schain-jc Commit - r548:f6f23959bcc9

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def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,

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def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,

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xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,

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xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,

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parameterIndex = None, onlyPositive = False,

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parameterIndex = None, onlyPositive = False,

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SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None,

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zlabel = "", parameterName = "", parameterObject = "data_param",

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zlabel = "", parameterName = "", parameterObject = "data_param",

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save=False, figpath='', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,

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save=False, figpath='', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,

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server=None, folder=None, username=None, password=None,

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server=None, folder=None, username=None, password=None,

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else:

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else:

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channelIndexList = numpy.array(channelIndexList)

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channelIndexList = numpy.array(channelIndexList)

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nchan = len(channelIndexList) #Number of channels being plotted

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if timerange != None:

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if timerange != None:

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self.timerange = timerange

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self.timerange = timerange

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zRange = dataOut.abscissaList

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zRange = dataOut.abscissaList

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nplots = z.shape[0] #Number of wind dimensions estimated

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nplots = z.shape[0] #Number of wind dimensions estimated

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# thisDatetime = dataOut.datatime

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# thisDatetime = dataOut.datatime

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if dataOut.data_SNR != None:

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SNRarray = dataOut.data_SNR

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SNRdB = 10*numpy.log10(SNRarray)

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# SNRavgdB = 10*numpy.log10(SNRavg)

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ind = numpy.where(SNRdB < 10**(SNRthresh/10))

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z[ind] = numpy.nan

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thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1])

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thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1])

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title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))

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title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))

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xlabel = ""

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xlabel = ""

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ylabel = "Range (Km)"

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ylabel = "Range (Km)"

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if SNR: nplots = 2*nplots

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if onlyPositive:

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if onlyPositive:

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colormap = "jet"

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colormap = "jet"

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zmin = 0

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zmin = 0

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if zmin == None: zmin = numpy.nanmin(zRange)

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if zmin == None: zmin = numpy.nanmin(zRange)

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if zmax == None: zmax = numpy.nanmax(zRange)

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if zmax == None: zmax = numpy.nanmax(zRange)

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if SNR != None:

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if SNRmin == None: SNRmin = numpy.nanmin(SNRdB)

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if SNRmax == None: SNRmax = numpy.nanmax(SNRdB)

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self.FTP_WEI = ftp_wei

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self.FTP_WEI = ftp_wei

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self.EXP_CODE = exp_code

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self.EXP_CODE = exp_code

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self.SUB_EXP_CODE = sub_exp_code

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self.SUB_EXP_CODE = sub_exp_code

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if ((self.xmax - x[1]) < (x[1]-x[0])):

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if ((self.xmax - x[1]) < (x[1]-x[0])):

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x[1] = self.xmax

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x[1] = self.xmax

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for i in range(n~~plots~~):

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for i in range(nchan):

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title = "%s Channel %d: %s" %(parameterName, dataOut.channelList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))

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if SNR: j = 2*i

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else: j = i

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title = "%s Channel %d: %s" %(parameterName, channelIndexList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))

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if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):

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if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):

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title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)

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title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)

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axes = self.axesList[i*self.__nsubplots]

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axes = self.axesList[j*self.__nsubplots]

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z1 = z[i,:].reshape((1,-1))

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z1 = z[i,:].reshape((1,-1))

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axes.pcolorbuffer(x, y, z1,

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axes.pcolorbuffer(x, y, z1,

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xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,

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xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,

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xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,

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xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,

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ticksize=9, cblabel=zlabel, cbsize="1%")

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ticksize=9, cblabel=zlabel, cbsize="1%")

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if SNR:

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title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))

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axes = self.axesList[(j + 1)*self.__nsubplots]

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z1 = SNRdB[i,:].reshape((1,-1))

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axes.pcolorbuffer(x, y, z1,

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xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,

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xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet",

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ticksize=9, cblabel=zlabel, cbsize="1%")

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self.draw()

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self.draw()

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if self.figfile == None:

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if self.figfile == None:

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                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,
                         parameterIndex = None, onlyPositive = False,
+                        SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None,
                         zlabel = "", parameterName = "", parameterObject = "data_param",
                         save=False, figpath='', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                     else:
                         channelIndexList = numpy.array(channelIndexList)
+                    nchan = len(channelIndexList) #Number of channels being plotted
                     if timerange != None:
                         self.timerange = timerange
                     zRange = dataOut.abscissaList
                     nplots = z.shape[0]    #Number of wind dimensions estimated
             #        thisDatetime = dataOut.datatime
+                    if dataOut.data_SNR != None:
+                        SNRarray = dataOut.data_SNR
+                        SNRdB = 10*numpy.log10(SNRarray)
+            #             SNRavgdB = 10*numpy.log10(SNRavg)
+                        ind = numpy.where(SNRdB < 10**(SNRthresh/10))
+                        z[ind] = numpy.nan
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
+                    if SNR: nplots = 2*nplots
                     if onlyPositive:
                         colormap = "jet"
                         zmin = 0
                         if zmin == None: zmin = numpy.nanmin(zRange)
                         if zmax == None: zmax = numpy.nanmax(zRange)
+                        if SNR != None:
+                            if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
+                            if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
-                    for i in range(nplots):
+                    for i in range(nchan):
-                        title = "%s Channel %d: %s" %(parameterName, dataOut.channelList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
+                        if SNR: j = 2*i
+                        else: j = i
+                        title = "%s Channel %d: %s" %(parameterName, channelIndexList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
-                        axes = self.axesList[i*self.__nsubplots]
+                        axes = self.axesList[j*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                     ticksize=9, cblabel=zlabel, cbsize="1%")
+                        if SNR:
+                            title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
+                            axes = self.axesList[(j + 1)*self.__nsubplots]
+                            z1 = SNRdB[i,:].reshape((1,-1))
+                            axes.pcolorbuffer(x, y, z1,
+                                    xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
+                                    xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet",
+                                    ticksize=9, cblabel=zlabel, cbsize="1%")
                     self.draw()
                     if self.figfile == None: