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jroproc_spectra_lags: decoding data from Tx Pulse (real data)
Miguel Valdez -
r776:12cd779dd5fc
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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 SpectraLagsProc(ProcessingUnit):
7 class SpectraLagsProc(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.__input_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 self.__codeIndex = 0
20
21 self.__lags_buffer = None
19
22
20 def __updateSpecFromVoltage(self):
23 def __updateSpecFromVoltage(self):
21
24
25 self.dataOut.plotting = "spectra_lags"
22 self.dataOut.timeZone = self.dataIn.timeZone
26 self.dataOut.timeZone = self.dataIn.timeZone
23 self.dataOut.dstFlag = self.dataIn.dstFlag
27 self.dataOut.dstFlag = self.dataIn.dstFlag
24 self.dataOut.errorCount = self.dataIn.errorCount
28 self.dataOut.errorCount = self.dataIn.errorCount
25 self.dataOut.useLocalTime = self.dataIn.useLocalTime
29 self.dataOut.useLocalTime = self.dataIn.useLocalTime
26
30
27 self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
31 self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
28 self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
32 self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
29 self.dataOut.ippSeconds = self.dataIn.getDeltaH()*(10**-6)/0.15
33 self.dataOut.ippSeconds = self.dataIn.getDeltaH()*(10**-6)/0.15
30
34
31 self.dataOut.channelList = self.dataIn.channelList
35 self.dataOut.channelList = self.dataIn.channelList
32 self.dataOut.heightList = self.dataIn.heightList
36 self.dataOut.heightList = self.dataIn.heightList
33 self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
37 self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
34
38
35 self.dataOut.nBaud = self.dataIn.nBaud
39 self.dataOut.nBaud = self.dataIn.nBaud
36 self.dataOut.nCode = self.dataIn.nCode
40 self.dataOut.nCode = self.dataIn.nCode
37 self.dataOut.code = self.dataIn.code
41 self.dataOut.code = self.dataIn.code
38 # self.dataOut.nProfiles = self.dataOut.nFFTPoints
42 # self.dataOut.nProfiles = self.dataOut.nFFTPoints
39
43
40 self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
44 self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
41 self.dataOut.utctime = self.firstdatatime
45 self.dataOut.utctime = self.firstdatatime
42 self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
46 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
47 self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
44 self.dataOut.flagShiftFFT = False
48 self.dataOut.flagShiftFFT = False
45
49
46 self.dataOut.nCohInt = self.dataIn.nCohInt
50 self.dataOut.nCohInt = self.dataIn.nCohInt
47 self.dataOut.nIncohInt = 1
51 self.dataOut.nIncohInt = 1
48
52
49 self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
53 self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
50
54
51 self.dataOut.frequency = self.dataIn.frequency
55 self.dataOut.frequency = self.dataIn.frequency
52 self.dataOut.realtime = self.dataIn.realtime
56 self.dataOut.realtime = self.dataIn.realtime
53
57
54 self.dataOut.azimuth = self.dataIn.azimuth
58 self.dataOut.azimuth = self.dataIn.azimuth
55 self.dataOut.zenith = self.dataIn.zenith
59 self.dataOut.zenith = self.dataIn.zenith
56
60
57 self.dataOut.beam.codeList = self.dataIn.beam.codeList
61 self.dataOut.beam.codeList = self.dataIn.beam.codeList
58 self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
62 self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
59 self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
63 self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
60
64
61 def __decodeData(self, nProfiles, code):
65 def __createLagsBlock(self, voltages):
62
66
63 if code is None:
67 if self.__lags_buffer is None:
64 return
68 self.__lags_buffer = numpy.zeros((self.dataOut.nChannels, self.dataOut.nProfiles, self.dataOut.nHeights), dtype='complex')
69
70 nsegments = self.dataOut.nHeights - self.dataOut.nProfiles
71
72 # codes = numpy.conjugate(self.__input_buffer[:,9:169])/10000
73
74 for i in range(nsegments):
75 self.__lags_buffer[:,:,i] = voltages[:,i:i+self.dataOut.nProfiles]#*codes
76
77 return self.__lags_buffer
65
78
66 for i in range(nProfiles):
79 def __decodeData(self, volt_buffer, pulseIndex=None):
67 self.buffer[:,i,:] = self.buffer[:,i,:]*code[0][i]
68
80
69 def __getFft(self):
81 if pulseIndex is None:
82 return volt_buffer
83
84 codes = numpy.conjugate(self.__input_buffer[:,pulseIndex[0]:pulseIndex[1]])/10000
85
86 nsegments = self.dataOut.nHeights - self.dataOut.nProfiles
87
88 for i in range(nsegments):
89 volt_buffer[:,:,i] = volt_buffer[:,:,i]*codes
90
91 return volt_buffer
92
93 def __getFft(self, datablock):
70 """
94 """
71 Convierte valores de Voltaje a Spectra
95 Convierte valores de Voltaje a Spectra
72
96
73 Affected:
97 Affected:
74 self.dataOut.data_spc
98 self.dataOut.data_spc
75 self.dataOut.data_cspc
99 self.dataOut.data_cspc
76 self.dataOut.data_dc
100 self.dataOut.data_dc
77 self.dataOut.heightList
101 self.dataOut.heightList
78 self.profIndex
102 self.profIndex
79 self.buffer
103 self.__input_buffer
80 self.dataOut.flagNoData
104 self.dataOut.flagNoData
81 """
105 """
82 nsegments = self.dataOut.nHeights
83
84 _fft_buffer = numpy.zeros((self.dataOut.nChannels, self.dataOut.nProfiles, nsegments), dtype='complex')
85
106
86 for i in range(nsegments):
107 fft_volt = numpy.fft.fft(datablock, n=self.dataOut.nFFTPoints, axis=1)
87 try:
88 _fft_buffer[:,:,i] = self.buffer[:,i:i+self.dataOut.nProfiles]
89
90 if self.code is not None:
91 _fft_buffer[:,:,i] = _fft_buffer[:,:,i]*self.code[0]
92 except:
93 pass
94
108
95 fft_volt = numpy.fft.fft(_fft_buffer, n=self.dataOut.nFFTPoints, axis=1)
109 # dc = fft_volt[:,0,:]
96 fft_volt = fft_volt.astype(numpy.dtype('complex'))
97 dc = fft_volt[:,0,:]
