| @@ -324,8 +324,8 class WpowerPlot_(Figure): | |||
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324 | 324 | zmin : None, |
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325 | 325 | zmax : None |
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326 | 326 | """ |
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327 | print("***************PLOTEO******************") | |
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328 | print("DATAOUT SHAPE : ",dataOut.data.shape) | |
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327 | #print("***************PLOTEO******************") | |
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328 | #print("DATAOUT SHAPE : ",dataOut.data.shape) | |
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329 | 329 | if dataOut.flagNoData: |
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330 | 330 | return dataOut |
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331 | 331 | |
| @@ -344,7 +344,7 class WpowerPlot_(Figure): | |||
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344 | 344 | channelIndexList.append(dataOut.channelList.index(channel)) |
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345 | 345 | |
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346 | 346 | |
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347 | print("channelIndexList",channelIndexList) | |
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347 | #print("channelIndexList",channelIndexList) | |
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348 | 348 | if normFactor is None: |
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349 | 349 | factor = dataOut.normFactor |
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350 | 350 | else: |
| @@ -364,7 +364,7 class WpowerPlot_(Figure): | |||
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364 | 364 | ylabel = "Range (km)" |
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365 | 365 | |
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366 | 366 | y = dataOut.getHeiRange() |
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367 | print("factor",factor) | |
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367 | #print("factor",factor) | |
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368 | 368 | |
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369 | 369 | z = dataOut.data/factor # dividido /factor |
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370 | 370 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
| @@ -88,6 +88,7 class SpectraProc(ProcessingUnit): | |||
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88 | 88 | # calculo de self-spectra |
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89 | 89 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) |
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90 | 90 | spc = fft_volt * numpy.conjugate(fft_volt) |
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91 | #print("spcch0",spc[0]) | |
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91 | 92 | spc = spc.real |
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92 | 93 | |
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93 | 94 | blocksize = 0 |
| @@ -1154,6 +1155,7 class PulsePair(Operation): | |||
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1154 | 1155 | self.__buffer = data*numpy.conjugate(data) |
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1155 | 1156 | self.__bufferV = data[:,(self.__nProf-1):,:]*numpy.conjugate(data[:,1:,:]) |
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1156 | 1157 | self.__profIndex = self.n |
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1158 | #print("spcch0",self.__buffer) | |
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1157 | 1159 | return |
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1158 | 1160 | |
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1159 | 1161 | def pushData(self): |
| @@ -1162,9 +1164,13 class PulsePair(Operation): | |||
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1162 | 1164 | data_IV = numpy.zeros((self.__nch,self.__nHeis)) |
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1163 | 1165 | |
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1164 | 1166 | for i in range(self.__nch): |
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1165 |
data_I[i,:] = numpy.sum( |
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1166 |
data_IV[i,:] = numpy.sum( |
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1167 | ||
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1167 | data_I[i,:] = numpy.sum(self.__buffer[i],axis=0)/self.n | |
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1168 | data_IV[i,:] = numpy.sum(self.__bufferV[i],axis=0)/(self.n-1) | |
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1169 | ##print("******") | |
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1170 | #print("data_I",data_I[0]) | |
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1171 | #print(self.__buffer.shape) | |
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1172 | #a=numpy.average(self.__buffer,axis=1) | |
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1173 | #print("average", a) | |
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1168 | 1174 | n = self.__profIndex |
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1169 | 1175 | ####data_intensity = numpy.sum(numpy.sum(self.__buffer,axis=0),axis=0)/self.n |
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1170 | 1176 | #print("data_intensity push data",data_intensity.shape) |
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