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Update de WR-Project

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schainpy/model/data/jrodata.py +12 -12

             '''
             $Author: murco $
             $Id: JROData.py 173 2012-11-20 15:06:21Z murco $
             '''
             import copy
             import numpy
             import datetime
             import json
             from schainpy.utils import log
             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:
                     mean    :    noise's level
                 """
                 sortdata = numpy.sort(data, axis=None)
                 lenOfData = len(sortdata)
                 nums_min = lenOfData*0.2
                 if nums_min <= 5:
                     nums_min = 5
                 sump = 0.
                 sumq = 0.
                 j = 0
                 cont = 1
                 while((cont == 1)and(j < lenOfData)):
                     sump += sortdata[j]
                     sumq += sortdata[j]**2
                     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
                 return lnoise
             class Beam:
                 def __init__(self):
                     self.codeList = []
                     self.azimuthList = []
                     self.zenithList = []
             class GenericData(object):
                 flagNoData = True
                 def copy(self, inputObj=None):
                     if inputObj == None:
                         return copy.deepcopy(self)
                     for key in list(inputObj.__dict__.keys()):
                         attribute = inputObj.__dict__[key]
                         # If this attribute is a tuple or list
                         if type(inputObj.__dict__[key]) in (tuple, list):
                             self.__dict__[key] = attribute[:]
                             continue
                         # If this attribute is another object or instance
                         if hasattr(attribute, '__dict__'):
                             self.__dict__[key] = attribute.copy()
                             continue
                         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
                 error = None
                 data = None
                 nmodes = None
                 def __str__(self):
                     return '{} - {}'.format(self.type, self.getDatatime())
                 def getNoise(self):
                     raise NotImplementedError
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return list(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 getDeltaH(self):
                     delta = self.heightList[1] - self.heightList[0]
                     return delta
                 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 + 1)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getFmaxTimeResponse(self):
                     period = (10**-6) * self.getDeltaH() / (0.15)
                     PRF = 1. / (period * self.nCohInt)
                     fmax = PRF
                     return fmax
                 def getFmax(self):
                     PRF = 1. / (self.ippSeconds * self.nCohInt)
                     fmax = PRF
                     return fmax
                 def getVmax(self):
                     _lambda = self.C / self.frequency
                     vmax = self.getFmax() * _lambda / 2
                     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
                 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 noise
                 def getPower(self, channel=None):
                     if channel != None:
                         data = self.data[channel]
                     else:
                         data = self.data
                     power = data * numpy.conjugate(data)
                     powerdB = 10 * numpy.log10(power.real)
                     powerdB = numpy.squeeze(powerdB)
                     return powerdB
                 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 spc es un numpy array de 2 dmensiones (canales, perfiles, alturas)
                 data_spc = None
                 # data cspc es un numpy array de 2 dmensiones (canales, pares, alturas)
                 data_cspc = None
                 # data dc es un numpy array de 2 dmensiones (canales, alturas)
                 data_dc = None
                 # data power
                 data_pwr = 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
                 plotting = "spectra"
                 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 is not None:
                         # this was estimated by getNoise Operation defined in jroproc_spectra.py
                         return self.noise_estimation
                     else:
                         noise = self.getNoisebyHildebrand(
                             xmin_index, xmax_index, ymin_index, ymax_index)
                         return noise
                 def getFreqRangeTimeResponse(self, extrapoints=0):
                     deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints * self.ippFactor)
                     freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getAcfRange(self, extrapoints=0):
                     deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
                     freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 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.)
                     if self.nmodes:
                         return velrange/self.nmodes
                     else:
                         return velrange
                 def getNPairs(self):
                     return len(self.pairsList)
                 def getPairsIndexList(self):
                     return list(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 is None:
                         return True
                     return False
                 def getFlagDc(self):
                     if self.data_dc is None:
                         return True
                     return False
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor
                     if self.nmodes:
                         return self.nmodes*timeInterval
                     else:
                         return timeInterval
                 def getPower(self):
                     factor = self.normFactor
                     z = self.data_spc / factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     return 10 * numpy.log10(avg)
                 def getCoherence(self, pairsList=None, phase=False):
                     z = []
                     if pairsList is None:
                         pairsIndexList = self.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in self.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" % (
                                     pair))
                             pairsIndexList.append(self.pairsList.index(pair))
                     for i in range(len(pairsIndexList)):
                         pair = self.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0)
                         powa = numpy.average(self.data_spc[pair[0], :, :], axis=0)
                         powb = numpy.average(self.data_spc[pair[1], :, :], axis=0)
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
                         if phase:
                             data = numpy.arctan2(avgcoherenceComplex.imag,
                                                  avgcoherenceComplex.real) * 180 / numpy.pi
                         else:
                             data = numpy.abs(avgcoherenceComplex)
                         z.append(data)
                     return numpy.array(z)
                 def setValue(self, value):
                     print("This property should not be initialized")
                     return
                 nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.")
                 pairsIndexList = property(
                     getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.")
                 normFactor = property(getNormFactor, setValue,
                                       "I'm the 'getNormFactor' property.")
                 flag_cspc = property(getFlagCspc, setValue)
                 flag_dc = property(getFlagDc, setValue)
                 noise = property(getNoise, setValue, "I'm the 'nHeights' property.")
                 timeInterval = property(getTimeInterval, setValue,
                                         "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 getNHeights(self):
                     return len(self.heightList)
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return list(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
                 def get_ippSeconds(self):
                     '''
                     '''
                     return self.ipp_sec
                 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.")
                 ltctime = property(getltctime, "I'm the 'ltctime' property")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
                 ippSeconds = property(get_ippSeconds, '')
             class Correlation(JROData):
                 noise = None
                 SNR = None
                 #--------------------------------------------------
                 mode = None
                 split = False
                 data_cf = None
                 lags = None
                 lagRange = None
                 pairsList = None
                 normFactor = None
                 #--------------------------------------------------
             #     calculateVelocity = None
                 nLags = None
                 nPairs = None
                 nAvg = 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 getPairsList(self):
                     return self.pairsList
                 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[list(range(0, 1))] = ind_vel[list(
                             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(list(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.nProfiles
                     return timeInterval
                 def splitFunctions(self):
                     pairsList = self.pairsList
                     ccf_pairs = []
                     acf_pairs = []
                     ccf_ind = []
                     acf_ind = []
                     for l in range(len(pairsList)):
                         chan0 = pairsList[l][0]
                         chan1 = pairsList[l][1]
                         # Obteniendo pares de Autocorrelacion
                         if chan0 == chan1:
                             acf_pairs.append(chan0)
                             acf_ind.append(l)
                         else:
                             ccf_pairs.append(pairsList[l])
                             ccf_ind.append(l)
                     data_acf = self.data_cf[acf_ind]
                     data_ccf = self.data_cf[ccf_ind]
                     return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf
                 def getNormFactor(self):
                     acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions()
                     acf_pairs = numpy.array(acf_pairs)
                     normFactor = numpy.zeros((self.nPairs, self.nHeights))
                     for p in range(self.nPairs):
                         pair = self.pairsList[p]
                         ch0 = pair[0]
                         ch1 = pair[1]
                         ch0_max = numpy.max(data_acf[acf_pairs == ch0, :, :], axis=1)
                         ch1_max = numpy.max(data_acf[acf_pairs == ch1, :, :], axis=1)
                         normFactor[p, :] = numpy.sqrt(ch0_max * ch1_max)
                     return normFactor
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
                 normFactor = property(getNormFactor, "I'm the 'normFactor property'")
             class Parameters(Spectra):
                 experimentInfo = None  # Information about the experiment
                 # 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
                 abscissaList = None  # Abscissa, can be velocities, lags or time
             #    noise = None            #Noise Potency
                 utctimeInit = None  # Initial UTC time
                 paramInterval = None  # Time interval to calculate Parameters in seconds
                 useLocalTime = True
                 # 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
                 nAvg = None
                 noise_estimation = None
                 GauSPC = None  # Fit gaussian SPC
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Parameters"
                 def getTimeRange1(self, interval):
                     datatime = []
                     if self.useLocalTime:
                         time1 = self.utctimeInit - self.timeZone * 60
                     else:
                         time1 = self.utctimeInit
                     datatime.append(time1)
                     datatime.append(time1 + interval)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getTimeInterval(self):
                     if hasattr(self, 'timeInterval1'):
                         return self.timeInterval1
                     else:
                         return self.paramInterval
                 def setValue(self, value):
                     print("This property should not be initialized")
                     return
                 def getNoise(self):
                     return self.spc_noise
                 timeInterval = property(getTimeInterval)
                 noise = property(getNoise, setValue, "I'm the 'Noise' property.")
             class PlotterData(object):
                 '''
                 Object to hold data to be plotted
                 '''
                 MAXNUMX = 100
                 MAXNUMY = 100
                 def __init__(self, code, throttle_value, exp_code, buffering=True, snr=False):
                     self.key = code
                     self.throttle = throttle_value
                     self.exp_code = exp_code
                     self.buffering = buffering
                     self.ready = False
                     self.localtime = False
                     self.data = {}
                     self.meta = {}
                     self.__times = []
                     self.__heights = []
                     if 'snr' in code:
                         self.plottypes = ['snr']
                     elif code == 'spc':
                         self.plottypes = ['spc', 'noise', 'rti']
                     elif code == 'rti':
                         self.plottypes = ['noise', 'rti']
                     else:
                         self.plottypes = [code]
                     if 'snr' not in self.plottypes and snr:
                         self.plottypes.append('snr')
                     for plot in self.plottypes:
                         self.data[plot] = {}
                 def __str__(self):
                     dum = ['{}{}'.format(key, self.shape(key)) for key in self.data]
                     return 'Data[{}][{}]'.format(';'.join(dum), len(self.__times))
                 def __len__(self):
                     return len(self.__times)
                 def __getitem__(self, key):
                     if key not in self.data:
                         raise KeyError(log.error('Missing key: {}'.format(key)))
                     if 'spc' in key or not self.buffering:
                         ret = self.data[key]
                     elif 'scope' in key:
                         ret = numpy.array(self.data[key][float(self.tm)])
                     else:
                         ret = numpy.array([self.data[key][x] for x in self.times])
                         if ret.ndim > 1:
                             ret = numpy.swapaxes(ret, 0, 1)
                     return ret
                 def __contains__(self, key):
                     return key in self.data
                 def setup(self):
                     '''
                     Configure object
                     '''
                     self.type = ''
                     self.ready = False
                     self.data = {}
                     self.__times = []
                     self.__heights = []
                     self.__all_heights = set()
                     for plot in self.plottypes:
                         if 'snr' in plot:
                             plot = 'snr'
                         elif 'spc_moments' == plot:
                             plot = 'moments'
                         self.data[plot] = {}
                     if 'spc' in self.data or 'rti' in self.data or 'cspc' in self.data or 'moments' in self.data:
                         self.data['noise'] = {}
                         self.data['rti'] = {}
                         if 'noise' not in self.plottypes:
                             self.plottypes.append('noise')
                         if 'rti' not in self.plottypes:
                             self.plottypes.append('rti')
                 def shape(self, key):
                     '''
                     Get the shape of the one-element data for the given key
                     '''
                     if len(self.data[key]):
                         if 'spc' in key or not self.buffering:
                             return self.data[key].shape
                         return self.data[key][self.__times[0]].shape
                     return (0,)
                 def update(self, dataOut, tm):
                     '''
                     Update data object with new dataOut
                     '''
                     if tm in self.__times:
                         return
                     self.profileIndex = dataOut.profileIndex
                     self.tm = tm
                     self.type = dataOut.type
                     self.parameters = getattr(dataOut, 'parameters', [])
                     if hasattr(dataOut, 'meta'):
                         self.meta.update(dataOut.meta)
                     self.pairs = dataOut.pairsList
                     self.interval = dataOut.getTimeInterval()
                     self.localtime = dataOut.useLocalTime
                     if 'spc' in self.plottypes or 'cspc' in self.plottypes or 'spc_moments' in self.plottypes:
                         self.xrange = (dataOut.getFreqRange(1)/1000.,
                                        dataOut.getAcfRange(1), dataOut.getVelRange(1))
                         self.factor = dataOut.normFactor
                     self.__heights.append(dataOut.heightList)
                     self.__all_heights.update(dataOut.heightList)
                     self.__times.append(tm)
                     for plot in self.plottypes:
                         if plot in ('spc', 'spc_moments'):
                             z = dataOut.data_spc/dataOut.normFactor
                             buffer = 10*numpy.log10(z)
                         if plot == 'cspc':
                             z = dataOut.data_spc/dataOut.normFactor
                             buffer = (dataOut.data_spc, dataOut.data_cspc)
                         if plot == 'noise':
                             buffer = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
                         if plot == 'rti':
                             buffer = dataOut.getPower()
                         if plot == 'snr_db':
                             buffer = dataOut.data_SNR
                         if plot == 'snr':
                             buffer = 10*numpy.log10(dataOut.data_SNR)
                         if plot == 'dop':
                             buffer = dataOut.data_DOP
                         if plot == 'pow':
                             buffer = 10*numpy.log10(dataOut.data_POW)
                         if plot == 'width':
                             buffer = dataOut.data_WIDTH
                         if plot == 'coh':
                             buffer = dataOut.getCoherence()
                         if plot == 'phase':
                             buffer = dataOut.getCoherence(phase=True)
                         if plot == 'output':
                             buffer = dataOut.data_output
                         if plot == 'param':
                             buffer = dataOut.data_param
                         if plot == 'scope':
                             buffer = dataOut.data
                             self.flagDataAsBlock = dataOut.flagDataAsBlock
                             self.nProfiles = dataOut.nProfiles
                         if plot == 'spc':
                             self.data['spc'] = buffer
                         elif plot == 'cspc':
                             self.data['spc'] = buffer[0]
                             self.data['cspc'] = buffer[1]
                         elif plot == 'spc_moments':
                             self.data['spc'] = buffer
                             self.data['moments'][tm] = dataOut.moments
                         else:
                             if self.buffering:
                                 self.data[plot][tm] = buffer
                             else:
                                 self.data[plot] = buffer
                     if dataOut.channelList is None:
                         self.channels = range(buffer.shape[0])
                     else:
                         self.channels = dataOut.channelList
                 def normalize_heights(self):
                     '''
                     Ensure same-dimension of the data for different heighList
                     '''
                     H = numpy.array(list(self.__all_heights))
                     H.sort()
                     for key in self.data:
                         shape = self.shape(key)[:-1] + H.shape
                         for tm, obj in list(self.data[key].items()):
                             h = self.__heights[self.__times.index(tm)]
                             if H.size == h.size:
                                 continue
                             index = numpy.where(numpy.in1d(H, h))[0]
                             dummy = numpy.zeros(shape) + numpy.nan
                             if len(shape) == 2:
                                 dummy[:, index] = obj
                             else:
                                 dummy[index] = obj
                             self.data[key][tm] = dummy
                     self.__heights = [H for tm in self.__times]
                 def jsonify(self, plot_name, plot_type, decimate=False):
                     '''
                     Convert data to json
                     '''
                     tm = self.times[-1]
                     dy = int(self.heights.size/self.MAXNUMY) + 1
                     if self.key in ('spc', 'cspc') or not self.buffering:
                         dx = int(self.data[self.key].shape[1]/self.MAXNUMX) + 1
                         data = self.roundFloats(
                             self.data[self.key][::, ::dx, ::dy].tolist())
                     else:
                         data = self.roundFloats(self.data[self.key][tm].tolist())
                         if self.key is 'noise':
                             data = [[x] for x in data]
                     meta = {}
                     ret = {
                         'plot': plot_name,
                         'code': self.exp_code,
                         'time': float(tm),
                         'data': data,
                         }
                     meta['type'] = plot_type
                     meta['interval'] = float(self.interval)
                     meta['localtime'] = self.localtime
                     meta['yrange'] = self.roundFloats(self.heights[::dy].tolist())
                     if 'spc' in self.data or 'cspc' in self.data:
                         meta['xrange'] = self.roundFloats(self.xrange[2][::dx].tolist())
                     else:
                         meta['xrange'] = []
                     meta.update(self.meta)
                     ret['metadata'] = meta
                     return json.dumps(ret)
                 @property
                 def times(self):
                     '''
                     Return the list of times of the current data
                     '''
                     ret = numpy.array(self.__times)
                     ret.sort()
                     return ret
                 @property
                 def min_time(self):
                     '''
                     Return the minimun time value
                     '''
                     return self.times[0]
                 @property
                 def max_time(self):
                     '''
                     Return the maximun time value
                     '''
                     return self.times[-1]
                 @property
                 def heights(self):
                     '''
                     Return the list of heights of the current data
                     '''
                     return numpy.array(self.__heights[-1])
                 @staticmethod
                 def roundFloats(obj):
                     if isinstance(obj, list):
                         return list(map(PlotterData.roundFloats, obj))
                     elif isinstance(obj, float):
                         return round(obj, 2)

