schain Commit - r605:a6d4a56ce242 · Jicamarca Repository

Bug fixed reading voltage data by block....

Miguel Valdez -

r605:a6d4a56ce242

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r605:a6d4a56ce242

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schainpy/model/data/jrodata.py +3 -3

             '''
             $Author: murco $
             $Id: JROData.py 173 2012-11-20 15:06:21Z murco $
             '''
             import copy
             import numpy
             import datetime
             from jroheaderIO import SystemHeader, RadarControllerHeader
             def getNumpyDtype(dataTypeCode):
                 if dataTypeCode == 0:
                     numpyDtype = numpy.dtype([('real','<i1'),('imag','<i1')])
                 elif dataTypeCode == 1:
                     numpyDtype = numpy.dtype([('real','<i2'),('imag','<i2')])
                 elif dataTypeCode == 2:
                     numpyDtype = numpy.dtype([('real','<i4'),('imag','<i4')])
                 elif dataTypeCode == 3:
                     numpyDtype = numpy.dtype([('real','<i8'),('imag','<i8')])
                 elif dataTypeCode == 4:
                     numpyDtype = numpy.dtype([('real','<f4'),('imag','<f4')])
                 elif dataTypeCode == 5:
                     numpyDtype = numpy.dtype([('real','<f8'),('imag','<f8')])
                 else:
                     raise ValueError, 'dataTypeCode was not defined'
                 return numpyDtype
             def getDataTypeCode(numpyDtype):
                 if numpyDtype == numpy.dtype([('real','<i1'),('imag','<i1')]):
                     datatype = 0
                 elif numpyDtype == numpy.dtype([('real','<i2'),('imag','<i2')]):
                     datatype = 1
                 elif numpyDtype == numpy.dtype([('real','<i4'),('imag','<i4')]):
                     datatype = 2
                 elif numpyDtype == numpy.dtype([('real','<i8'),('imag','<i8')]):
                     datatype = 3
                 elif numpyDtype == numpy.dtype([('real','<f4'),('imag','<f4')]):
                     datatype = 4
                 elif numpyDtype == numpy.dtype([('real','<f8'),('imag','<f8')]):
                     datatype = 5
                 else:
                     datatype = None
                 return datatype
             def hildebrand_sekhon(data, navg):
                 """
                 This method is for the objective determination of the noise level in Doppler spectra. This
                 implementation technique is based on the fact that the standard deviation of the spectral
                 densities is equal to the mean spectral density for white Gaussian noise
                 Inputs:
                     Data    :    heights
                     navg    :    numbers of averages
                 Return:
                     -1        :    any error
                     anoise    :    noise's level
                 """
                 sortdata = numpy.sort(data,axis=None)
                 lenOfData = len(sortdata)
                 nums_min = lenOfData/10
                 if (lenOfData/10) > 2:
                     nums_min = lenOfData/10
                 else:
                     nums_min = 2
                 sump = 0.
                 sumq = 0.
                 j = 0
                 cont = 1
                 while((cont==1)and(j<lenOfData)):
                     sump += sortdata[j]
                     sumq += sortdata[j]**2
-                    j += 1
                     if j > nums_min:
                         rtest = float(j)/(j-1) + 1.0/navg
                         if ((sumq*j) > (rtest*sump**2)):
                             j = j - 1
                             sump  = sump - sortdata[j]
                             sumq =  sumq - sortdata[j]**2
                             cont = 0
+                    j += 1
                 lnoise = sump /j
                 stdv = numpy.sqrt((sumq - lnoise**2)/(j - 1))
                 return lnoise
             class Beam:
                 def __init__(self):
                     self.codeList = []
                     self.azimuthList = []
                     self.zenithList = []
             class GenericData(object):
                 flagNoData = True
                 def __init__(self):
                     raise ValueError, "This class has not been implemented"
                 def copy(self, inputObj=None):
                     if inputObj == None:
                         return copy.deepcopy(self)
                     for key in inputObj.__dict__.keys():
                         self.__dict__[key] = inputObj.__dict__[key]
                 def deepcopy(self):
                     return copy.deepcopy(self)
                 def isEmpty(self):
                     return self.flagNoData
             class JROData(GenericData):
             #    m_BasicHeader = BasicHeader()
             #    m_ProcessingHeader = ProcessingHeader()
                 systemHeaderObj = SystemHeader()
                 radarControllerHeaderObj = RadarControllerHeader()
             #    data = None
                 type = None
                 datatype = None #dtype but in string
             #     dtype = None
             #    nChannels = None
             #    nHeights = None
                 nProfiles = None
                 heightList = None
                 channelList = None
                 flagDiscontinuousBlock = False
                 useLocalTime = False
                 utctime = None
                 timeZone = None
                 dstFlag = None
                 errorCount = None
                 blocksize = None
             #     nCode = None
             #
             #     nBaud = None
             #
             #     code = None
                 flagDecodeData = False #asumo q la data no esta decodificada
                 flagDeflipData = False #asumo q la data no esta sin flip
                 flagShiftFFT = False
             #     ippSeconds = None
             #     timeInterval = None
                 nCohInt = None
             #     noise = None
                 windowOfFilter = 1
                 #Speed of ligth
                 C = 3e8
                 frequency = 49.92e6
                 realtime = False
                 beacon_heiIndexList = None
                 last_block = None
                 blocknow = None
                 azimuth = None
                 zenith = None
                 beam = Beam()
                 profileIndex = None
                 def __init__(self):
                     raise ValueError, "This class has not been implemented"
                 def getNoise(self):
                     raise ValueError, "Not implemented"
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return range(self.nChannels)
                 def getNHeights(self):
                     return len(self.heightList)
                 def getHeiRange(self, extrapoints=0):
                     heis = self.heightList
             #        deltah = self.heightList[1] - self.heightList[0]
             #
             #        heis.append(self.heightList[-1])
                     return heis
                 def getltctime(self):
                     if self.useLocalTime:
                         return self.utctime - self.timeZone*60
                     return self.utctime
                 def getDatatime(self):
                     datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime)
                     return datatimeValue
                 def getTimeRange(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.timeInterval+60)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getFmax(self):
                     PRF = 1./(self.ippSeconds * self.nCohInt)
                     fmax = PRF/2.
                     return fmax
                 def getVmax(self):
                     _lambda = self.C/self.frequency
                     vmax = self.getFmax() * _lambda
                     return vmax
                 def get_ippSeconds(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.ippSeconds
                 def set_ippSeconds(self, ippSeconds):
                     '''
                     '''
                     self.radarControllerHeaderObj.ippSeconds = ippSeconds
                     return
                 def get_dtype(self):
                     '''
                     '''
                     return getNumpyDtype(self.datatype)
                 def set_dtype(self, numpyDtype):
                     '''
                     '''
                     self.datatype = getDataTypeCode(numpyDtype)
                 def get_code(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.code
                 def set_code(self, code):
                     '''
                     '''
                     self.radarControllerHeaderObj.code = code
                     return
                 def get_ncode(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.nCode
                 def set_ncode(self, nCode):
                     '''
                     '''
                     self.radarControllerHeaderObj.nCode = nCode
                     return
                 def get_nbaud(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.nBaud
                 def set_nbaud(self, nBaud):
                     '''
                     '''
                     self.radarControllerHeaderObj.nBaud = nBaud
                     return
             #     def getTimeInterval(self):
             #
             #         raise IOError, "This method should be implemented inside each Class"
                 nChannels = property(getNChannels, "I'm the 'nChannel' property.")
                 channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.")
                 nHeights = property(getNHeights, "I'm the 'nHeights' property.")
