schain-jc Commit - r612:d0a641be5ae3

-Bug fixed: selecting channels and cross pairs...

Miguel Valdez -

r612:d0a641be5ae3

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r612:d0a641be5ae3

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schainpy/model/graphics/jroplot_parameters.py +12 -12

             import os
             import datetime
             import numpy
             from figure import Figure, isRealtime
             from plotting_codes import *
             class MomentsPlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 def __init__(self):
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 280
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MOMENTS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 3
                         colspan = 2
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return None
                     if realtime:
                         if not(isRealtime(utcdatatime = dataOut.utctime)):
                             print 'Skipping this plot function'
                             return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = dataOut.data_pre[channelIndexList,:,:]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     noise = dataOut.noise/factor
                     zdB = 10*numpy.log10(z)
                     avgdB = 10*numpy.log10(avg)
                     noisedB = 10*numpy.log10(noise)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters"
                     xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(avgdB)*0.9
                         if zmax == None: zmax = numpy.nanmax(avgdB)*0.9
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i]+1, noisedB[i], str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[i,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, cblabel='')
                                     #Mean Line
                         mean = dataOut.data_param[i, 1, :]
                         axes.addpline(mean, y, idline=0, color="black", linestyle="solid", lw=1)
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[i], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                             noiseline = numpy.repeat(noisedB[i], len(y))
                             axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class SkyMapPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'mmap'
                 def __init__(self):
                     self.__isConfig = False
                     self.__nsubplots = 1
             #         self.WIDTH = 280
             #         self.HEIGHT = 250
                     self.WIDTH = 600
                     self.HEIGHT = 600
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MSKYMAP_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=False, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH, #+ self.WIDTHPROF,
                                       heightplot = self.HEIGHT,# + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = 1,1
                     counter = 0
                     x = 0
                     y = 0
                     self.addAxes(1, 1, 0, 0, 1, 1, True)
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     arrayParameters = dataOut.data_param[0,:]
                     error = arrayParameters[:,-1]
                     indValid = numpy.where(error == 0)[0]
                     finalMeteor = arrayParameters[indValid,:]
                     finalAzimuth = finalMeteor[:,4]
                     finalZenith = finalMeteor[:,5]
                     x = finalAzimuth*numpy.pi/180
                     y = finalZenith
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters"
                     xlabel = "Zonal Zenith Angle (deg) "
                     ylabel = "Meridional Zenith Angle (deg)"
                     if not self.__isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.firstdate = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         self.__isConfig = True
                     self.setWinTitle(title)
                     i = 0
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     axes = self.axesList[i*self.__nsubplots]
                     nevents = axes.x_buffer.shape[0] + x.shape[0]
                     title = "Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n" %(self.firstdate,str_datetime,nevents)
                     axes.polar(x, y,
                                 title=title, xlabel=xlabel, ylabel=ylabel,
                                 ticksize=9, cblabel='')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class WindProfilerPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'wind'
                 def __init__(self):
                     self.timerange = None
                     self.__isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 150
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = WIND_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='False',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmax_ver = None, zmin_ver = None, SNRmin = None, SNRmax = None,
                         timerange=None, SNRthresh = None,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
-            #         if timerange != None:
+            #         if timerange is not None:
             #             self.timerange = timerange
             #
             #         tmin = None
             #         tmax = None
                     x = dataOut.getTimeRange1()
             #         y = dataOut.heightList
                     y = dataOut.heightList
                     z = dataOut.data_output.copy()
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
-                    if dataOut.data_SNR != None:
+                    if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR
                         SNRavg = numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         if SNRthresh == None: SNRthresh = -5.0
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
             #         showprofile = False
             #        thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + "Wind"
                     xlabel = ""
                     ylabel = "Range (Km)"
                     if not self.__isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
-                        if timerange != None:
+                        if timerange is not None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmax == None: zmax = numpy.nanmax(abs(z[range(2),:]))
                         #if numpy.isnan(zmax): zmax = 50
                         if zmin == None: zmin = -zmax
                         if nplotsw == 3:
                             if zmax_ver == None: zmax_ver = numpy.nanmax(abs(z[2,:]))
                             if zmin_ver == None: zmin_ver = -zmax_ver
-                        if dataOut.data_SNR != None:
+                        if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.__isConfig = True
                         self.figfile = figfile
                     self.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal', 'Meridional', 'Vertical']
                     strCb = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
                     zmaxVector = [zmax, zmax, zmax_ver]
                     zminVector = [zmin, zmin, zmin_ver]
                     windFactor = [1,1,100]
                     for i in range(nplotsw):
                         title = "%s Wind: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))*windFactor[i]
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb[i], cbsize="1%", colormap="RdBu_r" )
-                    if dataOut.data_SNR != None:
+                    if dataOut.data_SNR is not None:
                         i += 1
                         title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.__isConfig = False
                         self.figfile = None
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=False)
             class ParametersPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 def __init__(self):
                     self.timerange = 2*60*60
                     self.__isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 150
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = PARMS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,
                         parameterIndex = None, onlyPositive = False,
                         SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None, onlySNR = False,
                         DOP = True,
                         zlabel = "", parameterName = "", parameterObject = "data_param",
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     data_param = getattr(dataOut, parameterObject)
                     if channelList == None:
                         channelIndexList = numpy.arange(data_param.shape[0])
                     else:
                         channelIndexList = numpy.array(channelList)
                     nchan = len(channelIndexList) #Number of channels being plotted
                     if nchan < 1:
                         return
                     nGraphsByChannel = 0
                     if SNR:
                         nGraphsByChannel += 1
                     if DOP:
                         nGraphsByChannel += 1
                     if nGraphsByChannel < 1:
                         return
                     nplots = nGraphsByChannel*nchan
-                    if timerange != None:
+                    if timerange is not None:
                         self.timerange = timerange
                     #tmin = None
                     #tmax = None
                     if parameterIndex == None:
                         parameterIndex = 1
                     x = dataOut.getTimeRange1()
                     y = dataOut.heightList
                     z = data_param[channelIndexList,parameterIndex,:].copy()
                     zRange = dataOut.abscissaList
             #         nChannels = z.shape[0]    #Number of wind dimensions estimated
             #        thisDatetime = dataOut.datatime
-                    if dataOut.data_SNR != None:
+                    if dataOut.data_SNR is not None:
                         SNRarray = dataOut.data_SNR[channelIndexList,:]
                         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()[0])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     if (SNR and not onlySNR): nplots = 2*nplots
                     if onlyPositive:
                         colormap = "jet"
                         zmin = 0
                     else: colormap = "RdBu_r"
                     if not self.__isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(zRange)
                         if zmax == None: zmax = numpy.nanmax(zRange)
                         if SNR:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.__isConfig = True
                         self.figfile = figfile
                     self.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     for i in range(nchan):
                         if (SNR and not onlySNR): j = 2*i
                         else: j = i
                         j = nGraphsByChannel*i
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                         if not onlySNR:
                             axes = self.axesList[j*self.__nsubplots]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                     ticksize=9, cblabel=zlabel, cbsize="1%")
                         if DOP:
                             title = "%s Channel %d: %s" %(parameterName, channelIndexList[i]+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[j]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                         xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                         xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                         ticksize=9, cblabel=zlabel, cbsize="1%")