schainpy/model/graphics/jroplot_spectra.py +234 -14

             '''
             Created on Jul 9, 2014
             @author: roj-idl71
             '''
             import os
             import datetime
             import numpy
             from .figure import Figure, isRealtime, isTimeInHourRange
             from .plotting_codes import *
             from schainpy.model.proc.jroproc_base import MPDecorator
             from schainpy.utils import log
             @MPDecorator
             class SpectraPlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spc'
                 def __init__(self):
                     Figure.__init__(self)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 250
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = SPEC_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.__xfilter_ena = False
                     self.__yfilter_ena = False
                     self.indice=1
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 3
                         colspan = 2
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False,
                         xaxis="frequency", colormap='jet', normFactor=None):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return dataOut
                     if realtime:
                         if not(isRealtime(utcdatatime = dataOut.utctime)):
                             print('Skipping this plot function')
                             return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList" %channel)
                             channelIndexList.append(dataOut.channelList.index(channel))
                     if normFactor is None:
                         factor = dataOut.normFactor
                     else:
                         factor = normFactor
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     ylabel = "Range (km)"
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     zdB = 10*numpy.log10(z)
                     avg = numpy.average(z, axis=1)
                     avgdB = 10*numpy.log10(avg)
                     noise = dataOut.getNoise()/factor
                     noisedB = 10*numpy.log10(noise)
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Spectra"
                     if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                         title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         index = channelIndexList[i]
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime)
                         if len(dataOut.beam.codeList) != 0:
                             title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[index,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap,
                                     ticksize=9, cblabel='')
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[index,:], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                             noiseline = numpy.repeat(noisedB[index], len(y))
                             axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     if figfile == None:
                         str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         name = str_datetime
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
                         figfile = self.getFilename(name)
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
                     return dataOut
             @MPDecorator
+            class WpowerPlot_(Figure):
+                isConfig = None
+                __nsubplots = None
+                WIDTHPROF = None
+                HEIGHTPROF = None
+                PREFIX = 'wpo'
+                def __init__(self):
+                    Figure.__init__(self)
+                    self.isConfig = False
+                    self.__nsubplots = 1
+                    self.WIDTH = 250
+                    self.HEIGHT = 250
+                    self.WIDTHPROF = 120
+                    self.HEIGHTPROF = 0
+                    self.counter_imagwr = 0
+                    self.PLOT_CODE = WPO_CODE
+                    self.FTP_WEI = None
+                    self.EXP_CODE = None
+                    self.SUB_EXP_CODE = None
+                    self.PLOT_POS = None
+                    self.__xfilter_ena = False
+                    self.__yfilter_ena = False
+                    self.indice=1
+                def getSubplots(self):
+                    ncol = int(numpy.sqrt(self.nplots)+0.9)
+                    nrow = int(self.nplots*1./ncol + 0.9)
+                    return nrow, ncol
+                def setup(self, id, nplots, wintitle, showprofile=True, show=True):
+                    self.__showprofile = showprofile
+                    self.nplots = nplots
+                    ncolspan = 1
+                    colspan = 1
+                    if showprofile:
+                        ncolspan = 3
+                        colspan = 2
+                        self.__nsubplots = 2
+                    self.createFigure(id = id,
+                                      wintitle = wintitle,
+                                      widthplot = self.WIDTH + self.WIDTHPROF,
+                                      heightplot = self.HEIGHT + self.HEIGHTPROF,
+                                      show=show)
+                    nrow, ncol = self.getSubplots()
+                    counter = 0
+                    for y in range(nrow):
+                        for x in range(ncol):
+                            if counter >= self.nplots:
+                                break
+                            self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
+                            if showprofile:
+                                self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
+                            counter += 1
+                def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
+                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
+                        save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
+                        server=None, folder=None, username=None, password=None,
+                        ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False,
+                        xaxis="frequency", colormap='jet', normFactor=None):
+                    """
+                    Input:
+                        dataOut         :
+                        id        :
+                        wintitle        :
+                        channelList     :
+                        showProfile     :
+                        xmin            :    None,
+                        xmax            :    None,
+                        ymin            :    None,
+                        ymax            :    None,
+                        zmin            :    None,
+                        zmax            :    None
+                    """
+                    print("***************PLOTEO******************")
+                    print("DATAOUT SHAPE : ",dataOut.data.shape)
+                    if dataOut.flagNoData:
+                        return dataOut
+                    if realtime:
+                        if not(isRealtime(utcdatatime = dataOut.utctime)):
+                            print('Skipping this plot function')
+                            return
+                    if channelList == None:
+                        channelIndexList = dataOut.channelIndexList
+                    else:
+                        channelIndexList = []
+                        for channel in channelList:
+                            if channel not in dataOut.channelList:
+                                raise ValueError("Channel %d is not in dataOut.channelList" %channel)
+                            channelIndexList.append(dataOut.channelList.index(channel))
+                    print("channelIndexList",channelIndexList)
+                    if normFactor is None:
+                        factor = dataOut.normFactor
+                    else:
+                        factor = normFactor
+                    if xaxis == "frequency":
+                        x = dataOut.getFreqRange(1)/1000.
+                        xlabel = "Frequency (kHz)"
+                    elif xaxis == "time":
+                        x = dataOut.getAcfRange(1)
+                        xlabel = "Time (ms)"
+                    else:
+                        x = dataOut.getVelRange(1)
+                        xlabel = "Velocity (m/s)"
+                    ylabel = "Range (km)"
+                    y = dataOut.getHeiRange()
+                    print("factor",factor)
+                    z = dataOut.data/factor # dividido /factor
+                    z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
+                    zdB = 10*numpy.log10(z)
+                    avg = numpy.average(z, axis=1)
+                    avgdB = 10*numpy.log10(avg)
+                    noise = dataOut.getNoise()/factor
+                    noisedB = 10*numpy.log10(noise)
+                    thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
+                    title = wintitle + "Weather Power"
+                    if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
+                        title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
+                    if not self.isConfig:
+                        nplots = len(channelIndexList)
+                        self.setup(id=id,
+                                   nplots=nplots,
+                                   wintitle=wintitle,
+                                   showprofile=showprofile,
+                                   show=show)
+                        if xmin == None: xmin = numpy.nanmin(x)
+                        if xmax == None: xmax = numpy.nanmax(x)
+                        if ymin == None: ymin = numpy.nanmin(y)
+                        if ymax == None: ymax = numpy.nanmax(y)
+                        if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
+                        if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
+                        self.FTP_WEI = ftp_wei
+                        self.EXP_CODE = exp_code
+                        self.SUB_EXP_CODE = sub_exp_code
+                        self.PLOT_POS = plot_pos
+                        self.isConfig = True
+                    self.setWinTitle(title)
+                    for i in range(self.nplots):
+                        index = channelIndexList[i]
+                        str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
+                        title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime)
+                        if len(dataOut.beam.codeList) != 0:
+                            title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime)
+                        axes = self.axesList[i*self.__nsubplots]
+                        axes.pcolor(x, y, zdB[index,:,:],
+                                    xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
+                                    xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap,
+                                    ticksize=9, cblabel='')
+                        if self.__showprofile:
+                            axes = self.axesList[i*self.__nsubplots +1]
+                            axes.pline(avgdB[index,:], y,
+                                    xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
+                                    xlabel='dB', ylabel='', title='',
+                                    ytick_visible=False,
+                                    grid='x')
+                            noiseline = numpy.repeat(noisedB[index], len(y))
+                            axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
+                    self.draw()
+                    if figfile == None:
+                        str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
+                        name = str_datetime
+                        if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
+                            name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
+                        figfile = self.getFilename(name)
+                    self.save(figpath=figpath,
+                              figfile=figfile,
+                              save=save,
+                              ftp=ftp,
+                              wr_period=wr_period,
+                              thisDatetime=thisDatetime)
+                    return dataOut
+            @MPDecorator
             class CrossSpectraPlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTH = None
                 HEIGHT = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'cspc'
                 def __init__(self):
                     Figure.__init__(self)
                     self.isConfig = False
                     self.__nsubplots = 4
                     self.counter_imagwr = 0
                     self.WIDTH = 250
                     self.HEIGHT = 250
                     self.WIDTHPROF = 0
                     self.HEIGHTPROF = 0
                     self.PLOT_CODE = CROSS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.indice=0
                 def getSubplots(self):
                     ncol = 4
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=True)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", pairsList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         coh_min=None, coh_max=None, phase_min=None, phase_max=None,
                         save=False, figpath='./', figfile=None, ftp=False, wr_period=1,
                         power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None,
                         xaxis='frequency'):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return dataOut
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" %str(pair))
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if not pairsIndexList:
                         return
                     if len(pairsIndexList) > 4:
                         pairsIndexList = pairsIndexList[0:4]
                     if normFactor is None:
                         factor = dataOut.normFactor
                     else:
                         factor = normFactor
                     x = dataOut.getVelRange(1)
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc[:,:,:]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     noise = dataOut.noise/factor
                     zdB = 10*numpy.log10(z)
                     noisedB = 10*numpy.log10(noise)
                     if coh_min == None:
                         coh_min = 0.0
                     if coh_max == None:
                         coh_max = 1.0
                     if phase_min == None:
                         phase_min = -180
                     if phase_max == None:
                         phase_max = 180
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
              #         xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=False,
                                    show=show)
                         avg = numpy.abs(numpy.average(z, axis=1))
                         avgdB = 10*numpy.log10(avg)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         chan_index0 = dataOut.channelList.index(pair[0])
                         chan_index1 = dataOut.channelList.index(pair[1])
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime)
                         zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor)
                         axes0 = self.axesList[i*self.__nsubplots]
                         axes0.pcolor(x, y, zdB,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=power_cmap, cblabel='')
                         title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime)
                         zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor)
                         axes0 = self.axesList[i*self.__nsubplots+1]
                         axes0.pcolor(x, y, zdB,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=power_cmap, cblabel='')
                         coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:]  /  numpy.sqrt(  dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:]  )
                         coherence = numpy.abs(coherenceComplex)
              #            phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi
                         phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi
                         title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1])
                         axes0 = self.axesList[i*self.__nsubplots+2]
                         axes0.pcolor(x, y, coherence,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=coherence_cmap, cblabel='')
                         title = "Phase Ch%d * Ch%d" %(pair[0], pair[1])
                         axes0 = self.axesList[i*self.__nsubplots+3]
                         axes0.pcolor(x, y, phase,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=phase_cmap, cblabel='')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
                     return dataOut
             @MPDecorator
             class RTIPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'rti'
                 def __init__(self):
                     Figure.__init__(self)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = RTI_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 7
                         colspan = 6
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         timerange=None, colormap='jet',
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return dataOut
                     #colormap = kwargs.get('colormap', 'jet')
                     if HEIGHT is not None:
                         self.HEIGHT  = HEIGHT
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     if normFactor is None:
                         factor = dataOut.normFactor
                     else:
                         factor = normFactor
                     #factor = dataOut.normFactor
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     avgdB = 10.*numpy.log10(avg)
                     # avgdB = dataOut.getPower()
                     thisDatetime = dataOut.datatime
                     #thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     update_figfile = False
                     if self.xmax is not None and dataOut.ltctime >= self.xmax: #yong
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         noise = dataOut.noise/factor
                         noisedB = 10*numpy.log10(noise)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         self.figfile = figfile
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         index = channelIndexList[i]
                         title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                         axes = self.axesList[i*self.__nsubplots]
                         zdB = avgdB[index].reshape((1,-1))
                         axes.pcolorbuffer(x, y, zdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap=colormap)
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[index], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     return dataOut
             @MPDecorator
             class CoherenceMap_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'cmap'
                 def __init__(self):
                     Figure.__init__(self)
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 180
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = COH_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.counter_imagwr = 0
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots*2
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 7
                         colspan = 6
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=True)
                     nrow, ncol = self.getSubplots()
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         timerange=None, phase_min=None, phase_max=None,
                         save=False, figpath='./', figfile=None, ftp=False, wr_period=1,
                         coherence_cmap='jet', phase_cmap='RdBu_r', show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if dataOut.flagNoData:
                         return dataOut
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" %(pair))
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if pairsIndexList == []:
                         return
                     if len(pairsIndexList) > 4:
                         pairsIndexList = pairsIndexList[0:4]
                     if phase_min == None:
                         phase_min = -180
                     if phase_max == None:
                         phase_max = 180
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
                     thisDatetime = dataOut.datatime
                     title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = 0.
                         if zmax == None: zmax = 1.
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0)
                         powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0)
                         powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0)
                         avgcoherenceComplex = ccf/numpy.sqrt(powa*powb)
                         coherence = numpy.abs(avgcoherenceComplex)
                         z = coherence.reshape((1,-1))
                         counter = 0
                         title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots*2]
                         axes.pcolorbuffer(x, y, z,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%")
                         if self.__showprofile:
                             counter += 1
                             axes = self.axesList[i*self.__nsubplots*2 + counter]
                             axes.pline(coherence, y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='', ylabel='', title='', ticksize=7,
                                     ytick_visible=False, nxticks=5,
                                     grid='x')
                         counter += 1
                         phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi
                         z = phase.reshape((1,-1))
                         title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots*2 + counter]
                         axes.pcolorbuffer(x, y, z,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%")
                         if self.__showprofile:
                             counter += 1
                             axes = self.axesList[i*self.__nsubplots*2 + counter]
                             axes.pline(phase, y,
                                     xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax,
                                     xlabel='', ylabel='', title='', ticksize=7,
                                     ytick_visible=False, nxticks=4,
                                     grid='x')
                     self.draw()
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     return dataOut
             @MPDecorator
             class PowerProfilePlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spcprofile'
                 def __init__(self):
                     Figure.__init__(self)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = POWER_CODE
                     self.WIDTH = 300
                     self.HEIGHT = 500
                     self.counter_imagwr = 0
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH,
                                       heightplot = self.HEIGHT,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True,
                         ftp=False, wr_period=1, server=None,
                         folder=None, username=None, password=None):
                     if dataOut.flagNoData:
                         return dataOut
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     y = dataOut.getHeiRange()
                     #for voltage
                     if dataOut.type == 'Voltage':
                         x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:])
                         x = x.real
                         x = numpy.where(numpy.isfinite(x), x, numpy.NAN)
                     #for spectra
                     if dataOut.type == 'Spectra':
                         x = dataOut.data_spc[channelIndexList,:,:]/factor
                         x = numpy.where(numpy.isfinite(x), x, numpy.NAN)
                         x = numpy.average(x, axis=1)
                     xdB = 10*numpy.log10(x)
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "dB"
                     ylabel = "Range (Km)"
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if xmin == None: xmin = numpy.nanmin(xdB)*0.9
                         if xmax == None: xmax = numpy.nanmax(xdB)*1.1
                         self.isConfig = True
                     self.setWinTitle(title)
                     title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     axes = self.axesList[0]
                     legendlabels = ["channel %d"%x for x in channelList]
                     axes.pmultiline(xdB, y,
                             xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                             xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels,
                             ytick_visible=True, nxticks=5,
                             grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
                     return dataOut
             @MPDecorator
             class SpectraCutPlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spc_cut'
                 def __init__(self):
                     Figure.__init__(self)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = POWER_CODE
                     self.WIDTH = 700
                     self.HEIGHT = 500
                     self.counter_imagwr = 0
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH,
                                       heightplot = self.HEIGHT,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True,
                         ftp=False, wr_period=1, server=None,
                         folder=None, username=None, password=None,
                         xaxis="frequency"):
                     if dataOut.flagNoData:
                         return dataOut
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     hei_index = numpy.arange(25)*3 + 20
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange()/1000.
                         zdB = 10*numpy.log10(z[0,:,hei_index])
                         xlabel = "Frequency (kHz)"
                         ylabel = "Power (dB)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange()
                         zdB = z[0,:,hei_index]
                         xlabel = "Time (ms)"
                         ylabel = "ACF"
                     else:
                         x = dataOut.getVelRange()
                         zdB = 10*numpy.log10(z[0,:,hei_index])
                         xlabel = "Velocity (m/s)"
                         ylabel = "Power (dB)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)*0.9
                         if xmax == None: xmax = numpy.nanmax(x)*1.1
                         if ymin == None: ymin = numpy.nanmin(zdB)
                         if ymax == None: ymax = numpy.nanmax(zdB)
                         self.isConfig = True
                     self.setWinTitle(title)
                     title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     axes = self.axesList[0]
                     legendlabels = ["Range = %dKm" %y[i] for i in hei_index]
                     axes.pmultilineyaxis( x, zdB,
                             xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                             xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels,
                             ytick_visible=True, nxticks=5,
                             grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
                     return dataOut
             @MPDecorator
             class Noise_(Figure):
                 isConfig = None
                 __nsubplots = None
                 PREFIX = 'noise'
                 def __init__(self):
                     Figure.__init__(self)
                     self.timerange = 24*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 800
                     self.HEIGHT = 400
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = NOISE_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.figfile = None
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def openfile(self, filename):
                     dirname = os.path.dirname(filename)
                     if not os.path.exists(dirname):
                         os.mkdir(dirname)
                     f = open(filename,'w+')
                     f.write('\n\n')
                     f.write('JICAMARCA RADIO OBSERVATORY - Noise \n')
                     f.write('DD MM YYYY  HH MM SS   Channel0    Channel1    Channel2    Channel3\n\n' )
                     f.close()
                 def save_data(self, filename_phase, data, data_datetime):
                     f=open(filename_phase,'a')
                     timetuple_data = data_datetime.timetuple()
                     day = str(timetuple_data.tm_mday)
                     month = str(timetuple_data.tm_mon)
                     year = str(timetuple_data.tm_year)
                     hour = str(timetuple_data.tm_hour)
                     minute = str(timetuple_data.tm_min)
                     second = str(timetuple_data.tm_sec)
                     data_msg = ''
                     for i in range(len(data)):
                         data_msg += str(data[i]) + '  '
                     f.write(day+' '+month+' '+year+'  '+hour+' '+minute+' '+second+'   ' + data_msg + '\n')
                     f.close()
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 7
                     colspan = 6
                     self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH+self.WIDTHPROF,
                                       heightplot = self.HEIGHT+self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1)
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         timerange=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if dataOut.flagNoData:
                         return dataOut
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     x = dataOut.getTimeRange()
                     #y = dataOut.getHeiRange()
                     factor = dataOut.normFactor
                     noise = dataOut.noise[channelIndexList]/factor
                     noisedB = 10*numpy.log10(noise)
                     thisDatetime = dataOut.datatime
                     title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Intensity (dB)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.floor(numpy.nanmin(noisedB)) - 10.0
                         if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         self.figfile = figfile
                         self.xdata = numpy.array([])
                         self.ydata = numpy.array([])
                         update_figfile = True
                         #open file beacon phase
                         path = '%s%03d' %(self.PREFIX, self.id)
                         noise_file = os.path.join(path,'%s.txt'%self.name)
                         self.filename_noise = os.path.join(figpath,noise_file)
                     self.setWinTitle(title)
                     title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["channel %d"%(idchannel) for idchannel in channelList]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata)==0:
                         self.ydata = noisedB.reshape(-1,1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, noisedB.reshape(-1,1)))
                     axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
                                 XAxisAsTime=True, grid='both'
                                 )
                     self.draw()
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     #store data beacon phase
                     if save:
                         self.save_data(self.filename_noise, noisedB, thisDatetime)
                     return dataOut
             @MPDecorator
             class BeaconPhase_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'beacon_phase'
                 def __init__(self):
                     Figure.__init__(self)
                     self.timerange = 24*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 800
                     self.HEIGHT = 400
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = BEACON_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.filename_phase = None
                     self.figfile = None
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 7
                     colspan = 6
                     self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH+self.WIDTHPROF,
                                       heightplot = self.HEIGHT+self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1)
                 def save_phase(self, filename_phase):
                     f = open(filename_phase,'w+')
                     f.write('\n\n')
                     f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n')
                     f.write('DD MM YYYY  HH MM SS   pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' )
                     f.close()
                 def save_data(self, filename_phase, data, data_datetime):
                     f=open(filename_phase,'a')
                     timetuple_data = data_datetime.timetuple()
                     day = str(timetuple_data.tm_mday)
                     month = str(timetuple_data.tm_mon)
                     year = str(timetuple_data.tm_year)
                     hour = str(timetuple_data.tm_hour)
                     minute = str(timetuple_data.tm_min)
                     second = str(timetuple_data.tm_sec)
                     f.write(day+' '+month+' '+year+'  '+hour+' '+minute+' '+second+'   '+str(data[0])+'   '+str(data[1])+'   '+str(data[2])+'   '+str(data[3])+'\n')
                     f.close()
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None,
                         timerange=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if dataOut.flagNoData:
                         return dataOut
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList[:10]
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" %(pair))
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if pairsIndexList == []:
                         return
              #         if len(pairsIndexList) > 4:
              #             pairsIndexList = pairsIndexList[0:4]
                     hmin_index = None
                     hmax_index = None
                     if hmin != None and hmax != None:
                         indexes = numpy.arange(dataOut.nHeights)
                         hmin_list = indexes[dataOut.heightList >= hmin]
                         hmax_list = indexes[dataOut.heightList <= hmax]
                         if hmin_list.any():
                             hmin_index = hmin_list[0]
                         if hmax_list.any():
                             hmax_index = hmax_list[-1]+1
                     x = dataOut.getTimeRange()
                     #y = dataOut.getHeiRange()
                     thisDatetime = dataOut.datatime
                     title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase (degrees)"
                     update_figfile = False
                     nplots = len(pairsIndexList)
                     #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = numpy.zeros(len(pairsIndexList))
                     for i in range(nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0)
                         powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0)
                         powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0)
                         avgcoherenceComplex = ccf/numpy.sqrt(powa*powb)
                         phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi
                         if dataOut.beacon_heiIndexList:
                             phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList])
                         else:
                             phase_beacon[i] = numpy.average(phase)
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = 0
                         if ymax == None: ymax = 360
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         self.figfile = figfile
                         self.xdata = numpy.array([])
                         self.ydata = numpy.array([])
                         update_figfile = True
                         #open file beacon phase
                         path = '%s%03d' %(self.PREFIX, self.id)
                         beacon_file = os.path.join(path,'%s.txt'%self.name)
                         self.filename_phase = os.path.join(figpath,beacon_file)
                         #self.save_phase(self.filename_phase)
                     #store data beacon phase
                     #self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata)==0:
                         self.ydata = phase_beacon.reshape(-1,1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1)))
                     axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
                                 XAxisAsTime=True, grid='both'
                                 )
                     self.draw()
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
-                    return dataOut
  No newline at end of file
+                    return dataOut

