| @@ -1,877 +1,904 | |||||
| 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 | class SpectraProc(ProcessingUnit): |
|
7 | class SpectraProc(ProcessingUnit): | |
| 8 |
|
8 | |||
| 9 | def __init__(self): |
|
9 | def __init__(self): | |
| 10 |
|
10 | |||
| 11 | ProcessingUnit.__init__(self) |
|
11 | ProcessingUnit.__init__(self) | |
| 12 |
|
12 | |||
| 13 | self.buffer = None |
|
13 | self.buffer = None | |
| 14 | self.firstdatatime = None |
|
14 | self.firstdatatime = None | |
| 15 | self.profIndex = 0 |
|
15 | self.profIndex = 0 | |
| 16 | self.dataOut = Spectra() |
|
16 | self.dataOut = Spectra() | |
| 17 | self.id_min = None |
|
17 | self.id_min = None | |
| 18 | self.id_max = None |
|
18 | self.id_max = None | |
| 19 |
|
19 | |||
| 20 | def __updateSpecFromVoltage(self): |
|
20 | def __updateSpecFromVoltage(self): | |
| 21 |
|
21 | |||
| 22 | self.dataOut.timeZone = self.dataIn.timeZone |
|
22 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 23 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
23 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 24 | self.dataOut.errorCount = self.dataIn.errorCount |
|
24 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 25 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
25 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 26 |
|
26 | |||
| 27 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
27 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 28 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
28 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 29 | self.dataOut.channelList = self.dataIn.channelList |
|
29 | self.dataOut.channelList = self.dataIn.channelList | |
| 30 | self.dataOut.heightList = self.dataIn.heightList |
|
30 | self.dataOut.heightList = self.dataIn.heightList | |
| 31 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
31 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 32 |
|
32 | |||
| 33 | self.dataOut.nBaud = self.dataIn.nBaud |
|
33 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 34 | self.dataOut.nCode = self.dataIn.nCode |
|
34 | self.dataOut.nCode = self.dataIn.nCode | |
| 35 | self.dataOut.code = self.dataIn.code |
|
35 | self.dataOut.code = self.dataIn.code | |
| 36 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
36 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 37 |
|
37 | |||
| 38 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
38 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 39 | self.dataOut.utctime = self.firstdatatime |
|
39 | self.dataOut.utctime = self.firstdatatime | |
| 40 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
40 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |
| 41 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
41 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |
| 42 | self.dataOut.flagShiftFFT = False |
|
42 | self.dataOut.flagShiftFFT = False | |
| 43 |
|
43 | |||
| 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
44 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 45 | self.dataOut.nIncohInt = 1 |
|
45 | self.dataOut.nIncohInt = 1 | |
| 46 |
|
46 | |||
| 47 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
47 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 48 |
|
48 | |||
| 49 | self.dataOut.frequency = self.dataIn.frequency |
|
49 | self.dataOut.frequency = self.dataIn.frequency | |
| 50 | self.dataOut.realtime = self.dataIn.realtime |
|
50 | self.dataOut.realtime = self.dataIn.realtime | |
| 51 |
|
51 | |||
| 52 | self.dataOut.azimuth = self.dataIn.azimuth |
|
52 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 53 | self.dataOut.zenith = self.dataIn.zenith |
|
53 | self.dataOut.zenith = self.dataIn.zenith | |
| 54 |
|
54 | |||
| 55 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
55 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 56 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
56 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 57 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
57 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 58 |
|
58 | |||
| 59 | def __getFft(self): |
|
59 | def __getFft(self): | |
| 60 | """ |
|
60 | """ | |
| 61 | Convierte valores de Voltaje a Spectra |
|
61 | Convierte valores de Voltaje a Spectra | |
| 62 |
|
62 | |||
| 63 | Affected: |
|
63 | Affected: | |
| 64 | self.dataOut.data_spc |
|
64 | self.dataOut.data_spc | |
| 65 | self.dataOut.data_cspc |
|
65 | self.dataOut.data_cspc | |
| 66 | self.dataOut.data_dc |
|
66 | self.dataOut.data_dc | |
| 67 | self.dataOut.heightList |
|
67 | self.dataOut.heightList | |
| 68 | self.profIndex |
|
68 | self.profIndex | |
| 69 | self.buffer |
|
69 | self.buffer | |
| 70 | self.dataOut.flagNoData |
|
70 | self.dataOut.flagNoData | |
| 71 | """ |
|
71 | """ | |
| 72 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) |
|
72 | fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1) | |
| 73 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
73 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 74 | dc = fft_volt[:,0,:] |
|
74 | dc = fft_volt[:,0,:] | |
| 75 |
|
75 | |||
| 76 | #calculo de self-spectra |
|
76 | #calculo de self-spectra | |
| 77 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) |
|
77 | fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,)) | |
| 78 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
78 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 79 | spc = spc.real |
|
79 | spc = spc.real | |
| 80 |
|
80 | |||
| 81 | blocksize = 0 |
|
81 | blocksize = 0 | |
| 82 | blocksize += dc.size |
|
82 | blocksize += dc.size | |
| 83 | blocksize += spc.size |
|
83 | blocksize += spc.size | |
| 84 |
|
84 | |||
| 85 | cspc = None |
|
85 | cspc = None | |
| 86 | pairIndex = 0 |
|
86 | pairIndex = 0 | |
| 87 | if self.dataOut.pairsList != None: |
|
87 | if self.dataOut.pairsList != None: | |
| 88 | #calculo de cross-spectra |
|
88 | #calculo de cross-spectra | |
| 89 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
89 | cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 90 | for pair in self.dataOut.pairsList: |
|
90 | for pair in self.dataOut.pairsList: | |
| 91 | if pair[0] not in self.dataOut.channelList: |
|
91 | if pair[0] not in self.dataOut.channelList: | |
| 92 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
92 | raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 93 | if pair[1] not in self.dataOut.channelList: |
|
93 | if pair[1] not in self.dataOut.channelList: | |
| 94 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) |
|
94 | raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList)) | |
| 95 |
|
95 | |||
| 96 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) |
|
96 | cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:]) | |
| 97 | pairIndex += 1 |
|
97 | pairIndex += 1 | |
| 98 | blocksize += cspc.size |
|
98 | blocksize += cspc.size | |
| 99 |
|
99 | |||
| 100 | self.dataOut.data_spc = spc |
|
100 | self.dataOut.data_spc = spc | |
| 101 | self.dataOut.data_cspc = cspc |
|
101 | self.dataOut.data_cspc = cspc | |
| 102 | self.dataOut.data_dc = dc |
|
102 | self.dataOut.data_dc = dc | |
| 103 | self.dataOut.blockSize = blocksize |
|
103 | self.dataOut.blockSize = blocksize | |
| 104 | self.dataOut.flagShiftFFT = True |
|
104 | self.dataOut.flagShiftFFT = True | |
| 105 |
|
105 | |||
| 106 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): |
|
106 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None): | |
| 107 |
|
107 | |||
