schain-jc Commit - r1205:45d75be01895

Wind and rainfall processing of CLAIRE radar with V3.0

George Yong -

r1205:45d75be01895

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r1205:45d75be01895

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

                 def getFreqRangeTimeResponse(self, extrapoints=0):
                     deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints * self.ippFactor)
-                    freqrange = deltafreq * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (numpy.arange(self.nFFTPoints + extrapoints) -
-                         self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getAcfRange(self, extrapoints=0):
                     deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
-                    freqrange = deltafreq * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (numpy.arange(self.nFFTPoints + extrapoints) -
-                         self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getFreqRange(self, extrapoints=0):
                     deltafreq = self.getFmax() / (self.nFFTPoints * self.ippFactor)
-                    freqrange = deltafreq * \
+                    freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
-                        (numpy.arange(self.nFFTPoints + extrapoints) -
-                         self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getVelRange(self, extrapoints=0):
                     deltav = self.getVmax() / (self.nFFTPoints * self.ippFactor)
-                    velrange = deltav * (numpy.arange(self.nFFTPoints +
+                    velrange = deltav * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.)
-                                                      extrapoints) - self.nFFTPoints / 2.)
                     if self.nmodes:
                         return velrange/self.nmodes
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
-                    normFactor = self.nProfiles * self.nIncohInt * \
+                    normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter
-                        self.nCohInt * pwcode * self.windowOfFilter
                     return normFactor
                 def getTimeInterval(self):
-                    timeInterval = self.ippSeconds * self.nCohInt * \
+                    timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor
-                        self.nIncohInt * self.nProfiles * self.ippFactor
                     return timeInterval
                             pairsIndexList.append(self.pairsList.index(pair))
                     for i in range(len(pairsIndexList)):
                         pair = self.pairsList[pairsIndexList[i]]
-                        ccf = numpy.average(
+                        ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0)
-                            self.data_cspc[pairsIndexList[i], :, :], axis=0)
                         powa = numpy.average(self.data_spc[pair[0], :, :], axis=0)
                         powb = numpy.average(self.data_spc[pair[1], :, :], axis=0)
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)

schainpy/model/graphics/jroplot_parameters.py +8 -3

+            @MPDecorator
             class WindProfilerPlot_(Figure):
                 __isConfig = None
                 HEIGHTPROF = None
                 PREFIX = 'wind'
-                def __init__(self, **kwargs):
+                def __init__(self):
-                    Figure.__init__(self, **kwargs)
+                    Figure.__init__(self)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                         zmax            :    None
                     """
+                    if dataOut.flagNoData:
+                        return dataOut
             #         if timerange is not None:
             #             self.timerange = timerange
             #
                         self.isConfig = False
                         update_figfile = True
+                    return dataOut
             @MPDecorator
             class ParametersPlot_(Figure):

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

                 z = numpy.ma.masked_invalid(z)
                 cmap = matplotlib.pyplot.get_cmap(colormap)
-                cmap.set_bad('black', 1.)
+                cmap.set_bad('white', 1.)
                 imesh = ax.pcolormesh(x, y, z.T, vmin=zmin, vmax=zmax, cmap=cmap)
                 cb = matplotlib.pyplot.colorbar(imesh, cax=ax_cb)
                 cb.set_label(cblabel)
                 z = numpy.ma.masked_invalid(z)
                 cmap = matplotlib.pyplot.get_cmap(colormap)
-                cmap.set_bad('black', 1.)
+                cmap.set_bad('white', 1.)
                 ax.pcolormesh(x, y, z.T, vmin=zmin, vmax=zmax, cmap=cmap)