schainpy/model/graphics/jroplot_voltage.py +123 -61

             '''
             Created on Jul 9, 2014
             @author: roj-idl71
             '''
             import os
             import datetime
             import numpy
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator  #YONG
             from schainpy.utils import log
             from .figure import Figure
             @MPDecorator
             class Scope_(Figure):
                 isConfig = None
                 def __init__(self):#, **kwargs):          #YONG
                     Figure.__init__(self)#, **kwargs)
                     self.isConfig = False
                     self.WIDTH = 300
                     self.HEIGHT = 200
                     self.counter_imagwr = 0
                 def getSubplots(self):
                     nrow = self.nplots
                     ncol = 3
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show):
                     self.nplots = nplots
                     self.createFigure(id=id,
                                       wintitle=wintitle,
                                       show=show)
                     nrow,ncol = self.getSubplots()
                     colspan = 3
                     rowspan = 1
                     for i in range(nplots):
                         self.addAxes(nrow, ncol, i, 0, colspan, rowspan)
                 def plot_iq(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax):
                     yreal = y[channelIndexList,:].real
                     yimag = y[channelIndexList,:].imag
                     title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     xlabel = "Range (Km)"
                     ylabel = "Intensity - IQ"
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle='',
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = min(numpy.nanmin(yreal),numpy.nanmin(yimag))
                         if ymax == None: ymax = max(numpy.nanmax(yreal),numpy.nanmax(yimag))
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(len(self.axesList)):
                         title = "Channel %d" %(i)
                         axes = self.axesList[i]
                         axes.pline(x, yreal[i,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                     xlabel=xlabel, ylabel=ylabel, title=title)
                         axes.addpline(x, yimag[i,:], idline=1, color="red", linestyle="solid", lw=2)
                 def plot_power(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax):
                     y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:])
                     yreal = y.real
                     title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     xlabel = "Range (Km)"
                     ylabel = "Intensity"
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle='',
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(yreal)
                         if ymax == None: ymax = numpy.nanmax(yreal)
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(len(self.axesList)):
                         title = "Channel %d" %(i)
                         axes = self.axesList[i]
                         ychannel = yreal[i,:]
                         axes.pline(x, ychannel,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                     xlabel=xlabel, ylabel=ylabel, title=title)
+                def plot_weatherpower(self, x, y, id, channelIndexList, thisDatetime, wintitle, show, xmin, xmax, ymin, ymax):
+                    y = y[channelIndexList,:]
+                    yreal = y
+                    title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
+                    xlabel = "Range (Km)"
+                    ylabel = "Intensity"
+                    if not self.isConfig:
+                        nplots = len(channelIndexList)
+                        self.setup(id=id,
+                                   nplots=nplots,
+                                   wintitle='',
+                                   show=show)
+                        if xmin == None: xmin = numpy.nanmin(x)
+                        if xmax == None: xmax = numpy.nanmax(x)
+                        if ymin == None: ymin = numpy.nanmin(yreal)
+                        if ymax == None: ymax = numpy.nanmax(yreal)
+                        self.isConfig = True
+                    self.setWinTitle(title)
+                    for i in range(len(self.axesList)):
+                        title = "Channel %d" %(i)
+                        axes = self.axesList[i]
+                        ychannel = yreal[i,:]
+                        axes.pline(x, ychannel,
+                                    xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
+                                    xlabel=xlabel, ylabel=ylabel, title=title)
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, save=False,
                         figpath='./', figfile=None, show=True, wr_period=1,
                         ftp=False, server=None, folder=None, username=None, password=None, type='power', **kwargs):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                     """
                     if dataOut.flagNoData:
                         return dataOut
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError("Channel %d is not in dataOut.channelList")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
+                    ### print("***************** PLOTEO **************************")
+                    ### print(dataOut.nProfiles)
+                    ### print(dataOut.heightList.shape)
                     if dataOut.flagDataAsBlock:
                         for i in range(dataOut.nProfiles):
                             wintitle1 = wintitle + " [Profile = %d] " %i
                             if type == "power":
                                 self.plot_power(dataOut.heightList,
                                                 dataOut.data[:,i,:],
                                                 id,
                                                 channelIndexList,
                                                 thisDatetime,
                                                 wintitle1,
                                                 show,
                                                 xmin,
                                                 xmax,
                                                 ymin,
                                                 ymax)
+                            if type == "weatherpower":
+                                self.plot_weatherpower(dataOut.heightList,
+                                                dataOut.data[:,i,:],
+                                                id,
+                                                channelIndexList,
+                                                thisDatetime,
+                                                wintitle1,
+                                                show,
+                                                xmin,
+                                                xmax,
+                                                ymin,
+                                                ymax)
+                            if type == "weathervelocity":
+                                self.plot_weatherpower(dataOut.heightList,
+                                                dataOut.data_velocity[:,i,:],
+                                                id,
+                                                channelIndexList,
+                                                thisDatetime,
+                                                wintitle1,
+                                                show,
+                                                xmin,
+                                                xmax,
+                                                ymin,
+                                                ymax)
                             if type == "iq":
                                 self.plot_iq(dataOut.heightList,
                                              dataOut.data[:,i,:],
                                              id,
                                              channelIndexList,
                                              thisDatetime,
                                              wintitle1,
                                              show,
                                              xmin,
                                              xmax,
                                              ymin,
                                              ymax)
                             self.draw()
                             str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                             figfile = self.getFilename(name = str_datetime) + "_" + str(i)
                             self.save(figpath=figpath,
                                       figfile=figfile,
                                       save=save,
                                       ftp=ftp,
                                       wr_period=wr_period,
                                       thisDatetime=thisDatetime)
                     else:
                         wintitle += " [Profile = %d] " %dataOut.profileIndex
                         if type == "power":
                             self.plot_power(dataOut.heightList,
                                             dataOut.data,
                                             id,
                                             channelIndexList,
                                             thisDatetime,
                                             wintitle,
                                             show,
                                             xmin,
                                             xmax,
                                             ymin,
                                             ymax)
                         if type == "iq":
                             self.plot_iq(dataOut.heightList,
                                          dataOut.data,
                                          id,
                                          channelIndexList,
                                          thisDatetime,
                                          wintitle,
                                          show,
                                          xmin,
                                          xmax,
                                          ymin,
                                          ymax)
                     self.draw()
                     str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") + "_" + str(dataOut.profileIndex)
                     figfile = self.getFilename(name = str_datetime)
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
-                    return dataOut                 
  No newline at end of file
+                    return dataOut

schainpy/model/graphics/plotting_codes.py +3 -1

             '''
             @author: roj-idl71
             '''
             #USED IN jroplot_spectra.py
             RTI_CODE = 0            #Range time intensity (RTI).
             SPEC_CODE = 1           #Spectra (and Cross-spectra) information.
             CROSS_CODE = 2          #Cross-Correlation information.
             COH_CODE = 3            #Coherence map.
             BASE_CODE = 4           #Base lines graphic.
             ROW_CODE = 5            #Row Spectra.
             TOTAL_CODE = 6          #Total Power.
             DRIFT_CODE = 7          #Drifts graphics.
             HEIGHT_CODE = 8         #Height profile.
             PHASE_CODE = 9          #Signal Phase.
             POWER_CODE = 16
             NOISE_CODE = 17
             BEACON_CODE = 18
             #USED IN jroplot_parameters.py
             WIND_CODE = 22
             MSKYMAP_CODE = 23
             MPHASE_CODE = 24
             MOMENTS_CODE = 25
-            PARMS_CODE = 26
+            PARMS_CODE   = 26
             SPECFIT_CODE = 27
             EWDRIFT_CODE = 28
+            WPO_CODE     = 29         #Weather Intensity - Power

