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'''
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Created on Feb 7, 2012
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@author $Author$
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@version $Id$
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'''
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import os, sys
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import numpy
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path = os.path.split(os.getcwd())[0]
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sys.path.append(path)
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from Model.Voltage import Voltage
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from IO.VoltageIO import VoltageWriter
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from Graphics.VoltagePlot import Osciloscope
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class VoltageProcessor:
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'''
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classdocs
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'''
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def __init__(self, voltageInObj, voltageOutObj=None):
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'''
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Constructor
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'''
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self.voltageInObj = voltageInObj
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if voltageOutObj == None:
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self.voltageOutObj = Voltage()
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else:
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self.voltageOutObj = voltageOutObj
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self.integratorIndex = None
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self.decoderIndex = None
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self.profSelectorIndex = None
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self.writerIndex = None
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self.plotterIndex = None
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self.integratorList = []
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self.decoderList = []
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self.profileSelectorList = []
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self.writerList = []
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self.plotterList = []
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def init(self):
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self.integratorIndex = 0
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self.decoderIndex = 0
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self.profSelectorIndex = 0
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self.writerIndex = 0
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self.plotterIndex = 0
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self.voltageOutObj.copy(self.voltageInObj)
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def addWriter(self, wrpath):
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objWriter = VoltageWriter(self.voltageOutObj)
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objWriter.setup(wrpath)
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self.writerList.append(objWriter)
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def addPlotter(self):
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plotObj = Osciloscope(self.voltageOutObj,self.plotterIndex)
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self.plotterList.append(plotObj)
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def addIntegrator(self, nCohInt):
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objCohInt = CoherentIntegrator(nCohInt)
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self.integratorList.append(objCohInt)
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def addDecoder(self, code, ncode, nbaud):
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objDecoder = Decoder(code,ncode,nbaud)
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self.decoderList.append(objDecoder)
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def addProfileSelector(self, nProfiles):
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objProfSelector = ProfileSelector(nProfiles)
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self.profileSelectorList.append(objProfSelector)
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def writeData(self,wrpath):
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if self.voltageOutObj.flagNoData:
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return 0
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if len(self.writerList) <= self.writerIndex:
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self.addWriter(wrpath)
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self.writerList[self.writerIndex].putData()
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# myWrObj = self.writerList[self.writerIndex]
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# myWrObj.putData()
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self.writerIndex += 1
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def plotData(self,idProfile, type, xmin=None, xmax=None, ymin=None, ymax=None, winTitle=''):
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if self.voltageOutObj.flagNoData:
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return 0
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if len(self.plotterList) <= self.plotterIndex:
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self.addPlotter()
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self.plotterList[self.plotterIndex].plotData(type=type, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,winTitle=winTitle)
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self.plotterIndex += 1
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def integrator(self, N):
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if self.voltageOutObj.flagNoData:
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return 0
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if len(self.integratorList) <= self.integratorIndex:
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self.addIntegrator(N)
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myCohIntObj = self.integratorList[self.integratorIndex]
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myCohIntObj.exe(self.voltageOutObj.data)
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if myCohIntObj.flag:
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self.voltageOutObj.data = myCohIntObj.data
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self.voltageOutObj.m_ProcessingHeader.coherentInt *= N
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self.voltageOutObj.flagNoData = False
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else:
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self.voltageOutObj.flagNoData = True
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self.integratorIndex += 1
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def decoder(self,code=None,type = 0):
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if self.voltageOutObj.flagNoData:
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return 0
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if code == None:
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code = self.voltageOutObj.m_RadarControllerHeader.code
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ncode, nbaud = code.shape
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if len(self.decoderList) <= self.decoderIndex:
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self.addDecoder(code,ncode,nbaud)
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myDecodObj = self.decoderList[self.decoderIndex]
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myDecodObj.exe(data=self.voltageOutObj.data,type=type)
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if myDecodObj.flag:
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self.voltageOutObj.data = myDecodObj.data
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self.voltageOutObj.flagNoData = False
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else:
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self.voltageOutObj.flagNoData = True
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self.decoderIndex += 1
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def filterByHei(self, window):
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pass
