schain-jc Commit - r1205:45d75be01895

Wind and rainfall processing of CLAIRE radar with V3.0

George Yong -

r1205:45d75be01895

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schainpy/model/data/jrodata.py +7 -17

             '''
             $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 * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (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 * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (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 * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (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 +
+                    velrange = deltav * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.)
-                                                      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 * \
+                    normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter
-                        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 * \
+                    timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor
-                        self.nIncohInt * self.nProfiles * self.ippFactor
                     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(
+                        ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0)
-                            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):
                     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]
                     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'
                         self.data[plot] = {}
                     if 'spc' in self.data or 'rti' in self.data or 'cspc' in self.data:
                         self.data['noise'] = {}
                         if 'noise' not in self.plottypes:
                             self.plottypes.append('noise')
                 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, 'pairsList'):
                         self.pairs = dataOut.pairsList
                     if hasattr(dataOut, 'meta'):
                         self.meta = dataOut.meta
                     self.channels = dataOut.channelList
                     self.interval = dataOut.getTimeInterval()
                     self.localtime = dataOut.useLocalTime
                     if 'spc' in self.plottypes or 'cspc' 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 == 'spc':
                             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 = 10*numpy.log10(dataOut.data_DOP)
                         if plot == 'mean':
                             buffer = dataOut.data_MEAN
                         if plot == 'std':
                             buffer = dataOut.data_STD
                         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[plot] = buffer
                         elif plot == 'cspc':
                             self.data['spc'] = buffer[0]
                             self.data['cspc'] = buffer[1]
                         else:
                             if self.buffering:
                                 self.data[plot][tm] = buffer
                             else:
                                 self.data[plot] = buffer
                 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, decimate=False):
                     '''
                     Convert data to json
                     '''
                     data = {}
                     tm = self.times[-1]
                     dy = int(self.heights.size/self.MAXNUMY) + 1
                     for key in self.data:
                         if key in ('spc', 'cspc') or not self.buffering:
                             dx = int(self.data[key].shape[1]/self.MAXNUMX) + 1
                             data[key] = self.roundFloats(
                                 self.data[key][::, ::dx, ::dy].tolist())
                         else:
                             data[key] = self.roundFloats(self.data[key][tm].tolist())
                     ret = {'data': data}
                     ret['exp_code'] = self.exp_code
                     ret['time'] = float(tm)
                     ret['interval'] = float(self.interval)
                     ret['localtime'] = self.localtime
                     ret['yrange'] = self.roundFloats(self.heights[::dy].tolist())
                     if 'spc' in self.data or 'cspc' in self.data:
                         ret['xrange'] = self.roundFloats(self.xrange[2][::dx].tolist())
                     else:
                         ret['xrange'] = []
                     if hasattr(self, 'pairs'):
                         ret['pairs'] = [(int(p[0]), int(p[1])) for p in self.pairs]
                     else:
                         ret['pairs'] = []
                     for key, value in list(self.meta.items()):
                         ret[key] = value
                     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_parameters.py +8 -3

             import os
             import datetime
             import numpy
             import inspect
             from .figure import Figure, isRealtime, isTimeInHourRange
             from .plotting_codes import *
             from schainpy.model.proc.jroproc_base import MPDecorator
             from schainpy.utils import log
             class ParamLine_(Figure):
                 isConfig = None
                 def __init__(self):
                     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 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):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                     """
                     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))
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     y = dataOut.RR
                     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(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(len(self.axesList)):
                         title = "Channel %d" %(i)
                         axes = self.axesList[i]
                         ychannel = y[i,:]
                         axes.pline(x, ychannel,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                     xlabel=xlabel, ylabel=ylabel, title=title)
                     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)
             class SpcParamPlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'SpcParam'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     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
                 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 , Selector = 0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     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.spcparam_range[0]
                         xlabel = "Frequency (kHz)"
                     elif xaxis == "time":
                         x = dataOut.spcparam_range[1]
                         xlabel = "Time (ms)"
                     else:
                         x = dataOut.spcparam_range[2]
                         xlabel = "Velocity (m/s)"
                     ylabel = "Range (km)"
                     y = dataOut.getHeiRange()
                     z = dataOut.SPCparam[Selector] /1966080.0#/ dataOut.normFactor#GauSelector]    #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.spc_noise
                     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)
             class MomentsPlot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 def __init__(self):
                     Figure.__init__(self)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 280
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MOMENTS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 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):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return None
                     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")
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = dataOut.data_pre[channelIndexList,:,:]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     noise = dataOut.noise/factor
                     zdB = 10*numpy.log10(z)
                     avgdB = 10*numpy.log10(avg)
                     noisedB = 10*numpy.log10(noise)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters"
                     xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     update_figfile = False
                     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.nanmin(avgdB)*0.9
                         if zmax == None: zmax = numpy.nanmax(avgdB)*0.9
                         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
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[i,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, cblabel='')
                                     #Mean Line
                         mean = dataOut.data_param[i, 1, :]
                         axes.addpline(mean, y, idline=0, color="black", linestyle="solid", lw=1)
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[i], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                             noiseline = numpy.repeat(noisedB[i], len(y))
                             axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class SkyMapPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'mmap'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
             #         self.WIDTH = 280
             #         self.HEIGHT = 250
                     self.WIDTH = 600
                     self.HEIGHT = 600
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MSKYMAP_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 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=False, 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=show)
                     nrow, ncol = 1,1
                     counter = 0
                     x = 0
                     y = 0
                     self.addAxes(1, 1, 0, 0, 1, 1, True)
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         tmin=0, tmax=24, 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, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     arrayParameters = dataOut.data_param
                     error = arrayParameters[:,-1]
                     indValid = numpy.where(error == 0)[0]
                     finalMeteor = arrayParameters[indValid,:]
                     finalAzimuth = finalMeteor[:,3]
                     finalZenith = finalMeteor[:,4]
                     x = finalAzimuth*numpy.pi/180
                     y = finalZenith
                     x1 = [dataOut.ltctime, dataOut.ltctime]
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     title = wintitle + " Parameters"
                     xlabel = "Zonal Zenith Angle (deg) "
                     ylabel = "Meridional Zenith Angle (deg)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if self.xmin is None and self.xmax is None:
                             self.xmin, self.xmax = self.getTimeLim(x1, tmin, tmax, timerange)
                         if timerange != None:
                             self.timerange = timerange
                         else:
                             self.timerange = self.xmax - self.xmin