schainpy/model/io/jroIO_param.py +63 -40

             import numpy
             import time
             import os
             import h5py
             import re
             import datetime
             import schainpy.admin
             from schainpy.model.data.jrodata import *
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.io.jroIO_base import *
             from schainpy.utils import log
             @MPDecorator
             class ParamReader(JRODataReader,ProcessingUnit):
                 '''
                 Reads HDF5 format files
                 path
                 startDate
                 endDate
                 startTime
                 endTime
                 '''
                 ext = ".hdf5"
                 optchar = "D"
                 timezone = None
                 startTime = None
                 endTime = None
                 fileIndex = None
                 utcList = None      #To select data in the utctime list
                 blockList = None    #List to blocks to be read from the file
                 blocksPerFile = None    #Number of blocks to be read
                 blockIndex = None
                 path = None
                 #List of Files
                 filenameList = None
                 datetimeList = None
                 #Hdf5 File
                 listMetaname = None
                 listMeta = None
                 listDataname = None
                 listData = None
                 listShapes = None
                 fp = None
                 #dataOut reconstruction
                 dataOut = None
                 def __init__(self):#, **kwargs):
                     ProcessingUnit.__init__(self) #, **kwargs)
                     self.dataOut = Parameters()
                     return
                 def setup(self, **kwargs):
                     path = kwargs['path']
                     startDate = kwargs['startDate']
                     endDate = kwargs['endDate']
                     startTime = kwargs['startTime']
                     endTime = kwargs['endTime']
                     walk = kwargs['walk']
                     if 'ext' in kwargs:
                         ext = kwargs['ext']
                     else:
                         ext = '.hdf5'
                     if 'timezone' in kwargs:
                         self.timezone = kwargs['timezone']
                     else:
                         self.timezone = 'lt'
                     print("[Reading] Searching files in offline mode ...")
                     pathList, filenameList = self.searchFilesOffLine(path, startDate=startDate, endDate=endDate,
                                                                            startTime=startTime, endTime=endTime,
                                                                            ext=ext, walk=walk)
                     if not(filenameList):
                         print("There is no files into the folder: %s"%(path))
                         sys.exit(-1)
                     self.fileIndex = -1
                     self.startTime = startTime
                     self.endTime = endTime
                     self.__readMetadata()
                     self.__setNextFileOffline()
                     return
                 def searchFilesOffLine(self,
                                         path,
                                         startDate=None,
                                         endDate=None,
                                         startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),
                                         ext='.hdf5',
                                         walk=True):
                     expLabel = ''
                     self.filenameList = []
                     self.datetimeList = []
                     pathList = []
                     JRODataObj = JRODataReader()
                     dateList, pathList = JRODataObj.findDatafiles(path, startDate, endDate, expLabel, ext, walk, include_path=True)
                     if dateList == []:
                         print("[Reading] No *%s files in %s from %s to %s)"%(ext, path,
                                                                     datetime.datetime.combine(startDate,startTime).ctime(),
                                                                     datetime.datetime.combine(endDate,endTime).ctime()))
                         return None, None
                     if len(dateList) > 1:
                         print("[Reading] %d days were found in date range: %s - %s" %(len(dateList), startDate, endDate))
                     else:
                         print("[Reading] data was found for the date %s" %(dateList[0]))
                     filenameList = []
                     datetimeList = []
                     #----------------------------------------------------------------------------------
                     for thisPath in pathList:
                         fileList = glob.glob1(thisPath, "*%s" %ext)
                         fileList.sort()
                         for file in fileList:
                             filename = os.path.join(thisPath,file)
                             if not isFileInDateRange(filename, startDate, endDate):
                                 continue
                             thisDatetime = self.__isFileInTimeRange(filename, startDate, endDate, startTime, endTime)
                             if not(thisDatetime):
                                 continue
                             filenameList.append(filename)
                             datetimeList.append(thisDatetime)
                     if not(filenameList):
                         print("[Reading] Any file was found int time range %s - %s" %(datetime.datetime.combine(startDate,startTime).ctime(), datetime.datetime.combine(endDate,endTime).ctime()))
                         return None, None
                     print("[Reading] %d file(s) was(were) found in time range: %s - %s" %(len(filenameList), startTime, endTime))
                     print()
                     self.filenameList = filenameList
                     self.datetimeList = datetimeList
                     return pathList, filenameList
                 def __isFileInTimeRange(self,filename, startDate, endDate, startTime, endTime):
                     """
                     Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
                     Inputs:
                         filename            :    nombre completo del archivo de datos en formato Jicamarca (.r)
                         startDate          :    fecha inicial del rango seleccionado en formato datetime.date
                         endDate            :    fecha final del rango seleccionado en formato datetime.date
                         startTime          :    tiempo inicial del rango seleccionado en formato datetime.time
                         endTime            :    tiempo final del rango seleccionado en formato datetime.time
                     Return:
                         Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                         fecha especificado, de lo contrario retorna False.
                     Excepciones:
                         Si el archivo no existe o no puede ser abierto
                         Si la cabecera no puede ser leida.
                     """
                     try:
                         fp = h5py.File(filename,'r')
                         grp1 = fp['Data']
                     except IOError:
                         traceback.print_exc()
                         raise IOError("The file %s can't be opened" %(filename))
                     #In case has utctime attribute
                     grp2 = grp1['utctime']
              #         thisUtcTime = grp2.value[0] - 5*3600 #To convert to local time
                     thisUtcTime = grp2.value[0]
                     fp.close()
                     if self.timezone == 'lt':
                         thisUtcTime -= 5*3600
                     thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate,startTime)- datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate,endTime)- datetime.datetime(1970, 1, 1)).total_seconds()
                     #General case
                     #           o>>>>>>>>>>>>>><<<<<<<<<<<<<<o
                     #-----------o----------------------------o-----------
                     #       startTime                     endTime
                     if endTime >= startTime:
                         thisUtcLog = numpy.logical_and(thisUtcTime > startUtcTime, thisUtcTime < endUtcTime)
                         if numpy.any(thisUtcLog):   #If there is one block between the hours mentioned
                             return thisDatetime
                         return None
                     #If endTime < startTime then endTime belongs to the next day
                     #<<<<<<<<<<<o                            o>>>>>>>>>>>
                     #-----------o----------------------------o-----------
                     #        endTime                    startTime
                     if (thisDate == startDate) and numpy.all(thisUtcTime < startUtcTime):
                         return None
                     if (thisDate == endDate) and numpy.all(thisUtcTime > endUtcTime):
                         return None
                     if numpy.all(thisUtcTime < startUtcTime) and numpy.all(thisUtcTime > endUtcTime):
                         return None
                     return thisDatetime
                 def __setNextFileOffline(self):
                     self.fileIndex += 1
                     idFile = self.fileIndex
                     if not(idFile < len(self.filenameList)):
                         raise schainpy.admin.SchainError("No more Files")
                         return 0
                     filename = self.filenameList[idFile]
                     filePointer = h5py.File(filename,'r')
                     self.filename = filename
                     self.fp = filePointer
                     print("Setting the file: %s"%self.filename)
                     self.__setBlockList()
                     self.__readData()
                     self.blockIndex = 0
                     return 1
                 def __setBlockList(self):
                     '''
                     Selects the data within the times defined
                     self.fp
                     self.startTime
                     self.endTime
                     self.blockList
                     self.blocksPerFile
                     '''
                     fp = self.fp
                     startTime = self.startTime
                     endTime = self.endTime
                     grp = fp['Data']
                     thisUtcTime = grp['utctime'].value.astype(numpy.float)[0]
                     #ERROOOOR
                     if self.timezone == 'lt':
                         thisUtcTime -= 5*3600
                     thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate,startTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate,endTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     ind = numpy.where(numpy.logical_and(thisUtcTime >= startUtcTime, thisUtcTime < endUtcTime))[0]
                     self.blockList = ind
                     self.blocksPerFile = len(ind)
                     return
                 def __readMetadata(self):
                     '''
                     Reads Metadata
                     self.pathMeta
                     self.listShapes
                     self.listMetaname
                     self.listMeta
                     '''
                     filename = self.filenameList[0]
                     fp = h5py.File(filename,'r')
                     gp = fp['Metadata']
                     listMetaname = []
                     listMetadata = []
                     for item in list(gp.items()):
                         name = item[0]
                         if name=='array dimensions':
                             table = gp[name][:]
                             listShapes = {}
                             for shapes in table:
                                 listShapes[shapes[0]] = numpy.array([shapes[1],shapes[2],shapes[3],shapes[4],shapes[5]])
                         else:
                             data = gp[name].value
                             listMetaname.append(name)
                             listMetadata.append(data)
                     self.listShapes = listShapes
                     self.listMetaname = listMetaname
                     self.listMeta = listMetadata
                     fp.close()
                     return
                 def __readData(self):
                     grp = self.fp['Data']
                     listdataname = []
                     listdata = []
                     for item in list(grp.items()):
                         name = item[0]
                         listdataname.append(name)
                         array = self.__setDataArray(grp[name],self.listShapes[name])
                         listdata.append(array)
                     self.listDataname = listdataname
                     self.listData = listdata
                     return
                 def __setDataArray(self, dataset, shapes):
                     nDims = shapes[0]
                     nDim2 = shapes[1]      #Dimension 0
                     nDim1 = shapes[2]      #Dimension 1, number of Points or Parameters
                     nDim0 = shapes[3]      #Dimension 2, number of samples or ranges
                     mode = shapes[4]        #Mode of storing
                     blockList = self.blockList
                     blocksPerFile = self.blocksPerFile
                     #Depending on what mode the data was stored
                     if mode == 0:       #Divided in channels
                         arrayData = dataset.value.astype(numpy.float)[0][blockList]
                     if mode == 1:     #Divided in parameter
                         strds = 'table'
                         nDatas = nDim1
                         newShapes = (blocksPerFile,nDim2,nDim0)
                     elif mode==2:       #Concatenated in a table
                         strds = 'table0'
                         arrayData = dataset[strds].value
                         #Selecting part of the dataset
                         utctime = arrayData[:,0]
                         u, indices = numpy.unique(utctime, return_index=True)
                         if blockList.size != indices.size:
                             indMin = indices[blockList[0]]
                             if blockList[1] + 1 >= indices.size:
                                 arrayData = arrayData[indMin:,:]
                             else:
                                 indMax = indices[blockList[1] + 1]
                                 arrayData = arrayData[indMin:indMax,:]
                         return arrayData
                     #    One dimension
                     if nDims == 0:
                         arrayData = dataset.value.astype(numpy.float)[0][blockList]
                     #    Two dimensions
                     elif nDims == 2:
                         arrayData = numpy.zeros((blocksPerFile,nDim1,nDim0))
                         newShapes = (blocksPerFile,nDim0)
                         nDatas = nDim1
                         for i in range(nDatas):
                             data = dataset[strds + str(i)].value
                             arrayData[:,i,:] = data[blockList,:]
                     #    Three dimensions
                     else:
                         arrayData = numpy.zeros((blocksPerFile,nDim2,nDim1,nDim0))
                         for i in range(nDatas):
                             data = dataset[strds + str(i)].value
                             for b in range(blockList.size):
                                 arrayData[b,:,i,:] = data[:,:,blockList[b]]
                     return arrayData
                 def __setDataOut(self):
                     listMeta = self.listMeta
                     listMetaname = self.listMetaname
                     listDataname = self.listDataname
                     listData = self.listData
                     listShapes = self.listShapes
                     blockIndex = self.blockIndex
              #         blockList = self.blockList
                     for i in range(len(listMeta)):
                         setattr(self.dataOut,listMetaname[i],listMeta[i])
                     for j in range(len(listData)):
                         nShapes = listShapes[listDataname[j]][0]
                         mode = listShapes[listDataname[j]][4]
                         if nShapes == 1:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex])
                         elif nShapes > 1:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex,:])
                         elif mode==0:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex])
                         #Mode Meteors
                         elif mode ==2:
                             selectedData = self.__selectDataMode2(listData[j], blockIndex)
                             setattr(self.dataOut, listDataname[j], selectedData)
                     return
                 def __selectDataMode2(self, data, blockIndex):
                     utctime = data[:,0]
                     aux, indices = numpy.unique(utctime, return_inverse=True)
                     selInd = numpy.where(indices == blockIndex)[0]
                     selData = data[selInd,:]
                     return selData
                 def getData(self):
                     if self.blockIndex==self.blocksPerFile:
                          if not( self.__setNextFileOffline() ):
                             self.dataOut.flagNoData = True
                             return 0
                     self.__setDataOut()
                     self.dataOut.flagNoData = False
                     self.blockIndex += 1
                     return
                 def run(self, **kwargs):
                     if not(self.isConfig):
                         self.setup(**kwargs)
                         self.isConfig = True
                     self.getData()
                     return
             @MPDecorator
             class ParamWriter(Operation):
                 '''
                 HDF5 Writer, stores parameters data in HDF5 format files
                 path:             path where the files will be stored
                 blocksPerFile:    number of blocks that will be saved in per HDF5 format file
                 mode:             selects the data stacking mode: '0' channels, '1' parameters, '3' table (for meteors)
                 metadataList:     list of attributes that will be stored as metadata
                 dataList:         list of attributes that will be stores as data
                 '''
                 ext = ".hdf5"
                 optchar = "D"
                 metaoptchar = "M"
                 metaFile = None
                 filename = None
                 path = None
                 setFile = None
                 fp = None
                 grp = None
                 ds = None
                 firsttime = True
                 #Configurations
                 blocksPerFile = None
                 blockIndex = None
                 dataOut = None
                 #Data Arrays
                 dataList = None
                 metadataList = None
                 dsList = None   #List of dictionaries with dataset properties
                 tableDim = None
                 dtype = [('arrayName', 'S20'),('nDimensions', 'i'), ('dim2', 'i'), ('dim1', 'i'),('dim0', 'i'),('mode', 'b')]
                 currentDay = None
                 lastTime = None
                 setType = None
                 def __init__(self):
                     Operation.__init__(self)
                     return
                 def setup(self, dataOut, path=None, blocksPerFile=10, metadataList=None, dataList=None, mode=None, setType=None):
                     self.path = path
                     self.blocksPerFile = blocksPerFile
                     self.metadataList = metadataList
                     self.dataList = dataList
                     self.dataOut = dataOut
                     self.mode = mode
                     if self.mode is not None:
                         self.mode = numpy.zeros(len(self.dataList)) + mode
                     else:
                         self.mode = numpy.ones(len(self.dataList))
                     self.setType = setType
                     arrayDim = numpy.zeros((len(self.dataList),5))
                     #Table dimensions
                     dtype0 = self.dtype
                     tableList = []
                     #Dictionary and list of tables
                     dsList = []
                     for i in range(len(self.dataList)):
                         dsDict = {}
                         dataAux = getattr(self.dataOut, self.dataList[i])
                         dsDict['variable'] = self.dataList[i]
                         #---------------------    Conditionals    ------------------------
                         #There is no data
                         if dataAux is None:
                             return 0
                         if isinstance(dataAux, (int, float, numpy.integer, numpy.float)):
                             dsDict['mode'] = 0
                             dsDict['nDim'] = 0
                             arrayDim[i,0] = 0
                             dsList.append(dsDict)
                         #Mode 2: meteors
                         elif self.mode[i] == 2:
                             dsDict['dsName'] = 'table0'
                             dsDict['mode'] = 2      # Mode meteors
                             dsDict['shape'] = dataAux.shape[-1]
                             dsDict['nDim'] = 0
                             dsDict['dsNumber'] = 1
                             arrayDim[i,3] = dataAux.shape[-1]
                             arrayDim[i,4] = self.mode[i]         #Mode the data was stored
                             dsList.append(dsDict)
                         #Mode 1
                         else:
                             arrayDim0 = dataAux.shape       #Data dimensions
                             arrayDim[i,0] = len(arrayDim0)  #Number of array dimensions
                             arrayDim[i,4] = self.mode[i]         #Mode the data was stored
                             strtable = 'table'
                             dsDict['mode'] = 1      # Mode parameters
                             # Three-dimension arrays
                             if len(arrayDim0) == 3:
                                 arrayDim[i,1:-1] = numpy.array(arrayDim0)
                                 nTables = int(arrayDim[i,2])
                                 dsDict['dsNumber'] = nTables
                                 dsDict['shape'] = arrayDim[i,2:4]
                                 dsDict['nDim'] = 3
                                 for j in range(nTables):
                                     dsDict = dsDict.copy()
                                     dsDict['dsName'] = strtable + str(j)
                                     dsList.append(dsDict)
                             # Two-dimension arrays
                             elif len(arrayDim0) == 2:
                                 arrayDim[i,2:-1] = numpy.array(arrayDim0)
                                 nTables = int(arrayDim[i,2])
                                 dsDict['dsNumber'] = nTables
                                 dsDict['shape'] = arrayDim[i,3]
                                 dsDict['nDim'] = 2
                                 for j in range(nTables):
                                     dsDict = dsDict.copy()
                                     dsDict['dsName'] = strtable + str(j)
                                     dsList.append(dsDict)
                             # One-dimension arrays
                             elif len(arrayDim0) == 1:
                                 arrayDim[i,3] = arrayDim0[0]
                                 dsDict['shape'] = arrayDim0[0]
                                 dsDict['dsNumber'] = 1
                                 dsDict['dsName'] = strtable + str(0)
                                 dsDict['nDim'] = 1
                                 dsList.append(dsDict)
                         table = numpy.array((self.dataList[i],) + tuple(arrayDim[i,:]),dtype = dtype0)
                         tableList.append(table)
                     self.dsList = dsList
                     self.tableDim = numpy.array(tableList, dtype = dtype0)
                     self.blockIndex = 0
                     timeTuple = time.localtime(dataOut.utctime)
                     self.currentDay = timeTuple.tm_yday
                 def putMetadata(self):
                     fp = self.createMetadataFile()
                     self.writeMetadata(fp)
                     fp.close()
                     return
                 def createMetadataFile(self):
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = ''
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     else:
                         filesList = os.listdir( fullpath )
                         filesList = sorted( filesList, key=str.lower )
                         if len( filesList ) > 0:
                             filesList = [k for k in filesList if k.startswith(self.metaoptchar)]
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber( filen[8:11] ):
                                 setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     filename = os.path.join( path, subfolder, file )
                     self.metaFile = file
                     #Setting HDF5 File
                     fp = h5py.File(filename,'w')
                     return fp
                 def writeMetadata(self, fp):
                     grp = fp.create_group("Metadata")
                     grp.create_dataset('array dimensions', data = self.tableDim, dtype = self.dtype)
                     for i in range(len(self.metadataList)):
                         grp.create_dataset(self.metadataList[i], data=getattr(self.dataOut, self.metadataList[i]))
                     return
                 def timeFlag(self):
                     currentTime = self.dataOut.utctime
                     if self.lastTime is None:
                         self.lastTime = currentTime
                     #Day
                     timeTuple = time.localtime(currentTime)
                     dataDay = timeTuple.tm_yday
                     #Time
                     timeDiff = currentTime - self.lastTime
                     #Si el dia es diferente o si la diferencia entre un dato y otro supera la hora
                     if dataDay != self.currentDay:
                         self.currentDay = dataDay
                         return True
                     elif timeDiff > 3*60*60:
                         self.lastTime = currentTime
                         return True
                     else:
                         self.lastTime = currentTime
                         return False
                 def setNextFile(self):
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     mode = self.mode
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if os.path.exists(fullpath):
                         filesList = os.listdir( fullpath )
                         filesList = [k for k in filesList if 'M' in k]
                         if len( filesList ) > 0:
                             filesList = sorted( filesList, key=str.lower )
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber( filen[8:11] ):
                                 setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     else:
                         os.makedirs(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     filename = os.path.join( path, subfolder, file )
                     #Setting HDF5 File
                     fp = h5py.File(filename,'w')
                     #write metadata
                     self.writeMetadata(fp)
