| @@ -1,906 +1,902 | |||||
| 1 | import itertools |
|
1 | import itertools | |
| 2 |
|
2 | |||
| 3 | import numpy |
|
3 | import numpy | |
| 4 |
|
4 | |||
| 5 | from jroproc_base import ProcessingUnit, Operation |
|
5 | from jroproc_base import ProcessingUnit, Operation | |
| 6 | from schainpy.model.data.jrodata import Spectra |
|
6 | from schainpy.model.data.jrodata import Spectra | |
| 7 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
7 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 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 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
75 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 76 | dc = fft_volt[:,0,:] |
|
76 | dc = fft_volt[:,0,:] | |
| 77 |
|
77 | |||
| 78 | #calculo de self-spectra |
|
78 | #calculo de self-spectra | |
| 79 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) |
|
79 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) | |
| 80 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
80 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 81 | spc = spc.real |
|
81 | spc = spc.real | |
| 82 |
|
82 | |||
| 83 | blocksize = 0 |
|
83 | blocksize = 0 | |
| 84 | blocksize += dc.size |
|
84 | blocksize += dc.size | |
| 85 | blocksize += spc.size |
|
85 | blocksize += spc.size | |
| 86 |
|
86 | |||
| 87 | cspc = None |
|
87 | cspc = None | |
| 88 | pairIndex = 0 |
|
88 | pairIndex = 0 | |
| 89 | if self.dataOut.pairsList != None: |
|
89 | if self.dataOut.pairsList != None: | |
| 90 | #calculo de cross-spectra |
|
90 | #calculo de cross-spectra | |
| 91 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
91 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 92 | for pair in self.dataOut.pairsList: |
|
92 | for pair in self.dataOut.pairsList: | |
| 93 | if pair[0] not in self.dataOut.channelList: |
|
93 | if pair[0] not in self.dataOut.channelList: | |
| 94 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
94 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 95 | if pair[1] not in self.dataOut.channelList: |
|
95 | if pair[1] not in self.dataOut.channelList: | |
| 96 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
96 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 97 |
|
97 | |||
| 98 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) |
|
98 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) | |
| 99 | pairIndex += 1 |
|
99 | pairIndex += 1 | |
| 100 | blocksize += cspc.size |
|
100 | blocksize += cspc.size | |
| 101 |
|
101 | |||
| 102 | self.dataOut.data_spc = spc |
|
102 | self.dataOut.data_spc = spc | |
| 103 | self.dataOut.data_cspc = cspc |
|
103 | self.dataOut.data_cspc = cspc | |
| 104 | self.dataOut.data_dc = dc |
|
104 | self.dataOut.data_dc = dc | |
| 105 | self.dataOut.blockSize = blocksize |
|
105 | self.dataOut.blockSize = blocksize | |
| 106 | self.dataOut.flagShiftFFT = True |
|
106 | self.dataOut.flagShiftFFT = True | |
| 107 |
|
107 | |||
| 108 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): |
|
108 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): | |
| 109 |
|
109 | |||
| 110 | self.dataOut.flagNoData = True |
|
110 | self.dataOut.flagNoData = True | |
| 111 |
|
111 | |||
| 112 | if self.dataIn.type == "Spectra": |
|
112 | if self.dataIn.type == "Spectra": | |
| 113 | self.dataOut.copy(self.dataIn) |
|
113 | self.dataOut.copy(self.dataIn) | |
| 114 | <<<<<<< HEAD |
|
|||
| 115 | # self.__selectPairs(pairsList) |
|
|||
| 116 | ======= |
|
|||
| 117 | if not pairsList: |
|
114 | if not pairsList: | |
| 118 | pairsList = itertools.combinations(self.dataOut.channelList, 2) |
|
115 | pairsList = itertools.combinations(self.dataOut.channelList, 2) | |
| 119 | if self.dataOut.data_cspc is not None: |
|
116 | if self.dataOut.data_cspc is not None: | |
| 120 | self.__selectPairs(pairsList) |
|
117 | self.__selectPairs(pairsList) | |
| 121 | >>>>>>> 8048843f4edfb980d0968f42f82054783b84e1cc |
|
|||
| 122 | return True |
|
118 | return True | |
| 123 |
|
119 | |||
| 124 | if self.dataIn.type == "Voltage": |
|
120 | if self.dataIn.type == "Voltage": | |
| 125 |
|
121 | |||
| 126 | if nFFTPoints == None: |
|
122 | if nFFTPoints == None: | |
| 127 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" |
|
123 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" | |
| 128 |
|
124 | |||
| 129 | if nProfiles == None: |
|
125 | if nProfiles == None: | |
| 130 | nProfiles = nFFTPoints |
|
126 | nProfiles = nFFTPoints | |
| 131 |
|
127 | |||
| 132 | if ippFactor == None: |
|
128 | if ippFactor == None: | |
| 133 | ippFactor = 1 |
|
129 | ippFactor = 1 | |
| 134 |
|
130 | |||
| 135 | self.dataOut.ippFactor = ippFactor |
|
131 | self.dataOut.ippFactor = ippFactor | |
| 136 |
|
132 | |||
| 137 | self.dataOut.nFFTPoints = nFFTPoints |
|
133 | self.dataOut.nFFTPoints = nFFTPoints | |
| 138 | self.dataOut.pairsList = pairsList |
|
134 | self.dataOut.pairsList = pairsList | |
| 139 |
|
135 | |||
| 140 | if self.buffer is None: |
|
136 | if self.buffer is None: | |
| 141 | self.buffer = numpy.zeros( (self.dataIn.nChannels, |
|
137 | self.buffer = numpy.zeros( (self.dataIn.nChannels, | |
| 142 | nProfiles, |
|
138 | nProfiles, | |
| 143 | self.dataIn.nHeights), |
|
139 | self.dataIn.nHeights), | |
| 144 | dtype='complex') |
|
140 | dtype='complex') | |
| 145 |
|
141 | |||
| 146 | if self.dataIn.flagDataAsBlock: |
|
142 | if self.dataIn.flagDataAsBlock: | |
| 147 | #data dimension: [nChannels, nProfiles, nSamples] |
|
143 | #data dimension: [nChannels, nProfiles, nSamples] | |
| 148 | nVoltProfiles = self.dataIn.data.shape[1] |
|
144 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 149 | # nVoltProfiles = self.dataIn.nProfiles |
|
145 | # nVoltProfiles = self.dataIn.nProfiles | |
| 150 |
|
146 | |||
| 151 | if nVoltProfiles == nProfiles: |
|
147 | if nVoltProfiles == nProfiles: | |
| 152 | self.buffer = self.dataIn.data.copy() |
|
148 | self.buffer = self.dataIn.data.copy() | |
| 153 | self.profIndex = nVoltProfiles |
|
149 | self.profIndex = nVoltProfiles | |
| 154 |
|
150 | |||
| 155 | elif nVoltProfiles < nProfiles: |
|
151 | elif nVoltProfiles < nProfiles: | |
| 156 |
|
152 | |||
| 157 | if self.profIndex == 0: |
|
153 | if self.profIndex == 0: | |
| 158 | self.id_min = 0 |
|
154 | self.id_min = 0 | |
| 159 | self.id_max = nVoltProfiles |
|
155 | self.id_max = nVoltProfiles | |
| 160 |
|
156 | |||
| 161 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data |
|
157 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data | |
| 162 | self.profIndex += nVoltProfiles |
|
158 | self.profIndex += nVoltProfiles | |
| 163 | self.id_min += nVoltProfiles |
|
159 | self.id_min += nVoltProfiles | |
| 164 | self.id_max += nVoltProfiles |
|
160 | self.id_max += nVoltProfiles | |
| 165 | else: |
|
161 | else: | |
| 166 | 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 | raise ValueError, "The type object %s has %d profiles, it should just has %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) | |