| 108 | self.dataOut.flagNoData = True |
|
108 | self.dataOut.flagNoData = True | |
| 109 |
|
109 | |||
| 110 | if self.dataIn.type == "Spectra": |
|
110 | if self.dataIn.type == "Spectra": | |
| 111 | self.dataOut.copy(self.dataIn) |
|
111 | self.dataOut.copy(self.dataIn) | |
|
|
112 | # self.__selectPairs(pairsList) | |||
| 112 | return True |
|
113 | return True | |
| 113 |
|
114 | |||
| 114 | if self.dataIn.type == "Voltage": |
|
115 | if self.dataIn.type == "Voltage": | |
| 115 |
|
116 | |||
| 116 | if nFFTPoints == None: |
|
117 | if nFFTPoints == None: | |
| 117 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" |
|
118 | raise ValueError, "This SpectraProc.run() need nFFTPoints input variable" | |
| 118 |
|
119 | |||
| 119 | if nProfiles == None: |
|
120 | if nProfiles == None: | |
| 120 | nProfiles = nFFTPoints |
|
121 | nProfiles = nFFTPoints | |
| 121 |
|
122 | |||
| 122 | if ippFactor == None: |
|
123 | if ippFactor == None: | |
| 123 | ippFactor = 1 |
|
124 | ippFactor = 1 | |
| 124 |
|
125 | |||
| 125 | self.dataOut.ippFactor = ippFactor |
|
126 | self.dataOut.ippFactor = ippFactor | |
| 126 |
|
127 | |||
| 127 | self.dataOut.nFFTPoints = nFFTPoints |
|
128 | self.dataOut.nFFTPoints = nFFTPoints | |
| 128 | self.dataOut.pairsList = pairsList |
|
129 | self.dataOut.pairsList = pairsList | |
| 129 |
|
130 | |||
| 130 | if self.buffer is None: |
|
131 | if self.buffer is None: | |
| 131 | self.buffer = numpy.zeros( (self.dataIn.nChannels, |
|
132 | self.buffer = numpy.zeros( (self.dataIn.nChannels, | |
| 132 | nProfiles, |
|
133 | nProfiles, | |
| 133 | self.dataIn.nHeights), |
|
134 | self.dataIn.nHeights), | |
| 134 | dtype='complex') |
|
135 | dtype='complex') | |
| 135 |
|
136 | |||
| 136 | if self.dataIn.flagDataAsBlock: |
|
137 | if self.dataIn.flagDataAsBlock: | |
| 137 | #data dimension: [nChannels, nProfiles, nSamples] |
|
138 | #data dimension: [nChannels, nProfiles, nSamples] | |
| 138 | nVoltProfiles = self.dataIn.data.shape[1] |
|
139 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 139 | nVoltProfiles = self.dataIn.nProfiles |
|
140 | # nVoltProfiles = self.dataIn.nProfiles | |
| 140 |
|
141 | |||
| 141 | if nVoltProfiles == nProfiles: |
|
142 | if nVoltProfiles == nProfiles: | |
| 142 | self.buffer = self.dataIn.data.copy() |
|
143 | self.buffer = self.dataIn.data.copy() | |
| 143 | self.profIndex = nVoltProfiles |
|
144 | self.profIndex = nVoltProfiles | |
| 144 |
|
145 | |||
| 145 | elif nVoltProfiles < nProfiles: |
|
146 | elif nVoltProfiles < nProfiles: | |
| 146 |
|
147 | |||
| 147 | if self.profIndex == 0: |
|
148 | if self.profIndex == 0: | |
| 148 | self.id_min = 0 |
|
149 | self.id_min = 0 | |
| 149 | self.id_max = nVoltProfiles |
|
150 | self.id_max = nVoltProfiles | |
| 150 |
|
151 | |||
| 151 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data |
|
152 | self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data | |
| 152 | self.profIndex += nVoltProfiles |
|
153 | self.profIndex += nVoltProfiles | |
| 153 | self.id_min += nVoltProfiles |
|
154 | self.id_min += nVoltProfiles | |
| 154 | self.id_max += nVoltProfiles |
|
155 | self.id_max += nVoltProfiles | |
| 155 | else: |
|
156 | else: | |
| 156 | raise ValueError, "The type object %s has %d profiles, it should be equal to %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) |
|
157 | raise ValueError, "The type object %s has %d profiles, it should be equal to %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles) | |
| 157 | self.dataOut.flagNoData = True |
|
158 | self.dataOut.flagNoData = True | |
| 158 | return 0 |
|
159 | return 0 | |
| 159 | else: |
|
160 | else: | |
| 160 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() |
|
161 | self.buffer[:,self.profIndex,:] = self.dataIn.data.copy() | |
| 161 | self.profIndex += 1 |
|
162 | self.profIndex += 1 | |
| 162 |
|
163 | |||
| 163 | if self.firstdatatime == None: |
|
164 | if self.firstdatatime == None: | |
| 164 | self.firstdatatime = self.dataIn.utctime |
|
165 | self.firstdatatime = self.dataIn.utctime | |
| 165 |
|
166 | |||
| 166 | if self.profIndex == nProfiles: |
|
167 | if self.profIndex == nProfiles: | |
| 167 | self.__updateSpecFromVoltage() |
|
168 | self.__updateSpecFromVoltage() | |
| 168 | self.__getFft() |
|
169 | self.__getFft() | |
| 169 |
|
170 | |||
| 170 | self.dataOut.flagNoData = False |
|
171 | self.dataOut.flagNoData = False | |
| 171 | self.firstdatatime = None |
|
172 | self.firstdatatime = None | |
| 172 | self.profIndex = 0 |
|
173 | self.profIndex = 0 | |
| 173 |
|
174 | |||
| 174 | return True |
|
175 | return True | |
| 175 |
|
176 | |||
| 176 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) |
|
177 | raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type) | |
| 177 |
|
178 | |||
| 178 |
def __selectPairs(self, |
|
179 | def __selectPairs(self, pairsList): | |
|
|
180 | ||||
|
|
181 | if channelList == None: | |||
|
|
182 | return | |||
|
|
183 | ||||
|
|
184 | pairsIndexListSelected = [] | |||
|
|
185 | ||||
|
|
186 | for thisPair in pairsList: | |||
|
|
187 | ||||
|
|
188 | if thisPair not in self.dataOut.pairsList: | |||
|
|
189 | continue | |||
|
|
190 | ||||
|
|
191 | pairIndex = self.dataOut.pairsList.index(thisPair) | |||
|
|
192 | ||||
|
|
193 | pairsIndexListSelected.append(pairIndex) | |||
|
|
194 | ||||
|
|
195 | if not pairsIndexListSelected: | |||
|
|
196 | self.dataOut.data_cspc = None | |||
|
|
197 | self.dataOut.pairsList = [] | |||
|
|
198 | return | |||
|
|
199 | ||||
|
|
200 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |||
|
|
201 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |||
|
|
202 | ||||
|
|
203 | return | |||
|
|
204 | ||||
|
|
205 | def __selectPairsByChannel(self, channelList=None): | |||
| 179 |
|
206 | |||
| 180 | if channelList == None: |
|
207 | if channelList == None: | |
| 181 | return |
|
208 | return | |
| 182 |
|
209 | |||
| 183 | pairsIndexListSelected = [] |
|
210 | pairsIndexListSelected = [] | |
| 184 | for pairIndex in self.dataOut.pairsIndexList: |
|
211 | for pairIndex in self.dataOut.pairsIndexList: | |
| 185 | #First pair |
|
212 | #First pair | |
| 186 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
213 | if self.dataOut.pairsList[pairIndex][0] not in channelList: | |
| 187 | continue |
|
214 | continue | |
| 188 | #Second pair |
|
215 | #Second pair | |
| 189 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
216 | if self.dataOut.pairsList[pairIndex][1] not in channelList: | |
| 190 | continue |
|
217 | continue | |
| 191 |
|
218 | |||
| 192 | pairsIndexListSelected.append(pairIndex) |
|
219 | pairsIndexListSelected.append(pairIndex) | |
| 193 |
|
220 | |||
| 194 | if not pairsIndexListSelected: |
|
221 | if not pairsIndexListSelected: | |
| 195 | self.dataOut.data_cspc = None |
|
222 | self.dataOut.data_cspc = None | |
| 196 | self.dataOut.pairsList = [] |
|
223 | self.dataOut.pairsList = [] | |
| 197 | return |
|
224 | return | |
| 198 |
|
225 | |||
| 199 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
226 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 200 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] |
|
227 | self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected] | |
| 201 |
|
228 | |||
| 202 | return |
|
229 | return | |
| 203 |
|
230 | |||
| 204 | def selectChannels(self, channelList): |
|
231 | def selectChannels(self, channelList): | |
| 205 |
|
232 | |||
| 206 | channelIndexList = [] |
|
233 | channelIndexList = [] | |
