| @@ -376,56 +376,56 class ProcessingHeader(Header): | |||
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376 | 376 | self.flag_cspc = False |
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377 | 377 | |
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378 | 378 | def read(self, fp): |
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379 | try: | |
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380 |
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381 |
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379 | # try: | |
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380 | header = numpy.fromfile(fp,self.struct,1) | |
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381 | self.size = int(header['nSize'][0]) | |
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382 | self.dtype = int(header['nDataType'][0]) | |
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383 | self.blockSize = int(header['nSizeOfDataBlock'][0]) | |
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384 | self.profilesPerBlock = int(header['nProfilesperBlock'][0]) | |
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385 | self.dataBlocksPerFile = int(header['nDataBlocksperFile'][0]) | |
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386 | self.nWindows = int(header['nNumWindows'][0]) | |
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387 | self.processFlags = header['nProcessFlags'] | |
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388 | self.nCohInt = int(header['nCoherentIntegrations'][0]) | |
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389 | self.nIncohInt = int(header['nIncoherentIntegrations'][0]) | |
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390 | self.totalSpectra = int(header['nTotalSpectra'][0]) | |
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391 | self.samplingWindow = numpy.fromfile(fp,self.structSamplingWindow,self.nWindows) | |
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392 | self.nHeights = int(numpy.sum(self.samplingWindow['nsa'])) | |
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393 | self.firstHeight = float(self.samplingWindow['h0'][0]) | |
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394 | self.deltaHeight = float(self.samplingWindow['dh'][0]) | |
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395 | self.samplesWin = self.samplingWindow['nsa'] | |
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396 | self.spectraComb = numpy.fromfile(fp,'u1',2*self.totalSpectra) | |
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397 | ||
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398 | # if ((self.processFlags & PROCFLAG.DEFINE_PROCESS_CODE) == PROCFLAG.DEFINE_PROCESS_CODE): | |
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399 | # self.nCode = int(numpy.fromfile(fp,'<u4',1)) | |
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400 | # self.nBaud = int(numpy.fromfile(fp,'<u4',1)) | |
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401 | # self.code = numpy.fromfile(fp,'<f4',self.nCode*self.nBaud).reshape(self.nCode,self.nBaud) | |
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402 | ||
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403 | if ((self.processFlags & PROCFLAG.SHIFT_FFT_DATA) == PROCFLAG.SHIFT_FFT_DATA): | |
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404 | self.shif_fft = True | |
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405 | else: | |
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406 | self.shif_fft = False | |
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402 | 407 | |
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403 |
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404 |
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408 | if ((self.processFlags & PROCFLAG.SAVE_CHANNELS_DC) == PROCFLAG.SAVE_CHANNELS_DC): | |
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409 | self.flag_dc = True | |
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410 | ||
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411 | nChannels = 0 | |
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412 | nPairs = 0 | |
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413 | pairList = [] | |
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414 | ||
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415 | for i in range( 0, self.totalSpectra*2, 2 ): | |
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416 | if self.spectraComb[i] == self.spectraComb[i+1]: | |
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417 | nChannels = nChannels + 1 #par de canales iguales | |
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405 | 418 | else: |
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406 | self.shif_fft = False | |
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407 | ||
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408 | if ((self.processFlags & PROCFLAG.SAVE_CHANNELS_DC) == PROCFLAG.SAVE_CHANNELS_DC): | |
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409 |
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410 |
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411 |
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412 | nPairs = 0 | |
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413 | pairList = [] | |
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414 | ||
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415 | for i in range( 0, self.totalSpectra*2, 2 ): | |
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416 | if self.spectraComb[i] == self.spectraComb[i+1]: | |
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417 | nChannels = nChannels + 1 #par de canales iguales | |
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418 | else: | |
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419 | nPairs = nPairs + 1 #par de canales diferentes | |
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420 | pairList.append( (self.spectraComb[i], self.spectraComb[i+1]) ) | |
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421 | ||
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422 | self.flag_cspc = False | |
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423 | if nPairs > 0: | |
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424 | self.flag_cspc = True | |
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419 | nPairs = nPairs + 1 #par de canales diferentes | |
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420 | pairList.append( (self.spectraComb[i], self.spectraComb[i+1]) ) | |
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421 | ||
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422 | self.flag_cspc = False | |
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423 | if nPairs > 0: | |
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424 | self.flag_cspc = True | |
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425 | 425 | |
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426 | except Exception, e: | |
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427 |
print "ProcessingHeader: " |
