schain Commit - r1385:83c0b1494611 · Jicamarca Repository

Adicionada operación Clean Rayleigh a Spectra Proc

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r1385:83c0b1494611

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r1385:83c0b1494611

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schainpy/model/graphics/jroplot_heispectra.py +4 -3

             # Copyright (c) 2012-2020 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """Classes to plo Specra Heis data
             """
             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt
+            import matplotlib.pyplot as plt
             class SpectraHeisPlot(Plot):
                 CODE = 'spc_heis'
                 def setup(self):
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.height = 2.6 * self.nrows
                     self.width = 3.5 * self.ncols
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.95, 'bottom': 0.08})
                     self.ylabel = 'Intensity [dB]'
                     self.xlabel = 'Frequency [KHz]'
                     self.colorbar = False
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = 10*numpy.log10(dataOut.data_spc / dataOut.normFactor)
                     data['spc_heis'] = spc
                     return data, meta
                 def plot(self):
                     c = 3E8
-                    deltaHeight = self.data.yrange[1] - self.data.yrange[0]
+                    deltaHeight = self.data.yrange[1] - self.data.yrange[0] # yrange = heightList
                     x = numpy.arange(-1*len(self.data.yrange)/2., len(self.data.yrange)/2.)*(c/(2*deltaHeight*len(self.data.yrange)*1000))
                     self.y = self.data[-1]['spc_heis']
                     self.titles = []
+                    Maintitle = "Range from %d km to %d km" %(int(self.data.yrange[0]),int(self.data.yrange[-1]))
                     for n, ax in enumerate(self.axes):
                         ychannel = self.y[n,:]
                         if ax.firsttime:
                             self.xmin = min(x) if self.xmin is None else self.xmin
                             self.xmax = max(x) if self.xmax is None else self.xmax
                             ax.plt = ax.plot(x, ychannel, lw=1, color='b')[0]
                         else:
                             ax.plt.set_data(x, ychannel)
                         self.titles.append("Channel {}: {:4.2f}dB".format(n, numpy.max(ychannel)))
+                    plt.suptitle(Maintitle)
             class RTIHeisPlot(Plot):
                 CODE = 'rti_heis'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Intensity [dB]'
                     self.xlabel = 'Time'
                     self.titles = ['RTI']
                     self.colorbar = False
                     self.height = 4
                     self.plots_adjust.update({'right': 0.85 })
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = dataOut.data_spc / dataOut.normFactor
                     spc = 10*numpy.log10(numpy.average(spc, axis=1))
                     data['rti_heis'] = spc
                     return data, meta
                 def plot(self):
                     x = self.data.times
                     Y = self.data['rti_heis']
                     if self.axes[0].firsttime:
                         self.ymin = numpy.nanmin(Y) - 5 if self.ymin == None else self.ymin
                         self.ymax = numpy.nanmax(Y) + 5 if self.ymax == None else self.ymax
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
                         plt.legend(bbox_to_anchor=(1.18, 1.0))
                     else:
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].lines[ch].set_data(x, y)

schainpy/model/graphics/jroplot_voltage.py +7 -7

             '''
             Created on Jul 9, 2014
             @author: roj-idl71
             '''
             import os
             import datetime
             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt
             class ScopePlot(Plot):
                 '''
                    Plot for Scope
                 '''
                 CODE = 'scope'
                 plot_type = 'scatter'
                 def setup(self):
                     self.xaxis = 'Range (Km)'
-                    self.ncols = 1
+                    self.nplots = len(self.data.channels)
-                    self.nrows = 1
+                    self.nrows = int(numpy.ceil(self.nplots/2))
-                    self.nplots = 1
+                    self.ncols = int(numpy.ceil(self.nplots/self.nrows))
                     self.ylabel = 'Intensity [dB]'
-                    self.titles = ['Scope']
+                    self.titles = ['Channel '+str(self.data.channels[i])+" " for i in self.data.channels]
                     self.colorbar = False
                     self.width = 6
                     self.height = 4
                 def update(self, dataOut):
                     data = {}
                     meta = {
                         'nProfiles': dataOut.nProfiles,
                         'flagDataAsBlock': dataOut.flagDataAsBlock,
                         'profileIndex': dataOut.profileIndex,
                     }
                     if self.CODE == 'scope':
                         data[self.CODE] = dataOut.data
                     elif self.CODE == 'pp_power':
                         data[self.CODE] = dataOut.dataPP_POWER
                     elif self.CODE == 'pp_signal':
                         data[self.CODE] = dataOut.dataPP_POW
                     elif self.CODE == 'pp_velocity':
                         data[self.CODE] = dataOut.dataPP_DOP
                     elif self.CODE == 'pp_specwidth':
                         data[self.CODE] = dataOut.dataPP_WIDTH
                     return data, meta
                 def plot_iq(self, x, y, channelIndexList, thisDatetime, wintitle):
                     yreal = y[channelIndexList,:].real
                     yimag = y[channelIndexList,:].imag
-                    title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y"))
+                    Maintitle = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     self.xlabel = "Range (Km)"
                     self.ylabel = "Intensity - IQ"
                     self.y = yreal
                     self.x = x
-                    self.titles[0] = title
                     for i,ax in enumerate(self.axes):
                         title = "Channel %d" %(i)
                         if ax.firsttime:
                             self.xmin = min(x)
                             self.xmax = max(x)
                             ax.plt_r = ax.plot(x, yreal[i,:], color='b')[0]
                             ax.plt_i = ax.plot(x, yimag[i,:], color='r')[0]
                         else:
                             ax.plt_r.set_data(x, yreal[i,:])
                             ax.plt_i.set_data(x, yimag[i,:])
+                    plt.suptitle(Maintitle)
                 def plot_power(self, x, y, channelIndexList, thisDatetime, wintitle):
                     y = y[channelIndexList,:] * numpy.conjugate(y[channelIndexList,:])
                     yreal = y.real
                     yreal = 10*numpy.log10(yreal)
                     self.y = yreal
                     title = wintitle + " Power: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     self.xlabel = "Range (Km)"
                     self.ylabel = "Intensity [dB]"
                     self.titles[0] = title
                     for i,ax in enumerate(self.axes):
                         title = "Channel %d" %(i)
                         ychannel = yreal[i,:]
                         if ax.firsttime:
                             self.xmin = min(x)
                             self.xmax = max(x)
                             ax.plt_r = ax.plot(x, ychannel)[0]
                         else:
                             ax.plt_r.set_data(x, ychannel)
                 def plot_weatherpower(self, x, y, channelIndexList, thisDatetime, wintitle):
                     y      = y[channelIndexList,:]
                     yreal  = y.real
                     yreal  = 10*numpy.log10(yreal)
                     self.y = yreal
                     title  = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     self.xlabel = "Range (Km)"
                     self.ylabel = "Intensity"
                     self.xmin   = min(x)
                     self.xmax   = max(x)
                     self.titles[0] =title
                     for i,ax in enumerate(self.axes):
                         title    = "Channel %d" %(i)
                         ychannel = yreal[i,:]
                         if ax.firsttime:
                             ax.plt_r = ax.plot(x, ychannel)[0]
                         else:
                             #pass
                             ax.plt_r.set_data(x, ychannel)
                 def plot_weathervelocity(self, x, y, channelIndexList, thisDatetime, wintitle):
                     x = x[channelIndexList,:]
                     yreal  = y
                     self.y = yreal
                     title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     self.xlabel = "Velocity (m/s)"
                     self.ylabel = "Range (Km)"
                     self.xmin   = numpy.min(x)
                     self.xmax   = numpy.max(x)
                     self.titles[0] =title
                     for i,ax in enumerate(self.axes):
                         title    = "Channel %d" %(i)
                         xchannel    = x[i,:]
                         if ax.firsttime:
                             ax.plt_r = ax.plot(xchannel, yreal)[0]
                         else:
                             #pass
                             ax.plt_r.set_data(xchannel, yreal)
                 def plot_weatherspecwidth(self, x, y, channelIndexList, thisDatetime, wintitle):
                     x = x[channelIndexList,:]
                     yreal  = y
                     self.y = yreal
                     title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     self.xlabel = "width "
                     self.ylabel = "Range (Km)"
                     self.xmin   = numpy.min(x)
                     self.xmax   = numpy.max(x)
                     self.titles[0] =title
                     for i,ax in enumerate(self.axes):
                         title    = "Channel %d" %(i)
                         xchannel    = x[i,:]
                         if ax.firsttime:
                             ax.plt_r = ax.plot(xchannel, yreal)[0]
                         else:
                             #pass
                             ax.plt_r.set_data(xchannel, yreal)
                 def plot(self):
                     if self.channels:
                         channels = self.channels
                     else:
                         channels = self.data.channels
                     thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1])
                     scope = self.data[-1][self.CODE]
