376 | |||
| 378 | minIndex = min(newheis[0]) |
|
377 | minIndex = min(newheis[0]) | |
| 379 | maxIndex = max(newheis[0]) |
|
378 | maxIndex = max(newheis[0]) | |
| 380 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
379 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 381 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
380 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 382 |
|
381 | |||
| 383 | # determina indices |
|
382 | # determina indices | |
| 384 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) |
|
383 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) | |
| 385 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) |
|
384 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) | |
| 386 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
385 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 387 | beacon_heiIndexList = [] |
|
386 | beacon_heiIndexList = [] | |
| 388 | for val in avg_dB.tolist(): |
|
387 | for val in avg_dB.tolist(): | |
| 389 | if val >= beacon_dB[0]: |
|
388 | if val >= beacon_dB[0]: | |
| 390 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
389 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 391 |
|
390 | |||
| 392 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
391 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 393 | data_cspc = None |
|
392 | data_cspc = None | |
| 394 | if self.dataOut.data_cspc is not None: |
|
393 | if self.dataOut.data_cspc is not None: | |
| 395 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
394 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 396 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
395 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 397 |
|
396 | |||
| 398 | data_dc = None |
|
397 | data_dc = None | |
| 399 | if self.dataOut.data_dc is not None: |
|
398 | if self.dataOut.data_dc is not None: | |
| 400 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
399 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 401 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
400 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 402 |
|
401 | |||
| 403 | self.dataOut.data_spc = data_spc |
|
402 | self.dataOut.data_spc = data_spc | |
| 404 | self.dataOut.data_cspc = data_cspc |
|
403 | self.dataOut.data_cspc = data_cspc | |
| 405 | self.dataOut.data_dc = data_dc |
|
404 | self.dataOut.data_dc = data_dc | |
| 406 | self.dataOut.heightList = heightList |
|
405 | self.dataOut.heightList = heightList | |
| 407 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
406 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 408 |
|
407 | |||
| 409 | return 1 |
|
408 | return 1 | |
| 410 |
|
409 | |||
| 411 | def selectFFTsByIndex(self, minIndex, maxIndex): |
|
410 | def selectFFTsByIndex(self, minIndex, maxIndex): | |
| 412 | """ |
|
411 | """ | |
| 413 |
|
412 | |||
| 414 | """ |
|
413 | """ | |
| 415 |
|
414 | |||
| 416 | if (minIndex < 0) or (minIndex > maxIndex): |
|
415 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 417 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
416 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 418 |
|
417 | |||
| 419 | if (maxIndex >= self.dataOut.nProfiles): |
|
418 | if (maxIndex >= self.dataOut.nProfiles): | |
| 420 | maxIndex = self.dataOut.nProfiles-1 |
|
419 | maxIndex = self.dataOut.nProfiles-1 | |
| 421 |
|
420 | |||
| 422 | #Spectra |
|
421 | #Spectra | |
| 423 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] |
|
422 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] | |
| 424 |
|
423 | |||
| 425 | data_cspc = None |
|
424 | data_cspc = None | |
| 426 | if self.dataOut.data_cspc is not None: |
|
425 | if self.dataOut.data_cspc is not None: | |
| 427 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] |
|
426 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] | |
| 428 |
|
427 | |||
| 429 | data_dc = None |
|
428 | data_dc = None | |
| 430 | if self.dataOut.data_dc is not None: |
|
429 | if self.dataOut.data_dc is not None: | |
| 431 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] |
|
430 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] | |
| 432 |
|
431 | |||
| 433 | self.dataOut.data_spc = data_spc |
|
432 | self.dataOut.data_spc = data_spc | |
| 434 | self.dataOut.data_cspc = data_cspc |
|
433 | self.dataOut.data_cspc = data_cspc | |
| 435 | self.dataOut.data_dc = data_dc |
|
434 | self.dataOut.data_dc = data_dc | |
| 436 |
|
435 | |||
| 437 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) |
|
436 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) | |
| 438 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] |
|
437 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] | |
| 439 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] |
|
438 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] | |
| 440 |
|
439 | |||
| 441 | #self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
440 | #self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 442 |
|
441 | |||
| 443 | return 1 |
|
442 | return 1 | |
| 444 |
|
443 | |||
| 445 |
|
444 | |||
| 446 |
|
445 | |||
| 447 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
446 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 448 | """ |
|
447 | """ | |
| 449 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
448 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 450 | minIndex <= index <= maxIndex |
|
449 | minIndex <= index <= maxIndex | |
| 451 |
|
450 | |||
| 452 | Input: |
|
451 | Input: | |
| 453 | minIndex : valor de indice minimo de altura a considerar |
|
452 | minIndex : valor de indice minimo de altura a considerar | |
| 454 | maxIndex : valor de indice maximo de altura a considerar |
|
453 | maxIndex : valor de indice maximo de altura a considerar | |
| 455 |
|
454 | |||
| 456 | Affected: |
|
455 | Affected: | |
| 457 | self.dataOut.data_spc |
|
456 | self.dataOut.data_spc | |
| 458 | self.dataOut.data_cspc |
|
457 | self.dataOut.data_cspc | |
| 459 | self.dataOut.data_dc |
|
458 | self.dataOut.data_dc | |
| 460 | self.dataOut.heightList |
|
459 | self.dataOut.heightList | |
| 461 |
|
460 | |||
| 462 | Return: |
|
461 | Return: | |
| 463 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
462 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 464 | """ |
|
463 | """ | |
| 465 |
|
464 | |||
| 466 | if (minIndex < 0) or (minIndex > maxIndex): |
|
465 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 467 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
466 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 468 |
|
467 | |||
| 469 | if (maxIndex >= self.dataOut.nHeights): |
|
468 | if (maxIndex >= self.dataOut.nHeights): | |
| 470 | maxIndex = self.dataOut.nHeights-1 |
|
469 | maxIndex = self.dataOut.nHeights-1 | |
| 471 |
|
470 | |||
| 472 | #Spectra |
|
471 | #Spectra | |
| 473 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
472 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 474 |
|
473 | |||
| 475 | data_cspc = None |
|
474 | data_cspc = None | |
| 476 | if self.dataOut.data_cspc is not None: |
|
475 | if self.dataOut.data_cspc is not None: | |
| 477 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
476 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 478 |
|
477 | |||
| 479 | data_dc = None |
|
478 | data_dc = None | |
| 480 | if self.dataOut.data_dc is not None: |
|
479 | if self.dataOut.data_dc is not None: | |
| 481 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
480 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 482 |
|
481 | |||
| 483 | self.dataOut.data_spc = data_spc |
|
482 | self.dataOut.data_spc = data_spc | |
| 484 | self.dataOut.data_cspc = data_cspc |
|
483 | self.dataOut.data_cspc = data_cspc | |
| 485 | self.dataOut.data_dc = data_dc |
|
484 | self.dataOut.data_dc = data_dc | |
| 486 |
|
485 | |||
| 487 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
486 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 488 |
|
487 | |||
| 489 | return 1 |
|
488 | return 1 | |
| 490 |
|
489 | |||
| 491 |
|
490 | |||
| 492 | def removeDC(self, mode = 2): |
|
491 | def removeDC(self, mode = 2): | |
| 493 | jspectra = self.dataOut.data_spc |
|
492 | jspectra = self.dataOut.data_spc | |
| 494 | jcspectra = self.dataOut.data_cspc |
|
493 | jcspectra = self.dataOut.data_cspc | |
| 495 |
|
494 | |||
| 496 |
|
495 | |||
| 497 | num_chan = jspectra.shape[0] |
|
496 | num_chan = jspectra.shape[0] | |
| 498 | num_hei = jspectra.shape[2] |
|
497 | num_hei = jspectra.shape[2] | |
| 499 |
|
498 | |||
| 500 | if jcspectra is not None: |
|
499 | if jcspectra is not None: | |
| 501 | jcspectraExist = True |
|
500 | jcspectraExist = True | |
| 502 | num_pairs = jcspectra.shape[0] |
|
501 | num_pairs = jcspectra.shape[0] | |
| 503 | else: jcspectraExist = False |
|
502 | else: jcspectraExist = False | |
| 504 |
|
503 | |||
| 505 | freq_dc = jspectra.shape[1]/2 |
|
504 | freq_dc = jspectra.shape[1]/2 | |
| 506 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
505 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |
| 507 |
|
506 | |||
| 508 | if ind_vel[0]<0: |
|
507 | if ind_vel[0]<0: | |
| 509 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
508 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |
| 510 |
|
509 | |||
| 511 | if mode == 1: |
|
510 | if mode == 1: | |
| 512 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
511 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
| 513 |
|
512 | |||
| 514 | if jcspectraExist: |
|
513 | if jcspectraExist: | |
| 515 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 |
|
514 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 | |
| 516 |
|
515 | |||
| 517 | if mode == 2: |
|
516 | if mode == 2: | |
| 518 |
|
517 | |||
| 519 | vel = numpy.array([-2,-1,1,2]) |
|
518 | vel = numpy.array([-2,-1,1,2]) | |
| 520 | xx = numpy.zeros([4,4]) |
|
519 | xx = numpy.zeros([4,4]) | |
| 521 |
|
520 | |||
| 522 | for fil in range(4): |
|
521 | for fil in range(4): | |
| 523 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
522 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |
| 524 |
|
523 | |||
| 525 | xx_inv = numpy.linalg.inv(xx) |
|
524 | xx_inv = numpy.linalg.inv(xx) | |
| 526 | xx_aux = xx_inv[0,:] |
|
525 | xx_aux = xx_inv[0,:] | |
| 527 |
|
526 | |||
| 528 | for ich in range(num_chan): |
|
527 | for ich in range(num_chan): | |
| 529 | yy = jspectra[ich,ind_vel,:] |
|
528 | yy = jspectra[ich,ind_vel,:] | |