| 167 | self.dataOut.flagNoData = True |
|
163 | self.dataOut.flagNoData = True | |
| 168 | return 0 |
|
164 | return 0 | |
| 169 | else: |
|
165 | else: | |
| 170 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() |
|
166 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() | |
| 171 | self.profIndex += 1 |
|
167 | self.profIndex += 1 | |
| 172 |
|
168 | |||
| 173 | if self.firstdatatime == None: |
|
169 | if self.firstdatatime == None: | |
| 174 | self.firstdatatime = self.dataIn.utctime |
|
170 | self.firstdatatime = self.dataIn.utctime | |
| 175 |
|
171 | |||
| 176 | if self.profIndex == nProfiles: |
|
172 | if self.profIndex == nProfiles: | |
| 177 | self.__updateSpecFromVoltage() |
|
173 | self.__updateSpecFromVoltage() | |
| 178 | self.__getFft() |
|
174 | self.__getFft() | |
| 179 |
|
175 | |||
| 180 | self.dataOut.flagNoData = False |
|
176 | self.dataOut.flagNoData = False | |
| 181 | self.firstdatatime = None |
|
177 | self.firstdatatime = None | |
| 182 | self.profIndex = 0 |
|
178 | self.profIndex = 0 | |
| 183 |
|
179 | |||
| 184 | return True |
|
180 | return True | |
| 185 |
|
181 | |||
| 186 | 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) | |
| 187 |
|
183 | |||
| 188 | def __selectPairs(self, pairsList): |
|
184 | def __selectPairs(self, pairsList): | |
| 189 |
|
185 | |||
| 190 | if not pairsList: |
|
186 | if not pairsList: | |
| 191 | return |
|
187 | return | |
| 192 |
|
188 | |||
| 193 | pairs = [] |
|
189 | pairs = [] | |
| 194 | pairsIndex = [] |
|
190 | pairsIndex = [] | |
| 195 |
|
191 | |||
| 196 | for pair in pairsList: |
|
192 | for pair in pairsList: | |
| 197 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: |
|
193 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: | |
| 198 | continue |
|
194 | continue | |
| 199 | pairs.append(pair) |
|
195 | pairs.append(pair) | |
| 200 | pairsIndex.append(pairs.index(pair)) |
|
196 | pairsIndex.append(pairs.index(pair)) | |
| 201 |
|
197 | |||
| 202 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] |
|
198 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] | |
| 203 | self.dataOut.pairsList = pairs |
|
199 | self.dataOut.pairsList = pairs | |
| 204 | self.dataOut.pairsIndexList = pairsIndex |
|
200 | self.dataOut.pairsIndexList = pairsIndex | |
| 205 |
|
201 | |||
| 206 | return |
|
202 | return | |
| 207 |
|
203 | |||
| 208 | def __selectPairsByChannel(self, channelList=None): |
|
204 | def __selectPairsByChannel(self, channelList=None): | |
| 209 |
|
205 | |||
| 210 | if channelList == None: |
|
206 | if channelList == None: | |
| 211 | return |
|
207 | return | |
| 212 |
|
208 | |||
| 213 | pairsIndexListSelected = [] |
|
209 | pairsIndexListSelected = [] | |
| 214 | for pairIndex in self.dataOut.pairsIndexList: |
|
210 | for pairIndex in self.dataOut.pairsIndexList: | |
| 215 | #First pair |
|
211 | #First pair | |
| 216 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
212 | if self.dataOut.pairsList[pairIndex][0] not in channelList: | |
| 217 | continue |
|
213 | continue | |
| 218 | #Second pair |
|
214 | #Second pair | |
| 219 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
215 | if self.dataOut.pairsList[pairIndex][1] not in channelList: | |
| 220 | continue |
|
216 | continue | |
| 221 |
|
217 | |||
| 222 | pairsIndexListSelected.append(pairIndex) |
|
218 | pairsIndexListSelected.append(pairIndex) | |
| 223 |
|
219 | |||
| 224 | if not pairsIndexListSelected: |
|
220 | if not pairsIndexListSelected: | |
| 225 | self.dataOut.data_cspc = None |
|
221 | self.dataOut.data_cspc = None | |
| 226 | self.dataOut.pairsList = [] |
|
222 | self.dataOut.pairsList = [] | |
| 227 | return |
|
223 | return | |
| 228 |
|
224 | |||
| 229 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
225 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 230 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
226 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 231 |
|
227 | |||
| 232 | return |
|
228 | return | |
| 233 |
|
229 | |||
| 234 | def selectChannels(self, channelList): |
|
230 | def selectChannels(self, channelList): | |
| 235 |
|
231 | |||
| 236 | channelIndexList = [] |
|
232 | channelIndexList = [] | |
| 237 |
|
233 | |||
| 238 | for channel in channelList: |
|
234 | for channel in channelList: | |
| 239 | if channel not in self.dataOut.channelList: |
|
235 | if channel not in self.dataOut.channelList: | |
| 240 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) |
|
236 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) | |
| 241 |
|
237 | |||
| 242 | index = self.dataOut.channelList.index(channel) |
|
238 | index = self.dataOut.channelList.index(channel) | |
| 243 | channelIndexList.append(index) |
|
239 | channelIndexList.append(index) | |
| 244 |
|
240 | |||
| 245 | self.selectChannelsByIndex(channelIndexList) |
|
241 | self.selectChannelsByIndex(channelIndexList) | |
| 246 |
|
242 | |||
| 247 | def selectChannelsByIndex(self, channelIndexList): |
|
243 | def selectChannelsByIndex(self, channelIndexList): | |
| 248 | """ |
|
244 | """ | |
| 249 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
245 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 250 |
|
246 | |||
| 251 | Input: |
|
247 | Input: | |
| 252 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
248 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 253 |
|
249 | |||
| 254 | Affected: |
|
250 | Affected: | |
| 255 | self.dataOut.data_spc |
|
251 | self.dataOut.data_spc | |
| 256 | self.dataOut.channelIndexList |
|
252 | self.dataOut.channelIndexList | |
| 257 | self.dataOut.nChannels |
|
253 | self.dataOut.nChannels | |
| 258 |
|
254 | |||
| 259 | Return: |
|
255 | Return: | |
| 260 | None |
|
256 | None | |
| 261 | """ |
|
257 | """ | |
| 262 |
|
258 | |||
| 263 | for channelIndex in channelIndexList: |
|
259 | for channelIndex in channelIndexList: | |
| 264 | if channelIndex not in self.dataOut.channelIndexList: |
|
260 | if channelIndex not in self.dataOut.channelIndexList: | |
| 265 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) |
|
261 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) | |
| 266 |
|
262 | |||
| 267 | # nChannels = len(channelIndexList) |
|
263 | # nChannels = len(channelIndexList) | |
| 268 |
|
264 | |||
| 269 | data_spc = self.dataOut.data_spc[channelIndexList,:] |
|
265 | data_spc = self.dataOut.data_spc[channelIndexList,:] | |
| 270 | data_dc = self.dataOut.data_dc[channelIndexList,:] |
|
266 | data_dc = self.dataOut.data_dc[channelIndexList,:] | |
| 271 |
|
267 | |||
| 272 | self.dataOut.data_spc = data_spc |
|
268 | self.dataOut.data_spc = data_spc | |
| 273 | self.dataOut.data_dc = data_dc |
|
269 | self.dataOut.data_dc = data_dc | |
| 274 |
|
270 | |||
| 275 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
271 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 276 | # self.dataOut.nChannels = nChannels |
|
272 | # self.dataOut.nChannels = nChannels | |
| 277 |
|
273 | |||