                     if self.data.flagDataAsBlock:
                         for i in range(self.data.nProfiles):
                             wintitle1 = " [Profile = %d] " %i
                             if self.CODE =="scope":
                                 if self.type == "power":
                                     self.plot_power(self.data.yrange,
                                                     scope[:,i,:],
                                                     channels,
                                                     thisDatetime,
                                                     wintitle1
                                                     )
                                 if self.type == "iq":
                                     self.plot_iq(self.data.yrange,
                                                  scope[:,i,:],
                                                  channels,
                                                  thisDatetime,
                                                  wintitle1
                                                 )
                             if self.CODE=="pp_power":
                                 self.plot_weatherpower(self.data.yrange,
                                            scope[:,i,:],
                                            channels,
                                            thisDatetime,
                                            wintitle
                                            )
                             if self.CODE=="pp_signal":
                                 self.plot_weatherpower(self.data.yrange,
                                            scope[:,i,:],
                                            channels,
                                            thisDatetime,
                                            wintitle
                                            )
                             if self.CODE=="pp_velocity":
                                 self.plot_weathervelocity(scope[:,i,:],
                                            self.data.yrange,
                                            channels,
                                            thisDatetime,
                                            wintitle
                                            )
                             if self.CODE=="pp_spcwidth":
                                 self.plot_weatherspecwidth(scope[:,i,:],
                                            self.data.yrange,
                                            channels,
                                            thisDatetime,
                                            wintitle
                                            )
                     else:
                         wintitle = " [Profile = %d] " %self.data.profileIndex
                         if self.CODE== "scope":
                             if self.type == "power":
                                  self.plot_power(self.data.yrange,
                                             scope,
                                             channels,
                                             thisDatetime,
                                             wintitle
                                             )
                             if self.type == "iq":
                                 self.plot_iq(self.data.yrange,
                                             scope,
                                             channels,
                                             thisDatetime,
                                             wintitle
                                             )
                         if self.CODE=="pp_power":
                             self.plot_weatherpower(self.data.yrange,
                                                 scope,
                                                 channels,
                                                 thisDatetime,
                                                 wintitle
                                                    )
                         if self.CODE=="pp_signal":
                             self.plot_weatherpower(self.data.yrange,
                                                 scope,
                                                 channels,
                                                 thisDatetime,
                                                 wintitle
                                                    )
                         if self.CODE=="pp_velocity":
                             self.plot_weathervelocity(scope,
                                                    self.data.yrange,
                                                    channels,
                                                    thisDatetime,
                                                    wintitle
                                                    )
                         if self.CODE=="pp_specwidth":
                             self.plot_weatherspecwidth(scope,
                                                    self.data.yrange,
                                                    channels,
                                                    thisDatetime,
                                                    wintitle
                                                    )
             class PulsepairPowerPlot(ScopePlot):
                 '''
                 Plot for  P= S+N
                 '''
                 CODE = 'pp_power'
                 plot_type = 'scatter'
             class PulsepairVelocityPlot(ScopePlot):
                 '''
                 Plot for VELOCITY
                 '''
                 CODE = 'pp_velocity'
                 plot_type = 'scatter'
             class PulsepairSpecwidthPlot(ScopePlot):
                 '''
                 Plot for WIDTH
                 '''
                 CODE = 'pp_specwidth'
                 plot_type = 'scatter'
             class PulsepairSignalPlot(ScopePlot):
                 '''
                 Plot for S
                 '''
                 CODE = 'pp_signal'
                 plot_type = 'scatter'

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

             """
             Created on Jul 2, 2014
             @author: roj-idl71
             """
             import os
             import sys
             import glob
             import time
             import numpy
             import fnmatch
             import inspect
             import time
             import datetime
             import zmq
             from schainpy.model.proc.jroproc_base import Operation, MPDecorator
             from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, RadarControllerHeader, ProcessingHeader
             from schainpy.model.data.jroheaderIO import get_dtype_index, get_numpy_dtype, get_procflag_dtype, get_dtype_width
             from schainpy.utils import log
             import schainpy.admin
             LOCALTIME = True
             DT_DIRECTIVES = {
                 '%Y': 4,
                 '%y': 2,
                 '%m': 2,
                 '%d': 2,
                 '%j': 3,
                 '%H': 2,
                 '%M': 2,
                 '%S': 2,
                 '%f': 6
             }
             def isNumber(cad):
                 """
                 Chequea si el conjunto de caracteres que componen un string puede ser convertidos a un numero.
                 Excepciones:
                     Si un determinado string no puede ser convertido a numero
                 Input:
                     str, string al cual se le analiza para determinar si convertible a un numero o no
                 Return:
                     True    :    si el string es uno numerico
                     False   :    no es un string numerico
                 """
                 try:
                     float(cad)
                     return True
                 except:
                     return False
             def isFileInEpoch(filename, startUTSeconds, endUTSeconds):
                 """
                 Esta funcion determina si un archivo de datos se encuentra o no dentro del rango de fecha especificado.
                 Inputs:
                     filename            :    nombre completo del archivo de datos en formato Jicamarca (.r)
                     startUTSeconds      :    fecha inicial del rango seleccionado. La fecha esta dada en
                                              segundos contados desde 01/01/1970.
                     endUTSeconds        :    fecha final del rango seleccionado. La fecha esta dada en
                                              segundos contados desde 01/01/1970.
                 Return:
                     Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                     fecha especificado, de lo contrario retorna False.
                 Excepciones:
                     Si el archivo no existe o no puede ser abierto
                     Si la cabecera no puede ser leida.
                 """
                 basicHeaderObj = BasicHeader(LOCALTIME)
                 try:
                     fp = open(filename, 'rb')
                 except IOError:
                     print("The file %s can't be opened" % (filename))
                     return 0
                 sts = basicHeaderObj.read(fp)
                 fp.close()
                 if not(sts):
                     print("Skipping the file %s because it has not a valid header" % (filename))
                     return 0
                 if not ((startUTSeconds <= basicHeaderObj.utc) and (endUTSeconds > basicHeaderObj.utc)):
                     return 0
                 return 1
             def isTimeInRange(thisTime, startTime, endTime):
                 if endTime >= startTime:
                     if (thisTime < startTime) or (thisTime > endTime):
                         return 0
                     return 1
                 else:
                     if (thisTime < startTime) and (thisTime > endTime):
                         return 0
                     return 1
             def isFileInTimeRange(filename, startDate, endDate, startTime, endTime):
                 """
                 Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
                 Inputs:
                     filename            :    nombre completo del archivo de datos en formato Jicamarca (.r)
                     startDate          :    fecha inicial del rango seleccionado en formato datetime.date
                     endDate            :    fecha final del rango seleccionado en formato datetime.date
                     startTime          :    tiempo inicial del rango seleccionado en formato datetime.time
                     endTime            :    tiempo final del rango seleccionado en formato datetime.time
                 Return:
                     Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                     fecha especificado, de lo contrario retorna False.