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def selectChannels(self, channelList):
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"""
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Selecciona un bloque de datos en base a canales y pares segun el channelList y el pairList
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Input:
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channelList : lista sencilla de canales a seleccionar por ej. (2,3,7)
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pairList : tupla de pares que se desea selecionar por ej. ( (0,1), (0,2) )
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Affected:
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self.dataOutObj.datablock
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self.dataOutObj.nChannels
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self.dataOutObj.m_SystemHeader.numChannels
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self.voltageOutObj.m_ProcessingHeader.blockSize
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Return:
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None
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"""
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if not(channelList):
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return
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channels = 0
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profiles = self.voltageOutObj.nProfiles
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heights = self.voltageOutObj.m_ProcessingHeader.numHeights
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#self spectra
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channels = len(channelList)
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data = numpy.zeros( (channels,profiles,heights), dtype='complex' )
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for index,channel in enumerate(channelList):
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data[index,:,:] = self.voltageOutObj.data_spc[channel,:,:]
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self.voltageOutObj.datablock = data
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#fill the m_ProcessingHeader.spectraComb up
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channels = len(channelList)
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self.voltageOutObj.channelList = channelList
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self.voltageOutObj.nChannels = nchannels
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self.voltageOutObj.m_ProcessingHeader.totalSpectra = nchannels
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self.voltageOutObj.m_SystemHeader.numChannels = nchannels
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self.voltageOutObj.m_ProcessingHeader.blockSize = data.size
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def selectHeightsByValue(self, minHei, maxHei):
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"""
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Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
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minHei <= height <= maxHei
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Input:
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minHei : valor minimo de altura a considerar
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maxHei : valor maximo de altura a considerar
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Affected:
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Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
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Return:
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None
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"""
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minIndex = 0
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maxIndex = 0
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data = self.dataOutObj.heightList
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for i,val in enumerate(data):
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if val < minHei:
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continue
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else:
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minIndex = i;
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break
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for i,val in enumerate(data):
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if val <= maxHei:
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maxIndex = i;
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else:
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break
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self.selectHeightsByIndex(minIndex, maxIndex)
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def selectHeightsByIndex(self, minIndex, maxIndex):
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"""
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Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
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minIndex <= index <= maxIndex
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Input:
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minIndex : valor minimo de altura a considerar
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maxIndex : valor maximo de altura a considerar
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Affected:
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self.voltageOutObj.datablock
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self.voltageOutObj.m_ProcessingHeader.numHeights
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self.voltageOutObj.m_ProcessingHeader.blockSize
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self.voltageOutObj.heightList
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self.voltageOutObj.nHeights
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self.voltageOutObj.m_RadarControllerHeader.numHeights
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Return:
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None
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"""
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channels = self.voltageOutObj.nChannels
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profiles = self.voltageOutObj.nProfiles
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newheis = maxIndex - minIndex + 1
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firstHeight = 0
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#voltage
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data = numpy.zeros( (channels,profiles,newheis), dtype='complex' )
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for i in range(channels):
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data[i] = self.voltageOutObj.data_spc[i,:,minIndex:maxIndex+1]
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self.voltageOutObj.datablock = data
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firstHeight = self.dataOutObj.heightList[minIndex]
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self.voltageOutObj.nHeights = newheis
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self.voltageOutObj.m_ProcessingHeader.blockSize = data.size
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self.voltageOutObj.m_ProcessingHeader.numHeights = newheis
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self.voltageOutObj.m_ProcessingHeader.firstHeight = firstHeight
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self.voltageOutObj.m_RadarControllerHeader = newheis
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xi = firstHeight
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step = self.voltageOutObj.m_ProcessingHeader.deltaHeight
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xf = xi + newheis * step
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self.voltageOutObj.heightList = numpy.arange(xi, xf, step)
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def selectProfiles(self, minIndex, maxIndex, nProfiles):
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"""
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Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
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minIndex <= index <= maxIndex
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Input:
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minIndex : valor minimo de altura a considerar
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maxIndex : valor maximo de altura a considerar
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Affected:
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self.voltageOutObj.datablock
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self.voltageOutObj.m_ProcessingHeader.numHeights
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self.voltageOutObj.heightList
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Return:
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None
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"""
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if self.voltageOutObj.flagNoData:
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return 0
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if self.profSelectorIndex >= len(self.profileSelectorList):
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self.addProfileSelector(nProfiles)
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profileSelectorObj = self.profileSelectorList[self.profSelectorIndex]
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if profileSelectorObj.isProfileInRange(minIndex, maxIndex):
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self.voltageOutObj.flagNoData = False
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self.profSelectorIndex += 1
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return 1
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self.voltageOutObj.flagNoData = True
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self.profSelectorIndex += 1
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return 0
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def selectNtxs(self, ntx):
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pass
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class Decoder:
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def __init__(self,code, ncode, nbaud):
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self.buffer = None
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self.profCounter = 1
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self.nCode = ncode
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self.nBaud = nbaud
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self.codeIndex = 0
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self.code = code #this is a List
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self.fft_code = None
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self.flag = False
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self.setCodeFft = False
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def exe(self, data, ndata=None, type = 0):
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if ndata == None: ndata = data.shape[1]
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if type == 0:
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self.convolutionInFreq(data,ndata)
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if type == 1:
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self.convolutionInTime(data, ndata)
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def convolutionInFreq(self,data, ndata):
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newcode = numpy.zeros(ndata)
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newcode[0:self.nBaud] = self.code[self.codeIndex]
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self.codeIndex += 1
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fft_data = numpy.fft.fft(data, axis=1)
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fft_code = numpy.conj(numpy.fft.fft(newcode))
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fft_code = fft_code.reshape(1,len(fft_code))
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conv = fft_data.copy()
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conv.fill(0)
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conv = fft_data*fft_code # This other way to calculate multiplication between bidimensional arrays
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# for i in range(ndata):
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# conv[i,:] = fft_data[i,:]*fft_code[i]
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self.data = numpy.fft.ifft(conv,axis=1)
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self.flag = True
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if self.profCounter == self.nCode:
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self.profCounter = 0
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self.codeIndex = 0
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self.profCounter += 1
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def convolutionInTime(self, data, ndata):
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nchannel = data.shape[1]
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newcode = self.code[self.codeIndex]
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self.codeIndex += 1
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conv = data.copy()
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for i in range(nchannel):
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conv[i,:] = numpy.correlate(data[i,:], newcode, 'same')
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self.data = conv
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self.flag = True
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if self.profCounter == self.nCode:
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self.profCounter = 0
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self.codeIndex = 0
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self.profCounter += 1
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class CoherentIntegrator:
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def __init__(self, N):
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self.profCounter = 1
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self.data = None
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self.buffer = None
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self.flag = False
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self.nCohInt = N
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def exe(self, data):
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if self.buffer == None:
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self.buffer = data
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else:
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self.buffer = self.buffer + data
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if self.profCounter == self.nCohInt:
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self.data = self.buffer
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self.buffer = None
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self.profCounter = 0
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self.flag = True
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else:
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self.flag = False
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self.profCounter += 1
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class ProfileSelector():
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indexProfile = None
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# Tamaño total de los perfiles
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nProfiles = None
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def __init__(self, nProfiles):
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self.indexProfile = 0
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self.nProfiles = nProfiles
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def isProfileInRange(self, minIndex, maxIndex):
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if minIndex < self.indexProfile:
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self.indexProfile += 1
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return False
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if maxIndex > self.indexProfile:
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self.indexProfile += 1
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return False
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self.indexProfile += 1
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return True
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def isProfileInList(self, profileList):
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if self.indexProfile not in profileList:
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self.indexProfile += 1
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return False
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self.indexProfile += 1
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return True
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