| 530 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
529 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 531 |
|
530 | |||
| 532 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
531 | junkid = jspectra[ich,freq_dc,:]<=0 | |
| 533 | cjunkid = sum(junkid) |
|
532 | cjunkid = sum(junkid) | |
| 534 |
|
533 | |||
| 535 | if cjunkid.any(): |
|
534 | if cjunkid.any(): | |
| 536 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
535 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |
| 537 |
|
536 | |||
| 538 | if jcspectraExist: |
|
537 | if jcspectraExist: | |
| 539 | for ip in range(num_pairs): |
|
538 | for ip in range(num_pairs): | |
| 540 | yy = jcspectra[ip,ind_vel,:] |
|
539 | yy = jcspectra[ip,ind_vel,:] | |
| 541 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
540 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 542 |
|
541 | |||
| 543 |
|
542 | |||
| 544 | self.dataOut.data_spc = jspectra |
|
543 | self.dataOut.data_spc = jspectra | |
| 545 | self.dataOut.data_cspc = jcspectra |
|
544 | self.dataOut.data_cspc = jcspectra | |
| 546 |
|
545 | |||
| 547 | return 1 |
|
546 | return 1 | |
| 548 |
|
547 | |||
| 549 | def removeInterference2(self): |
|
548 | def removeInterference2(self): | |
| 550 |
|
549 | |||
| 551 | cspc = self.dataOut.data_cspc |
|
550 | cspc = self.dataOut.data_cspc | |
| 552 | spc = self.dataOut.data_spc |
|
551 | spc = self.dataOut.data_spc | |
| 553 | print numpy.shape(spc) |
|
552 | print numpy.shape(spc) | |
| 554 | Heights = numpy.arange(cspc.shape[2]) |
|
553 | Heights = numpy.arange(cspc.shape[2]) | |
| 555 | realCspc = numpy.abs(cspc) |
|
554 | realCspc = numpy.abs(cspc) | |
| 556 |
|
555 | |||
| 557 | for i in range(cspc.shape[0]): |
|
556 | for i in range(cspc.shape[0]): | |
| 558 | LinePower= numpy.sum(realCspc[i], axis=0) |
|
557 | LinePower= numpy.sum(realCspc[i], axis=0) | |
| 559 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] |
|
558 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] | |
| 560 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] |
|
559 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] | |
| 561 | #print numpy.shape(realCspc) |
|
560 | #print numpy.shape(realCspc) | |
| 562 | #print '',SelectedHeights, '', numpy.shape(realCspc[i,:,SelectedHeights]) |
|
561 | #print '',SelectedHeights, '', numpy.shape(realCspc[i,:,SelectedHeights]) | |
| 563 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) |
|
562 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) | |
| 564 | print SelectedHeights |
|
563 | print SelectedHeights | |
| 565 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] |
|
564 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] | |
| 566 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] |
|
565 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] | |
| 567 |
|
566 | |||
| 568 |
|
567 | |||
| 569 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) |
|
568 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) | |
| 570 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) |
|
569 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) | |
| 571 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): |
|
570 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): | |
| 572 | cspc[i,InterferenceRange,:] = numpy.NaN |
|
571 | cspc[i,InterferenceRange,:] = numpy.NaN | |
| 573 |
|
572 | |||
| 574 | print '########################################################################################' |
|
573 | print '########################################################################################' | |
| 575 | print 'Len interference sum',len(InterferenceSum) |
|
574 | print 'Len interference sum',len(InterferenceSum) | |
| 576 | print 'InterferenceThresholdMin', InterferenceThresholdMin, 'InterferenceThresholdMax', InterferenceThresholdMax |
|
575 | print 'InterferenceThresholdMin', InterferenceThresholdMin, 'InterferenceThresholdMax', InterferenceThresholdMax | |
| 577 | print 'InterferenceRange',InterferenceRange |
|
576 | print 'InterferenceRange',InterferenceRange | |
| 578 | print '########################################################################################' |
|
577 | print '########################################################################################' | |
| 579 |
|
578 | |||
| 580 | ''' Ploteo ''' |
|
579 | ''' Ploteo ''' | |
| 581 |
|
580 | |||
| 582 | #for i in range(3): |
|
581 | #for i in range(3): | |
| 583 | #print 'FASE', numpy.shape(phase), y[25] |
|
582 | #print 'FASE', numpy.shape(phase), y[25] | |
| 584 | #print numpy.shape(coherence) |
|
583 | #print numpy.shape(coherence) | |
| 585 | #fig = plt.figure(10+ int(numpy.random.rand()*100)) |
|
584 | #fig = plt.figure(10+ int(numpy.random.rand()*100)) | |
| 586 | #plt.plot( x[0:256],coherence[:,25] ) |
|
585 | #plt.plot( x[0:256],coherence[:,25] ) | |
| 587 | #cohAv = numpy.average(coherence[i],1) |
|
586 | #cohAv = numpy.average(coherence[i],1) | |
| 588 | #Pendiente = FrecRange * PhaseSlope[i] |
|
587 | #Pendiente = FrecRange * PhaseSlope[i] | |
| 589 | #plt.plot( InterferenceSum) |
|
588 | #plt.plot( InterferenceSum) | |
| 590 | #plt.plot( numpy.sort(InterferenceSum)) |
|
589 | #plt.plot( numpy.sort(InterferenceSum)) | |
| 591 | #plt.plot( LinePower ) |
|
590 | #plt.plot( LinePower ) | |
| 592 | #plt.plot( xFrec,phase[i]) |
|
591 | #plt.plot( xFrec,phase[i]) | |
| 593 |
|
592 | |||
| 594 | #CSPCmean = numpy.mean(numpy.abs(CSPCSamples),0) |
|
593 | #CSPCmean = numpy.mean(numpy.abs(CSPCSamples),0) | |
| 595 | #plt.plot(xFrec, FitGauss01) |
|
594 | #plt.plot(xFrec, FitGauss01) | |
| 596 | #plt.plot(xFrec, CSPCmean) |
|
595 | #plt.plot(xFrec, CSPCmean) | |
| 597 | #plt.plot(xFrec, numpy.abs(CSPCSamples[0])) |
|
596 | #plt.plot(xFrec, numpy.abs(CSPCSamples[0])) | |
| 598 | #plt.plot(xFrec, FitGauss) |
|
597 | #plt.plot(xFrec, FitGauss) | |
| 599 | #plt.plot(xFrec, yMean) |
|
598 | #plt.plot(xFrec, yMean) | |
| 600 | #plt.plot(xFrec, numpy.abs(coherence[0])) |
|
599 | #plt.plot(xFrec, numpy.abs(coherence[0])) | |
| 601 |
|
600 | |||
| 602 | #plt.axis([-12, 12, 15, 50]) |
|
601 | #plt.axis([-12, 12, 15, 50]) | |
| 603 | #plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) |
|
602 | #plt.title("%s" %( '%s %s, Channel %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S") , i))) | |
| 604 |
|
603 | |||
| 605 |
|
604 | |||
| 606 | #fig.savefig('/home/erick/Documents/Pics/nom{}.png'.format(int(numpy.random.rand()*100))) |
|
605 | #fig.savefig('/home/erick/Documents/Pics/nom{}.png'.format(int(numpy.random.rand()*100))) | |
| 607 |
|
606 | |||
| 608 | #plt.show() |
|
607 | #plt.show() | |
| 609 | #self.indice=self.indice+1 |
|
608 | #self.indice=self.indice+1 | |
| 610 | #raise |
|
609 | #raise | |
| 611 |
|
610 | |||
| 612 |
|
611 | |||
| 613 | self.dataOut.data_cspc = cspc |
|
612 | self.dataOut.data_cspc = cspc | |
| 614 |
|
613 | |||
| 615 | # for i in range(spc.shape[0]): |
|
614 | # for i in range(spc.shape[0]): | |
| 616 | # LinePower= numpy.sum(spc[i], axis=0) |
|
615 | # LinePower= numpy.sum(spc[i], axis=0) | |
| 617 | # Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] |
|
616 | # Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] | |
| 618 | # SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] |
|
617 | # SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] | |
| 619 | # #print numpy.shape(realCspc) |
|
618 | # #print numpy.shape(realCspc) | |
| 620 | # #print '',SelectedHeights, '', numpy.shape(realCspc[i,:,SelectedHeights]) |
|
619 | # #print '',SelectedHeights, '', numpy.shape(realCspc[i,:,SelectedHeights]) | |
| 621 | # InterferenceSum = numpy.sum( spc[i,:,SelectedHeights], axis=0 ) |
|
620 | # InterferenceSum = numpy.sum( spc[i,:,SelectedHeights], axis=0 ) | |
| 622 | # InterferenceThreshold = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] |
|
621 | # InterferenceThreshold = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] | |
| 623 | # InterferenceRange = numpy.where( InterferenceSum > InterferenceThreshold ) |
|
622 | # InterferenceRange = numpy.where( InterferenceSum > InterferenceThreshold ) | |
| 624 | # if len(InterferenceRange)<int(spc.shape[1]*0.03): |
|
623 | # if len(InterferenceRange)<int(spc.shape[1]*0.03): | |
| 625 | # spc[i,InterferenceRange,:] = numpy.NaN |
|
624 | # spc[i,InterferenceRange,:] = numpy.NaN | |
| 626 |
|
625 | |||
| 627 | #self.dataOut.data_spc = spc |
|
626 | #self.dataOut.data_spc = spc | |
| 628 |
|
627 | |||
| 629 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
628 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 630 |
|
629 | |||
| 631 | jspectra = self.dataOut.data_spc |
|
630 | jspectra = self.dataOut.data_spc | |
| 632 | jcspectra = self.dataOut.data_cspc |
|
631 | jcspectra = self.dataOut.data_cspc | |
| 633 | jnoise = self.dataOut.getNoise() |
|
632 | jnoise = self.dataOut.getNoise() | |
| 634 | num_incoh = self.dataOut.nIncohInt |
|
633 | num_incoh = self.dataOut.nIncohInt | |
| 635 |
|
634 | |||
| 636 | num_channel = jspectra.shape[0] |
|
635 | num_channel = jspectra.shape[0] | |
| 637 | num_prof = jspectra.shape[1] |
|
636 | num_prof = jspectra.shape[1] | |
| 638 | num_hei = jspectra.shape[2] |
|
637 | num_hei = jspectra.shape[2] | |
| 639 |
|
638 | |||
| 640 | #hei_interf |
|
639 | #hei_interf | |
| 641 | if hei_interf is None: |
|
640 | if hei_interf is None: | |
| 642 | count_hei = num_hei/2 #Como es entero no importa |
|
641 | count_hei = num_hei/2 #Como es entero no importa | |
| 643 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei |
|
642 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei | |
| 644 | hei_interf = numpy.asarray(hei_interf)[0] |
|
643 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 645 | #nhei_interf |
|
644 | #nhei_interf | |
| 646 | if (nhei_interf == None): |
|
645 | if (nhei_interf == None): | |
| 647 | nhei_interf = 5 |
|
646 | nhei_interf = 5 | |
| 648 | if (nhei_interf < 1): |
|
647 | if (nhei_interf < 1): | |
| 649 | nhei_interf = 1 |
|
648 | nhei_interf = 1 | |
| 650 | if (nhei_interf > count_hei): |
|
649 | if (nhei_interf > count_hei): | |
| 651 | nhei_interf = count_hei |
|
650 | nhei_interf = count_hei | |
| 652 | if (offhei_interf == None): |
|
651 | if (offhei_interf == None): | |
| 653 | offhei_interf = 0 |
|
652 | offhei_interf = 0 | |
| 654 |
|
653 | |||
| 655 | ind_hei = range(num_hei) |
|
654 | ind_hei = range(num_hei) | |