                 Excepciones:
                     Si el archivo no existe o no puede ser abierto
                     Si la cabecera no puede ser leida.
                 """
                 try:
                     fp = open(filename, 'rb')
                 except IOError:
                     print("The file %s can't be opened" % (filename))
                     return None
                 firstBasicHeaderObj = BasicHeader(LOCALTIME)
                 systemHeaderObj = SystemHeader()
                 radarControllerHeaderObj = RadarControllerHeader()
                 processingHeaderObj = ProcessingHeader()
                 lastBasicHeaderObj = BasicHeader(LOCALTIME)
                 sts = firstBasicHeaderObj.read(fp)
                 if not(sts):
                     print("[Reading] Skipping the file %s because it has not a valid header" % (filename))
                     return None
                 if not systemHeaderObj.read(fp):
                     return None
                 if not radarControllerHeaderObj.read(fp):
                     return None
                 if not processingHeaderObj.read(fp):
                     return None
                 filesize = os.path.getsize(filename)
                 offset = processingHeaderObj.blockSize + 24  # header size
                 if filesize <= offset:
                     print("[Reading] %s: This file has not enough data" % filename)
                     return None
                 fp.seek(-offset, 2)
                 sts = lastBasicHeaderObj.read(fp)
                 fp.close()
                 thisDatetime = lastBasicHeaderObj.datatime
                 thisTime_last_block = thisDatetime.time()
                 thisDatetime = firstBasicHeaderObj.datatime
                 thisDate = thisDatetime.date()
                 thisTime_first_block = thisDatetime.time()
                 # General case
                 #           o>>>>>>>>>>>>>><<<<<<<<<<<<<<o
                 #-----------o----------------------------o-----------
                 #       startTime                     endTime
                 if endTime >= startTime:
                     if (thisTime_last_block < startTime) or (thisTime_first_block > endTime):
                         return None
                     return thisDatetime
                 # If endTime < startTime then endTime belongs to the next day
                 #<<<<<<<<<<<o                            o>>>>>>>>>>>
                 #-----------o----------------------------o-----------
                 #        endTime                    startTime
                 if (thisDate == startDate) and (thisTime_last_block < startTime):
                     return None
                 if (thisDate == endDate) and (thisTime_first_block > endTime):
                     return None
                 if (thisTime_last_block < startTime) and (thisTime_first_block > endTime):
                     return None
                 return thisDatetime
             def isFolderInDateRange(folder, startDate=None, endDate=None):
                 """
                 Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
                 Inputs:
                     folder            :    nombre completo del directorio.
                                            Su formato deberia ser "/path_root/?YYYYDDD"
                                             siendo:
                                                 YYYY    :    Anio         (ejemplo 2015)
                                                 DDD     :    Dia del anio (ejemplo 305)
                     startDate          :    fecha inicial del rango seleccionado en formato datetime.date
                     endDate            :    fecha final del rango seleccionado en formato datetime.date
                 Return:
                     Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                     fecha especificado, de lo contrario retorna False.
                 Excepciones:
                     Si el directorio no tiene el formato adecuado
                 """
                 basename = os.path.basename(folder)
                 if not isRadarFolder(basename):
                     print("The folder %s has not the rigth format" % folder)
                     return 0
                 if startDate and endDate:
                     thisDate = getDateFromRadarFolder(basename)
                     if thisDate < startDate:
                         return 0
                     if thisDate > endDate:
                         return 0
                 return 1
             def isFileInDateRange(filename, startDate=None, endDate=None):
                 """
                 Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
                 Inputs:
                     filename            :    nombre completo del archivo de datos en formato Jicamarca (.r)
                                            Su formato deberia ser "?YYYYDDDsss"
                                             siendo:
                                                 YYYY    :    Anio         (ejemplo 2015)
                                                 DDD     :    Dia del anio (ejemplo 305)
                                                 sss     :    set
                     startDate          :    fecha inicial del rango seleccionado en formato datetime.date
                     endDate            :    fecha final del rango seleccionado en formato datetime.date
                 Return:
                     Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                     fecha especificado, de lo contrario retorna False.
                 Excepciones:
                     Si el archivo no tiene el formato adecuado
                 """
                 basename = os.path.basename(filename)
                 if not isRadarFile(basename):
                     print("The filename %s has not the rigth format" % filename)
                     return 0
                 if startDate and endDate:
                     thisDate = getDateFromRadarFile(basename)
                     if thisDate < startDate:
                         return 0
                     if thisDate > endDate:
                         return 0
                 return 1
             def getFileFromSet(path, ext, set):
                 validFilelist = []
                 fileList = os.listdir(path)
                 # 0 1234 567 89A BCDE
                 # H YYYY DDD SSS .ext
                 for thisFile in fileList:
                     try:
                         year = int(thisFile[1:5])
                         doy = int(thisFile[5:8])
                     except:
                         continue
                     if (os.path.splitext(thisFile)[-1].lower() != ext.lower()):
                         continue
                     validFilelist.append(thisFile)
                 myfile = fnmatch.filter(
                     validFilelist, '*%4.4d%3.3d%3.3d*' % (year, doy, set))
                 if len(myfile) != 0:
                     return myfile[0]
                 else:
                     filename = '*%4.4d%3.3d%3.3d%s' % (year, doy, set, ext.lower())
                     print('the filename %s does not exist' % filename)
                     print('...going to the last file: ')
                 if validFilelist:
                     validFilelist = sorted(validFilelist, key=str.lower)
                     return validFilelist[-1]
                 return None
             def getlastFileFromPath(path, ext):
                 """
                 Depura el fileList dejando solo los que cumplan el formato de "PYYYYDDDSSS.ext"
                 al final de la depuracion devuelve el ultimo file de la lista que quedo.
                 Input:
                     fileList    :    lista conteniendo todos los files (sin path) que componen una determinada carpeta
                     ext         :    extension de los files contenidos en una carpeta
                 Return:
                     El ultimo file de una determinada carpeta, no se considera el path.