| 207 |
|
234 | |||
| 208 | for channel in channelList: |
|
235 | for channel in channelList: | |
| 209 | if channel not in self.dataOut.channelList: |
|
236 | if channel not in self.dataOut.channelList: | |
| 210 |
raise ValueError, "Error selecting channels |
|
237 | raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList)) | |
| 211 |
|
238 | |||
| 212 | index = self.dataOut.channelList.index(channel) |
|
239 | index = self.dataOut.channelList.index(channel) | |
| 213 | channelIndexList.append(index) |
|
240 | channelIndexList.append(index) | |
| 214 |
|
241 | |||
| 215 | self.selectChannelsByIndex(channelIndexList) |
|
242 | self.selectChannelsByIndex(channelIndexList) | |
| 216 |
|
243 | |||
| 217 | def selectChannelsByIndex(self, channelIndexList): |
|
244 | def selectChannelsByIndex(self, channelIndexList): | |
| 218 | """ |
|
245 | """ | |
| 219 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
246 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 220 |
|
247 | |||
| 221 | Input: |
|
248 | Input: | |
| 222 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
249 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 223 |
|
250 | |||
| 224 | Affected: |
|
251 | Affected: | |
| 225 | self.dataOut.data_spc |
|
252 | self.dataOut.data_spc | |
| 226 | self.dataOut.channelIndexList |
|
253 | self.dataOut.channelIndexList | |
| 227 | self.dataOut.nChannels |
|
254 | self.dataOut.nChannels | |
| 228 |
|
255 | |||
| 229 | Return: |
|
256 | Return: | |
| 230 | None |
|
257 | None | |
| 231 | """ |
|
258 | """ | |
| 232 |
|
259 | |||
| 233 | for channelIndex in channelIndexList: |
|
260 | for channelIndex in channelIndexList: | |
| 234 | if channelIndex not in self.dataOut.channelIndexList: |
|
261 | if channelIndex not in self.dataOut.channelIndexList: | |
| 235 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) |
|
262 | raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList) | |
| 236 |
|
263 | |||
| 237 | # nChannels = len(channelIndexList) |
|
264 | # nChannels = len(channelIndexList) | |
| 238 |
|
265 | |||
| 239 | data_spc = self.dataOut.data_spc[channelIndexList,:] |
|
266 | data_spc = self.dataOut.data_spc[channelIndexList,:] | |
| 240 | data_dc = self.dataOut.data_dc[channelIndexList,:] |
|
267 | data_dc = self.dataOut.data_dc[channelIndexList,:] | |
| 241 |
|
268 | |||
| 242 | self.dataOut.data_spc = data_spc |
|
269 | self.dataOut.data_spc = data_spc | |
| 243 | self.dataOut.data_dc = data_dc |
|
270 | self.dataOut.data_dc = data_dc | |
| 244 |
|
271 | |||
| 245 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
272 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 246 | # self.dataOut.nChannels = nChannels |
|
273 | # self.dataOut.nChannels = nChannels | |
| 247 |
|
274 | |||
| 248 | self.__selectPairs(self.dataOut.channelList) |
|
275 | self.__selectPairsByChannel(self.dataOut.channelList) | |
| 249 |
|
276 | |||
| 250 | return 1 |
|
277 | return 1 | |
| 251 |
|
278 | |||
| 252 | def selectHeights(self, minHei, maxHei): |
|
279 | def selectHeights(self, minHei, maxHei): | |
| 253 | """ |
|
280 | """ | |
| 254 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
281 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 255 | minHei <= height <= maxHei |
|
282 | minHei <= height <= maxHei | |
| 256 |
|
283 | |||
| 257 | Input: |
|
284 | Input: | |
| 258 | minHei : valor minimo de altura a considerar |
|
285 | minHei : valor minimo de altura a considerar | |
| 259 | maxHei : valor maximo de altura a considerar |
|
286 | maxHei : valor maximo de altura a considerar | |
| 260 |
|
287 | |||
| 261 | Affected: |
|
288 | Affected: | |
| 262 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
289 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 263 |
|
290 | |||
| 264 | Return: |
|
291 | Return: | |
| 265 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
292 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 266 | """ |
|
293 | """ | |
| 267 |
|
294 | |||
| 268 | if (minHei > maxHei): |
|
295 | if (minHei > maxHei): | |
| 269 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) |
|
296 | raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei) | |
| 270 |
|
297 | |||
| 271 | if (minHei < self.dataOut.heightList[0]): |
|
298 | if (minHei < self.dataOut.heightList[0]): | |
| 272 | minHei = self.dataOut.heightList[0] |
|
299 | minHei = self.dataOut.heightList[0] | |
| 273 |
|
300 | |||
| 274 | if (maxHei > self.dataOut.heightList[-1]): |
|
301 | if (maxHei > self.dataOut.heightList[-1]): | |
| 275 | maxHei = self.dataOut.heightList[-1] |
|
302 | maxHei = self.dataOut.heightList[-1] | |
| 276 |
|
303 | |||
| 277 | minIndex = 0 |
|
304 | minIndex = 0 | |
| 278 | maxIndex = 0 |
|
305 | maxIndex = 0 | |
| 279 | heights = self.dataOut.heightList |
|
306 | heights = self.dataOut.heightList | |
| 280 |
|
307 | |||
| 281 | inda = numpy.where(heights >= minHei) |
|
308 | inda = numpy.where(heights >= minHei) | |
| 282 | indb = numpy.where(heights <= maxHei) |
|
309 | indb = numpy.where(heights <= maxHei) | |
| 283 |
|
310 | |||
| 284 | try: |
|
311 | try: | |
| 285 | minIndex = inda[0][0] |
|
312 | minIndex = inda[0][0] | |
| 286 | except: |
|
313 | except: | |
| 287 | minIndex = 0 |
|
314 | minIndex = 0 | |
| 288 |
|
315 | |||
| 289 | try: |
|
316 | try: | |
| 290 | maxIndex = indb[0][-1] |
|
317 | maxIndex = indb[0][-1] | |
| 291 | except: |
|
318 | except: | |
| 292 | maxIndex = len(heights) |
|
319 | maxIndex = len(heights) | |
| 293 |
|
320 | |||
| 294 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
321 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 295 |
|
322 | |||
| 296 | return 1 |
|
323 | return 1 | |
| 297 |
|
324 | |||
| 298 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): |
|
325 | def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None): | |
| 299 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
326 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 300 |
|
327 | |||
| 301 | if hei_ref != None: |
|
328 | if hei_ref != None: | |
| 302 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
329 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 303 |
|
330 | |||
| 304 | minIndex = min(newheis[0]) |
|
331 | minIndex = min(newheis[0]) | |
| 305 | maxIndex = max(newheis[0]) |
|
332 | maxIndex = max(newheis[0]) | |
| 306 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
333 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 307 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
334 | heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 308 |
|
335 | |||
| 309 | # determina indices |
|
336 | # determina indices | |
| 310 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) |
|
337 | nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0])) | |
| 311 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) |
|
338 | avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0)) | |
| 312 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
339 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 313 | beacon_heiIndexList = [] |
|
340 | beacon_heiIndexList = [] | |
| 314 | for val in avg_dB.tolist(): |
|
341 | for val in avg_dB.tolist(): | |
| 315 | if val >= beacon_dB[0]: |
|
342 | if val >= beacon_dB[0]: | |
| 316 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
343 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 317 |
|
344 | |||
| 318 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
345 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 319 | data_cspc = None |