                         if SNR:
                             title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i]+1, thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                             axes = self.axesList[(j)*self.__nsubplots]
                             if not onlySNR:
                                 axes = self.axesList[(j + 1)*self.__nsubplots]
                             axes = self.axesList[(j + nGraphsByChannel-1)]
                             z1 = SNRdB[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 x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.__isConfig = False
                         self.figfile = None
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=False)
             class SpectralFittingPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 N = None
                 ippSeconds = None
                 def __init__(self):
                     self.__isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = SPECFIT_CODE
                     self.WIDTH = 450
                     self.HEIGHT = 250
                     self.WIDTHPROF = 0
                     self.HEIGHTPROF = 0
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=False, show=True):
                     showprofile = False
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 5
                     colspan = 4
                     if showprofile:
                         ncolspan = 5
                         colspan = 4
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, cutHeight=None, fit=False, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if cutHeight==None:
                         h=270
                     heightindex = numpy.abs(cutHeight - dataOut.heightList).argmin()
                     cutHeight = dataOut.heightList[heightindex]
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList[:-1]
                     #y = dataOut.getHeiRange()
                     z = dataOut.data_pre[:,:,heightindex]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     listChannels = z.shape[0]
                     #Reconstruct Function
                     if fit==True:
                         groupArray = dataOut.groupList
                         listChannels = groupArray.reshape((groupArray.size))
                         listChannels.sort()
                         spcFitLine = numpy.zeros(z.shape)
                         constants = dataOut.constants
                         nGroups = groupArray.shape[0]
                         nChannels = groupArray.shape[1]
                         nProfiles = z.shape[1]
                         for f in range(nGroups):
                             groupChann = groupArray[f,:]
                             p = dataOut.data_param[f,:,heightindex]
             #                 p = numpy.array([ 89.343967,0.14036615,0.17086219,18.89835291,1.58388365,1.55099167])
                             fitLineAux = dataOut.library.modelFunction(p, constants)*nProfiles
                             fitLineAux = fitLineAux.reshape((nChannels,nProfiles))
                             spcFitLine[groupChann,:] = fitLineAux
             #             spcFitLine = spcFitLine/factor
                         z = z[listChannels,:]
                         spcFitLine = spcFitLine[listChannels,:]
                         spcFitLinedB = 10*numpy.log10(spcFitLine)
                     zdB = 10*numpy.log10(z)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Doppler Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     xlabel = "Velocity (m/s)"
                     ylabel = "Spectrum"
                     if not self.__isConfig:
                         nplots = listChannels.size
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(zdB)
                         if ymax == None: ymax = numpy.nanmax(zdB)+2
                         self.__isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
             #             title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i])
                         title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i]+1)
                         axes = self.axesList[i*self.__nsubplots]
                         if fit == False:
                             axes.pline(x, zdB[i,:],
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title
                                         )
                         if fit == True:
                             fitline=spcFitLinedB[i,:]
                             y=numpy.vstack([zdB[i,:],fitline] )
                             legendlabels=['Data','Fitting']
                             axes.pmultilineyaxis(x, y,
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title,
                                         legendlabels=legendlabels, marker=None,
                                         linestyle='solid', grid='both')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class EWDriftsPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'drift'
                 def __init__(self):
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 150
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = EWDRIFT_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmaxVertical = None, zminVertical = None, zmaxZonal = None, zminZonal = None,
                         timerange=None, SNRthresh = -numpy.inf, SNRmin = None, SNRmax = None, SNR_1 = False,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
-                    if timerange != None:
+                    if timerange is not None:
                         self.timerange = timerange
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1()
             #         y = dataOut.heightList
                     y = dataOut.heightList
                     z = dataOut.data_output
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
-                    if dataOut.data_SNR != None:
+                    if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR
                         if SNR_1:
                             SNR += 1
                         SNRavg = numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
                     showprofile = False
             #        thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(x[1])
                     title = wintitle + " EW Drifts"
                     xlabel = ""
                     ylabel = "Height (Km)"
                     if not self.__isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmaxZonal == None: zmaxZonal = numpy.nanmax(abs(z[0,:]))
                         if zminZonal == None: zminZonal = -zmaxZonal
                         if zmaxVertical == None: zmaxVertical = numpy.nanmax(abs(z[1,:]))
                         if zminVertical == None: zminVertical = -zmaxVertical
-                        if dataOut.data_SNR != None:
+                        if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.__isConfig = True
                     self.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal','Vertical']
                     strCb = 'Velocity (m/s)'
                     zmaxVector = [zmaxZonal, zmaxVertical]
                     zminVector = [zminZonal, zminVertical]
                     for i in range(nplotsw):
                         title = "%s Drifts: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb, cbsize="1%", colormap="RdBu_r")
-                    if dataOut.data_SNR != None:
+                    if dataOut.data_SNR is not None:
                         i += 1
                         if SNR_1:
                             title = "Signal Noise Ratio + 1 (SNR+1): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         else:
                             title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.__isConfig = False
                         self.figfile = None
             class PhasePlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'mphase'
                 def __init__(self):
                     self.timerange = 24*60*60
                     self.__isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 600
                     self.HEIGHT = 300
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = MPHASE_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.filename_phase = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 7
                     colspan = 6
                     self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH+self.WIDTHPROF,
                                       heightplot = self.HEIGHT+self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1)
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         timerange=None,
                         save=False, figpath='', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1()
                     y = dataOut.getHeiRange()
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[1])
                     title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase"
                     #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = dataOut.data_output
                     if not self.__isConfig:
                         self.nplots = phase_beacon.size
                         self.setup(id=id,
                                    nplots=self.nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
-                        if timerange != None:
+                        if timerange is not None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0
                         if ymax == None: ymax = numpy.nanmax(phase_beacon) + 10.0
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.__isConfig = True
                         self.figfile = figfile
                         self.xdata = numpy.array([])
                         self.ydata = numpy.array([])
                         #open file beacon phase
                         path = '%s%03d' %(self.PREFIX, self.id)
                         beacon_file = os.path.join(path,'%s.txt'%self.name)
                         self.filename_phase = os.path.join(figpath,beacon_file)
                         #self.save_phase(self.filename_phase)
                     #store data beacon phase
                     #self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Offset %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["phase %d"%(chan) for chan in numpy.arange(self.nplots)]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata)==0:
                         self.ydata = phase_beacon.reshape(-1,1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1)))
                     axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
                                 XAxisAsTime=True, grid='both'
                                 )
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         del self.xdata
                         del self.ydata
                         self.__isConfig = False
                     if self.figfile == None:
                         str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.figfile = self.getFilename(name = str_datetime)
                     if figpath != '':
                         self.counter_imagwr += 1
                         if (self.counter_imagwr>=wr_period):
                             # store png plot to local folder
                             self.saveFigure(figpath, self.figfile)
                             # store png plot to FTP server according to RT-Web format
                             name = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS)
                             ftp_filename = os.path.join(figpath, name)
                             self.saveFigure(figpath, ftp_filename)
                             self.counter_imagwr = 0
                         self.figfile = None
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=False)