                 """
                 validFilelist = []
                 fileList = os.listdir(path)
                 # 0 1234 567 89A BCDE
                 # H YYYY DDD SSS .ext
                 for thisFile in fileList:
                     year = thisFile[1:5]
                     if not isNumber(year):
                         continue
                     doy = thisFile[5:8]
                     if not isNumber(doy):
                         continue
                     year = int(year)
                     doy = int(doy)
                     if (os.path.splitext(thisFile)[-1].lower() != ext.lower()):
                         continue
                     validFilelist.append(thisFile)
                 if validFilelist:
                     validFilelist = sorted(validFilelist, key=str.lower)
                     return validFilelist[-1]
                 return None
             def isRadarFolder(folder):
                 try:
                     year = int(folder[1:5])
                     doy = int(folder[5:8])
                 except:
                     return 0
                 return 1
             def isRadarFile(file):
                 try:
                     year = int(file[1:5])
                     doy = int(file[5:8])
                     set = int(file[8:11])
                 except:
                     return 0
                 return 1
             def getDateFromRadarFile(file):
                 try:
                     year = int(file[1:5])
                     doy = int(file[5:8])
                     set = int(file[8:11])
                 except:
                     return None
                 thisDate = datetime.date(year, 1, 1) + datetime.timedelta(doy - 1)
                 return thisDate
             def getDateFromRadarFolder(folder):
                 try:
                     year = int(folder[1:5])
                     doy = int(folder[5:8])
                 except:
                     return None
                 thisDate = datetime.date(year, 1, 1) + datetime.timedelta(doy - 1)
                 return thisDate
             def parse_format(s, fmt):
                 for i in range(fmt.count('%')):
                     x = fmt.index('%')
                     d = DT_DIRECTIVES[fmt[x:x+2]]
                     fmt = fmt.replace(fmt[x:x+2], s[x:x+d])
                 return fmt
             class Reader(object):
                 c = 3E8
                 isConfig = False
                 dtype = None
                 pathList = []
                 filenameList = []
                 datetimeList = []
                 filename = None
                 ext = None
                 flagIsNewFile = 1
                 flagDiscontinuousBlock = 0
                 flagIsNewBlock = 0
                 flagNoMoreFiles = 0
                 fp = None
                 firstHeaderSize = 0
                 basicHeaderSize = 24
                 versionFile = 1103
                 fileSize = None
                 fileSizeByHeader = None
                 fileIndex = -1
                 profileIndex = None
                 blockIndex = 0
                 nTotalBlocks = 0
                 maxTimeStep = 30
                 lastUTTime = None
                 datablock = None
                 dataOut = None
                 getByBlock = False
                 path = None
                 startDate = None
                 endDate = None
                 startTime = datetime.time(0, 0, 0)
                 endTime = datetime.time(23, 59, 59)
                 set = None
                 expLabel = ""
                 online = False
                 delay = 60
                 nTries = 3  # quantity tries
                 nFiles = 3  # number of files for searching
                 walk = True
                 getblock = False
                 nTxs = 1
                 realtime = False
                 blocksize = 0
                 blocktime = None
                 warnings = True
                 verbose = True
                 server = None
                 format = None
                 oneDDict = None
                 twoDDict = None
                 independentParam = None
                 filefmt = None
                 folderfmt = None
                 open_file = open
                 open_mode = 'rb'
                 def run(self):
                     raise NotImplementedError
                 def getAllowedArgs(self):
                     if hasattr(self, '__attrs__'):
                         return self.__attrs__
                     else:
                         return inspect.getargspec(self.run).args
                 def set_kwargs(self, **kwargs):
                     for key, value in kwargs.items():
                         setattr(self, key, value)
                 def find_folders(self, path, startDate, endDate, folderfmt, last=False):
                     folders = [x for f in path.split(',')
                                for x in os.listdir(f) if os.path.isdir(os.path.join(f, x))]
                     folders.sort()
                     if last:
                         folders = [folders[-1]]
                     for folder in folders:
                         try:
                             dt = datetime.datetime.strptime(parse_format(folder, folderfmt), folderfmt).date()
                             if dt >= startDate and dt <= endDate:
                                 yield os.path.join(path, folder)
                             else:
                                 log.log('Skiping folder {}'.format(folder), self.name)
                         except Exception as e:
                             log.log('Skiping folder {}'.format(folder), self.name)
                             continue
                     return
                 def find_files(self, folders, ext, filefmt, startDate=None, endDate=None,
                                expLabel='', last=False):
                     for path in folders:
                         files = glob.glob1(path, '*{}'.format(ext))
                         files.sort()
                         if last:
                             if files:
                                 fo = files[-1]
                                 try:
                                     dt = datetime.datetime.strptime(parse_format(fo, filefmt), filefmt).date()
                                     yield os.path.join(path, expLabel, fo)
                                 except Exception as e:
                                     pass
                                 return
                             else:
                                 return
                         for fo in files:
                             try:
                                 dt = datetime.datetime.strptime(parse_format(fo, filefmt), filefmt).date()
                                 if dt >= startDate and dt <= endDate:
                                     yield os.path.join(path, expLabel, fo)
                                 else:
                                     log.log('Skiping file {}'.format(fo), self.name)
                             except Exception as e:
                                 log.log('Skiping file {}'.format(fo), self.name)
                                 continue
                 def searchFilesOffLine(self, path, startDate, endDate,
                                        expLabel, ext, walk,
                                        filefmt, folderfmt):
                     """Search files in offline mode for the given arguments
                     Return:
                         Generator of files
                     """
                     if walk:
                         folders = self.find_folders(
                             path, startDate, endDate, folderfmt)
                     else:
                         folders = path.split(',')
                     return self.find_files(
                         folders, ext, filefmt, startDate, endDate, expLabel)
                 def searchFilesOnLine(self, path, startDate, endDate,
                                       expLabel, ext, walk,
                                       filefmt, folderfmt):
                     """Search for the last file of the last folder
                     Arguments:
                         path        :    carpeta donde estan contenidos los files que contiene data
                         expLabel    :    Nombre del subexperimento (subfolder)
                         ext         :    extension de los files
                         walk        :    Si es habilitado no realiza busquedas dentro de los ubdirectorios (doypath)
                     Return:
                         generator with the full path of last filename
                     """
                     if walk:
                         folders = self.find_folders(
                             path, startDate, endDate, folderfmt, last=True)
                     else:
                         folders = path.split(',')
                     return self.find_files(
                         folders, ext, filefmt, startDate, endDate, expLabel, last=True)
                 def setNextFile(self):
                     """Set the next file to be readed open it and parse de file header"""
                     while True:
                         if self.fp != None:
                             self.fp.close()
                         if self.online:
                             newFile = self.setNextFileOnline()
                         else:
                             newFile = self.setNextFileOffline()
                         if not(newFile):
                             if self.online:
                                 raise schainpy.admin.SchainError('Time to wait for new files reach')
                             else:
                                 if self.fileIndex == -1:
                                     raise schainpy.admin.SchainWarning('No files found in the given path')
                                 else:
                                     raise schainpy.admin.SchainWarning('No more files to read')
                         if self.verifyFile(self.filename):
                             break
                     log.log('Opening file: %s' % self.filename, self.name)
                     self.readFirstHeader()
                     self.nReadBlocks = 0
                 def setNextFileOnline(self):
                     """Check for the next file to be readed in online mode.