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

                         self.parameters = one + two
                         self.parameters_d = one_d + two_d
-                    log.success('Parameters found: {}'.format(','.join(self.parameters)),
+                    log.success('Parameters found: {}'.format(','.join(str(self.parameters))),
                                 'MADReader')
                     if s_parameters:
-                        log.success('Spatial parameters: {}'.format(','.join(s_parameters)),
+                        log.success('Spatial parameters: {}'.format(','.join(str(s_parameters))),
                                     'MADReader')
                     for param in list(self.oneDDict.keys()):

schainpy/model/proc/jroproc_parameters.py +13 -12

                         self.dataOut.ippFactor = self.dataIn.ippFactor
                         self.dataOut.abscissaList = self.dataIn.getVelRange(1)
                         self.dataOut.spc_noise = self.dataIn.getNoise()
-                        self.dataOut.spc_range = (self.dataIn.getFreqRange(1)/1000. , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1))
+                        self.dataOut.spc_range = (self.dataIn.getFreqRange(1) , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1))
                         # self.dataOut.normFactor = self.dataIn.normFactor
                         self.dataOut.pairsList = self.dataIn.pairsList
                         self.dataOut.groupList = self.dataIn.pairsList
                     '''Reacomodando SPCrange'''
-                    VelRange=numpy.roll(VelRange,-(self.Num_Bin/2) ,axis=0)
+                    VelRange=numpy.roll(VelRange,-(int(self.Num_Bin/2)) ,axis=0)
-                    VelRange[-(self.Num_Bin/2):]+= Vmax
+                    VelRange[-(int(self.Num_Bin/2)):]+= Vmax
-                    FrecRange=numpy.roll(FrecRange,-(self.Num_Bin/2),axis=0)
+                    FrecRange=numpy.roll(FrecRange,-(int(self.Num_Bin/2)),axis=0)
-                    FrecRange[-(self.Num_Bin/2):]+= Fmax
+                    FrecRange[-(int(self.Num_Bin/2)):]+= Fmax
-                    TimeRange=numpy.roll(TimeRange,-(self.Num_Bin/2),axis=0)
+                    TimeRange=numpy.roll(TimeRange,-(int(self.Num_Bin/2)),axis=0)
-                    TimeRange[-(self.Num_Bin/2):]+= Tmax
+                    TimeRange[-(int(self.Num_Bin/2)):]+= Tmax
                     ''' ------------------ '''
                     Breaker2R=numpy.where(VelRange == Breaker2R)
-                    SPCroll = numpy.roll(self.spc,-(self.Num_Bin/2) ,axis=1)
+                    SPCroll = numpy.roll(self.spc,-(int(self.Num_Bin/2)) ,axis=1)
                     SPCcut = SPCroll.copy()
                     for i in range(self.Num_Chn):
                     dataOut.spcparam_range[2]=VelRange
                     dataOut.spcparam_range[1]=TimeRange
                     dataOut.spcparam_range[0]=FrecRange
+                    return dataOut
             class GaussianFit(Operation):
                         Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) )
                         Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * tauW * numpy.pi * ThetaT * ThetaR)
-                        RadarConstant = 5e-26 * Numerator / Denominator #
+                        RadarConstant = 10e-26 * Numerator / Denominator #
                         ''' =============================  '''
                     dataOut.data_param[1]=V_mean
                     dataOut.data_param[2]=RR
+                    return dataOut
                 def dBZeMODE2(self, dataOut): #    Processing for MIRA35C
                     for Height in range(nHeights):
-                        [Vzon,Vmer,Vver, GaussCenter, PhaseSlope, FitGaussCSPC]= self.WindEstimation(spc, cspc, pairsList, ChanDist, Height, noise, dataOut.spc_range.copy(), dbSNR[Height], SNRlimit)
+                        [Vzon,Vmer,Vver, GaussCenter, PhaseSlope, FitGaussCSPC]= self.WindEstimation(spc, cspc, pairsList, ChanDist, Height, noise, dataOut.spc_range, dbSNR[Height], SNRlimit)
                         PhaseLine = numpy.append(PhaseLine, PhaseSlope)
                         if abs(Vzon)<100. and abs(Vzon)> 0.:
                     dataOut.data_output=data_output
-                    return
+                    return dataOut
                 def moving_average(self,x, N=2):

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