                     #Write data
                     grp = fp.create_group("Data")
                     ds = []
                     data = []
                     dsList = self.dsList
                     i = 0
                     while i < len(dsList):
                         dsInfo = dsList[i]
                         #One-dimension data
                         if dsInfo['mode'] == 0:
                             ds0 = grp.create_dataset(dsInfo['variable'], (1,1), maxshape=(1,self.blocksPerFile) , chunks = True, dtype=numpy.float64)
                             ds.append(ds0)
                             data.append([])
                             i += 1
                             continue
                         elif dsInfo['mode'] == 2:
                             grp0 = grp.create_group(dsInfo['variable'])
                             ds0 = grp0.create_dataset(dsInfo['dsName'], (1,dsInfo['shape']), data = numpy.zeros((1,dsInfo['shape'])) , maxshape=(None,dsInfo['shape']), chunks=True)
                             ds.append(ds0)
                             data.append([])
                             i += 1
                             continue
                         elif dsInfo['mode'] == 1:
                             grp0 = grp.create_group(dsInfo['variable'])
                             for j in range(dsInfo['dsNumber']):
                                 dsInfo = dsList[i]
                                 tableName = dsInfo['dsName']
                                 if dsInfo['nDim'] == 3:
                                     shape = dsInfo['shape'].astype(int)
                                     ds0 = grp0.create_dataset(tableName, (shape[0],shape[1],1) , data = numpy.zeros((shape[0],shape[1],1)), maxshape = (None,shape[1],None), chunks=True)
                                 else:
                                     shape = int(dsInfo['shape'])
                                     ds0 = grp0.create_dataset(tableName, (1,shape), data = numpy.zeros((1,shape)) , maxshape=(None,shape), chunks=True)
                                 ds.append(ds0)
                                 data.append([])
                                 i += 1
                     fp.flush()
                     fp.close()
                     log.log('creating file: {}'.format(filename), 'Writing')
                     self.filename = filename
                     self.ds = ds
                     self.data = data
                     self.firsttime = True
                     self.blockIndex = 0
                     return
                 def putData(self):
                     if self.blockIndex == self.blocksPerFile or self.timeFlag():
                         self.setNextFile()
                     self.readBlock()
                     self.setBlock()     #Prepare data to be written
                     self.writeBlock()   #Write data
                     return
                 def readBlock(self):
                     '''
                     data Array configured
                     self.data
                     '''
                     dsList = self.dsList
                     ds = self.ds
                             #Setting HDF5 File
                     fp = h5py.File(self.filename,'r+')
                     grp = fp["Data"]
                     ind = 0
                     while ind < len(dsList):
                         dsInfo = dsList[ind]
                         if dsInfo['mode'] == 0:
                             ds0 = grp[dsInfo['variable']]
                             ds[ind] = ds0
                             ind += 1
                         else:
                             grp0 = grp[dsInfo['variable']]
                             for j in range(dsInfo['dsNumber']):
                                 dsInfo = dsList[ind]
                                 ds0 = grp0[dsInfo['dsName']]
                                 ds[ind] = ds0
                                 ind += 1
                     self.fp = fp
                     self.grp = grp
                     self.ds = ds
                     return
                 def setBlock(self):
                     '''
                     data Array configured
                     self.data
                     '''
                     #Creating Arrays
                     dsList = self.dsList
                     data = self.data
                     ind = 0
+                    #print("dsList              ",dsList)
+                    #print("len                 ",len(dsList))
                     while ind < len(dsList):
                         dsInfo = dsList[ind]
                         dataAux = getattr(self.dataOut, dsInfo['variable'])
                         mode = dsInfo['mode']
                         nDim = dsInfo['nDim']
                         if mode == 0 or mode == 2 or nDim == 1:
                             data[ind] = dataAux
                             ind += 1
              #             elif nDim == 1:
              #                 data[ind] = numpy.reshape(dataAux,(numpy.size(dataAux),1))
              #                 ind += 1
                         elif nDim == 2:
                             for j in range(dsInfo['dsNumber']):
                                 data[ind] = dataAux[j,:]
                                 ind += 1
                         elif nDim == 3:
                             for j in range(dsInfo['dsNumber']):
                                 data[ind] = dataAux[:,j,:]
                                 ind += 1
                     self.data = data
                     return
                 def writeBlock(self):
                     '''
                     Saves the block in the HDF5 file
                     '''
                     dsList = self.dsList
                     for i in range(len(self.ds)):
+                        print("#############", i , "#######################")
                         dsInfo = dsList[i]
                         nDim = dsInfo['nDim']
                         mode = dsInfo['mode']
+                        print("dsInfo",dsInfo)
+                        print("nDim",nDim)
+                        print("mode",mode)
                         #    First time
                         if self.firsttime:
+                            print("ENTRE FIRSTIME")
                             if type(self.data[i]) == numpy.ndarray:
                                 if nDim == 3:
+                                    print("xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
+                                    print("ndim","dentro del primer if 3")
                                     self.data[i] = self.data[i].reshape((self.data[i].shape[0],self.data[i].shape[1],1))
+                                    print(self.data[i].shape)
+                                    print(type(self.data[i]))
                                     self.ds[i].resize(self.data[i].shape)
+                                    print(self.ds[i].shape)
+                                    print(type(self.ds[i]))
                                 if mode == 2:
                                     self.ds[i].resize(self.data[i].shape)
-                            self.ds[i][:] = self.data[i]
+                            try:
-                        else:
+                                print("PTM ODIO ESTO")
+                                print(self.ds[i][:].shape)
+                                self.ds[i][:] = self.data[i]
+                                print("*****___________********______******")
+                            except:
+                                print("q habra pasaado")
+                                return
+                            print("LLEGUE Y CUMPLI EL IF")
+                        else:
+                            print("ELSE -----------------------")
                         #    From second time
                             #    Meteors!
                             if mode == 2:
                                 dataShape = self.data[i].shape
                                 dsShape = self.ds[i].shape
                                 self.ds[i].resize((self.ds[i].shape[0] + dataShape[0],self.ds[i].shape[1]))
                                 self.ds[i][dsShape[0]:,:] = self.data[i]
                             #    No dimension
                             elif mode == 0:
                                 self.ds[i].resize((self.ds[i].shape[0], self.ds[i].shape[1] + 1))
                                 self.ds[i][0,-1] = self.data[i]
                             #    One dimension
                             elif nDim == 1:
                                 self.ds[i].resize((self.ds[i].shape[0] + 1, self.ds[i].shape[1]))
                                 self.ds[i][-1,:] = self.data[i]
                             #    Two dimension
                             elif nDim == 2:
                                 self.ds[i].resize((self.ds[i].shape[0] + 1,self.ds[i].shape[1]))
                                 self.ds[i][self.blockIndex,:] = self.data[i]
                             #    Three dimensions
                             elif nDim == 3:
                                 self.ds[i].resize((self.ds[i].shape[0],self.ds[i].shape[1],self.ds[i].shape[2]+1))
                                 self.ds[i][:,:,-1] = self.data[i]
                     self.firsttime = False
                     self.blockIndex += 1
+                    print("HOLA AMIGOS COMO ESTAN LLEGUE")
+                    print("xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
                     #Close to save changes
                     self.fp.flush()
                     self.fp.close()
                     return
                 def run(self, dataOut, path, blocksPerFile=10, metadataList=None, dataList=None, mode=None, setType=None):
                     self.dataOut = dataOut
                     if not(self.isConfig):
                         self.setup(dataOut, path=path, blocksPerFile=blocksPerFile,
                                    metadataList=metadataList, dataList=dataList, mode=mode,
                                    setType=setType)
                         self.isConfig = True
                         self.setNextFile()
                     self.putData()
                     return
             @MPDecorator
             class ParameterReader(Reader, ProcessingUnit):
                 '''
                 Reads HDF5 format files
                 '''
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Parameters()
                     self.ext = ".hdf5"
                     self.optchar = "D"
                     self.timezone = "lt"
                     self.listMetaname = []
                     self.listMeta = []
                     self.listDataname = []
                     self.listData = []
                     self.listShapes = []
                     self.open_file = h5py.File
                     self.open_mode = 'r'
                     self.metadata = False
                     self.filefmt = "*%Y%j***"
                     self.folderfmt = "*%Y%j"
                 def setup(self, **kwargs):
                     self.set_kwargs(**kwargs)
                     if not self.ext.startswith('.'):
                         self.ext = '.{}'.format(self.ext)
                     if self.online:
                         log.log("Searching files in online mode...", self.name)
                         for nTries in range(self.nTries):
                             fullpath = self.searchFilesOnLine(self.path, self.startDate,
                                 self.endDate, self.expLabel, self.ext, self.walk,
                                 self.filefmt, self.folderfmt)
                             try:
                                 fullpath = next(fullpath)
                             except:
                                 fullpath = None
                             if fullpath:
                                 break
                             log.warning(
                                 'Waiting {} sec for a valid file in {}: try {} ...'.format(
                                     self.delay, self.path, nTries + 1),
                                 self.name)
                             time.sleep(self.delay)
                         if not(fullpath):
                             raise schainpy.admin.SchainError(
                                 'There isn\'t any valid file in {}'.format(self.path))
                         pathname, filename = os.path.split(fullpath)
                         self.year = int(filename[1:5])
                         self.doy = int(filename[5:8])
                         self.set = int(filename[8:11]) - 1
                     else:
                         log.log("Searching files in {}".format(self.path), self.name)
                         self.filenameList = self.searchFilesOffLine(self.path, self.startDate,
                             self.endDate, self.expLabel, self.ext, self.walk, self.filefmt, self.folderfmt)
                     self.setNextFile()
                     return
                 def readFirstHeader(self):
                     '''Read metadata and data'''
                     self.__readMetadata()
                     self.__readData()
                     self.__setBlockList()
                     self.blockIndex = 0
                     return
                 def __setBlockList(self):
                     '''
                     Selects the data within the times defined
                     self.fp
                     self.startTime
                     self.endTime
                     self.blockList
                     self.blocksPerFile
                     '''
                     startTime = self.startTime
                     endTime = self.endTime
                     index = self.listDataname.index('utctime')
                     thisUtcTime = self.listData[index]
                     self.interval = numpy.min(thisUtcTime[1:] - thisUtcTime[:-1])
                     if self.timezone == 'lt':
                         thisUtcTime -= 5*3600
                     thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate,startTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate,endTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     ind = numpy.where(numpy.logical_and(thisUtcTime >= startUtcTime, thisUtcTime < endUtcTime))[0]
                     self.blockList = ind
                     self.blocksPerFile = len(ind)
                     return
                 def __readMetadata(self):
                     '''
                     Reads Metadata
                     '''
                     listMetaname = []
                     listMetadata = []
                     if 'Metadata' in self.fp:
                         gp = self.fp['Metadata']
                         for item in list(gp.items()):
                             name = item[0]
                             if name=='variables':
                                 table = gp[name][:]
                                 listShapes = {}
                                 for shapes in table:
                                     listShapes[shapes[0].decode()] = numpy.array([shapes[1]])
                             else:
                                 data = gp[name].value
                                 listMetaname.append(name)
                                 listMetadata.append(data)
                     elif self.metadata:
                         metadata = json.loads(self.metadata)
                         listShapes = {}
                         for tup in metadata:
                             name, values, dim = tup
                             if dim == -1:
                                 listMetaname.append(name)
                                 listMetadata.append(self.fp[values].value)
                             else:
                                 listShapes[name] = numpy.array([dim])
                     else:
                         raise IOError('Missing Metadata group in file or metadata info')
                     self.listShapes = listShapes
                     self.listMetaname = listMetaname
                     self.listMeta = listMetadata
                     return
                 def __readData(self):
                     listdataname = []
                     listdata = []
                     if 'Data' in self.fp:
                         grp = self.fp['Data']
                         for item in list(grp.items()):
                             name = item[0]
                             listdataname.append(name)
                             dim = self.listShapes[name][0]
                             if dim == 0:
                                 array = grp[name].value
                             else:
                                 array = []
                                 for i in range(dim):
                                     array.append(grp[name]['table{:02d}'.format(i)].value)
                                 array = numpy.array(array)
                             listdata.append(array)
                     elif self.metadata:
                         metadata = json.loads(self.metadata)
                         for tup in metadata:
                             name, values, dim = tup
                             listdataname.append(name)
                             if dim == -1:
                                 continue
                             elif dim == 0:
                                 array = self.fp[values].value
                             else:
                                 array = []
                                 for var in values:
                                     array.append(self.fp[var].value)
                                 array = numpy.array(array)
                             listdata.append(array)
                     else:
                         raise IOError('Missing Data group in file or metadata info')
                     self.listDataname = listdataname
                     self.listData = listdata
                     return
                 def getData(self):
                     for i in range(len(self.listMeta)):
                         setattr(self.dataOut, self.listMetaname[i], self.listMeta[i])
                     for j in range(len(self.listData)):
                         dim = self.listShapes[self.listDataname[j]][0]
                         if dim == 0:
                             setattr(self.dataOut, self.listDataname[j], self.listData[j][self.blockIndex])
                         else:
                             setattr(self.dataOut, self.listDataname[j], self.listData[j][:,self.blockIndex])
                     self.dataOut.paramInterval = self.interval
                     self.dataOut.flagNoData = False
                     self.blockIndex += 1
                     return
                 def run(self, **kwargs):
                     if not(self.isConfig):
                         self.setup(**kwargs)
                         self.isConfig = True
                     if self.blockIndex == self.blocksPerFile:
                         self.setNextFile()
                     self.getData()
                     return
             @MPDecorator
             class ParameterWriter(Operation):
                 '''
                 HDF5 Writer, stores parameters data in HDF5 format files
                 path:             path where the files will be stored
                 blocksPerFile:    number of blocks that will be saved in per HDF5 format file
                 mode:             selects the data stacking mode: '0' channels, '1' parameters, '3' table (for meteors)
                 metadataList:     list of attributes that will be stored as metadata
                 dataList:         list of attributes that will be stores as data
                 '''
                 ext = ".hdf5"
                 optchar = "D"
                 metaoptchar = "M"
                 metaFile = None
                 filename = None
                 path = None
                 setFile = None
                 fp = None
                 grp = None
                 ds = None
                 firsttime = True
                 #Configurations
                 blocksPerFile = None
                 blockIndex = None
                 dataOut = None
                 #Data Arrays
                 dataList = None
                 metadataList = None
                 dsList = None   #List of dictionaries with dataset properties
                 tableDim = None
                 dtype = [('name', 'S20'),('nDim', 'i')]
                 currentDay = None
                 lastTime = None
                 def __init__(self):
                     Operation.__init__(self)
                     return
                 def setup(self, path=None, blocksPerFile=10, metadataList=None, dataList=None, setType=None):
                     self.path = path
                     self.blocksPerFile = blocksPerFile
                     self.metadataList = metadataList
                     self.dataList = dataList
                     self.setType = setType
                     tableList = []
                     dsList = []
                     for i in range(len(self.dataList)):
                         dsDict = {}
                         dataAux = getattr(self.dataOut, self.dataList[i])
                         dsDict['variable'] = self.dataList[i]
                         if dataAux is None:
                             continue
                         elif isinstance(dataAux, (int, float, numpy.integer, numpy.float)):
                             dsDict['nDim'] = 0
                         else:
                             dsDict['nDim'] = len(dataAux.shape)
                             dsDict['shape'] = dataAux.shape
                             dsDict['dsNumber'] = dataAux.shape[0]
                         dsList.append(dsDict)
                         tableList.append((self.dataList[i], dsDict['nDim']))
                     self.dsList = dsList
                     self.tableDim = numpy.array(tableList, dtype=self.dtype)
                     self.currentDay = self.dataOut.datatime.date()
                 def timeFlag(self):
                     currentTime = self.dataOut.utctime
                     timeTuple = time.localtime(currentTime)
                     dataDay = timeTuple.tm_yday
                     if self.lastTime is None:
                         self.lastTime = currentTime
                         self.currentDay = dataDay
                         return False
                     timeDiff = currentTime - self.lastTime
                     #Si el dia es diferente o si la diferencia entre un dato y otro supera la hora
                     if dataDay != self.currentDay:
                         self.currentDay = dataDay
                         return True
                     elif timeDiff > 3*60*60:
                         self.lastTime = currentTime
                         return True
                     else:
                         self.lastTime = currentTime
                         return False
                 def run(self, dataOut, path, blocksPerFile=10, metadataList=None, dataList=None, setType=None):
                     self.dataOut = dataOut
                     if not(self.isConfig):
                         self.setup(path=path, blocksPerFile=blocksPerFile,
                                    metadataList=metadataList, dataList=dataList,
                                    setType=setType)
                         self.isConfig = True
                         self.setNextFile()
                     self.putData()
                     return
                 def setNextFile(self):
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join(path, subfolder)
                     if os.path.exists(fullpath):
                         filesList = os.listdir(fullpath)
                         filesList = [k for k in filesList if k.startswith(self.optchar)]
                         if len( filesList ) > 0:
                             filesList = sorted(filesList, key=str.lower)
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber(filen[8:11]):
                                 setFile = int(filen[8:11]) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     else:
                         os.makedirs(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.optchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     self.filename = os.path.join( path, subfolder, file )
                     #Setting HDF5 File
                     self.fp = h5py.File(self.filename, 'w')
                     #write metadata
                     self.writeMetadata(self.fp)
                     #Write data
                     self.writeData(self.fp)
                 def writeMetadata(self, fp):
                     grp = fp.create_group("Metadata")
                     grp.create_dataset('variables', data=self.tableDim, dtype=self.dtype)
                     for i in range(len(self.metadataList)):
                         if not hasattr(self.dataOut, self.metadataList[i]):
                             log.warning('Metadata: `{}` not found'.format(self.metadataList[i]), self.name)
                             continue
                         value = getattr(self.dataOut, self.metadataList[i])
                         grp.create_dataset(self.metadataList[i], data=value)
                     return
                 def writeData(self, fp):
                     grp = fp.create_group("Data")
                     dtsets = []
                     data = []
                     for dsInfo in self.dsList:
                         if dsInfo['nDim'] == 0:
                             ds = grp.create_dataset(
                                 dsInfo['variable'],
                                 (self.blocksPerFile, ),
                                 chunks=True,
                                 dtype=numpy.float64)
                             dtsets.append(ds)
                             data.append((dsInfo['variable'], -1))
                         else:
                             sgrp = grp.create_group(dsInfo['variable'])
                             for i in range(dsInfo['dsNumber']):
                                 ds = sgrp.create_dataset(
                                     'table{:02d}'.format(i),
                                     (self.blocksPerFile, ) + dsInfo['shape'][1:],
                                     chunks=True)
                                 dtsets.append(ds)
                                 data.append((dsInfo['variable'], i))
                     fp.flush()
                     log.log('Creating file: {}'.format(fp.filename), self.name)
                     self.ds = dtsets
                     self.data = data
                     self.firsttime = True
                     self.blockIndex = 0
                     return
                 def putData(self):
                     if (self.blockIndex == self.blocksPerFile) or self.timeFlag():
                         self.closeFile()
                         self.setNextFile()
                     for i, ds in enumerate(self.ds):
+                        print(i,ds)
                         attr, ch = self.data[i]
                         if ch == -1:
                             ds[self.blockIndex] = getattr(self.dataOut, attr)
                         else:
+                            print(ch, getattr(self.dataOut, attr).shape)
                             ds[self.blockIndex] = getattr(self.dataOut, attr)[ch]
                     self.fp.flush()
                     self.blockIndex += 1
                     log.log('Block No. {}/{}'.format(self.blockIndex, self.blocksPerFile), self.name)
                     return
                 def closeFile(self):
                     if self.blockIndex != self.blocksPerFile:
                         for ds in self.ds:
                             ds.resize(self.blockIndex, axis=0)
                     self.fp.flush()
                     self.fp.close()
                 def close(self):
                     self.closeFile()