                     Set:
                         self.filename
                         self.fp
                         self.filesize
                     Return:
                         boolean
                     """
                     nextFile = True
                     nextDay = False
                     for nFiles in range(self.nFiles+1):
                         for nTries in range(self.nTries):
                             fullfilename, filename = self.checkForRealPath(nextFile, nextDay)
                             if fullfilename is not None:
                                 break
                             log.warning(
                                 "Waiting %0.2f sec for the next file: \"%s\" , try %02d ..." % (self.delay, filename, nTries + 1),
                                 self.name)
                             time.sleep(self.delay)
                             nextFile = False
                             continue
                         if fullfilename is not None:
                             break
                         self.nTries = 1
                         nextFile = True
                         if nFiles == (self.nFiles - 1):
                             log.log('Trying with next day...', self.name)
                             nextDay = True
                             self.nTries = 3
                     if fullfilename:
                         self.fileSize = os.path.getsize(fullfilename)
                         self.filename = fullfilename
                         self.flagIsNewFile = 1
                         if self.fp != None:
                             self.fp.close()
                         self.fp = self.open_file(fullfilename, self.open_mode)
                         self.flagNoMoreFiles = 0
                         self.fileIndex += 1
                         return 1
                     else:
                         return 0
                 def setNextFileOffline(self):
                     """Open the next file to be readed in offline mode"""
                     try:
                         filename = next(self.filenameList)
                         self.fileIndex +=1
                     except StopIteration:
                         self.flagNoMoreFiles = 1
                         return 0
                     self.filename = filename
                     self.fileSize = os.path.getsize(filename)
                     self.fp = self.open_file(filename, self.open_mode)
                     self.flagIsNewFile = 1
                     return 1
                 @staticmethod
                 def isDateTimeInRange(dt, startDate, endDate, startTime, endTime):
                     """Check if the given datetime is in range"""
+                    startDateTime= datetime.datetime.combine(startDate,startTime)
-                    if startDate <= dt.date() <= endDate:
+                    endDateTime = datetime.datetime.combine(endDate,endTime)
-                        if startTime <= dt.time() <= endTime:
+                    if startDateTime <= dt <= endDateTime:
                         return True
                     return False
                 def verifyFile(self, filename):
                     """Check for a valid file
                     Arguments:
                         filename -- full path filename
                     Return:
                         boolean
                     """
                     return True
                 def checkForRealPath(self, nextFile, nextDay):
                     """Check if the next file to be readed exists"""
                     raise NotImplementedError
                 def readFirstHeader(self):
                     """Parse the file header"""
                     pass
                 def waitDataBlock(self, pointer_location, blocksize=None):
                     """
                     """
                     currentPointer = pointer_location
                     if blocksize is None:
                         neededSize = self.processingHeaderObj.blockSize  # + self.basicHeaderSize
                     else:
                         neededSize = blocksize
                     for nTries in range(self.nTries):
                         self.fp.close()
                         self.fp = open(self.filename, 'rb')
                         self.fp.seek(currentPointer)
                         self.fileSize = os.path.getsize(self.filename)
                         currentSize = self.fileSize - currentPointer
                         if (currentSize >= neededSize):
                             return 1
                         log.warning(
                             "Waiting %0.2f seconds for the next block, try %03d ..." % (self.delay, nTries + 1),
                             self.name
                             )
                         time.sleep(self.delay)
                     return 0
             class JRODataReader(Reader):
                 utc = 0
                 nReadBlocks = 0
                 foldercounter = 0
                 firstHeaderSize = 0
                 basicHeaderSize = 24
                 __isFirstTimeOnline = 1
                 filefmt = "*%Y%j***"
                 folderfmt = "*%Y%j"
                 __attrs__ = ['path', 'startDate', 'endDate', 'startTime', 'endTime', 'online', 'delay', 'walk']
                 def getDtypeWidth(self):
                     dtype_index = get_dtype_index(self.dtype)
                     dtype_width = get_dtype_width(dtype_index)
                     return dtype_width
                 def checkForRealPath(self, nextFile, nextDay):
                     """Check if the next file to be readed exists.
                     Example    :
                         nombre correcto del file es  .../.../D2009307/P2009307367.ext
                         Entonces la funcion prueba con las siguientes combinaciones
                             .../.../y2009307367.ext
                             .../.../Y2009307367.ext
                             .../.../x2009307/y2009307367.ext
                             .../.../x2009307/Y2009307367.ext
                             .../.../X2009307/y2009307367.ext
                             .../.../X2009307/Y2009307367.ext
                         siendo para este caso, la ultima combinacion de letras, identica al file buscado
                     Return:
                         str -- fullpath of the file
                     """
                     if nextFile:
                         self.set += 1
                     if nextDay:
                         self.set = 0
                         self.doy += 1
                     foldercounter = 0
                     prefixDirList = [None, 'd', 'D']
                     if self.ext.lower() == ".r":  # voltage
                         prefixFileList = ['d', 'D']
                     elif self.ext.lower() == ".pdata":  # spectra
                         prefixFileList = ['p', 'P']
                     # barrido por las combinaciones posibles
                     for prefixDir in prefixDirList:
                         thispath = self.path
                         if prefixDir != None:
                             # formo el nombre del directorio xYYYYDDD (x=d o x=D)
                             if foldercounter == 0:
                                 thispath = os.path.join(self.path, "%s%04d%03d" %
                                                         (prefixDir, self.year, self.doy))
                             else:
                                 thispath = os.path.join(self.path, "%s%04d%03d_%02d" % (
                                     prefixDir, self.year, self.doy, foldercounter))
                         for prefixFile in prefixFileList:  # barrido por las dos combinaciones posibles de "D"
                             # formo el nombre del file xYYYYDDDSSS.ext
                             filename = "%s%04d%03d%03d%s" % (prefixFile, self.year, self.doy, self.set, self.ext)
                             fullfilename = os.path.join(
                                 thispath, filename)
                             if os.path.exists(fullfilename):
                                 return fullfilename, filename
                     return None, filename
                 def __waitNewBlock(self):
                     """
                     Return 1 si se encontro un nuevo bloque de datos, 0 de otra forma.
                     Si el modo de lectura es OffLine siempre retorn 0
                     """
                     if not self.online:
                         return 0
                     if (self.nReadBlocks >= self.processingHeaderObj.dataBlocksPerFile):
                         return 0
                     currentPointer = self.fp.tell()
                     neededSize = self.processingHeaderObj.blockSize + self.basicHeaderSize
                     for nTries in range(self.nTries):
                         self.fp.close()
                         self.fp = open(self.filename, 'rb')
                         self.fp.seek(currentPointer)
                         self.fileSize = os.path.getsize(self.filename)
                         currentSize = self.fileSize - currentPointer
                         if (currentSize >= neededSize):
                             self.basicHeaderObj.read(self.fp)
                             return 1
                         if self.fileSize == self.fileSizeByHeader:
                             #                self.flagEoF = True
                             return 0
                         print("[Reading] Waiting %0.2f seconds for the next block, try %03d ..." % (self.delay, nTries + 1))
                         time.sleep(self.delay)
                     return 0
                 def __setNewBlock(self):
                     if self.fp == None:
                         return 0
                     if self.flagIsNewFile:
                         self.lastUTTime = self.basicHeaderObj.utc
                         return 1
                     if self.realtime:
                         self.flagDiscontinuousBlock = 1
                         if not(self.setNextFile()):
                             return 0
                         else:
                             return 1
                     currentSize = self.fileSize - self.fp.tell()
                     neededSize = self.processingHeaderObj.blockSize + self.basicHeaderSize
                     if (currentSize >= neededSize):
                         self.basicHeaderObj.read(self.fp)
                         self.lastUTTime = self.basicHeaderObj.utc
                         return 1
                     if self.__waitNewBlock():
                         self.lastUTTime = self.basicHeaderObj.utc
                         return 1
                     if not(self.setNextFile()):
                         return 0
                     deltaTime = self.basicHeaderObj.utc - self.lastUTTime
                     self.lastUTTime = self.basicHeaderObj.utc
                     self.flagDiscontinuousBlock = 0
                     if deltaTime > self.maxTimeStep:
                         self.flagDiscontinuousBlock = 1
                     return 1
                 def readNextBlock(self):
                     while True:
                         if not(self.__setNewBlock()):
                             continue
                         if not(self.readBlock()):
                             return 0
                         self.getBasicHeader()
                         if not self.isDateTimeInRange(self.dataOut.datatime, self.startDate, self.endDate, self.startTime, self.endTime):
                             print("[Reading] Block No. %d/%d -> %s [Skipping]" % (self.nReadBlocks,
                                                                                   self.processingHeaderObj.dataBlocksPerFile,
                                                                                   self.dataOut.datatime.ctime()))
                             continue
                         break
                     if self.verbose:
                         print("[Reading] Block No. %d/%d -> %s" % (self.nReadBlocks,
                                                                    self.processingHeaderObj.dataBlocksPerFile,
                                                                    self.dataOut.datatime.ctime()))
                     return 1
                 def readFirstHeader(self):
                     self.basicHeaderObj.read(self.fp)
                     self.systemHeaderObj.read(self.fp)
                     self.radarControllerHeaderObj.read(self.fp)
                     self.processingHeaderObj.read(self.fp)
                     self.firstHeaderSize = self.basicHeaderObj.size
                     datatype = int(numpy.log2((self.processingHeaderObj.processFlags &
                                                PROCFLAG.DATATYPE_MASK)) - numpy.log2(PROCFLAG.DATATYPE_CHAR))
                     if datatype == 0:
                         datatype_str = numpy.dtype([('real', '<i1'), ('imag', '<i1')])
                     elif datatype == 1:
                         datatype_str = numpy.dtype([('real', '<i2'), ('imag', '<i2')])
                     elif datatype == 2:
                         datatype_str = numpy.dtype([('real', '<i4'), ('imag', '<i4')])
                     elif datatype == 3:
                         datatype_str = numpy.dtype([('real', '<i8'), ('imag', '<i8')])
                     elif datatype == 4:
                         datatype_str = numpy.dtype([('real', '<f4'), ('imag', '<f4')])
                     elif datatype == 5:
                         datatype_str = numpy.dtype([('real', '<f8'), ('imag', '<f8')])
                     else:
                         raise ValueError('Data type was not defined')
                     self.dtype = datatype_str
                     #self.ippSeconds = 2 * 1000 * self.radarControllerHeaderObj.ipp / self.c
                     self.fileSizeByHeader = self.processingHeaderObj.dataBlocksPerFile * self.processingHeaderObj.blockSize + \
                         self.firstHeaderSize + self.basicHeaderSize * \
                         (self.processingHeaderObj.dataBlocksPerFile - 1)
                     #        self.dataOut.channelList = numpy.arange(self.systemHeaderObj.numChannels)
                     #        self.dataOut.channelIndexList = numpy.arange(self.systemHeaderObj.numChannels)
                     self.getBlockDimension()
                 def verifyFile(self, filename):
                     flag = True
                     try:
                         fp = open(filename, 'rb')
                     except IOError:
                         log.error("File {} can't be opened".format(filename), self.name)
                         return False
                     if self.online and self.waitDataBlock(0):
                         pass
                     basicHeaderObj = BasicHeader(LOCALTIME)
                     systemHeaderObj = SystemHeader()
                     radarControllerHeaderObj = RadarControllerHeader()
                     processingHeaderObj = ProcessingHeader()
                     if not(basicHeaderObj.read(fp)):
                         flag = False
                     if not(systemHeaderObj.read(fp)):
                         flag = False
                     if not(radarControllerHeaderObj.read(fp)):
                         flag = False
                     if not(processingHeaderObj.read(fp)):
                         flag = False
                     if not self.online:
                         dt1 = basicHeaderObj.datatime
                         pos = self.fileSize-processingHeaderObj.blockSize-24
                         if pos<0:
                             flag = False
                             log.error('Invalid size for file: {}'.format(self.filename), self.name)
                         else:
                             fp.seek(pos)
                             if not(basicHeaderObj.read(fp)):
                                 flag = False
                         dt2 = basicHeaderObj.datatime
                         if not self.isDateTimeInRange(dt1, self.startDate, self.endDate, self.startTime, self.endTime) and not \
                                 self.isDateTimeInRange(dt2, self.startDate, self.endDate, self.startTime, self.endTime):
                             flag = False
                     fp.close()
                     return flag
                 def findDatafiles(self, path, startDate=None, endDate=None, expLabel='', ext='.r', walk=True, include_path=False):
                     path_empty = True
                     dateList = []
                     pathList = []
                     multi_path = path.split(',')
                     if not walk:
                         for single_path in multi_path:
                             if not os.path.isdir(single_path):
                                 continue
                             fileList = glob.glob1(single_path, "*" + ext)
                             if not fileList:
                                 continue
                             path_empty = False
                             fileList.sort()
                             for thisFile in fileList:
                                 if not os.path.isfile(os.path.join(single_path, thisFile)):
                                     continue
                                 if not isRadarFile(thisFile):
                                     continue
                                 if not isFileInDateRange(thisFile, startDate, endDate):
                                     continue
                                 thisDate = getDateFromRadarFile(thisFile)
                                 if thisDate in dateList or single_path in pathList:
                                     continue
                                 dateList.append(thisDate)
                                 pathList.append(single_path)
                     else:
                         for single_path in multi_path:
                             if not os.path.isdir(single_path):
                                 continue
                             dirList = []
                             for thisPath in os.listdir(single_path):
                                 if not os.path.isdir(os.path.join(single_path, thisPath)):
                                     continue
                                 if not isRadarFolder(thisPath):
                                     continue
                                 if not isFolderInDateRange(thisPath, startDate, endDate):
                                     continue
                                 dirList.append(thisPath)
                             if not dirList:
                                 continue
                             dirList.sort()
                             for thisDir in dirList:
                                 datapath = os.path.join(single_path, thisDir, expLabel)
                                 fileList = glob.glob1(datapath, "*" + ext)
                                 if not fileList:
                                     continue
                                 path_empty = False
                                 thisDate = getDateFromRadarFolder(thisDir)
                                 pathList.append(datapath)
                                 dateList.append(thisDate)
                     dateList.sort()
                     if walk:
                         pattern_path = os.path.join(multi_path[0], "[dYYYYDDD]", expLabel)
                     else:
                         pattern_path = multi_path[0]
                     if path_empty:
                         raise schainpy.admin.SchainError("[Reading] No *%s files in %s for %s to %s" % (ext, pattern_path, startDate, endDate))
                     else:
                         if not dateList:
                             raise schainpy.admin.SchainError("[Reading] Date range selected invalid [%s - %s]: No *%s files in %s)" % (startDate, endDate, ext, path))
                     if include_path:
                         return dateList, pathList
                     return dateList
                 def setup(self, **kwargs):
                     self.set_kwargs(**kwargs)
                     if not self.ext.startswith('.'):
                         self.ext = '.{}'.format(self.ext)
                     if self.server is not None:
                         if 'tcp://' in self.server:
                             address = server
                         else:
                             address = 'ipc:///tmp/%s' % self.server
                         self.server = address
                         self.context = zmq.Context()
                         self.receiver = self.context.socket(zmq.PULL)
                         self.receiver.connect(self.server)
                         time.sleep(0.5)
                         print('[Starting] ReceiverData from {}'.format(self.server))
                     else:
                         self.server = None
                         if self.path == None:
                             raise ValueError("[Reading] The path is not valid")
                         if self.online:
                             log.log("[Reading] Searching files in online mode...", self.name)
                             for nTries in range(self.nTries):
                                 fullpath = self.searchFilesOnLine(self.path, self.startDate,
                                     self.endDate, self.expLabel, self.ext, self.walk,
                                     self.filefmt, self.folderfmt)