| 278 | self.__selectPairsByChannel(self.dataOut.channelList) |
|
274 | self.__selectPairsByChannel(self.dataOut.channelList) | |
| 279 |
|
275 | |||
| 280 | return 1 |
|
276 | return 1 | |
| 281 |
|
277 | |||
| 282 | def selectHeights(self, minHei, maxHei): |
|
278 | def selectHeights(self, minHei, maxHei): | |
| 283 | """ |
|
279 | """ | |
| 284 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
280 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 285 | minHei <= height <= maxHei |
|
281 | minHei <= height <= maxHei | |
| 286 |
|
282 | |||
| 287 | Input: |
|
283 | Input: | |
| 288 | minHei : valor minimo de altura a considerar |
|
284 | minHei : valor minimo de altura a considerar | |
| 289 | maxHei : valor maximo de altura a considerar |
|
285 | maxHei : valor maximo de altura a considerar | |
| 290 |
|
286 | |||
| 291 | Affected: |
|
287 | Affected: | |
| 292 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
288 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 293 |
|
289 | |||
| 294 | Return: |
|
290 | Return: | |
| 295 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
291 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 296 | """ |
|
292 | """ | |
| 297 |
|
293 | |||
| 298 | if (minHei > maxHei): |
|
294 | if (minHei > maxHei): | |
| 299 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) |
|
295 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) | |
| 300 |
|
296 | |||
| 301 | if (minHei < self.dataOut.heightList[0]): |
|
297 | if (minHei < self.dataOut.heightList[0]): | |
| 302 | minHei = self.dataOut.heightList[0] |
|
298 | minHei = self.dataOut.heightList[0] | |
| 303 |
|
299 | |||
| 304 | if (maxHei > self.dataOut.heightList[-1]): |
|
300 | if (maxHei > self.dataOut.heightList[-1]): | |
| 305 | maxHei = self.dataOut.heightList[-1] |
|
301 | maxHei = self.dataOut.heightList[-1] | |
| 306 |
|
302 | |||
| 307 | minIndex = 0 |
|
303 | minIndex = 0 | |
| 308 | maxIndex = 0 |
|
304 | maxIndex = 0 | |
| 309 | heights = self.dataOut.heightList |
|
305 | heights = self.dataOut.heightList | |
| 310 |
|
306 | |||
| 311 | inda = numpy.where(heights >= minHei) |
|
307 | inda = numpy.where(heights >= minHei) | |
| 312 | indb = numpy.where(heights <= maxHei) |
|
308 | indb = numpy.where(heights <= maxHei) | |
| 313 |
|
309 | |||
| 314 | try: |
|
310 | try: | |
| 315 | minIndex = inda[0][0] |
|
311 | minIndex = inda[0][0] | |
| 316 | except: |
|
312 | except: | |
| 317 | minIndex = 0 |
|
313 | minIndex = 0 | |
| 318 |
|
314 | |||
| 319 | try: |
|
315 | try: | |
| 320 | maxIndex = indb[0][-1] |
|
316 | maxIndex = indb[0][-1] | |
| 321 | except: |
|
317 | except: | |
| 322 | maxIndex = len(heights) |
|
318 | maxIndex = len(heights) | |
| 323 |
|
319 | |||
| 324 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
320 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 325 |
|
321 | |||
| 326 | return 1 |
|
322 | return 1 | |
| 327 |
|
323 | |||
| 328 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): |
|
324 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): | |
| 329 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
325 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 330 |
|
326 | |||
| 331 | if hei_ref != None: |
|
327 | if hei_ref != None: | |
| 332 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
328 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 333 |
|
329 | |||
| 334 | minIndex = min(newheis[0]) |
|
330 | minIndex = min(newheis[0]) | |
| 335 | maxIndex = max(newheis[0]) |
|
331 | maxIndex = max(newheis[0]) | |
| 336 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
332 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 337 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
333 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 338 |
|
334 | |||
| 339 | # determina indices |
|
335 | # determina indices | |
| 340 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) |
|
336 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) | |
| 341 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) |
|
337 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) | |
| 342 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
338 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 343 | beacon_heiIndexList = [] |
|
339 | beacon_heiIndexList = [] | |
| 344 | for val in avg_dB.tolist(): |
|
340 | for val in avg_dB.tolist(): | |
| 345 | if val >= beacon_dB[0]: |
|
341 | if val >= beacon_dB[0]: | |
| 346 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
342 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 347 |
|
343 | |||
| 348 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
344 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 349 | data_cspc = None |
|
345 | data_cspc = None | |
| 350 | if self.dataOut.data_cspc is not None: |
|
346 | if self.dataOut.data_cspc is not None: | |
| 351 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
347 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 352 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
348 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 353 |
|
349 | |||
| 354 | data_dc = None |
|
350 | data_dc = None | |
| 355 | if self.dataOut.data_dc is not None: |
|
351 | if self.dataOut.data_dc is not None: | |
| 356 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
352 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 357 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
353 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 358 |
|
354 | |||
| 359 | self.dataOut.data_spc = data_spc |
|
355 | self.dataOut.data_spc = data_spc | |
| 360 | self.dataOut.data_cspc = data_cspc |
|
356 | self.dataOut.data_cspc = data_cspc | |
| 361 | self.dataOut.data_dc = data_dc |
|
357 | self.dataOut.data_dc = data_dc | |
| 362 | self.dataOut.heightList = heightList |
|
358 | self.dataOut.heightList = heightList | |
| 363 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
359 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 364 |
|
360 | |||
| 365 | return 1 |
|
361 | return 1 | |
| 366 |
|
362 | |||
| 367 |
|
363 | |||
| 368 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
364 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 369 | """ |
|
365 | """ | |
| 370 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
366 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 371 | minIndex <= index <= maxIndex |
|
367 | minIndex <= index <= maxIndex | |
| 372 |
|
368 | |||
| 373 | Input: |
|
369 | Input: | |
| 374 | minIndex : valor de indice minimo de altura a considerar |
|
370 | minIndex : valor de indice minimo de altura a considerar | |
| 375 | maxIndex : valor de indice maximo de altura a considerar |
|
371 | maxIndex : valor de indice maximo de altura a considerar | |
| 376 |
|
372 | |||
| 377 | Affected: |
|
373 | Affected: | |
| 378 | self.dataOut.data_spc |
|
374 | self.dataOut.data_spc | |
| 379 | self.dataOut.data_cspc |
|
375 | self.dataOut.data_cspc | |