| 656 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
655 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 657 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
656 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 658 | mask_prof = numpy.asarray(range(num_prof)) |
|
657 | mask_prof = numpy.asarray(range(num_prof)) | |
| 659 | num_mask_prof = mask_prof.size |
|
658 | num_mask_prof = mask_prof.size | |
| 660 | comp_mask_prof = [0, num_prof/2] |
|
659 | comp_mask_prof = [0, num_prof/2] | |
| 661 |
|
660 | |||
| 662 |
|
661 | |||
| 663 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
662 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 664 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
663 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 665 | jnoise = numpy.nan |
|
664 | jnoise = numpy.nan | |
| 666 | noise_exist = jnoise[0] < numpy.Inf |
|
665 | noise_exist = jnoise[0] < numpy.Inf | |
| 667 |
|
666 | |||
| 668 | #Subrutina de Remocion de la Interferencia |
|
667 | #Subrutina de Remocion de la Interferencia | |
| 669 | for ich in range(num_channel): |
|
668 | for ich in range(num_channel): | |
| 670 | #Se ordena los espectros segun su potencia (menor a mayor) |
|
669 | #Se ordena los espectros segun su potencia (menor a mayor) | |
| 671 | power = jspectra[ich,mask_prof,:] |
|
670 | power = jspectra[ich,mask_prof,:] | |
| 672 | power = power[:,hei_interf] |
|
671 | power = power[:,hei_interf] | |
| 673 | power = power.sum(axis = 0) |
|
672 | power = power.sum(axis = 0) | |
| 674 | psort = power.ravel().argsort() |
|
673 | psort = power.ravel().argsort() | |
| 675 |
|
674 | |||
| 676 | #Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
675 | #Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 677 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
676 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 678 |
|
677 | |||
| 679 | if noise_exist: |
|
678 | if noise_exist: | |
| 680 | # tmp_noise = jnoise[ich] / num_prof |
|
679 | # tmp_noise = jnoise[ich] / num_prof | |
| 681 | tmp_noise = jnoise[ich] |
|
680 | tmp_noise = jnoise[ich] | |
| 682 | junkspc_interf = junkspc_interf - tmp_noise |
|
681 | junkspc_interf = junkspc_interf - tmp_noise | |
| 683 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
682 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 684 |
|
683 | |||
| 685 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf |
|
684 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf | |
| 686 | jspc_interf = jspc_interf.transpose() |
|
685 | jspc_interf = jspc_interf.transpose() | |
| 687 | #Calculando el espectro de interferencia promedio |
|
686 | #Calculando el espectro de interferencia promedio | |
| 688 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) |
|
687 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) | |
| 689 | noiseid = noiseid[0] |
|
688 | noiseid = noiseid[0] | |
| 690 | cnoiseid = noiseid.size |
|
689 | cnoiseid = noiseid.size | |
| 691 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) |
|
690 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) | |
| 692 | interfid = interfid[0] |
|
691 | interfid = interfid[0] | |
| 693 | cinterfid = interfid.size |
|
692 | cinterfid = interfid.size | |
| 694 |
|
693 | |||
| 695 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 |
|
694 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 | |
| 696 |
|
695 | |||
| 697 | #Expandiendo los perfiles a limpiar |
|
696 | #Expandiendo los perfiles a limpiar | |
| 698 | if (cinterfid > 0): |
|
697 | if (cinterfid > 0): | |
| 699 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof |
|
698 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof | |
| 700 | new_interfid = numpy.asarray(new_interfid) |
|
699 | new_interfid = numpy.asarray(new_interfid) | |
| 701 | new_interfid = {x for x in new_interfid} |
|
700 | new_interfid = {x for x in new_interfid} | |
| 702 | new_interfid = numpy.array(list(new_interfid)) |
|
701 | new_interfid = numpy.array(list(new_interfid)) | |
| 703 | new_cinterfid = new_interfid.size |
|
702 | new_cinterfid = new_interfid.size | |
| 704 | else: new_cinterfid = 0 |
|
703 | else: new_cinterfid = 0 | |
| 705 |
|
704 | |||
| 706 | for ip in range(new_cinterfid): |
|
705 | for ip in range(new_cinterfid): | |
| 707 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() |
|
706 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() | |
| 708 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] |
|
707 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] | |
| 709 |
|
708 | |||
| 710 |
|
709 | |||
| 711 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices |
|
710 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices | |
| 712 |
|
711 | |||
| 713 | #Removiendo la interferencia del punto de mayor interferencia |
|
712 | #Removiendo la interferencia del punto de mayor interferencia | |
| 714 | ListAux = jspc_interf[mask_prof].tolist() |
|
713 | ListAux = jspc_interf[mask_prof].tolist() | |
| 715 | maxid = ListAux.index(max(ListAux)) |
|
714 | maxid = ListAux.index(max(ListAux)) | |
| 716 |
|
715 | |||
| 717 |
|
716 | |||
| 718 | if cinterfid > 0: |
|
717 | if cinterfid > 0: | |
| 719 | for ip in range(cinterfid*(interf == 2) - 1): |
|
718 | for ip in range(cinterfid*(interf == 2) - 1): | |
| 720 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() |
|
719 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() | |
| 721 | cind = len(ind) |
|
720 | cind = len(ind) | |
| 722 |
|
721 | |||
| 723 | if (cind > 0): |
|
722 | if (cind > 0): | |
| 724 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) |
|
723 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) | |
| 725 |
|
724 | |||
| 726 | ind = numpy.array([-2,-1,1,2]) |
|
725 | ind = numpy.array([-2,-1,1,2]) | |
| 727 | xx = numpy.zeros([4,4]) |
|
726 | xx = numpy.zeros([4,4]) | |
| 728 |
|
727 | |||
| 729 | for id1 in range(4): |
|
728 | for id1 in range(4): | |
| 730 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
729 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 731 |
|
730 | |||
| 732 | xx_inv = numpy.linalg.inv(xx) |
|
731 | xx_inv = numpy.linalg.inv(xx) | |
| 733 | xx = xx_inv[:,0] |
|
732 | xx = xx_inv[:,0] | |
| 734 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
733 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 735 | yy = jspectra[ich,mask_prof[ind],:] |
|
734 | yy = jspectra[ich,mask_prof[ind],:] | |
| 736 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
735 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 737 |
|
736 | |||
| 738 |
|
737 | |||
| 739 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() |
|
738 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() | |
| 740 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) |
|
739 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) | |
| 741 |
|
740 | |||
| 742 | #Remocion de Interferencia en el Cross Spectra |
|
741 | #Remocion de Interferencia en el Cross Spectra | |
| 743 | if jcspectra is None: return jspectra, jcspectra |
|
742 | if jcspectra is None: return jspectra, jcspectra | |
| 744 | num_pairs = jcspectra.size/(num_prof*num_hei) |
|
743 | num_pairs = jcspectra.size/(num_prof*num_hei) | |
| 745 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
744 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 746 |
|
745 | |||
| 747 | for ip in range(num_pairs): |
|
746 | for ip in range(num_pairs): | |
| 748 |
|
747 | |||
| 749 | #------------------------------------------- |
|
748 | #------------------------------------------- | |
| 750 |
|
749 | |||
| 751 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) |
|
750 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) | |
| 752 | cspower = cspower[:,hei_interf] |
|
751 | cspower = cspower[:,hei_interf] | |
| 753 | cspower = cspower.sum(axis = 0) |
|
752 | cspower = cspower.sum(axis = 0) | |
| 754 |
|
753 | |||
| 755 | cspsort = cspower.ravel().argsort() |
|
754 | cspsort = cspower.ravel().argsort() | |
| 756 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
755 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 757 | junkcspc_interf = junkcspc_interf.transpose() |
|
756 | junkcspc_interf = junkcspc_interf.transpose() | |
| 758 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf |
|
757 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf | |
| 759 |
|
758 | |||
| 760 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
759 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 761 |
|
760 | |||
| 762 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
761 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 763 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
762 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 764 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) |
|
763 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) | |
| 765 |
|
764 | |||
| 766 | for iprof in range(num_prof): |
|
765 | for iprof in range(num_prof): | |
| 767 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() |
|
766 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() | |
| 768 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] |
|
767 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] | |
| 769 |
|
768 | |||
| 770 | #Removiendo la Interferencia |
|
769 | #Removiendo la Interferencia | |
| 771 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf |
|
770 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf | |
| 772 |
|
771 | |||
| 773 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
772 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 774 | maxid = ListAux.index(max(ListAux)) |
|
773 | maxid = ListAux.index(max(ListAux)) | |
| 775 |
|
774 | |||
| 776 | ind = numpy.array([-2,-1,1,2]) |
|
775 | ind = numpy.array([-2,-1,1,2]) | |
| 777 | xx = numpy.zeros([4,4]) |
|
776 | xx = numpy.zeros([4,4]) | |
| 778 |
|
777 | |||
| 779 | for id1 in range(4): |
|
778 | for id1 in range(4): | |
| 780 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
779 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 781 |
|
780 | |||
| 782 | xx_inv = numpy.linalg.inv(xx) |
|
781 | xx_inv = numpy.linalg.inv(xx) | |
| 783 | xx = xx_inv[:,0] |
|
782 | xx = xx_inv[:,0] | |
| 784 |
|
783 | |||
| 785 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
784 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 786 | yy = jcspectra[ip,mask_prof[ind],:] |
|
785 | yy = jcspectra[ip,mask_prof[ind],:] | |
| 787 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
786 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 788 |
|
787 | |||
| 789 | #Guardar Resultados |
|
788 | #Guardar Resultados | |
| 790 | self.dataOut.data_spc = jspectra |
|
789 | self.dataOut.data_spc = jspectra | |
| 791 | self.dataOut.data_cspc = jcspectra |
|
790 | self.dataOut.data_cspc = jcspectra | |
| 792 |
|
791 | |||
| 793 | return 1 |
|
792 | return 1 | |
| 794 |
|
793 | |||
| 795 | def setRadarFrequency(self, frequency=None): |
|
794 | def setRadarFrequency(self, frequency=None): | |
| 796 |
|
795 | |||
| 797 | if frequency != None: |
|
796 | if frequency != None: | |
| 798 | self.dataOut.frequency = frequency |
|
797 | self.dataOut.frequency = frequency | |
| 799 |
|
798 | |||
| 800 | return 1 |
|
799 | return 1 | |
| 801 |
|
800 | |||
| 802 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
801 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 803 | #validacion de rango |
|
802 | #validacion de rango | |
| 804 | if minHei == None: |
|
803 | if minHei == None: | |
| 805 | minHei = self.dataOut.heightList[0] |
|
804 | minHei = self.dataOut.heightList[0] | |
| 806 |
|
805 | |||
| 807 | if maxHei == None: |
|
806 | if maxHei == None: | |
| 808 | maxHei = self.dataOut.heightList[-1] |
|
807 | maxHei = self.dataOut.heightList[-1] | |
| 809 |
|
808 | |||
| 810 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
809 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 811 | print 'minHei: %.2f is out of the heights range'%(minHei) |
|
810 | print 'minHei: %.2f is out of the heights range'%(minHei) | |
| 812 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) |
|
811 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) | |
| 813 | minHei = self.dataOut.heightList[0] |
|
812 | minHei = self.dataOut.heightList[0] | |
| 814 |
|
813 | |||
| 815 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
814 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 816 | print 'maxHei: %.2f is out of the heights range'%(maxHei) |
|
815 | print 'maxHei: %.2f is out of the heights range'%(maxHei) | |
| 817 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) |
|
816 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) | |
| 818 | maxHei = self.dataOut.heightList[-1] |
|
817 | maxHei = self.dataOut.heightList[-1] | |
| 819 |
|
818 | |||
| 820 | # validacion de velocidades |
|
819 | # validacion de velocidades | |
| 821 | velrange = self.dataOut.getVelRange(1) |
|
820 | velrange = self.dataOut.getVelRange(1) | |
| 822 |
|
821 | |||
| 823 | if minVel == None: |
|
822 | if minVel == None: | |
| 824 | minVel = velrange[0] |
|
823 | minVel = velrange[0] | |
| 825 |
|
824 | |||
| 826 | if maxVel == None: |
|
825 | if maxVel == None: | |
| 827 | maxVel = velrange[-1] |
|
826 | maxVel = velrange[-1] | |
| 828 |
|
827 | |||
| 829 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
828 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 830 | print 'minVel: %.2f is out of the velocity range'%(minVel) |
|
829 | print 'minVel: %.2f is out of the velocity range'%(minVel) | |
| 831 | print 'minVel is setting to %.2f'%(velrange[0]) |
|
830 | print 'minVel is setting to %.2f'%(velrange[0]) | |
| 832 | minVel = velrange[0] |
|
831 | minVel = velrange[0] | |
| 833 |
|
832 | |||
| 834 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
833 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 835 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) |
|
834 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) | |
| 836 | print 'maxVel is setting to %.2f'%(velrange[-1]) |
|
835 | print 'maxVel is setting to %.2f'%(velrange[-1]) | |
| 837 | maxVel = velrange[-1] |
|
836 | maxVel = velrange[-1] | |
| 838 |
|
837 | |||
| 839 | # seleccion de indices para rango |
|
838 | # seleccion de indices para rango | |
| 840 | minIndex = 0 |
|
839 | minIndex = 0 | |
| 841 | maxIndex = 0 |
|
840 | maxIndex = 0 | |
| 842 | heights = self.dataOut.heightList |
|
841 | heights = self.dataOut.heightList | |
| 843 |
|
842 | |||
| 844 | inda = numpy.where(heights >= minHei) |
|
843 | inda = numpy.where(heights >= minHei) | |
| 845 | indb = numpy.where(heights <= maxHei) |
|
844 | indb = numpy.where(heights <= maxHei) | |
| 846 |
|
845 | |||
| 847 | try: |
|
846 | try: | |
| 848 | minIndex = inda[0][0] |
|
847 | minIndex = inda[0][0] | |
| 849 | except: |
|
848 | except: | |
| 850 | minIndex = 0 |
|
849 | minIndex = 0 | |
| 851 |
|
850 | |||
| 852 | try: |
|
851 | try: | |
| 853 | maxIndex = indb[0][-1] |
|
852 | maxIndex = indb[0][-1] | |
| 854 | except: |
|
853 | except: | |
| 855 | maxIndex = len(heights) |
|
854 | maxIndex = len(heights) | |
| 856 |
|
855 | |||
| 857 | if (minIndex < 0) or (minIndex > maxIndex): |
|
856 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 858 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
857 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 859 |
|
858 | |||
| 860 | if (maxIndex >= self.dataOut.nHeights): |
|
859 | if (maxIndex >= self.dataOut.nHeights): | |
| 861 | maxIndex = self.dataOut.nHeights-1 |
|
860 | maxIndex = self.dataOut.nHeights-1 | |
| 862 |
|
861 | |||
| 863 | # seleccion de indices para velocidades |
|
862 | # seleccion de indices para velocidades | |
| 864 | indminvel = numpy.where(velrange >= minVel) |
|
863 | indminvel = numpy.where(velrange >= minVel) | |
| 865 | indmaxvel = numpy.where(velrange <= maxVel) |
|
864 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 866 | try: |
|
865 | try: | |
| 867 | minIndexVel = indminvel[0][0] |
|
866 | minIndexVel = indminvel[0][0] | |
| 868 | except: |
|
867 | except: | |
| 869 | minIndexVel = 0 |
|
868 | minIndexVel = 0 | |
| 870 |
|
869 | |||
| 871 | try: |
|
870 | try: | |
| 872 | maxIndexVel = indmaxvel[0][-1] |
|
871 | maxIndexVel = indmaxvel[0][-1] | |
| 873 | except: |
|
872 | except: | |
| 874 | maxIndexVel = len(velrange) |
|
873 | maxIndexVel = len(velrange) | |
| 875 |
|
874 | |||
| 876 | #seleccion del espectro |
|
875 | #seleccion del espectro | |
| 877 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] |
|
876 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] | |
| 878 | #estimacion de ruido |
|
877 | #estimacion de ruido | |
| 879 | noise = numpy.zeros(self.dataOut.nChannels) |
|
878 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 880 |
|
879 | |||
| 881 | for channel in range(self.dataOut.nChannels): |
|
880 | for channel in range(self.dataOut.nChannels): | |
| 882 | daux = data_spc[channel,:,:] |
|
881 | daux = data_spc[channel,:,:] | |
| 883 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) |
|
882 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) | |
| 884 |
|
883 | |||
| 885 | self.dataOut.noise_estimation = noise.copy() |
|
884 | self.dataOut.noise_estimation = noise.copy() | |
| 886 |
|
885 | |||
| 887 | return 1 |
|
886 | return 1 | |
| 888 |
|
887 | |||
| 889 | class IncohInt(Operation): |
|
888 | class IncohInt(Operation): | |
| 890 |
|
889 | |||
| 891 |
|
890 | |||
| 892 | __profIndex = 0 |
|
891 | __profIndex = 0 | |
| 893 | __withOverapping = False |
|
892 | __withOverapping = False | |
| 894 |
|
893 | |||
| 895 | __byTime = False |
|
894 | __byTime = False | |
| 896 | __initime = None |
|
895 | __initime = None | |
| 897 | __lastdatatime = None |
|
896 | __lastdatatime = None | |
| 898 | __integrationtime = None |
|
897 | __integrationtime = None | |
| 899 |
|
898 | |||
| 900 | __buffer_spc = None |
|
899 | __buffer_spc = None | |
| 901 | __buffer_cspc = None |
|
900 | __buffer_cspc = None | |
| 902 | __buffer_dc = None |
|
901 | __buffer_dc = None | |
| 903 |
|
902 | |||
| 904 | __dataReady = False |
|
903 | __dataReady = False | |
| 905 |
|
904 | |||
| 906 | __timeInterval = None |
|
905 | __timeInterval = None | |
| 907 |
|
906 | |||
| 908 | n = None |
|
907 | n = None | |
| 909 |
|
908 | |||
| 910 |
|
909 | |||
| 911 |
|
910 | |||
| 912 | def __init__(self, **kwargs): |
|
911 | def __init__(self, **kwargs): | |
| 913 |
|
912 | |||
| 914 | Operation.__init__(self, **kwargs) |
|
913 | Operation.__init__(self, **kwargs) | |
| 915 | # self.isConfig = False |
|
914 | # self.isConfig = False | |
| 916 |
|
915 | |||
| 917 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
916 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 918 | """ |
|
917 | """ | |
| 919 | Set the parameters of the integration class. |
|
918 | Set the parameters of the integration class. | |
| 920 |
|
919 | |||
| 921 | Inputs: |
|
920 | Inputs: | |
| 922 |
|
921 | |||
| 923 | n : Number of coherent integrations |
|
922 | n : Number of coherent integrations | |
| 924 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
923 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 925 | overlapping : |
|
924 | overlapping : | |
| 926 |
|
925 | |||
| 927 | """ |
|
926 | """ | |
| 928 |
|
927 | |||
| 929 | self.__initime = None |
|
928 | self.__initime = None | |
| 930 | self.__lastdatatime = 0 |
|
929 | self.__lastdatatime = 0 | |
| 931 |
|
930 | |||
| 932 | self.__buffer_spc = 0 |
|
931 | self.__buffer_spc = 0 | |
| 933 | self.__buffer_cspc = 0 |
|
932 | self.__buffer_cspc = 0 | |
| 934 | self.__buffer_dc = 0 |
|
933 | self.__buffer_dc = 0 | |
| 935 |
|
934 | |||
| 936 | self.__profIndex = 0 |
|
935 | self.__profIndex = 0 | |
| 937 | self.__dataReady = False |
|
936 | self.__dataReady = False | |
| 938 | self.__byTime = False |
|
937 | self.__byTime = False | |
| 939 |
|
938 | |||
| 940 | if n is None and timeInterval is None: |
|
939 | if n is None and timeInterval is None: | |
| 941 | raise ValueError, "n or timeInterval should be specified ..." |
|
940 | raise ValueError, "n or timeInterval should be specified ..." | |
| 942 |
|
941 | |||
| 943 | if n is not None: |
|
942 | if n is not None: | |
| 944 | self.n = int(n) |
|
943 | self.n = int(n) | |
| 945 | else: |
|
944 | else: | |
| 946 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line |
|
945 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line | |
| 947 | self.n = None |
|
946 | self.n = None | |
| 948 | self.__byTime = True |
|
947 | self.__byTime = True | |
| 949 |
|
948 | |||
| 950 | def putData(self, data_spc, data_cspc, data_dc): |
|
949 | def putData(self, data_spc, data_cspc, data_dc): | |
| 951 |
|
950 | |||
| 952 | """ |
|
951 | """ | |
| 953 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
952 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 954 |
|
953 | |||
| 955 | """ |
|
954 | """ | |
| 956 |
|
955 | |||
| 957 | self.__buffer_spc += data_spc |
|
956 | self.__buffer_spc += data_spc | |
| 958 |
|
957 | |||
| 959 | if data_cspc is None: |
|
958 | if data_cspc is None: | |
| 960 | self.__buffer_cspc = None |
|
959 | self.__buffer_cspc = None | |
| 961 | else: |
|
960 | else: | |
| 962 | self.__buffer_cspc += data_cspc |
|
961 | self.__buffer_cspc += data_cspc | |
| 963 |
|
962 | |||
| 964 | if data_dc is None: |
|
963 | if data_dc is None: | |
| 965 | self.__buffer_dc = None |
|
964 | self.__buffer_dc = None | |
| 966 | else: |
|
965 | else: | |
| 967 | self.__buffer_dc += data_dc |
|
966 | self.__buffer_dc += data_dc | |
| 968 |
|
967 | |||
| 969 | self.__profIndex += 1 |
|
968 | self.__profIndex += 1 | |
| 970 |
|
969 | |||
| 971 | return |
|
970 | return | |
| 972 |
|
971 | |||
| 973 | def pushData(self): |
|
972 | def pushData(self): | |
| 974 | """ |
|
973 | """ | |
| 975 | Return the sum of the last profiles and the profiles used in the sum. |
|
974 | Return the sum of the last profiles and the profiles used in the sum. | |
| 976 |
|
975 | |||
| 977 | Affected: |
|
976 | Affected: | |
| 978 |
|
977 | |||
| 979 | self.__profileIndex |
|
978 | self.__profileIndex | |
| 980 |
|
979 | |||
| 981 | """ |
|
980 | """ | |
| 982 |
|
981 | |||
| 983 | data_spc = self.__buffer_spc |
|
982 | data_spc = self.__buffer_spc | |
| 984 | data_cspc = self.__buffer_cspc |
|
983 | data_cspc = self.__buffer_cspc | |
| 985 | data_dc = self.__buffer_dc |
|
984 | data_dc = self.__buffer_dc | |
| 986 | n = self.__profIndex |
|
985 | n = self.__profIndex | |
| 987 |
|
986 | |||
| 988 | self.__buffer_spc = 0 |
|
987 | self.__buffer_spc = 0 | |
| 989 | self.__buffer_cspc = 0 |
|
988 | self.__buffer_cspc = 0 | |
| 990 | self.__buffer_dc = 0 |
|
989 | self.__buffer_dc = 0 | |
| 991 | self.__profIndex = 0 |
|
990 | self.__profIndex = 0 | |
| 992 |
|
991 | |||
| 993 | return data_spc, data_cspc, data_dc, n |
|
992 | return data_spc, data_cspc, data_dc, n | |
| 994 |
|
993 | |||
| 995 | def byProfiles(self, *args): |
|
994 | def byProfiles(self, *args): | |
| 996 |
|
995 | |||
| 997 | self.__dataReady = False |
|
996 | self.__dataReady = False | |
| 998 | avgdata_spc = None |
|
997 | avgdata_spc = None | |
| 999 | avgdata_cspc = None |
|
998 | avgdata_cspc = None | |
| 1000 | avgdata_dc = None |
|
999 | avgdata_dc = None | |
| 1001 |
|
1000 | |||
| 1002 | self.putData(*args) |
|
1001 | self.putData(*args) | |
| 1003 |
|
1002 | |||
| 1004 | if self.__profIndex == self.n: |
|
1003 | if self.__profIndex == self.n: | |
| 1005 |
|
1004 | |||
| 1006 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
1005 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 1007 | self.n = n |
|
1006 | self.n = n | |
| 1008 | self.__dataReady = True |
|
1007 | self.__dataReady = True | |
| 1009 |
|
1008 | |||
| 1010 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
1009 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1011 |
|
1010 | |||
| 1012 | def byTime(self, datatime, *args): |
|
1011 | def byTime(self, datatime, *args): | |
| 1013 |
|
1012 | |||
| 1014 | self.__dataReady = False |
|
1013 | self.__dataReady = False | |
| 1015 | avgdata_spc = None |
|
1014 | avgdata_spc = None | |
| 1016 | avgdata_cspc = None |
|
1015 | avgdata_cspc = None | |
| 1017 | avgdata_dc = None |
|
1016 | avgdata_dc = None | |
| 1018 |
|
1017 | |||
| 1019 | self.putData(*args) |
|
1018 | self.putData(*args) | |
| 1020 |
|
1019 | |||
| 1021 | if (datatime - self.__initime) >= self.__integrationtime: |
|
1020 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 1022 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
1021 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 1023 | self.n = n |
|
1022 | self.n = n | |
| 1024 | self.__dataReady = True |
|
1023 | self.__dataReady = True | |
| 1025 |
|
1024 | |||
| 1026 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
1025 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1027 |
|
1026 | |||
| 1028 | def integrate(self, datatime, *args): |
|
1027 | def integrate(self, datatime, *args): | |
| 1029 |
|
1028 | |||
| 1030 | if self.__profIndex == 0: |
|
1029 | if self.__profIndex == 0: | |
| 1031 | self.__initime = datatime |
|
1030 | self.__initime = datatime | |
| 1032 |
|
1031 | |||
| 1033 | if self.__byTime: |
|
1032 | if self.__byTime: | |
| 1034 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) |
|
1033 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) | |
| 1035 | else: |
|
1034 | else: | |
| 1036 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
1035 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 1037 |
|
1036 | |||
| 1038 | if not self.__dataReady: |
|
1037 | if not self.__dataReady: | |
| 1039 | return None, None, None, None |
|
1038 | return None, None, None, None | |
| 1040 |
|
1039 | |||
| 1041 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
1040 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1042 |
|
1041 | |||
| 1043 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
1042 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 1044 |
|
1043 | |||
| 1045 | if n==1: |
|
1044 | if n==1: | |
| 1046 | return |
|
1045 | return | |
| 1047 |
|
1046 | |||
| 1048 | dataOut.flagNoData = True |
|
1047 | dataOut.flagNoData = True | |
| 1049 |
|
1048 | |||
| 1050 | if not self.isConfig: |
|
1049 | if not self.isConfig: | |
| 1051 | self.setup(n, timeInterval, overlapping) |
|
1050 | self.setup(n, timeInterval, overlapping) | |
| 1052 | self.isConfig = True |
|
1051 | self.isConfig = True | |
| 1053 |
|
1052 | |||
| 1054 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
1053 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 1055 | dataOut.data_spc, |
|
1054 | dataOut.data_spc, | |
| 1056 | dataOut.data_cspc, |
|
1055 | dataOut.data_cspc, | |
| 1057 | dataOut.data_dc) |
|
1056 | dataOut.data_dc) | |
| 1058 |
|
1057 | |||
| 1059 | if self.__dataReady: |
|
1058 | if self.__dataReady: | |
| 1060 |
|
1059 | |||
| 1061 | dataOut.data_spc = avgdata_spc |
|
1060 | dataOut.data_spc = avgdata_spc | |
| 1062 | dataOut.data_cspc = avgdata_cspc |
|
1061 | dataOut.data_cspc = avgdata_cspc | |
| 1063 | dataOut.data_dc = avgdata_dc |
|
1062 | dataOut.data_dc = avgdata_dc | |
| 1064 |
|
1063 | |||
| 1065 | dataOut.nIncohInt *= self.n |
|
1064 | dataOut.nIncohInt *= self.n | |
| 1066 | dataOut.utctime = avgdatatime |
|
1065 | dataOut.utctime = avgdatatime | |
| 1067 | dataOut.flagNoData = False |
|
1066 | dataOut.flagNoData = False | |
| 1068 |
|
1067 | |||
| @@ -1,1 +1,1 | |||||
| 1 | <Project description="Segundo Test" id="191" name="test01"><ReadUnit datatype="SpectraReader" id="1911" inputId="0" name="SpectraReader"><Operation id="19111" name="run" priority="1" type="self"><Parameter format="str" id="191111" name="datatype" value="SpectraReader" /><Parameter format="str" id="191112" name="path" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdatatest/test1024/d2017234" /><Parameter format="date" id="191113" name="startDate" value="2017/08/22" /><Parameter format="date" id="191114" name="endDate" value="2017/08/22" /><Parameter format="time" id="191115" name="startTime" value="02:00:00" /><Parameter format="time" id="191116" name="endTime" value="06:00:00" /><Parameter format="int" id="191118" name="online" value="0" /><Parameter format="int" id="191119" name="walk" value="0" /></Operation><Operation id="19112" name="printInfo" priority="2" type="self" /><Operation id="19113" name="printNumberOfBlock" priority="3" type="self" /></ReadUnit><ProcUnit datatype="Parameters" id="1913" inputId="1912" name="ParametersProc"><Operation id="19131" name="run" priority="1" type="self" /><Operation id="19132" name="SpectralMoments" priority="2" type="other" /><Operation id="19133" name="FullSpectralAnalysis" priority="3" type="other"><Parameter format="float" id="191331" name="SNRlimit" value="-16" /><Parameter format="float" id="191332" name="E01" value="1.500" /><Parameter format="float" id="191333" name="E02" value="1.500" /><Parameter format="float" id="191334" name="E12" value="0" /><Parameter format="float" id="191335" name="N01" value="0.875" /><Parameter format="float" id="191336" name="N02" value="-0.875" /><Parameter format="float" id="191337" name="N12" value="-1.750" /></Operation><Operation id="19134" name="ParamWriter" priority="4" type="other"><Parameter format="str" id="191341" name="path" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdatatest/test1024" /><Parameter format="int" id="191342" name="blocksPerFile" value="100" /><Parameter format="list" id="191343" name="metadataList" value="heightList,timeZone,paramInterval" /><Parameter format="list" id="191344" name="dataList" value="data_output,data_SNR,utctime,utctimeInit" /></Operation></ProcUnit><ProcUnit datatype="SpectraProc" id="1912" inputId="1911" name="SpectraProc"><Operation id="19121" name="run" priority="1" type="self"><Parameter format="pairslist" id="191211" name="pairsList" value="(0,1),(0,2),(1,2)" /></Operation><Operation id="19122" name="setRadarFrequency" priority="2" type="self"><Parameter format="float" id="191221" name="frequency" value="445.09e6" /></Operation><Operation id="19123" name="IncohInt" priority="3" type="external"><Parameter format="float" id="191231" name="n" value="5" /></Operation><Operation id="19124" name="SpectraPlot" priority="4" type="external"><Parameter format="int" id="191241" name="id" value="11" /><Parameter format="str" id="191242" name="wintitle" value="SpectraPlot" /><Parameter format="str" id="191243" name="xaxis" value="frequency" /><Parameter format="float" id="191244" name="ymin" value="1" /><Parameter format="int" id="191245" name="ymax" value="5" /><Parameter format="int" id="191246" name="zmin" value="15" /><Parameter format="int" id="191247" name="zmax" value="50" /><Parameter format="int" id="191248" name="save" value="2" /><Parameter format="int" id="191249" name="save" value="5" /><Parameter format="str" id="191250" name="figpath" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/Images/FirstResults1024" /></Operation><Operation id="19125" name="CrossSpectraPlot" priority="5" type="other"><Parameter format="int" id="191251" name="id" value="2005" /><Parameter format="str" id="191252" name="wintitle" value="CrossSpectraPlot_ShortPulse" /><Parameter format="str" id="191253" name="xaxis" value="Velocity" /><Parameter format="float" id="191254" name="xmin" value="-10" /><Parameter format="float" id="191255" name="xmax" value="10" /><Parameter format="int" id="191256" name="zmin" value="15" /><Parameter format="int" id="191257" name="zmax" value="50" /><Parameter format="str" id="191258" name="phase_cmap" value="bwr" /><Parameter format="float" id="191259" name="ymin" value="1" /><Parameter format="float" id="191260" name="ymax" value="5" /></Operation></ProcUnit></Project> No newline at end of file |
|
1 | <Project description="Segundo Test" id="191" name="test01"><ReadUnit datatype="SpectraReader" id="1911" inputId="0" name="SpectraReader"><Operation id="19111" name="run" priority="1" type="self"><Parameter format="str" id="191111" name="datatype" value="SpectraReader" /><Parameter format="str" id="191112" name="path" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdataCLAIRE/Extra" /><Parameter format="date" id="191113" name="startDate" value="2018/02/01" /><Parameter format="date" id="191114" name="endDate" value="2018/02/01" /><Parameter format="time" id="191115" name="startTime" value="17:00:00" /><Parameter format="time" id="191116" name="endTime" value="20:00:00" /><Parameter format="int" id="191118" name="online" value="0" /><Parameter format="int" id="191119" name="walk" value="1" /></Operation><Operation id="19112" name="printInfo" priority="2" type="self" /><Operation id="19113" name="printNumberOfBlock" priority="3" type="self" /></ReadUnit><ProcUnit datatype="Parameters" id="1913" inputId="1912" name="ParametersProc"><Operation id="19131" name="run" priority="1" type="self" /><Operation id="19132" name="SpectralFilters" priority="2" type="other"><Parameter format="float" id="191321" name="Wind_Velocity_Limit" value="2.5" /><Parameter format="float" id="191322" name="Rain_Velocity_Limit" value="1.5" /></Operation><Operation id="19133" name="FullSpectralAnalysis" priority="3" type="other"><Parameter format="float" id="191331" name="SNRlimit" value="-16" /><Parameter format="float" id="191332" name="E01" value="1.500" /><Parameter format="float" id="191333" name="E02" value="1.500" /><Parameter format="float" id="191334" name="E12" value="0" /><Parameter format="float" id="191335" name="N01" value="0.875" /><Parameter format="float" id="191336" name="N02" value="-0.875" /><Parameter format="float" id="191337" name="N12" value="-1.750" /></Operation><Operation id="19134" name="WindProfilerPlot" priority="4" type="other"><Parameter format="int" id="191341" name="id" value="4" /><Parameter format="str" id="191342" name="wintitle" value="Wind Profiler" /><Parameter format="float" id="191343" name="xmin" value="17" /><Parameter format="float" id="191344" name="xmax" value="20" /><Parameter format="float" id="191345" name="ymin" value="0" /><Parameter format="int" id="191346" name="ymax" value="8" /><Parameter format="float" id="191347" name="zmin" value="-20" /><Parameter format="float" id="191348" name="zmax" value="20" /><Parameter format="float" id="191349" name="SNRmin" value="-20" /><Parameter format="float" id="191350" name="SNRmax" value="20" /><Parameter format="float" id="191351" name="zmin_ver" value="-200" /><Parameter format="float" id="191352" name="zmax_ver" value="200" /><Parameter format="float" id="191353" name="SNRthresh" value="-20" /><Parameter format="int" id="191354" name="save" value="1" /><Parameter format="str" id="191355" name="figpath" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdataCLAIRE/Extra" /></Operation><Operation id="19135" name="PrecipitationProc" priority="5" type="other" /><Operation id="19136" name="ParametersPlot" priority="6" type="other"><Parameter format="int" id="191361" name="id" value="10" /><Parameter format="str" id="191362" name="wintitle" value="First_gg" /><Parameter format="int" id="191363" name="zmin" value="-20" /><Parameter format="int" id="191364" name="zmax" value="60" /><Parameter format="int" id="191365" name="ymin" value="0" /><Parameter format="int" id="191366" name="ymax" value="8" /><Parameter format="int" id="191367" name="xmin" value="17" /><Parameter format="int" id="191368" name="xmax" value="20" /><Parameter format="int" id="191369" name="save" value="1" /><Parameter format="str" id="191370" name="figpath" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdataCLAIRE/Extra" /></Operation><Operation id="19137" name="ParamWriter" priority="7" type="other"><Parameter format="str" id="191371" name="path" value="/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdatatest/test1024" /><Parameter format="int" id="191372" name="blocksPerFile" value="100" /><Parameter format="list" id="191373" name="metadataList" value="heightList,timeZone,paramInterval" /><Parameter format="list" id="191374" name="dataList" value="data_output,data_SNR,utctime,utctimeInit" /></Operation></ProcUnit><ProcUnit datatype="SpectraProc" id="1912" inputId="1911" name="SpectraProc"><Operation id="19121" name="run" priority="1" type="self" /><Operation id="19122" name="setRadarFrequency" priority="2" type="self"><Parameter format="float" id="191221" name="frequency" value="445.09e6" /></Operation></ProcUnit></Project> No newline at end of file | |
| @@ -1,238 +1,239 | |||||
| 1 | import os, sys |
|
1 | import os, sys | |
| 2 |
|
2 | |||
| 3 | from schainpy.controller import Project |
|
3 | from schainpy.controller import Project | |
| 4 |
|
4 | |||
| 5 | if __name__ == '__main__': |
|
5 | if __name__ == '__main__': | |
| 6 |
|
6 | |||
| 7 | desc = "Segundo Test" |
|
7 | desc = "Segundo Test" | |
| 8 | filename = "schain.xml" |
|
8 | filename = "schain.xml" | |
| 9 |
|
9 | |||
| 10 |
pathW='/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdata |
|
10 | pathW='/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdataCLAIRE/Extra' | |
| 11 |
figpath = '/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/ |
|
11 | figpath = '/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/pdataCLAIRE/Extra' | |
| 12 |
|
12 | |||
| 13 | controllerObj = Project() |
|
13 | controllerObj = Project() | |
| 14 |
|
14 | |||
| 15 | controllerObj.setup(id='191', name='test01', description=desc) |
|
15 | controllerObj.setup(id='191', name='test01', description=desc) | |
| 16 |
|
16 | |||
| 17 | readUnitConfObj = controllerObj.addReadUnit(datatype='VoltageReader', |
|
17 | readUnitConfObj = controllerObj.addReadUnit(datatype='VoltageReader', | |
| 18 | path='/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/', |
|
18 | path='/media/erick/6F60F7113095A154/CLAIRE/CLAIRE_WINDS_2MHZ/DATA/', | |
| 19 | #path='/home/erick/Documents/Data/Claire_Data/raw', |
|
19 | #path='/home/erick/Documents/Data/Claire_Data/raw', | |
| 20 |
startDate='201 |
|
20 | startDate='2018/02/01', | |
| 21 |
endDate='201 |
|
21 | endDate='2018/02/01', | |
| 22 |
startTime=' |
|
22 | startTime='12:00:00', | |
| 23 |
endTime='0 |
|
23 | endTime='20:00:00', | |
| 24 | online=0, |
|
24 | online=0, | |
| 25 | walk=1) |
|
25 | walk=1) | |
| 26 |
|
26 | |||
| 27 | opObj00 = readUnitConfObj.addOperation(name='printInfo') |
|
27 | opObj00 = readUnitConfObj.addOperation(name='printInfo') | |
| 28 | # |
|
28 | # | |
| 29 | # procUnitConfObj0 = controllerObj.addProcUnit(datatype='VoltageProc', |
|
29 | # procUnitConfObj0 = controllerObj.addProcUnit(datatype='VoltageProc', | |
| 30 | # inputId=readUnitConfObj.getId()) |
|
30 | # inputId=readUnitConfObj.getId()) | |
| 31 | # |
|
31 | # | |
| 32 | # opObj10 = procUnitConfObj0.addOperation(name='selectHeights') |
|
32 | # opObj10 = procUnitConfObj0.addOperation(name='selectHeights') | |
| 33 | # opObj10.addParameter(name='minHei', value='0', format='float') |
|
33 | # opObj10.addParameter(name='minHei', value='0', format='float') | |
| 34 | # opObj10.addParameter(name='maxHei', value='8', format='float') |
|
34 | # opObj10.addParameter(name='maxHei', value='8', format='float') | |
| 35 | # |
|
35 | # | |
| 36 | # opObj10 = procUnitConfObj0.addOperation(name='filterByHeights') |
|
36 | # opObj10 = procUnitConfObj0.addOperation(name='filterByHeights') | |
| 37 | # opObj10.addParameter(name='window', value='2', format='float') |
|
37 | # opObj10.addParameter(name='window', value='2', format='float') | |
| 38 | # |
|
38 | # | |
| 39 | # opObj10 = procUnitConfObj0.addOperation(name='Decoder', optype='external') |
|
39 | # opObj10 = procUnitConfObj0.addOperation(name='Decoder', optype='external') | |
| 40 | # opObj10.addParameter(name='code', value='1,-1', format='intlist') |
|
40 | # opObj10.addParameter(name='code', value='1,-1', format='intlist') | |
| 41 | # opObj10.addParameter(name='nCode', value='2', format='float') |
|
41 | # opObj10.addParameter(name='nCode', value='2', format='float') | |
| 42 | # opObj10.addParameter(name='nBaud', value='1', format='float') |
|
42 | # opObj10.addParameter(name='nBaud', value='1', format='float') | |
| 43 | # |
|
43 | # | |
| 44 | # |
|
44 | # | |
| 45 | # opObj10 = procUnitConfObj0.addOperation(name='CohInt', optype='external') |
|
45 | # opObj10 = procUnitConfObj0.addOperation(name='CohInt', optype='external') | |
| 46 | # opObj10.addParameter(name='n', value='1296', format='float') |
|
46 | # opObj10.addParameter(name='n', value='1296', format='float') | |
| 47 |
|
47 | |||
| 48 | opObj00 = readUnitConfObj.addOperation(name='printNumberOfBlock') |
|
48 | opObj00 = readUnitConfObj.addOperation(name='printNumberOfBlock') | |
| 49 |
|
49 | |||
| 50 | procUnitConfObj0 = controllerObj.addProcUnit(datatype='VoltageProc', |
|
50 | procUnitConfObj0 = controllerObj.addProcUnit(datatype='VoltageProc', | |
| 51 | inputId=readUnitConfObj.getId()) |
|
51 | inputId=readUnitConfObj.getId()) | |
| 52 |
|
52 | |||
| 53 |
|
53 | |||
| 54 | opObj10 = procUnitConfObj0.addOperation(name='setRadarFrequency') |
|
54 | opObj10 = procUnitConfObj0.addOperation(name='setRadarFrequency') | |
| 55 | opObj10.addParameter(name='frequency', value='445.09e6', format='float') |
|
55 | opObj10.addParameter(name='frequency', value='445.09e6', format='float') | |
| 56 |
|
56 | |||
| 57 |
|
|
57 | opObj10 = procUnitConfObj0.addOperation(name='CohInt', optype='external') | |
| 58 |
|
|
58 | opObj10.addParameter(name='n', value='2', format='float') | |
| 59 |
|
59 | |||
| 60 | #opObj10 = procUnitConfObj0.addOperation(name='selectHeights') |
|
60 | #opObj10 = procUnitConfObj0.addOperation(name='selectHeights') | |
| 61 | #opObj10.addParameter(name='minHei', value='1', format='float') |
|