                                 try:
                                     fullpath = next(fullpath)
                                 except:
                                     fullpath = None
                                 if fullpath:
                                     break
                                 log.warning(
                                     'Waiting {} sec for a valid file in {}: try {} ...'.format(
                                         self.delay, self.path, nTries + 1),
                                     self.name)
                                 time.sleep(self.delay)
                             if not(fullpath):
                                 raise schainpy.admin.SchainError(
                                     'There isn\'t any valid file in {}'.format(self.path))
                             pathname, filename = os.path.split(fullpath)
                             self.year = int(filename[1:5])
                             self.doy = int(filename[5:8])
                             self.set = int(filename[8:11]) - 1
                         else:
                             log.log("Searching files in {}".format(self.path), self.name)
                             self.filenameList = self.searchFilesOffLine(self.path, self.startDate,
                                 self.endDate, self.expLabel, self.ext, self.walk, self.filefmt, self.folderfmt)
                         self.setNextFile()
                     return
                 def getBasicHeader(self):
                     self.dataOut.utctime = self.basicHeaderObj.utc + self.basicHeaderObj.miliSecond / \
 . + self.profileIndex * self.radarControllerHeaderObj.ippSeconds
                     self.dataOut.flagDiscontinuousBlock = self.flagDiscontinuousBlock
                     self.dataOut.timeZone = self.basicHeaderObj.timeZone
                     self.dataOut.dstFlag = self.basicHeaderObj.dstFlag
                     self.dataOut.errorCount = self.basicHeaderObj.errorCount
                     self.dataOut.useLocalTime = self.basicHeaderObj.useLocalTime
                     self.dataOut.ippSeconds = self.radarControllerHeaderObj.ippSeconds / self.nTxs
                 def getFirstHeader(self):
                     raise NotImplementedError
                 def getData(self):
                     raise NotImplementedError
                 def hasNotDataInBuffer(self):
                     raise NotImplementedError
                 def readBlock(self):
                     raise NotImplementedError
                 def isEndProcess(self):
                     return self.flagNoMoreFiles
                 def printReadBlocks(self):
                     print("[Reading] Number of read blocks per file %04d" % self.nReadBlocks)
                 def printTotalBlocks(self):
                     print("[Reading] Number of read blocks %04d" % self.nTotalBlocks)
                 def run(self, **kwargs):
                     """
                     Arguments:
                         path        :
                         startDate   :
                         endDate     :
                         startTime   :
                         endTime     :
                         set         :
                         expLabel    :
                         ext         :
                         online      :
                         delay       :
                         walk        :
                         getblock    :
                         nTxs        :
                         realtime    :
                         blocksize   :
                         blocktime   :
                         skip        :
                         cursor      :
                         warnings    :
                         server      :
                         verbose     :
                         format      :
                         oneDDict    :
                         twoDDict    :
                         independentParam    :
                     """
                     if not(self.isConfig):
                         self.setup(**kwargs)
                         self.isConfig = True
                     if self.server is None:
                         self.getData()
                     else:
                         self.getFromServer()
             class JRODataWriter(Reader):
                 """
                 Esta clase permite escribir datos a archivos procesados (.r o ,pdata). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 setFile = None
                 profilesPerBlock = None
                 blocksPerFile = None
                 nWriteBlocks = 0
                 fileDate = None
                 def __init__(self, dataOut=None):
                     raise NotImplementedError
                 def hasAllDataInBuffer(self):
                     raise NotImplementedError
                 def setBlockDimension(self):
                     raise NotImplementedError
                 def writeBlock(self):
                     raise NotImplementedError
                 def putData(self):
                     raise NotImplementedError
                 def getDtypeWidth(self):
                     dtype_index = get_dtype_index(self.dtype)
                     dtype_width = get_dtype_width(dtype_index)
                     return dtype_width
                 def getProcessFlags(self):
                     processFlags = 0
                     dtype_index = get_dtype_index(self.dtype)
                     procflag_dtype = get_procflag_dtype(dtype_index)
                     processFlags += procflag_dtype
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
                     if self.dataOut.code is not None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nCohInt > 1:
                         processFlags += PROCFLAG.COHERENT_INTEGRATION
                     if self.dataOut.type == "Spectra":
                         if self.dataOut.nIncohInt > 1:
                             processFlags += PROCFLAG.INCOHERENT_INTEGRATION
                         if self.dataOut.data_dc is not None:
                             processFlags += PROCFLAG.SAVE_CHANNELS_DC
                         if self.dataOut.flagShiftFFT:
                             processFlags += PROCFLAG.SHIFT_FFT_DATA
                     return processFlags
                 def setBasicHeader(self):
                     self.basicHeaderObj.size = self.basicHeaderSize  # bytes
                     self.basicHeaderObj.version = self.versionFile
                     self.basicHeaderObj.dataBlock = self.nTotalBlocks
                     utc = numpy.floor(self.dataOut.utctime)
                     milisecond = (self.dataOut.utctime - utc) * 1000.0
                     self.basicHeaderObj.utc = utc
                     self.basicHeaderObj.miliSecond = milisecond
                     self.basicHeaderObj.timeZone = self.dataOut.timeZone
                     self.basicHeaderObj.dstFlag = self.dataOut.dstFlag
                     self.basicHeaderObj.errorCount = self.dataOut.errorCount
                 def setFirstHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.basicHeaderObj
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.processingHeaderObj self.
                     Return:
                         None
                     """
                     raise NotImplementedError
                 def __writeFirstHeader(self):
                     """
                     Escribe el primer header del file es decir el Basic header y el Long header (SystemHeader, RadarControllerHeader, ProcessingHeader)
                     Affected:
                         __dataType
                     Return:
                         None
                     """
             #        CALCULAR PARAMETROS
                     sizeLongHeader = self.systemHeaderObj.size + \
                         self.radarControllerHeaderObj.size + self.processingHeaderObj.size
                     self.basicHeaderObj.size = self.basicHeaderSize + sizeLongHeader
                     self.basicHeaderObj.write(self.fp)
                     self.systemHeaderObj.write(self.fp)
                     self.radarControllerHeaderObj.write(self.fp)
                     self.processingHeaderObj.write(self.fp)
                 def __setNewBlock(self):
                     """
                     Si es un nuevo file escribe el First Header caso contrario escribe solo el Basic Header
                     Return:
 :    si no pudo escribir nada
 :    Si escribio el Basic el First Header
                     """
                     if self.fp == None:
                         self.setNextFile()
                     if self.flagIsNewFile:
                         return 1
                     if self.blockIndex < self.processingHeaderObj.dataBlocksPerFile:
                         self.basicHeaderObj.write(self.fp)
                         return 1
                     if not(self.setNextFile()):
                         return 0
                     return 1
                 def writeNextBlock(self):
                     """
                     Selecciona el bloque siguiente de datos y los escribe en un file
                     Return:
 :    Si no hizo pudo escribir el bloque de datos
 :    Si no pudo escribir el bloque de datos
                     """
                     if not(self.__setNewBlock()):
                         return 0
                     self.writeBlock()
                     print("[Writing] Block No. %d/%d" % (self.blockIndex,
                                                          self.processingHeaderObj.dataBlocksPerFile))
                     return 1
                 def setNextFile(self):
                     """Determina el siguiente file que sera escrito
                     Affected:
                         self.filename
                         self.subfolder
                         self.fp
                         self.setFile
                         self.flagIsNewFile
                     Return:
 :    Si el archivo no puede ser escrito
 :    Si el archivo esta listo para ser escrito
                     """
                     ext = self.ext
                     path = self.path
                     if self.fp != None:
                         self.fp.close()
                     if not os.path.exists(path):
                         os.mkdir(path)
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year, timeTuple.tm_yday)
                     fullpath = os.path.join(path, subfolder)
                     setFile = self.setFile
                     if not(os.path.exists(fullpath)):
                         os.mkdir(fullpath)
                         setFile = -1  # inicializo mi contador de seteo
                     else:
                         filesList = os.listdir(fullpath)