98
110
99 #calculo de self-spectra
111 #calculo de self-spectra
100 fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
112 fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
101 spc = fft_volt * numpy.conjugate(fft_volt)
113 spc = fft_volt * numpy.conjugate(fft_volt)
102 spc = spc.real
114 spc = spc.real
103
115
104 blocksize = 0
116 blocksize = 0
105 blocksize += dc.size
117 # blocksize += dc.size
106 blocksize += spc.size
118 blocksize += spc.size
107
119
108 cspc = None
120 cspc = None
109 pairIndex = 0
121 pairIndex = 0
110
122
111 if self.dataOut.pairsList != None:
123 if self.dataOut.pairsList != None:
112 #calculo de cross-spectra
124 #calculo de cross-spectra
113 cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
125 cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
114 for pair in self.dataOut.pairsList:
126 for pair in self.dataOut.pairsList:
115 if pair[0] not in self.dataOut.channelList:
127 if pair[0] not in self.dataOut.channelList:
116 raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
128 raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
117 if pair[1] not in self.dataOut.channelList:
129 if pair[1] not in self.dataOut.channelList:
118 raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
130 raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
119
131
120 chan_index0 = self.dataOut.channelList.index(pair[0])
132 chan_index0 = self.dataOut.channelList.index(pair[0])
121 chan_index1 = self.dataOut.channelList.index(pair[1])
133 chan_index1 = self.dataOut.channelList.index(pair[1])
122
134
123 cspc[pairIndex,:,:] = fft_volt[chan_index0,:,:] * numpy.conjugate(fft_volt[chan_index1,:,:])
135 cspc[pairIndex,:,:] = fft_volt[chan_index0,:,:] * numpy.conjugate(fft_volt[chan_index1,:,:])
124 pairIndex += 1
136 pairIndex += 1
125 blocksize += cspc.size
137 blocksize += cspc.size
126
138
127 self.dataOut.data_spc = spc
139 self.dataOut.data_spc = spc
128 self.dataOut.data_cspc = cspc
140 self.dataOut.data_cspc = cspc
129 self.dataOut.data_dc = dc
141 # self.dataOut.data_dc = dc
130 self.dataOut.blockSize = blocksize
142 self.dataOut.blockSize = blocksize
131 self.dataOut.flagShiftFFT = True
143 self.dataOut.flagShiftFFT = True
132
144
133 def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=1, nBaud=1):
145 def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=None, nBaud=None, codeFromHeader=False, pulseIndex=None):
134
146
135 self.dataOut.flagNoData = True
147 self.dataOut.flagNoData = True
136
148
149 self.code = None
150
151 if codeFromHeader:
152 if self.dataIn.code is not None:
153 self.code = self.dataIn.code
154
137 if code is not None:
155 if code is not None:
138 self.code = numpy.array(code).reshape(nCode,nBaud)
156 self.code = numpy.array(code).reshape(nCode,nBaud)
139 else:
140 self.code = None
141
157
142 if self.dataIn.type == "Voltage":
158 if self.dataIn.type == "Voltage":
143
159
144 if nFFTPoints == None:
160 if nFFTPoints == None:
145 raise ValueError, "This SpectraProc.run() need nFFTPoints input variable"
161 raise ValueError, "This SpectraProc.run() need nFFTPoints input variable"
146
162
147 if nProfiles == None:
163 if nProfiles == None:
148 nProfiles = nFFTPoints
164 nProfiles = nFFTPoints
149
165
150 self.dataOut.ippFactor = 1
166 self.profIndex == nProfiles
167 self.firstdatatime = self.dataIn.utctime
151
168
169 self.dataOut.ippFactor = 1
152 self.dataOut.nFFTPoints = nFFTPoints
170 self.dataOut.nFFTPoints = nFFTPoints
153 self.dataOut.nProfiles = nProfiles
171 self.dataOut.nProfiles = nProfiles
154 self.dataOut.pairsList = pairsList
172 self.dataOut.pairsList = pairsList
155
173
156 # if self.buffer is None:
174 self.__updateSpecFromVoltage()
157 # self.buffer = numpy.zeros( (self.dataIn.nChannels, nProfiles, self.dataIn.nHeights),
158 # dtype='complex')
159
175
160 if not self.dataIn.flagDataAsBlock:
176 if not self.dataIn.flagDataAsBlock:
161 self.buffer = self.dataIn.data.copy()
177 self.__input_buffer = self.dataIn.data.copy()
162
178
163 # for i in range(self.dataIn.nHeights):
179 lags_block = self.__createLagsBlock(self.__input_buffer)
164 # self.buffer[:, self.profIndex, self.profIndex:] = voltage_data[:,:self.dataIn.nHeights - self.profIndex]
165 #
166 # self.profIndex += 1
167
180
168 else:
181 lags_block = self.__decodeData(lags_block, pulseIndex)
169 raise ValueError, ""
170
171 self.firstdatatime = self.dataIn.utctime
172
182
173 self.profIndex == nProfiles
183 else:
174
184 self.__input_buffer = self.dataIn.data.copy()
175 self.__updateSpecFromVoltage()
176
185
177 self.__getFft()
186 self.__getFft(lags_block)
178
187
179 self.dataOut.flagNoData = False
188 self.dataOut.flagNoData = False
180
189
181 return True
190 return True
182
191
183 raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type)
192 raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type)
184
193
185 def __selectPairs(self, pairsList):
194 def __selectPairs(self, pairsList):
186
195
187 if channelList == None:
196 if channelList == None:
188 return
197 return
189
198
190 pairsIndexListSelected = []
199 pairsIndexListSelected = []
191
200
192 for thisPair in pairsList:
201 for thisPair in pairsList:
193
202
194 if thisPair not in self.dataOut.pairsList:
203 if thisPair not in self.dataOut.pairsList:
195 continue
204 continue
196
205
197 pairIndex = self.dataOut.pairsList.index(thisPair)
206 pairIndex = self.dataOut.pairsList.index(thisPair)
198
207
199 pairsIndexListSelected.append(pairIndex)
208 pairsIndexListSelected.append(pairIndex)
200
209
201 if not pairsIndexListSelected:
210 if not pairsIndexListSelected:
202 self.dataOut.data_cspc = None
211 self.dataOut.data_cspc = None
203 self.dataOut.pairsList = []
212 self.dataOut.pairsList = []
204 return
213 return
205
214
206 self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