                         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.firstdate = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         self.isConfig = True
                         update_figfile = True
                     self.setWinTitle(title)
                     i = 0
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     axes = self.axesList[i*self.__nsubplots]
                     nevents = axes.x_buffer.shape[0] + x.shape[0]
                     title = "Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n" %(self.firstdate,str_datetime,nevents)
                     axes.polar(x, y,
                                 title=title, xlabel=xlabel, ylabel=ylabel,
                                 ticksize=9, cblabel='')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     if dataOut.ltctime >= self.xmax:
                         self.isConfigmagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                         axes.__firsttime = True
                         self.xmin += self.timerange
                         self.xmax += self.timerange
+            @MPDecorator
             class WindProfilerPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'wind'
-                def __init__(self, **kwargs):
+                def __init__(self):
-                    Figure.__init__(self, **kwargs)
+                    Figure.__init__(self)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 300
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = WIND_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
                     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):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='False',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmax_ver = None, zmin_ver = None, SNRmin = None, SNRmax = None,
                         timerange=None, SNRthresh = None,
                         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):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
+                    if dataOut.flagNoData:
+                        return dataOut
             #         if timerange is not None:
             #             self.timerange = timerange
             #
             #         tmin = None
             #         tmax = None
                     x = dataOut.getTimeRange1(dataOut.paramInterval)
                     y = dataOut.heightList
                     z = dataOut.data_output.copy()
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
                     if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR[0]
                         SNRavg = SNR#numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         if SNRthresh == None:
                             SNRthresh = -5.0
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     #thisDatetime = datetime.datetime.now()
                     title = wintitle + "Wind"
                     xlabel = ""
                     ylabel = "Height (km)"
                     update_figfile = False
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange is not 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 zmax == None: zmax = numpy.nanmax(abs(z[list(range(2)),:]))
                         #if numpy.isnan(zmax): zmax = 50
                         if zmin == None: zmin = -zmax
                         if nplotsw == 3:
                             if zmax_ver == None: zmax_ver = numpy.nanmax(abs(z[2,:]))
                             if zmin_ver == None: zmin_ver = -zmax_ver
                         if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         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)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal', 'Meridional', 'Vertical']
                     strCb = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
                     zmaxVector = [zmax, zmax, zmax_ver]
                     zminVector = [zmin, zmin, zmin_ver]
                     windFactor = [1,1,100]
                     for i in range(nplotsw):
                         title = "%s Wind: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))*windFactor[i]
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb[i], cbsize="1%", colormap="seismic" )
                     if dataOut.data_SNR is not None:
                         i += 1
                         title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     if dataOut.ltctime + dataOut.paramInterval >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
+                    return dataOut
             @MPDecorator
             class ParametersPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'param'
                 nplots = None
                 nchan = None
                 def __init__(self):#, **kwargs):
                     Figure.__init__(self)#, **kwargs)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 300
                     self.HEIGHT = 550
                     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, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     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)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap="jet",
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None,
                         showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None,
                         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, 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
                     if HEIGHT is not None:
                         self.HEIGHT = HEIGHT
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = list(range(dataOut.data_param.shape[0]))
                     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.getTimeRange1(dataOut.paramInterval)
                     y = dataOut.getHeiRange()
                     if dataOut.data_param.ndim == 3:
                         z = dataOut.data_param[channelIndexList,paramIndex,:]
                     else:
                         z = dataOut.data_param[channelIndexList,:]
                     if showSNR:
                         #SNR data
                         SNRarray = dataOut.data_SNR[channelIndexList,:]
                         SNRdB = 10*numpy.log10(SNRarray)
                         ind = numpy.where(SNRdB < SNRthresh)
                         z[ind] = numpy.nan
                     thisDatetime = dataOut.datatime
             #         thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (km)"
                     update_figfile = False
                     if not self.isConfig:
                         nchan = len(channelIndexList)
                         self.nchan = nchan
                         self.plotFact = 1
                         nplots = nchan
                         if showSNR:
                             nplots = nchan*2
                             self.plotFact = 2
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    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 = numpy.nanmin(z)
                         if zmax == None: zmax = numpy.nanmax(z)
                         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.nchan):
             #             index = channelIndexList[i]
             #             title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
             #             axes = self.axesList[i*self.plotFact]
             #             z1 = z[i,:].reshape((1,-1))
             #             axes.pcolorbuffer(x, y, z1,
             #                         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 showSNR:
             #                 title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
             #                 axes = self.axesList[i*self.plotFact + 1]
             #                 SNRdB1 = SNRdB[i,:].reshape((1,-1))
             #                 axes.pcolorbuffer(x, y, SNRdB1,
             #                         xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
             #                         xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
             #                         ticksize=9, cblabel='', cbsize="1%",colormap='jet')
                     i=0
                     index = channelIndexList[i]
                     title = "Factor de reflectividad Z [dBZ]"
                     axes = self.axesList[i*self.plotFact]
                     z1 = z[i,:].reshape((1,-1))
                     axes.pcolorbuffer(x, y, z1,
                                 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 showSNR:
                         title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.plotFact + 1]
                         SNRdB1 = SNRdB[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRdB1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                 ticksize=9, cblabel='', cbsize="1%",colormap='jet')
                     i=1
                     index = channelIndexList[i]
                     title = "Velocidad vertical Doppler [m/s]"
                     axes = self.axesList[i*self.plotFact]
                     z1 = z[i,:].reshape((1,-1))
                     axes.pcolorbuffer(x, y, z1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=-10, zmax=10,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                 ticksize=9, cblabel='', cbsize="1%",colormap='seismic_r')
                     if showSNR:
                         title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.plotFact + 1]
                         SNRdB1 = SNRdB[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRdB1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                 ticksize=9, cblabel='', cbsize="1%",colormap='jet')
                     i=2
                     index = channelIndexList[i]
                     title = "Intensidad de lluvia [mm/h]"
                     axes = self.axesList[i*self.plotFact]
                     z1 = z[i,:].reshape((1,-1))
                     axes.pcolorbuffer(x, y, z1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=0, zmax=40,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                 ticksize=9, cblabel='', cbsize="1%",colormap='ocean_r')
                     if showSNR:
                         title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.plotFact + 1]
                         SNRdB1 = SNRdB[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRdB1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                 ticksize=9, cblabel='', cbsize="1%",colormap='jet')
                     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 Parameters1Plot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 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 = PARMS_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
                     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=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,
                         parameterIndex = None, onlyPositive = False,
                         SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None, onlySNR = False,
                         DOP = True,
                         zlabel = "", parameterName = "", parameterObject = "data_param",
