schain-jc Commit - r937:6cdcc42f2694

Add SkyMapPlotData, operation can access parent kwargs, fix server plot for multiple ReceiverData

Juan C. Espinoza -

r937:6cdcc42f2694

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r937:6cdcc42f2694

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schainpy/model/data/jrodata.py +4 -1

             '''
             $Author: murco $
             $Id: JROData.py 173 2012-11-20 15:06:21Z murco $
             '''
             import copy
             import numpy
             import datetime
             from jroheaderIO import SystemHeader, RadarControllerHeader
             from schainpy import cSchain
             def getNumpyDtype(dataTypeCode):
                 if dataTypeCode == 0:
                     numpyDtype = numpy.dtype([('real','<i1'),('imag','<i1')])
                 elif dataTypeCode == 1:
                     numpyDtype = numpy.dtype([('real','<i2'),('imag','<i2')])
                 elif dataTypeCode == 2:
                     numpyDtype = numpy.dtype([('real','<i4'),('imag','<i4')])
                 elif dataTypeCode == 3:
                     numpyDtype = numpy.dtype([('real','<i8'),('imag','<i8')])
                 elif dataTypeCode == 4:
                     numpyDtype = numpy.dtype([('real','<f4'),('imag','<f4')])
                 elif dataTypeCode == 5:
                     numpyDtype = numpy.dtype([('real','<f8'),('imag','<f8')])
                 else:
                     raise ValueError, 'dataTypeCode was not defined'
                 return numpyDtype
             def getDataTypeCode(numpyDtype):
                 if numpyDtype == numpy.dtype([('real','<i1'),('imag','<i1')]):
                     datatype = 0
                 elif numpyDtype == numpy.dtype([('real','<i2'),('imag','<i2')]):
                     datatype = 1
                 elif numpyDtype == numpy.dtype([('real','<i4'),('imag','<i4')]):
                     datatype = 2
                 elif numpyDtype == numpy.dtype([('real','<i8'),('imag','<i8')]):
                     datatype = 3
                 elif numpyDtype == numpy.dtype([('real','<f4'),('imag','<f4')]):
                     datatype = 4
                 elif numpyDtype == numpy.dtype([('real','<f8'),('imag','<f8')]):
                     datatype = 5
                 else:
                     datatype = None
                 return datatype
             def hildebrand_sekhon(data, navg):
                 """
                 This method is for the objective determination of the noise level in Doppler spectra. This
                 implementation technique is based on the fact that the standard deviation of the spectral
                 densities is equal to the mean spectral density for white Gaussian noise
                 Inputs:
                     Data    :    heights
                     navg    :    numbers of averages
                 Return:
                     -1        :    any error
                     anoise    :    noise's level
                 """
                 sortdata = numpy.sort(data,axis=None)
             #     lenOfData = len(sortdata)
             #     nums_min = lenOfData*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
                 return cSchain.hildebrand_sekhon(sortdata, navg)
             class Beam:
                 def __init__(self):
                     self.codeList = []
                     self.azimuthList = []
                     self.zenithList = []
             class GenericData(object):
                 flagNoData = True
                 def __init__(self):
                     raise NotImplementedError
                 def copy(self, inputObj=None):
                     if inputObj == None:
                         return copy.deepcopy(self)
                     for key in 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
                 def __init__(self):
                     raise NotImplementedError
                 def getNoise(self):
                     raise NotImplementedError
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return range(self.nChannels)
                 def getNHeights(self):
                     return len(self.heightList)
                 def getHeiRange(self, extrapoints=0):
                     heis = self.heightList
             #        deltah = self.heightList[1] - self.heightList[0]
             #
             #        heis.append(self.heightList[-1])
                     return heis
                 def 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:
                         return self.noise_estimation #this was estimated by getNoise Operation defined in jroproc_spectra.py
                     else:
                         noise = self.getNoisebyHildebrand(xmin_index, xmax_index, ymin_index, ymax_index)
                         return noise
                 def getFreqRangeTimeResponse(self, extrapoints=0):
                     deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints*self.ippFactor)
                     freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2
                     return freqrange
                 def getAcfRange(self, extrapoints=0):
                     deltafreq = 10./(self.getFmax() / (self.nFFTPoints*self.ippFactor))
                     freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2
                     return freqrange
                 def getFreqRange(self, extrapoints=0):
                     deltafreq = self.getFmax() / (self.nFFTPoints*self.ippFactor)
                     freqrange = deltafreq*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltafreq/2
                     return freqrange
                 def getVelRange(self, extrapoints=0):
                     deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor)
                     velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) #- deltav/2
                     return velrange
                 def getNPairs(self):
                     return len(self.pairsList)
                 def getPairsIndexList(self):
                     return range(self.nPairs)
                 def getNormFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
                     normFactor = self.nProfiles*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
                     return normFactor
                 def getFlagCspc(self):
                     if self.data_cspc is None:
                         return True
                     return False
                 def getFlagDc(self):
                     if self.data_dc is None:
                         return True
                     return False
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles
                     return timeInterval
                 def getPower(self):
                     factor = self.normFactor
                     z = self.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     return 10*numpy.log10(avg)
                 def getCoherence(self, pairsList=None, phase=False):
                     z = []
                     if pairsList is None:
                         pairsIndexList = self.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in self.pairsList:
                                 raise ValueError, "Pair %s is not in dataOut.pairsList" %(pair)
                             pairsIndexList.append(self.pairsList.index(pair))
                     for i in range(len(pairsIndexList)):
                         pair = self.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0)
                         powa = numpy.average(self.data_spc[pair[0], :, :], axis=0)
                         powb = numpy.average(self.data_spc[pair[1], :, :], axis=0)
                         avgcoherenceComplex = ccf/numpy.sqrt(powa*powb)
                         if phase:
                             data = numpy.arctan2(avgcoherenceComplex.imag,
                                                  avgcoherenceComplex.real)*180/numpy.pi
                         else:
                             data = numpy.abs(avgcoherenceComplex)
                         z.append(data)
                     return numpy.array(z)
                 def setValue(self, value):
                     print "This property should not be initialized"
                     return
                 nPairs = property(getNPairs, setValue, "I'm the 'nPairs' property.")
                 pairsIndexList = property(getPairsIndexList, setValue, "I'm the 'pairsIndexList' property.")
                 normFactor = property(getNormFactor, setValue, "I'm the 'getNormFactor' property.")
                 flag_cspc = property(getFlagCspc, setValue)
                 flag_dc = property(getFlagDc, setValue)
                 noise = property(getNoise, setValue, "I'm the 'nHeights' property.")