215 self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
207 self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected]
216 self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected]
208
217
209 return
218 return
210
219
211 def __selectPairsByChannel(self, channelList=None):
220 def __selectPairsByChannel(self, channelList=None):
212
221
213 if channelList == None:
222 if channelList == None:
214 return
223 return
215
224
216 pairsIndexListSelected = []
225 pairsIndexListSelected = []
217 for pairIndex in self.dataOut.pairsIndexList:
226 for pairIndex in self.dataOut.pairsIndexList:
218 #First pair
227 #First pair
219 if self.dataOut.pairsList[pairIndex][0] not in channelList:
228 if self.dataOut.pairsList[pairIndex][0] not in channelList:
220 continue
229 continue
221 #Second pair
230 #Second pair
222 if self.dataOut.pairsList[pairIndex][1] not in channelList:
231 if self.dataOut.pairsList[pairIndex][1] not in channelList:
223 continue
232 continue
224
233
225 pairsIndexListSelected.append(pairIndex)
234 pairsIndexListSelected.append(pairIndex)
226
235
227 if not pairsIndexListSelected:
236 if not pairsIndexListSelected:
228 self.dataOut.data_cspc = None
237 self.dataOut.data_cspc = None
229 self.dataOut.pairsList = []
238 self.dataOut.pairsList = []
230 return
239 return
231
240
232 self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
241 self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
233 self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected]
242 self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected]
234
243
235 return
244 return
236
245
237 def selectChannels(self, channelList):
246 def selectChannels(self, channelList):
238
247
239 channelIndexList = []
248 channelIndexList = []
240
249
241 for channel in channelList:
250 for channel in channelList:
242 if channel not in self.dataOut.channelList:
251 if channel not in self.dataOut.channelList:
243 raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList))
252 raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList))
244
253
245 index = self.dataOut.channelList.index(channel)
254 index = self.dataOut.channelList.index(channel)
246 channelIndexList.append(index)
255 channelIndexList.append(index)
247
256
248 self.selectChannelsByIndex(channelIndexList)
257 self.selectChannelsByIndex(channelIndexList)
249
258
250 def selectChannelsByIndex(self, channelIndexList):
259 def selectChannelsByIndex(self, channelIndexList):
251 """
260 """
252 Selecciona un bloque de datos en base a canales segun el channelIndexList
261 Selecciona un bloque de datos en base a canales segun el channelIndexList
253
262
254 Input:
263 Input:
255 channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
264 channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7]
256
265
257 Affected:
266 Affected:
258 self.dataOut.data_spc
267 self.dataOut.data_spc
259 self.dataOut.channelIndexList
268 self.dataOut.channelIndexList
260 self.dataOut.nChannels
269 self.dataOut.nChannels
261
270
262 Return:
271 Return:
263 None
272 None
264 """
273 """
265
274
266 for channelIndex in channelIndexList:
275 for channelIndex in channelIndexList:
267 if channelIndex not in self.dataOut.channelIndexList:
276 if channelIndex not in self.dataOut.channelIndexList:
268 raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList)
277 raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList)
269
278
270 # nChannels = len(channelIndexList)
279 # nChannels = len(channelIndexList)
271
280
272 data_spc = self.dataOut.data_spc[channelIndexList,:]
281 data_spc = self.dataOut.data_spc[channelIndexList,:]
273 data_dc = self.dataOut.data_dc[channelIndexList,:]
282 data_dc = self.dataOut.data_dc[channelIndexList,:]
274
283
275 self.dataOut.data_spc = data_spc
284 self.dataOut.data_spc = data_spc
276 self.dataOut.data_dc = data_dc
285 self.dataOut.data_dc = data_dc
277
286
278 self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
287 self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
279 # self.dataOut.nChannels = nChannels
288 # self.dataOut.nChannels = nChannels
280
289
281 self.__selectPairsByChannel(self.dataOut.channelList)
290 self.__selectPairsByChannel(self.dataOut.channelList)
282
291
283 return 1
292 return 1
284
293
285 def selectHeights(self, minHei, maxHei):
294 def selectHeights(self, minHei, maxHei):
286 """
295 """
287 Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
296 Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
288 minHei <= height <= maxHei
297 minHei <= height <= maxHei
289
298
290 Input:
299 Input:
291 minHei : valor minimo de altura a considerar
300 minHei : valor minimo de altura a considerar
292 maxHei : valor maximo de altura a considerar
301 maxHei : valor maximo de altura a considerar
293
302
294 Affected:
303 Affected:
295 Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
304 Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
296
305
297 Return:
306 Return:
298 1 si el metodo se ejecuto con exito caso contrario devuelve 0
307 1 si el metodo se ejecuto con exito caso contrario devuelve 0
299 """
308 """
300
309
301 if (minHei > maxHei):
310 if (minHei > maxHei):
302 raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei)
311 raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei)
303
312
304 if (minHei < self.dataOut.heightList[0]):
313 if (minHei < self.dataOut.heightList[0]):
305 minHei = self.dataOut.heightList[0]
314 minHei = self.dataOut.heightList[0]
306
315
307 if (maxHei > self.dataOut.heightList[-1]):
316 if (maxHei > self.dataOut.heightList[-1]):
308 maxHei = self.dataOut.heightList[-1]
317 maxHei = self.dataOut.heightList[-1]
309
318
310 minIndex = 0
319 minIndex = 0
311 maxIndex = 0
320 maxIndex = 0
312 heights = self.dataOut.heightList
321 heights = self.dataOut.heightList
313
322
314 inda = numpy.where(heights >= minHei)
323 inda = numpy.where(heights >= minHei)
315 indb = numpy.where(heights <= maxHei)
324 indb = numpy.where(heights <= maxHei)
316
325
317 try:
326 try:
318 minIndex = inda[0][0]
327 minIndex = inda[0][0]
319 except:
328 except:
320 minIndex = 0
329 minIndex = 0
321
330
322 try:
331 try:
323 maxIndex = indb[0][-1]
332 maxIndex = indb[0][-1]
324 except:
333 except:
325 maxIndex = len(heights)
334 maxIndex = len(heights)
326
335
327 self.selectHeightsByIndex(minIndex, maxIndex)
336 self.selectHeightsByIndex(minIndex, maxIndex)
328
337
329 return 1
338 return 1
330
339
331 def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
340 def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
332 newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
341 newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
333
342
334 if hei_ref != None:
343 if hei_ref != None:
335 newheis = numpy.where(self.dataOut.heightList>hei_ref)
344 newheis = numpy.where(self.dataOut.heightList>hei_ref)
336
345
337 minIndex = min(newheis[0])
346 minIndex = min(newheis[0])
338 maxIndex = max(newheis[0])
347 maxIndex = max(newheis[0])
339 data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
348 data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
340 heightList = self.dataOut.heightList[minIndex:maxIndex+1]
349 heightList = self.dataOut.heightList[minIndex:maxIndex+1]
341
350
342 # determina indices
351 # determina indices
343 nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
352 nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
344 avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
353 avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
345 beacon_dB = numpy.sort(avg_dB)[-nheis:]
354 beacon_dB = numpy.sort(avg_dB)[-nheis:]
346 beacon_heiIndexList = []
355 beacon_heiIndexList = []
347 for val in avg_dB.tolist():
356 for val in avg_dB.tolist():
348 if val >= beacon_dB[0]:
357 if val >= beacon_dB[0]:
349 beacon_heiIndexList.append(avg_dB.tolist().index(val))
358 beacon_heiIndexList.append(avg_dB.tolist().index(val))
350
359
351 #data_spc = data_spc[:,:,beacon_heiIndexList]
360 #data_spc = data_spc[:,:,beacon_heiIndexList]
352 data_cspc = None
361 data_cspc = None
353 if self.dataOut.data_cspc is not None:
362 if self.dataOut.data_cspc is not None:
354 data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
363 data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
355 #data_cspc = data_cspc[:,:,beacon_heiIndexList]
364 #data_cspc = data_cspc[:,:,beacon_heiIndexList]
356
365
357 data_dc = None
366 data_dc = None
358 if self.dataOut.data_dc is not None:
367 if self.dataOut.data_dc is not None:
359 data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
368 data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
360 #data_dc = data_dc[:,beacon_heiIndexList]
369 #data_dc = data_dc[:,beacon_heiIndexList]
361
370
362 self.dataOut.data_spc = data_spc
371 self.dataOut.data_spc = data_spc
363 self.dataOut.data_cspc = data_cspc
372 self.dataOut.data_cspc = data_cspc
364 self.dataOut.data_dc = data_dc
373 self.dataOut.data_dc = data_dc
365 self.dataOut.heightList = heightList
374 self.dataOut.heightList = heightList
366 self.dataOut.beacon_heiIndexList = beacon_heiIndexList
375 self.dataOut.beacon_heiIndexList = beacon_heiIndexList
367
376
368 return 1
377 return 1
369
378
370
379
371 def selectHeightsByIndex(self, minIndex, maxIndex):
380 def selectHeightsByIndex(self, minIndex, maxIndex):
372 """
381 """
373 Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
382 Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
374 minIndex <= index <= maxIndex
383 minIndex <= index <= maxIndex
375
384
376 Input:
385 Input:
377 minIndex : valor de indice minimo de altura a considerar
386 minIndex : valor de indice minimo de altura a considerar
378 maxIndex : valor de indice maximo de altura a considerar
387 maxIndex : valor de indice maximo de altura a considerar
379
388
380 Affected:
389 Affected:
381 self.dataOut.data_spc
390 self.dataOut.data_spc
382 self.dataOut.data_cspc
391 self.dataOut.data_cspc
383 self.dataOut.data_dc
392 self.dataOut.data_dc
384 self.dataOut.heightList
393 self.dataOut.heightList
385
394
386 Return:
395 Return:
387 1 si el metodo se ejecuto con exito caso contrario devuelve 0
396 1 si el metodo se ejecuto con exito caso contrario devuelve 0
388 """
397 """
389
398
390 if (minIndex < 0) or (minIndex > maxIndex):
399 if (minIndex < 0) or (minIndex > maxIndex):
391 raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)
400 raise ValueError, "Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)
392
401
393 if (maxIndex >= self.dataOut.nHeights):
402 if (maxIndex >= self.dataOut.nHeights):
394 maxIndex = self.dataOut.nHeights-1
403 maxIndex = self.dataOut.nHeights-1
395
404
396 #Spectra
405 #Spectra
397 data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
406 data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
398
407
399 data_cspc = None
408 data_cspc = None
400 if self.dataOut.data_cspc is not None:
409 if self.dataOut.data_cspc is not None:
401 data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
410 data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
402
411
403 data_dc = None
412 data_dc = None
404 if self.dataOut.data_dc is not None:
413 if self.dataOut.data_dc is not None:
405 data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
414 data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
406
415
407 self.dataOut.data_spc = data_spc
416 self.dataOut.data_spc = data_spc
408 self.dataOut.data_cspc = data_cspc
417 self.dataOut.data_cspc = data_cspc
409 self.dataOut.data_dc = data_dc
418 self.dataOut.data_dc = data_dc
410
419
411 self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
420 self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
412
421
413 return 1
422 return 1
414
423
415 def removeDC(self, mode = 2):
424 def removeDC(self, mode = 2):
416 jspectra = self.dataOut.data_spc
425 jspectra = self.dataOut.data_spc
417 jcspectra = self.dataOut.data_cspc
426 jcspectra = self.dataOut.data_cspc
418
427
419
428
420 num_chan = jspectra.shape[0]
429 num_chan = jspectra.shape[0]
421 num_hei = jspectra.shape[2]
430 num_hei = jspectra.shape[2]
422
431
423 if jcspectra is not None:
432 if jcspectra is not None:
424 jcspectraExist = True
433 jcspectraExist = True
425 num_pairs = jcspectra.shape[0]
434 num_pairs = jcspectra.shape[0]
426 else: jcspectraExist = False
435 else: jcspectraExist = False
427
436
428 freq_dc = jspectra.shape[1]/2
437 freq_dc = jspectra.shape[1]/2
429 ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
438 ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
430
439
431 if ind_vel[0]<0:
440 if ind_vel[0]<0:
432 ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
441 ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
433
442
434 if mode == 1:
443 if mode == 1:
435 jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
444 jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
436
445
437 if jcspectraExist:
446 if jcspectraExist:
438 jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
447 jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
439
448
440 if mode == 2:
449 if mode == 2:
441
450
442 vel = numpy.array([-2,-1,1,2])
451 vel = numpy.array([-2,-1,1,2])
443 xx = numpy.zeros([4,4])
452 xx = numpy.zeros([4,4])
444
453
445 for fil in range(4):
454 for fil in range(4):
446 xx[fil,:] = vel[fil]**numpy.asarray(range(4))
455 xx[fil,:] = vel[fil]**numpy.asarray(range(4))
447
456
448 xx_inv = numpy.linalg.inv(xx)
457 xx_inv = numpy.linalg.inv(xx)
449 xx_aux = xx_inv[0,:]
458 xx_aux = xx_inv[0,:]
450
459
451 for ich in range(num_chan):
460 for ich in range(num_chan):
452 yy = jspectra[ich,ind_vel,:]
461 yy = jspectra[ich,ind_vel,:]
453 jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
462 jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
454
463
455 junkid = jspectra[ich,freq_dc,:]<=0
464 junkid = jspectra[ich,freq_dc,:]<=0
456 cjunkid = sum(junkid)
465 cjunkid = sum(junkid)
457
466
458 if cjunkid.any():
467 if cjunkid.any():
459 jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
468 jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
460
469
461 if jcspectraExist:
470 if jcspectraExist:
462 for ip in range(num_pairs):
471 for ip in range(num_pairs):
463 yy = jcspectra[ip,ind_vel,:]
472 yy = jcspectra[ip,ind_vel,:]
464 jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
473 jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
465
474
466
475
467 self.dataOut.data_spc = jspectra
476 self.dataOut.data_spc = jspectra
468 self.dataOut.data_cspc = jcspectra
477 self.dataOut.data_cspc = jcspectra
469
478
470 return 1
479 return 1
471
480
472 def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
481 def removeInterference(self, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
473
482
474 jspectra = self.dataOut.data_spc
483 jspectra = self.dataOut.data_spc
475 jcspectra = self.dataOut.data_cspc
484 jcspectra = self.dataOut.data_cspc
476 jnoise = self.dataOut.getNoise()
485 jnoise = self.dataOut.getNoise()
477 num_incoh = self.dataOut.nIncohInt
486 num_incoh = self.dataOut.nIncohInt
478
487
479 num_channel = jspectra.shape[0]
488 num_channel = jspectra.shape[0]
480 num_prof = jspectra.shape[1]
489 num_prof = jspectra.shape[1]
481 num_hei = jspectra.shape[2]
490 num_hei = jspectra.shape[2]
482
491
483 #hei_interf
492 #hei_interf
484 if hei_interf is None:
493 if hei_interf is None:
485 count_hei = num_hei/2 #Como es entero no importa
494 count_hei = num_hei/2 #Como es entero no importa
486 hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
495 hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
487 hei_interf = numpy.asarray(hei_interf)[0]
496 hei_interf = numpy.asarray(hei_interf)[0]
488 #nhei_interf
497 #nhei_interf
489 if (nhei_interf == None):
498 if (nhei_interf == None):
490 nhei_interf = 5
499 nhei_interf = 5
491 if (nhei_interf < 1):
500 if (nhei_interf < 1):
492 nhei_interf = 1
501 nhei_interf = 1
493 if (nhei_interf > count_hei):
502 if (nhei_interf > count_hei):
494 nhei_interf = count_hei
503 nhei_interf = count_hei
495 if (offhei_interf == None):
504 if (offhei_interf == None):
496 offhei_interf = 0
505 offhei_interf = 0
497
506
498 ind_hei = range(num_hei)
507 ind_hei = range(num_hei)
499 # mask_prof = numpy.asarray(range(num_prof - 2)) + 1
508 # mask_prof = numpy.asarray(range(num_prof - 2)) + 1
500 # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
509 # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
501 mask_prof = numpy.asarray(range(num_prof))
510 mask_prof = numpy.asarray(range(num_prof))
502 num_mask_prof = mask_prof.size
511 num_mask_prof = mask_prof.size
503 comp_mask_prof = [0, num_prof/2]
512 comp_mask_prof = [0, num_prof/2]
504
513
505
514
506 #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
515 #noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
507 if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
516 if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
508 jnoise = numpy.nan
517 jnoise = numpy.nan
509 noise_exist = jnoise[0] < numpy.Inf
518 noise_exist = jnoise[0] < numpy.Inf
510
519
511 #Subrutina de Remocion de la Interferencia
520 #Subrutina de Remocion de la Interferencia
512 for ich in range(num_channel):
521 for ich in range(num_channel):
513 #Se ordena los espectros segun su potencia (menor a mayor)
522 #Se ordena los espectros segun su potencia (menor a mayor)
514 power = jspectra[ich,mask_prof,:]
523 power = jspectra[ich,mask_prof,:]
515 power = power[:,hei_interf]
524 power = power[:,hei_interf]
516 power = power.sum(axis = 0)
525 power = power.sum(axis = 0)
517 psort = power.ravel().argsort()
526 psort = power.ravel().argsort()
518
527
519 #Se estima la interferencia promedio en los Espectros de Potencia empleando
528 #Se estima la interferencia promedio en los Espectros de Potencia empleando
520 junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
529 junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
521
530
522 if noise_exist:
531 if noise_exist:
523 # tmp_noise = jnoise[ich] / num_prof
532 # tmp_noise = jnoise[ich] / num_prof
524 tmp_noise = jnoise[ich]
533 tmp_noise = jnoise[ich]
525 junkspc_interf = junkspc_interf - tmp_noise
534 junkspc_interf = junkspc_interf - tmp_noise
526 #junkspc_interf[:,comp_mask_prof] = 0
535 #junkspc_interf[:,comp_mask_prof] = 0
527
536
528 jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
537 jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
529 jspc_interf = jspc_interf.transpose()
538 jspc_interf = jspc_interf.transpose()
530 #Calculando el espectro de interferencia promedio
539 #Calculando el espectro de interferencia promedio
531 noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh))
540 noiseid = numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh))
532 noiseid = noiseid[0]
541 noiseid = noiseid[0]
533 cnoiseid = noiseid.size
542 cnoiseid = noiseid.size
534 interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh))
543 interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh))
535 interfid = interfid[0]
544 interfid = interfid[0]
536 cinterfid = interfid.size
545 cinterfid = interfid.size
537
546
538 if (cnoiseid > 0): jspc_interf[noiseid] = 0
547 if (cnoiseid > 0): jspc_interf[noiseid] = 0
539
548
540 #Expandiendo los perfiles a limpiar
549 #Expandiendo los perfiles a limpiar
541 if (cinterfid > 0):
550 if (cinterfid > 0):
542 new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
551 new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
543 new_interfid = numpy.asarray(new_interfid)
552 new_interfid = numpy.asarray(new_interfid)
544 new_interfid = {x for x in new_interfid}
553 new_interfid = {x for x in new_interfid}
545 new_interfid = numpy.array(list(new_interfid))
554 new_interfid = numpy.array(list(new_interfid))
546 new_cinterfid = new_interfid.size
555 new_cinterfid = new_interfid.size
547 else: new_cinterfid = 0
556 else: new_cinterfid = 0
548
557
549 for ip in range(new_cinterfid):
558 for ip in range(new_cinterfid):
550 ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
559 ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
551 jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
560 jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
552
561
553
562
554 jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
563 jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
555
564
556 #Removiendo la interferencia del punto de mayor interferencia
565 #Removiendo la interferencia del punto de mayor interferencia
557 ListAux = jspc_interf[mask_prof].tolist()
566 ListAux = jspc_interf[mask_prof].tolist()
558 maxid = ListAux.index(max(ListAux))
567 maxid = ListAux.index(max(ListAux))
559
568
560
569
561 if cinterfid > 0:
570 if cinterfid > 0:
562 for ip in range(cinterfid*(interf == 2) - 1):
571 for ip in range(cinterfid*(interf == 2) - 1):
563 ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero()
572 ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero()
564 cind = len(ind)
573 cind = len(ind)
565
574
566 if (cind > 0):
575 if (cind > 0):
567 jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh))
576 jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh))
568
577
569 ind = numpy.array([-2,-1,1,2])
578 ind = numpy.array([-2,-1,1,2])
570 xx = numpy.zeros([4,4])
579 xx = numpy.zeros([4,4])
571
580
572 for id1 in range(4):
581 for id1 in range(4):
573 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
582 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
574
583
575 xx_inv = numpy.linalg.inv(xx)
584 xx_inv = numpy.linalg.inv(xx)
576 xx = xx_inv[:,0]
585 xx = xx_inv[:,0]
577 ind = (ind + maxid + num_mask_prof)%num_mask_prof
586 ind = (ind + maxid + num_mask_prof)%num_mask_prof
578 yy = jspectra[ich,mask_prof[ind],:]
587 yy = jspectra[ich,mask_prof[ind],:]
579 jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
588 jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
580
589
581
590
582 indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero()
591 indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero()
583 jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh))
592 jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh))
584
593
585 #Remocion de Interferencia en el Cross Spectra
594 #Remocion de Interferencia en el Cross Spectra
586 if jcspectra is None: return jspectra, jcspectra
595 if jcspectra is None: return jspectra, jcspectra
587 num_pairs = jcspectra.size/(num_prof*num_hei)
596 num_pairs = jcspectra.size/(num_prof*num_hei)
588 jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
597 jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
589
598
590 for ip in range(num_pairs):
599 for ip in range(num_pairs):
591
600
592 #-------------------------------------------
601 #-------------------------------------------
593
602
594 cspower = numpy.abs(jcspectra[ip,mask_prof,:])
603 cspower = numpy.abs(jcspectra[ip,mask_prof,:])
595 cspower = cspower[:,hei_interf]
604 cspower = cspower[:,hei_interf]
596 cspower = cspower.sum(axis = 0)
605 cspower = cspower.sum(axis = 0)
597
606
598 cspsort = cspower.ravel().argsort()
607 cspsort = cspower.ravel().argsort()
599 junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
608 junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
600 junkcspc_interf = junkcspc_interf.transpose()
609 junkcspc_interf = junkcspc_interf.transpose()