schainpy/model/io/jroIO_spectra.py +12 -12

             '''
             Created on Jul 2, 2014
             @author: roj-idl71
             '''
             import numpy
             from jroIO_base import LOCALTIME, JRODataReader, JRODataWriter
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, RadarControllerHeader, ProcessingHeader
             from schainpy.model.data.jrodata import Spectra
             class SpectraReader(JRODataReader, ProcessingUnit):
                 """
                 Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura
                 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones)
                 son almacenados en tres buffer's para el Self Spectra, el Cross Spectra y el DC Channel.
                                     paresCanalesIguales    * alturas * perfiles  (Self Spectra)
                                     paresCanalesDiferentes * alturas * perfiles  (Cross Spectra)
                                     canales * alturas                            (DC Channels)
                 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
                 RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la
                 cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de
                 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
                 Example:
                     dpath = "/home/myuser/data"
                     startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
                     endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
                     readerObj = SpectraReader()
                     readerObj.setup(dpath, startTime, endTime)
                     while(True):
                         readerObj.getData()
                         print readerObj.data_spc
                         print readerObj.data_cspc
                         print readerObj.data_dc
                         if readerObj.flagNoMoreFiles:
                             break
                 """
                 pts2read_SelfSpectra = 0
                 pts2read_CrossSpectra = 0
                 pts2read_DCchannels = 0
                 ext = ".pdata"
                 optchar = "P"
                 dataOut = None
                 nRdChannels = None
                 nRdPairs = None
                 rdPairList = []
                 def __init__(self):
                     """
                     Inicializador de la clase SpectraReader para la lectura de datos de espectros.
                     Inputs:
                         dataOut    :    Objeto de la clase Spectra. Este objeto sera utilizado para
                                           almacenar un perfil de datos cada vez que se haga un requerimiento
                                           (getData). El perfil sera obtenido a partir del buffer de datos,
                                           si el buffer esta vacio se hara un nuevo proceso de lectura de un
                                           bloque de datos.
                                           Si este parametro no es pasado se creara uno internamente.
                     Affected:
                         self.dataOut
                     Return      : None
                     """
                     #Eliminar de la base la herencia
                     ProcessingUnit.__init__(self)
             #         self.isConfig = False
                     self.pts2read_SelfSpectra = 0
                     self.pts2read_CrossSpectra = 0
                     self.pts2read_DCchannels = 0
                     self.datablock = None
                     self.utc = None
                     self.ext = ".pdata"
                     self.optchar = "P"
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                     self.online = 0
                     self.fp = None
                     self.idFile = None
                     self.dtype = None
                     self.fileSizeByHeader = None
                     self.filenameList = []
                     self.filename = None
                     self.fileSize = None
                     self.firstHeaderSize = 0
                     self.basicHeaderSize = 24
                     self.pathList = []
                     self.lastUTTime = 0
                     self.maxTimeStep = 30
                     self.flagNoMoreFiles = 0
                     self.set = 0
                     self.path = None
                     self.delay  = 60   #seconds
                     self.nTries = 3  #quantity tries
                     self.nFiles = 3   #number of files for searching
                     self.nReadBlocks = 0
                     self.flagIsNewFile = 1
                     self.__isFirstTimeOnline = 1
             #         self.ippSeconds = 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     self.nTotalBlocks = 0
                     self.blocksize = 0
                     self.dataOut = self.createObjByDefault()
                     self.profileIndex = 1 #Always
                 def createObjByDefault(self):
                     dataObj = Spectra()
                     return dataObj
                 def __hasNotDataInBuffer(self):
                     return 1
                 def getBlockDimension(self):
                     """
                     Obtiene la cantidad de puntos a leer por cada bloque de datos
                     Affected:
                         self.nRdChannels
                         self.nRdPairs
                         self.pts2read_SelfSpectra
                         self.pts2read_CrossSpectra
                         self.pts2read_DCchannels
                         self.blocksize
                         self.dataOut.nChannels
                         self.dataOut.nPairs
                     Return:
                         None
                     """
                     self.nRdChannels = 0
                     self.nRdPairs = 0
                     self.rdPairList = []
                     for i in range(0, self.processingHeaderObj.totalSpectra*2, 2):
                         if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]:
                             self.nRdChannels = self.nRdChannels + 1 #par de canales iguales
                         else:
                             self.nRdPairs = self.nRdPairs + 1 #par de canales diferentes
                             self.rdPairList.append((self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1]))
                     pts2read = self.processingHeaderObj.nHeights * self.processingHeaderObj.profilesPerBlock
                     self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read)
                     self.blocksize = self.pts2read_SelfSpectra
                     if self.processingHeaderObj.flag_cspc:
                         self.pts2read_CrossSpectra = int(self.nRdPairs * pts2read)
                         self.blocksize += self.pts2read_CrossSpectra
                     if self.processingHeaderObj.flag_dc:
                         self.pts2read_DCchannels = int(self.systemHeaderObj.nChannels * self.processingHeaderObj.nHeights)
                         self.blocksize += self.pts2read_DCchannels
             #        self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels
                 def readBlock(self):
                     """
                     Lee el bloque de datos desde la posicion actual del puntero del archivo
                     (self.fp) y actualiza todos los parametros relacionados al bloque de datos
                     (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
                     es seteado a 0
                     Return: None
                     Variables afectadas:
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                     Exceptions:
                         Si un bloque leido no es un bloque valido
                     """
                     blockOk_flag = False
                     fpointer = self.fp.tell()
                     spc = numpy.fromfile( self.fp, self.dtype[0], self.pts2read_SelfSpectra )
                     spc = spc.reshape( (self.nRdChannels, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
                     if self.processingHeaderObj.flag_cspc:
                         cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra )
                         cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
                     if self.processingHeaderObj.flag_dc:
                         dc = numpy.fromfile( self.fp, self.dtype, self.pts2read_DCchannels ) #int(self.processingHeaderObj.nHeights*self.systemHeaderObj.nChannels) )
                         dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D
                     if not(self.processingHeaderObj.shif_fft):
                         #desplaza a la derecha en el eje 2 determinadas posiciones
                         shift = int(self.processingHeaderObj.profilesPerBlock/2)
                         spc = numpy.roll( spc, shift , axis=2 )
                         if self.processingHeaderObj.flag_cspc:
                             #desplaza a la derecha en el eje 2 determinadas posiciones
                             cspc = numpy.roll( cspc, shift, axis=2 )
             #            self.processingHeaderObj.shif_fft = True
                     spc = numpy.transpose( spc, (0,2,1) )
                     self.data_spc = spc
                     if self.processingHeaderObj.flag_cspc:
                         cspc = numpy.transpose( cspc, (0,2,1) )
                         self.data_cspc = cspc['real'] + cspc['imag']*1j
                     else:
                         self.data_cspc = None
                     if self.processingHeaderObj.flag_dc:
                         self.data_dc = dc['real'] + dc['imag']*1j
                     else:
                         self.data_dc = None
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def getFirstHeader(self):
                     self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
                     self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
             #         self.dataOut.ippSeconds = self.ippSeconds
             #         self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt * self.processingHeaderObj.nIncohInt * self.processingHeaderObj.profilesPerBlock
                     self.dataOut.dtype = self.dtype
             #         self.dataOut.nPairs = self.nPairs
                     self.dataOut.pairsList = self.rdPairList
                     self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.nFFTPoints = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
                     self.dataOut.nIncohInt = self.processingHeaderObj.nIncohInt
                     xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight
                     self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
                     self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
                     self.dataOut.flagShiftFFT = self.processingHeaderObj.shif_fft
                     self.dataOut.flagDecodeData = False #asumo q la data no esta decodificada
                     self.dataOut.flagDeflipData = False #asumo q la data esta sin flip
-                    if self.radarControllerHeaderObj.code != None:
+                    if self.radarControllerHeaderObj.code is not None:
             #             self.dataOut.nCode = self.radarControllerHeaderObj.nCode
             #
             #             self.dataOut.nBaud = self.radarControllerHeaderObj.nBaud
             #
             #             self.dataOut.code = self.radarControllerHeaderObj.code
                         self.dataOut.flagDecodeData = True
                 def getData(self):
                     """
                     First method to execute before "RUN" is called.
                     Copia el buffer de lectura a la clase "Spectra",
                     con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de
                     lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock"
                     Return:
 :    Si no hay mas archivos disponibles
 :    Si hizo una buena copia del buffer
                     Affected:
                         self.dataOut
                         self.flagDiscontinuousBlock
                         self.flagIsNewBlock
                     """
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     if self.__hasNotDataInBuffer():
                         if not( self.readNextBlock() ):
                             self.dataOut.flagNoData = True
                             return 0
                     #data es un numpy array de 3 dmensiones (perfiles, alturas y canales)
-                    if self.data_dc == None:
+                    if self.data_dc is None:
                         self.dataOut.flagNoData = True
                         return 0
                     self.getBasicHeader()
                     self.getFirstHeader()
                     self.dataOut.data_spc = self.data_spc
                     self.dataOut.data_cspc = self.data_cspc
                     self.dataOut.data_dc = self.data_dc