                         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):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return dataOut
                     data_param = getattr(dataOut, parameterObject)
                     if channelList == None:
                         channelIndexList = numpy.arange(data_param.shape[0])
                     else:
                         channelIndexList = numpy.array(channelList)
                     nchan = len(channelIndexList) #Number of channels being plotted
                     if nchan < 1:
                         return
                     nGraphsByChannel = 0
                     if SNR:
                         nGraphsByChannel += 1
                     if DOP:
                         nGraphsByChannel += 1
                     if nGraphsByChannel < 1:
                         return
                     nplots = nGraphsByChannel*nchan
                     if timerange is not None:
                         self.timerange = timerange
                     #tmin = None
                     #tmax = None
                     if parameterIndex == None:
                         parameterIndex = 1
                     x = dataOut.getTimeRange1(dataOut.paramInterval)
                     y = dataOut.heightList
                     if dataOut.data_param.ndim == 3:
                         z = dataOut.data_param[channelIndexList,parameterIndex,:]
                     else:
                         z = dataOut.data_param[channelIndexList,:]
                     if dataOut.data_SNR is not None:
                         if dataOut.data_SNR.ndim == 2:
                             SNRavg = numpy.average(dataOut.data_SNR, axis=0)
                         else:
                             SNRavg = dataOut.data_SNR
                         SNRdB = 10*numpy.log10(SNRavg)
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     if onlyPositive:
                         colormap = "jet"
                         zmin = 0
                     else: colormap = "RdBu_r"
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         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 = numpy.nanmin(z)
                         if zmax == None: zmax = numpy.nanmax(z)
                         if SNR:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         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.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     for i in range(nchan):
                         if (SNR and not onlySNR): j = 2*i
                         else: j = i
                         j = nGraphsByChannel*i
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                         if not onlySNR:
                             axes = self.axesList[j*self.__nsubplots]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                     ticksize=9, cblabel=zlabel, cbsize="1%")
                         if DOP:
                             title = "%s Channel %d: %s" %(parameterName, channelIndexList[i], 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[j]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                         xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                         xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                         ticksize=9, cblabel=zlabel, cbsize="1%")
                     if SNR:
                         title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[(j)*self.__nsubplots]
                         if not onlySNR:
                             axes = self.axesList[(j + 1)*self.__nsubplots]
                         axes = self.axesList[(j + nGraphsByChannel-1)]
                         z1 = SNRdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet",
                                 ticksize=9, cblabel=zlabel, cbsize="1%")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         self.figfile = None
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=False)
                     return dataOut
             class SpectralFittingPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 N = None
                 ippSeconds = None
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = SPECFIT_CODE
                     self.WIDTH = 450
                     self.HEIGHT = 250
                     self.WIDTHPROF = 0
                     self.HEIGHTPROF = 0
                 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=False, show=True):
                     showprofile = False
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 5
                     colspan = 4
                     if showprofile:
                         ncolspan = 5
                         colspan = 4
                         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, cutHeight=None, fit=False, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if cutHeight==None:
                         h=270
                     heightindex = numpy.abs(cutHeight - dataOut.heightList).argmin()
                     cutHeight = dataOut.heightList[heightindex]
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList[:-1]
                     #y = dataOut.getHeiRange()
                     z = dataOut.data_pre[:,:,heightindex]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     listChannels = z.shape[0]
                     #Reconstruct Function
                     if fit==True:
                         groupArray = dataOut.groupList
                         listChannels = groupArray.reshape((groupArray.size))
                         listChannels.sort()
                         spcFitLine = numpy.zeros(z.shape)
                         constants = dataOut.constants
                         nGroups = groupArray.shape[0]
                         nChannels = groupArray.shape[1]
                         nProfiles = z.shape[1]
                         for f in range(nGroups):
                             groupChann = groupArray[f,:]
                             p = dataOut.data_param[f,:,heightindex]
             #                 p = numpy.array([ 89.343967,0.14036615,0.17086219,18.89835291,1.58388365,1.55099167])
                             fitLineAux = dataOut.library.modelFunction(p, constants)*nProfiles
                             fitLineAux = fitLineAux.reshape((nChannels,nProfiles))
                             spcFitLine[groupChann,:] = fitLineAux
             #             spcFitLine = spcFitLine/factor
                         z = z[listChannels,:]
                         spcFitLine = spcFitLine[listChannels,:]
                         spcFitLinedB = 10*numpy.log10(spcFitLine)
                     zdB = 10*numpy.log10(z)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Doppler Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     xlabel = "Velocity (m/s)"
                     ylabel = "Spectrum"
                     if not self.isConfig:
                         nplots = listChannels.size
                         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(zdB)
                         if ymax == None: ymax = numpy.nanmax(zdB)+2
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
             #             title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i])
                         title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i])
                         axes = self.axesList[i*self.__nsubplots]
                         if fit == False:
                             axes.pline(x, zdB[i,:],
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title
                                         )
                         if fit == True:
                             fitline=spcFitLinedB[i,:]
                             y=numpy.vstack([zdB[i,:],fitline] )
                             legendlabels=['Data','Fitting']
                             axes.pmultilineyaxis(x, y,
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title,
                                         legendlabels=legendlabels, marker=None,
                                         linestyle='solid', grid='both')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class EWDriftsPlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'drift'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 150
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = EWDRIFT_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
                     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):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmaxVertical = None, zminVertical = None, zmaxZonal = None, zminZonal = None,
                         timerange=None, SNRthresh = -numpy.inf, SNRmin = None, SNRmax = None, SNR_1 = False,
                         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):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if timerange is not None:
                         self.timerange = timerange
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1(dataOut.outputInterval)
             #         y = dataOut.heightList
                     y = dataOut.heightList
                     z = dataOut.data_output
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
                     if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR
                         if SNR_1:
                             SNR += 1
                         SNRavg = numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
                     showprofile = False
             #        thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(x[1])
                     title = wintitle + " EW Drifts"
                     xlabel = ""
                     ylabel = "Height (Km)"
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         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 zmaxZonal == None: zmaxZonal = numpy.nanmax(abs(z[0,:]))
                         if zminZonal == None: zminZonal = -zmaxZonal
                         if zmaxVertical == None: zmaxVertical = numpy.nanmax(abs(z[1,:]))
                         if zminVertical == None: zminVertical = -zmaxVertical
                         if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         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.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal','Vertical']
                     strCb = 'Velocity (m/s)'
                     zmaxVector = [zmaxZonal, zmaxVertical]
                     zminVector = [zminZonal, zminVertical]
                     for i in range(nplotsw):
                         title = "%s Drifts: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb, cbsize="1%", colormap="RdBu_r")
                     if dataOut.data_SNR is not None:
                         i += 1
                         if SNR_1:
                             title = "Signal Noise Ratio + 1 (SNR+1): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         else:
                             title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         self.figfile = None
             class PhasePlot_(Figure):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'mphase'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 24*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 600