                 timeInterval = property(getTimeInterval, setValue, "I'm the 'timeInterval' property")
             class SpectraHeis(Spectra):
                 data_spc = None
                 data_cspc = None
                 data_dc = None
                 nFFTPoints = None
             #     nPairs = None
                 pairsList = None
                 nCohInt = None
                 nIncohInt = None
                 def __init__(self):
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "SpectraHeis"
             #         self.dtype = None
             #        self.nChannels = 0
             #        self.nHeights = 0
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #        self.channelIndexList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
             #         self.nPairs = 0
                     self.utctime = None
                     self.blocksize = None
                     self.profileIndex = 0
                     self.nCohInt = 1
                     self.nIncohInt = 1
                 def getNormFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     normFactor = self.nIncohInt*self.nCohInt*pwcode
                     return normFactor
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     return timeInterval
                 normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             class Fits(JROData):
                 heightList = None
                 channelList = None
                 flagNoData = True
                 flagDiscontinuousBlock = False
                 useLocalTime = False
                 utctime = None
                 timeZone = None
             #     ippSeconds = None
             #     timeInterval = None
                 nCohInt = None
                 nIncohInt = None
                 noise = None
                 windowOfFilter = 1
                 #Speed of ligth
                 C = 3e8
                 frequency = 49.92e6
                 realtime = False
                 def __init__(self):
                     self.type = "Fits"
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
             #         self.channelIndexList = None
                     self.flagNoData = True
                     self.utctime = None
                     self.nCohInt = 1
                     self.nIncohInt = 1
                     self.useLocalTime = True
                     self.profileIndex = 0
             #         self.utctime = None
             #         self.timeZone = None
             #         self.ltctime = None
             #         self.timeInterval = None
             #         self.header = None
             #         self.data_header = None
             #         self.data = None
             #         self.datatime = None
             #         self.flagNoData = False
             #         self.expName = ''
             #         self.nChannels = None
             #         self.nSamples = None
             #         self.dataBlocksPerFile = None
             #         self.comments = ''
             #
                 def getltctime(self):
                     if self.useLocalTime:
                         return self.utctime - self.timeZone*60
                     return self.utctime
                 def getDatatime(self):
                     datatime = datetime.datetime.utcfromtimestamp(self.ltctime)
                     return datatime
                 def getTimeRange(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.timeInterval)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getHeiRange(self):
                     heis = self.heightList
                     return heis
                 def getNHeights(self):
                     return len(self.heightList)
                 def getNChannels(self):
                     return len(self.channelList)
                 def getChannelIndexList(self):
                     return range(self.nChannels)
                 def getNoise(self, type = 1):
                     #noise = numpy.zeros(self.nChannels)
                     if type == 1:
                         noise = self.getNoisebyHildebrand()
                     if type == 2:
                         noise = self.getNoisebySort()
                     if type == 3:
                         noise = self.getNoisebyWindow()
                     return noise
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     return timeInterval
                 datatime = property(getDatatime, "I'm the 'datatime' property")
                 nHeights = property(getNHeights, "I'm the 'nHeights' property.")
                 nChannels = property(getNChannels, "I'm the 'nChannel' property.")
                 channelIndexList = property(getChannelIndexList, "I'm the 'channelIndexList' property.")
                 noise = property(getNoise, "I'm the 'nHeights' property.")
                 ltctime = property(getltctime, "I'm the 'ltctime' property")
                 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
             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[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
                     if mode == 1:
                         jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
                     if mode == 2:
                         vel = numpy.array([-2,-1,1,2])
                         xx = numpy.zeros([4,4])
                         for fil in range(4):
                             xx[fil,:] = vel[fil]**numpy.asarray(range(4))
                         xx_inv = numpy.linalg.inv(xx)
                         xx_aux = xx_inv[0,:]
                         for ich in range(num_chan):
                             yy = jspectra[ich,ind_vel,:]
                             jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
                             junkid = jspectra[ich,freq_dc,:]<=0
                             cjunkid = sum(junkid)
                             if cjunkid.any():
                                 jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
                     noise = jspectra0[:,freq_dc,:] - jspectra[:,freq_dc,:]
                     return noise
                 def getTimeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.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
                 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):
-                    return self.timeInterval1
+                    if hasattr(self, 'timeInterval1'):
+                        return self.timeInterval1
+                    else:
+                        return self.paramInterval
                 def getNoise(self):
                     return self.spc_noise
                 timeInterval = property(getTimeInterval)

schainpy/model/graphics/jroplot_data.py +72 -9

             import os
             import zmq
             import time
             import numpy
             import datetime
             import numpy as np
             import matplotlib
             matplotlib.use('TkAgg')
             import matplotlib.pyplot as plt
             from mpl_toolkits.axes_grid1 import make_axes_locatable
             from matplotlib.ticker import FuncFormatter, LinearLocator
             from multiprocessing import Process
             from schainpy.model.proc.jroproc_base import Operation
             plt.ioff()
             func = lambda x, pos: ('%s') %(datetime.datetime.fromtimestamp(x).strftime('%H:%M'))
             d1970 = datetime.datetime(1970,1,1)
             class PlotData(Operation, Process):
                 CODE = 'Figure'
                 colormap = 'jro'
                 CONFLATE = True
                 __MAXNUMX = 80
                 __MAXNUMY = 80
                 __missing = 1E30
                 def __init__(self, **kwargs):
                     Operation.__init__(self, plot=True, **kwargs)
                     Process.__init__(self)
                     self.kwargs['code'] = self.CODE
                     self.mp = False
                     self.dataOut = None
                     self.isConfig = False
                     self.figure = None
                     self.axes = []
                     self.localtime = kwargs.pop('localtime', True)
                     self.show = kwargs.get('show', True)
                     self.save = kwargs.get('save', False)
                     self.colormap = kwargs.get('colormap', self.colormap)
                     self.colormap_coh = kwargs.get('colormap_coh', 'jet')
                     self.colormap_phase = kwargs.get('colormap_phase', 'RdBu_r')
                     self.showprofile = kwargs.get('showprofile', True)
                     self.title = kwargs.get('wintitle', '')
                     self.xaxis = kwargs.get('xaxis', 'frequency')
                     self.zmin = kwargs.get('zmin', None)
                     self.zmax = kwargs.get('zmax', None)
                     self.xmin = kwargs.get('xmin', None)
                     self.xmax = kwargs.get('xmax', None)
                     self.xrange = kwargs.get('xrange', 24)
                     self.ymin = kwargs.get('ymin', None)
                     self.ymax = kwargs.get('ymax', None)
                     self.throttle_value = 5
                 def fill_gaps(self, x_buffer, y_buffer, z_buffer):
                     if x_buffer.shape[0] < 2:
                         return x_buffer, y_buffer, z_buffer
                     deltas = x_buffer[1:] - x_buffer[0:-1]
                     x_median = np.median(deltas)
                     index = np.where(deltas > 5*x_median)
                     if len(index[0]) != 0:
                         z_buffer[::, index[0], ::] = self.__missing
                         z_buffer = np.ma.masked_inside(z_buffer,
 .99*self.__missing,
 .01*self.__missing)
                     return x_buffer, y_buffer, z_buffer
                 def decimate(self):
                     # dx = int(len(self.x)/self.__MAXNUMX) + 1
                     dy = int(len(self.y)/self.__MAXNUMY) + 1
                     # x = self.x[::dx]
                     x = self.x
                     y = self.y[::dy]
                     z = self.z[::, ::, ::dy]
                     return x, y, z
                 def __plot(self):
                     print 'plotting...{}'.format(self.CODE)
                     if self.show:
-                        print 'showing'
                         self.figure.show()
                     self.plot()
                     plt.tight_layout()
-                    self.figure.canvas.manager.set_window_title('{} {} - Date:{}'.format(self.title, self.CODE.upper(),
+                    self.figure.canvas.manager.set_window_title('{} {} - {}'.format(self.title, self.CODE.upper(),
-                                                                                         datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')))
+                                                                                    datetime.datetime.fromtimestamp(self.max_time).strftime('%Y/%m/%d')))
                     if self.save:
                         figname = os.path.join(self.save, '{}_{}.png'.format(self.CODE,
                                                                              datetime.datetime.fromtimestamp(self.saveTime).strftime('%y%m%d_%H%M%S')))
                         print 'Saving figure: {}'.format(figname)
                         self.figure.savefig(figname)
                     self.figure.canvas.draw()
                 def plot(self):
                     print 'plotting...{}'.format(self.CODE.upper())
                     return
                 def run(self):
                     print '[Starting] {}'.format(self.name)
                     context = zmq.Context()
                     receiver = context.socket(zmq.SUB)
                     receiver.setsockopt(zmq.SUBSCRIBE, '')
                     receiver.setsockopt(zmq.CONFLATE, self.CONFLATE)
-                    receiver.connect("ipc:///tmp/zmq.plots")
+                    if 'server' in self.kwargs['parent']:
+                        receiver.connect('ipc:///tmp/{}.plots'.format(self.kwargs['parent']['server']))
+                    else:
+                        receiver.connect("ipc:///tmp/zmq.plots")
                     while True:
                         try:
                             self.data = receiver.recv_pyobj(flags=zmq.NOBLOCK)
                             self.dataOut = self.data['dataOut']
                             self.times = self.data['times']
                             self.times.sort()
                             self.throttle_value = self.data['throttle']
                             self.min_time = self.times[0]
                             self.max_time = self.times[-1]
                             if self.isConfig is False:
                                 self.setup()
                                 self.isConfig = True
                             self.__plot()
                             if self.data['ENDED'] is True:
                                 self.isConfig = False
                         except zmq.Again as e:
                             print 'Waiting for data...'