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428 | return 0 | |
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426 | # except Exception, e: | |
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427 | # print "Error ProcessingHeader: " | |
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428 | # return 0 | |
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429 | 429 | |
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430 | 430 | return 1 |
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431 | 431 | |
| @@ -107,8 +107,9 class CrossSpectraPlot(Figure): | |||
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107 | 107 | noisedB = 10*numpy.log10(noise) |
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108 | 108 | |
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109 | 109 | |
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110 | thisDatetime = dataOut.datatime | |
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111 | title = "Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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110 | #thisDatetime = dataOut.datatime | |
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111 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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112 | title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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112 | 113 | xlabel = "Velocity (m/s)" |
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113 | 114 | ylabel = "Range (Km)" |
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114 | 115 | |
| @@ -293,7 +294,7 class RTIPlot(Figure): | |||
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293 | 294 | |
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294 | 295 | # thisDatetime = dataOut.datatime |
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295 | 296 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) |
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296 |
title = wintitle |
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297 | title = wintitle + " RTI: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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297 | 298 | xlabel = "" |
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298 | 299 | ylabel = "Range (Km)" |
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299 | 300 | |
| @@ -455,8 +456,9 class SpectraPlot(Figure): | |||
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455 | 456 | avgdB = 10*numpy.log10(avg) |
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456 | 457 | noisedB = 10*numpy.log10(noise) |
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457 | 458 | |
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458 | thisDatetime = dataOut.datatime | |
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459 | title = "Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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459 | #thisDatetime = dataOut.datatime | |
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460 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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461 | title = wintitle + " Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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460 | 462 | xlabel = "Velocity (m/s)" |
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461 | 463 | ylabel = "Range (Km)" |
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462 | 464 | |
| @@ -572,8 +574,9 class Scope(Figure): | |||
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572 | 574 | y = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:]) |
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573 | 575 | y = y.real |
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574 | 576 | |
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575 | thisDatetime = dataOut.datatime | |
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576 | title = "Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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577 | #thisDatetime = dataOut.datatime | |
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578 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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579 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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577 | 580 | xlabel = "Range (Km)" |
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578 | 581 | ylabel = "Intensity" |
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579 | 582 | |
| @@ -674,8 +677,9 class PowerProfilePlot(Figure): | |||
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674 | 677 | |
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675 | 678 | avgdB = 10*numpy.log10(avg) |
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676 | 679 | |
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677 | thisDatetime = dataOut.datatime | |
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678 | title = "Power Profile" | |
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680 | #thisDatetime = dataOut.datatime | |
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681 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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682 | title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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679 | 683 | xlabel = "dB" |
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680 | 684 | ylabel = "Range (Km)" |
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681 | 685 | |
| @@ -798,8 +802,9 class CoherenceMap(Figure): | |||
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798 | 802 | x = dataOut.getTimeRange() |
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799 | 803 | y = dataOut.getHeiRange() |
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800 | 804 | |
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801 | thisDatetime = dataOut.datatime | |
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802 | title = "CoherenceMap: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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805 | #thisDatetime = dataOut.datatime | |
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806 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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807 | title = wintitle + " CoherenceMap: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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803 | 808 | xlabel = "" |
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804 | 809 | ylabel = "Range (Km)" |
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805 | 810 | |
| @@ -963,8 +968,9 class RTIfromNoise(Figure): | |||
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963 | 968 | noise = dataOut.getNoise()/factor |
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964 | 969 | noisedB = 10*numpy.log10(noise) |
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965 | 970 | |
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966 | thisDatetime = dataOut.datatime | |