601 jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
610 jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
602
611
603 ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
612 ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
604
613
605 median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
614 median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
606 median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
615 median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
607 junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
616 junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
608
617
609 for iprof in range(num_prof):
618 for iprof in range(num_prof):
610 ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
619 ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
611 jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
620 jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
612
621
613 #Removiendo la Interferencia
622 #Removiendo la Interferencia
614 jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
623 jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
615
624
616 ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
625 ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
617 maxid = ListAux.index(max(ListAux))
626 maxid = ListAux.index(max(ListAux))
618
627
619 ind = numpy.array([-2,-1,1,2])
628 ind = numpy.array([-2,-1,1,2])
620 xx = numpy.zeros([4,4])
629 xx = numpy.zeros([4,4])
621
630
622 for id1 in range(4):
631 for id1 in range(4):
623 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
632 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
624
633
625 xx_inv = numpy.linalg.inv(xx)
634 xx_inv = numpy.linalg.inv(xx)
626 xx = xx_inv[:,0]
635 xx = xx_inv[:,0]
627
636
628 ind = (ind + maxid + num_mask_prof)%num_mask_prof
637 ind = (ind + maxid + num_mask_prof)%num_mask_prof
629 yy = jcspectra[ip,mask_prof[ind],:]
638 yy = jcspectra[ip,mask_prof[ind],:]
630 jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
639 jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
631
640
632 #Guardar Resultados
641 #Guardar Resultados
633 self.dataOut.data_spc = jspectra
642 self.dataOut.data_spc = jspectra
634 self.dataOut.data_cspc = jcspectra
643 self.dataOut.data_cspc = jcspectra
635
644
636 return 1
645 return 1
637
646
638 def setRadarFrequency(self, frequency=None):
647 def setRadarFrequency(self, frequency=None):
639
648
640 if frequency != None:
649 if frequency != None:
641 self.dataOut.frequency = frequency
650 self.dataOut.frequency = frequency
642
651
643 return 1
652 return 1
644
653
645 def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
654 def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
646 #validacion de rango
655 #validacion de rango
647 if minHei == None:
656 if minHei == None:
648 minHei = self.dataOut.heightList[0]
657 minHei = self.dataOut.heightList[0]
649
658
650 if maxHei == None:
659 if maxHei == None:
651 maxHei = self.dataOut.heightList[-1]
660 maxHei = self.dataOut.heightList[-1]
652
661
653 if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
662 if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
654 print 'minHei: %.2f is out of the heights range'%(minHei)
663 print 'minHei: %.2f is out of the heights range'%(minHei)
655 print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
664 print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
656 minHei = self.dataOut.heightList[0]
665 minHei = self.dataOut.heightList[0]
657
666
658 if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
667 if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
659 print 'maxHei: %.2f is out of the heights range'%(maxHei)
668 print 'maxHei: %.2f is out of the heights range'%(maxHei)
660 print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
669 print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
661 maxHei = self.dataOut.heightList[-1]
670 maxHei = self.dataOut.heightList[-1]
662
671
663 # validacion de velocidades
672 # validacion de velocidades
664 velrange = self.dataOut.getVelRange(1)
673 velrange = self.dataOut.getVelRange(1)
665
674
666 if minVel == None:
675 if minVel == None:
667 minVel = velrange[0]
676 minVel = velrange[0]
668
677
669 if maxVel == None:
678 if maxVel == None:
670 maxVel = velrange[-1]
679 maxVel = velrange[-1]
671
680
672 if (minVel < velrange[0]) or (minVel > maxVel):
681 if (minVel < velrange[0]) or (minVel > maxVel):
673 print 'minVel: %.2f is out of the velocity range'%(minVel)
682 print 'minVel: %.2f is out of the velocity range'%(minVel)
674 print 'minVel is setting to %.2f'%(velrange[0])
683 print 'minVel is setting to %.2f'%(velrange[0])
675 minVel = velrange[0]
684 minVel = velrange[0]
676
685
677 if (maxVel > velrange[-1]) or (maxVel < minVel):
686 if (maxVel > velrange[-1]) or (maxVel < minVel):
678 print 'maxVel: %.2f is out of the velocity range'%(maxVel)
687 print 'maxVel: %.2f is out of the velocity range'%(maxVel)
679 print 'maxVel is setting to %.2f'%(velrange[-1])
688 print 'maxVel is setting to %.2f'%(velrange[-1])
680 maxVel = velrange[-1]
689 maxVel = velrange[-1]
681
690
682 # seleccion de indices para rango
691 # seleccion de indices para rango
683 minIndex = 0
692 minIndex = 0
684 maxIndex = 0
693 maxIndex = 0
685 heights = self.dataOut.heightList
694 heights = self.dataOut.heightList
686
695
687 inda = numpy.where(heights >= minHei)
696 inda = numpy.where(heights >= minHei)
688 indb = numpy.where(heights <= maxHei)
697 indb = numpy.where(heights <= maxHei)
689
698
690 try:
699 try:
691 minIndex = inda[0][0]
700 minIndex = inda[0][0]
692 except:
701 except:
693 minIndex = 0
702 minIndex = 0
694
703
695 try:
704 try:
696 maxIndex = indb[0][-1]
705 maxIndex = indb[0][-1]
697 except:
706 except:
698 maxIndex = len(heights)
707 maxIndex = len(heights)
699
708
700 if (minIndex < 0) or (minIndex > maxIndex):
709 if (minIndex < 0) or (minIndex > maxIndex):
701 raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
710 raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
702
711
703 if (maxIndex >= self.dataOut.nHeights):
712 if (maxIndex >= self.dataOut.nHeights):
704 maxIndex = self.dataOut.nHeights-1
713 maxIndex = self.dataOut.nHeights-1
705
714
706 # seleccion de indices para velocidades
715 # seleccion de indices para velocidades
707 indminvel = numpy.where(velrange >= minVel)
716 indminvel = numpy.where(velrange >= minVel)
708 indmaxvel = numpy.where(velrange <= maxVel)
717 indmaxvel = numpy.where(velrange <= maxVel)
709 try:
718 try:
710 minIndexVel = indminvel[0][0]
719 minIndexVel = indminvel[0][0]
711 except:
720 except:
712 minIndexVel = 0
721 minIndexVel = 0
713
722
714 try:
723 try:
715 maxIndexVel = indmaxvel[0][-1]
724 maxIndexVel = indmaxvel[0][-1]
716 except:
725 except:
717 maxIndexVel = len(velrange)
726 maxIndexVel = len(velrange)
718
727
719 #seleccion del espectro
728 #seleccion del espectro
720 data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
729 data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
721 #estimacion de ruido
730 #estimacion de ruido
722 noise = numpy.zeros(self.dataOut.nChannels)
731 noise = numpy.zeros(self.dataOut.nChannels)
723
732
724 for channel in range(self.dataOut.nChannels):
733 for channel in range(self.dataOut.nChannels):
725 daux = data_spc[channel,:,:]
734 daux = data_spc[channel,:,:]
726 noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
735 noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
727
736
728 self.dataOut.noise_estimation = noise.copy()
737 self.dataOut.noise_estimation = noise.copy()
729
738
730 return 1
739 return 1
No newline at end of file
731
732 class IncohIntLags(Operation):
733
734
735 __profIndex = 0
736 __withOverapping = False
737
738 __byTime = False
739 __initime = None
740 __lastdatatime = None
741 __integrationtime = None
742
743 __buffer_spc = None
744 __buffer_cspc = None
745 __buffer_dc = None
746
747 __dataReady = False
748
749 __timeInterval = None
750
751 n = None
752
753
754
755 def __init__(self):
756
757 Operation.__init__(self)
758 # self.isConfig = False
759
760 def setup(self, n=None, timeInterval=None, overlapping=False):
761 """
762 Set the parameters of the integration class.
763
764 Inputs:
765
766 n : Number of coherent integrations
767 timeInterval : Time of integration. If the parameter "n" is selected this one does not work
768 overlapping :
769
770 """
771
772 self.__initime = None
773 self.__lastdatatime = 0
774
775 self.__buffer_spc = 0
776 self.__buffer_cspc = 0
777 self.__buffer_dc = 0
778
779 self.__profIndex = 0
780 self.__dataReady = False
781 self.__byTime = False
782
783 if n is None and timeInterval is None:
784 raise ValueError, "n or timeInterval should be specified ..."
785
786 if n is not None:
787 self.n = int(n)
788 else:
789 self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line
790 self.n = None
791 self.__byTime = True
792
793 def putData(self, data_spc, data_cspc, data_dc):
794
795 """
796 Add a profile to the __buffer_spc and increase in one the __profileIndex
797
798 """
799
800 self.__buffer_spc += data_spc
801
802 if data_cspc is None:
803 self.__buffer_cspc = None
804 else:
805 self.__buffer_cspc += data_cspc
806
807 if data_dc is None:
808 self.__buffer_dc = None
809 else:
810 self.__buffer_dc += data_dc
811
812 self.__profIndex += 1
813
814 return
815
816 def pushData(self):
817 """
818 Return the sum of the last profiles and the profiles used in the sum.
819
820 Affected:
821
822 self.__profileIndex
823
824 """
825
826 data_spc = self.__buffer_spc
827 data_cspc = self.__buffer_cspc
828 data_dc = self.__buffer_dc
829 n = self.__profIndex
830
831 self.__buffer_spc = 0
832 self.__buffer_cspc = 0
833 self.__buffer_dc = 0
834 self.__profIndex = 0
835
836 return data_spc, data_cspc, data_dc, n
837
838 def byProfiles(self, *args):
839
840 self.__dataReady = False
841 avgdata_spc = None
842 avgdata_cspc = None
843 avgdata_dc = None
844
845 self.putData(*args)
846
847 if self.__profIndex == self.n:
848
849 avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
850 self.n = n
851 self.__dataReady = True
852
853 return avgdata_spc, avgdata_cspc, avgdata_dc
854
855 def byTime(self, datatime, *args):
856
857 self.__dataReady = False
858 avgdata_spc = None
859 avgdata_cspc = None
860 avgdata_dc = None
861
862 self.putData(*args)
863
864 if (datatime - self.__initime) >= self.__integrationtime:
865 avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
866 self.n = n
867 self.__dataReady = True
868
869 return avgdata_spc, avgdata_cspc, avgdata_dc
870
871 def integrate(self, datatime, *args):
872
873 if self.__profIndex == 0:
874 self.__initime = datatime
875
876 if self.__byTime:
877 avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
878 else:
879 avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
880
881 if not self.__dataReady:
882 return None, None, None, None
883
884 return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc
885
886 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
887
888 if n==1:
889 return
890
891 dataOut.flagNoData = True
892
893 if not self.isConfig:
894 self.setup(n, timeInterval, overlapping)
895 self.isConfig = True
896
897 avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
898 dataOut.data_spc,
899 dataOut.data_cspc,
900 dataOut.data_dc)
901
902 if self.__dataReady:
903
904 dataOut.data_spc = avgdata_spc
905 dataOut.data_cspc = avgdata_cspc
906 dataOut.data_dc = avgdata_dc
907
908 dataOut.nIncohInt *= self.n
909 dataOut.utctime = avgdatatime
910 dataOut.flagNoData = False
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