|
346 | data_cspc = None | |
| 320 | if self.dataOut.data_cspc is not None: |
|
347 | if self.dataOut.data_cspc is not None: | |
| 321 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
348 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 322 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
349 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 323 |
|
350 | |||
| 324 | data_dc = None |
|
351 | data_dc = None | |
| 325 | if self.dataOut.data_dc is not None: |
|
352 | if self.dataOut.data_dc is not None: | |
| 326 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
353 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 327 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
354 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 328 |
|
355 | |||
| 329 | self.dataOut.data_spc = data_spc |
|
356 | self.dataOut.data_spc = data_spc | |
| 330 | self.dataOut.data_cspc = data_cspc |
|
357 | self.dataOut.data_cspc = data_cspc | |
| 331 | self.dataOut.data_dc = data_dc |
|
358 | self.dataOut.data_dc = data_dc | |
| 332 | self.dataOut.heightList = heightList |
|
359 | self.dataOut.heightList = heightList | |
| 333 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
360 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 334 |
|
361 | |||
| 335 | return 1 |
|
362 | return 1 | |
| 336 |
|
363 | |||
| 337 |
|
364 | |||
| 338 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
365 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 339 | """ |
|
366 | """ | |
| 340 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
367 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 341 | minIndex <= index <= maxIndex |
|
368 | minIndex <= index <= maxIndex | |
| 342 |
|
369 | |||
| 343 | Input: |
|
370 | Input: | |
| 344 | minIndex : valor de indice minimo de altura a considerar |
|
371 | minIndex : valor de indice minimo de altura a considerar | |
| 345 | maxIndex : valor de indice maximo de altura a considerar |
|
372 | maxIndex : valor de indice maximo de altura a considerar | |
| 346 |
|
373 | |||
| 347 | Affected: |
|
374 | Affected: | |
| 348 | self.dataOut.data_spc |
|
375 | self.dataOut.data_spc | |
| 349 | self.dataOut.data_cspc |
|
376 | self.dataOut.data_cspc | |
| 350 | self.dataOut.data_dc |
|
377 | self.dataOut.data_dc | |
| 351 | self.dataOut.heightList |
|
378 | self.dataOut.heightList | |
| 352 |
|
379 | |||
| 353 | Return: |
|
380 | Return: | |
| 354 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
381 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 355 | """ |
|
382 | """ | |
| 356 |
|
383 | |||
| 357 | if (minIndex < 0) or (minIndex > maxIndex): |
|
384 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 358 |
raise ValueError, "Error selecting heights |
|
385 | raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 359 |
|
386 | |||
| 360 | if (maxIndex >= self.dataOut.nHeights): |
|
387 | if (maxIndex >= self.dataOut.nHeights): | |
| 361 | maxIndex = self.dataOut.nHeights-1 |
|
388 | maxIndex = self.dataOut.nHeights-1 | |
| 362 |
|
389 | |||
| 363 | #Spectra |
|
390 | #Spectra | |
| 364 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] |
|
391 | data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1] | |
| 365 |
|
392 | |||
| 366 | data_cspc = None |
|
393 | data_cspc = None | |
| 367 | if self.dataOut.data_cspc is not None: |
|
394 | if self.dataOut.data_cspc is not None: | |
| 368 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] |
|
395 | data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1] | |
| 369 |
|
396 | |||
| 370 | data_dc = None |
|
397 | data_dc = None | |
| 371 | if self.dataOut.data_dc is not None: |
|
398 | if self.dataOut.data_dc is not None: | |
| 372 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] |
|
399 | data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1] | |
| 373 |
|
400 | |||
| 374 | self.dataOut.data_spc = data_spc |
|
401 | self.dataOut.data_spc = data_spc | |
| 375 | self.dataOut.data_cspc = data_cspc |
|
402 | self.dataOut.data_cspc = data_cspc | |
| 376 | self.dataOut.data_dc = data_dc |
|
403 | self.dataOut.data_dc = data_dc | |
| 377 |
|
404 | |||
| 378 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] |
|
405 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1] | |
| 379 |
|
406 | |||
| 380 | return 1 |
|
407 | return 1 | |
| 381 |
|
408 | |||
| 382 | def removeDC(self, mode = 2): |
|
409 | def removeDC(self, mode = 2): | |
| 383 | jspectra = self.dataOut.data_spc |
|
410 | jspectra = self.dataOut.data_spc | |
| 384 | jcspectra = self.dataOut.data_cspc |
|
411 | jcspectra = self.dataOut.data_cspc | |
| 385 |
|
412 | |||
| 386 |
|
413 | |||
| 387 | num_chan = jspectra.shape[0] |
|
414 | num_chan = jspectra.shape[0] | |
| 388 | num_hei = jspectra.shape[2] |
|
415 | num_hei = jspectra.shape[2] | |
| 389 |
|
416 | |||
| 390 | if jcspectra is not None: |
|
417 | if jcspectra is not None: | |
| 391 | jcspectraExist = True |
|
418 | jcspectraExist = True | |
| 392 | num_pairs = jcspectra.shape[0] |
|
419 | num_pairs = jcspectra.shape[0] | |
| 393 | else: jcspectraExist = False |
|
420 | else: jcspectraExist = False | |
| 394 |
|
421 | |||
| 395 | freq_dc = jspectra.shape[1]/2 |
|
422 | freq_dc = jspectra.shape[1]/2 | |
| 396 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc |
|
423 | ind_vel = numpy.array([-2,-1,1,2]) + freq_dc | |
| 397 |
|
424 | |||
| 398 | if ind_vel[0]<0: |
|
425 | if ind_vel[0]<0: | |
| 399 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof |
|
426 | ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof | |
| 400 |
|
427 | |||
| 401 | if mode == 1: |
|
428 | if mode == 1: | |
| 402 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION |
|
429 | jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION | |
| 403 |
|
430 | |||
| 404 | if jcspectraExist: |
|
431 | if jcspectraExist: | |
| 405 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 |
|
432 | jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2 | |
| 406 |
|
433 | |||
| 407 | if mode == 2: |
|
434 | if mode == 2: | |
| 408 |
|
435 | |||
| 409 | vel = numpy.array([-2,-1,1,2]) |
|
436 | vel = numpy.array([-2,-1,1,2]) | |
| 410 | xx = numpy.zeros([4,4]) |
|
437 | xx = numpy.zeros([4,4]) | |
| 411 |
|
438 | |||
| 412 | for fil in range(4): |
|
439 | for fil in range(4): | |
| 413 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) |
|
440 | xx[fil,:] = vel[fil]**numpy.asarray(range(4)) | |
| 414 |
|
441 | |||
| 415 | xx_inv = numpy.linalg.inv(xx) |
|
442 | xx_inv = numpy.linalg.inv(xx) | |
| 416 | xx_aux = xx_inv[0,:] |
|
443 | xx_aux = xx_inv[0,:] | |
| 417 |
|
444 | |||
| 418 | for ich in range(num_chan): |
|
445 | for ich in range(num_chan): | |
| 419 | yy = jspectra[ich,ind_vel,:] |
|
446 | yy = jspectra[ich,ind_vel,:] | |
| 420 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
447 | jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 421 |
|
448 | |||
| 422 | junkid = jspectra[ich,freq_dc,:]<=0 |
|
449 | junkid = jspectra[ich,freq_dc,:]<=0 | |
| 423 | cjunkid = sum(junkid) |
|
450 | cjunkid = sum(junkid) | |
| 424 |
|
451 | |||
| 425 | if cjunkid.any(): |
|
452 | if cjunkid.any(): | |
| 426 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 |
|
453 | jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2 | |
| 427 |
|
454 | |||
| 428 | if jcspectraExist: |
|
455 | if jcspectraExist: | |
| 429 | for ip in range(num_pairs): |
|
456 | for ip in range(num_pairs): | |