                     self.dataOut.flagNoData = False
                     self.dataOut.realtime = self.online
                     return self.dataOut.data_spc
             class SpectraWriter(JRODataWriter, Operation):
                 """
                 Esta clase permite escribir datos de espectros a archivos procesados (.pdata). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 ext = ".pdata"
                 optchar = "P"
                 shape_spc_Buffer = None
                 shape_cspc_Buffer = None
                 shape_dc_Buffer = None
                 data_spc = None
                 data_cspc = None
                 data_dc = None
             #    dataOut = None
                 def __init__(self):
                     """
                     Inicializador de la clase SpectraWriter para la escritura de datos de espectros.
                     Affected:
                         self.dataOut
                         self.basicHeaderObj
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.processingHeaderObj
                     Return: None
                     """
                     Operation.__init__(self)
                     self.isConfig = False
                     self.nTotalBlocks = 0
                     self.data_spc = None
                     self.data_cspc = None
                     self.data_dc = None
                     self.fp = None
                     self.flagIsNewFile = 1
                     self.nTotalBlocks = 0
                     self.flagIsNewBlock = 0
                     self.setFile = None
                     self.dtype = None
                     self.path = None
                     self.noMoreFiles = 0
                     self.filename = None
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                 def hasAllDataInBuffer(self):
                     return 1
                 def setBlockDimension(self):
                     """
                     Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
                     Affected:
                         self.shape_spc_Buffer
                         self.shape_cspc_Buffer
                         self.shape_dc_Buffer
                     Return: None
                     """
                     self.shape_spc_Buffer = (self.dataOut.nChannels,
                                              self.processingHeaderObj.nHeights,
                                              self.processingHeaderObj.profilesPerBlock)
                     self.shape_cspc_Buffer = (self.dataOut.nPairs,
                                               self.processingHeaderObj.nHeights,
                                               self.processingHeaderObj.profilesPerBlock)
                     self.shape_dc_Buffer = (self.dataOut.nChannels,
                                             self.processingHeaderObj.nHeights)
                 def writeBlock(self):
                     """
                     Escribe el buffer en el file designado
                     Affected:
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.nWriteBlocks
                     Return: None
                     """
                     spc = numpy.transpose( self.data_spc, (0,2,1) )
                     if not( self.processingHeaderObj.shif_fft ):
                         spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
                     data = spc.reshape((-1))
                     data = data.astype(self.dtype[0])
                     data.tofile(self.fp)
-                    if self.data_cspc != None:
+                    if self.data_cspc is not None:
                         data = numpy.zeros( self.shape_cspc_Buffer, self.dtype )
                         cspc = numpy.transpose( self.data_cspc, (0,2,1) )
                         if not( self.processingHeaderObj.shif_fft ):
                             cspc = numpy.roll( cspc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
                         data['real'] = cspc.real
                         data['imag'] = cspc.imag
                         data = data.reshape((-1))
                         data.tofile(self.fp)
-                    if self.data_dc != None:
+                    if self.data_dc is not None:
                         data = numpy.zeros( self.shape_dc_Buffer, self.dtype )
                         dc = self.data_dc
                         data['real'] = dc.real
                         data['imag'] = dc.imag
                         data = data.reshape((-1))
                         data.tofile(self.fp)
                     self.data_spc.fill(0)
-                    if self.data_dc != None:
+                    if self.data_dc is not None:
                         self.data_dc.fill(0)
-                    if self.data_cspc != None:
+                    if self.data_cspc is not None:
                         self.data_cspc.fill(0)
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nWriteBlocks += 1
                     self.blockIndex += 1
             #         print "[Writing] Block = %d04" %self.blockIndex
                 def putData(self):
                     """
                     Setea un bloque de datos y luego los escribe en un file
                     Affected:
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                     Return:
 :    Si no hay data o no hay mas files que puedan escribirse
 :    Si se escribio la data de un bloque en un file
                     """
                     if self.dataOut.flagNoData:
                         return 0
                     self.flagIsNewBlock = 0
                     if self.dataOut.flagDiscontinuousBlock:
                         self.data_spc.fill(0)
                         self.data_cspc.fill(0)
                         self.data_dc.fill(0)
                         self.setNextFile()
                     if self.flagIsNewFile == 0:
                         self.setBasicHeader()
                     self.data_spc = self.dataOut.data_spc.copy()
-                    if self.dataOut.data_cspc != None:
+                    if self.dataOut.data_cspc is not None:
                         self.data_cspc = self.dataOut.data_cspc.copy()
                     self.data_dc = self.dataOut.data_dc.copy()
                     # #self.processingHeaderObj.dataBlocksPerFile)
                     if self.hasAllDataInBuffer():
             #            self.setFirstHeader()
                         self.writeNextBlock()
                     return 1
                 def __getProcessFlags(self):
                     processFlags = 0
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList =  [PROCFLAG.DATATYPE_CHAR,
                                        PROCFLAG.DATATYPE_SHORT,
                                        PROCFLAG.DATATYPE_LONG,
                                        PROCFLAG.DATATYPE_INT64,
                                        PROCFLAG.DATATYPE_FLOAT,
                                        PROCFLAG.DATATYPE_DOUBLE]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             dtypeValue = datatypeValueList[index]
                             break
                     processFlags += dtypeValue
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
-                    if self.dataOut.code != None:
+                    if self.dataOut.code is not None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nIncohInt > 1:
                         processFlags += PROCFLAG.INCOHERENT_INTEGRATION
-                    if self.dataOut.data_dc != None:
+                    if self.dataOut.data_dc is not None:
                         processFlags += PROCFLAG.SAVE_CHANNELS_DC
                     return processFlags
                 def __getBlockSize(self):
                     '''
                     Este metodos determina el cantidad de bytes para un bloque de datos de tipo Spectra
                     '''
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList = [1,2,4,8,4,8]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             datatypeValue = datatypeValueList[index]
                             break
                     pts2write = self.dataOut.nHeights * self.dataOut.nFFTPoints
                     pts2write_SelfSpectra = int(self.dataOut.nChannels * pts2write)
                     blocksize = (pts2write_SelfSpectra*datatypeValue)
-                    if self.dataOut.data_cspc != None:
+                    if self.dataOut.data_cspc is not None:
                         pts2write_CrossSpectra = int(self.dataOut.nPairs * pts2write)
                         blocksize += (pts2write_CrossSpectra*datatypeValue*2)
-                    if self.dataOut.data_dc != None:
+                    if self.dataOut.data_dc is not None:
                         pts2write_DCchannels = int(self.dataOut.nChannels * self.dataOut.nHeights)
                         blocksize += (pts2write_DCchannels*datatypeValue*2)
                     blocksize = blocksize #* datatypeValue * 2 #CORREGIR ESTO
                     return blocksize
                 def setFirstHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.dtype
                     Return:
                         None
                     """
                     self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
                     self.systemHeaderObj.nChannels = self.dataOut.nChannels
                     self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
                     old_code_size = self.dataOut.radarControllerHeaderObj.code_size
                     new_code_size = int(numpy.ceil(self.dataOut.nBaud/32.))*self.dataOut.nCode*4
                     self.radarControllerHeaderObj.size = self.radarControllerHeaderObj.size - old_code_size + new_code_size
                     self.setBasicHeader()
                     processingHeaderSize = 40 # bytes
                     self.processingHeaderObj.dtype = 1 # Spectra
                     self.processingHeaderObj.blockSize = self.__getBlockSize()
                     self.processingHeaderObj.profilesPerBlock = self.dataOut.nFFTPoints
                     self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
                     self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
                     self.processingHeaderObj.processFlags = self.__getProcessFlags()
                     self.processingHeaderObj.nCohInt = self.dataOut.nCohInt# Se requiere para determinar el valor de timeInterval
                     self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt
                     self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels
                     self.processingHeaderObj.shif_fft = self.dataOut.flagShiftFFT
                     if self.processingHeaderObj.totalSpectra > 0:
                         channelList = []
                         for channel in range(self.dataOut.nChannels):
                             channelList.append(channel)
                             channelList.append(channel)
                         pairsList = []
                         if self.dataOut.nPairs > 0:
                             for pair in self.dataOut.pairsList:
                                 pairsList.append(pair[0])
                                 pairsList.append(pair[1])
                         spectraComb = channelList + pairsList
                         spectraComb = numpy.array(spectraComb,dtype="u1")
                         self.processingHeaderObj.spectraComb = spectraComb
                         sizeOfSpcComb = len(spectraComb)
                         processingHeaderSize += sizeOfSpcComb
             #        The processing header should not have information about code
-            #        if self.dataOut.code != None:
+            #        if self.dataOut.code is not None:
             #            self.processingHeaderObj.code = self.dataOut.code
             #            self.processingHeaderObj.nCode = self.dataOut.nCode
             #            self.processingHeaderObj.nBaud = self.dataOut.nBaud
             #            nCodeSize = 4 # bytes
             #            nBaudSize = 4 # bytes
             #            codeSize = 4 # bytes
             #            sizeOfCode = int(nCodeSize + nBaudSize + codeSize * self.dataOut.nCode * self.dataOut.nBaud)
             #            processingHeaderSize += sizeOfCode
                     if self.processingHeaderObj.nWindows != 0:
                         self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
                         self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                         self.processingHeaderObj.nHeights = self.dataOut.nHeights
                         self.processingHeaderObj.samplesWin = self.dataOut.nHeights
                         sizeOfFirstHeight = 4
                         sizeOfdeltaHeight = 4
                         sizeOfnHeights = 4
                         sizeOfWindows = (sizeOfFirstHeight + sizeOfdeltaHeight + sizeOfnHeights)*self.processingHeaderObj.nWindows
                         processingHeaderSize += sizeOfWindows
                     self.processingHeaderObj.size = processingHeaderSize