| 380 | self.dataOut.data_dc |
|
376 | self.dataOut.data_dc | |
| 381 | self.dataOut.heightList |
|
377 | self.dataOut.heightList | |
| 382 |
|
378 | |||
| 383 | Return: |
|
379 | Return: | |
| 384 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
380 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 385 | """ |
|
381 | """ | |
| 386 |
|
382 | |||
| 387 | if (minIndex < 0) or (minIndex > maxIndex): |
|
383 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 388 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
384 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 389 |
|
385 | |||
| 390 | if (maxIndex >= self.dataOut.nHeights): |
|
386 | if (maxIndex >= self.dataOut.nHeights): | |
| 391 | maxIndex = self.dataOut.nHeights-1 |
|
387 | maxIndex = self.dataOut.nHeights-1 | |
| 392 |
|
388 | |||
| 393 | #Spectra |
|
389 | #Spectra | |
| 394 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
390 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 395 |
|
391 | |||
| 396 | data_cspc = None |
|
392 | data_cspc = None | |
| 397 | if self.dataOut.data_cspc is not None: |
|
393 | if self.dataOut.data_cspc is not None: | |
| 398 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
394 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 399 |
|
395 | |||
| 400 | data_dc = None |
|
396 | data_dc = None | |
| 401 | if self.dataOut.data_dc is not None: |
|
397 | if self.dataOut.data_dc is not None: | |
| 402 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
398 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 403 |
|
399 | |||
| 404 | self.dataOut.data_spc = data_spc |
|
400 | self.dataOut.data_spc = data_spc | |
| 405 | self.dataOut.data_cspc = data_cspc |
|
401 | self.dataOut.data_cspc = data_cspc | |
| 406 | self.dataOut.data_dc = data_dc |
|
402 | self.dataOut.data_dc = data_dc | |
| 407 |
|
403 | |||
| 408 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
404 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 409 |
|
405 | |||
| 410 | return 1 |
|
406 | return 1 | |
| 411 |
|
407 | |||
| 412 | def removeDC(self, mode = 2): |
|
408 | def removeDC(self, mode = 2): | |
| 413 | jspectra = self.dataOut.data_spc |
|
409 | jspectra = self.dataOut.data_spc | |
| 414 | jcspectra = self.dataOut.data_cspc |
|
410 | jcspectra = self.dataOut.data_cspc | |
| 415 |
|
411 | |||
| 416 |
|
412 | |||
| 417 | num_chan = jspectra.shape[0] |
|
413 | num_chan = jspectra.shape[0] | |
| 418 | num_hei = jspectra.shape[2] |
|
414 | num_hei = jspectra.shape[2] | |
| 419 |
|
415 | |||
| 420 | if jcspectra is not None: |
|
416 | if jcspectra is not None: | |
| 421 | jcspectraExist = True |
|
417 | jcspectraExist = True | |
| 422 | num_pairs = jcspectra.shape[0] |
|
418 | num_pairs = jcspectra.shape[0] | |
| 423 | else: jcspectraExist = False |
|
419 | else: jcspectraExist = False | |
| 424 |
|
420 | |||
| 425 | freq_dc = jspectra.shape[1]/2 |
|
421 | freq_dc = jspectra.shape[1]/2 | |
| 426 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
422 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |
| 427 |
|
423 | |||
| 428 | if ind_vel[0]<0: |
|
424 | if ind_vel[0]<0: | |
| 429 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
425 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |
| 430 |
|
426 | |||
| 431 | if mode == 1: |
|
427 | if mode == 1: | |
| 432 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
428 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
| 433 |
|
429 | |||
| 434 | if jcspectraExist: |
|
430 | if jcspectraExist: | |
| 435 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 |
|
431 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 | |
| 436 |
|
432 | |||
| 437 | if mode == 2: |
|
433 | if mode == 2: | |
| 438 |
|
434 | |||
| 439 | vel = numpy.array([-2,-1,1,2]) |
|
435 | vel = numpy.array([-2,-1,1,2]) | |
| 440 | xx = numpy.zeros([4,4]) |
|
436 | xx = numpy.zeros([4,4]) | |
| 441 |
|
437 | |||
| 442 | for fil in range(4): |
|
438 | for fil in range(4): | |
| 443 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
439 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |
| 444 |
|
440 | |||
| 445 | xx_inv = numpy.linalg.inv(xx) |
|
441 | xx_inv = numpy.linalg.inv(xx) | |
| 446 | xx_aux = xx_inv[0,:] |
|
442 | xx_aux = xx_inv[0,:] | |
| 447 |
|
443 | |||
| 448 | for ich in range(num_chan): |
|
444 | for ich in range(num_chan): | |
| 449 | yy = jspectra[ich,ind_vel,:] |
|
445 | yy = jspectra[ich,ind_vel,:] | |
| 450 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
446 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 451 |
|
447 | |||
| 452 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
448 | junkid = jspectra[ich,freq_dc,:]<=0 | |
| 453 | cjunkid = sum(junkid) |
|
449 | cjunkid = sum(junkid) | |
| 454 |
|
450 | |||
| 455 | if cjunkid.any(): |
|
451 | if cjunkid.any(): | |
| 456 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
452 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |
| 457 |
|
453 | |||
| 458 | if jcspectraExist: |
|
454 | if jcspectraExist: | |
| 459 | for ip in range(num_pairs): |
|
455 | for ip in range(num_pairs): | |
| 460 | yy = jcspectra[ip,ind_vel,:] |
|
456 | yy = jcspectra[ip,ind_vel,:] | |
| 461 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
457 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 462 |
|
458 | |||
| 463 |
|
459 | |||
| 464 | self.dataOut.data_spc = jspectra |
|
460 | self.dataOut.data_spc = jspectra | |
| 465 | self.dataOut.data_cspc = jcspectra |
|
461 | self.dataOut.data_cspc = jcspectra | |
| 466 |
|
462 | |||
| 467 | return 1 |
|
463 | return 1 | |
| 468 |
|
464 | |||
| 469 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
465 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 470 |
|
466 | |||
| 471 | jspectra = self.dataOut.data_spc |
|
467 | jspectra = self.dataOut.data_spc | |
| 472 | jcspectra = self.dataOut.data_cspc |
|
468 | jcspectra = self.dataOut.data_cspc | |
| 473 | jnoise = self.dataOut.getNoise() |
|
469 | jnoise = self.dataOut.getNoise() | |
| 474 | num_incoh = self.dataOut.nIncohInt |
|
470 | num_incoh = self.dataOut.nIncohInt | |
| 475 |
|
471 | |||
| 476 | num_channel = jspectra.shape[0] |
|
472 | num_channel = jspectra.shape[0] | |
| 477 | num_prof = jspectra.shape[1] |
|
473 | num_prof = jspectra.shape[1] | |
| 478 | num_hei = jspectra.shape[2] |
|
474 | num_hei = jspectra.shape[2] | |
| 479 |
|
475 | |||
| 480 | #hei_interf |
|
476 | #hei_interf | |
| 481 | if hei_interf is None: |
|
477 | if hei_interf is None: | |
| 482 | count_hei = num_hei/2 #Como es entero no importa |
|
478 | count_hei = num_hei/2 #Como es entero no importa | |
| 483 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei |
|
479 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei | |
| 484 | hei_interf = numpy.asarray(hei_interf)[0] |
|
480 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 485 | #nhei_interf |
|
481 | #nhei_interf | |
| 486 | if (nhei_interf == None): |
|
482 | if (nhei_interf == None): | |
| 487 | nhei_interf = 5 |
|
483 | nhei_interf = 5 | |
| 488 | if (nhei_interf < 1): |
|
484 | if (nhei_interf < 1): | |
| 489 | nhei_interf = 1 |
|
485 | nhei_interf = 1 | |
| 490 | if (nhei_interf > count_hei): |
|
486 | if (nhei_interf > count_hei): | |
| 491 | nhei_interf = count_hei |
|
487 | nhei_interf = count_hei | |
| 492 | if (offhei_interf == None): |
|
488 | if (offhei_interf == None): | |
| 493 | offhei_interf = 0 |
|
489 | offhei_interf = 0 | |
| 494 |
|
490 | |||
| 495 | ind_hei = range(num_hei) |
|
491 | ind_hei = range(num_hei) | |
| 496 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
492 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 497 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
493 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 498 | mask_prof = numpy.asarray(range(num_prof)) |
|
494 | mask_prof = numpy.asarray(range(num_prof)) | |
| 499 | num_mask_prof = mask_prof.size |
|
495 | num_mask_prof = mask_prof.size | |
| 500 | comp_mask_prof = [0, num_prof/2] |
|
496 | comp_mask_prof = [0, num_prof/2] | |
| 501 |
|
497 | |||
| 502 |
|
498 | |||
| 503 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
499 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 504 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
500 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 505 | jnoise = numpy.nan |
|
501 | jnoise = numpy.nan | |
| 506 | noise_exist = jnoise[0] < numpy.Inf |
|
502 | noise_exist = jnoise[0] < numpy.Inf | |
| 507 |
|
503 | |||
| 508 | #Subrutina de Remocion de la Interferencia |
|
504 | #Subrutina de Remocion de la Interferencia | |
| 509 | for ich in range(num_channel): |
|
505 | for ich in range(num_channel): | |
| 510 | #Se ordena los espectros segun su potencia (menor a mayor) |
|
506 | #Se ordena los espectros segun su potencia (menor a mayor) | |
| 511 | power = jspectra[ich,mask_prof,:] |
|
507 | power = jspectra[ich,mask_prof,:] | |
| 512 | power = power[:,hei_interf] |
|
508 | power = power[:,hei_interf] | |
| 513 | power = power.sum(axis = 0) |
|
509 | power = power.sum(axis = 0) | |
| 514 | psort = power.ravel().argsort() |
|
510 | psort = power.ravel().argsort() | |
| 515 |
|
511 | |||
| 516 | #Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
512 | #Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 517 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
513 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 518 |
|
514 | |||
| 519 | if noise_exist: |
|
515 | if noise_exist: | |
| 520 | # tmp_noise = jnoise[ich] / num_prof |
|
516 | # tmp_noise = jnoise[ich] / num_prof | |
| 521 | tmp_noise = jnoise[ich] |
|
517 | tmp_noise = jnoise[ich] | |
| 522 | junkspc_interf = junkspc_interf - tmp_noise |
|
518 | junkspc_interf = junkspc_interf - tmp_noise | |
| 523 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
519 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 524 |
|
520 | |||
| 525 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf |
|
521 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf | |
| 526 | jspc_interf = jspc_interf.transpose() |
|
522 | jspc_interf = jspc_interf.transpose() | |
| 527 | #Calculando el espectro de interferencia promedio |
|
523 | #Calculando el espectro de interferencia promedio | |
| 528 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) |
|
524 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) | |
| 529 | noiseid = noiseid[0] |
|
525 | noiseid = noiseid[0] | |
| 530 | cnoiseid = noiseid.size |
|
526 | cnoiseid = noiseid.size | |
| 531 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) |
|
527 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) | |
| 532 | interfid = interfid[0] |
|
528 | interfid = interfid[0] | |
| 533 | cinterfid = interfid.size |
|
529 | cinterfid = interfid.size | |
| 534 |
|
530 | |||
| 535 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 |
|
531 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 | |
| 536 |
|
532 | |||
| 537 | #Expandiendo los perfiles a limpiar |
|
533 | #Expandiendo los perfiles a limpiar | |
| 538 | if (cinterfid > 0): |
|
534 | if (cinterfid > 0): | |
| 539 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof |
|
535 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof | |
| 540 | new_interfid = numpy.asarray(new_interfid) |
|
536 | new_interfid = numpy.asarray(new_interfid) | |
| 541 | new_interfid = {x for x in new_interfid} |
|
537 | new_interfid = {x for x in new_interfid} | |
| 542 | new_interfid = numpy.array(list(new_interfid)) |
|
538 | new_interfid = numpy.array(list(new_interfid)) | |
| 543 | new_cinterfid = new_interfid.size |
|
539 | new_cinterfid = new_interfid.size | |
| 544 | else: new_cinterfid = 0 |
|
540 | else: new_cinterfid = 0 | |
| 545 |
|
541 | |||
| 546 | for ip in range(new_cinterfid): |
|
542 | for ip in range(new_cinterfid): | |
| 547 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() |
|
543 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() | |
| 548 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] |
|
544 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] | |
| 549 |
|
545 | |||
| 550 |
|
546 | |||
| 551 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices |
|
547 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices | |
| 552 |
|
548 | |||
| 553 | #Removiendo la interferencia del punto de mayor interferencia |
|
549 | #Removiendo la interferencia del punto de mayor interferencia | |
| 554 | ListAux = jspc_interf[mask_prof].tolist() |
|
550 | ListAux = jspc_interf[mask_prof].tolist() | |
| 555 | maxid = ListAux.index(max(ListAux)) |
|
551 | maxid = ListAux.index(max(ListAux)) | |
| 556 |
|
552 | |||
| 557 |
|
553 | |||
| 558 | if cinterfid > 0: |
|
554 | if cinterfid > 0: | |
| 559 | for ip in range(cinterfid*(interf == 2) - 1): |
|
555 | for ip in range(cinterfid*(interf == 2) - 1): | |
| 560 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() |
|
556 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() | |
| 561 | cind = len(ind) |
|
557 | cind = len(ind) | |
| 562 |
|
558 | |||
| 563 | if (cind > 0): |
|
559 | if (cind > 0): | |
| 564 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) |
|
560 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) | |
| 565 |
|
561 | |||
| 566 | ind = numpy.array([-2,-1,1,2]) |
|
562 | ind = numpy.array([-2,-1,1,2]) | |
| 567 | xx = numpy.zeros([4,4]) |
|
563 | xx = numpy.zeros([4,4]) | |
| 568 |
|
564 | |||
| 569 | for id1 in range(4): |
|
565 | for id1 in range(4): | |
| 570 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
566 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 571 |
|
567 | |||
| 572 | xx_inv = numpy.linalg.inv(xx) |
|
568 | xx_inv = numpy.linalg.inv(xx) | |
| 573 | xx = xx_inv[:,0] |
|
569 | xx = xx_inv[:,0] | |
| 574 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
570 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 575 | yy = jspectra[ich,mask_prof[ind],:] |
|