                 #noise = property(getNoise, "I'm the 'nHeights' property.")
                 datatime = property(getDatatime, "I'm the 'datatime' property")
                 ltctime = property(getltctime, "I'm the 'ltctime' property")
                 ippSeconds = property(get_ippSeconds, set_ippSeconds)
                 dtype = property(get_dtype, set_dtype)
             #     timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
                 code = property(get_code, set_code)
                 nCode = property(get_ncode, set_ncode)
                 nBaud = property(get_nbaud, set_nbaud)
             class Voltage(JROData):
                 #data es un numpy array de 2 dmensiones (canales, alturas)
                 data = None
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.useLocalTime = True
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Voltage"
                     self.data = None
             #         self.dtype = None
             #        self.nChannels = 0
             #        self.nHeights = 0
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #        self.channelIndexList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.timeZone = None
                     self.dstFlag = None
                     self.errorCount = None
                     self.nCohInt = None
                     self.blocksize = None
                     self.flagDecodeData = False #asumo q la data no esta decodificada
                     self.flagDeflipData = False #asumo q la data no esta sin flip
                     self.flagShiftFFT = False
                     self.flagDataAsBlock = False    #Asumo que la data es leida perfil a perfil
                     self.profileIndex = 0
                 def getNoisebyHildebrand(self, channel = None):
                     """
                     Determino el nivel de ruido usando el metodo Hildebrand-Sekhon
                     Return:
                         noiselevel
                     """
                     if channel != None:
                         data = self.data[channel]
                         nChannels = 1
                     else:
                         data = self.data
                         nChannels = self.nChannels
                     noise = numpy.zeros(nChannels)
                     power = data * numpy.conjugate(data)
                     for thisChannel in range(nChannels):
                         if nChannels == 1:
                             daux = power[:].real
                         else:
                             daux = power[thisChannel,:].real
                         noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt)
                     return noise
                 def getNoise(self, type = 1, channel = None):
                     if type == 1:
                         noise = self.getNoisebyHildebrand(channel)
                     return 10*numpy.log10(noise)
                 def getPower(self, channel = None):
                     if channel != None:
                         data = self.data[channel]
                     else:
                         data = self.data
                     power = data * numpy.conjugate(data)
                     return 10*numpy.log10(power.real)
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt
                     return timeInterval
                 noise = property(getNoise, "I'm the 'nHeights' property.")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             class Spectra(JROData):
                 #data es un numpy array de 2 dmensiones (canales, perfiles, alturas)
                 data_spc = None
                 #data es un numpy array de 2 dmensiones (canales, pares, alturas)
                 data_cspc = None
                 #data es un numpy array de 2 dmensiones (canales, alturas)
                 data_dc = None
                 nFFTPoints = None
             #     nPairs = None
                 pairsList = None
                 nIncohInt = None
                 wavelength = None #Necesario para cacular el rango de velocidad desde la frecuencia
                 nCohInt = None #se requiere para determinar el valor de timeInterval
                 ippFactor = None
                 profileIndex = 0
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.useLocalTime = True
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Spectra"
             #        self.data = None
             #         self.dtype = None
             #        self.nChannels = 0
             #        self.nHeights = 0
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #        self.channelIndexList = None
                     self.pairsList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.nCohInt = None
                     self.nIncohInt = None
                     self.blocksize = None
                     self.nFFTPoints = None
                     self.wavelength = None
                     self.flagDecodeData = False #asumo q la data no esta decodificada
                     self.flagDeflipData = False #asumo q la data no esta sin flip
                     self.flagShiftFFT = False
                     self.ippFactor = 1
                     #self.noise = None
                     self.beacon_heiIndexList = []
                     self.noise_estimation = None
                 def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None):
                     """
                     Determino el nivel de ruido usando el metodo Hildebrand-Sekhon
                     Return:
                         noiselevel
                     """
                     noise = numpy.zeros(self.nChannels)
                     for channel in range(self.nChannels):
                         daux = self.data_spc[channel,xmin_index:xmax_index,ymin_index:ymax_index]
                         noise[channel] = hildebrand_sekhon(daux, self.nIncohInt)
                     return noise
                 def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None):
                     if self.noise_estimation != None:
                         return self.noise_estimation #this was estimated by getNoise Operation defined in jroproc_spectra.py
                     else:
                         noise = self.getNoisebyHildebrand(xmin_index, xmax_index, ymin_index, ymax_index)
                         return noise
                 def getFreqRange(self, extrapoints=0):
                     deltafreq = self.getFmax() / (self.nFFTPoints*self.ippFactor)
                     freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2
                     return freqrange
                 def getVelRange(self, extrapoints=0):
                     deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor)
                     velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltav/2
                     return velrange
                 def getNPairs(self):
                     return len(self.pairsList)
                 def getPairsIndexList(self):
                     return range(self.nPairs)
                 def getNormFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
                     normFactor = self.nProfiles*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
                     return normFactor
                 def getFlagCspc(self):
                     if self.data_cspc == None:
                         return True
                     return False
                 def getFlagDc(self):
                     if self.data_dc == None:
                         return True
                     return False
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles
                     return timeInterval
                 nPairs = property(getNPairs, "I'm the 'nPairs' property.")
                 pairsIndexList = property(getPairsIndexList, "I'm the 'pairsIndexList' property.")
                 normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.")
                 flag_cspc = property(getFlagCspc)
                 flag_dc = property(getFlagDc)
                 noise = property(getNoise, "I'm the 'nHeights' property.")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             class SpectraHeis(Spectra):
                 data_spc = None
                 data_cspc = None
                 data_dc = None
                 nFFTPoints = None
             #     nPairs = None
                 pairsList = None
                 nCohInt = None
                 nIncohInt = None
                 def __init__(self):
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "SpectraHeis"
             #         self.dtype = None
             #        self.nChannels = 0
             #        self.nHeights = 0
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #        self.channelIndexList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
             #         self.nPairs = 0
                     self.utctime = None
                     self.blocksize = None
                     self.profileIndex = 0
                     self.nCohInt = 1
                     self.nIncohInt = 1
                 def getNormFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     normFactor = self.nIncohInt*self.nCohInt*pwcode
                     return normFactor
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     return timeInterval
                 normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             class Fits(JROData):
                 heightList = None
                 channelList = None
                 flagNoData = True
                 flagDiscontinuousBlock = False
                 useLocalTime = False
                 utctime = None
                 timeZone = None
             #     ippSeconds = None
             #     timeInterval = None
                 nCohInt = None
                 nIncohInt = None
                 noise = None
                 windowOfFilter = 1
                 #Speed of ligth
                 C = 3e8
                 frequency = 49.92e6
                 realtime = False
                 def __init__(self):
                     self.type = "Fits"
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #         self.channelIndexList = None
                     self.flagNoData = True
                     self.utctime = None
                     self.nCohInt = 1
                     self.nIncohInt = 1
                     self.useLocalTime = True
                     self.profileIndex = 0
             #         self.utctime = None
             #         self.timeZone = None
             #         self.ltctime = None
             #         self.timeInterval = None
             #         self.header = None
             #         self.data_header = None
             #         self.data = None
             #         self.datatime = None
             #         self.flagNoData = False
             #         self.expName = ''
             #         self.nChannels = None
             #         self.nSamples = None
             #         self.dataBlocksPerFile = None
             #         self.comments = ''
             #
                 def getltctime(self):
                     if self.useLocalTime:
                         return self.utctime - self.timeZone*60
                     return self.utctime
                 def getDatatime(self):
                     datatime = datetime.datetime.utcfromtimestamp(self.ltctime)
                     return datatime
                 def getTimeRange(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.timeInterval)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getHeiRange(self):
                     heis = self.heightList
                     return heis
                 def isEmpty(self):
                     return self.flagNoData
                 def getNHeights(self):
                     return len(self.heightList)
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return range(self.nChannels)
                 def getNoise(self, type = 1):
                     #noise = numpy.zeros(self.nChannels)
                     if type == 1:
                         noise = self.getNoisebyHildebrand()
                     if type == 2:
                         noise = self.getNoisebySort()
                     if type == 3:
                         noise = self.getNoisebyWindow()
                     return noise
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     return timeInterval
                 datatime = property(getDatatime, "I'm the 'datatime' property")
                 nHeights = property(getNHeights, "I'm the 'nHeights' property.")