                     self.HEIGHT = 300
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = MPHASE_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
                 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 run(self, dataOut, id, wintitle="", pairsList=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):
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1(dataOut.outputInterval)
                     y = dataOut.getHeiRange()
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase"
                     #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = dataOut.data_output
                     update_figfile = False
                     if not self.isConfig:
                         self.nplots = phase_beacon.size
                         self.setup(id=id,
                                    nplots=self.nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange is not None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0
                         if ymax == None: ymax = numpy.nanmax(phase_beacon) + 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([])
                         #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)
                         update_figfile = True
                     #store data beacon phase
                     #self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Offset %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["phase %d"%(chan) for chan in numpy.arange(self.nplots)]
                     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()
                     self.save(figpath=figpath,
                       figfile=figfile,
                       save=save,
                       ftp=ftp,
                       wr_period=wr_period,
                       thisDatetime=thisDatetime,
                       update_figfile=update_figfile)
                     if dataOut.ltctime + dataOut.outputInterval >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
             class NSMeteorDetection1Plot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'nsm'
                 zminList = None
                 zmaxList = None
                 cmapList = None
                 titleList = None
                 nPairs = None
                 nChannels = None
                 nParam = None
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 750
                     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
                 def getSubplots(self):
                     ncol = 3
                     nrow = int(numpy.ceil(self.nplots/3.0))
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     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)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None,
                         vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA',
                         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"):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     #SEPARAR EN DOS PLOTS
                     nParam = dataOut.data_param.shape[1] - 3
                     utctime = dataOut.data_param[0,0]
                     tmet = dataOut.data_param[:,1].astype(int)
                     hmet = dataOut.data_param[:,2].astype(int)
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = numpy.zeros((nParam, y.size, x.size - 1))
                     z[:,:] = numpy.nan
                     z[:,hmet,tmet] = dataOut.data_param[:,3:].T
                     z[0,:,:] = 10*numpy.log10(z[0,:,:])
                     xlabel = "Time (s)"
                     ylabel = "Range (km)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     if not self.isConfig:
                         nplots = nParam
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin is None: xmin = numpy.nanmin(x)
                         if xmax is None: xmax = numpy.nanmax(x)
                         if ymin is None: ymin = numpy.nanmin(y)
                         if ymax is None: ymax = numpy.nanmax(y)
                         if SNRmin is None: SNRmin = numpy.nanmin(z[0,:])
                         if SNRmax is None: SNRmax = numpy.nanmax(z[0,:])
                         if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:]))
                         if vmin is None: vmin = -vmax
                         if wmin is None: wmin = 0
                         if wmax is None: wmax = 50
                         pairsList = dataOut.groupList
                         self.nPairs = len(dataOut.groupList)
                         zminList = [SNRmin, vmin, cmin] + [pmin]*self.nPairs
                         zmaxList = [SNRmax, vmax, cmax] + [pmax]*self.nPairs
                         titleList = ["SNR","Radial Velocity","Coherence"]
                         cmapList = ["jet","RdBu_r","jet"]
                         for i in range(self.nPairs):
                             strAux1 = "Phase Difference "+ str(pairsList[i][0]) + str(pairsList[i][1])
                             titleList = titleList + [strAux1]
                             cmapList = cmapList + ["RdBu_r"]
                         self.zminList = zminList
                         self.zmaxList = zmaxList
                         self.cmapList = cmapList
                         self.titleList = titleList
                         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
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     for i in range(nParam):
                         title = self.titleList[i] + ": " +str_datetime
                         axes = self.axesList[i]
                         axes.pcolor(x, y, z[i,:].T,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='')
                     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)
             class NSMeteorDetection2Plot_(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'nsm'
                 zminList = None
                 zmaxList = None
                 cmapList = None
                 titleList = None
                 nPairs = None
                 nChannels = None
                 nParam = None
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 750
                     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
                 def getSubplots(self):
                     ncol = 3
                     nrow = int(numpy.ceil(self.nplots/3.0))
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     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)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None,
                         vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA',
                         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"):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     #Rebuild matrix
                     utctime = dataOut.data_param[0,0]
                     cmet = dataOut.data_param[:,1].astype(int)
                     tmet = dataOut.data_param[:,2].astype(int)
                     hmet = dataOut.data_param[:,3].astype(int)
                     nParam = 3
                     nChan = len(dataOut.groupList)
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = numpy.full((nChan, nParam, y.size, x.size - 1),numpy.nan)
                     z[cmet,:,hmet,tmet] = dataOut.data_param[:,4:]
                     z[:,0,:,:] = 10*numpy.log10(z[:,0,:,:]) #logarithmic scale
                     z = numpy.reshape(z, (nChan*nParam, y.size, x.size-1))
                     xlabel = "Time (s)"
                     ylabel = "Range (km)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     if not self.isConfig:
                         nplots = nParam*nChan
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin is None: xmin = numpy.nanmin(x)
                         if xmax is None: xmax = numpy.nanmax(x)
                         if ymin is None: ymin = numpy.nanmin(y)
                         if ymax is None: ymax = numpy.nanmax(y)
                         if SNRmin is None: SNRmin = numpy.nanmin(z[0,:])
                         if SNRmax is None: SNRmax = numpy.nanmax(z[0,:])
                         if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:]))
                         if vmin is None: vmin = -vmax
                         if wmin is None: wmin = 0
                         if wmax is None: wmax = 50
                         self.nChannels = nChan
                         zminList = []
                         zmaxList = []
                         titleList = []
                         cmapList = []
                         for i in range(self.nChannels):
                             strAux1 = "SNR Channel "+ str(i)
                             strAux2 = "Radial Velocity Channel "+ str(i)
                             strAux3 = "Spectral Width Channel "+ str(i)
                             titleList = titleList + [strAux1,strAux2,strAux3]
                             cmapList = cmapList + ["jet","RdBu_r","jet"]
                             zminList = zminList + [SNRmin,vmin,wmin]
                             zmaxList = zmaxList + [SNRmax,vmax,wmax]
                         self.zminList = zminList
                         self.zmaxList = zmaxList
                         self.cmapList = cmapList
                         self.titleList = titleList
                         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
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     for i in range(self.nplots):
                         title = self.titleList[i] + ": " +str_datetime
                         axes = self.axesList[i]
                         axes.pcolor(x, y, z[i,:].T,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='')
                     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)
   No newline at end of file

schainpy/model/graphics/mpldriver.py +2 -2

             import os
             import sys
             import datetime
             import numpy
             import matplotlib
             if 'BACKEND' in os.environ:
                 matplotlib.use(os.environ['BACKEND'])
             elif 'linux' in sys.platform:
                 matplotlib.use("TkAgg")
             elif 'darwin' in sys.platform:
                 matplotlib.use('TkAgg')
             else:
                 from schainpy.utils import log
                 log.warning('Using default Backend="Agg"', 'INFO')
                 matplotlib.use('Agg')
             # Qt4Agg', 'GTK', 'GTKAgg', 'ps', 'agg', 'cairo', 'MacOSX', 'GTKCairo', 'WXAgg', 'template', 'TkAgg', 'GTK3Cairo', 'GTK3Agg', 'svg', 'WebAgg', 'CocoaAgg', 'emf', 'gdk', 'WX'
             import matplotlib.pyplot
             from mpl_toolkits.axes_grid1 import make_axes_locatable
             from matplotlib.ticker import FuncFormatter, LinearLocator
             ###########################################
             # Actualizacion de las funciones del driver
             ###########################################
             # create jro colormap
             jet_values = matplotlib.pyplot.get_cmap("jet", 100)(numpy.arange(100))[10:90]
             blu_values = matplotlib.pyplot.get_cmap(
                 "seismic_r", 20)(numpy.arange(20))[10:15]
             ncmap = matplotlib.colors.LinearSegmentedColormap.from_list(