| 430 | yy = jcspectra[ip,ind_vel,:] |
|
457 | yy = jcspectra[ip,ind_vel,:] | |
| 431 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) |
|
458 | jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy) | |
| 432 |
|
459 | |||
| 433 |
|
460 | |||
| 434 | self.dataOut.data_spc = jspectra |
|
461 | self.dataOut.data_spc = jspectra | |
| 435 | self.dataOut.data_cspc = jcspectra |
|
462 | self.dataOut.data_cspc = jcspectra | |
| 436 |
|
463 | |||
| 437 | return 1 |
|
464 | return 1 | |
| 438 |
|
465 | |||
| 439 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
466 | def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 440 |
|
467 | |||
| 441 | jspectra = self.dataOut.data_spc |
|
468 | jspectra = self.dataOut.data_spc | |
| 442 | jcspectra = self.dataOut.data_cspc |
|
469 | jcspectra = self.dataOut.data_cspc | |
| 443 | jnoise = self.dataOut.getNoise() |
|
470 | jnoise = self.dataOut.getNoise() | |
| 444 | num_incoh = self.dataOut.nIncohInt |
|
471 | num_incoh = self.dataOut.nIncohInt | |
| 445 |
|
472 | |||
| 446 | num_channel = jspectra.shape[0] |
|
473 | num_channel = jspectra.shape[0] | |
| 447 | num_prof = jspectra.shape[1] |
|
474 | num_prof = jspectra.shape[1] | |
| 448 | num_hei = jspectra.shape[2] |
|
475 | num_hei = jspectra.shape[2] | |
| 449 |
|
476 | |||
| 450 | #hei_interf |
|
477 | #hei_interf | |
| 451 | if hei_interf is None: |
|
478 | if hei_interf is None: | |
| 452 | count_hei = num_hei/2 #Como es entero no importa |
|
479 | count_hei = num_hei/2 #Como es entero no importa | |
| 453 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei |
|
480 | hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei | |
| 454 | hei_interf = numpy.asarray(hei_interf)[0] |
|
481 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 455 | #nhei_interf |
|
482 | #nhei_interf | |
| 456 | if (nhei_interf == None): |
|
483 | if (nhei_interf == None): | |
| 457 | nhei_interf = 5 |
|
484 | nhei_interf = 5 | |
| 458 | if (nhei_interf < 1): |
|
485 | if (nhei_interf < 1): | |
| 459 | nhei_interf = 1 |
|
486 | nhei_interf = 1 | |
| 460 | if (nhei_interf > count_hei): |
|
487 | if (nhei_interf > count_hei): | |
| 461 | nhei_interf = count_hei |
|
488 | nhei_interf = count_hei | |
| 462 | if (offhei_interf == None): |
|
489 | if (offhei_interf == None): | |
| 463 | offhei_interf = 0 |
|
490 | offhei_interf = 0 | |
| 464 |
|
491 | |||
| 465 | ind_hei = range(num_hei) |
|
492 | ind_hei = range(num_hei) | |
| 466 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
493 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 467 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
494 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 468 | mask_prof = numpy.asarray(range(num_prof)) |
|
495 | mask_prof = numpy.asarray(range(num_prof)) | |
| 469 | num_mask_prof = mask_prof.size |
|
496 | num_mask_prof = mask_prof.size | |
| 470 | comp_mask_prof = [0, num_prof/2] |
|
497 | comp_mask_prof = [0, num_prof/2] | |
| 471 |
|
498 | |||
| 472 |
|
499 | |||
| 473 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
500 | #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 474 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
501 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 475 | jnoise = numpy.nan |
|
502 | jnoise = numpy.nan | |
| 476 | noise_exist = jnoise[0] < numpy.Inf |
|
503 | noise_exist = jnoise[0] < numpy.Inf | |
| 477 |
|
504 | |||
| 478 | #Subrutina de Remocion de la Interferencia |
|
505 | #Subrutina de Remocion de la Interferencia | |
| 479 | for ich in range(num_channel): |
|
506 | for ich in range(num_channel): | |
| 480 | #Se ordena los espectros segun su potencia (menor a mayor) |
|
507 | #Se ordena los espectros segun su potencia (menor a mayor) | |
| 481 | power = jspectra[ich,mask_prof,:] |
|
508 | power = jspectra[ich,mask_prof,:] | |
| 482 | power = power[:,hei_interf] |
|
509 | power = power[:,hei_interf] | |
| 483 | power = power.sum(axis = 0) |
|
510 | power = power.sum(axis = 0) | |
| 484 | psort = power.ravel().argsort() |
|
511 | psort = power.ravel().argsort() | |
| 485 |
|
512 | |||
| 486 | #Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
513 | #Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 487 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
514 | junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 488 |
|
515 | |||
| 489 | if noise_exist: |
|
516 | if noise_exist: | |
| 490 | # tmp_noise = jnoise[ich] / num_prof |
|
517 | # tmp_noise = jnoise[ich] / num_prof | |
| 491 | tmp_noise = jnoise[ich] |
|
518 | tmp_noise = jnoise[ich] | |
| 492 | junkspc_interf = junkspc_interf - tmp_noise |
|
519 | junkspc_interf = junkspc_interf - tmp_noise | |
| 493 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
520 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 494 |
|
521 | |||
| 495 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf |
|
522 | jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf | |
| 496 | jspc_interf = jspc_interf.transpose() |
|
523 | jspc_interf = jspc_interf.transpose() | |
| 497 | #Calculando el espectro de interferencia promedio |
|
524 | #Calculando el espectro de interferencia promedio | |
| 498 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) |
|
525 | noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh)) | |
| 499 | noiseid = noiseid[0] |
|
526 | noiseid = noiseid[0] | |
| 500 | cnoiseid = noiseid.size |
|
527 | cnoiseid = noiseid.size | |
| 501 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) |
|
528 | interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh)) | |
| 502 | interfid = interfid[0] |
|
529 | interfid = interfid[0] | |
| 503 | cinterfid = interfid.size |
|
530 | cinterfid = interfid.size | |
| 504 |
|
531 | |||
| 505 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 |
|
532 | if (cnoiseid > 0): jspc_interf[noiseid] = 0 | |
| 506 |
|
533 | |||
| 507 | #Expandiendo los perfiles a limpiar |
|
534 | #Expandiendo los perfiles a limpiar | |
| 508 | if (cinterfid > 0): |
|
535 | if (cinterfid > 0): | |
| 509 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof |
|
536 | new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof | |
| 510 | new_interfid = numpy.asarray(new_interfid) |
|
537 | new_interfid = numpy.asarray(new_interfid) | |
| 511 | new_interfid = {x for x in new_interfid} |
|
538 | new_interfid = {x for x in new_interfid} | |
| 512 | new_interfid = numpy.array(list(new_interfid)) |
|
539 | new_interfid = numpy.array(list(new_interfid)) | |
| 513 | new_cinterfid = new_interfid.size |
|
540 | new_cinterfid = new_interfid.size | |
| 514 | else: new_cinterfid = 0 |
|
541 | else: new_cinterfid = 0 | |
| 515 |
|
542 | |||
| 516 | for ip in range(new_cinterfid): |
|
543 | for ip in range(new_cinterfid): | |
| 517 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() |
|
544 | ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort() | |
| 518 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] |
|
545 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]] | |
| 519 |
|
546 | |||
| 520 |
|
547 | |||
| 521 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices |
|
548 | jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices | |
| 522 |
|
549 | |||
| 523 | #Removiendo la interferencia del punto de mayor interferencia |
|
550 | #Removiendo la interferencia del punto de mayor interferencia | |
| 524 | ListAux = jspc_interf[mask_prof].tolist() |
|
551 | ListAux = jspc_interf[mask_prof].tolist() | |
| 525 | maxid = ListAux.index(max(ListAux)) |
|
552 | maxid = ListAux.index(max(ListAux)) | |
| 526 |
|
553 | |||
| 527 |
|
554 | |||
| 528 | if cinterfid > 0: |
|
555 | if cinterfid > 0: | |
| 529 | for ip in range(cinterfid*(interf == 2) - 1): |
|
556 | for ip in range(cinterfid*(interf == 2) - 1): | |
| 530 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() |
|
557 | ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero() | |
| 531 | cind = len(ind) |
|
558 | cind = len(ind) | |
| 532 |
|
559 | |||
| 533 | if (cind > 0): |
|
560 | if (cind > 0): | |
| 534 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) |
|
561 | jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh)) | |
| 535 |
|
562 | |||
| 536 | ind = numpy.array([-2,-1,1,2]) |
|
563 | ind = numpy.array([-2,-1,1,2]) | |
| 537 | xx = numpy.zeros([4,4]) |
|
564 | xx = numpy.zeros([4,4]) | |
| 538 |
|
565 | |||
| 539 | for id1 in range(4): |
|
566 | for id1 in range(4): | |
| 540 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
567 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 541 |
|
568 | |||
| 542 | xx_inv = numpy.linalg.inv(xx) |
|
569 | xx_inv = numpy.linalg.inv(xx) | |
| 543 | xx = xx_inv[:,0] |
|
570 | xx = xx_inv[:,0] | |
| 544 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
571 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 545 | yy = jspectra[ich,mask_prof[ind],:] |
|
572 | yy = jspectra[ich,mask_prof[ind],:] | |
| 546 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
573 | jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 547 |
|
574 | |||
| 548 |
|
575 | |||
| 549 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() |
|
576 | indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero() | |
| 550 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) |
|
577 | jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh)) | |
| 551 |
|
578 | |||
| 552 | #Remocion de Interferencia en el Cross Spectra |
|
579 | #Remocion de Interferencia en el Cross Spectra | |
| 553 | if jcspectra is None: return jspectra, jcspectra |
|
580 | if jcspectra is None: return jspectra, jcspectra | |
| 554 | num_pairs = jcspectra.size/(num_prof*num_hei) |
|
581 | num_pairs = jcspectra.size/(num_prof*num_hei) | |
| 555 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
582 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 556 |
|
583 | |||
| 557 | for ip in range(num_pairs): |
|
584 | for ip in range(num_pairs): | |
| 558 |
|
585 | |||
| 559 | #------------------------------------------- |
|
586 | #------------------------------------------- | |
| 560 |
|
587 | |||
| 561 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) |
|
588 | cspower = numpy.abs(jcspectra[ip,mask_prof,:]) | |
| 562 | cspower = cspower[:,hei_interf] |
|
589 | cspower = cspower[:,hei_interf] | |
| 563 | cspower = cspower.sum(axis = 0) |
|
590 | cspower = cspower.sum(axis = 0) | |
| 564 |
|
591 | |||
| 565 | cspsort = cspower.ravel().argsort() |
|
592 | cspsort = cspower.ravel().argsort() | |
| 566 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] |
|
593 | junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]] | |
| 567 | junkcspc_interf = junkcspc_interf.transpose() |
|
594 | junkcspc_interf = junkcspc_interf.transpose() | |
| 568 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf |
|
595 | jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf | |
| 569 |
|
596 | |||
| 570 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
597 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 571 |
|
598 | |||
| 572 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
599 | median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 573 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) |
|
600 | median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:])) | |
| 574 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) |
|
601 | junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag) | |
| 575 |
|
602 | |||
| 576 | for iprof in range(num_prof): |
|
603 | for iprof in range(num_prof): | |
| 577 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() |
|
604 | ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort() | |
| 578 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] |
|
605 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]] | |
| 579 |
|
606 | |||
| 580 | #Removiendo la Interferencia |
|
607 | #Removiendo la Interferencia | |
| 581 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf |
|
608 | jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf | |
| 582 |
|
609 | |||
| 583 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
610 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 584 | maxid = ListAux.index(max(ListAux)) |
|
611 | maxid = ListAux.index(max(ListAux)) | |
| 585 |
|
612 | |||
| 586 | ind = numpy.array([-2,-1,1,2]) |
|
613 | ind = numpy.array([-2,-1,1,2]) | |
| 587 | xx = numpy.zeros([4,4]) |
|
614 | xx = numpy.zeros([4,4]) | |
| 588 |
|
615 | |||
| 589 | for id1 in range(4): |
|
616 | for id1 in range(4): | |
| 590 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) |
|
617 | xx[:,id1] = ind[id1]**numpy.asarray(range(4)) | |
| 591 |
|
618 | |||
| 592 | xx_inv = numpy.linalg.inv(xx) |
|
619 | xx_inv = numpy.linalg.inv(xx) | |
| 593 | xx = xx_inv[:,0] |
|
620 | xx = xx_inv[:,0] | |
| 594 |
|
621 | |||
| 595 | ind = (ind + maxid + num_mask_prof)%num_mask_prof |
|
622 | ind = (ind + maxid + num_mask_prof)%num_mask_prof | |
| 596 | yy = jcspectra[ip,mask_prof[ind],:] |
|
623 | yy = jcspectra[ip,mask_prof[ind],:] | |
| 597 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) |
|
624 | jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx) | |
| 598 |
|
625 | |||
| 599 | #Guardar Resultados |
|
626 | #Guardar Resultados | |
| 600 | self.dataOut.data_spc = jspectra |
|
627 | self.dataOut.data_spc = jspectra | |
| 601 | self.dataOut.data_cspc = jcspectra |
|
628 | self.dataOut.data_cspc = jcspectra | |
| 602 |
|
629 | |||
| 603 | return 1 |
|
630 | return 1 | |
| 604 |
|
631 | |||
| 605 | def setRadarFrequency(self, frequency=None): |
|
632 | def setRadarFrequency(self, frequency=None): | |
| 606 |
|
633 | |||
| 607 | if frequency != None: |
|
634 | if frequency != None: | |
| 608 | self.dataOut.frequency = frequency |
|
635 | self.dataOut.frequency = frequency | |
| 609 |
|
636 | |||
| 610 | return 1 |
|
637 | return 1 | |
| 611 |
|
638 | |||
| 612 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
639 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 613 | #validacion de rango |
|
640 | #validacion de rango | |
| 614 | if minHei == None: |
|
641 | if minHei == None: | |
| 615 | minHei = self.dataOut.heightList[0] |
|
642 | minHei = self.dataOut.heightList[0] | |
| 616 |
|
643 | |||
| 617 | if maxHei == None: |
|
644 | if maxHei == None: | |
| 618 | maxHei = self.dataOut.heightList[-1] |
|
645 | maxHei = self.dataOut.heightList[-1] | |
| 619 |
|
646 | |||
| 620 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
647 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 621 | print 'minHei: %.2f is out of the heights range'%(minHei) |
|
648 | print 'minHei: %.2f is out of the heights range'%(minHei) | |
| 622 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) |
|
649 | print 'minHei is setting to %.2f'%(self.dataOut.heightList[0]) | |
| 623 | minHei = self.dataOut.heightList[0] |
|
650 | minHei = self.dataOut.heightList[0] | |
| 624 |
|
651 | |||
| 625 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