schainpy/model/proc/jroproc_parameters.py 0 0

	1	NO CONTENT: modified file			NO CONTENT: modified file
The requested commit or file is too big and content was truncated. Show full diff

schainpy/model/proc/jroproc_spectra.py +241 -37

             import itertools
             import numpy
             from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation
             from schainpy.model.data.jrodata import Spectra
             from schainpy.model.data.jrodata import hildebrand_sekhon
             from schainpy.utils import log
             @MPDecorator
             class SpectraProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.buffer = None
                     self.firstdatatime = None
                     self.profIndex = 0
                     self.dataOut = Spectra()
                     self.id_min = None
                     self.id_max = None
                     self.setupReq = False #Agregar a todas las unidades de proc
                 def __updateSpecFromVoltage(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
                     try:
                         self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy()
                     except:
                         pass
                     self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
                     self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')])
                     self.dataOut.nBaud = self.dataIn.nBaud
                     self.dataOut.nCode = self.dataIn.nCode
                     self.dataOut.code = self.dataIn.code
                     self.dataOut.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.firstdatatime
                     # asumo q la data esta decodificada
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData
                     # asumo q la data esta sin flip
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.realtime = self.dataIn.realtime
                     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
                 def __getFft(self):
                     """
                     Convierte valores de Voltaje a Spectra
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                         self.profIndex
                         self.buffer
                         self.dataOut.flagNoData
                     """
                     fft_volt = numpy.fft.fft(
                         self.buffer, n=self.dataOut.nFFTPoints, axis=1)
                     fft_volt = fft_volt.astype(numpy.dtype('complex'))
                     dc = fft_volt[:, 0, :]
                     # calculo de self-spectra
                     fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
                     spc = fft_volt * numpy.conjugate(fft_volt)
                     spc = spc.real
                     blocksize = 0
                     blocksize += dc.size
                     blocksize += spc.size
+                    #print("spc                                   :",spc.shape)
+                    data_wr = None
+                    if self.dataOut.flagWR:
+                        data_wr   = fft_volt
+                        blocksize = fft_volt.size
                     cspc = None
                     pairIndex = 0
                     if self.dataOut.pairsList != None:
                         # calculo de cross-spectra
                         cspc = numpy.zeros(
                             (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
                         for pair in self.dataOut.pairsList:
                             if pair[0] not in self.dataOut.channelList:
                                 raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % (
                                     str(pair), str(self.dataOut.channelList)))
                             if pair[1] not in self.dataOut.channelList:
                                 raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % (
                                     str(pair), str(self.dataOut.channelList)))
                             cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \
                                 numpy.conjugate(fft_volt[pair[1], :, :])
                             pairIndex += 1
                         blocksize += cspc.size
-                    self.dataOut.data_spc = spc
+                    self.dataOut.data_spc     = spc
-                    self.dataOut.data_cspc = cspc
+                    self.dataOut.data_cspc    = cspc
-                    self.dataOut.data_dc = dc
+                    self.dataOut.data_wr      = data_wr
-                    self.dataOut.blockSize = blocksize
+                    self.dataOut.data_dc      = dc
+                    self.dataOut.blockSize    = blocksize
                     self.dataOut.flagShiftFFT = False
-                def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None, shift_fft=False):
+                def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None, shift_fft=False,flagWR= 0):
+                    self.dataOut.flagWR = flagWR
                     if self.dataIn.type == "Spectra":
                         self.dataOut.copy(self.dataIn)
                         if shift_fft:
                             #desplaza a la derecha en el eje 2 determinadas posiciones
                             shift = int(self.dataOut.nFFTPoints/2)
                             self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1)
                             if self.dataOut.data_cspc is not None:
                                 #desplaza a la derecha en el eje 2 determinadas posiciones
                                 self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1)
                         return True
                     if self.dataIn.type == "Voltage":
+                        #print("VOLTAGE INPUT SPECTRA")
                         self.dataOut.flagNoData = True
                         if nFFTPoints == None:
                             raise ValueError("This SpectraProc.run() need nFFTPoints input variable")
                         if nProfiles == None:
                             nProfiles = nFFTPoints
                         if ippFactor == None:
                             ippFactor = 1
                         self.dataOut.ippFactor = ippFactor
                         self.dataOut.nFFTPoints = nFFTPoints
                         self.dataOut.pairsList = pairsList
                         if self.buffer is None:
                             self.buffer = numpy.zeros((self.dataIn.nChannels,
                                                        nProfiles,
                                                        self.dataIn.nHeights),
                                                       dtype='complex')
+                            #print("buffer                            :",self.buffer.shape)
                         if self.dataIn.flagDataAsBlock:
                             nVoltProfiles = self.dataIn.data.shape[1]
                             if nVoltProfiles == nProfiles:
                                 self.buffer = self.dataIn.data.copy()
                                 self.profIndex = nVoltProfiles
                             elif nVoltProfiles < nProfiles:
                                 if self.profIndex == 0:
                                     self.id_min = 0
                                     self.id_max = nVoltProfiles
                                 self.buffer[:, self.id_min:self.id_max,
                                             :] = self.dataIn.data
                                 self.profIndex += nVoltProfiles
                                 self.id_min += nVoltProfiles
                                 self.id_max += nVoltProfiles
                             else:
                                 raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % (
                                     self.dataIn.type, self.dataIn.data.shape[1], nProfiles))
                                 self.dataOut.flagNoData = True
                                 return 0
                         else:
+                            #print("Spectra ",self.profIndex)
                             self.buffer[:, self.profIndex, :] = self.dataIn.data.copy()
                             self.profIndex += 1
                         if self.firstdatatime == None:
                             self.firstdatatime = self.dataIn.utctime
                         if self.profIndex == nProfiles:
                             self.__updateSpecFromVoltage()
                             self.__getFft()
+                            #print(" DATAOUT SHAPE SPEC",self.dataOut.data_spc.shape)
                             self.dataOut.flagNoData = False
                             self.firstdatatime = None
                             self.profIndex = 0
                         return True
                     raise ValueError("The type of input object '%s' is not valid" % (
                         self.dataIn.type))
                 def __selectPairs(self, pairsList):
                     if not pairsList:
                         return
                     pairs = []
                     pairsIndex = []
                     for pair in pairsList:
                         if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList:
                             continue
                         pairs.append(pair)
                         pairsIndex.append(pairs.index(pair))
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex]
                     self.dataOut.pairsList = pairs
                     return
                 def __selectPairsByChannel(self, channelList=None):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for pairIndex in self.dataOut.pairsIndexList:
                         # First pair
                         if self.dataOut.pairsList[pairIndex][0] not in channelList:
                             continue
                         # Second pair
                         if self.dataOut.pairsList[pairIndex][1] not in channelList:
                             continue
                         pairsIndexListSelected.append(pairIndex)
                     if not pairsIndexListSelected:
                         self.dataOut.data_cspc = None
                         self.dataOut.pairsList = []
                         return
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
                     self.dataOut.pairsList = [self.dataOut.pairsList[i]
                                               for i in pairsIndexListSelected]
                     return
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError("Error selecting channels, Channel %d is not valid.\nAvailable channels = %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_spc
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError("Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " % (
                                 channelIndex, self.dataOut.channelIndexList))
                     data_spc = self.dataOut.data_spc[channelIndexList, :]
                     data_dc = self.dataOut.data_dc[channelIndexList, :]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_dc = data_dc
                     # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                     self.dataOut.channelList = range(len(channelIndexList))
                     self.__selectPairsByChannel(channelIndexList)
                     return 1
                 def selectFFTs(self, minFFT, maxFFT ):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango
                     minFFT<= FFT <= maxFFT
                     """
                     if (minFFT > maxFFT):
                         raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT))
                     if (minFFT < self.dataOut.getFreqRange()[0]):
                         minFFT = self.dataOut.getFreqRange()[0]
                     if (maxFFT > self.dataOut.getFreqRange()[-1]):
                         maxFFT = self.dataOut.getFreqRange()[-1]
                     minIndex = 0
                     maxIndex = 0
                     FFTs = self.dataOut.getFreqRange()
                     inda = numpy.where(FFTs >= minFFT)
                     indb = numpy.where(FFTs <= maxFFT)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(FFTs)
                     self.selectFFTsByIndex(minIndex, maxIndex)
                     return 1
                 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 selectHeights(self, minHei, maxHei):
                     """
                     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 > maxHei):
                         raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei))
                     if (minHei < self.dataOut.heightList[0]):
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
                     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 getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None):
                     newheis = numpy.where(
                         self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex])
                     if hei_ref != None:
                         newheis = numpy.where(self.dataOut.heightList > hei_ref)
                     minIndex = min(newheis[0])
                     maxIndex = max(newheis[0])
                     data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1]
                     heightList = self.dataOut.heightList[minIndex:maxIndex + 1]
                     # determina indices
                     nheis = int(self.dataOut.radarControllerHeaderObj.txB /
                                 (self.dataOut.heightList[1] - self.dataOut.heightList[0]))
                     avg_dB = 10 * \
                         numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0))
                     beacon_dB = numpy.sort(avg_dB)[-nheis:]
                     beacon_heiIndexList = []
                     for val in avg_dB.tolist():
                         if val >= beacon_dB[0]:
                             beacon_heiIndexList.append(avg_dB.tolist().index(val))
                     #data_spc = data_spc[:,:,beacon_heiIndexList]
                     data_cspc = None
                     if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
                         #data_cspc = data_cspc[:,:,beacon_heiIndexList]
                     data_dc = None
                     if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
                         #data_dc = data_dc[:,beacon_heiIndexList]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = heightList
                     self.dataOut.beacon_heiIndexList = beacon_heiIndexList
                     return 1
                 def selectFFTsByIndex(self, minIndex, maxIndex):
                     """
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex))
                     if (maxIndex >= self.dataOut.nProfiles):
                         maxIndex = self.dataOut.nProfiles-1
                     #Spectra
                     data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:]
                     data_cspc = None
                     if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:]
                     data_dc = None
                     if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1])
                     self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1]
                     self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1]
                     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_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (
                             minIndex, maxIndex))
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights - 1
                     # Spectra
                     data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1]
                     data_cspc = None
                     if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
                     data_dc = None
                     if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1]
                     return 1
                 def removeDC(self, mode=2):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
                     if jcspectra is not None:
                         jcspectraExist = True
                         num_pairs = jcspectra.shape[0]
                     else:
                         jcspectraExist = False
                     freq_dc = int(jspectra.shape[1] / 2)
                     ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc
                     ind_vel = ind_vel.astype(int)
                     if ind_vel[0] < 0:
                         ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof
                     if mode == 1:
                         jspectra[:, freq_dc, :] = (
                             jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2  # CORRECCION
                         if jcspectraExist:
                             jcspectra[:, freq_dc, :] = (
                                 jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2
                     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(list(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
                         if jcspectraExist:
                             for ip in range(num_pairs):
                                 yy = jcspectra[ip, ind_vel, :]
                                 jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy)
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def removeInterference2(self):
                     cspc = self.dataOut.data_cspc
                     spc = self.dataOut.data_spc
                     Heights = numpy.arange(cspc.shape[2])
                     realCspc = numpy.abs(cspc)
                     for i in range(cspc.shape[0]):
                         LinePower= numpy.sum(realCspc[i], axis=0)
                         Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)]
                         SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ]
                         InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 )
                         InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)]
                         InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)]
                         InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) )
                         #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax]))
                         if len(InterferenceRange)<int(cspc.shape[1]*0.3):
                             cspc[i,InterferenceRange,:] = numpy.NaN
                     self.dataOut.data_cspc = cspc
                 def removeInterference(self,  interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     jnoise = self.dataOut.getNoise()
                     num_incoh = self.dataOut.nIncohInt
                     num_channel = jspectra.shape[0]
                     num_prof = jspectra.shape[1]
                     num_hei = jspectra.shape[2]
                     # hei_interf
                     if hei_interf is None:
                         count_hei = int(num_hei / 2)
                         hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei
                         hei_interf = numpy.asarray(hei_interf)[0]
                     # nhei_interf
                     if (nhei_interf == None):
                         nhei_interf = 5
                     if (nhei_interf < 1):
                         nhei_interf = 1
                     if (nhei_interf > count_hei):
                         nhei_interf = count_hei
                     if (offhei_interf == None):
                         offhei_interf = 0
                     ind_hei = list(range(num_hei))
             #         mask_prof = numpy.asarray(range(num_prof - 2)) + 1
             #         mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
                     mask_prof = numpy.asarray(list(range(num_prof)))
                     num_mask_prof = mask_prof.size
                     comp_mask_prof = [0, num_prof / 2]
                     # noise_exist:    Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
                     if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
                         jnoise = numpy.nan
                     noise_exist = jnoise[0] < numpy.Inf
                     # Subrutina de Remocion de la Interferencia
                     for ich in range(num_channel):
                         # Se ordena los espectros segun su potencia (menor a mayor)
                         power = jspectra[ich, mask_prof, :]
                         power = power[:, hei_interf]
                         power = power.sum(axis=0)
                         psort = power.ravel().argsort()
                         # Se estima la interferencia promedio en los Espectros de Potencia empleando
                         junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range(
                             offhei_interf, nhei_interf + offhei_interf))]]]
                         if noise_exist:
                             #    tmp_noise = jnoise[ich] / num_prof
                             tmp_noise = jnoise[ich]
                         junkspc_interf = junkspc_interf - tmp_noise
                         #junkspc_interf[:,comp_mask_prof] = 0
                         jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf
                         jspc_interf = jspc_interf.transpose()
                         # Calculando el espectro de interferencia promedio
                         noiseid = numpy.where(
                             jspc_interf <= tmp_noise / numpy.sqrt(num_incoh))
                         noiseid = noiseid[0]
                         cnoiseid = noiseid.size
                         interfid = numpy.where(
                             jspc_interf > tmp_noise / numpy.sqrt(num_incoh))
                         interfid = interfid[0]
                         cinterfid = interfid.size
                         if (cnoiseid > 0):
                             jspc_interf[noiseid] = 0
                         # Expandiendo los perfiles a limpiar
                         if (cinterfid > 0):
                             new_interfid = (
                                 numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof
                             new_interfid = numpy.asarray(new_interfid)
                             new_interfid = {x for x in new_interfid}
                             new_interfid = numpy.array(list(new_interfid))
                             new_cinterfid = new_interfid.size
                         else:
                             new_cinterfid = 0
                         for ip in range(new_cinterfid):
                             ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort()
                             jspc_interf[new_interfid[ip]
                                         ] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]]
                         jspectra[ich, :, ind_hei] = jspectra[ich, :,
                                                              ind_hei] - jspc_interf  # Corregir indices
                         # Removiendo la interferencia del punto de mayor interferencia
                         ListAux = jspc_interf[mask_prof].tolist()
                         maxid = ListAux.index(max(ListAux))
                         if cinterfid > 0:
                             for ip in range(cinterfid * (interf == 2) - 1):
                                 ind = (jspectra[ich, interfid[ip], :] < tmp_noise *
                                        (1 + 1 / numpy.sqrt(num_incoh))).nonzero()
                                 cind = len(ind)
                                 if (cind > 0):
                                     jspectra[ich, interfid[ip], ind] = tmp_noise * \
                                         (1 + (numpy.random.uniform(cind) - 0.5) /
                                          numpy.sqrt(num_incoh))
                             ind = numpy.array([-2, -1, 1, 2])
                             xx = numpy.zeros([4, 4])
                             for id1 in range(4):
                                 xx[:, id1] = ind[id1]**numpy.asarray(list(range(4)))
                             xx_inv = numpy.linalg.inv(xx)
                             xx = xx_inv[:, 0]
                             ind = (ind + maxid + num_mask_prof) % num_mask_prof
                             yy = jspectra[ich, mask_prof[ind], :]
                             jspectra[ich, mask_prof[maxid], :] = numpy.dot(
                                 yy.transpose(), xx)
                         indAux = (jspectra[ich, :, :] < tmp_noise *
                                   (1 - 1 / numpy.sqrt(num_incoh))).nonzero()
                         jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \
                             (1 - 1 / numpy.sqrt(num_incoh))
                     # Remocion de Interferencia en el Cross Spectra
                     if jcspectra is None:
                         return jspectra, jcspectra
                     num_pairs = int(jcspectra.size / (num_prof * num_hei))
                     jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
                     for ip in range(num_pairs):
                         #-------------------------------------------
                         cspower = numpy.abs(jcspectra[ip, mask_prof, :])
                         cspower = cspower[:, hei_interf]
                         cspower = cspower.sum(axis=0)
                         cspsort = cspower.ravel().argsort()
                         junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range(
                             offhei_interf, nhei_interf + offhei_interf))]]]
                         junkcspc_interf = junkcspc_interf.transpose()
                         jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf
                         ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
                         median_real = int(numpy.median(numpy.real(
                             junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :])))
                         median_imag = int(numpy.median(numpy.imag(
                             junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :])))
                         comp_mask_prof = [int(e) for e in comp_mask_prof]
                         junkcspc_interf[comp_mask_prof, :] = numpy.complex(
                             median_real, median_imag)
                         for iprof in range(num_prof):
                             ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort()
                             jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]]
                         # Removiendo la Interferencia
                         jcspectra[ip, :, ind_hei] = jcspectra[ip,
                                                               :, ind_hei] - jcspc_interf
                         ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
                         maxid = ListAux.index(max(ListAux))
                         ind = numpy.array([-2, -1, 1, 2])
                         xx = numpy.zeros([4, 4])
                         for id1 in range(4):
                             xx[:, id1] = ind[id1]**numpy.asarray(list(range(4)))
                         xx_inv = numpy.linalg.inv(xx)
                         xx = xx_inv[:, 0]
                         ind = (ind + maxid + num_mask_prof) % num_mask_prof
                         yy = jcspectra[ip, mask_prof[ind], :]
                         jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx)
                     # Guardar Resultados
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def setRadarFrequency(self, frequency=None):
                     if frequency != None:
                         self.dataOut.frequency = frequency
                     return 1
                 def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
                     # validacion de rango
                     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):
                         print('minHei: %.2f is out of the heights range' % (minHei))
                         print('minHei is setting to %.2f' % (self.dataOut.heightList[0]))
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
                         print('maxHei: %.2f is out of the heights range' % (maxHei))
                         print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1]))
                         maxHei = self.dataOut.heightList[-1]
                     # validacion de velocidades
                     velrange = self.dataOut.getVelRange(1)
                     if minVel == None:
                         minVel = velrange[0]
                     if maxVel == None:
                         maxVel = velrange[-1]
                     if (minVel < velrange[0]) or (minVel > maxVel):
                         print('minVel: %.2f is out of the velocity range' % (minVel))
                         print('minVel is setting to %.2f' % (velrange[0]))
                         minVel = velrange[0]
                     if (maxVel > velrange[-1]) or (maxVel < minVel):
                         print('maxVel: %.2f is out of the velocity range' % (maxVel))
                         print('maxVel is setting to %.2f' % (velrange[-1]))
                         maxVel = velrange[-1]
                     # seleccion de indices para rango
                     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)
                     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 - 1
                     # seleccion de indices para velocidades
                     indminvel = numpy.where(velrange >= minVel)
                     indmaxvel = numpy.where(velrange <= maxVel)
                     try:
                         minIndexVel = indminvel[0][0]
                     except:
                         minIndexVel = 0
                     try:
                         maxIndexVel = indmaxvel[0][-1]
                     except:
                         maxIndexVel = len(velrange)
                     # seleccion del espectro
                     data_spc = self.dataOut.data_spc[:,
                                                      minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1]
                     # estimacion de ruido
                     noise = numpy.zeros(self.dataOut.nChannels)
                     for channel in range(self.dataOut.nChannels):
                         daux = data_spc[channel, :, :]
                         noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
                     self.dataOut.noise_estimation = noise.copy()
                     return 1
             class IncohInt(Operation):
                 __profIndex = 0
                 __withOverapping = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer_spc = None
                 __buffer_cspc = None
                 __buffer_dc = None
                 __dataReady = False
                 __timeInterval = None
                 n = None
                 def __init__(self):
                     Operation.__init__(self)
                 def setup(self, n=None, timeInterval=None, overlapping=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_spc = 0
                     self.__buffer_cspc = 0
                     self.__buffer_dc = 0
                     self.__profIndex = 0
                     self.__dataReady = False
                     self.__byTime = False
                     if n is None and timeInterval is None:
                         raise ValueError("n or timeInterval should be specified ...")
                     if n is not None:
                         self.n = int(n)
                     else:
                         self.__integrationtime = int(timeInterval)
                         self.n = None
                         self.__byTime = True
                 def putData(self, data_spc, data_cspc, data_dc):
                     """
                     Add a profile to the __buffer_spc and increase in one the __profileIndex
                     """
+                    print("profIndex:      ",self.__profIndex)
+                    print("data_spc.shape: ",data_spc.shape)
+                    print("data_spc.shape: ",data_spc[0,0,:])
                     self.__buffer_spc += data_spc
                     if data_cspc is None:
                         self.__buffer_cspc = None
                     else:
                         self.__buffer_cspc += data_cspc
                     if data_dc is None:
                         self.__buffer_dc = None
                     else:
                         self.__buffer_dc += data_dc
                     self.__profIndex += 1
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     data_spc = self.__buffer_spc
                     data_cspc = self.__buffer_cspc
                     data_dc = self.__buffer_dc
                     n = self.__profIndex
                     self.__buffer_spc = 0
                     self.__buffer_cspc = 0
                     self.__buffer_dc = 0
                     self.__profIndex = 0
                     return data_spc, data_cspc, data_dc, n
                 def byProfiles(self, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     self.putData(*args)
                     if self.__profIndex == self.n:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def byTime(self, datatime, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     self.putData(*args)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def integrate(self, datatime, *args):
                     if self.__profIndex == 0:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(
                             datatime, *args)
                     else:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
                     if not self.__dataReady:
                         return None, None, None, None
                     return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
                     if n == 1:
                         return
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(n, timeInterval, overlapping)
                         self.isConfig = True
                     avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
                                                                                         dataOut.data_spc,
                                                                                         dataOut.data_cspc,
                                                                                         dataOut.data_dc)
                     if self.__dataReady:
                         dataOut.data_spc = avgdata_spc
                         dataOut.data_cspc = avgdata_cspc
                         dataOut.data_dc = avgdata_dc
                         dataOut.nIncohInt *= self.n
                         dataOut.utctime = avgdatatime
                         dataOut.flagNoData = False
-                    return dataOut
  No newline at end of file
+                    return dataOut
+            class PulsePair(Operation):
+                isConfig       = False
+                __profIndex    = 0
+                __profIndex2   = 0
+                __initime      = None
+                __lastdatatime = None
+                __buffer       = None
+                __buffer2      = []
+                __buffer3      = None
+                __dataReady    = False
+                n              = None
+                __nch          =0
+                __nProf        =0
+                __nHeis        =0
+                def __init__(self,**kwargs):
+                    Operation.__init__(self,**kwargs)
+                def setup(self,dataOut,n =None, m = None):
+                    self.__initime      = None
+                    self.__lastdatatime = 0
+                    self.__buffer         = 0
+                    self.__bufferV        = 0
+                    #self.__buffer2        = []
+                    self.__buffer3        = 0
+                    self.__dataReady      = False
+                    self.__profIndex      = 0
+                    self.__profIndex2     = 0
+                    self.count            = 0
+                    self.__nch            = dataOut.nChannels
+                    self.__nHeis          = dataOut.nHeights
+                    self.__nProf          = dataOut.nProfiles
+                    self.__nFFT           = dataOut.nFFTPoints
+                    #print("Valores de Ch,Samples,Perfiles,nFFT",self.__nch,self.__nHeis,self.__nProf, self.__nFFT)
+                    #print("EL VALOR DE n es:",n)
+                    if n == None:
+                        raise ValueError("n Should be specified.")
+                    if n != None:
+                        if n<2:
+                            raise ValueError("n Should be greather than 2 ")
+                    self.n                = n
+                    if m == None:
+                        m = n
+                    if m != None:
+                        if  m<2:
+                            raise ValueError("n Should be greather than 2 ")
+                    self.m               = m
+                    self.__buffer2        = numpy.zeros((self.__nch,self.m,self.__nHeis))
+                    self.__bufferV2       = numpy.zeros((self.__nch,self.m,self.__nHeis))
+                def putData(self,data):
+                    #print("###################################################")
+                    '''
+                    data_tmp   =    numpy.zeros(self.__nch,self.n,self.__nHeis, dtype= complex)
+                    if self.count < self.__nProf:
+                        for i in range(self.n):
+                            data_tmp[:,i,:]    =  data[:,i+self.count,:]
+                        self.__buffer          =  data_tmp*numpy.conjugate(data_tmp)
+                    #####self.__buffer          = data*numpy.conjugate(data)
+                    #####self.__bufferV         = data[:,(self.__nProf-1):,:]*numpy.conjugate(data[:,1:,:])
+                    #self.__buffer2.append(numpy.conjugate(data))
+                    #####self.__profIndex        = data.shape[1]
+                    self.count              = self.count + self.n -1
+                    self.__profIndex        = self.n
+                    '''
+                    self.__buffer          = data*numpy.conjugate(data)
+                    self.__bufferV         = data[:,(self.__nProf-1):,:]*numpy.conjugate(data[:,1:,:])
+                    self.__profIndex        = self.n
+                    return
+                def pushData(self):
+                    data_I           = numpy.zeros((self.__nch,self.__nHeis))
+                    data_IV          = numpy.zeros((self.__nch,self.__nHeis))
+                    for i in range(self.__nch):
+                        data_I[i,:]  = numpy.sum(numpy.sum(self.__buffer[i],axis=0),axis=0)/self.n
+                        data_IV[i,:] = numpy.sum(numpy.sum(self.__bufferV[i],axis=0),axis=0)/(self.n-1)
+                    n                = self.__profIndex
+                    ####data_intensity = numpy.sum(numpy.sum(self.__buffer,axis=0),axis=0)/self.n
+                    #print("data_intensity push data",data_intensity.shape)
+                    #data_velocity  = self.__buffer3/(self.n-1)
+                    ####n              = self.__profIndex
+                    self.__buffer    = 0
+                    self.__buffer3   = 0
+                    self.__profIndex = 0
+                    #return data_intensity,data_velocity,n
+                    return data_I,data_IV,n
+                def pulsePairbyProfiles(self,data):
+                    self.__dataReady      = False
+                    data_intensity        = None
+                    data_velocity         = None
+                    self.putData(data)
+                    if self.__profIndex == self.n:
+                        #data_intensity,data_velocity,n = self.pushData()
+                        data_intensity,data_velocity,n = self.pushData()
+                        #print(data_intensity.shape)
+                        #print("self.__profIndex2", self.__profIndex2)
+                        if self.__profIndex2 == 0:
+                            #print("PRIMERA VEZ")
+                            #print("self.__buffer2",self.__buffer2)
+                            for i in range(self.__nch):
+                                self.__buffer2[i][self.__profIndex2]  = data_intensity[i]
+                                self.__bufferV2[i][self.__profIndex2] = data_velocity[i]
+                            self.__profIndex2       += 1
+                            return None,None
+                        if self.__profIndex2 > 0:
+                            for i in range(self.__nch):
+                                self.__buffer2[i][self.__profIndex2]  = data_intensity[i]
+                                self.__bufferV2[i][self.__profIndex2] = data_velocity[i]
+                            #print("Dentro del bucle",self.__buffer2)
+                            self.__profIndex2       += 1
+                            if self.__profIndex2 == self.m :
+                                data_i                         = self.__buffer2
+                                data_v                         = self.__bufferV2
+                                #print(data_i.shape)
+                                self.__dataReady               = True
+                                self.__profIndex2              = 0
+                                self.__buffer2                 = numpy.zeros((self.__nch,self.m,self.__nHeis))
+                                self.__bufferV2                = numpy.zeros((self.__nch,self.m,self.__nHeis))
+                                return data_i,data_v
+                            return  None,None
+                def pulsePairOp(self,data,datatime=None):
+                    if self.__initime == None:
+                        self.__initime = datatime
+                    data_intensity,data_velocity = self.pulsePairbyProfiles(data)
+                    self.__lastdatatime           = datatime
+                    if data_intensity is None:
+                        return None,None,None
+                    avgdatatime    = self.__initime
+                    self.__initime = datatime
+                    return data_intensity,data_velocity,avgdatatime
+                def run(self,dataOut,n =None,m=None):
+                    if not self.isConfig:
+                        self.setup(dataOut = dataOut, n   = n, m = m)
+                        self.isConfig  = True
+                    data_intensity,data_velocity,avgdatatime  = self.pulsePairOp(dataOut.data_wr,dataOut.utctime)
+                    dataOut.flagNoData                          = True
+                    if self.__dataReady:
+                        #print(" DATA " , data_intensity.shape)
+                        #dataOut.data            = numpy.array([data_intensity])#aqui amigo revisa
+                        #tmp                     = numpy.zeros([1,data_intensity.shape[0],data_intensity.shape[1]])
+                        #tmp[0]                  = data_intensity
+                        dataOut.data            = data_intensity
+                        dataOut.data_velocity   = data_velocity
+                        #dataOut.data            = tmp
+                        #print(" DATA " , dataOut.data.shape)
+                        dataOut.nIncohInt      *= self.n
+                        dataOut.nProfiles       = self.m
+                        dataOut.nFFTPoints      = self.m
+                        #dataOut.data_intensity  = data_intensity
+                        dataOut.PRFbyAngle      = self.n
+                        dataOut.utctime         = avgdatatime
+                        dataOut.flagNoData      = False
+                        #####print("TIEMPO:                     ",dataOut.utctime)
+                    return dataOut