schainpy/model/io/jroIO_voltage.py +3 -3

             '''
             Created on Jul 2, 2014
             @author: roj-idl71
             '''
             import numpy
             from jroIO_base import LOCALTIME, JRODataReader, JRODataWriter
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, RadarControllerHeader, ProcessingHeader
             from schainpy.model.data.jrodata import Voltage
             class VoltageReader(JRODataReader, ProcessingUnit):
                 """
                 Esta clase permite leer datos de voltage desde archivos en formato rawdata (.r). La lectura
                 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones:
                 perfiles*alturas*canales) son almacenados en la variable "buffer".
                                          perfiles * alturas * canales
                 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
                 RadarControllerHeader y Voltage. Los tres primeros se usan para almacenar informacion de la
                 cabecera de datos (metadata), y el cuarto (Voltage) para obtener y almacenar un perfil de
                 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
                 Example:
                     dpath = "/home/myuser/data"
                     startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
                     endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
                     readerObj = VoltageReader()
                     readerObj.setup(dpath, startTime, endTime)
                     while(True):
                         #to get one profile
                         profile =  readerObj.getData()
                         #print the profile
                         print profile
                         #If you want to see all datablock
                         print readerObj.datablock
                         if readerObj.flagNoMoreFiles:
                             break
                 """
                 ext = ".r"
                 optchar = "D"
                 dataOut = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageReader para la lectura de datos de voltage.
                     Input:
                         dataOut    :    Objeto de la clase Voltage. Este objeto sera utilizado para
                                           almacenar un perfil de datos cada vez que se haga un requerimiento
                                           (getData). El perfil sera obtenido a partir del buffer de datos,
                                           si el buffer esta vacio se hara un nuevo proceso de lectura de un
                                           bloque de datos.
                                           Si este parametro no es pasado se creara uno internamente.
                     Variables afectadas:
                         self.dataOut
                     Return:
                         None
                     """
                     ProcessingUnit.__init__(self)
                     self.isConfig = False
                     self.datablock = None
                     self.utc = 0
                     self.ext = ".r"
                     self.optchar = "D"
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                     self.online = 0
                     self.fp = None
                     self.idFile = None
                     self.dtype = None
                     self.fileSizeByHeader = None
                     self.filenameList = []
                     self.filename = None
                     self.fileSize = None
                     self.firstHeaderSize = 0
                     self.basicHeaderSize = 24
                     self.pathList = []
                     self.filenameList = []
                     self.lastUTTime = 0
                     self.maxTimeStep = 30
                     self.flagNoMoreFiles = 0
                     self.set = 0
                     self.path = None
                     self.profileIndex = 2**32-1
                     self.delay  = 3   #seconds
                     self.nTries  = 3  #quantity tries
                     self.nFiles = 3   #number of files for searching
                     self.nReadBlocks = 0
                     self.flagIsNewFile = 1
                     self.__isFirstTimeOnline = 1
             #         self.ippSeconds = 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     self.nTotalBlocks = 0
                     self.blocksize = 0
                     self.dataOut = self.createObjByDefault()
                     self.nTxs = 1
                     self.txIndex = 0
                 def createObjByDefault(self):
                     dataObj = Voltage()
                     return dataObj
                 def __hasNotDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def getBlockDimension(self):
                     """
                     Obtiene la cantidad de puntos a leer por cada bloque de datos
                     Affected:
                         self.blocksize
                     Return:
                         None
                     """
                     pts2read = self.processingHeaderObj.profilesPerBlock * self.processingHeaderObj.nHeights * self.systemHeaderObj.nChannels
                     self.blocksize = pts2read
                 def readBlock(self):
                     """
                     readBlock lee el bloque de datos desde la posicion actual del puntero del archivo
                     (self.fp) y actualiza todos los parametros relacionados al bloque de datos
                     (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
                     es seteado a 0
                     Inputs:
                         None
                     Return:
                         None
                     Affected:
                         self.profileIndex
                         self.datablock
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                     Exceptions:
                         Si un bloque leido no es un bloque valido
                     """
                     current_pointer_location = self.fp.tell()
                     junk = numpy.fromfile( self.fp, self.dtype, self.blocksize )
                     try:
                         junk = junk.reshape( (self.processingHeaderObj.profilesPerBlock, self.processingHeaderObj.nHeights, self.systemHeaderObj.nChannels) )
                     except:
                         #print "The read block (%3d) has not enough data" %self.nReadBlocks
                         if self.waitDataBlock(pointer_location=current_pointer_location):
                             junk = numpy.fromfile( self.fp, self.dtype, self.blocksize )
                             junk = junk.reshape( (self.processingHeaderObj.profilesPerBlock, self.processingHeaderObj.nHeights, self.systemHeaderObj.nChannels) )
             #             return 0
                     junk = numpy.transpose(junk, (2,0,1))
                     self.datablock = junk['real'] + junk['imag']*1j
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def getFirstHeader(self):
                     self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
                     self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
                     if self.nTxs > 1:
                         self.dataOut.radarControllerHeaderObj.ippSeconds = self.radarControllerHeaderObj.ippSeconds/self.nTxs
             #         self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt
             #
-            #         if self.radarControllerHeaderObj.code != None:
+            #         if self.radarControllerHeaderObj.code is not None:
             #
             #             self.dataOut.nCode = self.radarControllerHeaderObj.nCode
             #
             #             self.dataOut.nBaud = self.radarControllerHeaderObj.nBaud
             #
             #             self.dataOut.code = self.radarControllerHeaderObj.code
                     self.dataOut.dtype = self.dtype
                     self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock*self.nTxs
                     if self.processingHeaderObj.nHeights % self.nTxs != 0:
                         raise ValueError, "nTxs (%d) should be a multiple of nHeights (%d)" %(self.nTxs, self.processingHeaderObj.nHeights)
                     xf = self.processingHeaderObj.firstHeight + int(self.processingHeaderObj.nHeights/self.nTxs)*self.processingHeaderObj.deltaHeight
                     self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
                     self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
                     self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.flagDecodeData = False #asumo q la data no esta decodificada
                     self.dataOut.flagDeflipData = False #asumo q la data no esta sin flip
                     self.dataOut.flagShiftFFT = False
                 def getData(self):
                     """
                     getData obtiene una unidad de datos del buffer de lectura, un perfil,  y la copia al objeto self.dataOut
                     del tipo "Voltage" con todos los parametros asociados a este (metadata). cuando no hay datos
                     en el buffer de lectura es necesario hacer una nueva lectura de los bloques de datos usando
                     "readNextBlock"
                     Ademas incrementa el contador del buffer "self.profileIndex" en 1.
                     Return:
                         Si el flag self.getByBlock ha sido seteado el bloque completo es copiado a self.dataOut y el self.profileIndex
                         es igual al total de perfiles leidos desde el archivo.
                         Si self.getByBlock == False:
                             self.dataOut.data = buffer[:, thisProfile, :]
                             shape = [nChannels, nHeis]
                         Si self.getByBlock == True:
                             self.dataOut.data = buffer[:, :, :]
                             shape = [nChannels, nProfiles, nHeis]
                     Variables afectadas:
                         self.dataOut
                         self.profileIndex
                     Affected:
                         self.dataOut
                         self.profileIndex
                         self.flagDiscontinuousBlock
                         self.flagIsNewBlock
                     """
