##// END OF EJS Templates
schain-jc
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Se corrige bug en el metodo filterByHeights....
Daniel Valdez -
r236:b12f3705eeef
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@@ -1400,13 +1400,13 class VoltageReader(JRODataReader):
1400 1400
1401 1401 self.dataOut.flagShiftFFT = False
1402 1402
1403 if self.processingHeaderObj.code != None:
1403 if self.radarControllerHeaderObj.code != None:
1404 1404
1405 self.dataOut.nCode = self.processingHeaderObj.nCode
1405 self.dataOut.nCode = self.radarControllerHeaderObj.nCode
1406 1406
1407 self.dataOut.nBaud = self.processingHeaderObj.nBaud
1407 self.dataOut.nBaud = self.radarControllerHeaderObj.nBaud
1408 1408
1409 self.dataOut.code = self.processingHeaderObj.code
1409 self.dataOut.code = self.radarControllerHeaderObj.code
1410 1410
1411 1411 self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
1412 1412
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@@ -360,7 +360,7 class VoltageProc(ProcessingUnit):
360 360 buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window)
361 361 buffer = numpy.average(buffer,2)
362 362 self.dataOut.data = buffer
363 self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*self.dataOut.nHeights/window,newdelta)
363 self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*self.dataOut.nHeights/window-newdelta,newdelta)
364 364
365 365
366 366
@@ -586,7 +586,7 class Decoder(Operation):
586 586
587 587 def convolutionInFreq(self, data):
588 588
589 ndata = data.shape[1]
589 nchannel, ndata = data.shape
590 590 newcode = numpy.zeros(ndata)
591 591 newcode[0:self.nBaud] = self.code[self.__profIndex]
592 592
@@ -604,8 +604,9 class Decoder(Operation):
604 604 datadec = data[:,:-self.nBaud+1]
605 605 ndatadec = ndata - self.nBaud + 1
606 606
607 if self.__profIndex == self.nCode:
607 if self.__profIndex == self.nCode-1:
608 608 self.__profIndex = 0
609 return ndatadec, datadec
609 610
610 611 self.__profIndex += 1
611 612
@@ -614,18 +615,18 class Decoder(Operation):
614 615
615 616 def convolutionInTime(self, data):
616 617
617 nchannel = data.shape[1]
618 nchannel, ndata = data.shape
618 619 newcode = self.code[self.__profIndex]
620 ndatadec = ndata - self.nBaud + 1
619 621
620 datadec = data.copy()
622 datadec = numpy.zeros((nchannel, ndatadec))
621 623
622 624 for i in range(nchannel):
623 625 datadec[i,:] = numpy.correlate(data[i,:], newcode)
624 626
625 ndatadec = ndata - self.nBaud + 1
626
627 if self.__profIndex == self.nCode:
628 self.__profIndex = 0
627 if self.__profIndex == self.nCode-1:
628 self.__profIndex = 0
629 return ndatadec, datadec
629 630
630 631 self.__profIndex += 1
631 632
@@ -642,14 +643,15 class Decoder(Operation):
642 643 self.__isConfig = True
643 644
644 645 if mode == 0:
645 ndatadec, datadec = self.convolutionInFreq(data)
646 ndatadec, datadec = self.convolutionInFreq(dataOut.data)
646 647
647 648 if mode == 1:
648 ndatadec, datadec = self.convolutionInTime(data)
649 print "This function is not implemented"
650 # ndatadec, datadec = self.convolutionInTime(dataOut.data)
649 651
650 652 dataOut.data = datadec
651 653
652 dataOut.heightList = dataOut.heightList[0:ndatadec+1]
654 dataOut.heightList = dataOut.heightList[0:ndatadec]
653 655
654 656 dataOut.flagDecodeData = True #asumo q la data no esta decodificada
655 657
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