                             plt.pause(self.throttle_value)
                 def close(self):
                     if self.dataOut:
                         self.__plot()
             class PlotSpectraData(PlotData):
                 CODE = 'spc'
                 colormap = 'jro'
                 CONFLATE = False
                 def setup(self):
                     ncolspan = 1
                     colspan = 1
                     self.ncols = int(numpy.sqrt(self.dataOut.nChannels)+0.9)
                     self.nrows = int(self.dataOut.nChannels*1./self.ncols + 0.9)
                     self.width = 3.6*self.ncols
                     self.height = 3.2*self.nrows
                     if self.showprofile:
                         ncolspan = 3
                         colspan = 2
                         self.width += 1.2*self.ncols
                     self.ylabel = 'Range [Km]'
                     self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                     n = 0
                     for y in range(self.nrows):
                         for x in range(self.ncols):
                             if n >= self.dataOut.nChannels:
                                 break
                             ax = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan), 1, colspan)
                             if self.showprofile:
                                 ax.ax_profile = plt.subplot2grid((self.nrows, self.ncols*ncolspan), (y, x*ncolspan+colspan), 1, 1)
                             ax.firsttime = True
                             self.axes.append(ax)
                             n += 1
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = self.dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     y = self.dataOut.getHeiRange()
                     z = self.data[self.CODE]
                     for n, ax in enumerate(self.axes):
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else np.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.ymin = self.ymin if self.ymin else np.nanmin(y)
                             self.ymax = self.ymax if self.ymax else np.nanmax(y)
                             self.zmin = self.zmin if self.zmin else np.nanmin(z)
                             self.zmax = self.zmax if self.zmax else np.nanmax(z)
                             ax.plot = ax.pcolormesh(x, y, z[n].T,
                                                     vmin=self.zmin,
                                                     vmax=self.zmax,
                                                     cmap=plt.get_cmap(self.colormap)
                                                    )
                             divider = make_axes_locatable(ax)
                             cax = divider.new_horizontal(size='3%', pad=0.05)
                             self.figure.add_axes(cax)
                             plt.colorbar(ax.plot, cax)
                             ax.set_xlim(self.xmin, self.xmax)
                             ax.set_ylim(self.ymin, self.ymax)
                             ax.set_ylabel(self.ylabel)
                             ax.set_xlabel(xlabel)
                             ax.firsttime = False
                             if self.showprofile:
                                 ax.plot_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
                                 ax.ax_profile.set_xlim(self.zmin, self.zmax)
                                 ax.ax_profile.set_ylim(self.ymin, self.ymax)
                                 ax.ax_profile.set_xlabel('dB')
                                 ax.ax_profile.grid(b=True, axis='x')
                                 ax.plot_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
                                                                    color="k", linestyle="dashed", lw=2)[0]
                                 [tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
                         else:
                             ax.plot.set_array(z[n].T.ravel())
                             if self.showprofile:
                                 ax.plot_profile.set_data(self.data['rti'][self.max_time][n], y)
                                 ax.plot_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
                         ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
                                      size=8)
                         self.saveTime = self.max_time
             class PlotCrossSpectraData(PlotData):
                 CODE = 'cspc'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 CONFLATE = False
                 def setup(self):
                     ncolspan = 1
                     colspan = 1
                     self.ncols = 2
                     self.nrows = self.dataOut.nPairs
                     self.width = 3.6*self.ncols
                     self.height = 3.2*self.nrows
                     self.ylabel = 'Range [Km]'
                     self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                     for y in range(self.nrows):
                         for x in range(self.ncols):
                             ax = plt.subplot2grid((self.nrows, self.ncols), (y, x), 1, 1)
                             ax.firsttime = True
                             self.axes.append(ax)
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = self.dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     y = self.dataOut.getHeiRange()
                     z_coh = self.data['cspc_coh']
                     z_phase = self.data['cspc_phase']
                     for n in range(self.nrows):
                         ax = self.axes[2*n]
                         ax1 = self.axes[2*n+1]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else np.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.ymin = self.ymin if self.ymin else np.nanmin(y)
                             self.ymax = self.ymax if self.ymax else np.nanmax(y)
                             self.zmin_coh = self.zmin_coh if self.zmin_coh else 0.0
                             self.zmax_coh = self.zmax_coh if self.zmax_coh else 1.0
                             self.zmin_phase = self.zmin_phase if self.zmin_phase else -180
                             self.zmax_phase = self.zmax_phase if self.zmax_phase else 180
                             ax.plot = ax.pcolormesh(x, y, z_coh[n].T,
                                                     vmin=self.zmin_coh,
                                                     vmax=self.zmax_coh,
                                                     cmap=plt.get_cmap(self.colormap_coh)
                                                    )
                             divider = make_axes_locatable(ax)
                             cax = divider.new_horizontal(size='3%', pad=0.05)
                             self.figure.add_axes(cax)
                             plt.colorbar(ax.plot, cax)
                             ax.set_xlim(self.xmin, self.xmax)
                             ax.set_ylim(self.ymin, self.ymax)
                             ax.set_ylabel(self.ylabel)
                             ax.set_xlabel(xlabel)
                             ax.firsttime = False
                             ax1.plot = ax1.pcolormesh(x, y, z_phase[n].T,
                                                     vmin=self.zmin_phase,
                                                     vmax=self.zmax_phase,
                                                     cmap=plt.get_cmap(self.colormap_phase)
                                                    )
                             divider = make_axes_locatable(ax1)
                             cax = divider.new_horizontal(size='3%', pad=0.05)
                             self.figure.add_axes(cax)
                             plt.colorbar(ax1.plot, cax)
                             ax1.set_xlim(self.xmin, self.xmax)
                             ax1.set_ylim(self.ymin, self.ymax)
                             ax1.set_ylabel(self.ylabel)
                             ax1.set_xlabel(xlabel)
                             ax1.firsttime = False
                         else:
                             ax.plot.set_array(z_coh[n].T.ravel())
                             ax1.plot.set_array(z_phase[n].T.ravel())
                         ax.set_title('Coherence Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
                         ax1.set_title('Phase Ch{} * Ch{}'.format(self.dataOut.pairsList[n][0], self.dataOut.pairsList[n][1]), size=8)
                         self.saveTime = self.max_time
             class PlotSpectraMeanData(PlotSpectraData):
                 CODE = 'spc_mean'
                 colormap = 'jet'
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = self.dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     y = self.dataOut.getHeiRange()
                     z = self.data['spc']
                     mean = self.data['mean'][self.max_time]
                     for n, ax in enumerate(self.axes):
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else np.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.ymin = self.ymin if self.ymin else np.nanmin(y)
                             self.ymax = self.ymax if self.ymax else np.nanmax(y)
                             self.zmin = self.zmin if self.zmin else np.nanmin(z)
                             self.zmax = self.zmax if self.zmax else np.nanmax(z)
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             ax.plt_dop = ax.plot(mean[n], y,
                                                  color='k')[0]
                             divider = make_axes_locatable(ax)
                             cax = divider.new_horizontal(size='3%', pad=0.05)
                             self.figure.add_axes(cax)
                             plt.colorbar(ax.plt, cax)
                             ax.set_xlim(self.xmin, self.xmax)