                 "jro", numpy.vstack((blu_values, jet_values)))
             matplotlib.pyplot.register_cmap(cmap=ncmap)
             def createFigure(id, wintitle, width, height, facecolor="w", show=True, dpi=80):
                 matplotlib.pyplot.ioff()
                 fig = matplotlib.pyplot.figure(num=id, facecolor=facecolor, figsize=(
 .0 * width / dpi, 1.0 * height / dpi))
                 fig.canvas.manager.set_window_title(wintitle)
             #     fig.canvas.manager.resize(width, height)
                 matplotlib.pyplot.ion()
                 if show:
                     matplotlib.pyplot.show()
                 return fig
             def closeFigure(show=False, fig=None):
                 #     matplotlib.pyplot.ioff()
                 #     matplotlib.pyplot.pause(0)
                 if show:
                     matplotlib.pyplot.show()
                 if fig != None:
                     matplotlib.pyplot.close(fig)
             #         matplotlib.pyplot.pause(0)
             #         matplotlib.pyplot.ion()
                     return
                 matplotlib.pyplot.close("all")
             #     matplotlib.pyplot.pause(0)
             #     matplotlib.pyplot.ion()
                 return
             def saveFigure(fig, filename):
                 #     matplotlib.pyplot.ioff()
                 fig.savefig(filename, dpi=matplotlib.pyplot.gcf().dpi)
             #     matplotlib.pyplot.ion()
             def clearFigure(fig):
                 fig.clf()
             def setWinTitle(fig, title):
                 fig.canvas.manager.set_window_title(title)
             def setTitle(fig, title):
                 fig.suptitle(title)
             def createAxes(fig, nrow, ncol, xpos, ypos, colspan, rowspan, polar=False):
                 matplotlib.pyplot.ioff()
                 matplotlib.pyplot.figure(fig.number)
                 axes = matplotlib.pyplot.subplot2grid((nrow, ncol),
                                                       (xpos, ypos),
                                                       colspan=colspan,
                                                       rowspan=rowspan,
                                                       polar=polar)
                 matplotlib.pyplot.ion()
                 return axes
             def setAxesText(ax, text):
                 ax.annotate(text,
                             xy=(.1, .99),
                             xycoords='figure fraction',
                             horizontalalignment='left',
                             verticalalignment='top',
                             fontsize=10)
             def printLabels(ax, xlabel, ylabel, title):
                 ax.set_xlabel(xlabel, size=11)
                 ax.set_ylabel(ylabel, size=11)
                 ax.set_title(title, size=8)
             def createPline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='',
                             ticksize=9, xtick_visible=True, ytick_visible=True,
                             nxticks=4, nyticks=10,
                             grid=None, color='blue'):
                 """
                 Input:
                     grid    :    None, 'both', 'x', 'y'
                 """
                 matplotlib.pyplot.ioff()
                 ax.set_xlim([xmin, xmax])
                 ax.set_ylim([ymin, ymax])
                 printLabels(ax, xlabel, ylabel, title)
                 ######################################################
                 if (xmax - xmin) <= 1:
                     xtickspos = numpy.linspace(xmin, xmax, nxticks)
                     xtickspos = numpy.array([float("%.1f" % i) for i in xtickspos])
                     ax.set_xticks(xtickspos)
                 else:
                     xtickspos = numpy.arange(nxticks) * \
                         int((xmax - xmin) / (nxticks)) + int(xmin)
             #         xtickspos = numpy.arange(nxticks)*float(xmax-xmin)/float(nxticks) + int(xmin)
                     ax.set_xticks(xtickspos)
                 for tick in ax.get_xticklabels():
                     tick.set_visible(xtick_visible)
                 for tick in ax.xaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 ######################################################
                 for tick in ax.get_yticklabels():
                     tick.set_visible(ytick_visible)
                 for tick in ax.yaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 ax.plot(x, y, color=color)
                 iplot = ax.lines[-1]
                 ######################################################
                 if '0.' in matplotlib.__version__[0:2]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if '1.0.' in matplotlib.__version__[0:4]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if grid != None:
                     ax.grid(b=True, which='major', axis=grid)
                 matplotlib.pyplot.tight_layout()
                 matplotlib.pyplot.ion()
                 return iplot
             def set_linedata(ax, x, y, idline):
                 ax.lines[idline].set_data(x, y)
             def pline(iplot, x, y, xlabel='', ylabel='', title=''):
                 ax = iplot.axes
                 printLabels(ax, xlabel, ylabel, title)
                 set_linedata(ax, x, y, idline=0)
             def addpline(ax, x, y, color, linestyle, lw):
                 ax.plot(x, y, color=color, linestyle=linestyle, lw=lw)
             def createPcolor(ax, x, y, z, xmin, xmax, ymin, ymax, zmin, zmax,
                              xlabel='', ylabel='', title='', ticksize=9,
                              colormap='jet', cblabel='', cbsize="5%",
                              XAxisAsTime=False):
                 matplotlib.pyplot.ioff()
                 divider = make_axes_locatable(ax)
                 ax_cb = divider.new_horizontal(size=cbsize, pad=0.05)
                 fig = ax.get_figure()
                 fig.add_axes(ax_cb)
                 ax.set_xlim([xmin, xmax])
                 ax.set_ylim([ymin, ymax])
                 printLabels(ax, xlabel, ylabel, title)
                 z = numpy.ma.masked_invalid(z)
                 cmap = matplotlib.pyplot.get_cmap(colormap)
-                cmap.set_bad('black', 1.)
+                cmap.set_bad('white', 1.)
                 imesh = ax.pcolormesh(x, y, z.T, vmin=zmin, vmax=zmax, cmap=cmap)
                 cb = matplotlib.pyplot.colorbar(imesh, cax=ax_cb)
                 cb.set_label(cblabel)
             #    for tl in ax_cb.get_yticklabels():
             #        tl.set_visible(True)
                 for tick in ax.yaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 for tick in ax.xaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 for tick in cb.ax.get_yticklabels():
                     tick.set_fontsize(ticksize)
                 ax_cb.yaxis.tick_right()
                 if '0.' in matplotlib.__version__[0:2]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return imesh
                 if '1.0.' in matplotlib.__version__[0:4]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return imesh
                 matplotlib.pyplot.tight_layout()
                 if XAxisAsTime:
                     def func(x, pos): return ('%s') % (
                         datetime.datetime.utcfromtimestamp(x).strftime("%H:%M:%S"))
                     ax.xaxis.set_major_formatter(FuncFormatter(func))
                     ax.xaxis.set_major_locator(LinearLocator(7))
                 matplotlib.pyplot.ion()
                 return imesh
             def pcolor(imesh, z, xlabel='', ylabel='', title=''):
                 z = z.T
                 ax = imesh.axes
                 printLabels(ax, xlabel, ylabel, title)
                 imesh.set_array(z.ravel())
             def addpcolor(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'):
                 printLabels(ax, xlabel, ylabel, title)
                 ax.pcolormesh(x, y, z.T, vmin=zmin, vmax=zmax,
                               cmap=matplotlib.pyplot.get_cmap(colormap))
             def addpcolorbuffer(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'):
                 printLabels(ax, xlabel, ylabel, title)
                 ax.collections.remove(ax.collections[0])
                 z = numpy.ma.masked_invalid(z)
                 cmap = matplotlib.pyplot.get_cmap(colormap)
-                cmap.set_bad('black', 1.)
+                cmap.set_bad('white', 1.)
                 ax.pcolormesh(x, y, z.T, vmin=zmin, vmax=zmax, cmap=cmap)
             def createPmultiline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', legendlabels=None,
                                  ticksize=9, xtick_visible=True, ytick_visible=True,
                                  nxticks=4, nyticks=10,
                                  grid=None):
                 """
                 Input:
                     grid    :    None, 'both', 'x', 'y'
                 """
                 matplotlib.pyplot.ioff()
                 lines = ax.plot(x.T, y)
                 leg = ax.legend(lines, legendlabels, loc='upper right')
                 leg.get_frame().set_alpha(0.5)
                 ax.set_xlim([xmin, xmax])
                 ax.set_ylim([ymin, ymax])
                 printLabels(ax, xlabel, ylabel, title)
                 xtickspos = numpy.arange(nxticks) * \
                     int((xmax - xmin) / (nxticks)) + int(xmin)
                 ax.set_xticks(xtickspos)
                 for tick in ax.get_xticklabels():
                     tick.set_visible(xtick_visible)
                 for tick in ax.xaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 for tick in ax.get_yticklabels():
                     tick.set_visible(ytick_visible)
                 for tick in ax.yaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 iplot = ax.lines[-1]
                 if '0.' in matplotlib.__version__[0:2]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if '1.0.' in matplotlib.__version__[0:4]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if grid != None:
                     ax.grid(b=True, which='major', axis=grid)
                 matplotlib.pyplot.tight_layout()
                 matplotlib.pyplot.ion()
                 return iplot
             def pmultiline(iplot, x, y, xlabel='', ylabel='', title=''):
                 ax = iplot.axes
                 printLabels(ax, xlabel, ylabel, title)
                 for i in range(len(ax.lines)):
                     line = ax.lines[i]
                     line.set_data(x[i, :], y)
             def createPmultilineYAxis(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', legendlabels=None,
                                       ticksize=9, xtick_visible=True, ytick_visible=True,
                                       nxticks=4, nyticks=10, marker='.', markersize=10, linestyle="None",
                                       grid=None, XAxisAsTime=False):
                 """
                 Input:
                     grid    :    None, 'both', 'x', 'y'
                 """
                 matplotlib.pyplot.ioff()
             #    lines = ax.plot(x, y.T, marker=marker,markersize=markersize,linestyle=linestyle)
                 lines = ax.plot(x, y.T)