61 | #opObj10.addParameter(name='minHei', value='1', format='float') | |
| 62 | #opObj10.addParameter(name='maxHei', value='15', format='float') |
|
62 | #opObj10.addParameter(name='maxHei', value='15', format='float') | |
| 63 |
|
63 | |||
| 64 | #opObj10 = procUnitConfObj0.addOperation(name='selectFFTs') |
|
64 | #opObj10 = procUnitConfObj0.addOperation(name='selectFFTs') | |
| 65 | #opObj10.addParameter(name='minHei', value='', format='float') |
|
65 | #opObj10.addParameter(name='minHei', value='', format='float') | |
| 66 | #opObj10.addParameter(name='maxHei', value='', format='float') |
|
66 | #opObj10.addParameter(name='maxHei', value='', format='float') | |
| 67 |
|
67 | |||
| 68 | procUnitConfObj1 = controllerObj.addProcUnit(datatype='SpectraProc', |
|
68 | procUnitConfObj1 = controllerObj.addProcUnit(datatype='SpectraProc', | |
| 69 | inputId=procUnitConfObj0.getId()) |
|
69 | inputId=procUnitConfObj0.getId()) | |
| 70 |
|
70 | |||
| 71 | # Creating a processing object with its parameters |
|
71 | # Creating a processing object with its parameters | |
| 72 | # schainpy.model.proc.jroproc_spectra.SpectraProc.run() |
|
72 | # schainpy.model.proc.jroproc_spectra.SpectraProc.run() | |
| 73 | # If you need to add more parameters can use the "addParameter method" |
|
73 | # If you need to add more parameters can use the "addParameter method" | |
| 74 |
procUnitConfObj1.addParameter(name='nFFTPoints', value=' |
|
74 | procUnitConfObj1.addParameter(name='nFFTPoints', value='256', format='int') | |
| 75 |
|
75 | |||
| 76 |
|
76 | |||
| 77 | opObj10 = procUnitConfObj1.addOperation(name='removeDC') |
|
77 | opObj10 = procUnitConfObj1.addOperation(name='removeDC') | |
| 78 | #opObj10 = procUnitConfObj1.addOperation(name='removeInterference') |
|
78 | #opObj10 = procUnitConfObj1.addOperation(name='removeInterference') | |
| 79 |
|
|
79 | opObj10 = procUnitConfObj1.addOperation(name='IncohInt', optype='external') | |
| 80 |
|
|
80 | opObj10.addParameter(name='n', value='10', format='float') | |
| 81 |
|
81 | |||
| 82 |
|
82 | |||
| 83 |
|
83 | |||
| 84 | #opObj10 = procUnitConfObj1.addOperation(name='selectFFTs') |
|
84 | #opObj10 = procUnitConfObj1.addOperation(name='selectFFTs') | |
| 85 | #opObj10.addParameter(name='minFFT', value='-15', format='float') |
|
85 | #opObj10.addParameter(name='minFFT', value='-15', format='float') | |
| 86 | #opObj10.addParameter(name='maxFFT', value='15', format='float') |
|
86 | #opObj10.addParameter(name='maxFFT', value='15', format='float') | |
| 87 |
|
87 | |||
| 88 |
|
88 | |||
| 89 |
|
89 | |||
| 90 | opObj10 = procUnitConfObj1.addOperation(name='SpectraWriter', optype='other') |
|
90 | opObj10 = procUnitConfObj1.addOperation(name='SpectraWriter', optype='other') | |
| 91 | opObj10.addParameter(name='blocksPerFile', value='64', format = 'int') |
|
91 | opObj10.addParameter(name='blocksPerFile', value='64', format = 'int') | |
| 92 | opObj10.addParameter(name='path', value=pathW) |
|
92 | opObj10.addParameter(name='path', value=pathW) | |
| 93 | # Using internal methods |
|
93 | # Using internal methods | |
| 94 | # schainpy.model.proc.jroproc_spectra.SpectraProc.selectChannels() |
|
94 | # schainpy.model.proc.jroproc_spectra.SpectraProc.selectChannels() | |
| 95 | # opObj10 = procUnitConfObj1.addOperation(name='selectChannels') |
|
95 | # opObj10 = procUnitConfObj1.addOperation(name='selectChannels') | |
| 96 | # opObj10.addParameter(name='channelList', value='0,1', format='intlist') |
|
96 | # opObj10.addParameter(name='channelList', value='0,1', format='intlist') | |
| 97 |
|
97 | |||
| 98 | # Using internal methods |
|
98 | # Using internal methods | |
| 99 | # schainpy.model.proc.jroproc_spectra.SpectraProc.selectHeights() |
|
99 | # schainpy.model.proc.jroproc_spectra.SpectraProc.selectHeights() | |
| 100 | # opObj10 = procUnitConfObj1.addOperation(name='selectHeights') |
|
100 | # opObj10 = procUnitConfObj1.addOperation(name='selectHeights') | |
| 101 | # opObj10.addParameter(name='minHei', value='90', format='float') |
|
101 | # opObj10.addParameter(name='minHei', value='90', format='float') | |
| 102 | # opObj10.addParameter(name='maxHei', value='180', format='float') |
|
102 | # opObj10.addParameter(name='maxHei', value='180', format='float') | |
| 103 |
|
103 | |||
| 104 | # Using external methods (new modules) |
|
104 | # Using external methods (new modules) | |
| 105 | # #schainpy.model.proc.jroproc_spectra.IncohInt.setup() |
|
105 | # #schainpy.model.proc.jroproc_spectra.IncohInt.setup() | |
| 106 | # opObj12 = procUnitConfObj1.addOperation(name='IncohInt', optype='other') |
|
106 | # opObj12 = procUnitConfObj1.addOperation(name='IncohInt', optype='other') | |
| 107 | # opObj12.addParameter(name='n', value='1', format='int') |
|
107 | # opObj12.addParameter(name='n', value='1', format='int') | |
| 108 |
|
108 | |||
| 109 | # Using external methods (new modules) |
|
109 | # Using external methods (new modules) | |
| 110 | # schainpy.model.graphics.jroplot_spectra.SpectraPlot.setup() |
|
110 | # schainpy.model.graphics.jroplot_spectra.SpectraPlot.setup() | |
| 111 | opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='external') |
|
111 | opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='external') | |
| 112 | opObj11.addParameter(name='id', value='11', format='int') |
|
112 | opObj11.addParameter(name='id', value='11', format='int') | |
| 113 | opObj11.addParameter(name='wintitle', value='SpectraPlot', format='str') |
|
113 | opObj11.addParameter(name='wintitle', value='SpectraPlot', format='str') | |
| 114 | opObj11.addParameter(name='xaxis', value='velocity', format='str') |
|
114 | opObj11.addParameter(name='xaxis', value='velocity', format='str') | |
| 115 | # opObj11.addParameter(name='xmin', value='-10', format='int') |
|
115 | # opObj11.addParameter(name='xmin', value='-10', format='int') | |
| 116 | # opObj11.addParameter(name='xmax', value='10', format='int') |
|
116 | # opObj11.addParameter(name='xmax', value='10', format='int') | |
| 117 |
|
117 | |||
| 118 | # opObj11.addParameter(name='ymin', value='1', format='float') |
|
118 | # opObj11.addParameter(name='ymin', value='1', format='float') | |
| 119 | # opObj11.addParameter(name='ymax', value='3', format='int') |
|
119 | # opObj11.addParameter(name='ymax', value='3', format='int') | |
| 120 | #opObj11.addParameter(name='zmin', value='10', format='int') |
|
120 | #opObj11.addParameter(name='zmin', value='10', format='int') | |
| 121 | #opObj11.addParameter(name='zmax', value='35', format='int') |
|
121 | #opObj11.addParameter(name='zmax', value='35', format='int') | |
| 122 | # opObj11.addParameter(name='save', value='2', format='int') |
|
122 | # opObj11.addParameter(name='save', value='2', format='int') | |
| 123 | # opObj11.addParameter(name='save', value='5', format='int') |
|
123 | # opObj11.addParameter(name='save', value='5', format='int') | |
| 124 | # opObj11.addParameter(name='figpath', value=figpath, format='str') |
|
124 | # opObj11.addParameter(name='figpath', value=figpath, format='str') | |
| 125 |
|
125 | |||
| 126 |
|
126 | |||
| 127 | opObj11 = procUnitConfObj1.addOperation(name='CrossSpectraPlot', optype='other') |
|
127 | opObj11 = procUnitConfObj1.addOperation(name='CrossSpectraPlot', optype='other') | |
| 128 | procUnitConfObj1.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList') |
|
128 | procUnitConfObj1.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList') | |
| 129 | opObj11.addParameter(name='id', value='2005', format='int') |
|
129 | opObj11.addParameter(name='id', value='2005', format='int') | |
| 130 | #opObj11.addParameter(name='wintitle', value='CrossSpectraPlot_ShortPulse', format='str') |
|
130 | #opObj11.addParameter(name='wintitle', value='CrossSpectraPlot_ShortPulse', format='str') | |
| 131 | #opObj11.addParameter(name='exp_code', value='13', format='int') |
|
131 | #opObj11.addParameter(name='exp_code', value='13', format='int') | |
| 132 | opObj11.addParameter(name='xaxis', value='Velocity', format='str') |
|
132 | opObj11.addParameter(name='xaxis', value='Velocity', format='str') | |
| 133 | #opObj11.addParameter(name='xmin', value='-6', format='float') |
|
133 | #opObj11.addParameter(name='xmin', value='-6', format='float') | |
| 134 | #opObj11.addParameter(name='xmax', value='6', format='float') |
|
134 | #opObj11.addParameter(name='xmax', value='6', format='float') | |
| 135 | opObj11.addParameter(name='zmin', value='15', format='float') |
|
135 | opObj11.addParameter(name='zmin', value='15', format='float') | |
| 136 | opObj11.addParameter(name='zmax', value='50', format='float') |
|
136 | opObj11.addParameter(name='zmax', value='50', format='float') | |
| 137 | opObj11.addParameter(name='ymin', value='0', format='float') |
|
137 | opObj11.addParameter(name='ymin', value='0', format='float') | |
| 138 | opObj11.addParameter(name='ymax', value='7', format='float') |
|
138 | opObj11.addParameter(name='ymax', value='7', format='float') | |
| 139 | #opObj11.addParameter(name='phase_min', value='-4', format='int') |
|
139 | #opObj11.addParameter(name='phase_min', value='-4', format='int') | |
| 140 | #opObj11.addParameter(name='phase_max', value='4', format='int') |
|
140 | #opObj11.addParameter(name='phase_max', value='4', format='int') | |
| 141 | # |
|
141 | # | |
| 142 |
|
142 | |||
| 143 | # Using external methods (new modules) |
|
143 | # Using external methods (new modules) | |
| 144 | # schainpy.model.graphics.jroplot_spectra.RTIPlot.setup() |
|
144 | # schainpy.model.graphics.jroplot_spectra.RTIPlot.setup() | |
| 145 | opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other') |
|
145 | opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other') | |
| 146 | opObj11.addParameter(name='id', value='30', format='int') |
|
146 | opObj11.addParameter(name='id', value='30', format='int') | |
| 147 | opObj11.addParameter(name='wintitle', value='RTI', format='str') |
|
147 | opObj11.addParameter(name='wintitle', value='RTI', format='str') | |
| 148 | opObj11.addParameter(name='zmin', value='15', format='int') |
|
148 | opObj11.addParameter(name='zmin', value='15', format='int') | |
| 149 | opObj11.addParameter(name='zmax', value='40', format='int') |
|
149 | opObj11.addParameter(name='zmax', value='40', format='int') | |
| 150 | opObj11.addParameter(name='ymin', value='1', format='int') |
|
150 | opObj11.addParameter(name='ymin', value='1', format='int') | |