652 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 626 | print 'maxHei: %.2f is out of the heights range'%(maxHei) |
|
653 | print 'maxHei: %.2f is out of the heights range'%(maxHei) | |
| 627 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) |
|
654 | print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1]) | |
| 628 | maxHei = self.dataOut.heightList[-1] |
|
655 | maxHei = self.dataOut.heightList[-1] | |
| 629 |
|
656 | |||
| 630 | # validacion de velocidades |
|
657 | # validacion de velocidades | |
| 631 | velrange = self.dataOut.getVelRange(1) |
|
658 | velrange = self.dataOut.getVelRange(1) | |
| 632 |
|
659 | |||
| 633 | if minVel == None: |
|
660 | if minVel == None: | |
| 634 | minVel = velrange[0] |
|
661 | minVel = velrange[0] | |
| 635 |
|
662 | |||
| 636 | if maxVel == None: |
|
663 | if maxVel == None: | |
| 637 | maxVel = velrange[-1] |
|
664 | maxVel = velrange[-1] | |
| 638 |
|
665 | |||
| 639 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
666 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 640 | print 'minVel: %.2f is out of the velocity range'%(minVel) |
|
667 | print 'minVel: %.2f is out of the velocity range'%(minVel) | |
| 641 | print 'minVel is setting to %.2f'%(velrange[0]) |
|
668 | print 'minVel is setting to %.2f'%(velrange[0]) | |
| 642 | minVel = velrange[0] |
|
669 | minVel = velrange[0] | |
| 643 |
|
670 | |||
| 644 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
671 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 645 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) |
|
672 | print 'maxVel: %.2f is out of the velocity range'%(maxVel) | |
| 646 | print 'maxVel is setting to %.2f'%(velrange[-1]) |
|
673 | print 'maxVel is setting to %.2f'%(velrange[-1]) | |
| 647 | maxVel = velrange[-1] |
|
674 | maxVel = velrange[-1] | |
| 648 |
|
675 | |||
| 649 | # seleccion de indices para rango |
|
676 | # seleccion de indices para rango | |
| 650 | minIndex = 0 |
|
677 | minIndex = 0 | |
| 651 | maxIndex = 0 |
|
678 | maxIndex = 0 | |
| 652 | heights = self.dataOut.heightList |
|
679 | heights = self.dataOut.heightList | |
| 653 |
|
680 | |||
| 654 | inda = numpy.where(heights >= minHei) |
|
681 | inda = numpy.where(heights >= minHei) | |
| 655 | indb = numpy.where(heights <= maxHei) |
|
682 | indb = numpy.where(heights <= maxHei) | |
| 656 |
|
683 | |||
| 657 | try: |
|
684 | try: | |
| 658 | minIndex = inda[0][0] |
|
685 | minIndex = inda[0][0] | |
| 659 | except: |
|
686 | except: | |
| 660 | minIndex = 0 |
|
687 | minIndex = 0 | |
| 661 |
|
688 | |||
| 662 | try: |
|
689 | try: | |
| 663 | maxIndex = indb[0][-1] |
|
690 | maxIndex = indb[0][-1] | |
| 664 | except: |
|
691 | except: | |
| 665 | maxIndex = len(heights) |
|
692 | maxIndex = len(heights) | |
| 666 |
|
693 | |||
| 667 | if (minIndex < 0) or (minIndex > maxIndex): |
|
694 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 668 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) |
|
695 | raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex) | |
| 669 |
|
696 | |||
| 670 | if (maxIndex >= self.dataOut.nHeights): |
|
697 | if (maxIndex >= self.dataOut.nHeights): | |
| 671 | maxIndex = self.dataOut.nHeights-1 |
|
698 | maxIndex = self.dataOut.nHeights-1 | |
| 672 |
|
699 | |||
| 673 | # seleccion de indices para velocidades |
|
700 | # seleccion de indices para velocidades | |
| 674 | indminvel = numpy.where(velrange >= minVel) |
|
701 | indminvel = numpy.where(velrange >= minVel) | |
| 675 | indmaxvel = numpy.where(velrange <= maxVel) |
|
702 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 676 | try: |
|
703 | try: | |
| 677 | minIndexVel = indminvel[0][0] |
|
704 | minIndexVel = indminvel[0][0] | |
| 678 | except: |
|
705 | except: | |
| 679 | minIndexVel = 0 |
|
706 | minIndexVel = 0 | |
| 680 |
|
707 | |||
| 681 | try: |
|
708 | try: | |
| 682 | maxIndexVel = indmaxvel[0][-1] |
|
709 | maxIndexVel = indmaxvel[0][-1] | |
| 683 | except: |
|
710 | except: | |
| 684 | maxIndexVel = len(velrange) |
|
711 | maxIndexVel = len(velrange) | |
| 685 |
|
712 | |||
| 686 | #seleccion del espectro |
|
713 | #seleccion del espectro | |
| 687 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] |
|
714 | data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1] | |
| 688 | #estimacion de ruido |
|
715 | #estimacion de ruido | |
| 689 | noise = numpy.zeros(self.dataOut.nChannels) |
|
716 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 690 |
|
717 | |||
| 691 | for channel in range(self.dataOut.nChannels): |
|
718 | for channel in range(self.dataOut.nChannels): | |
| 692 | daux = data_spc[channel,:,:] |
|
719 | daux = data_spc[channel,:,:] | |
| 693 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) |
|
720 | noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt) | |
| 694 |
|
721 | |||
| 695 | self.dataOut.noise_estimation = noise.copy() |
|
722 | self.dataOut.noise_estimation = noise.copy() | |
| 696 |
|
723 | |||
| 697 | return 1 |
|
724 | return 1 | |
| 698 |
|
725 | |||
| 699 | class IncohInt(Operation): |
|
726 | class IncohInt(Operation): | |
| 700 |
|
727 | |||
| 701 |
|
728 | |||
| 702 | __profIndex = 0 |
|
729 | __profIndex = 0 | |
| 703 | __withOverapping = False |
|
730 | __withOverapping = False | |
| 704 |
|
731 | |||
| 705 | __byTime = False |
|
732 | __byTime = False | |
| 706 | __initime = None |
|
733 | __initime = None | |
| 707 | __lastdatatime = None |
|
734 | __lastdatatime = None | |
| 708 | __integrationtime = None |
|
735 | __integrationtime = None | |
| 709 |
|
736 | |||
| 710 | __buffer_spc = None |
|
737 | __buffer_spc = None | |
| 711 | __buffer_cspc = None |
|
738 | __buffer_cspc = None | |
| 712 | __buffer_dc = None |
|
739 | __buffer_dc = None | |
| 713 |
|
740 | |||
| 714 | __dataReady = False |
|
741 | __dataReady = False | |
| 715 |
|
742 | |||
| 716 | __timeInterval = None |
|
743 | __timeInterval = None | |
| 717 |
|
744 | |||
| 718 | n = None |
|
745 | n = None | |
| 719 |
|
746 | |||
| 720 |
|
747 | |||
| 721 |
|
748 | |||
| 722 | def __init__(self): |
|
749 | def __init__(self): | |
| 723 |
|
750 | |||
| 724 | Operation.__init__(self) |
|
751 | Operation.__init__(self) | |
| 725 | # self.isConfig = False |
|
752 | # self.isConfig = False | |
| 726 |
|
753 | |||
| 727 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
754 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 728 | """ |
|
755 | """ | |
| 729 | Set the parameters of the integration class. |
|
756 | Set the parameters of the integration class. | |
| 730 |
|
757 | |||
| 731 | Inputs: |
|
758 | Inputs: | |
| 732 |
|
759 | |||
| 733 | n : Number of coherent integrations |
|
760 | n : Number of coherent integrations | |
| 734 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
761 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 735 | overlapping : |
|
762 | overlapping : | |
| 736 |
|
763 | |||
| 737 | """ |
|
764 | """ | |
| 738 |
|
765 | |||
| 739 | self.__initime = None |
|
766 | self.__initime = None | |
| 740 | self.__lastdatatime = 0 |
|
767 | self.__lastdatatime = 0 | |
| 741 |
|
768 | |||
| 742 | self.__buffer_spc = 0 |
|
769 | self.__buffer_spc = 0 | |
| 743 | self.__buffer_cspc = 0 |
|
770 | self.__buffer_cspc = 0 | |
| 744 | self.__buffer_dc = 0 |
|
771 | self.__buffer_dc = 0 | |
| 745 |
|
772 | |||
| 746 | self.__profIndex = 0 |
|
773 | self.__profIndex = 0 | |
| 747 | self.__dataReady = False |
|
774 | self.__dataReady = False | |
| 748 | self.__byTime = False |
|