             #     leg = ax.legend(lines, legendlabels, loc=2, bbox_to_anchor=(1.01, 1.00), numpoints=1, handlelength=1.5, \
             #                     handletextpad=0.5, borderpad=0.5, labelspacing=0.5, borderaxespad=0.)
                 leg = ax.legend(lines, legendlabels,
                                 loc='upper right', bbox_to_anchor=(1.16, 1), borderaxespad=0)
                 for label in leg.get_texts():
                     label.set_fontsize(9)
                 ax.set_xlim([xmin, xmax])
                 ax.set_ylim([ymin, ymax])
                 printLabels(ax, xlabel, ylabel, title)
             #    xtickspos = numpy.arange(nxticks)*int((xmax-xmin)/(nxticks)) + int(xmin)
             #    ax.set_xticks(xtickspos)
                 for tick in ax.get_xticklabels():
                     tick.set_visible(xtick_visible)
                 for tick in ax.xaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 for tick in ax.get_yticklabels():
                     tick.set_visible(ytick_visible)
                 for tick in ax.yaxis.get_major_ticks():
                     tick.label.set_fontsize(ticksize)
                 iplot = ax.lines[-1]
                 if '0.' in matplotlib.__version__[0:2]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if '1.0.' in matplotlib.__version__[0:4]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if grid != None:
                     ax.grid(b=True, which='major', axis=grid)
                 matplotlib.pyplot.tight_layout()
                 if XAxisAsTime:
                     def func(x, pos): return ('%s') % (
                         datetime.datetime.utcfromtimestamp(x).strftime("%H:%M:%S"))
                     ax.xaxis.set_major_formatter(FuncFormatter(func))
                     ax.xaxis.set_major_locator(LinearLocator(7))
                 matplotlib.pyplot.ion()
                 return iplot
             def pmultilineyaxis(iplot, x, y, xlabel='', ylabel='', title=''):
                 ax = iplot.axes
                 printLabels(ax, xlabel, ylabel, title)
                 for i in range(len(ax.lines)):
                     line = ax.lines[i]
                     line.set_data(x, y[i, :])
             def createPolar(ax, x, y,
                             xlabel='', ylabel='', title='', ticksize=9,
                             colormap='jet', cblabel='', cbsize="5%",
                             XAxisAsTime=False):
                 matplotlib.pyplot.ioff()
                 ax.plot(x, y, 'bo', markersize=5)
             #     ax.set_rmax(90)
                 ax.set_ylim(0, 90)
                 ax.set_yticks(numpy.arange(0, 90, 20))
             #     ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center' ,size='11')
             #     ax.text(0, 50, ylabel, rotation='vertical', va ='center', ha = 'left' ,size='11')
             #     ax.text(100, 100, 'example', ha='left', va='center', rotation='vertical')
                 ax.yaxis.labelpad = 40
                 printLabels(ax, xlabel, ylabel, title)
                 iplot = ax.lines[-1]
                 if '0.' in matplotlib.__version__[0:2]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
                 if '1.0.' in matplotlib.__version__[0:4]:
                     print("The matplotlib version has to be updated to 1.1 or newer")
                     return iplot
             #     if grid != None:
             #         ax.grid(b=True, which='major', axis=grid)
                 matplotlib.pyplot.tight_layout()
                 matplotlib.pyplot.ion()
                 return iplot
             def polar(iplot, x, y, xlabel='', ylabel='', title=''):
                 ax = iplot.axes
             #     ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center',size='11')
                 printLabels(ax, xlabel, ylabel, title)
                 set_linedata(ax, x, y, idline=0)
             def draw(fig):
                 if type(fig) == 'int':
                     raise ValueError("Error drawing: Fig parameter should be a matplotlib figure object figure")
                 fig.canvas.draw()
             def pause(interval=0.000001):
                 matplotlib.pyplot.pause(interval)

schainpy/model/io/jroIO_madrigal.py +2 -2

             '''
             Created on Aug 1, 2017
             @author: Juan C. Espinoza
             '''
             import os
             import sys
             import time
             import json
             import glob
             import datetime
             import numpy
             import h5py
             from schainpy.model.io.jroIO_base import JRODataReader
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Parameters
             from schainpy.utils import log
             try:
                 import madrigal.cedar
             except:
                 log.warning(
                     'You should install "madrigal library" module if you want to read/write Madrigal data'
                     )
             DEF_CATALOG = {
                 'principleInvestigator': 'Marco Milla',
                 'expPurpose': None,
                 'cycleTime': None,
                 'correlativeExp': None,
                 'sciRemarks': None,
                 'instRemarks': None
                 }
             DEF_HEADER = {
                 'kindatDesc': None,
                 'analyst': 'Jicamarca User',
                 'comments': None,
                 'history': None
                 }
             MNEMONICS = {
 : 'jro',
 : 'jbr',
 : 'jul',
 : 'jas',
 : 'pbr',
 : 'hbr',
 : 'obr',
             }
             UT1970 = datetime.datetime(1970, 1, 1) - datetime.timedelta(seconds=time.timezone)
             def load_json(obj):
                 '''
                 Parse json as string instead of unicode
                 '''
                 if isinstance(obj, str):
                     iterable = json.loads(obj)
                 else:
                     iterable = obj
                 if isinstance(iterable, dict):
                     return {str(k): load_json(v) if isinstance(v, dict) else str(v) if isinstance(v, str) else v
                         for k, v in list(iterable.items())}
                 elif isinstance(iterable, (list, tuple)):
                     return [str(v) if isinstance(v, str) else v for v in iterable]
                 return iterable
             @MPDecorator
             class MADReader(JRODataReader, ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Parameters()
                     self.counter_records = 0
                     self.nrecords = None
                     self.flagNoMoreFiles = 0
                     self.isConfig = False
                     self.filename = None
                     self.intervals = set()
                 def setup(self,
                           path=None,
                           startDate=None,
                           endDate=None,
                           format=None,
                           startTime=datetime.time(0, 0, 0),
                           endTime=datetime.time(23, 59, 59),
                           **kwargs):
                     self.path = path
                     self.startDate = startDate
                     self.endDate = endDate
                     self.startTime = startTime
                     self.endTime = endTime
                     self.datatime = datetime.datetime(1900,1,1)
                     self.oneDDict = load_json(kwargs.get('oneDDict',
                                                          "{\"GDLATR\":\"lat\", \"GDLONR\":\"lon\"}"))
                     self.twoDDict = load_json(kwargs.get('twoDDict',
                                                          "{\"GDALT\": \"heightList\"}"))
                     self.ind2DList = load_json(kwargs.get('ind2DList',
                                                           "[\"GDALT\"]"))
                     if self.path is None:
                         raise ValueError('The path is not valid')
                     if format is None:
                         raise ValueError('The format is not valid choose simple or hdf5')
                     elif format.lower() in ('simple', 'txt'):
                         self.ext = '.txt'
                     elif format.lower() in ('cedar',):
                         self.ext = '.001'
                     else:
                         self.ext = '.hdf5'
                     self.search_files(self.path)
                     self.fileId = 0
                     if not self.fileList:
                         raise  Warning('There is no files matching these date in the folder: {}. \n Check startDate and endDate'.format(path))
                     self.setNextFile()
                 def search_files(self, path):
                     '''
                      Searching for madrigal files in path
                      Creating a list of files to procces included in [startDate,endDate]
                      Input:
                          path - Path to find files
                     '''
                     log.log('Searching files {} in {} '.format(self.ext, path), 'MADReader')
                     foldercounter = 0
                     fileList0 = glob.glob1(path, '*{}'.format(self.ext))
                     fileList0.sort()
                     self.fileList = []
                     self.dateFileList = []
                     startDate = self.startDate - datetime.timedelta(1)
                     endDate = self.endDate + datetime.timedelta(1)
                     for thisFile in fileList0:
                         year = thisFile[3:7]
                         if not year.isdigit():
                             continue
                         month = thisFile[7:9]
                         if not month.isdigit():
                             continue
                         day = thisFile[9:11]
                         if not day.isdigit():
                             continue
                         year, month, day = int(year), int(month), int(day)
                         dateFile = datetime.date(year, month, day)
                         if (startDate > dateFile) or (endDate < dateFile):
                             continue
                         self.fileList.append(thisFile)
                         self.dateFileList.append(dateFile)
                     return
                 def parseHeader(self):
                     '''
                     '''
                     self.output = {}
                     self.version = '2'
                     s_parameters = None
                     if self.ext == '.txt':
                         self.parameters = [s.strip().lower() for s in self.fp.readline().strip().split(' ') if s]
                     elif self.ext == '.hdf5':