schainpy/model/proc/jroproc_voltage.py +315 -20

             import sys
             import numpy
             from scipy import interpolate
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Voltage
             from schainpy.utils import log
             from time import time
             @MPDecorator
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Voltage()
                     self.flip = 1
                     self.setupReq = False
                 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)
                     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.channelList = range(len(channelIndexList))
                     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]):
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
                     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("Height index range (%d,%d) is not valid" % (minIndex, maxIndex))
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights
                     #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:int(self.dataOut.nHeights-r)]
                         buffer = buffer.reshape(self.dataOut.nChannels, self.dataOut.nProfiles, int(self.dataOut.nHeights/window), window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = self.dataOut.data[:,0:int(self.dataOut.nHeights-r)]
                         buffer = buffer.reshape(self.dataOut.nChannels,int(self.dataOut.nHeights/window),int(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 = list(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
                 def interpolateHeights(self, topLim, botLim):
                     #69 al 72 para julia
                     #82-84 para meteoros
                     if len(numpy.shape(self.dataOut.data))==2:
                         sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2
                         sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1)))
                         #self.dataOut.data[:,botLim:limSup+1] = sampInterp
                         self.dataOut.data[:,botLim:topLim+1] = sampInterp
                     else:
                         nHeights = self.dataOut.data.shape[2]
                         x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights)))
                         y = self.dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))]
                         f = interpolate.interp1d(x, y, axis = 2)
                         xnew = numpy.arange(botLim,topLim+1)
                         ynew = f(xnew)
                         self.dataOut.data[:,:,botLim:topLim+1]  = ynew
                 # import collections
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __bufferStride = []
                 __dataReady = False
                 __profIndexStride = 0
                 __dataToPutStride = False
                 n = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     #   self.isConfig = False
                 def setup(self, n=None, timeInterval=None, stride=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
                     self.stride = stride
                     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.__withOverlapping = True
                         self.__buffer = None
                     else:
                         self.__withOverlapping = 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.__withOverlapping:
+                        print("inside over")
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
+                    print("show me the light",data.shape)
                     data = numpy.reshape(data, (1, nChannels, nHeis))
+                    print(data.shape)
                     #If the buffer is empty then it takes the data value
                     if self.__buffer is 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.__withOverlapping:
+                        #print("ahora que fue")
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
+                    #print("cual funciona")
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     # print data
                     # raise
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
                     #         n = None
                     # print data
                     # raise
+                    #print("beforeputdata")
                     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 integrateByStride(self, data, datatime):
                     # print data
                     if self.__profIndex == 0:
                         self.__buffer = [[data.copy(), datatime]]
                     else:
                         self.__buffer.append([data.copy(),datatime])
                     self.__profIndex += 1
                     self.__dataReady = False
                     if self.__profIndex == self.n * self.stride :
                         self.__dataToPutStride = True
                         self.__profIndexStride = 0
                         self.__profIndex = 0
                         self.__bufferStride = []
                         for i in range(self.stride):
                             current = self.__buffer[i::self.stride]
                             data = numpy.sum([t[0] for t in current], axis=0)
                             avgdatatime = numpy.average([t[1] for t in current])
                             # print data
                             self.__bufferStride.append((data, avgdatatime))
                     if self.__dataToPutStride:
                         self.__dataReady = True
                         self.__profIndexStride += 1
                         if self.__profIndexStride == self.stride:
                             self.__dataToPutStride = False
                         # print self.__bufferStride[self.__profIndexStride - 1]
                         # raise
                         return self.__bufferStride[self.__profIndexStride - 1]
                     return None, None
                 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 is None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime - self.__lastdatatime
                     if not self.__withOverlapping:
                         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, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         avgdata, avgdatatime = self.integrateByBlock(dataOut)
                         dataOut.nProfiles /= self.n
                     else:
                         if stride is None:
                             avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
                         else:
                             avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime)
                     #   dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
                         # print avgdata, avgdatatime
                         # raise
                         #   dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
                     return dataOut
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.times = None
                     self.osamp = None
                 #         self.__setValues = False
                     self.isConfig = False
                     self.setupReq = 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 self.__nHeis < self.nBaud:
                         raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud))
                     #Frequency
                     __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))
                     if dataOut.flagDataAsBlock:
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex)
                     else:
                         #Time
                         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)
                     return data
                 def __convolutionInFreqOpt(self, data):
                     raise NotImplementedError
                 def __convolutionInTime(self, data):
                     code = self.code[self.__profIndex]
                     for i in range(self.__nChannels):
                         self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInTime(self, data):
                     repetitions = int(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))
                     profilesList = range(self.__nProfiles)
                     for i in range(self.__nChannels):
                         for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInFreq(self, data):
                     raise NotImplementedError("Decoder by frequency fro Blocks not implemented")
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=2)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=2)
                     return data
                 def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None):
                     if dataOut.flagDecodeData:
                         print("This data is already decoded, recoding again ...")
                     if not self.isConfig:
                         if code is None:
                             if dataOut.code is None:
                                 raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type)
                             code = dataOut.code
                         else:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         self.setup(code, osamp, dataOut)
                         self.isConfig = True
                         if mode == 3:
                             sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode)
                         if times != None:
                             sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n")
                     if self.code is None:
                         print("Fail decoding: Code is not defined.")
                         return
                     self.__nProfiles = dataOut.nProfiles
                     datadec = None
                     if mode == 3:
                         mode = 0
                     if dataOut.flagDataAsBlock:
                         """
                         Decoding when data have been read as block,
                         """
                         if mode == 0:
                             datadec = self.__convolutionByBlockInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionByBlockInFreq(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)
                     if datadec is None:
                         raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode)
                     dataOut.code = self.code
                     dataOut.nCode = self.nCode
                     dataOut.nBaud = self.nBaud
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]]
                     dataOut.flagDecodeData = True #asumo q la data esta decodificada
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return dataOut
                     self.__profIndex += 1
                     return dataOut
                 #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class ProfileConcat(Operation):
                 isConfig = False
                 buffer = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     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.shape[1]#.nHeights
                     self.start_index = 0
                     self.times = 1
                 def concat(self, data):
                     self.buffer[:,self.start_index:self.nHeights*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
                     return dataOut
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def incProfileIndex(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))
                     """
                     if rangeList is not None:
                         if type(rangeList[0]) not in (tuple, list):
                             rangeList = [rangeList]
                     dataOut.flagNoData = True
                     if dataOut.flagDataAsBlock:
                         """
                         data dimension  = [nChannels, nProfiles, nHeis]
                         """
                         if profileList != None:
                             dataOut.data = dataOut.data[:,profileList,:]
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             profileList = list(range(minIndex, maxIndex+1))
                             dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:]
                         if rangeList != None:
                             profileList = []
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 profileList.extend(list(range(minIndex, maxIndex+1)))
                             dataOut.data = dataOut.data[:,profileList,:]
                         dataOut.nProfiles = len(profileList)
                         dataOut.profileIndex = dataOut.nProfiles - 1
                         dataOut.flagNoData = False
                         return dataOut
                     """
                     data dimension  = [nChannels, nHeis]
                     """
                     if profileList != None:
                         if self.isThisProfileInList(dataOut.profileIndex, profileList):
                             self.nProfiles = len(profileList)
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if profileRangeList != None:
                         minIndex = profileRangeList[0]
                         maxIndex = profileRangeList[1]
                         if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                             self.nProfiles = maxIndex - minIndex + 1
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if rangeList != None:
                         nProfiles = 0
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             nProfiles += maxIndex - minIndex + 1
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                                 self.nProfiles = nProfiles
                                 dataOut.nProfiles = self.nProfiles
                                 dataOut.profileIndex = self.profileIndex
                                 dataOut.flagNoData = False
                                 self.incProfileIndex()
                                 break
                         return dataOut
                     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.incProfileIndex()
                         return dataOut
                     raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter")
                     #return False
                     return dataOut
             class Reshaper(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__buffer = None
                     self.__nitems = 0
                 def __appendProfile(self, dataOut, nTxs):
                     if self.__buffer is None:
                         shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) )
                         self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype)
                     ini = dataOut.nHeights * self.__nitems
                     end = ini + dataOut.nHeights
                     self.__buffer[:, ini:end] = dataOut.data
                     self.__nitems += 1
                     return int(self.__nitems*nTxs)
                 def __getBuffer(self):
                     if self.__nitems == int(1./self.__nTxs):
                         self.__nitems = 0
                         return self.__buffer.copy()
                     return None
                 def __checkInputs(self, dataOut, shape, nTxs):
                     if shape is None and nTxs is None:
                         raise ValueError("Reshaper: shape of factor should be defined")
                     if nTxs:
                         if nTxs < 0:
                             raise ValueError("nTxs should be greater than 0")
                         if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0:
                             raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)))
                         shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs]
                         return shape, nTxs
                     if len(shape) != 2 and len(shape) !=  3:
                         raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights))
                     if len(shape) == 2:
                         shape_tuple = [dataOut.nChannels]
                         shape_tuple.extend(shape)
                     else:
                         shape_tuple = list(shape)
                     nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles
                     return shape_tuple, nTxs
                 def run(self, dataOut, shape=None, nTxs=None):
                     shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs)
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         dataOut.data = numpy.reshape(dataOut.data, shape_tuple)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1
                     else:
                         if self.__nTxs < 1:
                             self.__appendProfile(dataOut, self.__nTxs)
                             new_data = self.__getBuffer()
                             if new_data is not None:
                                 dataOut.data = new_data
                                 dataOut.flagNoData = False
                                 profileIndex = dataOut.profileIndex*nTxs
                         else:
                             raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= self.__nTxs
                     return dataOut
             class SplitProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         if shape[2] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]))
                         new_shape = shape[0], shape[1]*n, int(shape[2]/n)
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles/n) - 1
                     else:
                         raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= n
                     return dataOut
             class CombineProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__remData = None
                     self.__profileIndex = 0
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         new_shape = shape[0], shape[1]/n, shape[2]*n
                         if shape[1] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]))
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*n) - 1
                     else:
                         #nchannels, nsamples
                         if self.__remData is None:
                             newData = dataOut.data
                         else:
                             newData = numpy.concatenate((self.__remData, dataOut.data), axis=1)
                         self.__profileIndex += 1
                         if self.__profileIndex < n:
                             self.__remData = newData
                             #continue
                             return
                         self.__profileIndex = 0
                         self.__remData = None
                         dataOut.data = newData
                         dataOut.flagNoData = False
                         profileIndex = dataOut.profileIndex/n
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles/n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds *= n
                     return dataOut
+            class CreateBlockVoltage(Operation):
+                isConfig       = False
+                __Index        = 0
+                bufferShape    = None
+                buffer         = None
+                firstdatatime  = None
+                def __init__(self,**kwargs):
+                    Operation.__init__(self,**kwargs)
+                    self.isConfig = False
+                    self.__Index = 0
+                    self.firstdatatime = None
+                def setup(self,dataOut, m = None ):
+                    '''
+                    m= Numero perfiles
+                    '''
+                    #print("CONFIGURANDO CBV")
+                    self.__nChannels  = dataOut.nChannels
+                    self.__nHeis      = dataOut.nHeights
+                    shape             = dataOut.data.shape #nchannels, nprofiles, nsamples
+                    #print("input nChannels",self.__nChannels)
+                    #print("input nHeis",self.__nHeis)
+                    #print("SETUP CREATE BLOCK VOLTAGE")
+                    #print("input Shape",shape)
+                    #print("dataOut.nProfiles",dataOut.nProfiles)
+                    numberSamples     = self.__nHeis
+                    numberProfile     = int(m)
+                    dataOut.nProfiles = numberProfile
+                    #print("new numberProfile",numberProfile)
+                    #print("new numberSamples",numberSamples)
+                    self.bufferShape  = shape[0], numberProfile, numberSamples  # nchannels,nprofiles,nsamples
+                    self.buffer       = numpy.zeros((self.bufferShape))
+                    self.bufferVel    = numpy.zeros((self.bufferShape))
+                def run(self, dataOut, m=None):
+                    #print("RUN")
+                    dataOut.flagNoData      = True
+                    dataOut.flagDataAsBlock = False
+                    #print("BLOCK INDEX        ",self.__Index)
+                    if not self.isConfig:
+                        self.setup(dataOut, m= m)
+                        self.isConfig = True
+                    if self.__Index < m:
+                        #print("PROFINDEX BLOCK         CBV",self.__Index)
+                        self.buffer[:,self.__Index,:]    = dataOut.data
+                        self.bufferVel[:,self.__Index,:] = dataOut.data_velocity
+                        self.__Index += 1
+                        dataOut.flagNoData =  True
+                    if self.firstdatatime == None:
+                        self.firstdatatime = dataOut.utctime
+                    if self.__Index == m:
+                        #print("**********************************************")
+                        #print("self.buffer.shape           ",self.buffer.shape)
+                        #print("##############",self.firstdatatime)
+                        ##print("*********************************************")
+                        ##print("*********************************************")
+                        ##print("******* nProfiles *******", dataOut.nProfiles)
+                        ##print("*********************************************")
+                        ##print("*********************************************")
+                        dataOut.data            = self.buffer
+                        dataOut.data_velocity   = self.bufferVel
+                        dataOut.utctime         = self.firstdatatime
+                        dataOut.nProfiles       = m
+                        self.firstdatatime      = None
+                        dataOut.flagNoData      = False
+                        dataOut.flagDataAsBlock = True
+                        self.__Index            = 0
+                        dataOut.identifierWR    = True
+                    return dataOut
+            class PulsePairVoltage(Operation):
+                '''
+                Function PulsePair(Signal Power, Velocity)
+                The real component of Lag[0] provides Intensity Information
+                The imag component of Lag[1] Phase provides Velocity Information
+                Configuration Parameters:
+                nPRF = Number of Several PRF
+                theta = Degree Azimuth angel Boundaries
+                Input:
+                      self.dataOut
+                      lag[N]
+                Affected:
+                      self.dataOut.spc
+                '''
+                isConfig       = False
+                __profIndex    = 0
+                __initime      = None
+                __lastdatatime = None
+                __buffer       = None
+                __buffer2      = []
+                __buffer3      = None
+                __dataReady    = False
+                n              = None
+                __nch          = 0
+                __nHeis        = 0
+                def __init__(self,**kwargs):
+                    Operation.__init__(self,**kwargs)
+                def setup(self, dataOut, n = None ):
+                    '''
+                    n= Numero de PRF's de entrada
+                    '''
+                    self.__initime        = None
+                    self.__lastdatatime   = 0
+                    self.__dataReady      = False
+                    self.__buffer         = 0
+                    self.__buffer2        = []
+                    self.__buffer3        = 0
+                    self.__profIndex      = 0
+                    self.__nch            = dataOut.nChannels
+                    self.__nHeis          = dataOut.nHeights
+                    print("ELVALOR DE n es:", n)
+                    if n == None:
+                        raise ValueError("n should be specified.")
+                    if n != None:
+                        if n<2:
+                            raise ValueError("n should be greater than 2")
+                    self.n       = n
+                    self.__nProf = n
+                    '''
+                    if overlapping:
+                        self.__withOverlapping = True
+                        self.__buffer          = None
+                    else:
+                        #print ("estoy sin __withO")
+                        self.__withOverlapping = False
+                        self.__buffer          = 0
+                        self.__buffer2         = []
+                        self.__buffer3         = 0
+                    '''
+                def putData(self,data):
+                    '''
+                    Add a profile to he __buffer and increase in one the __profiel Index
+                    '''
+                    #print("self.__profIndex             :",self.__profIndex)
+                    self.__buffer         += data*numpy.conjugate(data)
+                    self.__buffer2.append(numpy.conjugate(data))
+                    if self.__profIndex > 0:
+                        self.__buffer3    += self.__buffer2[self.__profIndex-1]*data
+                    self.__profIndex      += 1
+                    return
+                    '''
+                    if not self.__withOverlapping:
+                        #print("Putdata inside over")
+                        self.__buffer       += data* numpy.conjugate(data)
+                        self.__buffer2.append(numpy.conjugate(data))
+                        if self.__profIndex >0:
+                            self.__buffer3 += self.__buffer2[self.__profIndex-1]*data
+                        self.__profIndex   += 1
+                        return
+                    if self.__buffer is None:
+                        #print("aqui bro")
+                        self.__buffer     = data* numpy.conjugate(data)
+                        self.__buffer2.append(numpy.conjugate(data))
+                        self.__profIndex += 1
+                        return
+                    if self.__profIndex < self.n:
+                        self.__buffer = numpy.vstack(self.__buffer,data* numpy.conjugate(data))
+                        self.__buffer2.append(numpy.conjugate(data))
+                        if self.__profIndex == 1:
+                            self.__buffer3  =  self.__buffer2[self.__profIndex -1] * data
+                        else:
+                            self.__buffer3  = numpy.vstack(self.__buffer3, self.__buffer2[self.profIndex-1]*data)
+                        self.__profIndex += 1
+                        return
+                    '''
+                def pushData(self):
+                    '''
+                    Return the PULSEPAIR and the profiles used in the operation
+                    Affected :  self.__profileIndex
+                    '''
+                    #print("************************************************")
+                    #print("push data int vel n")
+                    data_intensity   = self.__buffer/self.n
+                    data_velocity    = self.__buffer3/(self.n-1)
+                    n                = self.__profIndex
+                    self.__buffer    = 0
+                    self.__buffer2   = []
+                    self.__buffer3   = 0
+                    self.__profIndex = 0
+                    return data_intensity, data_velocity,n
+                    '''
+                    if not self.__withOverlapping:
+                        #print("ahora que fue")
+                        data_intensity = self.__buffer/self.n
+                        data_velocity  = self.__buffer3/(self.n-1)
+                        n = self.__profIndex
+                        self.__buffer    = 0
+                        self.__buffer2   = []
+                        self.__buffer3   = 0
+                        self.__profIndex = 0
+                        return data_intensity, data_velocity,n
+                    data_intensity = numpy.sum(self.__buffer,axis  = 0)
+                    data_velocity  = numpy.sum(self.__buffer3,axis = 0)
+                    n              = self.__profIndex
+                    #self.__buffer    = 0
+                    #self.__buffer2   = []
+                    #self.__buffer3   = 0
+                    #self.__profIndex = 0
+                    return data_intensity, data_velocity,n
+                    '''
+                def pulsePairbyProfiles(self,data):
+                    self.__dataReady     =  False
+                    data_intensity       =  None
+                    data_velocity        =  None
+                    #print("beforeputada")
+                    self.putData(data)
+                    #print("ProfileIndex:",self.__profIndex)
+                    if self.__profIndex  == self.n:
+                        data_intensity, data_velocity, n   = self.pushData()
+                        self.__dataReady                   = True
+                        #print("-----------------------------------------------")
+                        #print("data_intensity",data_intensity.shape,"data_velocity",data_velocity.shape)
+                    return data_intensity, data_velocity
+                def pulsePairOp(self, data, datatime= None):
+                    if self.__initime == None:
+                        self.__initime = datatime
+                    data_intensity, data_velocity = self.pulsePairbyProfiles(data)
+                    self.__lastdatatime           = datatime
+                    if data_intensity is None:
+                        return None, None, None
+                    avgdatatime    = self.__initime
+                    deltatime      = datatime - self.__lastdatatime
+                    self.__initime = datatime
+                    '''
+                    if not self.__withOverlapping:
+                        self.__initime = datatime
+                    else:
+                        self.__initime += deltatime
+                    '''
+                    return data_intensity, data_velocity, avgdatatime
+                def run(self, dataOut,n = None, overlapping= False,**kwargs):
+                    if not self.isConfig:
+                        self.setup(dataOut = dataOut, n    = n , **kwargs)
+                        self.isConfig   = True
+                    #print("*******************")
+                    #print("print Shape input data:",dataOut.data.shape)
+                    data_intensity, data_velocity, avgdatatime = self.pulsePairOp(dataOut.data, dataOut.utctime)
+                    dataOut.flagNoData                         = True
+                    if self.__dataReady:
+                        #print("#------------------------------------------------------")
+                        #print("data_ready",data_intensity.shape)
+                        dataOut.data            = data_intensity #valor para plotear RTI
+                        dataOut.nCohInt        *= self.n
+                        dataOut.data_intensity  = data_intensity #valor para intensidad
+                        dataOut.data_velocity   = data_velocity  #valor para velocidad
+                        dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
+                        dataOut.utctime         = avgdatatime
+                        dataOut.flagNoData      = False
+                    return dataOut
             # import collections
             # from scipy.stats import mode
             #
             # class Synchronize(Operation):
             #
             #     isConfig = False
             #     __profIndex = 0
             #
             #     def __init__(self, **kwargs):
             #
             #         Operation.__init__(self, **kwargs)
             # #         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/USRP_PLOT_THOR.py +27 -7