571 | yy = jspectra[ich,mask_prof[ind],:] | |
| 576 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
572 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 577 |
|
573 | |||
| 578 |
|
574 | |||
| 579 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() |
|
575 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() | |
| 580 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) |
|
576 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) | |
| 581 |
|
577 | |||
| 582 | #Remocion de Interferencia en el Cross Spectra |
|
578 | #Remocion de Interferencia en el Cross Spectra | |
| 583 | if jcspectra is None: return jspectra, jcspectra |
|
579 | if jcspectra is None: return jspectra, jcspectra | |
| 584 | num_pairs = jcspectra.size/(num_prof*num_hei) |
|
580 | num_pairs = jcspectra.size/(num_prof*num_hei) | |
| 585 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
581 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 586 |
|
582 | |||
| 587 | for ip in range(num_pairs): |
|
583 | for ip in range(num_pairs): | |
| 588 |
|
584 | |||
| 589 | #------------------------------------------- |
|
585 | #------------------------------------------- | |
| 590 |
|
586 | |||
| 591 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) |
|
587 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) | |
| 592 | cspower = cspower[:,hei_interf] |
|
588 | cspower = cspower[:,hei_interf] | |
| 593 | cspower = cspower.sum(axis = 0) |
|
589 | cspower = cspower.sum(axis = 0) | |
| 594 |
|
590 | |||
| 595 | cspsort = cspower.ravel().argsort() |
|
591 | cspsort = cspower.ravel().argsort() | |
| 596 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
592 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 597 | junkcspc_interf = junkcspc_interf.transpose() |
|
593 | junkcspc_interf = junkcspc_interf.transpose() | |
| 598 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf |
|
594 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf | |
| 599 |
|
595 | |||
| 600 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
596 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 601 |
|
597 | |||
| 602 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
598 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 603 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
599 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 604 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) |
|
600 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) | |
| 605 |
|
601 | |||
| 606 | for iprof in range(num_prof): |
|
602 | for iprof in range(num_prof): | |
| 607 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() |
|
603 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() | |
| 608 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] |
|
604 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] | |
| 609 |
|
605 | |||
| 610 | #Removiendo la Interferencia |
|
606 | #Removiendo la Interferencia | |
| 611 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf |
|
607 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf | |
| 612 |
|
608 | |||
| 613 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
609 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 614 | maxid = ListAux.index(max(ListAux)) |
|
610 | maxid = ListAux.index(max(ListAux)) | |
| 615 |
|
611 | |||
| 616 | ind = numpy.array([-2,-1,1,2]) |
|
612 | ind = numpy.array([-2,-1,1,2]) | |
| 617 | xx = numpy.zeros([4,4]) |
|
613 | xx = numpy.zeros([4,4]) | |
| 618 |
|
614 | |||
| 619 | for id1 in range(4): |
|
615 | for id1 in range(4): | |
| 620 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
616 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 621 |
|
617 | |||
| 622 | xx_inv = numpy.linalg.inv(xx) |
|
618 | xx_inv = numpy.linalg.inv(xx) | |
| 623 | xx = xx_inv[:,0] |
|
619 | xx = xx_inv[:,0] | |
| 624 |
|
620 | |||
| 625 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
621 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 626 | yy = jcspectra[ip,mask_prof[ind],:] |
|
622 | yy = jcspectra[ip,mask_prof[ind],:] | |
| 627 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
623 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 628 |
|
624 | |||
| 629 | #Guardar Resultados |
|
625 | #Guardar Resultados | |
| 630 | self.dataOut.data_spc = jspectra |
|
626 | self.dataOut.data_spc = jspectra | |
| 631 | self.dataOut.data_cspc = jcspectra |
|
627 | self.dataOut.data_cspc = jcspectra | |
| 632 |
|
628 | |||
| 633 | return 1 |
|
629 | return 1 | |
| 634 |
|
630 | |||
| 635 | def setRadarFrequency(self, frequency=None): |
|
631 | def setRadarFrequency(self, frequency=None): | |
| 636 |
|
632 | |||
| 637 | if frequency != None: |
|
633 | if frequency != None: | |
| 638 | self.dataOut.frequency = frequency |
|
634 | self.dataOut.frequency = frequency | |
| 639 |
|
635 | |||
| 640 | return 1 |
|
636 | return 1 | |
| 641 |
|
637 | |||
| 642 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
638 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 643 | #validacion de rango |
|
639 | #validacion de rango | |
| 644 | if minHei == None: |
|
640 | if minHei == None: | |
| 645 | minHei = self.dataOut.heightList[0] |
|
641 | minHei = self.dataOut.heightList[0] | |
| 646 |
|
642 | |||
| 647 | if maxHei == None: |
|
643 | if maxHei == None: | |
| 648 | maxHei = self.dataOut.heightList[-1] |
|
644 | maxHei = self.dataOut.heightList[-1] | |
| 649 |
|
645 | |||
| 650 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
646 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 651 | print 'minHei: %.2f is out of the heights range'%(minHei) |
|
647 | print 'minHei: %.2f is out of the heights range'%(minHei) | |
| 652 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) |
|
648 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) | |
| 653 | minHei = self.dataOut.heightList[0] |
|
649 | minHei = self.dataOut.heightList[0] | |
| 654 |
|
650 | |||
| 655 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
651 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 656 | print 'maxHei: %.2f is out of the heights range'%(maxHei) |
|
652 | print 'maxHei: %.2f is out of the heights range'%(maxHei) | |
| 657 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) |
|
653 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) | |
| 658 | maxHei = self.dataOut.heightList[-1] |
|
654 | maxHei = self.dataOut.heightList[-1] | |
| 659 |
|
655 | |||
| 660 | # validacion de velocidades |
|
656 | # validacion de velocidades | |
| 661 | velrange = self.dataOut.getVelRange(1) |
|
657 | velrange = self.dataOut.getVelRange(1) | |
| 662 |
|
658 | |||
| 663 | if minVel == None: |
|
659 | if minVel == None: | |
| 664 | minVel = velrange[0] |
|
660 | minVel = velrange[0] | |
| 665 |
|
661 | |||
| 666 | if maxVel == None: |
|
662 | if maxVel == None: | |
| 667 | maxVel = velrange[-1] |
|
663 | maxVel = velrange[-1] | |
| 668 |
|
664 | |||
| 669 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