                             ax.set_ylim(self.ymin, self.ymax)
                             ax.set_ylabel(self.ylabel)
                             ax.set_xlabel(xlabel)
                             ax.firsttime = False
                             if self.showprofile:
                                 ax.plt_profile= ax.ax_profile.plot(self.data['rti'][self.max_time][n], y)[0]
                                 ax.ax_profile.set_xlim(self.zmin, self.zmax)
                                 ax.ax_profile.set_ylim(self.ymin, self.ymax)
                                 ax.ax_profile.set_xlabel('dB')
                                 ax.ax_profile.grid(b=True, axis='x')
                                 ax.plt_noise = ax.ax_profile.plot(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y,
                                                                    color="k", linestyle="dashed", lw=2)[0]
                                 [tick.set_visible(False) for tick in ax.ax_profile.get_yticklabels()]
                         else:
                             ax.plt.set_array(z[n].T.ravel())
                             ax.plt_dop.set_data(mean[n], y)
                             if self.showprofile:
                                 ax.plt_profile.set_data(self.data['rti'][self.max_time][n], y)
                                 ax.plt_noise.set_data(numpy.repeat(self.data['noise'][self.max_time][n], len(y)), y)
                         ax.set_title('{} - Noise: {:.2f} dB'.format(self.titles[n], self.data['noise'][self.max_time][n]),
                                      size=8)
                         self.saveTime = self.max_time
             class PlotRTIData(PlotData):
                 CODE = 'rti'
                 colormap = 'jro'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = self.dataOut.nChannels
                     self.width = 10
                     self.height = 2.2*self.nrows if self.nrows<6 else 12
                     if self.nrows==1:
                         self.height += 1
                     self.ylabel = 'Range [Km]'
                     self.titles = ['Channel {}'.format(x) for x in self.dataOut.channelList]
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                         self.axes = []
                     for n in range(self.nrows):
                         ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
                         ax.firsttime = True
                         self.axes.append(ax)
                 def plot(self):
                     self.x = np.array(self.times)
                     self.y = self.dataOut.getHeiRange()
                     self.z = []
                     for ch in range(self.nrows):
                         self.z.append([self.data[self.CODE][t][ch] for t in self.times])
                     self.z = np.array(self.z)
                     for n, ax in enumerate(self.axes):
                         x, y, z = self.fill_gaps(*self.decimate())
                         xmin = self.min_time
                         xmax = xmin+self.xrange*60*60
                         if ax.firsttime:
                             self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
                             self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
                             self.zmin = self.zmin if self.zmin else np.nanmin(self.z)
                             self.zmax = self.zmax if self.zmax else np.nanmax(self.z)
                             plot = ax.pcolormesh(x, y, z[n].T,
                                                  vmin=self.zmin,
                                                  vmax=self.zmax,
                                                  cmap=plt.get_cmap(self.colormap)
                                                 )
                             divider = make_axes_locatable(ax)
                             cax = divider.new_horizontal(size='2%', pad=0.05)
                             self.figure.add_axes(cax)
                             plt.colorbar(plot, cax)
                             ax.set_ylim(self.ymin, self.ymax)
                             ax.xaxis.set_major_formatter(FuncFormatter(func))
                             ax.xaxis.set_major_locator(LinearLocator(6))
                             ax.set_ylabel(self.ylabel)
                             # if self.xmin is None:
                             #     xmin = self.min_time
                             # else:
                             #     xmin = (datetime.datetime.combine(self.dataOut.datatime.date(),
                             #                                      datetime.time(self.xmin, 0, 0))-d1970).total_seconds()
                             ax.set_xlim(xmin, xmax)
                             ax.firsttime = False
                         else:
                             ax.collections.remove(ax.collections[0])
                             ax.set_xlim(xmin, xmax)
                             plot = ax.pcolormesh(x, y, z[n].T,
                                                  vmin=self.zmin,
                                                  vmax=self.zmax,
                                                  cmap=plt.get_cmap(self.colormap)
                                                 )
                         ax.set_title('{} {}'.format(self.titles[n],
                                                     datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
                                      size=8)
                         self.saveTime = self.min_time
             class PlotCOHData(PlotRTIData):
                 CODE = 'coh'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = self.dataOut.nPairs
                     self.width = 10
                     self.height = 2.2*self.nrows if self.nrows<6 else 12
                     if self.nrows==1:
                         self.height += 1
                     self.ylabel = 'Range [Km]'
                     self.titles = ['{} Ch{} * Ch{}'.format(self.CODE.upper(), x[0], x[1]) for x in self.dataOut.pairsList]
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                         self.axes = []
                     for n in range(self.nrows):
                         ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
                         ax.firsttime = True
                         self.axes.append(ax)
             class PlotNoiseData(PlotData):
                 CODE = 'noise'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width = 10
                     self.height = 3.2
                     self.ylabel = 'Intensity [dB]'
                     self.titles = ['Noise']
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                         self.axes = []
                     self.ax = self.figure.add_subplot(self.nrows, self.ncols, 1)
                     self.ax.firsttime = True
                 def plot(self):
                     x = self.times
                     xmin = self.min_time
                     xmax = xmin+self.xrange*60*60
                     if self.ax.firsttime:
                         for ch in self.dataOut.channelList:
                             y = [self.data[self.CODE][t][ch] for t in self.times]
                             self.ax.plot(x, y, lw=1, label='Ch{}'.format(ch))
                         self.ax.firsttime = False
                         self.ax.xaxis.set_major_formatter(FuncFormatter(func))
                         self.ax.xaxis.set_major_locator(LinearLocator(6))
                         self.ax.set_ylabel(self.ylabel)
                         plt.legend()
                     else:
                         for ch in self.dataOut.channelList:
                             y = [self.data[self.CODE][t][ch] for t in self.times]
                             self.ax.lines[ch].set_data(x, y)
                     self.ax.set_xlim(xmin, xmax)
                     self.ax.set_ylim(min(y)-5, max(y)+5)
                     self.saveTime = self.min_time
             class PlotWindProfilerData(PlotRTIData):
                 CODE = 'wind'
                 colormap = 'seismic'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = self.dataOut.data_output.shape[0]
                     self.width = 10
                     self.height = 2.2*self.nrows
                     self.ylabel = 'Height [Km]'
-                    self.titles = ['Zonal' ,'Meridional', 'Vertical']
+                    self.titles = ['Zonal Wind' ,'Meridional Wind', 'Vertical Wind']
                     self.clabels = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
                     self.windFactor = [1, 1, 100]
                     if self.figure is None:
                         self.figure = plt.figure(figsize=(self.width, self.height),
                                                  edgecolor='k',
                                                  facecolor='w')
                     else:
                         self.figure.clf()
                         self.axes = []
                     for n in range(self.nrows):
                         ax = self.figure.add_subplot(self.nrows, self.ncols, n+1)
                         ax.firsttime = True
                         self.axes.append(ax)
                 def plot(self):
                     self.x = np.array(self.times)
                     self.y = self.dataOut.heightList
                     self.z = []
                     for ch in range(self.nrows):
-                        self.z.append([self.data[self.CODE][t][ch] for t in self.times])
+                        self.z.append([self.data['output'][t][ch] for t in self.times])
                     self.z = np.array(self.z)
                     self.z = numpy.ma.masked_invalid(self.z)
                     cmap=plt.get_cmap(self.colormap)
-                    cmap.set_bad('white', 1.)
+                    cmap.set_bad('black', 1.)
                     for n, ax in enumerate(self.axes):
                         x, y, z = self.fill_gaps(*self.decimate())
                         xmin = self.min_time
                         xmax = xmin+self.xrange*60*60
                         if ax.firsttime:
                             self.ymin = self.ymin if self.ymin else np.nanmin(self.y)
                             self.ymax = self.ymax if self.ymax else np.nanmax(self.y)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(abs(self.z[:-1, :]))
                             self.zmin = self.zmin if self.zmin else -self.zmax
                             plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
                                                  vmin=self.zmin,
                                                  vmax=self.zmax,
                                                  cmap=cmap
                                                 )
                             divider = make_axes_locatable(ax)
                             cax = divider.new_horizontal(size='2%', pad=0.05)
-                            cax.set_ylabel(self.clabels[n])
                             self.figure.add_axes(cax)
-                            plt.colorbar(plot, cax)
+                            cb = plt.colorbar(plot, cax)
+                            cb.set_label(self.clabels[n])
                             ax.set_ylim(self.ymin, self.ymax)
                             ax.xaxis.set_major_formatter(FuncFormatter(func))
                             ax.xaxis.set_major_locator(LinearLocator(6))
                             ax.set_ylabel(self.ylabel)
                             ax.set_xlim(xmin, xmax)
                             ax.firsttime = False
                         else:
                             ax.collections.remove(ax.collections[0])
                             ax.set_xlim(xmin, xmax)
                             plot = ax.pcolormesh(x, y, z[n].T*self.windFactor[n],
                                                  vmin=self.zmin,
                                                  vmax=self.zmax,
                                                  cmap=plt.get_cmap(self.colormap)
                                                 )
                         ax.set_title('{} {}'.format(self.titles[n],
                                                     datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')),
                                      size=8)
                         self.saveTime = self.min_time
             class PlotSNRData(PlotRTIData):
                 CODE = 'snr'
                 colormap = 'jet'
             class PlotDOPData(PlotRTIData):
                 CODE = 'dop'
                 colormap = 'jet'
             class PlotPHASEData(PlotCOHData):
                 CODE = 'phase'
                 colormap = 'seismic'
+            class PlotSkyMapData(PlotData):
+                CODE = 'met'
+                def setup(self):
+                    self.ncols = 1
+                    self.nrows = 1
+                    self.width = 7.2
+                    self.height = 7.2
+                    self.xlabel = 'Zonal Zenith Angle (deg)'
+                    self.ylabel = 'Meridional Zenith Angle (deg)'
+                    if self.figure is None:
+                        self.figure = plt.figure(figsize=(self.width, self.height),
+                                                 edgecolor='k',
+                                                 facecolor='w')
+                    else:
+                        self.figure.clf()
+                    self.ax = plt.subplot2grid((self.nrows, self.ncols), (0, 0), 1, 1, polar=True)
+                    self.ax.firsttime = True
+                def plot(self):
+                    arrayParameters = np.concatenate([self.data['param'][t] for t in self.times])
+                    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
+                    if self.ax.firsttime:
+                        self.ax.plot = self.ax.plot(x, y, 'bo', markersize=5)[0]
+                        self.ax.set_ylim(0,90)
+                        self.ax.set_yticks(numpy.arange(0,90,20))
+                        self.ax.set_xlabel(self.xlabel)
+                        self.ax.set_ylabel(self.ylabel)
+                        self.ax.yaxis.labelpad = 40
+                        self.ax.firsttime = False
+                    else:
+                        self.ax.plot.set_data(x, y)
+                    dt1 = datetime.datetime.fromtimestamp(self.min_time).strftime('%y/%m/%d %H:%M:%S')
+                    dt2 = datetime.datetime.fromtimestamp(self.max_time).strftime('%y/%m/%d %H:%M:%S')
+                    title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
+                                                                                                 dt2,
+                                                                                                 len(x))
+                    self.ax.set_title(title, size=8)
+                    self.saveTime = self.max_time

schainpy/model/proc/jroproc_base.py +5 -2

             '''
             $Author: murco $
             $Id: jroproc_base.py 1 2012-11-12 18:56:07Z murco $
             '''
             class ProcessingUnit(object):
                 """
                 Esta es la clase base para el procesamiento de datos.
                 Contiene el metodo "call" para llamar operaciones. Las operaciones pueden ser:
                     - Metodos internos (callMethod)
                     - Objetos del tipo Operation (callObject). Antes de ser llamados, estos objetos
                       tienen que ser agreagados con el metodo "add".
                 """
                 # objeto de datos de entrada (Voltage, Spectra o Correlation)
                 dataIn = None
                 dataInList = []
                 # objeto de datos de entrada (Voltage, Spectra o Correlation)
                 dataOut = None
                 operations2RunDict = None
                 isConfig = False
                 def __init__(self, *args, **kwargs):
                     self.dataIn = None
                     self.dataInList = []
                     self.dataOut = None
                     self.operations2RunDict = {}
                     self.operationKwargs = {}
                     self.isConfig = False
                     self.args = args
                     self.kwargs = kwargs
                 def addOperationKwargs(self, objId, **kwargs):
                     '''
                     '''
                     self.operationKwargs[objId] = kwargs
                 def addOperation(self, opObj, objId):
                     """
                     Agrega un objeto del tipo "Operation" (opObj) a la lista de objetos "self.objectList" y retorna el
                     identificador asociado a este objeto.