| 151 | opObj11.addParameter(name='ymax', value='7', format='int') |
|
151 | opObj11.addParameter(name='ymax', value='7', format='int') | |
| 152 | opObj11.addParameter(name='showprofile', value='1', format='int') |
|
152 | opObj11.addParameter(name='showprofile', value='1', format='int') | |
| 153 | # opObj11.addParameter(name='timerange', value=str(5*60*60*60), format='int') |
|
153 | # opObj11.addParameter(name='timerange', value=str(5*60*60*60), format='int') | |
| 154 | opObj11.addParameter(name='xmin', value='1', format='float') |
|
154 | #opObj11.addParameter(name='xmin', value='1', format='float') | |
| 155 | opObj11.addParameter(name='xmax', value='6', format='float') |
|
155 | #opObj11.addParameter(name='xmax', value='6', format='float') | |
| 156 | opObj11.addParameter(name='save', value='1', format='int') |
|
156 | opObj11.addParameter(name='save', value='1', format='int') | |
|
|
157 | opObj11.addParameter(name='figpath', value=figpath, format='str') | |||
| 157 |
|
158 | |||
| 158 |
|
159 | |||
| 159 | # '''#########################################################################################''' |
|
160 | # '''#########################################################################################''' | |
| 160 | # |
|
161 | # | |
| 161 | # |
|
162 | # | |
| 162 | # procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=procUnitConfObj1.getId()) |
|
163 | # procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=procUnitConfObj1.getId()) | |
| 163 | # opObj11 = procUnitConfObj2.addOperation(name='SpectralMoments', optype='other') |
|
164 | # opObj11 = procUnitConfObj2.addOperation(name='SpectralMoments', optype='other') | |
| 164 | # |
|
165 | # | |
| 165 | # ''' |
|
166 | # ''' | |
| 166 | # # Discriminacion de ecos |
|
167 | # # Discriminacion de ecos | |
| 167 | # opObj11 = procUnitConfObj2.addOperation(name='GaussianFit', optype='other') |
|
168 | # opObj11 = procUnitConfObj2.addOperation(name='GaussianFit', optype='other') | |
| 168 | # opObj11.addParameter(name='SNRlimit', value='0', format='int') |
|
169 | # opObj11.addParameter(name='SNRlimit', value='0', format='int') | |
| 169 | # ''' |
|
170 | # ''' | |
| 170 | # |
|
171 | # | |
| 171 | # ''' |
|
172 | # ''' | |
| 172 | # # Estimacion de Precipitacion |
|
173 | # # Estimacion de Precipitacion | |
| 173 | # opObj11 = procUnitConfObj2.addOperation(name='PrecipitationProc', optype='other') |
|
174 | # opObj11 = procUnitConfObj2.addOperation(name='PrecipitationProc', optype='other') | |
| 174 | # ''' |
|
175 | # ''' | |
| 175 | # |
|
176 | # | |
| 176 | # opObj22 = procUnitConfObj2.addOperation(name='FullSpectralAnalysis', optype='other') |
|
177 | # opObj22 = procUnitConfObj2.addOperation(name='FullSpectralAnalysis', optype='other') | |
| 177 | # |
|
178 | # | |
| 178 | # opObj22.addParameter(name='SNRlimit', value='-10', format='float') |
|
179 | # opObj22.addParameter(name='SNRlimit', value='-10', format='float') | |
| 179 | # opObj22.addParameter(name='E01', value='1.500', format='float') |
|
180 | # opObj22.addParameter(name='E01', value='1.500', format='float') | |
| 180 | # opObj22.addParameter(name='E02', value='1.500', format='float') |
|
181 | # opObj22.addParameter(name='E02', value='1.500', format='float') | |
| 181 | # opObj22.addParameter(name='E12', value='0', format='float') |
|
182 | # opObj22.addParameter(name='E12', value='0', format='float') | |
| 182 | # opObj22.addParameter(name='N01', value='0.875', format='float') |
|
183 | # opObj22.addParameter(name='N01', value='0.875', format='float') | |
| 183 | # opObj22.addParameter(name='N02', value='-0.875', format='float') |
|
184 | # opObj22.addParameter(name='N02', value='-0.875', format='float') | |
| 184 | # opObj22.addParameter(name='N12', value='-1.750', format='float') |
|
185 | # opObj22.addParameter(name='N12', value='-1.750', format='float') | |
| 185 | # |
|
186 | # | |
| 186 | # |
|
187 | # | |
| 187 | # opObj22 = procUnitConfObj2.addOperation(name='WindProfilerPlot', optype='other') |
|
188 | # opObj22 = procUnitConfObj2.addOperation(name='WindProfilerPlot', optype='other') | |
| 188 | # opObj22.addParameter(name='id', value='4', format='int') |
|
189 | # opObj22.addParameter(name='id', value='4', format='int') | |
| 189 | # opObj22.addParameter(name='wintitle', value='Wind Profiler', format='str') |
|
190 | # opObj22.addParameter(name='wintitle', value='Wind Profiler', format='str') | |
| 190 | # opObj22.addParameter(name='save', value='1', format='bool') |
|
191 | # opObj22.addParameter(name='save', value='1', format='bool') | |
| 191 | # opObj22.addParameter(name='xmin', value='0', format='float') |
|
192 | # opObj22.addParameter(name='xmin', value='0', format='float') | |
| 192 | # opObj22.addParameter(name='xmax', value='6', format='float') |
|
193 | # opObj22.addParameter(name='xmax', value='6', format='float') | |
| 193 | # opObj22.addParameter(name='ymin', value='1', format='float') |
|
194 | # opObj22.addParameter(name='ymin', value='1', format='float') | |
| 194 | # opObj22.addParameter(name='ymax', value='3.5', format='float') |
|
195 | # opObj22.addParameter(name='ymax', value='3.5', format='float') | |
| 195 | # opObj22.addParameter(name='zmin', value='-1', format='float') |
|
196 | # opObj22.addParameter(name='zmin', value='-1', format='float') | |
| 196 | # opObj22.addParameter(name='zmax', value='1', format='float') |
|
197 | # opObj22.addParameter(name='zmax', value='1', format='float') | |
| 197 | # opObj22.addParameter(name='SNRmin', value='-15', format='float') |
|
198 | # opObj22.addParameter(name='SNRmin', value='-15', format='float') | |
| 198 | # opObj22.addParameter(name='SNRmax', value='20', format='float') |
|
199 | # opObj22.addParameter(name='SNRmax', value='20', format='float') | |
| 199 | # opObj22.addParameter(name='zmin_ver', value='-200', format='float') |
|
200 | # opObj22.addParameter(name='zmin_ver', value='-200', format='float') | |
| 200 | # opObj22.addParameter(name='zmax_ver', value='200', format='float') |
|
201 | # opObj22.addParameter(name='zmax_ver', value='200', format='float') | |
| 201 | # opObj22.addParameter(name='save', value='1', format='int') |
|
202 | # opObj22.addParameter(name='save', value='1', format='int') | |
| 202 | # opObj22.addParameter(name='figpath', value=figpath, format='str') |
|
203 | # opObj22.addParameter(name='figpath', value=figpath, format='str') | |
| 203 | # |
|
204 | # | |
| 204 | # |
|
205 | # | |
| 205 | # |
|
206 | # | |
| 206 | # #opObj11.addParameter(name='zmin', value='75', format='int') |
|
207 | # #opObj11.addParameter(name='zmin', value='75', format='int') | |
| 207 | # |
|
208 | # | |
| 208 | # #opObj12 = procUnitConfObj2.addOperation(name='ParametersPlot', optype='other') |
|
209 | # #opObj12 = procUnitConfObj2.addOperation(name='ParametersPlot', optype='other') | |
| 209 | # #opObj12.addParameter(name='id',value='4',format='int') |
|
210 | # #opObj12.addParameter(name='id',value='4',format='int') | |
| 210 | # #opObj12.addParameter(name='wintitle',value='First_gg',format='str') |
|
211 | # #opObj12.addParameter(name='wintitle',value='First_gg',format='str') | |
| 211 | # ''' |
|
212 | # ''' | |
| 212 | # #Ploteo de Discriminacion de Gaussianas |
|
213 | # #Ploteo de Discriminacion de Gaussianas | |
| 213 | # |
|
214 | # | |
| 214 | # opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other') |
|
215 | # opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other') | |
| 215 | # opObj11.addParameter(name='id', value='21', format='int') |
|
216 | # opObj11.addParameter(name='id', value='21', format='int') | |
| 216 | # opObj11.addParameter(name='wintitle', value='Rainfall Gaussian', format='str') |
|
217 | # opObj11.addParameter(name='wintitle', value='Rainfall Gaussian', format='str') | |
| 217 | # opObj11.addParameter(name='xaxis', value='velocity', format='str') |
|
218 | # opObj11.addParameter(name='xaxis', value='velocity', format='str') | |
| 218 | # opObj11.addParameter(name='showprofile', value='1', format='int') |
|
219 | # opObj11.addParameter(name='showprofile', value='1', format='int') | |
| 219 | # opObj11.addParameter(name='zmin', value='75', format='int') |
|
220 | # opObj11.addParameter(name='zmin', value='75', format='int') | |
| 220 | # opObj11.addParameter(name='zmax', value='100', format='int') |
|
221 | # opObj11.addParameter(name='zmax', value='100', format='int') | |
| 221 | # opObj11.addParameter(name='GauSelector', value='1', format='int') |
|
222 | # opObj11.addParameter(name='GauSelector', value='1', format='int') | |
| 222 | # #opObj11.addParameter(name='save', value='1', format='int') |
|
223 | # #opObj11.addParameter(name='save', value='1', format='int') | |
| 223 | # #opObj11.addParameter(name='figpath', value='/home/erick/Documents/Data/d2015106') |
|
224 | # #opObj11.addParameter(name='figpath', value='/home/erick/Documents/Data/d2015106') | |
| 224 | # |
|
225 | # | |
| 225 | # opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other') |
|
226 | # opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other') | |
| 226 | # opObj11.addParameter(name='id', value='22', format='int') |
|
227 | # opObj11.addParameter(name='id', value='22', format='int') | |
| 227 | # opObj11.addParameter(name='wintitle', value='Wind Gaussian', format='str') |
|
228 | # opObj11.addParameter(name='wintitle', value='Wind Gaussian', format='str') | |
| 228 | # opObj11.addParameter(name='xaxis', value='velocity', format='str') |
|
229 | # opObj11.addParameter(name='xaxis', value='velocity', format='str') | |
| 229 | # opObj11.addParameter(name='showprofile', value='1', format='int') |
|
230 | # opObj11.addParameter(name='showprofile', value='1', format='int') | |
| 230 | # opObj11.addParameter(name='zmin', value='75', format='int') |
|
231 | # opObj11.addParameter(name='zmin', value='75', format='int') | |
| 231 | # opObj11.addParameter(name='zmax', value='100', format='int') |
|
232 | # opObj11.addParameter(name='zmax', value='100', format='int') | |
| 232 | # opObj11.addParameter(name='GauSelector', value='0', format='int') |
|
233 | # opObj11.addParameter(name='GauSelector', value='0', format='int') | |
| 233 | # ''' |
|
234 | # ''' | |
| 234 | # |
|
235 | # | |
| 235 | # |
|
236 | # | |
| 236 |
|
237 | |||
| 237 |
|
238 | |||
| 238 | controllerObj.start() |
|
239 | controllerObj.start() | |
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