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     if self.__hasNotDataInBuffer():
                         if not( self.readNextBlock() ):
                             return 0
                         self.getFirstHeader()
                     if self.datablock is None:
                         self.dataOut.flagNoData = True
                         return 0
                     if not self.getByBlock:
                         """
                         Return profile by profile
                         If nTxs > 1 then one profile is divided by nTxs and number of total
                         blocks is increased by nTxs (nProfiles *= nTxs)
                         """
                         self.dataOut.flagDataAsBlock = False
                         if self.nTxs == 1:
                             self.dataOut.data = self.datablock[:,self.profileIndex,:]
                             self.dataOut.profileIndex = self.profileIndex
                             self.profileIndex += 1
                         else:
                             iniHei_ForThisTx = (self.txIndex)*int(self.processingHeaderObj.nHeights/self.nTxs)
                             endHei_ForThisTx = (self.txIndex+1)*int(self.processingHeaderObj.nHeights/self.nTxs)
             #                 print iniHei_ForThisTx, endHei_ForThisTx
                             self.dataOut.data = self.datablock[:, self.profileIndex, iniHei_ForThisTx:endHei_ForThisTx]
                             self.dataOut.profileIndex = self.profileIndex*self.nTxs + self.txIndex
                             self.txIndex += 1
                             if self.txIndex == self.nTxs:
                                 self.txIndex = 0
                                 self.profileIndex += 1
                     else:
                         """
                         Return all block
                         """
                         self.dataOut.flagDataAsBlock = True
                         self.dataOut.data = self.datablock
                         self.dataOut.profileIndex = self.processingHeaderObj.profilesPerBlock
                         self.profileIndex = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.flagNoData = False
                     self.getBasicHeader()
                     self.dataOut.realtime = self.online
                     return self.dataOut.data
             class VoltageWriter(JRODataWriter, Operation):
                 """
                 Esta clase permite escribir datos de voltajes a archivos procesados (.r). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 ext = ".r"
                 optchar = "D"
                 shapeBuffer = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageWriter para la escritura de datos de espectros.
                     Affected:
                         self.dataOut
                     Return: None
                     """
                     Operation.__init__(self)
                     self.nTotalBlocks = 0
                     self.profileIndex = 0
                     self.isConfig = False
                     self.fp = None
                     self.flagIsNewFile = 1
                     self.nTotalBlocks = 0
                     self.flagIsNewBlock = 0
                     self.setFile = None
                     self.dtype = None
                     self.path = None
                     self.filename = None
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                 def hasAllDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def setBlockDimension(self):
                     """
                     Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
                     Affected:
                         self.shape_spc_Buffer
                         self.shape_cspc_Buffer
                         self.shape_dc_Buffer
                     Return: None
                     """
                     self.shapeBuffer = (self.processingHeaderObj.profilesPerBlock,
                                         self.processingHeaderObj.nHeights,
                                         self.systemHeaderObj.nChannels)
                     self.datablock = numpy.zeros((self.systemHeaderObj.nChannels,
                                                  self.processingHeaderObj.profilesPerBlock,
                                                  self.processingHeaderObj.nHeights),
                                                  dtype=numpy.dtype('complex64'))
                 def writeBlock(self):
                     """
                     Escribe el buffer en el file designado
                     Affected:
                         self.profileIndex
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.blockIndex
                     Return: None
                     """
                     data = numpy.zeros( self.shapeBuffer, self.dtype )
                     junk = numpy.transpose(self.datablock, (1,2,0))
                     data['real'] = junk.real
                     data['imag'] = junk.imag
                     data = data.reshape( (-1) )
                     data.tofile( self.fp )
                     self.datablock.fill(0)
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.blockIndex += 1
                     self.nTotalBlocks += 1
             #         print "[Writing] Block = %04d" %self.blockIndex
                 def putData(self):
                     """
                     Setea un bloque de datos y luego los escribe en un file
                     Affected:
                         self.flagIsNewBlock
                         self.profileIndex
                     Return:
 :    Si no hay data o no hay mas files que puedan escribirse
 :    Si se escribio la data de un bloque en un file
                     """
                     if self.dataOut.flagNoData:
                         return 0
                     self.flagIsNewBlock = 0
                     if self.dataOut.flagDiscontinuousBlock:
                         self.datablock.fill(0)
                         self.profileIndex = 0
                         self.setNextFile()
                     if self.profileIndex == 0:
                         self.setBasicHeader()
                     self.datablock[:,self.profileIndex,:] = self.dataOut.data
                     self.profileIndex += 1
                     if self.hasAllDataInBuffer():
                         #if self.flagIsNewFile:
                         self.writeNextBlock()
             #            self.setFirstHeader()
                     return 1
                 def __getProcessFlags(self):
                     processFlags = 0
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList =  [PROCFLAG.DATATYPE_CHAR,
                                        PROCFLAG.DATATYPE_SHORT,
                                        PROCFLAG.DATATYPE_LONG,
                                        PROCFLAG.DATATYPE_INT64,
                                        PROCFLAG.DATATYPE_FLOAT,
                                        PROCFLAG.DATATYPE_DOUBLE]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             dtypeValue = datatypeValueList[index]
                             break
                     processFlags += dtypeValue
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
-                    if self.dataOut.code != None:
+                    if self.dataOut.code is not None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nCohInt > 1:
                         processFlags += PROCFLAG.COHERENT_INTEGRATION
                     return processFlags
                 def __getBlockSize(self):
                     '''
                     Este metodos determina el cantidad de bytes para un bloque de datos de tipo Voltage
                     '''
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList = [1,2,4,8,4,8]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             datatypeValue = datatypeValueList[index]
                             break
                     blocksize = int(self.dataOut.nHeights * self.dataOut.nChannels * self.profilesPerBlock * datatypeValue * 2)
                     return blocksize
                 def setFirstHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.dtype
                     Return:
                         None
                     """
                     self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
                     self.systemHeaderObj.nChannels = self.dataOut.nChannels
                     self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
                     self.setBasicHeader()
                     processingHeaderSize = 40 # bytes
                     self.processingHeaderObj.dtype = 0 # Voltage
                     self.processingHeaderObj.blockSize = self.__getBlockSize()
                     self.processingHeaderObj.profilesPerBlock = self.profilesPerBlock
                     self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
                     self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
                     self.processingHeaderObj.processFlags = self.__getProcessFlags()
                     self.processingHeaderObj.nCohInt = self.dataOut.nCohInt
                     self.processingHeaderObj.nIncohInt = 1 # Cuando la data de origen es de tipo Voltage
                     self.processingHeaderObj.totalSpectra = 0 # Cuando la data de origen es de tipo Voltage
-            #         if self.dataOut.code != None:
+            #         if self.dataOut.code is not None:
             #             self.processingHeaderObj.code = self.dataOut.code
             #             self.processingHeaderObj.nCode = self.dataOut.nCode
             #             self.processingHeaderObj.nBaud = self.dataOut.nBaud
             #             codesize = int(8 + 4 * self.dataOut.nCode * self.dataOut.nBaud)
             #             processingHeaderSize += codesize
                     if self.processingHeaderObj.nWindows != 0:
                         self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
                         self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                         self.processingHeaderObj.nHeights = self.dataOut.nHeights
                         self.processingHeaderObj.samplesWin = self.dataOut.nHeights
                         processingHeaderSize += 12
                     self.processingHeaderObj.size = processingHeaderSize