                     Input:
                         object    :    objeto de la clase "Operation"
                     Return:
                         objId    :    identificador del objeto, necesario para ejecutar la operacion
                     """
                     self.operations2RunDict[objId] = opObj
                     return objId
                 def getOperationObj(self, objId):
                     if objId not in self.operations2RunDict.keys():
                         return None
                     return self.operations2RunDict[objId]
                 def operation(self, **kwargs):
                     """
                     Operacion directa sobre la data (dataOut.data). Es necesario actualizar los valores de los
                     atributos del objeto dataOut
                     Input:
                         **kwargs    :    Diccionario de argumentos de la funcion a ejecutar
                     """
                     raise NotImplementedError
                 def callMethod(self, name, opId):
                     """
                     Ejecuta el metodo con el nombre "name" y con argumentos **kwargs de la propia clase.
                     Input:
                         name        :    nombre del metodo a ejecutar
                         **kwargs     :    diccionario con los nombres y valores de la funcion a ejecutar.
                     """
                     #Checking the inputs
                     if name == 'run':
                         if not self.checkInputs():
                             self.dataOut.flagNoData = True
                             return False
                     else:
                         #Si no es un metodo RUN la entrada es la misma dataOut (interna)
                         if self.dataOut is not None and self.dataOut.isEmpty():
                             return False
                     #Getting the pointer to method
                     methodToCall = getattr(self, name)
                     #Executing the self method
                     if hasattr(self, 'mp'):
                         if name=='run':
                             if self.mp is False:
                                 self.mp = True
                                 self.start()
                         else:
+                            self.operationKwargs[opId]['parent'] = self.kwargs
                             methodToCall(**self.operationKwargs[opId])
                     else:
                         if name=='run':
                             methodToCall(**self.kwargs)
                         else:
                             methodToCall(**self.operationKwargs[opId])
                     if self.dataOut is None:
                         return False
                     if self.dataOut.isEmpty():
                         return False
                     return True
                 def callObject(self, objId):
                     """
                     Ejecuta la operacion asociada al identificador del objeto "objId"
                     Input:
                         objId        :    identificador del objeto a ejecutar
                         **kwargs    :    diccionario con los nombres y valores de la funcion a ejecutar.
                     Return:
                         None
                     """
                     if self.dataOut is not None and self.dataOut.isEmpty():
                         return False
                     externalProcObj = self.operations2RunDict[objId]
                     if hasattr(externalProcObj, 'mp'):
                         if externalProcObj.mp is False:
+                            externalProcObj.kwargs['parent'] = self.kwargs
                             self.operationKwargs[objId] = externalProcObj.kwargs
                             externalProcObj.mp = True
                             externalProcObj.start()
                     else:
                         externalProcObj.run(self.dataOut, **externalProcObj.kwargs)
                         self.operationKwargs[objId] = externalProcObj.kwargs
                     return True
                 def call(self, opType, opName=None, opId=None):
                     """
                     Return True si ejecuta la operacion interna nombrada "opName" o la operacion externa
                     identificada con el id "opId"; con los argumentos "**kwargs".
                     False si la operacion no se ha ejecutado.
                     Input:
                         opType    :    Puede ser "self" o "external"
                             Depende del tipo de operacion para llamar a:callMethod or callObject:
 . If opType = "self": Llama a un metodo propio de esta clase:
                                     name_method = getattr(self, name)
                                     name_method(**kwargs)
 . If opType = "other" o"external": Llama al metodo "run()" de una instancia de la
                                clase "Operation" o de un derivado de ella:
                                     instanceName = self.operationList[opId]
                                     instanceName.run(**kwargs)
                         opName    : Si la operacion es interna (opType = 'self'), entonces el "opName" sera
                                     usada para llamar a un metodo interno de la clase Processing
                         opId    :    Si la operacion es externa (opType = 'other' o 'external), entonces el
                                     "opId" sera usada para llamar al metodo "run" de la clase Operation
                                     registrada anteriormente con ese Id
                     Exception:
                            Este objeto de tipo Operation debe de haber sido agregado antes con el metodo:
                            "addOperation" e identificado con el valor "opId"  = el id de la operacion.
                            De lo contrario retornara un error del tipo ValueError
                     """
                     if opType == 'self':
                         if not opName:
                             raise ValueError, "opName parameter should be defined"
                         sts = self.callMethod(opName, opId)
                     elif opType == 'other' or opType == 'external' or opType == 'plotter':
                         if not opId:
                             raise ValueError, "opId parameter should be defined"
                         if opId not in self.operations2RunDict.keys():
                             raise ValueError, "Any operation with id=%s has been added" %str(opId)
                         sts = self.callObject(opId)
                     else:
                         raise ValueError, "opType should be 'self', 'external' or 'plotter'; and not '%s'" %opType
                     return sts
                 def setInput(self, dataIn):
                     self.dataIn = dataIn
                     self.dataInList.append(dataIn)
                 def getOutputObj(self):
                     return self.dataOut
                 def checkInputs(self):
                     for thisDataIn in self.dataInList:
                         if thisDataIn.isEmpty():
                             return False
                     return True
                 def setup(self):
                     raise NotImplementedError
                 def run(self):
                     raise NotImplementedError
                 def close(self):
                     #Close every thread, queue or any other object here is it is neccesary.
                     return
             class Operation(object):
                 """
                 Clase base para definir las operaciones adicionales que se pueden agregar a la clase ProcessingUnit
                 y necesiten acumular informacion previa de los datos a procesar. De preferencia usar un buffer de
                 acumulacion dentro de esta clase
                 Ejemplo: Integraciones coherentes, necesita la informacion previa de los n perfiles anteriores (bufffer)
                 """
                 __buffer = None
                 isConfig = False
                 def __init__(self, **kwargs):
                     self.__buffer = None
                     self.isConfig = False
                     self.kwargs = kwargs
                 def setup(self):
                     self.isConfig = True
                     raise NotImplementedError
                 def run(self, dataIn, **kwargs):
                     """
                     Realiza las operaciones necesarias sobre la dataIn.data y actualiza los
                     atributos del objeto dataIn.
                     Input:
                         dataIn    :    objeto del tipo JROData
                     Return:
                         None
                     Affected:
                         __buffer    :    buffer de recepcion de datos.
                     """
                     if not self.isConfig:
                         self.setup(**kwargs)
                     raise NotImplementedError
                 def close(self):
                     pass

schainpy/model/utils/jroutils_publish.py +7 -2

             '''
             @author: Juan C. Espinoza
             '''
             import time
             import json
             import numpy
             import paho.mqtt.client as mqtt
             import zmq
             import cPickle as pickle
             import datetime
             from zmq.utils.monitor import recv_monitor_message
             from functools import wraps
             from threading import Thread
             from multiprocessing import Process
             from schainpy.model.proc.jroproc_base import Operation, ProcessingUnit
             MAXNUMX = 100
             MAXNUMY = 100
             class PrettyFloat(float):
                 def __repr__(self):
                     return '%.2f' % self
             def roundFloats(obj):
                 if isinstance(obj, list):
                     return map(roundFloats, obj)
                 elif isinstance(obj, float):
                     return round(obj, 2)
             def decimate(z):
                 # dx = int(len(self.x)/self.__MAXNUMX) + 1
                 dy = int(len(z[0])/MAXNUMY) + 1
                 return z[::, ::dy]
             class throttle(object):
                 """Decorator that prevents a function from being called more than once every
                 time period.
                 To create a function that cannot be called more than once a minute, but
                 will sleep until it can be called:
                 @throttle(minutes=1)
                 def foo():
                   pass
                 for i in range(10):
                   foo()
                   print "This function has run %s times." % i
                 """
                 def __init__(self, seconds=0, minutes=0, hours=0):
                     self.throttle_period = datetime.timedelta(
                         seconds=seconds, minutes=minutes, hours=hours
                     )
                     self.time_of_last_call = datetime.datetime.min
                 def __call__(self, fn):
                     @wraps(fn)
                     def wrapper(*args, **kwargs):
                         now = datetime.datetime.now()
                         time_since_last_call = now - self.time_of_last_call
                         time_left = self.throttle_period - time_since_last_call
                         if time_left > datetime.timedelta(seconds=0):
                             return
                         self.time_of_last_call = datetime.datetime.now()
                         return fn(*args, **kwargs)
                     return wrapper
             class PublishData(Operation):
                 """Clase publish."""
                 def __init__(self, **kwargs):
                     """Inicio."""
                     Operation.__init__(self, **kwargs)
                     self.isConfig = False
                     self.client = None
                     self.zeromq = None
                     self.mqtt = None
                 def on_disconnect(self, client, userdata, rc):
                     if rc != 0:
                         print("Unexpected disconnection.")
                     self.connect()
                 def connect(self):
                     print 'trying to connect'
                     try:
                         self.client.connect(
                             host=self.host,
                             port=self.port,
                             keepalive=60*10,
                             bind_address='')
                         self.client.loop_start()
                         # self.client.publish(
                         #     self.topic + 'SETUP',
                         #     json.dumps(setup),
                         #     retain=True
                         #     )
                     except:
                         print "MQTT Conection error."
                         self.client = False
                 def setup(self, port=1883, username=None, password=None, clientId="user", zeromq=1, **kwargs):
                     self.counter = 0
                     self.topic = kwargs.get('topic', 'schain')
                     self.delay = kwargs.get('delay', 0)
                     self.plottype = kwargs.get('plottype', 'spectra')
                     self.host = kwargs.get('host', "10.10.10.82")
                     self.port = kwargs.get('port', 3000)
                     self.clientId = clientId
                     self.cnt = 0
                     self.zeromq = zeromq
                     self.mqtt = kwargs.get('plottype', 0)
                     self.client = None
                     setup = []
                     if mqtt is 1:
                         self.client = mqtt.Client(
                             client_id=self.clientId + self.topic + 'SCHAIN',
                             clean_session=True)
                         self.client.on_disconnect = self.on_disconnect
                         self.connect()
                         for plot in self.plottype:
                             setup.append({
                                 'plot': plot,
                                 'topic': self.topic + plot,
                                 'title': getattr(self, plot + '_' + 'title', False),
                                 'xlabel': getattr(self, plot + '_' + 'xlabel', False),
                                 'ylabel': getattr(self, plot + '_' + 'ylabel', False),
                                 'xrange': getattr(self, plot + '_' + 'xrange', False),
                                 'yrange': getattr(self, plot + '_' + 'yrange', False),
                                 'zrange': getattr(self, plot + '_' + 'zrange', False),
                             })
                     if zeromq is 1:
                         context = zmq.Context()
                         self.zmq_socket = context.socket(zmq.PUSH)
                         server = kwargs.get('server', 'zmq.pipe')
                         if 'tcp://' in server:
                             address = server
                         else:
                             address = 'ipc:///tmp/%s' % server
                         self.zmq_socket.connect(address)
                         time.sleep(1)
                 def publish_data(self):
                     self.dataOut.finished = False
                     if self.mqtt is 1:
                         yData = self.dataOut.heightList[:2].tolist()
                         if self.plottype == 'spectra':
                             data = getattr(self.dataOut, 'data_spc')
                             z = data/self.dataOut.normFactor
                             zdB = 10*numpy.log10(z)
                             xlen, ylen = zdB[0].shape
                             dx = int(xlen/MAXNUMX) + 1
                             dy = int(ylen/MAXNUMY) + 1
                             Z = [0 for i in self.dataOut.channelList]
                             for i in self.dataOut.channelList:
                                 Z[i] = zdB[i][::dx, ::dy].tolist()
                             payload = {
                                 'timestamp': self.dataOut.utctime,
                                 'data': roundFloats(Z),
                                 'channels': ['Ch %s' % ch for ch in self.dataOut.channelList],
                                 'interval': self.dataOut.getTimeInterval(),
                                 'type': self.plottype,
                                 'yData': yData
                             }
                             # print payload
                         elif self.plottype in ('rti', 'power'):
                             data = getattr(self.dataOut, 'data_spc')
                             z = data/self.dataOut.normFactor
                             avg = numpy.average(z, axis=1)
                             avgdB = 10*numpy.log10(avg)
                             xlen, ylen = z[0].shape
                             dy = numpy.floor(ylen/self.__MAXNUMY) + 1
                             AVG = [0 for i in self.dataOut.channelList]
                             for i in self.dataOut.channelList:
                                 AVG[i] = avgdB[i][::dy].tolist()
                             payload = {
                                 'timestamp': self.dataOut.utctime,
                                 'data': roundFloats(AVG),
                                 'channels': ['Ch %s' % ch for ch in self.dataOut.channelList],
                                 'interval': self.dataOut.getTimeInterval(),
                                 'type': self.plottype,
                                 'yData': yData
                             }
                         elif self.plottype == 'noise':
                             noise = self.dataOut.getNoise()/self.dataOut.normFactor
                             noisedB = 10*numpy.log10(noise)
                             payload = {
                                 'timestamp': self.dataOut.utctime,
                                 'data': roundFloats(noisedB.reshape(-1, 1).tolist()),
                                 'channels': ['Ch %s' % ch for ch in self.dataOut.channelList],
                                 'interval': self.dataOut.getTimeInterval(),
                                 'type': self.plottype,
                                 'yData': yData
                             }
                         elif self.plottype == 'snr':
                             data = getattr(self.dataOut, 'data_SNR')
                             avgdB = 10*numpy.log10(data)
                             ylen = data[0].size
                             dy = numpy.floor(ylen/self.__MAXNUMY) + 1
                             AVG = [0 for i in self.dataOut.channelList]
                             for i in self.dataOut.channelList:
                                 AVG[i] = avgdB[i][::dy].tolist()
                             payload = {
                                 'timestamp': self.dataOut.utctime,
                                 'data': roundFloats(AVG),
                                 'channels': ['Ch %s' % ch for ch in self.dataOut.channelList],
                                 'type': self.plottype,
                                 'yData': yData
                             }
                         else:
                             print "Tipo de grafico invalido"
                             payload = {
                                 'data': 'None',
                                 'timestamp': 'None',
                                 'type': None
                             }
                             # print 'Publishing data to {}'.format(self.host)
                         self.client.publish(self.topic + self.plottype, json.dumps(payload), qos=0)
                     if self.zeromq is 1:
                         print '[Sending] {} - {}'.format(self.dataOut.type, self.dataOut.datatime)
                         self.zmq_socket.send_pyobj(self.dataOut)
                 def run(self, dataOut, **kwargs):
                     self.dataOut = dataOut
                     if not self.isConfig:
                         self.setup(**kwargs)
                         self.isConfig = True
                     self.publish_data()
                     time.sleep(self.delay)
                 def close(self):
                     if self.zeromq is 1:
                         self.dataOut.finished = True
                         self.zmq_socket.send_pyobj(self.dataOut)
                     if self.client:
                         self.client.loop_stop()
                         self.client.disconnect()
             class ReceiverData(ProcessingUnit, Process):
                 throttle_value = 5
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
                     Process.__init__(self)
                     self.mp = False
                     self.isConfig = False
                     self.isWebConfig = False
                     self.plottypes =[]
                     self.connections = 0
                     server = kwargs.get('server', 'zmq.pipe')
                     plot_server = kwargs.get('plot_server', 'zmq.web')
                     if 'tcp://' in server:
                         address = server
                     else:
                         address = 'ipc:///tmp/%s' % server
                     if 'tcp://' in plot_server:
                         plot_address = plot_server
                     else:
                         plot_address = 'ipc:///tmp/%s' % plot_server
                     self.address = address
                     self.plot_address = plot_address
                     self.plottypes = [s.strip() for s in kwargs.get('plottypes', 'rti').split(',')]
                     self.realtime = kwargs.get('realtime', False)
                     self.throttle_value = kwargs.get('throttle', 5)
                     self.sendData = self.initThrottle(self.throttle_value)
                     self.setup()
                 def setup(self):
                     self.data = {}
                     self.data['times'] = []
                     for plottype in self.plottypes:
                         self.data[plottype] = {}
                     self.data['noise'] = {}
                     self.data['throttle'] = self.throttle_value
                     self.data['ENDED'] = False
                     self.isConfig = True
                     self.data_web = {}
                 def event_monitor(self, monitor):
                     events = {}
                     for name in dir(zmq):
                         if name.startswith('EVENT_'):
                             value = getattr(zmq, name)
                             events[value] = name
                     while monitor.poll():
                         evt = recv_monitor_message(monitor)
                         if evt['event'] == 32:
                             self.connections += 1
                         if evt['event'] == 512:
                             pass
                         if self.connections == 0 and self.started is True:
                             self.ended = True
                         evt.update({'description': events[evt['event']]})
                         if evt['event'] == zmq.EVENT_MONITOR_STOPPED:
                             break
                     monitor.close()
                     print("event monitor thread done!")