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967 | title = "RTI Noise: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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971 | #thisDatetime = dataOut.datatime | |
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972 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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973 | title = wintitle + " RTI Noise: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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968 | 974 | xlabel = "" |
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969 | 975 | ylabel = "Range (Km)" |
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970 | 976 | |
| @@ -1156,8 +1162,9 class SpectraHeisScope(Figure): | |||
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1156 | 1162 | datadB = 10.*numpy.log10(dataOut.data_spc) |
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1157 | 1163 | y = datadB |
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1158 | 1164 | |
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1159 | thisDatetime = dataOut.datatime | |
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1160 | title = "Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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1165 | #thisDatetime = dataOut.datatime | |
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1166 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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1167 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) | |
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1161 | 1168 | xlabel = "Frequency x 10000" |
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1162 | 1169 | ylabel = "Intensity (dB)" |
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1163 | 1170 | |
| @@ -1283,8 +1290,9 class RTIfromSpectraHeis(Figure): | |||
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1283 | 1290 | # noise = dataOut.getNoise()/factor |
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1284 | 1291 | # noisedB = 10*numpy.log10(noise) |
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1285 | 1292 | |
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1286 | thisDatetime = dataOut.datatime | |
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1287 | title = "RTI: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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1293 | #thisDatetime = dataOut.datatime | |
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1294 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1]) | |
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1295 | title = wintitle + " RTI: %s" %(thisDatetime.strftime("%d-%b-%Y")) | |
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1288 | 1296 | xlabel = "Local Time" |
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1289 | 1297 | ylabel = "Intensity (dB)" |
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1290 | 1298 | |
| @@ -273,7 +273,7 class VoltageProc(ProcessingUnit): | |||
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273 | 273 | |
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274 | 274 | return 1 |
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275 | 275 | |
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276 | def selectHeights(self, minHei, maxHei): | |
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276 | def selectHeights(self, minHei=None, maxHei=None): | |
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277 | 277 | """ |
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278 | 278 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
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279 | 279 | minHei <= height <= maxHei |
| @@ -288,9 +288,17 class VoltageProc(ProcessingUnit): | |||
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288 | 288 | Return: |
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289 | 289 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
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290 | 290 | """ |
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291 | ||
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292 | if minHei == None: | |
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293 | minHei = self.dataOut.heightList[0] | |
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294 | ||
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295 | if maxHei == None: | |
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296 | maxHei = self.dataOut.heightList[-1] | |
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297 | ||
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291 | 298 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
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292 | 299 | raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
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293 | 300 | |
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301 | ||
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294 | 302 | if (maxHei > self.dataOut.heightList[-1]): |
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295 | 303 | maxHei = self.dataOut.heightList[-1] |
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296 | 304 | # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei) |
| @@ -358,7 +366,7 class VoltageProc(ProcessingUnit): | |||
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358 | 366 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
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359 | 367 | |
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360 | 368 | if window == None: |
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361 | window = self.dataOut.radarControllerHeaderObj.txA / deltaHeight | |
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369 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
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362 | 370 | |
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363 | 371 | newdelta = deltaHeight * window |
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364 | 372 | r = self.dataOut.data.shape[1] % window |
| @@ -366,7 +374,7 class VoltageProc(ProcessingUnit): | |||
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366 | 374 | buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window) |
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367 | 375 | buffer = numpy.sum(buffer,2) |
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368 | 376 | self.dataOut.data = buffer |
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369 | self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*self.dataOut.nHeights/window,newdelta) | |
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377 | self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*(self.dataOut.nHeights-r)/window,newdelta) | |
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370 | 378 | self.dataOut.windowOfFilter = window |
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371 | 379 | |
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372 | 380 | def deFlip(self): |
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