schainpy/model/proc/jroproc_spectra.py +17 -17

             import numpy
             import math
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import Spectra
             from schainpy.model.data.jrodata import hildebrand_sekhon
             class SpectraProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.buffer = None
                     self.firstdatatime = None
                     self.profIndex = 0
                     self.dataOut = Spectra()
                     self.id_min = None
                     self.id_max = None
                 def __updateObjFromInput(self):
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.dstFlag = self.dataIn.dstFlag
                     self.dataOut.errorCount = self.dataIn.errorCount
                     self.dataOut.useLocalTime = self.dataIn.useLocalTime
                     self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
                     self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
             #        self.dataOut.nHeights = self.dataIn.nHeights
             #        self.dataOut.nChannels = self.dataIn.nChannels
                     self.dataOut.nBaud = self.dataIn.nBaud
                     self.dataOut.nCode = self.dataIn.nCode
                     self.dataOut.code = self.dataIn.code
                     self.dataOut.nProfiles = self.dataOut.nFFTPoints
             #        self.dataOut.channelIndexList = self.dataIn.channelIndexList
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.firstdatatime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
             #        self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
             #         self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
             #         self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.realtime = self.dataIn.realtime
                     self.dataOut.azimuth = self.dataIn.azimuth
                     self.dataOut.zenith = self.dataIn.zenith
                     self.dataOut.beam.codeList = self.dataIn.beam.codeList
                     self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
                     self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
                 def __getFft(self):
                     """
                     Convierte valores de Voltaje a Spectra
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                         self.profIndex
                         self.buffer
                         self.dataOut.flagNoData
                     """
                     fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1)
                     fft_volt = fft_volt.astype(numpy.dtype('complex'))
                     dc = fft_volt[:,0,:]
                     #calculo de self-spectra
                     fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
                     spc = fft_volt * numpy.conjugate(fft_volt)
                     spc = spc.real
                     blocksize = 0
                     blocksize += dc.size
                     blocksize += spc.size
                     cspc = None
                     pairIndex = 0
                     if self.dataOut.pairsList != None:
                         #calculo de cross-spectra
                         cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
                         for pair in self.dataOut.pairsList:
                             if pair[0] not in self.dataOut.channelList:
                                 raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
                             if pair[1] not in self.dataOut.channelList:
                                 raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
                             cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:])
                             pairIndex += 1
                         blocksize += cspc.size
                     self.dataOut.data_spc = spc
                     self.dataOut.data_cspc = cspc
                     self.dataOut.data_dc = dc
                     self.dataOut.blockSize = blocksize
                     self.dataOut.flagShiftFFT = False
                 def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None):
                     self.dataOut.flagNoData = True
                     if self.dataIn.type == "Spectra":
                         self.dataOut.copy(self.dataIn)
                         return True
                     if self.dataIn.type == "Voltage":
                         if nFFTPoints == None:
                             raise ValueError, "This SpectraProc.run() need nFFTPoints input variable"
                         if nProfiles == None:
                             nProfiles = nFFTPoints
             #                 raise ValueError, "This SpectraProc.run() need nProfiles input variable"
                         if ippFactor == None:
                             ippFactor = 1
                         self.dataOut.ippFactor = ippFactor
                         self.dataOut.nFFTPoints = nFFTPoints
                         self.dataOut.pairsList = pairsList
                         if self.buffer is None:
                             self.buffer = numpy.zeros((self.dataIn.nChannels,
                                                        nProfiles,
                                                        self.dataIn.nHeights),
                                                     dtype='complex')
                             self.id_min = 0
                             self.id_max = self.dataIn.data.shape[1]
                         if len(self.dataIn.data.shape) == 2:
                             self.buffer[:,self.profIndex,:] = self.dataIn.data.copy()
                             self.profIndex += 1
                         else:
                             if self.dataIn.data.shape[1] == nProfiles:
                                 self.buffer = self.dataIn.data.copy()
                                 self.profIndex = nProfiles
                             elif self.dataIn.data.shape[1] < nProfiles:
                                 self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data
                                 self.profIndex += self.dataIn.data.shape[1]
                                 self.id_min += self.dataIn.data.shape[1]
                                 self.id_max += self.dataIn.data.shape[1]
                             else:
                                 raise ValueError, "The type object %s has %d profiles, it should be equal to %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles)
                                 self.dataOut.flagNoData = True
                                 return 0
                         if self.firstdatatime == None:
                             self.firstdatatime = self.dataIn.utctime
                         if self.profIndex == nProfiles:
                             self.__updateObjFromInput()
                             self.__getFft()
                             self.dataOut.flagNoData = False
                             self.buffer = None
                             self.firstdatatime = None
                             self.profIndex = 0
                         return True
                     raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type)
                 def __selectPairs(self, channelList=None):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for pairIndex in self.dataOut.pairsIndexList:
                         #First pair
                         if self.dataOut.pairsList[pairIndex][0] not in channelList:
                             continue
                         #Second pair
                         if self.dataOut.pairsList[pairIndex][1] not in channelList:
                             continue
                         pairsIndexListSelected.append(pairIndex)
                     if not pairsIndexListSelected:
                         self.dataOut.data_cspc = None
                         self.dataOut.pairsList = []
                         return
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
-                    self.dataOut.pairsList = self.dataOut.pairsList[pairsIndexListSelected]
+                    self.dataOut.pairsList = [self.dataOut.pairsList[i] for i in pairsIndexListSelected]
                     return
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError, "Error selecting channels: The value %d in channelList is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                 def selectChannelsByIndex(self, channelIndexList):
                     """
                     Selecciona un bloque de datos en base a canales segun el channelIndexList
                     Input:
                         channelIndexList    :    lista sencilla de canales a seleccionar por ej. [2,3,7]
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList)
             #         nChannels = len(channelIndexList)
                     data_spc = self.dataOut.data_spc[channelIndexList,:]
                     data_dc = self.dataOut.data_dc[channelIndexList,:]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
             #        self.dataOut.nChannels = nChannels
                     self.__selectPairs(self.dataOut.channelList)
                     return 1
                 def selectHeights(self, minHei, maxHei):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minHei > maxHei):
                         raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, maxHei)
                     if (minHei < self.dataOut.heightList[0]):
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     minIndex = 0
                     maxIndex = 0
                     heights = self.dataOut.heightList
                     inda = numpy.where(heights >= minHei)
                     indb = numpy.where(heights <= maxHei)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return 1
                 def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
                     newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
                     if hei_ref != None:
                         newheis = numpy.where(self.dataOut.heightList>hei_ref)
                     minIndex = min(newheis[0])
                     maxIndex = max(newheis[0])
                     data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
                     heightList = self.dataOut.heightList[minIndex:maxIndex+1]
                     # determina indices
                     nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
                     avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
                     beacon_dB = numpy.sort(avg_dB)[-nheis:]
                     beacon_heiIndexList = []
                     for val in avg_dB.tolist():
                         if val >= beacon_dB[0]:
                             beacon_heiIndexList.append(avg_dB.tolist().index(val))
                     #data_spc = data_spc[:,:,beacon_heiIndexList]
                     data_cspc = None
-                    if self.dataOut.data_cspc != None:
+                    if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
                         #data_cspc = data_cspc[:,:,beacon_heiIndexList]
                     data_dc = None
-                    if self.dataOut.data_dc != None:
+                    if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
                         #data_dc = data_dc[:,beacon_heiIndexList]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = heightList
                     self.dataOut.beacon_heiIndexList = beacon_heiIndexList
                     return 1
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError, "Error selecting heights by index: Index range in (%d,%d) is not valid" % (minIndex, maxIndex)
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights-1
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
             #         nHeights = maxIndex - minIndex + 1
                     #Spectra
                     data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
                     data_cspc = None
-                    if self.dataOut.data_cspc != None:
+                    if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
                     data_dc = None
-                    if self.dataOut.data_dc != None:
+                    if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
                     return 1
                 def removeDC(self, mode = 2):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
-                    if jcspectra != None:
+                    if jcspectra is not None:
                         jcspectraExist = True
                         num_pairs = jcspectra.shape[0]
                     else:   jcspectraExist = False
                     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 jcspectraExist:
                             jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
                     if mode == 2:
                         vel = numpy.array([-2,-1,1,2])
                         xx = numpy.zeros([4,4])
                         for fil in range(4):
                             xx[fil,:] = vel[fil]**numpy.asarray(range(4))
                         xx_inv = numpy.linalg.inv(xx)
                         xx_aux = xx_inv[0,:]
                         for ich in range(num_chan):
                             yy = jspectra[ich,ind_vel,:]
                             jspectra[ich,freq_dc,:] = numpy.dot(xx_aux,yy)
                             junkid = jspectra[ich,freq_dc,:]<=0
                             cjunkid = sum(junkid)
                             if cjunkid.any():
                                 jspectra[ich,freq_dc,junkid.nonzero()] = (jspectra[ich,ind_vel[1],junkid] + jspectra[ich,ind_vel[2],junkid])/2
                         if jcspectraExist:
                             for ip in range(num_pairs):
                                 yy = jcspectra[ip,ind_vel,:]
                                 jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def removeInterference(self,  interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     jnoise = self.dataOut.getNoise()
                     num_incoh = self.dataOut.nIncohInt
                     num_channel  = jspectra.shape[0]
                     num_prof  = jspectra.shape[1]
                     num_hei   = jspectra.shape[2]
                     #hei_interf
-                    if hei_interf == None:
+                    if hei_interf is None:
                         count_hei = num_hei/2   #Como es entero no importa
                         hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
                         hei_interf = numpy.asarray(hei_interf)[0]
                     #nhei_interf
                     if (nhei_interf == None):
                         nhei_interf = 5
                     if (nhei_interf < 1):
                         nhei_interf = 1
                     if (nhei_interf > count_hei):
                         nhei_interf = count_hei
                     if (offhei_interf == None):
                         offhei_interf = 0
                     ind_hei = range(num_hei)
             #         mask_prof = numpy.asarray(range(num_prof - 2)) + 1
             #         mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
                     mask_prof = numpy.asarray(range(num_prof))
                     num_mask_prof = mask_prof.size
                     comp_mask_prof = [0, num_prof/2]
                     #noise_exist:    Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
                     if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
                         jnoise = numpy.nan
                     noise_exist = jnoise[0] < numpy.Inf
                     #Subrutina de Remocion de la Interferencia
                     for ich in range(num_channel):
                         #Se ordena los espectros segun su potencia (menor a mayor)
                         power = jspectra[ich,mask_prof,:]
                         power = power[:,hei_interf]
                         power = power.sum(axis = 0)
                         psort = power.ravel().argsort()
                         #Se estima la interferencia promedio en los Espectros de Potencia empleando
                         junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
                         if noise_exist:
                         #    tmp_noise = jnoise[ich] / num_prof
                             tmp_noise = jnoise[ich]
                         junkspc_interf = junkspc_interf - tmp_noise
                         #junkspc_interf[:,comp_mask_prof] = 0
                         jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
                         jspc_interf = jspc_interf.transpose()
                         #Calculando el espectro de interferencia promedio
                         noiseid =  numpy.where(jspc_interf <= tmp_noise/ math.sqrt(num_incoh))
                         noiseid = noiseid[0]
                         cnoiseid = noiseid.size
                         interfid = numpy.where(jspc_interf > tmp_noise/ math.sqrt(num_incoh))
                         interfid = interfid[0]