                 nChannels = property(getNChannels, "I'm the 'nChannel' property.")
                 channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.")
                 noise = property(getNoise, "I'm the 'nHeights' property.")
                 datatime = property(getDatatime, "I'm the 'datatime' property")
                 ltctime = property(getltctime, "I'm the 'ltctime' property")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             class Correlation(JROData):
                 noise = None
                 SNR = None
                 pairsAutoCorr = None    #Pairs of Autocorrelation
                 #--------------------------------------------------
                 data_corr = None
                 data_volt = None
                 lagT = None # each element value is a profileIndex
                 lagR = None # each element value is in km
                 pairsList = None
                 calculateVelocity = None
                 nPoints = None
                 nAvg = None
                 bufferSize = None
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Correlation"
                     self.data = None
                     self.dtype = None
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.timeZone = None
                     self.dstFlag = None
                     self.errorCount = None
                     self.blocksize = None
                     self.flagDecodeData = False #asumo q la data no esta decodificada
                     self.flagDeflipData = False #asumo q la data no esta sin flip
                     self.pairsList = None
                     self.nPoints = None
                 def getLagTRange(self, extrapoints=0):
                     lagTRange = self.lagT
                     diff = lagTRange[1] - lagTRange[0]
                     extra = numpy.arange(1,extrapoints + 1)*diff + lagTRange[-1]
                     lagTRange = numpy.hstack((lagTRange, extra))
                     return lagTRange
                 def getLagRRange(self, extrapoints=0):
                     return self.lagR
                 def getPairsList(self):
                     return self.pairsList
                 def getCalculateVelocity(self):
                     return self.calculateVelocity
                 def getNPoints(self):
                     return self.nPoints
                 def getNAvg(self):
                     return self.nAvg
                 def getBufferSize(self):
                     return self.bufferSize
                 def getPairsAutoCorr(self):
                     pairsList = self.pairsList
                     pairsAutoCorr = numpy.zeros(self.nChannels, dtype = 'int')*numpy.nan
                     for l in range(len(pairsList)):
                         firstChannel = pairsList[l][0]
                         secondChannel = pairsList[l][1]
                         #Obteniendo pares de Autocorrelacion
                         if firstChannel == secondChannel:
                             pairsAutoCorr[firstChannel] = int(l)
                     pairsAutoCorr = pairsAutoCorr.astype(int)
                     return pairsAutoCorr
                 def getNoise(self, mode = 2):
                     indR = numpy.where(self.lagR == 0)[0][0]
                     indT = numpy.where(self.lagT == 0)[0][0]
                     jspectra0 = self.data_corr[:,:,indR,:]
                     jspectra = copy.copy(jspectra0)
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
                     freq_dc = jspectra.shape[1]/2
                     ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
                     if ind_vel[0]<0:
                         ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
                     if mode == 1:
                         jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
                     if mode == 2:
                         vel = numpy.array([-2,-1,1,2])
                         xx = numpy.zeros([4,4])
                         for fil in range(4):
                             xx[fil,:] = vel[fil]**numpy.asarray(range(4))
                         xx_inv = numpy.linalg.inv(xx)
                         xx_aux = xx_inv[0,:]
                         for ich in range(num_chan):
                             yy = jspectra[ich,ind_vel,:]
                             jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
                             junkid = jspectra[ich,freq_dc,:]<=0
                             cjunkid = sum(junkid)
                             if cjunkid.any():
                                 jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
                     noise = jspectra0[:,freq_dc,:] - jspectra[:,freq_dc,:]
                     return noise
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nPoints
                     return timeInterval
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             #     pairsList = property(getPairsList, "I'm the 'pairsList' property.")
             #     nPoints = property(getNPoints, "I'm the 'nPoints' property.")
                 calculateVelocity = property(getCalculateVelocity, "I'm the 'calculateVelocity' property.")
                 nAvg = property(getNAvg, "I'm the 'nAvg' property.")
                 bufferSize = property(getBufferSize, "I'm the 'bufferSize' property.")
             class Parameters(JROData):
                 #Information from previous data
                 inputUnit = None        #Type of data to be processed
                 operation = None        #Type of operation to parametrize
                 normFactor = None       #Normalization Factor
                 groupList = None        #List of Pairs, Groups, etc
                 #Parameters
                 data_param = None       #Parameters obtained
                 data_pre = None         #Data Pre Parametrization
                 data_SNR = None         #Signal to Noise Ratio
                 heightRange = None      #Heights
                 abscissaRange = None    #Abscissa, can be velocities, lags or time
                 noise = None            #Noise Potency
             #     initUtcTime = None      #Initial UTC time
                 paramInterval = None    #Time interval to calculate Parameters in seconds
                 #Fitting
                 data_error = None       #Error of the estimation
                 constants = None
                 library = None
                 #Output signal
                 outputInterval = None     #Time interval to calculate output signal in seconds
                 data_output = None       #Out signal
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Parameters"
                 def getTimeRange1(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.outputInterval - 1)
                     datatime = numpy.array(datatime)
                     return datatime

schainpy/model/io/jroIO_voltage.py +4 -5

             '''
             Created on Jul 2, 2014
             @author: roj-idl71
             '''
             import numpy
             from jroIO_base import LOCALTIME, JRODataReader, JRODataWriter
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, RadarControllerHeader, ProcessingHeader
             from schainpy.model.data.jrodata import Voltage
             class VoltageReader(JRODataReader, ProcessingUnit):
                 """
                 Esta clase permite leer datos de voltage desde archivos en formato rawdata (.r). La lectura
                 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones:
                 perfiles*alturas*canales) son almacenados en la variable "buffer".
                                          perfiles * alturas * canales
                 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
                 RadarControllerHeader y Voltage. Los tres primeros se usan para almacenar informacion de la
                 cabecera de datos (metadata), y el cuarto (Voltage) para obtener y almacenar un perfil de
                 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
                 Example:
                     dpath = "/home/myuser/data"
                     startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
                     endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
                     readerObj = VoltageReader()
                     readerObj.setup(dpath, startTime, endTime)
                     while(True):
                         #to get one profile
                         profile =  readerObj.getData()
                         #print the profile
                         print profile
                         #If you want to see all datablock
                         print readerObj.datablock
                         if readerObj.flagNoMoreFiles:
                             break
                 """
                 ext = ".r"
                 optchar = "D"
                 dataOut = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageReader para la lectura de datos de voltage.