665 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 670 | print 'minVel: %.2f is out of the velocity range'%(minVel) |
|
666 | print 'minVel: %.2f is out of the velocity range'%(minVel) | |
| 671 | print 'minVel is setting to %.2f'%(velrange[0]) |
|
667 | print 'minVel is setting to %.2f'%(velrange[0]) | |
| 672 | minVel = velrange[0] |
|
668 | minVel = velrange[0] | |
| 673 |
|
669 | |||
| 674 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
670 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 675 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) |
|
671 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) | |
| 676 | print 'maxVel is setting to %.2f'%(velrange[-1]) |
|
672 | print 'maxVel is setting to %.2f'%(velrange[-1]) | |
| 677 | maxVel = velrange[-1] |
|
673 | maxVel = velrange[-1] | |
| 678 |
|
674 | |||
| 679 | # seleccion de indices para rango |
|
675 | # seleccion de indices para rango | |
| 680 | minIndex = 0 |
|
676 | minIndex = 0 | |
| 681 | maxIndex = 0 |
|
677 | maxIndex = 0 | |
| 682 | heights = self.dataOut.heightList |
|
678 | heights = self.dataOut.heightList | |
| 683 |
|
679 | |||
| 684 | inda = numpy.where(heights >= minHei) |
|
680 | inda = numpy.where(heights >= minHei) | |
| 685 | indb = numpy.where(heights <= maxHei) |
|
681 | indb = numpy.where(heights <= maxHei) | |
| 686 |
|
682 | |||
| 687 | try: |
|
683 | try: | |
| 688 | minIndex = inda[0][0] |
|
684 | minIndex = inda[0][0] | |
| 689 | except: |
|
685 | except: | |
| 690 | minIndex = 0 |
|
686 | minIndex = 0 | |
| 691 |
|
687 | |||
| 692 | try: |
|
688 | try: | |
| 693 | maxIndex = indb[0][-1] |
|
689 | maxIndex = indb[0][-1] | |
| 694 | except: |
|
690 | except: | |
| 695 | maxIndex = len(heights) |
|
691 | maxIndex = len(heights) | |
| 696 |
|
692 | |||
| 697 | if (minIndex < 0) or (minIndex > maxIndex): |
|
693 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 698 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
694 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 699 |
|
695 | |||
| 700 | if (maxIndex >= self.dataOut.nHeights): |
|
696 | if (maxIndex >= self.dataOut.nHeights): | |
| 701 | maxIndex = self.dataOut.nHeights-1 |
|
697 | maxIndex = self.dataOut.nHeights-1 | |
| 702 |
|
698 | |||
| 703 | # seleccion de indices para velocidades |
|
699 | # seleccion de indices para velocidades | |
| 704 | indminvel = numpy.where(velrange >= minVel) |
|
700 | indminvel = numpy.where(velrange >= minVel) | |
| 705 | indmaxvel = numpy.where(velrange <= maxVel) |
|
701 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 706 | try: |
|
702 | try: | |
| 707 | minIndexVel = indminvel[0][0] |
|
703 | minIndexVel = indminvel[0][0] | |
| 708 | except: |
|
704 | except: | |
| 709 | minIndexVel = 0 |
|
705 | minIndexVel = 0 | |
| 710 |
|
706 | |||
| 711 | try: |
|
707 | try: | |
| 712 | maxIndexVel = indmaxvel[0][-1] |
|
708 | maxIndexVel = indmaxvel[0][-1] | |
| 713 | except: |
|
709 | except: | |
| 714 | maxIndexVel = len(velrange) |
|
710 | maxIndexVel = len(velrange) | |
| 715 |
|
711 | |||
| 716 | #seleccion del espectro |
|
712 | #seleccion del espectro | |
| 717 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] |
|
713 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] | |
| 718 | #estimacion de ruido |
|
714 | #estimacion de ruido | |
| 719 | noise = numpy.zeros(self.dataOut.nChannels) |
|
715 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 720 |
|
716 | |||
| 721 | for channel in range(self.dataOut.nChannels): |
|
717 | for channel in range(self.dataOut.nChannels): | |
| 722 | daux = data_spc[channel,:,:] |
|
718 | daux = data_spc[channel,:,:] | |
| 723 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) |
|
719 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) | |
| 724 |
|
720 | |||
| 725 | self.dataOut.noise_estimation = noise.copy() |
|
721 | self.dataOut.noise_estimation = noise.copy() | |
| 726 |
|
722 | |||
| 727 | return 1 |
|
723 | return 1 | |
| 728 |
|
724 | |||
| 729 | class IncohInt(Operation): |
|
725 | class IncohInt(Operation): | |
| 730 |
|
726 | |||
| 731 |
|
727 | |||
| 732 | __profIndex = 0 |
|
728 | __profIndex = 0 | |
| 733 | __withOverapping = False |
|
729 | __withOverapping = False | |
| 734 |
|
730 | |||
| 735 | __byTime = False |
|
731 | __byTime = False | |
| 736 | __initime = None |
|
732 | __initime = None | |
| 737 | __lastdatatime = None |
|
733 | __lastdatatime = None | |
| 738 | __integrationtime = None |
|
734 | __integrationtime = None | |
| 739 |
|
735 | |||
| 740 | __buffer_spc = None |
|
736 | __buffer_spc = None | |
| 741 | __buffer_cspc = None |
|
737 | __buffer_cspc = None | |
| 742 | __buffer_dc = None |
|
738 | __buffer_dc = None | |
| 743 |
|
739 | |||
| 744 | __dataReady = False |
|
740 | __dataReady = False | |
| 745 |
|
741 | |||
| 746 | __timeInterval = None |
|
742 | __timeInterval = None | |
| 747 |
|
743 | |||
| 748 | n = None |
|
744 | n = None | |
| 749 |
|
745 | |||
| 750 |
|
746 | |||
| 751 |
|
747 | |||
| 752 | def __init__(self, **kwargs): |
|
748 | def __init__(self, **kwargs): | |
| 753 |
|
749 | |||
| 754 | Operation.__init__(self, **kwargs) |
|
750 | Operation.__init__(self, **kwargs) | |
| 755 | # self.isConfig = False |
|
751 | # self.isConfig = False | |
| 756 |
|
752 | |||
| 757 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
753 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 758 | """ |
|
754 | """ | |
| 759 | Set the parameters of the integration class. |
|
755 | Set the parameters of the integration class. | |
| 760 |
|
756 | |||
| 761 | Inputs: |
|
757 | Inputs: | |
| 762 |
|
758 | |||
| 763 | n : Number of coherent integrations |
|
759 | n : Number of coherent integrations | |
| 764 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
760 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 765 | overlapping : |
|
761 | overlapping : | |
| 766 |
|
762 | |||
| 767 | """ |
|
763 | """ | |
| 768 |
|
764 | |||
| 769 | self.__initime = None |
|
765 | self.__initime = None | |
| 770 | self.__lastdatatime = 0 |
|
766 | self.__lastdatatime = 0 | |
| 771 |
|
767 | |||
| 772 | self.__buffer_spc = 0 |
|
768 | self.__buffer_spc = 0 | |
| 773 | self.__buffer_cspc = 0 |
|
769 | self.__buffer_cspc = 0 | |
| 774 | self.__buffer_dc = 0 |
|
770 | self.__buffer_dc = 0 | |
| 775 |
|
771 | |||
| 776 | self.__profIndex = 0 |
|
772 | self.__profIndex = 0 | |
| 777 | self.__dataReady = False |
|
773 | self.__dataReady = False | |
| 778 | self.__byTime = False |
|
774 | self.__byTime = False | |
| 779 |
|
775 | |||
| 780 | if n is None and timeInterval is None: |
|
776 | if n is None and timeInterval is None: | |
| 781 | raise ValueError, "n or timeInterval should be specified ..." |
|
777 | raise ValueError, "n or timeInterval should be specified ..." | |
| 782 |
|
778 | |||
| 783 | if n is not None: |
|
779 | if n is not None: | |
| 784 | self.n = int(n) |
|
780 | self.n = int(n) | |
| 785 | else: |
|
781 | else: | |
| 786 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line |