775 | self.__byTime = False | |
| 749 |
|
776 | |||
| 750 | if n is None and timeInterval is None: |
|
777 | if n is None and timeInterval is None: | |
| 751 | raise ValueError, "n or timeInterval should be specified ..." |
|
778 | raise ValueError, "n or timeInterval should be specified ..." | |
| 752 |
|
779 | |||
| 753 | if n is not None: |
|
780 | if n is not None: | |
| 754 | self.n = int(n) |
|
781 | self.n = int(n) | |
| 755 | else: |
|
782 | else: | |
| 756 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line |
|
783 | self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line | |
| 757 | self.n = None |
|
784 | self.n = None | |
| 758 | self.__byTime = True |
|
785 | self.__byTime = True | |
| 759 |
|
786 | |||
| 760 | def putData(self, data_spc, data_cspc, data_dc): |
|
787 | def putData(self, data_spc, data_cspc, data_dc): | |
| 761 |
|
788 | |||
| 762 | """ |
|
789 | """ | |
| 763 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
790 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 764 |
|
791 | |||
| 765 | """ |
|
792 | """ | |
| 766 |
|
793 | |||
| 767 | self.__buffer_spc += data_spc |
|
794 | self.__buffer_spc += data_spc | |
| 768 |
|
795 | |||
| 769 | if data_cspc is None: |
|
796 | if data_cspc is None: | |
| 770 | self.__buffer_cspc = None |
|
797 | self.__buffer_cspc = None | |
| 771 | else: |
|
798 | else: | |
| 772 | self.__buffer_cspc += data_cspc |
|
799 | self.__buffer_cspc += data_cspc | |
| 773 |
|
800 | |||
| 774 | if data_dc is None: |
|
801 | if data_dc is None: | |
| 775 | self.__buffer_dc = None |
|
802 | self.__buffer_dc = None | |
| 776 | else: |
|
803 | else: | |
| 777 | self.__buffer_dc += data_dc |
|
804 | self.__buffer_dc += data_dc | |
| 778 |
|
805 | |||
| 779 | self.__profIndex += 1 |
|
806 | self.__profIndex += 1 | |
| 780 |
|
807 | |||
| 781 | return |
|
808 | return | |
| 782 |
|
809 | |||
| 783 | def pushData(self): |
|
810 | def pushData(self): | |
| 784 | """ |
|
811 | """ | |
| 785 | Return the sum of the last profiles and the profiles used in the sum. |
|
812 | Return the sum of the last profiles and the profiles used in the sum. | |
| 786 |
|
813 | |||
| 787 | Affected: |
|
814 | Affected: | |
| 788 |
|
815 | |||
| 789 | self.__profileIndex |
|
816 | self.__profileIndex | |
| 790 |
|
817 | |||
| 791 | """ |
|
818 | """ | |
| 792 |
|
819 | |||
| 793 | data_spc = self.__buffer_spc |
|
820 | data_spc = self.__buffer_spc | |
| 794 | data_cspc = self.__buffer_cspc |
|
821 | data_cspc = self.__buffer_cspc | |
| 795 | data_dc = self.__buffer_dc |
|
822 | data_dc = self.__buffer_dc | |
| 796 | n = self.__profIndex |
|
823 | n = self.__profIndex | |
| 797 |
|
824 | |||
| 798 | self.__buffer_spc = 0 |
|
825 | self.__buffer_spc = 0 | |
| 799 | self.__buffer_cspc = 0 |
|
826 | self.__buffer_cspc = 0 | |
| 800 | self.__buffer_dc = 0 |
|
827 | self.__buffer_dc = 0 | |
| 801 | self.__profIndex = 0 |
|
828 | self.__profIndex = 0 | |
| 802 |
|
829 | |||
| 803 | return data_spc, data_cspc, data_dc, n |
|
830 | return data_spc, data_cspc, data_dc, n | |
| 804 |
|
831 | |||
| 805 | def byProfiles(self, *args): |
|
832 | def byProfiles(self, *args): | |
| 806 |
|
833 | |||
| 807 | self.__dataReady = False |
|
834 | self.__dataReady = False | |
| 808 | avgdata_spc = None |
|
835 | avgdata_spc = None | |
| 809 | avgdata_cspc = None |
|
836 | avgdata_cspc = None | |
| 810 | avgdata_dc = None |
|
837 | avgdata_dc = None | |
| 811 |
|
838 | |||
| 812 | self.putData(*args) |
|
839 | self.putData(*args) | |
| 813 |
|
840 | |||
| 814 | if self.__profIndex == self.n: |
|
841 | if self.__profIndex == self.n: | |
| 815 |
|
842 | |||
| 816 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
843 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 817 | self.n = n |
|
844 | self.n = n | |
| 818 | self.__dataReady = True |
|
845 | self.__dataReady = True | |
| 819 |
|
846 | |||
| 820 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
847 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 821 |
|
848 | |||
| 822 | def byTime(self, datatime, *args): |
|
849 | def byTime(self, datatime, *args): | |
| 823 |
|
850 | |||
| 824 | self.__dataReady = False |
|
851 | self.__dataReady = False | |
| 825 | avgdata_spc = None |
|
852 | avgdata_spc = None | |
| 826 | avgdata_cspc = None |
|
853 | avgdata_cspc = None | |
| 827 | avgdata_dc = None |
|
854 | avgdata_dc = None | |
| 828 |
|
855 | |||
| 829 | self.putData(*args) |
|
856 | self.putData(*args) | |
| 830 |
|
857 | |||
| 831 | if (datatime - self.__initime) >= self.__integrationtime: |
|
858 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 832 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
859 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 833 | self.n = n |
|
860 | self.n = n | |
| 834 | self.__dataReady = True |
|
861 | self.__dataReady = True | |
| 835 |
|
862 | |||
| 836 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
863 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 837 |
|
864 | |||
| 838 | def integrate(self, datatime, *args): |
|
865 | def integrate(self, datatime, *args): | |
| 839 |
|
866 | |||
| 840 | if self.__profIndex == 0: |
|
867 | if self.__profIndex == 0: | |
| 841 | self.__initime = datatime |
|
868 | self.__initime = datatime | |
| 842 |
|
869 | |||
| 843 | if self.__byTime: |
|
870 | if self.__byTime: | |
| 844 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) |
|
871 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args) | |
| 845 | else: |
|
872 | else: | |
| 846 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
873 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 847 |
|
874 | |||
| 848 | if not self.__dataReady: |
|
875 | if not self.__dataReady: | |
| 849 | return None, None, None, None |
|
876 | return None, None, None, None | |
| 850 |
|
877 | |||
| 851 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
878 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 852 |
|
879 | |||
| 853 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
880 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 854 |
|
881 | |||
| 855 | if n==1: |
|
882 | if n==1: | |
| 856 | return |
|
883 | return | |
| 857 |
|
884 | |||
| 858 | dataOut.flagNoData = True |
|
885 | dataOut.flagNoData = True | |
| 859 |
|
886 | |||
| 860 | if not self.isConfig: |
|
887 | if not self.isConfig: | |
| 861 | self.setup(n, timeInterval, overlapping) |
|
888 | self.setup(n, timeInterval, overlapping) | |
| 862 | self.isConfig = True |
|
889 | self.isConfig = True | |
| 863 |
|
890 | |||
| 864 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
891 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 865 | dataOut.data_spc, |
|
892 | dataOut.data_spc, | |
| 866 | dataOut.data_cspc, |
|
893 | dataOut.data_cspc, | |
| 867 | dataOut.data_dc) |
|
894 | dataOut.data_dc) | |
| 868 |
|
895 | |||
| 869 | if self.__dataReady: |
|
896 | if self.__dataReady: | |
| 870 |
|
897 | |||
| 871 | dataOut.data_spc = avgdata_spc |
|
898 | dataOut.data_spc = avgdata_spc | |
| 872 | dataOut.data_cspc = avgdata_cspc |
|
899 | dataOut.data_cspc = avgdata_cspc | |
| 873 | dataOut.data_dc = avgdata_dc |
|
900 | dataOut.data_dc = avgdata_dc | |
| 874 |
|
901 | |||
| 875 | dataOut.nIncohInt *= self.n |
|
902 | dataOut.nIncohInt *= self.n | |
| 876 | dataOut.utctime = avgdatatime |
|
903 | dataOut.utctime = avgdatatime | |
| 877 | dataOut.flagNoData = False |
|
904 | dataOut.flagNoData = False | |
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