                         cinterfid = interfid.size
                         if (cnoiseid > 0):   jspc_interf[noiseid] = 0
                         #Expandiendo los perfiles a limpiar
                         if (cinterfid > 0):
                             new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
                             new_interfid = numpy.asarray(new_interfid)
                             new_interfid = {x for x in new_interfid}
                             new_interfid = numpy.array(list(new_interfid))
                             new_cinterfid = new_interfid.size
                         else: new_cinterfid = 0
                         for ip in range(new_cinterfid):
                             ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
                             jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
                         jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
                         #Removiendo la interferencia del punto de mayor interferencia
                         ListAux = jspc_interf[mask_prof].tolist()
                         maxid = ListAux.index(max(ListAux))
                         if cinterfid > 0:
                             for ip in range(cinterfid*(interf == 2) - 1):
                                 ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/math.sqrt(num_incoh))).nonzero()
                                 cind = len(ind)
                                 if (cind > 0):
                                     jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/math.sqrt(num_incoh))
                             ind = numpy.array([-2,-1,1,2])
                             xx = numpy.zeros([4,4])
                             for id1 in range(4):
                                 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
                             xx_inv = numpy.linalg.inv(xx)
                             xx = xx_inv[:,0]
                             ind = (ind + maxid + num_mask_prof)%num_mask_prof
                             yy = jspectra[ich,mask_prof[ind],:]
                             jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
                         indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/math.sqrt(num_incoh))).nonzero()
                         jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/math.sqrt(num_incoh))
                     #Remocion de Interferencia en el Cross Spectra
-                    if jcspectra == None: return jspectra, jcspectra
+                    if jcspectra is None: return jspectra, jcspectra
                     num_pairs = jcspectra.size/(num_prof*num_hei)
                     jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
                     for ip in range(num_pairs):
                         #-------------------------------------------
                         cspower = numpy.abs(jcspectra[ip,mask_prof,:])
                         cspower = cspower[:,hei_interf]
                         cspower = cspower.sum(axis = 0)
                         cspsort = cspower.ravel().argsort()
                         junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
                         junkcspc_interf = junkcspc_interf.transpose()
                         jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
                         ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
                         median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
                         median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
                         junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
                         for iprof in range(num_prof):
                             ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
                             jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
                         #Removiendo la Interferencia
                         jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
                         ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
                         maxid = ListAux.index(max(ListAux))
                         ind = numpy.array([-2,-1,1,2])
                         xx = numpy.zeros([4,4])
                         for id1 in range(4):
                             xx[:,id1] = ind[id1]**numpy.asarray(range(4))
                         xx_inv = numpy.linalg.inv(xx)
                         xx = xx_inv[:,0]
                         ind = (ind + maxid + num_mask_prof)%num_mask_prof
                         yy = jcspectra[ip,mask_prof[ind],:]
                         jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
                     #Guardar Resultados
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def setRadarFrequency(self, frequency=None):
                     if frequency != None:
                         self.dataOut.frequency = frequency
                     return 1
                 def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
                     #validacion de rango
                     if minHei == None:
                         minHei = self.dataOut.heightList[0]
                     if maxHei == None:
                         maxHei = self.dataOut.heightList[-1]
                     if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
                         print 'minHei: %.2f is out of the heights range'%(minHei)
                         print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
                         print 'maxHei: %.2f is out of the heights range'%(maxHei)
                         print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
                         maxHei = self.dataOut.heightList[-1]
                     # validacion de velocidades
                     velrange = self.dataOut.getVelRange(1)
                     if minVel == None:
                         minVel = velrange[0]
                     if maxVel == None:
                         maxVel = velrange[-1]
                     if (minVel < velrange[0]) or (minVel > maxVel):
                         print 'minVel: %.2f is out of the velocity range'%(minVel)
                         print 'minVel is setting to %.2f'%(velrange[0])
                         minVel = velrange[0]
                     if (maxVel > velrange[-1]) or (maxVel < minVel):
                         print 'maxVel: %.2f is out of the velocity range'%(maxVel)
                         print 'maxVel is setting to %.2f'%(velrange[-1])
                         maxVel = velrange[-1]
                     # seleccion de indices para rango
                     minIndex = 0
                     maxIndex = 0
                     heights = self.dataOut.heightList
                     inda = numpy.where(heights >= minHei)
                     indb = numpy.where(heights <= maxHei)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(heights)
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights-1
                     # seleccion de indices para velocidades
                     indminvel = numpy.where(velrange >= minVel)
                     indmaxvel = numpy.where(velrange <= maxVel)
                     try:
                         minIndexVel = indminvel[0][0]
                     except:
                         minIndexVel = 0
                     try:
                         maxIndexVel = indmaxvel[0][-1]
                     except:
                         maxIndexVel = len(velrange)
                     #seleccion del espectro
                     data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
                     #estimacion de ruido
                     noise = numpy.zeros(self.dataOut.nChannels)
                     for channel in range(self.dataOut.nChannels):
                         daux = data_spc[channel,:,:]
                         noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
                     self.dataOut.noise_estimation = noise.copy()
                     return 1
             class IncohInt(Operation):
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer_spc = None
                 __buffer_cspc = None
                 __buffer_dc = None
                 __dataReady = False
                 __timeInterval = None
                 n = None
                 def __init__(self):
                     Operation.__init__(self)
             #         self.isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n        :    Number of coherent integrations
                         timeInterval   :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping    :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer_spc = None
                     self.__buffer_cspc = None
                     self.__buffer_dc = None
                     self.__dataReady = False
                     if n == None and timeInterval == None:
                         raise ValueError, "n or timeInterval should be specified ..."
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverapping = True
                     else:
                         self.__withOverapping = False
                         self.__buffer_spc = 0
                         self.__buffer_cspc = 0
                         self.__buffer_dc = 0
                     self.__profIndex = 0
                 def putData(self, data_spc, data_cspc, data_dc):
                     """
                     Add a profile to the __buffer_spc and increase in one the __profileIndex
                     """
                     if not self.__withOverapping:
                         self.__buffer_spc += data_spc
                         if data_cspc is None:
                             self.__buffer_cspc = None
                         else:
                             self.__buffer_cspc += data_cspc
                         if data_dc is None:
                             self.__buffer_dc = None
                         else:
                             self.__buffer_dc += data_dc
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nFFTPoints, nHeis = data_spc.shape
                     data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis))
-                    if data_cspc != None:
+                    if data_cspc is not None:
                         data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis))
-                    if data_dc != None:
+                    if data_dc is not None:
                         data_dc = numpy.reshape(data_dc, (1, -1, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer_spc is None:
                         self.__buffer_spc = data_spc
                         if data_cspc is None:
                             self.__buffer_cspc = None
                         else:
                             self.__buffer_cspc += data_cspc
                         if data_dc is None:
                             self.__buffer_dc = None
                         else:
                             self.__buffer_dc += data_dc
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc))
-                        if data_cspc != None:
+                        if data_cspc is not None:
                             self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc))
-                        if data_dc != None:
+                        if data_dc is not None:
                             self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0)
                     self.__buffer_spc[self.n-1] = data_spc
-                    if data_cspc != None:
+                    if data_cspc is not None:
                         self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0)
                         self.__buffer_cspc[self.n-1] = data_cspc
-                    if data_dc != None:
+                    if data_dc is not None:
                         self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0)
                         self.__buffer_dc[self.n-1] = data_dc
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     data_spc = None
                     data_cspc  = None
                     data_dc = None
                     if not self.__withOverapping:
                         data_spc = self.__buffer_spc
                         data_cspc = self.__buffer_cspc
                         data_dc = self.__buffer_dc
                         n = self.__profIndex
                         self.__buffer_spc = 0
                         self.__buffer_cspc = 0
                         self.__buffer_dc = 0
                         self.__profIndex = 0
                         return data_spc, data_cspc, data_dc, n
                     #Integration with Overlapping
                     data_spc = numpy.sum(self.__buffer_spc, axis=0)
-                    if self.__buffer_cspc != None:
+                    if self.__buffer_cspc is not None:
                         data_cspc = numpy.sum(self.__buffer_cspc, axis=0)
-                    if self.__buffer_dc != None:
+                    if self.__buffer_dc is not None:
                         data_dc = numpy.sum(self.__buffer_dc, axis=0)
                     n = self.__profIndex
                     return data_spc, data_cspc, data_dc, n
                 def byProfiles(self, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
             #         n = None
                     self.putData(*args)
                     if self.__profIndex == self.n:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def byTime(self, datatime, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     n = None
                     self.putData(*args)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def integrate(self, datatime, *args):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
                     else:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
                     self.__lastdatatime = datatime
                     if avgdata_spc is None:
                         return None, None, None, None
                     avgdatatime = self.__initime
                     try:
                         self.__timeInterval = (self.__lastdatatime - self.__initime)/(self.n - 1)
                     except:
                         self.__timeInterval = self.__lastdatatime - self.__initime
                     deltatime = datatime -self.__lastdatatime
                     if not self.__withOverapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
                     if n==1:
                         dataOut.flagNoData = False
                         return
                     if not self.isConfig:
                         self.setup(n, timeInterval, overlapping)
                         self.isConfig = True
                     avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
                                                                                         dataOut.data_spc,
                                                                                         dataOut.data_cspc,
                                                                                         dataOut.data_dc)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data_spc = avgdata_spc
                         dataOut.data_cspc = avgdata_cspc
                         dataOut.data_dc = avgdata_dc
                         dataOut.nIncohInt *= self.n
                         dataOut.utctime = avgdatatime
                         #dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints
             #             dataOut.timeInterval = self.__timeInterval*self.n
                         dataOut.flagNoData = False

setup.py +1 -1

             '''
             Created on Jul 16, 2014
             @author: roj-idl71
             '''
             from distutils.core import setup, Extension
             setup(name="schainpy",
-                    version="2.0",
+                    version="2.1.0",
                     description="Python tools to read, write and process Jicamarca data",
                     author="Miguel Urco",
                     author_email="miguel.urco@jro.igp.gob.pe",
                     url="http://jro.igp.gob.pe",
                     packages = {'schainpy',
                                 'schainpy.model',
                                 'schainpy.model.data',
                                 'schainpy.model.graphics',
                                 'schainpy.model.io',
                                 'schainpy.model.proc',
                                 'schainpy.model.utils',
                                 'schainpy.gui',
                                 'schainpy.gui.figures',
                                 'schainpy.gui.viewcontroller',
                                 'schainpy.gui.viewer',
                                 'schainpy.gui.viewer.windows'},
                     py_modules=['schainpy.serializer.DataTranslate',
                                 'schainpy.serializer.JROSerializer'],
                     package_data={'schainpy.gui.figures': ['*.jpg', '*.jpeg', '*.png', '*.gif']},
                     include_package_data=True,
                     scripts =['schainpy/gui/schainGUI'])

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