|
782 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line | |
| 787 | self.n = None |
|
783 | self.n = None | |
| 788 | self.__byTime = True |
|
784 | self.__byTime = True | |
| 789 |
|
785 | |||
| 790 | def putData(self, data_spc, data_cspc, data_dc): |
|
786 | def putData(self, data_spc, data_cspc, data_dc): | |
| 791 |
|
787 | |||
| 792 | """ |
|
788 | """ | |
| 793 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
789 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 794 |
|
790 | |||
| 795 | """ |
|
791 | """ | |
| 796 |
|
792 | |||
| 797 | self.__buffer_spc += data_spc |
|
793 | self.__buffer_spc += data_spc | |
| 798 |
|
794 | |||
| 799 | if data_cspc is None: |
|
795 | if data_cspc is None: | |
| 800 | self.__buffer_cspc = None |
|
796 | self.__buffer_cspc = None | |
| 801 | else: |
|
797 | else: | |
| 802 | self.__buffer_cspc += data_cspc |
|
798 | self.__buffer_cspc += data_cspc | |
| 803 |
|
799 | |||
| 804 | if data_dc is None: |
|
800 | if data_dc is None: | |
| 805 | self.__buffer_dc = None |
|
801 | self.__buffer_dc = None | |
| 806 | else: |
|
802 | else: | |
| 807 | self.__buffer_dc += data_dc |
|
803 | self.__buffer_dc += data_dc | |
| 808 |
|
804 | |||
| 809 | self.__profIndex += 1 |
|
805 | self.__profIndex += 1 | |
| 810 |
|
806 | |||
| 811 | return |
|
807 | return | |
| 812 |
|
808 | |||
| 813 | def pushData(self): |
|
809 | def pushData(self): | |
| 814 | """ |
|
810 | """ | |
| 815 | Return the sum of the last profiles and the profiles used in the sum. |
|
811 | Return the sum of the last profiles and the profiles used in the sum. | |
| 816 |
|
812 | |||
| 817 | Affected: |
|
813 | Affected: | |
| 818 |
|
814 | |||
| 819 | self.__profileIndex |
|
815 | self.__profileIndex | |
| 820 |
|
816 | |||
| 821 | """ |
|
817 | """ | |
| 822 |
|
818 | |||
| 823 | data_spc = self.__buffer_spc |
|
819 | data_spc = self.__buffer_spc | |
| 824 | data_cspc = self.__buffer_cspc |
|
820 | data_cspc = self.__buffer_cspc | |
| 825 | data_dc = self.__buffer_dc |
|
821 | data_dc = self.__buffer_dc | |
| 826 | n = self.__profIndex |
|
822 | n = self.__profIndex | |
| 827 |
|
823 | |||
| 828 | self.__buffer_spc = 0 |
|
824 | self.__buffer_spc = 0 | |
| 829 | self.__buffer_cspc = 0 |
|
825 | self.__buffer_cspc = 0 | |
| 830 | self.__buffer_dc = 0 |
|
826 | self.__buffer_dc = 0 | |
| 831 | self.__profIndex = 0 |
|
827 | self.__profIndex = 0 | |
| 832 |
|
828 | |||
| 833 | return data_spc, data_cspc, data_dc, n |
|
829 | return data_spc, data_cspc, data_dc, n | |
| 834 |
|
830 | |||
| 835 | def byProfiles(self, *args): |
|
831 | def byProfiles(self, *args): | |
| 836 |
|
832 | |||
| 837 | self.__dataReady = False |
|
833 | self.__dataReady = False | |
| 838 | avgdata_spc = None |
|
834 | avgdata_spc = None | |
| 839 | avgdata_cspc = None |
|
835 | avgdata_cspc = None | |
| 840 | avgdata_dc = None |
|
836 | avgdata_dc = None | |
| 841 |
|
837 | |||
| 842 | self.putData(*args) |
|
838 | self.putData(*args) | |
| 843 |
|
839 | |||
| 844 | if self.__profIndex == self.n: |
|
840 | if self.__profIndex == self.n: | |
| 845 |
|
841 | |||
| 846 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
842 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 847 | self.n = n |
|
843 | self.n = n | |
| 848 | self.__dataReady = True |
|
844 | self.__dataReady = True | |
| 849 |
|
845 | |||
| 850 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
846 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 851 |
|
847 | |||
| 852 | def byTime(self, datatime, *args): |
|
848 | def byTime(self, datatime, *args): | |
| 853 |
|
849 | |||
| 854 | self.__dataReady = False |
|
850 | self.__dataReady = False | |
| 855 | avgdata_spc = None |
|
851 | avgdata_spc = None | |
| 856 | avgdata_cspc = None |
|
852 | avgdata_cspc = None | |
| 857 | avgdata_dc = None |
|
853 | avgdata_dc = None | |
| 858 |
|
854 | |||
| 859 | self.putData(*args) |
|
855 | self.putData(*args) | |
| 860 |
|
856 | |||
| 861 | if (datatime - self.__initime) >= self.__integrationtime: |
|
857 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 862 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
858 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 863 | self.n = n |
|
859 | self.n = n | |
| 864 | self.__dataReady = True |
|
860 | self.__dataReady = True | |
| 865 |
|
861 | |||
| 866 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
862 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 867 |
|
863 | |||
| 868 | def integrate(self, datatime, *args): |
|
864 | def integrate(self, datatime, *args): | |
| 869 |
|
865 | |||
| 870 | if self.__profIndex == 0: |
|
866 | if self.__profIndex == 0: | |
| 871 | self.__initime = datatime |
|
867 | self.__initime = datatime | |
| 872 |
|
868 | |||
| 873 | if self.__byTime: |
|
869 | if self.__byTime: | |
| 874 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) |
|
870 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) | |
| 875 | else: |
|
871 | else: | |
| 876 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
872 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 877 |
|
873 | |||
| 878 | if not self.__dataReady: |
|
874 | if not self.__dataReady: | |
| 879 | return None, None, None, None |
|
875 | return None, None, None, None | |
| 880 |
|
876 | |||
| 881 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
877 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 882 |
|
878 | |||
| 883 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
879 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 884 | if n==1: |
|
880 | if n==1: | |
| 885 | return |
|
881 | return | |
| 886 |
|
882 | |||
| 887 | dataOut.flagNoData = True |
|
883 | dataOut.flagNoData = True | |
| 888 |
|
884 | |||
| 889 | if not self.isConfig: |
|
885 | if not self.isConfig: | |
| 890 | self.setup(n, timeInterval, overlapping) |
|
886 | self.setup(n, timeInterval, overlapping) | |
| 891 | self.isConfig = True |
|
887 | self.isConfig = True | |
| 892 |
|
888 | |||
| 893 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
889 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 894 | dataOut.data_spc, |
|
890 | dataOut.data_spc, | |
| 895 | dataOut.data_cspc, |
|
891 | dataOut.data_cspc, | |
| 896 | dataOut.data_dc) |
|
892 | dataOut.data_dc) | |
| 897 |
|
893 | |||
| 898 | if self.__dataReady: |
|
894 | if self.__dataReady: | |
| 899 |
|
895 | |||
| 900 | dataOut.data_spc = avgdata_spc |
|
896 | dataOut.data_spc = avgdata_spc | |
| 901 | dataOut.data_cspc = avgdata_cspc |
|
897 | dataOut.data_cspc = avgdata_cspc | |
| 902 | dataOut.data_dc = avgdata_dc |
|
898 | dataOut.data_dc = avgdata_dc | |
| 903 |
|
899 | |||
| 904 | dataOut.nIncohInt *= self.n |
|
900 | dataOut.nIncohInt *= self.n | |
| 905 | dataOut.utctime = avgdatatime |
|
901 | dataOut.utctime = avgdatatime | |
| 906 | dataOut.flagNoData = False |
|
902 | dataOut.flagNoData = False | |
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