                         metadata = self.fp['Metadata']
                         data = self.fp['Data']['Array Layout']
                         if 'Independent Spatial Parameters' in metadata:
                             s_parameters = [s[0].lower() for s in metadata['Independent Spatial Parameters']]
                             self.version = '3'
                         one = [s[0].lower() for s in data['1D Parameters']['Data Parameters']]
                         one_d = [1 for s in one]
                         two = [s[0].lower() for s in data['2D Parameters']['Data Parameters']]
                         two_d = [2 for s in two]
                         self.parameters = one + two
                         self.parameters_d = one_d + two_d
-                    log.success('Parameters found: {}'.format(','.join(self.parameters)),
+                    log.success('Parameters found: {}'.format(','.join(str(self.parameters))),
                                 'MADReader')
                     if s_parameters:
-                        log.success('Spatial parameters: {}'.format(','.join(s_parameters)),
+                        log.success('Spatial parameters: {}'.format(','.join(str(s_parameters))),
                                     'MADReader')
                     for param in list(self.oneDDict.keys()):
                         if param.lower() not in self.parameters:
                             log.warning(
                                 'Parameter {} not found will be ignored'.format(
                                     param),
                                 'MADReader')
                             self.oneDDict.pop(param, None)
                     for param, value in list(self.twoDDict.items()):
                         if param.lower() not in self.parameters:
                             log.warning(
                                 'Parameter {} not found, it will be ignored'.format(
                                     param),
                                 'MADReader')
                             self.twoDDict.pop(param, None)
                             continue
                         if isinstance(value, list):
                             if value[0] not in self.output:
                                 self.output[value[0]] = []
                             self.output[value[0]].append(None)
                 def parseData(self):
                     '''
                     '''
                     if self.ext == '.txt':
                         self.data = numpy.genfromtxt(self.fp, missing_values=('missing'))
                         self.nrecords = self.data.shape[0]
                         self.ranges = numpy.unique(self.data[:,self.parameters.index(self.ind2DList[0].lower())])
                     elif self.ext == '.hdf5':
                         self.data = self.fp['Data']['Array Layout']
                         self.nrecords = len(self.data['timestamps'].value)
                         self.ranges = self.data['range'].value
                 def setNextFile(self):
                     '''
                     '''
                     file_id = self.fileId
                     if file_id == len(self.fileList):
                         log.success('No more files', 'MADReader')
                         self.flagNoMoreFiles = 1
                         return 0
                     log.success(
                         'Opening: {}'.format(self.fileList[file_id]),
                         'MADReader'
                         )
                     filename = os.path.join(self.path, self.fileList[file_id])
                     if self.filename is not None:
                         self.fp.close()
                     self.filename = filename
                     self.filedate = self.dateFileList[file_id]
                     if self.ext=='.hdf5':
                         self.fp = h5py.File(self.filename, 'r')
                     else:
                         self.fp = open(self.filename, 'rb')
                     self.parseHeader()
                     self.parseData()
                     self.sizeOfFile = os.path.getsize(self.filename)
                     self.counter_records = 0
                     self.flagIsNewFile = 0
                     self.fileId += 1
                     return 1
                 def readNextBlock(self):
                     while True:
                         self.flagDiscontinuousBlock = 0
                         if self.flagIsNewFile:
                             if not self.setNextFile():
                                 return 0
                         self.readBlock()
                         if (self.datatime < datetime.datetime.combine(self.startDate, self.startTime)) or \
                            (self.datatime > datetime.datetime.combine(self.endDate, self.endTime)):
                             log.warning(
                                 'Reading Record No. {}/{} -> {} [Skipping]'.format(
                                     self.counter_records,
                                     self.nrecords,
                                     self.datatime.ctime()),
                                 'MADReader')
                             continue
                         break
                     log.log(
                         'Reading Record No. {}/{} -> {}'.format(
                             self.counter_records,
                             self.nrecords,
                             self.datatime.ctime()),
                         'MADReader')
                     return 1
                 def readBlock(self):
                     '''
                     '''
                     dum = []
                     if self.ext == '.txt':
                         dt = self.data[self.counter_records][:6].astype(int)
                         if datetime.datetime(dt[0], dt[1], dt[2], dt[3], dt[4], dt[5]).date() > self.datatime.date():
                             self.flagDiscontinuousBlock = 1
                         self.datatime = datetime.datetime(dt[0], dt[1], dt[2], dt[3], dt[4], dt[5])
                         while True:
                             dt = self.data[self.counter_records][:6].astype(int)
                             datatime = datetime.datetime(dt[0], dt[1], dt[2], dt[3], dt[4], dt[5])
                             if datatime == self.datatime:
                                 dum.append(self.data[self.counter_records])
                                 self.counter_records += 1
                                 if self.counter_records == self.nrecords:
                                     self.flagIsNewFile = True
                                     break
                                 continue
                             self.intervals.add((datatime-self.datatime).seconds)
                             break
                     elif self.ext == '.hdf5':
                         datatime = datetime.datetime.utcfromtimestamp(
                             self.data['timestamps'][self.counter_records])
                         nHeights = len(self.ranges)
                         for n, param in enumerate(self.parameters):
                             if self.parameters_d[n] == 1:
                                 dum.append(numpy.ones(nHeights)*self.data['1D Parameters'][param][self.counter_records])
                             else:
                                 if self.version == '2':
                                     dum.append(self.data['2D Parameters'][param][self.counter_records])
                                 else:
                                     tmp = self.data['2D Parameters'][param].value.T
                                     dum.append(tmp[self.counter_records])
                         self.intervals.add((datatime-self.datatime).seconds)
                         if datatime.date()>self.datatime.date():
                             self.flagDiscontinuousBlock = 1
                         self.datatime = datatime
                         self.counter_records += 1
                         if self.counter_records == self.nrecords:
                             self.flagIsNewFile = True
                     self.buffer = numpy.array(dum)
                     return
                 def set_output(self):
                     '''
                     Storing data from buffer to dataOut object
                     '''
                     parameters = [None for __ in self.parameters]
                     for param, attr in list(self.oneDDict.items()):
                         x = self.parameters.index(param.lower())
                         setattr(self.dataOut, attr, self.buffer[0][x])
                     for param, value in list(self.twoDDict.items()):
                         x = self.parameters.index(param.lower())
                         if self.ext == '.txt':
                             y = self.parameters.index(self.ind2DList[0].lower())
                             ranges = self.buffer[:,y]
                             if self.ranges.size == ranges.size:
                                 continue
                             index = numpy.where(numpy.in1d(self.ranges, ranges))[0]
                             dummy = numpy.zeros(self.ranges.shape) + numpy.nan
                             dummy[index] = self.buffer[:,x]
                         else:
                             dummy = self.buffer[x]
                         if isinstance(value, str):
                             if value not in self.ind2DList:
                                 setattr(self.dataOut, value, dummy.reshape(1,-1))
                         elif isinstance(value, list):
                             self.output[value[0]][value[1]] = dummy
                             parameters[value[1]] = param
                     for key, value in list(self.output.items()):
                         setattr(self.dataOut, key, numpy.array(value))
                     self.dataOut.parameters = [s for s in parameters if s]
                     self.dataOut.heightList = self.ranges
                     self.dataOut.utctime = (self.datatime - datetime.datetime(1970, 1, 1)).total_seconds()
                     self.dataOut.utctimeInit = self.dataOut.utctime
                     self.dataOut.paramInterval = min(self.intervals)
                     self.dataOut.useLocalTime = False
                     self.dataOut.flagNoData = False
                     self.dataOut.nrecords = self.nrecords
                     self.dataOut.flagDiscontinuousBlock = self.flagDiscontinuousBlock
                 def getData(self):
                     '''
                     Storing data from databuffer to dataOut object
                     '''