             #!python
             '''
             '''
             import os, sys
             import datetime
             import time
             #path = os.path.dirname(os.getcwd())
             #path = os.path.dirname(path)
             #sys.path.insert(0, path)
             from schainpy.controller import Project
             desc = "USRP_test"
             filename = "USRP_processing.xml"
             controllerObj = Project()
             controllerObj.setup(id = '191', name='Test_USRP', description=desc)
             ############## USED TO PLOT IQ VOLTAGE, POWER AND SPECTRA #############
             #######################################################################
             ######PATH DE LECTURA, ESCRITURA, GRAFICOS Y ENVIO WEB#################
             #######################################################################
             #path = '/media/data/data/vientos/57.2063km/echoes/NCO_Woodman'
-            path = '/home/soporte/data_hdf5' #### with clock   35.16 db noise
+            #path = '/home/soporte/data_hdf5' #### with clock   35.16 db noise
+            path = '/home/alex/WEATHER_DATA/DATA'
-            figpath = '/home/soporte/data_hdf5_imag'
+            figpath = '/home/alex/WEATHER_DATA/DATA/pic'
+            #figpath = '/home/soporte/data_hdf5_imag'
             #remotefolder = "/home/wmaster/graficos"
             #######################################################################
             ################# RANGO DE PLOTEO######################################
             #######################################################################
             dBmin = '30'
             dBmax = '60'
             xmin = '0'
             xmax ='24'
             ymin = '0'
             ymax = '600'
             #######################################################################
             ########################FECHA##########################################
             #######################################################################
             str = datetime.date.today()
             today = str.strftime("%Y/%m/%d")
             str2 = str - datetime.timedelta(days=1)
             yesterday = str2.strftime("%Y/%m/%d")
             #######################################################################
             ######################## UNIDAD DE LECTURA#############################
             #######################################################################
             readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
                                                         path=path,
                                                         startDate="2019/01/01",#today,
                                                         endDate="2109/12/30",#today,
                                                         startTime='00:00:00',
                                                         endTime='23:59:59',
                                                         delay=0,
                                                         #set=0,
                                                         online=0,
                                                         walk=1,
                                                         ippKm = 1000)
             opObj11 = readUnitConfObj.addOperation(name='printInfo')
             opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
             #######################################################################
             ################ OPERACIONES DOMINIO DEL TIEMPO########################
             #######################################################################
             procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
             #
             # codigo64='1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,1,0,'+\
             #              '1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,1,0,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1'
             #opObj11 = procUnitConfObjA.addOperation(name='setRadarFrequency')
             #opObj11.addParameter(name='frequency', value='30e6', format='float')
             #opObj10 = procUnitConfObjA.addOperation(name='Scope', optype='external')
             #opObj10.addParameter(name='id', value='10', format='int')
             ##opObj10.addParameter(name='xmin', value='0', format='int')
             ##opObj10.addParameter(name='xmax', value='50', format='int')
             #opObj10.addParameter(name='type', value='iq')
             #opObj10.addParameter(name='ymin', value='-5000', format='int')
             ##opObj10.addParameter(name='ymax', value='8500', format='int')
             #opObj10 = procUnitConfObjA.addOperation(name='setH0')
             #opObj10.addParameter(name='h0', value='-5000', format='float')
             #opObj11 =  procUnitConfObjA.addOperation(name='filterByHeights')
             #opObj11.addParameter(name='window', value='1', format='int')
             #codigo='1,1,-1,1,1,-1,1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,1,1,1,-1,-1,-1'
             #opObj11 = procUnitConfObjSousy.addOperation(name='Decoder', optype='other')
             #opObj11.addParameter(name='code', value=codigo, format='floatlist')
             #opObj11.addParameter(name='nCode', value='1', format='int')
             #opObj11.addParameter(name='nBaud', value='28', format='int')
             #opObj11 = procUnitConfObjA.addOperation(name='CohInt', optype='other')
-            #opObj11.addParameter(name='n', value='100', format='int')
+            #opObj11.addParameter(name='n', value='10', format='int')
+            opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other')
+            opObj11.addParameter(name='n', value='10', format='int')
+            opObj11 = procUnitConfObjA.addOperation(name='CreateBlockVoltage', optype='other')
+            opObj11.addParameter(name='m', value='16', format='int')
+            procUnitConfObj2 = controllerObj.addProcUnit(datatype='ParametersProc', inputId=procUnitConfObjA.getId())
+            #Not used because the RGB data is obtained directly from the HF Reader.
+            #opObj21 = procUnitConfObj2.addOperation(name='GetRGBData')
+            opObj21 = procUnitConfObj2.addOperation(name='ParamWriter', optype='external')
+            opObj21.addParameter(name='path', value=figpath+'/NEWData')
+            opObj21.addParameter(name='blocksPerFile', value='1', format='int')
+            opObj21.addParameter(name='metadataList',value='heightList',format='list')
+            opObj21.addParameter(name='dataList',value='data_intensity',format='list')
+            '''
             #######################################################################
             ########## OPERACIONES DOMINIO DE LA FRECUENCIA########################
             #######################################################################
             procUnitConfObjSousySpectra = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId())
-            procUnitConfObjSousySpectra.addParameter(name='nFFTPoints', value='100', format='int')
+            procUnitConfObjSousySpectra.addParameter(name='nFFTPoints', value='16', format='int')
-            procUnitConfObjSousySpectra.addParameter(name='nProfiles', value='100', format='int')
+            procUnitConfObjSousySpectra.addParameter(name='nProfiles', value='16', format='int')
             #procUnitConfObjSousySpectra.addParameter(name='pairsList', value='(0,0),(1,1),(0,1)', format='pairsList')
             #opObj13 = procUnitConfObjSousySpectra.addOperation(name='removeDC')
             #opObj13.addParameter(name='mode', value='2', format='int')
             #opObj11 = procUnitConfObjSousySpectra.addOperation(name='IncohInt', optype='other')
             #opObj11.addParameter(name='n', value='60', format='float')
             #######################################################################
             ########## PLOTEO DOMINIO DE LA FRECUENCIA#############################
             #######################################################################
             #SpectraPlot
             opObj11 = procUnitConfObjSousySpectra.addOperation(name='SpectraPlot', optype='external')
             opObj11.addParameter(name='id', value='1', format='int')
             opObj11.addParameter(name='wintitle', value='Spectra', format='str')
             #opObj11.addParameter(name='xmin', value=-0.01, format='float')
             #opObj11.addParameter(name='xmax', value=0.01, format='float')
             #opObj11.addParameter(name='zmin', value=dBmin, format='int')
             #opObj11.addParameter(name='zmax', value=dBmax, format='int')
             #opObj11.addParameter(name='ymin', value=ymin, format='int')
             #opObj11.addParameter(name='ymax', value=ymax, format='int')
             opObj11.addParameter(name='showprofile', value='1', format='int')
             opObj11.addParameter(name='save', value=figpath, format='str')
             opObj11.addParameter(name='save_period', value=10, format='int')
             #RTIPLOT
             opObj11 = procUnitConfObjSousySpectra.addOperation(name='RTIPlot', optype='external')
             opObj11.addParameter(name='id', value='2', format='int')
             opObj11.addParameter(name='wintitle', value='RTIPlot', format='str')
             #opObj11.addParameter(name='zmin', value=dBmin, format='int')
             #opObj11.addParameter(name='zmax', value=dBmax, format='int')
             #opObj11.addParameter(name='ymin', value=ymin, format='int')
             #opObj11.addParameter(name='ymax', value=ymax, format='int')
             opObj11.addParameter(name='xmin', value=0, format='int')
             opObj11.addParameter(name='xmax', value=23, format='int')
             opObj11.addParameter(name='showprofile', value='1', format='int')
             opObj11.addParameter(name='save', value=figpath, format='str')
             opObj11.addParameter(name='save_period', value=10, format='int')
             # opObj11 = procUnitConfObjSousySpectra.addOperation(name='CrossSpectraPlot', optype='other')
             # opObj11.addParameter(name='id', value='3', format='int')
             # opObj11.addParameter(name='wintitle', value='CrossSpectraPlot', format='str')
             # opObj11.addParameter(name='ymin', value=ymin, format='int')
             # opObj11.addParameter(name='ymax', value=ymax, format='int')
             # opObj11.addParameter(name='phase_cmap', value='jet', format='str')
             # opObj11.addParameter(name='zmin', value=dBmin, format='int')
             # opObj11.addParameter(name='zmax', value=dBmax, format='int')
             # opObj11.addParameter(name='figpath', value=figures_path, format='str')
             # opObj11.addParameter(name='save', value=0, format='bool')
             # opObj11.addParameter(name='pairsList', value='(0,1)', format='pairsList')
             # #
             # opObj11 = procUnitConfObjSousySpectra.addOperation(name='CoherenceMap', optype='other')
             # opObj11.addParameter(name='id', value='4', format='int')
             # opObj11.addParameter(name='wintitle', value='Coherence', format='str')
             # opObj11.addParameter(name='phase_cmap', value='jet', format='str')
             # opObj11.addParameter(name='xmin', value=xmin, format='float')
             # opObj11.addParameter(name='xmax', value=xmax, format='float')
             # opObj11.addParameter(name='figpath', value=figures_path, format='str')
             # opObj11.addParameter(name='save', value=0, format='bool')
             # opObj11.addParameter(name='pairsList', value='(0,1)', format='pairsList')
             #
             #######################################################################
             ############### UNIDAD DE ESCRITURA ###################################
             #######################################################################
             #opObj11 = procUnitConfObjSousySpectra.addOperation(name='SpectraWriter', optype='other')
             #opObj11.addParameter(name='path', value=wr_path)
             #opObj11.addParameter(name='blocksPerFile', value='50', format='int')
+            '''
             print ("Escribiendo el archivo XML")
             print ("Leyendo el archivo XML")
             controllerObj.start()

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