                     Input:
                         dataOut    :    Objeto de la clase Voltage. Este objeto sera utilizado para
                                           almacenar un perfil de datos cada vez que se haga un requerimiento
                                           (getData). El perfil sera obtenido a partir del buffer de datos,
                                           si el buffer esta vacio se hara un nuevo proceso de lectura de un
                                           bloque de datos.
                                           Si este parametro no es pasado se creara uno internamente.
                     Variables afectadas:
                         self.dataOut
                     Return:
                         None
                     """
                     ProcessingUnit.__init__(self)
                     self.isConfig = False
                     self.datablock = None
                     self.utc = 0
                     self.ext = ".r"
                     self.optchar = "D"
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                     self.online = 0
                     self.fp = None
                     self.idFile = None
                     self.dtype = None
                     self.fileSizeByHeader = None
                     self.filenameList = []
                     self.filename = None
                     self.fileSize = None
                     self.firstHeaderSize = 0
                     self.basicHeaderSize = 24
                     self.pathList = []
                     self.filenameList = []
                     self.lastUTTime = 0
                     self.maxTimeStep = 30
                     self.flagNoMoreFiles = 0
                     self.set = 0
                     self.path = None
                     self.profileIndex = 2**32-1
                     self.delay  = 3   #seconds
                     self.nTries  = 3  #quantity tries
                     self.nFiles = 3   #number of files for searching
                     self.nReadBlocks = 0
                     self.flagIsNewFile = 1
                     self.__isFirstTimeOnline = 1
             #         self.ippSeconds = 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     self.nTotalBlocks = 0
                     self.blocksize = 0
                     self.dataOut = self.createObjByDefault()
                     self.nTxs = 1
                     self.txIndex = 0
                 def createObjByDefault(self):
                     dataObj = Voltage()
                     return dataObj
                 def __hasNotDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def getBlockDimension(self):
                     """
                     Obtiene la cantidad de puntos a leer por cada bloque de datos
                     Affected:
                         self.blocksize
                     Return:
                         None
                     """
                     pts2read = self.processingHeaderObj.profilesPerBlock * self.processingHeaderObj.nHeights * self.systemHeaderObj.nChannels
                     self.blocksize = pts2read
                 def readBlock(self):
                     """
                     readBlock lee el bloque de datos desde la posicion actual del puntero del archivo
                     (self.fp) y actualiza todos los parametros relacionados al bloque de datos
                     (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
                     es seteado a 0
                     Inputs:
                         None
                     Return:
                         None
                     Affected:
                         self.profileIndex
                         self.datablock
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                     Exceptions:
                         Si un bloque leido no es un bloque valido
                     """
                     current_pointer_location = self.fp.tell()
                     junk = numpy.fromfile( self.fp, self.dtype, self.blocksize )
                     try:
                         junk = junk.reshape( (self.processingHeaderObj.profilesPerBlock, self.processingHeaderObj.nHeights, self.systemHeaderObj.nChannels) )
                     except:
                         #print "The read block (%3d) has not enough data" %self.nReadBlocks
                         if self.waitDataBlock(pointer_location=current_pointer_location):
                             junk = numpy.fromfile( self.fp, self.dtype, self.blocksize )
                             junk = junk.reshape( (self.processingHeaderObj.profilesPerBlock, self.processingHeaderObj.nHeights, self.systemHeaderObj.nChannels) )
             #             return 0
                     junk = numpy.transpose(junk, (2,0,1))
                     self.datablock = junk['real'] + junk['imag']*1j
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def getFirstHeader(self):
                     self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
                     self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
                     if self.nTxs > 1:
                         self.dataOut.radarControllerHeaderObj.ippSeconds = self.radarControllerHeaderObj.ippSeconds/self.nTxs
             #         self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt
             #
             #         if self.radarControllerHeaderObj.code != None:
             #
             #             self.dataOut.nCode = self.radarControllerHeaderObj.nCode
             #
             #             self.dataOut.nBaud = self.radarControllerHeaderObj.nBaud
             #
             #             self.dataOut.code = self.radarControllerHeaderObj.code
                     self.dataOut.dtype = self.dtype
                     self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock*self.nTxs
                     if self.processingHeaderObj.nHeights % self.nTxs != 0:
                         raise ValueError, "nTxs (%d) should be a multiple of nHeights (%d)" %(self.nTxs, self.processingHeaderObj.nHeights)
                     xf = self.processingHeaderObj.firstHeight + int(self.processingHeaderObj.nHeights/self.nTxs)*self.processingHeaderObj.deltaHeight
                     self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
                     self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
                     self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.flagDecodeData = False #asumo q la data no esta decodificada
                     self.dataOut.flagDeflipData = False #asumo q la data no esta sin flip
                     self.dataOut.flagShiftFFT = False
                 def getData(self):
                     """
                     getData obtiene una unidad de datos del buffer de lectura, un perfil,  y la copia al objeto self.dataOut
                     del tipo "Voltage" con todos los parametros asociados a este (metadata). cuando no hay datos
                     en el buffer de lectura es necesario hacer una nueva lectura de los bloques de datos usando
                     "readNextBlock"
                     Ademas incrementa el contador del buffer "self.profileIndex" en 1.
                     Return:
                         Si el flag self.getByBlock ha sido seteado el bloque completo es copiado a self.dataOut y el self.profileIndex
                         es igual al total de perfiles leidos desde el archivo.
                         Si self.getByBlock == False:
                             self.dataOut.data = buffer[:, thisProfile, :]
                             shape = [nChannels, nHeis]
                         Si self.getByBlock == True:
                             self.dataOut.data = buffer[:, :, :]
                             shape = [nChannels, nProfiles, nHeis]
                     Variables afectadas:
                         self.dataOut
                         self.profileIndex
                     Affected:
                         self.dataOut
                         self.profileIndex
                         self.flagDiscontinuousBlock
                         self.flagIsNewBlock
                     """
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     if self.__hasNotDataInBuffer():
                         if not( self.readNextBlock() ):
                             return 0
                         self.getFirstHeader()
                     if self.datablock == None:
                         self.dataOut.flagNoData = True
                         return 0
                     if not self.getByBlock:
                         """
                         Return profile by profile
                         If nTxs > 1 then one profile is divided by nTxs and number of total
                         blocks is increased by nTxs (nProfiles *= nTxs)
                         """
+                        self.dataOut.flagDataAsBlock = False
                         if self.nTxs == 1:
-                            self.dataOut.flagDataAsBlock = False
                             self.dataOut.data = self.datablock[:,self.profileIndex,:]
                             self.dataOut.profileIndex = self.profileIndex
                             self.profileIndex += 1
                         else:
-                            self.dataOut.flagDataAsBlock = False
                             iniHei_ForThisTx = (self.txIndex)*int(self.processingHeaderObj.nHeights/self.nTxs)
                             endHei_ForThisTx = (self.txIndex+1)*int(self.processingHeaderObj.nHeights/self.nTxs)
             #                 print iniHei_ForThisTx, endHei_ForThisTx
                             self.dataOut.data = self.datablock[:, self.profileIndex, iniHei_ForThisTx:endHei_ForThisTx]
                             self.dataOut.profileIndex = self.profileIndex*self.nTxs + self.txIndex
                             self.txIndex += 1
                             if self.txIndex == self.nTxs:
                                 self.txIndex = 0
                                 self.profileIndex += 1
                     else:
                         """
                         Return all block
                         """
                         self.dataOut.flagDataAsBlock = True
                         self.dataOut.data = self.datablock
-                        self.dataOut.profileIndex = self.processingHeaderObj.profilesPerBlock - 1
+                        self.dataOut.profileIndex = self.processingHeaderObj.profilesPerBlock
-                        self.profileIndex = self.processingHeaderObj.profilesPerBlock - 1
+                        self.profileIndex = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.flagNoData = False
                     self.getBasicHeader()
                     self.dataOut.realtime = self.online
                     return self.dataOut.data
             class VoltageWriter(JRODataWriter, Operation):
                 """
                 Esta clase permite escribir datos de voltajes a archivos procesados (.r). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 ext = ".r"
                 optchar = "D"
                 shapeBuffer = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageWriter para la escritura de datos de espectros.
                     Affected:
                         self.dataOut
                     Return: None
                     """
                     Operation.__init__(self)
                     self.nTotalBlocks = 0
                     self.profileIndex = 0
                     self.isConfig = False
                     self.fp = None
                     self.flagIsNewFile = 1
                     self.nTotalBlocks = 0
                     self.flagIsNewBlock = 0
                     self.setFile = None
                     self.dtype = None
                     self.path = None
                     self.filename = None
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                 def hasAllDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def setBlockDimension(self):
                     """
                     Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
                     Affected:
                         self.shape_spc_Buffer
                         self.shape_cspc_Buffer
                         self.shape_dc_Buffer
                     Return: None
                     """
                     self.shapeBuffer = (self.processingHeaderObj.profilesPerBlock,
                                         self.processingHeaderObj.nHeights,
                                         self.systemHeaderObj.nChannels)
                     self.datablock = numpy.zeros((self.systemHeaderObj.nChannels,
                                                  self.processingHeaderObj.profilesPerBlock,
                                                  self.processingHeaderObj.nHeights),
                                                  dtype=numpy.dtype('complex64'))
                 def writeBlock(self):
                     """
                     Escribe el buffer en el file designado
                     Affected:
                         self.profileIndex
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.blockIndex
                     Return: None
                     """
                     data = numpy.zeros( self.shapeBuffer, self.dtype )
                     junk = numpy.transpose(self.datablock, (1,2,0))
                     data['real'] = junk.real
                     data['imag'] = junk.imag
                     data = data.reshape( (-1) )
                     data.tofile( self.fp )
                     self.datablock.fill(0)
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.blockIndex += 1
                     self.nTotalBlocks += 1
             #         print "[Writing] Block = %04d" %self.blockIndex
                 def putData(self):
                     """
                     Setea un bloque de datos y luego los escribe en un file
                     Affected:
                         self.flagIsNewBlock
                         self.profileIndex
                     Return:
 :    Si no hay data o no hay mas files que puedan escribirse
 :    Si se escribio la data de un bloque en un file
                     """
                     if self.dataOut.flagNoData:
                         return 0
                     self.flagIsNewBlock = 0
                     if self.dataOut.flagDiscontinuousBlock:
                         self.datablock.fill(0)
                         self.profileIndex = 0
                         self.setNextFile()
                     if self.profileIndex == 0:
                         self.setBasicHeader()
                     self.datablock[:,self.profileIndex,:] = self.dataOut.data
                     self.profileIndex += 1
                     if self.hasAllDataInBuffer():
                         #if self.flagIsNewFile:
                         self.writeNextBlock()
             #            self.setFirstHeader()
                     return 1
                 def __getProcessFlags(self):
                     processFlags = 0
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList =  [PROCFLAG.DATATYPE_CHAR,
                                        PROCFLAG.DATATYPE_SHORT,
                                        PROCFLAG.DATATYPE_LONG,
                                        PROCFLAG.DATATYPE_INT64,
                                        PROCFLAG.DATATYPE_FLOAT,
                                        PROCFLAG.DATATYPE_DOUBLE]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             dtypeValue = datatypeValueList[index]
                             break
                     processFlags += dtypeValue
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
                     if self.dataOut.code != None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nCohInt > 1:
                         processFlags += PROCFLAG.COHERENT_INTEGRATION
                     return processFlags
                 def __getBlockSize(self):
                     '''
                     Este metodos determina el cantidad de bytes para un bloque de datos de tipo Voltage
                     '''
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList = [1,2,4,8,4,8]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             datatypeValue = datatypeValueList[index]
                             break
                     blocksize = int(self.dataOut.nHeights * self.dataOut.nChannels * self.profilesPerBlock * datatypeValue * 2)
                     return blocksize
                 def setFirstHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.dtype
                     Return:
                         None
                     """
                     self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
                     self.systemHeaderObj.nChannels = self.dataOut.nChannels
                     self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
                     self.setBasicHeader()
                     processingHeaderSize = 40 # bytes
                     self.processingHeaderObj.dtype = 0 # Voltage
                     self.processingHeaderObj.blockSize = self.__getBlockSize()
                     self.processingHeaderObj.profilesPerBlock = self.profilesPerBlock
                     self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
                     self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
                     self.processingHeaderObj.processFlags = self.__getProcessFlags()
                     self.processingHeaderObj.nCohInt = self.dataOut.nCohInt
                     self.processingHeaderObj.nIncohInt = 1 # Cuando la data de origen es de tipo Voltage
                     self.processingHeaderObj.totalSpectra = 0 # Cuando la data de origen es de tipo Voltage
             #         if self.dataOut.code != None:
             #             self.processingHeaderObj.code = self.dataOut.code
             #             self.processingHeaderObj.nCode = self.dataOut.nCode
             #             self.processingHeaderObj.nBaud = self.dataOut.nBaud
             #             codesize = int(8 + 4 * self.dataOut.nCode * self.dataOut.nBaud)
             #             processingHeaderSize += codesize
                     if self.processingHeaderObj.nWindows != 0:
                         self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
                         self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                         self.processingHeaderObj.nHeights = self.dataOut.nHeights
                         self.processingHeaderObj.samplesWin = self.dataOut.nHeights
                         processingHeaderSize += 12
                     self.processingHeaderObj.size = processingHeaderSize

schainpy/model/proc/jroproc_voltage.py +1 -1

             import numpy
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import Voltage
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
             #         self.objectDict = {}
                     self.dataOut = Voltage()
                     self.flip = 1
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.__updateObjFromAmisrInput()
                     if self.dataIn.type == 'Voltage':
                         self.dataOut.copy(self.dataIn)
             #         self.dataOut.copy(self.dataIn)
                 def __updateObjFromAmisrInput(self):
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.dstFlag = self.dataIn.dstFlag
                     self.dataOut.errorCount = self.dataIn.errorCount
                     self.dataOut.useLocalTime = self.dataIn.useLocalTime
                     self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.data = self.dataIn.data
                     self.dataOut.utctime = self.dataIn.utctime
                     self.dataOut.channelList = self.dataIn.channelList
             #         self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.nProfiles = self.dataIn.nProfiles
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.azimuth = self.dataIn.azimuth
                     self.dataOut.zenith = self.dataIn.zenith
                     self.dataOut.beam.codeList = self.dataIn.beam.codeList
                     self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
                     self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
             #
             #        pass#
             #
             #    def init(self):
             #
             #
             #        if self.dataIn.type == 'AMISR':
             #            self.__updateObjFromAmisrInput()
             #
             #        if self.dataIn.type == 'Voltage':
             #            self.dataOut.copy(self.dataIn)
             #        # No necesita copiar en cada init() los atributos de dataIn
             #        # la copia deberia hacerse por cada nuevo bloque de datos
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError, "Channel %d is not in %s" %(channel, str(self.dataOut.channelList))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                 def selectChannelsByIndex(self, channelIndexList):
                     """
                     Selecciona un bloque de datos en base a canales segun el channelIndexList
                     Input:
                         channelIndexList    :    lista sencilla de canales a seleccionar por ej. [2,3,7]
                     Affected:
                         self.dataOut.data
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                         self.dataOut.m_ProcessingHeader.totalSpectra
                         self.dataOut.systemHeaderObj.numChannels
                         self.dataOut.m_ProcessingHeader.blockSize
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             print channelIndexList
                             raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
             #         nChannels = len(channelIndexList)
                     if self.dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         data = self.dataOut.data[channelIndexList,:,:]
                     else:
                         data = self.dataOut.data[channelIndexList,:]
                     self.dataOut.data = data
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
             #        self.dataOut.nChannels = nChannels
                     return 1
                 def selectHeights(self, minHei=None, maxHei=None):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if minHei == None:
                         minHei = self.dataOut.heightList[0]
                     if maxHei == None:
                         maxHei = self.dataOut.heightList[-1]
                     if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     minIndex = 0
                     maxIndex = 0
                     heights = self.dataOut.heightList
                     inda = numpy.where(heights >= minHei)
                     indb = numpy.where(heights <= maxHei)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return 1
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
             #         nHeights = maxIndex - minIndex + 1
                     #voltage