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         self.dataOut.error = 'No file left to process'
                         return 0
                     if not  self.readNextBlock():
                         self.dataOut.flagNoData = True
                         return 0
                     self.set_output()
                     return 1
             class MADWriter(Operation):
                 missing = -32767
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.dataOut = Parameters()
                     self.counter = 0
                     self.path = None
                     self.fp = None
                 def run(self, dataOut, path, oneDDict, ind2DList='[]', twoDDict='{}',
                         metadata='{}', format='cedar', **kwargs):
                     '''
                     Inputs:
                         path - path where files will be created
                         oneDDict - json of one-dimensional parameters in record where keys
                         are Madrigal codes (integers or mnemonics) and values the corresponding
                         dataOut attribute e.g: {
                             'gdlatr': 'lat',
                             'gdlonr': 'lon',
                             'gdlat2':'lat',
                             'glon2':'lon'}
                         ind2DList - list of independent spatial two-dimensional parameters e.g:
                             ['heighList']
                         twoDDict - json of two-dimensional parameters in record where keys
                         are Madrigal codes (integers or mnemonics) and values the corresponding
                         dataOut attribute if multidimensional array specify as tupple
                         ('attr', pos) e.g: {
                             'gdalt': 'heightList',
                             'vn1p2': ('data_output', 0),
                             'vn2p2': ('data_output', 1),
                             'vn3': ('data_output', 2),
                             'snl': ('data_SNR', 'db')
                             }
                         metadata - json of madrigal metadata (kinst, kindat, catalog and header)
                     '''
                     if not self.isConfig:
                         self.setup(path, oneDDict, ind2DList, twoDDict, metadata, format, **kwargs)
                         self.isConfig = True
                     self.dataOut = dataOut
                     self.putData()
                     return
                 def setup(self, path, oneDDict, ind2DList, twoDDict, metadata, format, **kwargs):
                     '''
                     Configure Operation
                     '''
                     self.path = path
                     self.blocks = kwargs.get('blocks', None)
                     self.counter = 0
                     self.oneDDict = load_json(oneDDict)
                     self.twoDDict = load_json(twoDDict)
                     self.ind2DList = load_json(ind2DList)
                     meta = load_json(metadata)
                     self.kinst = meta.get('kinst')
                     self.kindat = meta.get('kindat')
                     self.catalog = meta.get('catalog', DEF_CATALOG)
                     self.header = meta.get('header', DEF_HEADER)
                     if format == 'cedar':
                         self.ext = '.dat'
                         self.extra_args = {}
                     elif format == 'hdf5':
                         self.ext = '.hdf5'
                         self.extra_args = {'ind2DList': self.ind2DList}
                     self.keys = [k.lower() for k in self.twoDDict]
                     if 'range' in self.keys:
                         self.keys.remove('range')
                     if 'gdalt' in self.keys:
                         self.keys.remove('gdalt')
                 def setFile(self):
                     '''
                     Create new cedar file object
                     '''
                     self.mnemonic = MNEMONICS[self.kinst]   #TODO get mnemonic from madrigal
                     date = datetime.datetime.utcfromtimestamp(self.dataOut.utctime)
                     filename = '{}{}{}'.format(self.mnemonic,
                                                date.strftime('%Y%m%d_%H%M%S'),
                                                self.ext)
                     self.fullname = os.path.join(self.path, filename)
                     if os.path.isfile(self.fullname) :
                         log.warning(
                             'Destination file {} already exists, previous file deleted.'.format(
                                 self.fullname),
                             'MADWriter')
                         os.remove(self.fullname)
                     try:
                         log.success(
                             'Creating file: {}'.format(self.fullname),
                             'MADWriter')
                         self.fp = madrigal.cedar.MadrigalCedarFile(self.fullname, True)
                     except ValueError as e:
                         log.error(
                             'Impossible to create a cedar object with "madrigal.cedar.MadrigalCedarFile"',
                             'MADWriter')
                         return
                     return 1
                 def writeBlock(self):
                     '''
                     Add data records to cedar file taking data from oneDDict and twoDDict
                     attributes.
                     Allowed parameters in: parcodes.tab
                     '''
                     startTime = datetime.datetime.utcfromtimestamp(self.dataOut.utctime)
                     endTime = startTime + datetime.timedelta(seconds=self.dataOut.paramInterval)
                     heights = self.dataOut.heightList
                     if self.ext == '.dat':
                         for key, value in list(self.twoDDict.items()):
                             if isinstance(value, str):
                                 data = getattr(self.dataOut, value)
                                 invalid = numpy.isnan(data)
                                 data[invalid] = self.missing
                             elif isinstance(value, (tuple, list)):
                                 attr, key = value
                                 data = getattr(self.dataOut, attr)
                                 invalid = numpy.isnan(data)
                                 data[invalid] = self.missing
                     out = {}
                     for key, value in list(self.twoDDict.items()):
                         key = key.lower()
                         if isinstance(value, str):
                             if 'db' in value.lower():
                                 tmp = getattr(self.dataOut, value.replace('_db', ''))
                                 SNRavg = numpy.average(tmp, axis=0)
                                 tmp = 10*numpy.log10(SNRavg)
                             else:
                                 tmp = getattr(self.dataOut, value)
                             out[key] = tmp.flatten()
                         elif isinstance(value, (tuple, list)):
                             attr, x = value
                             data = getattr(self.dataOut, attr)
                             out[key] = data[int(x)]
                     a = numpy.array([out[k] for k in self.keys])
                     nrows = numpy.array([numpy.isnan(a[:, x]).all() for x in range(len(heights))])
                     index = numpy.where(nrows == False)[0]
                     rec = madrigal.cedar.MadrigalDataRecord(
                         self.kinst,
                         self.kindat,
                         startTime.year,
                         startTime.month,
                         startTime.day,
                         startTime.hour,
                         startTime.minute,
                         startTime.second,
                         startTime.microsecond/10000,
                         endTime.year,
                         endTime.month,
                         endTime.day,
                         endTime.hour,
                         endTime.minute,
                         endTime.second,
                         endTime.microsecond/10000,
                         list(self.oneDDict.keys()),
                         list(self.twoDDict.keys()),
                         len(index),
                         **self.extra_args
                     )
                     # Setting 1d values
                     for key in self.oneDDict:
                         rec.set1D(key, getattr(self.dataOut, self.oneDDict[key]))
                     # Setting 2d values
                     nrec = 0
                     for n in index:
                         for key in out:
                             rec.set2D(key, nrec, out[key][n])
                         nrec += 1
                     self.fp.append(rec)
                     if self.ext == '.hdf5' and self.counter % 500 == 0 and self.counter > 0:
                         self.fp.dump()
                     if self.counter % 100 == 0 and self.counter > 0:
                         log.log(
                             'Writing {} records'.format(
                                 self.counter),
                             'MADWriter')
                 def setHeader(self):
                     '''
                     Create an add catalog and header to cedar file
                     '''
                     log.success('Closing file {}'.format(self.fullname), 'MADWriter')
                     if self.ext == '.dat':
                         self.fp.write()
                     else:
                         self.fp.dump()
                         self.fp.close()
                     header = madrigal.cedar.CatalogHeaderCreator(self.fullname)
                     header.createCatalog(**self.catalog)
                     header.createHeader(**self.header)
                     header.write()
                 def putData(self):
                     if self.dataOut.flagNoData:
                         return 0
                     if self.dataOut.flagDiscontinuousBlock or self.counter == self.blocks:
                         if self.counter > 0:
                             self.setHeader()
                         self.counter = 0
                     if self.counter == 0:
                         self.setFile()
                     self.writeBlock()
                     self.counter += 1
                 def close(self):
                     if self.counter > 0:
                         self.setHeader()

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