                 def initThrottle(self, throttle_value):
                     @throttle(seconds=throttle_value)
                     def sendDataThrottled(fn_sender, data):
                         fn_sender(data)
                     return sendDataThrottled
                 def send(self, data):
                     # print '[sending] data=%s size=%s' % (data.keys(), len(data['times']))
                     self.sender.send_pyobj(data)
                 def update(self):
                     t = self.dataOut.utctime
                     if t in self.data['times']:
                         return
                     self.data['times'].append(t)
                     self.data['dataOut'] = self.dataOut
                     for plottype in self.plottypes:
                         if plottype == 'spc':
                             z = self.dataOut.data_spc/self.dataOut.normFactor
                             self.data[plottype] = 10*numpy.log10(z)
                             self.data['noise'][t] = 10*numpy.log10(self.dataOut.getNoise()/self.dataOut.normFactor)
                         if plottype == 'cspc':
                             jcoherence = self.dataOut.data_cspc/numpy.sqrt(self.dataOut.data_spc*self.dataOut.data_spc)
                             self.data['cspc_coh'] = numpy.abs(jcoherence)
                             self.data['cspc_phase'] = numpy.arctan2(jcoherence.imag, jcoherence.real)*180/numpy.pi
                         if plottype == 'rti':
                             self.data[plottype][t] = self.dataOut.getPower()
                         if plottype == 'snr':
                             self.data[plottype][t] = 10*numpy.log10(self.dataOut.data_SNR)
                         if plottype == 'dop':
                             self.data[plottype][t] = 10*numpy.log10(self.dataOut.data_DOP)
                         if plottype == 'mean':
                             self.data[plottype][t] = self.dataOut.data_MEAN
                         if plottype == 'std':
                             self.data[plottype][t] = self.dataOut.data_STD
                         if plottype == 'coh':
                             self.data[plottype][t] = self.dataOut.getCoherence()
                         if plottype == 'phase':
                             self.data[plottype][t] = self.dataOut.getCoherence(phase=True)
-                        if plottype == 'wind':
+                        if plottype == 'output':
                             self.data[plottype][t] = self.dataOut.data_output
+                        if plottype == 'param':
+                            self.data[plottype][t] = self.dataOut.data_param
                         if self.realtime:
                             self.data_web['timestamp'] = t
                             if plottype == 'spc':
                                 self.data_web[plottype] = roundFloats(decimate(self.data[plottype]).tolist())
                             elif plottype == 'cspc':
                                 self.data_web['cspc_coh'] = roundFloats(decimate(self.data['cspc_coh']).tolist())
                                 self.data_web['cspc_phase'] = roundFloats(decimate(self.data['cspc_phase']).tolist())
                             elif plottype == 'noise':
                                 self.data_web['noise'] = roundFloats(self.data['noise'][t].tolist())
                             else:
                                 self.data_web[plottype] = roundFloats(decimate(self.data[plottype][t]).tolist())
                             self.data_web['interval'] = self.dataOut.getTimeInterval()
                             self.data_web['type'] = plottype
                 def run(self):
                     print '[Starting] {} from {}'.format(self.name, self.address)
                     self.context = zmq.Context()
                     self.receiver = self.context.socket(zmq.PULL)
                     self.receiver.bind(self.address)
                     monitor = self.receiver.get_monitor_socket()
                     self.sender = self.context.socket(zmq.PUB)
                     if self.realtime:
                         self.sender_web = self.context.socket(zmq.PUB)
                         self.sender_web.connect(self.plot_address)
                         time.sleep(1)
-                    self.sender.bind("ipc:///tmp/zmq.plots")
+                    if 'server' in self.kwargs:
+                        self.sender.bind("ipc:///tmp/{}.plots".format(self.kwargs['server']))
+                    else:
+                        self.sender.bind("ipc:///tmp/zmq.plots")
                     t = Thread(target=self.event_monitor, args=(monitor,))
                     t.start()
                     while True:
                         self.dataOut = self.receiver.recv_pyobj()
                         # print '[Receiving] {} - {}'.format(self.dataOut.type,
                         #                                    self.dataOut.datatime.ctime())
                         self.update()
                         if self.dataOut.finished is True:
                             self.send(self.data)
                             self.connections -= 1
                             if self.connections == 0 and self.started:
                                 self.ended = True
                                 self.data['ENDED'] = True
                                 self.send(self.data)
                                 self.setup()
                         else:
                             if self.realtime:
                                 self.send(self.data)
                                 self.sender_web.send_string(json.dumps(self.data_web))
                             else:
                                 self.sendData(self.send, self.data)
                             self.started = True
                     return
                 def sendToWeb(self):
                     if not self.isWebConfig:
                         context = zmq.Context()
                         sender_web_config = context.socket(zmq.PUB)
                         if 'tcp://' in self.plot_address:
                             dum, address, port = self.plot_address.split(':')
                             conf_address = '{}:{}:{}'.format(dum, address, int(port)+1)
                         else:
                             conf_address = self.plot_address + '.config'
                         sender_web_config.bind(conf_address)
                         time.sleep(1)
                         for kwargs in self.operationKwargs.values():
                             if 'plot' in kwargs:
                                 print '[Sending] Config data to web for {}'.format(kwargs['code'].upper())
                                 sender_web_config.send_string(json.dumps(kwargs))
                         self.isWebConfig = True

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