                     if self.dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         data = self.dataOut.data[:,minIndex:maxIndex,:]
                     else:
                         data = self.dataOut.data[:,minIndex:maxIndex]
             #         firstHeight = self.dataOut.heightList[minIndex]
                     self.dataOut.data = data
                     self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex]
                     if self.dataOut.nHeights <= 1:
                         raise ValueError, "selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)
                     return 1
                 def filterByHeights(self, window):
                     deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     if window == None:
                         window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
                     newdelta = deltaHeight * window
                     r = self.dataOut.nHeights % window
                     newheights = (self.dataOut.nHeights-r)/window
                     if newheights <= 1:
                         raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window)
                     if self.dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r]
                         buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r]
                         buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window)
                         buffer = numpy.sum(buffer,2)
                     self.dataOut.data = buffer
                     self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta
                     self.dataOut.windowOfFilter = window
                 def setH0(self, h0, deltaHeight = None):
                     if not deltaHeight:
                         deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     nHeights = self.dataOut.nHeights
                     newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight
                     self.dataOut.heightList = newHeiRange
                 def deFlip(self, channelList = []):
                     data = self.dataOut.data.copy()
                     if self.dataOut.flagDataAsBlock:
                         flip = self.flip
                         profileList = range(self.dataOut.nProfiles)
                         if not channelList:
                             for thisProfile in profileList:
                                 data[:,thisProfile,:] = data[:,thisProfile,:]*flip
                                 flip *= -1.0
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in self.dataOut.channelList:
                                     continue
                                 for thisProfile in profileList:
                                     data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip
                                     flip *= -1.0
                         self.flip = flip
                     else:
                         if not channelList:
                             data[:,:] = data[:,:]*self.flip
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in self.dataOut.channelList:
                                     continue
                                 data[thisChannel,:] = data[thisChannel,:]*self.flip
                         self.flip *= -1.
                     self.dataOut.data = data
                 def setRadarFrequency(self, frequency=None):
                     if frequency != None:
                         self.dataOut.frequency = frequency
                     return 1
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 n = None
                 def __init__(self):
                     Operation.__init__(self)
             #         self.isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=False, byblock=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n        :    Number of coherent integrations
                         timeInterval   :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping    :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = None
                     self.__dataReady = False
                     self.byblock = byblock
                     if n == None and timeInterval == None:
                         raise ValueError, "n or timeInterval should be specified ..."
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverapping = True
                         self.__buffer = None
                     else:
                         self.__withOverapping = False
                         self.__buffer = 0
                     self.__profIndex = 0
                 def putData(self, data):
                     """
                     Add a profile to the __buffer and increase in one the __profileIndex
                     """
                     if not self.__withOverapping:
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
                     data = numpy.reshape(data, (1, nChannels, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer == None:
                         self.__buffer = data
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer = numpy.vstack((self.__buffer, data))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
                     self.__buffer[self.n-1] = data
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     if not self.__withOverapping:
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
             #         n = None
                     self.putData(data)
                     if self.__profIndex == self.n:
                         avgdata, n = self.pushData()
                         self.__dataReady = True
                     return avgdata
                 def byTime(self, data, datatime):
                     self.__dataReady = False
                     avgdata = None
                     n = None
                     self.putData(data)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata
                 def integrate(self, data, datatime=None):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata = self.byTime(data, datatime)
                     else:
                         avgdata = self.byProfiles(data)
                     self.__lastdatatime = datatime
                     if avgdata == None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime -self.__lastdatatime
                     if not self.__withOverapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
                 def integrateByBlock(self, dataOut):
                     times = int(dataOut.data.shape[1]/self.n)
                     avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex)
                     id_min = 0
                     id_max = self.n
                     for i in range(times):
                         junk = dataOut.data[:,id_min:id_max,:]
                         avgdata[:,i,:] = junk.sum(axis=1)
                         id_min += self.n
                         id_max += self.n
                     timeInterval = dataOut.ippSeconds*self.n
                     avgdatatime = (times - 1) * timeInterval + dataOut.utctime
                     self.__dataReady = True
                     return avgdata, avgdatatime
                 def run(self, dataOut, **kwargs):
                     if not self.isConfig:
                         self.setup(**kwargs)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         avgdata, avgdatatime = self.integrateByBlock(dataOut)
                     else:
                         avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
             #             dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self):
                     Operation.__init__(self)
                     self.times = None
                     self.osamp = None
             #         self.__setValues = False
                     self.isConfig = False
                 def setup(self, code, osamp, dataOut):
                     self.__profIndex = 0
                     self.code = code
                     self.nCode = len(code)
                     self.nBaud = len(code[0])
                     if (osamp != None) and (osamp >1):
                         self.osamp = osamp
                         self.code = numpy.repeat(code, repeats=self.osamp, axis=1)
                         self.nBaud = self.nBaud*self.osamp
                     self.__nChannels = dataOut.nChannels
                     self.__nProfiles = dataOut.nProfiles
                     self.__nHeis = dataOut.nHeights
                     if dataOut.flagDataAsBlock:
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex)
                     else:
                         __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
                         __codeBuffer[:,0:self.nBaud] = self.code
                         self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
                 def convolutionInFreq(self, data):
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=1)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=1)
                     datadec = data#[:,:]
                     return datadec
                 def convolutionInFreqOpt(self, data):
                     raise NotImplementedError
             #         fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
             #
             #         data = cfunctions.decoder(fft_code, data)
             #
             #         datadec = data#[:,:]
             #
             #         return datadec
                 def convolutionInTime(self, data):
                     code = self.code[self.__profIndex]
                     for i in range(self.__nChannels):
                         self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='same')
                     return self.datadecTime
                 def convolutionByBlockInTime(self, data):
                     repetitions = self.__nProfiles / self.nCode
                     junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize))
                     junk = junk.flatten()
                     code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud))
                     for i in range(self.__nChannels):
                         for j in range(self.__nProfiles):
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='same')
                     return self.datadecTime
-                def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None):
+                def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None):
                     if not self.isConfig:
                         if code == None:
                             code = dataOut.code
                         else:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         self.setup(code, osamp, dataOut)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Decoding when data have been read as block,
                         """
                         datadec = self.convolutionByBlockInTime(dataOut.data)
                     else:
                         """
                         Decoding when data have been read profile by profile
                         """
                         if mode == 0:
                             datadec = self.convolutionInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.convolutionInFreq(dataOut.data)
                         if mode == 2:
                             datadec = self.convolutionInFreqOpt(dataOut.data)
                     dataOut.code = self.code
                     dataOut.nCode = self.nCode
                     dataOut.nBaud = self.nBaud
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:self.ndatadec]
                     dataOut.flagDecodeData = True #asumo q la data esta decodificada
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return 1
                     self.__profIndex += 1
                     return 1
             #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class ProfileConcat(Operation):
                 isConfig = False
                 buffer = None
                 def __init__(self):
                     Operation.__init__(self)
                     self.profileIndex = 0
                 def reset(self):
                     self.buffer = numpy.zeros_like(self.buffer)
                     self.start_index = 0
                     self.times = 1
                 def setup(self, data, m, n=1):
                     self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
                     self.nHeights = data.nHeights
                     self.start_index = 0
                     self.times = 1
                 def concat(self, data):
                     self.buffer[:,self.start_index:self.profiles*self.times] = data.copy()
                     self.start_index = self.start_index + self.nHeights
                 def run(self, dataOut, m):
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(dataOut.data, m, 1)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False"
                     else:
                         self.concat(dataOut.data)
                         self.times += 1
                         if self.times > m:
                             dataOut.data = self.buffer
                             self.reset()
                             dataOut.flagNoData = False
                             # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
                             deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                             xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m
                             dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
                             dataOut.ippSeconds *= m
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self):
                     Operation.__init__(self)
                     self.profileIndex = 0
                 def incIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isThisProfileInRange(self, profileIndex, minIndex, maxIndex):
                     if profileIndex < minIndex:
                         return False
                     if profileIndex > maxIndex:
                         return False
                     return True
                 def isThisProfileInList(self, profileIndex, profileList):
                     if profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None):
                     """
                     ProfileSelector:
                     Inputs:
                         profileList        :    Index of profiles selected. Example: profileList = (0,1,2,7,8)
                         profileRangeList    :    Minimum and maximum profile indexes. Example: profileRangeList = (4, 30)
                         rangeList            :    List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256))
                     """
                     dataOut.flagNoData = True
                     if nProfiles:
                         self.nProfiles = dataOut.nProfiles
                     else:
                         self.nProfiles = nProfiles
                     if dataOut.flagDataAsBlock:
                         """
                         data dimension  = [nChannels, nProfiles, nHeis]
                         """
                         if profileList != None:
                             dataOut.data = dataOut.data[:,profileList,:]
                             dataOut.nProfiles = len(profileList)
                             dataOut.profileIndex = dataOut.nProfiles - 1
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:]
                             dataOut.nProfiles = maxIndex - minIndex + 1
                             dataOut.profileIndex = dataOut.nProfiles - 1
                         if rangeList != None:
                             raise ValueError, "Profile Selector: Not implemented for rangeList yet"
                         dataOut.flagNoData = False
                         return True
                     else:
                         """
                         data dimension  = [nChannels, nHeis]
                         """
                         if profileList != None:
                             dataOut.nProfiles = len(profileList)
                             if self.isThisProfileInList(dataOut.profileIndex, profileList):
                                 dataOut.flagNoData = False
                                 dataOut.profileIndex = self.profileIndex
                                 self.incIndex()
                             return True
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             dataOut.nProfiles = maxIndex - minIndex + 1
                             if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                                 dataOut.flagNoData = False
                                 dataOut.profileIndex = self.profileIndex
                                 self.incIndex()
                             return True
                         if rangeList != None:
                             nProfiles = 0
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 nProfiles += maxIndex - minIndex + 1
                             dataOut.nProfiles = nProfiles
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
             #                         print "profileIndex = ", dataOut.profileIndex
                                     dataOut.flagNoData = False
                                     dataOut.profileIndex = self.profileIndex
                                     self.incIndex()
                                     break
                             return True
                         if beam != None: #beam is only for AMISR data
                             if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]):
                                 dataOut.flagNoData = False
                                 dataOut.profileIndex = self.profileIndex
                                 self.incIndex()
                             return 1
                     raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter"
                     return 0
             class Reshaper(Operation):
                 def __init__(self):
                     Operation.__init__(self)
                     self.updateNewHeights = True
                 def run(self, dataOut, shape):
                     if not dataOut.flagDataAsBlock:
                         raise ValueError, "Reshaper can only be used when voltage have been read as Block, getBlock = True"
                     if len(shape) != 3:
                         raise ValueError, "shape len should be equal to 3, (nChannels, nProfiles, nHeis)"
                     shape_tuple = tuple(shape)
                     dataOut.data = numpy.reshape(dataOut.data, shape_tuple)
                     dataOut.flagNoData = False
                     if self.updateNewHeights:
                         old_nheights = dataOut.nHeights
                         new_nheights = dataOut.data.shape[2]
                         factor = 1.0*new_nheights / old_nheights
                         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                         xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * factor
                         dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
                         dataOut.nProfiles = dataOut.data.shape[1]
                         dataOut.ippSeconds *= factor
             import collections
             from scipy.stats import mode
             class Synchronize(Operation):
                 isConfig = False
                 __profIndex = 0
                 def __init__(self):
                     Operation.__init__(self)
             #         self.isConfig = False
                     self.__powBuffer = None
                     self.__startIndex = 0
                     self.__pulseFound = False
                 def __findTxPulse(self, dataOut, channel=0, pulse_with = None):
                     #Read data
                     powerdB = dataOut.getPower(channel = channel)
                     noisedB = dataOut.getNoise(channel = channel)[0]
                     self.__powBuffer.extend(powerdB.flatten())
                     dataArray = numpy.array(self.__powBuffer)
                     filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same")
                     maxValue = numpy.nanmax(filteredPower)
                     if maxValue < noisedB + 10:
                         #No se encuentra ningun pulso de transmision
                         return None
                     maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0]
                     if len(maxValuesIndex) < 2:
                         #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX
                         return None
                     phasedMaxValuesIndex = maxValuesIndex - self.__nSamples
                     #Seleccionar solo valores con un espaciamiento de nSamples
                     pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex)
                     if len(pulseIndex) < 2:
                         #Solo se encontro un pulso de transmision con ancho mayor a 1
                         return None
                     spacing = pulseIndex[1:] - pulseIndex[:-1]
                     #remover senales que se distancien menos de 10 unidades o muestras
                     #(No deberian existir IPP menor a 10 unidades)
                     realIndex = numpy.where(spacing > 10 )[0]
                     if len(realIndex) < 2:
                         #Solo se encontro un pulso de transmision con ancho mayor a 1
                         return None
                     #Eliminar pulsos anchos (deja solo la diferencia entre IPPs)
                     realPulseIndex = pulseIndex[realIndex]
                     period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0]
                     print "IPP = %d samples" %period
                     self.__newNSamples = dataOut.nHeights #int(period)
                     self.__startIndex = int(realPulseIndex[0])
                     return 1
                 def setup(self, nSamples, nChannels, buffer_size = 4):
                     self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float),
                                                       maxlen = buffer_size*nSamples)
                     bufferList = []
                     for i in range(nChannels):
                         bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) +  numpy.NAN,
                                                       maxlen = buffer_size*nSamples)
                         bufferList.append(bufferByChannel)
                     self.__nSamples = nSamples
                     self.__nChannels = nChannels
                     self.__bufferList = bufferList
                 def run(self, dataOut, channel = 0):
                     if not self.isConfig:
                         nSamples = dataOut.nHeights
                         nChannels = dataOut.nChannels
                         self.setup(nSamples, nChannels)
                         self.isConfig = True
                     #Append new data to internal buffer
                     for thisChannel in range(self.__nChannels):
                         bufferByChannel = self.__bufferList[thisChannel]
                         bufferByChannel.extend(dataOut.data[thisChannel])
                     if self.__pulseFound:
                         self.__startIndex -= self.__nSamples
                     #Finding Tx Pulse
                     if not self.__pulseFound:
                         indexFound = self.__findTxPulse(dataOut, channel)
                         if indexFound == None:
                             dataOut.flagNoData = True
                             return
                         self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex)
                         self.__pulseFound = True
                         self.__startIndex = indexFound
                     #If pulse was found ...
                     for thisChannel in range(self.__nChannels):
                         bufferByChannel = self.__bufferList[thisChannel]
                         #print self.__startIndex
                         x = numpy.array(bufferByChannel)
                         self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples]
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight
             #             dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6
                     dataOut.data = self.__arrayBuffer
                     self.__startIndex += self.__newNSamples
                     return

schainpy/scripts/test_mst_blocks.py +1 -1

             import os, sys
             #import timeit
             import datetime
             path = os.path.split(os.getcwd())[0]
             path = os.path.split(path)[0]
-            sys.path.append(path)
+            sys.path.insert(0, path)
             from schainpy.controller import Project
             desc = "MST-ISR-EEJ Experiment Test"
             filename = "mst_blocks.xml"
             controllerObj = Project()
             controllerObj.setup(id = '191', name='test01', description=desc)
             #path = '/home/operaciones/mst_data/MST_ISR_EEJ/'
             path ='/home/operaciones/mst_data'
             figpath = '/home/operaciones/Pictures/mst_isr_eej/mst'
             readUnitConfObj = controllerObj.addReadUnit(datatype='VoltageReader',
                                                         path=path,
                                                         startDate='2014/05/01',
                                                         endDate='2014/05/30',
                                                         startTime='00:00:00',
                                                         endTime='23:59:59',
                                                         online=1,
                                                         delay=10,
                                                         walk=1,
                                                         getblock=1)
             opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
             procUnitConfObjMST = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
             opObj11 = procUnitConfObjMST.addOperation(name='ProfileSelector', optype='other')
             profileIndex =  '0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119'
             #profileIndex =  '0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19'
             opObj11.addParameter(name='profileList', value=profileIndex, format='intlist')
             opObj11.addParameter(name='byblock', value='1', format='bool')
             opObj11 = procUnitConfObjMST.addOperation(name='Decoder', optype='other')
             opObj11.addParameter(name='mode',value='3',format='int')
             opObj11.addParameter(name='times',value='10',format='int')
             opObj11 = procUnitConfObjMST.addOperation(name='CohInt', optype='other')
             opObj11.addParameter(name='n', value='20', format='int')
             opObj11.addParameter(name='byblock', value='1', format='bool')
             procUnitConfObjMSTSpectra = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjMST.getId())
             procUnitConfObjMSTSpectra.addParameter(name='nFFTPoints', value='64', format='int')
             procUnitConfObjMSTSpectra.addParameter(name='nProfiles', value='64', format='int')
             opObj11 = procUnitConfObjMSTSpectra.addOperation(name='IncohInt', optype='other')
             opObj11.addParameter(name='n', value='2', format='float')
             opObj11 = procUnitConfObjMSTSpectra.addOperation(name='SpectraPlot', optype='other')
             opObj11.addParameter(name='id', value='401', format='int')
             opObj11.addParameter(name='wintitle', value='MST', format='str')
             opObj11.addParameter(name='zmin', value='20', format='int')
             opObj11.addParameter(name='zmax', value='40', format='int')
             # # opObj11.addParameter(name='save', value='1', format='int')
             opObj11.addParameter(name='figpath', value=figpath, format='str')
             opObj11.addParameter(name='wr_period', value='5', format='int')
             # # opObj11.addParameter(name='ftp', value='1', format='int')
             # # opObj11.addParameter(name='server', value='jro-app.igp.gob.pe', format='str')
             # # opObj11.addParameter(name='folder', value='/home/wmaster/graficos', format='str')
             # # opObj11.addParameter(name='username', value='wmaster', format='str')
             # # opObj11.addParameter(name='password', value='mst2010vhf', format='str')
             # # opObj11.addParameter(name='ftp_wei', value='0', format='int')
             opObj11.addParameter(name='exp_code', value='19', format='int')
             # # opObj11.addParameter(name='sub_exp_code', value='0', format='int')
             # # opObj11.addParameter(name='plot_pos', value='0', format='int')
             # #
             opObj11 = procUnitConfObjMSTSpectra.addOperation(name='RTIPlot', optype='other')
             opObj11.addParameter(name='id', value='402', format='int')
             opObj11.addParameter(name='wintitle', value='MST', format='str')
             opObj11.addParameter(name='showprofile', value='0', format='int')
             opObj11.addParameter(name='xmin', value='0', format='int')
             opObj11.addParameter(name='xmax', value='24', format='int')
             opObj11.addParameter(name='zmin', value='20', format='int')
             opObj11.addParameter(name='zmax', value='40', format='int')
             # # opObj11.addParameter(name='save', value='1', format='int')
             opObj11.addParameter(name='figpath', value=figpath, format='str')
             opObj11.addParameter(name='wr_period', value='2', format='int')
             # # opObj11.addParameter(name='ftp', value='1', format='int')
             # # opObj11.addParameter(name='server', value='jro-app.igp.gob.pe', format='str')
             # # opObj11.addParameter(name='folder', value='/home/wmaster/graficos', format='str')
             # # opObj11.addParameter(name='username', value='wmaster', format='str')
             # # opObj11.addParameter(name='password', value='mst2010vhf', format='str')
             # # opObj11.addParameter(name='ftp_wei', value='0', format='int')
             opObj11.addParameter(name='exp_code', value='19', format='int')
             # # opObj11.addParameter(name='sub_exp_code', value='0', format='int')
             # # opObj11.addParameter(name='plot_pos', value='0', format='int')
             opObj11 = procUnitConfObjMSTSpectra.addOperation(name='SendByFTP', optype='other')
             opObj11.addParameter(name='ext', value='*.png', format='str')
             opObj11.addParameter(name='localfolder', value=figpath, format='str')
             opObj11.addParameter(name='remotefolder', value='/home/wmaster/graficos', format='str')
             opObj11.addParameter(name='server', value='10.10.120.125', format='str')
             opObj11.addParameter(name='username', value='wmaster', format='str')
             opObj11.addParameter(name='password', value='mst2010vhf', format='str')
             opObj11.addParameter(name='period', value='2', format='int')
             print "Escribiendo el archivo XML"
             controllerObj.writeXml(filename)
             print "Leyendo el archivo XML"
             controllerObj.readXml(filename)
             controllerObj.createObjects()
             controllerObj.connectObjects()
             #timeit.timeit('controllerObj.run()', number=2)
             controllerObj.run()
             #print fib(5)

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