                         if len(filesList) > 0:
                             filesList = sorted(filesList, key=str.lower)
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber(filen[8:11]):
                                 # inicializo mi contador de seteo al seteo del ultimo file
                                 setFile = int(filen[8:11])
                             else:
                                 setFile = -1
                         else:
                             setFile = -1  # inicializo mi contador de seteo
                     setFile += 1
                     # If this is a new day it resets some values
                     if self.dataOut.datatime.date() > self.fileDate:
                         setFile = 0
                         self.nTotalBlocks = 0
                     filen = '{}{:04d}{:03d}{:03d}{}'.format(
                             self.optchar, timeTuple.tm_year, timeTuple.tm_yday, setFile, ext)
                     filename = os.path.join(path, subfolder, filen)
                     fp = open(filename, 'wb')
                     self.blockIndex = 0
                     self.filename = filename
                     self.subfolder = subfolder
                     self.fp = fp
                     self.setFile = setFile
                     self.flagIsNewFile = 1
                     self.fileDate = self.dataOut.datatime.date()
                     self.setFirstHeader()
                     print('[Writing] Opening file: %s' % self.filename)
                     self.__writeFirstHeader()
                     return 1
                 def setup(self, dataOut, path, blocksPerFile, profilesPerBlock=64, set=None, ext=None, datatype=4):
                     """
                     Setea el tipo de formato en la cual sera guardada la data y escribe el First Header
                     Inputs:
                         path                :    directory where data will be saved
                         profilesPerBlock    :    number of profiles per block
                         set                 :    initial file set
                         datatype            :    An integer number that defines data type:
 : int8  (1 byte)
 : int16 (2 bytes)
 : int32 (4 bytes)
 : int64 (8 bytes)
 : float32 (4 bytes)
 : double64 (8 bytes)
                     Return:
 :    Si no realizo un buen seteo
 :    Si realizo un buen seteo
                     """
                     if ext == None:
                         ext = self.ext
                     self.ext = ext.lower()
                     self.path = path
                     if set is None:
                         self.setFile = -1
                     else:
                         self.setFile = set - 1
                     self.blocksPerFile = blocksPerFile
                     self.profilesPerBlock = profilesPerBlock
                     self.dataOut = dataOut
                     self.fileDate = self.dataOut.datatime.date()
                     self.dtype = self.dataOut.dtype
                     if datatype is not None:
                         self.dtype = get_numpy_dtype(datatype)
                     if not(self.setNextFile()):
                         print("[Writing] There isn't a next file")
                         return 0
                     self.setBlockDimension()
                     return 1
                 def run(self, dataOut, path, blocksPerFile=100, profilesPerBlock=64, set=None, ext=None, datatype=4, **kwargs):
                     if not(self.isConfig):
                         self.setup(dataOut, path, blocksPerFile, profilesPerBlock=profilesPerBlock,
                                    set=set, ext=ext, datatype=datatype, **kwargs)
                         self.isConfig = True
                     self.dataOut = dataOut
                     self.putData()
                     return self.dataOut
             @MPDecorator
             class printInfo(Operation):
                 def __init__(self):
                     Operation.__init__(self)
                     self.__printInfo = True
                 def run(self, dataOut, headers = ['systemHeaderObj', 'radarControllerHeaderObj', 'processingHeaderObj']):
                     if self.__printInfo == False:
                         return
                     for header in headers:
                         if hasattr(dataOut, header):
                             obj = getattr(dataOut, header)
                             if hasattr(obj, 'printInfo'):
                                 obj.printInfo()
                             else:
                                 print(obj)
                         else:
                             log.warning('Header {} Not found in object'.format(header))
                     self.__printInfo = False

schainpy/model/io/jroIO_kamisr.py +5 -3

             '''
             Created on Set 9, 2015
             @author: roj-idl71 Karim Kuyeng
             @update: 2021, Joab Apaza
             '''
             import os
             import sys
             import glob
             import fnmatch
             import datetime
             import time
             import re
             import h5py
             import numpy
             try:
                 from gevent import sleep
             except:
                 from time import sleep
             from schainpy.model.data.jroheaderIO import RadarControllerHeader, SystemHeader
             from schainpy.model.data.jrodata import Voltage
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from numpy import imag
             class AMISRReader(ProcessingUnit):
                 '''
                 classdocs
                 '''
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     ProcessingUnit.__init__(self)
                     self.set = None
                     self.subset = None
                     self.extension_file = '.h5'
                     self.dtc_str = 'dtc'
                     self.dtc_id = 0
                     self.status = True
                     self.isConfig = False
                     self.dirnameList = []
                     self.filenameList = []
                     self.fileIndex = None
                     self.flagNoMoreFiles = False
                     self.flagIsNewFile = 0
                     self.filename = ''
                     self.amisrFilePointer = None
                     self.realBeamCode = []
                     self.dataShape = None
                     self.profileIndex = 0
                     self.beamCodeByFrame = None
                     self.radacTimeByFrame = None
                     self.dataset = None
                     self.__firstFile = True
                     self.buffer = None
                     self.timezone = 'ut'
                     self.__waitForNewFile = 20
                     self.__filename_online = None
                     #Is really necessary create the output object in the initializer
                     self.dataOut = Voltage()
                     self.dataOut.error=False
                 def setup(self,path=None,
                                 startDate=None,
                                 endDate=None,
                                 startTime=None,
                                 endTime=None,
                                 walk=True,
                                 timezone='ut',
                                 all=0,
                                 code = None,
                                 nCode = 0,
                                 nBaud = 0,
                                 online=False):
                     self.timezone = timezone
                     self.all = all
                     self.online = online
                     self.code = code
                     self.nCode = int(nCode)
                     self.nBaud = int(nBaud)
                     #self.findFiles()
                     if not(online):
                         #Busqueda de archivos offline
                         self.searchFilesOffLine(path, startDate, endDate, startTime, endTime, walk)
                     else:
                         self.searchFilesOnLine(path, startDate, endDate, startTime,endTime,walk)
                     if not(self.filenameList):
                         print("There is no files into the folder: %s"%(path))
                         sys.exit()
                     self.fileIndex = 0
                     self.readNextFile(online)
                     '''
                     Add code
                     '''
                     self.isConfig = True
                     # print("Setup Done")
                     pass
                 def readAMISRHeader(self,fp):
                     if self.isConfig and (not self.flagNoMoreFiles):
                         newShape = fp.get('Raw11/Data/Samples/Data').shape[1:]
                         if self.dataShape != newShape and newShape != None:
                             print("\nNEW FILE HAS A DIFFERENT SHAPE")
                             print(self.dataShape,newShape,"\n")
                             return 0
                     else:
                         self.dataShape = fp.get('Raw11/Data/Samples/Data').shape[1:]
                     header = 'Raw11/Data/RadacHeader'
                     self.beamCodeByPulse = fp.get(header+'/BeamCode') # LIST OF BEAMS PER PROFILE, TO BE USED ON REARRANGE
                     if (self.startDate> datetime.date(2021, 7, 15)): #Se cambió la forma de extracción de Apuntes el 17
                         self.beamcodeFile = fp['Setup/Beamcodefile'][()].decode()
                         self.trueBeams = self.beamcodeFile.split("\n")
                         self.trueBeams.pop()#remove last
                         [self.realBeamCode.append(x) for x in self.trueBeams if x not in self.realBeamCode]
                         self.beamCode = [int(x, 16) for x in self.realBeamCode]
                     else:
                         _beamCode= fp.get('Raw11/Data/Beamcodes') #se usa la manera previa al cambio de apuntes
                         self.beamCode = _beamCode[0,:]
                     #self.code = fp.get(header+'/Code') # NOT USE FOR THIS
                     self.frameCount = fp.get(header+'/FrameCount')# NOT USE FOR THIS
                     self.modeGroup = fp.get(header+'/ModeGroup')# NOT USE FOR THIS
                     self.nsamplesPulse = fp.get(header+'/NSamplesPulse')# TO GET NSA OR USING DATA FOR THAT
                     self.pulseCount = fp.get(header+'/PulseCount')# NOT USE FOR THIS
                     self.radacTime = fp.get(header+'/RadacTime')# 1st TIME ON FILE ANDE CALCULATE THE REST WITH IPP*nindexprofile
                     self.timeCount = fp.get(header+'/TimeCount')# NOT USE FOR THIS
                     self.timeStatus = fp.get(header+'/TimeStatus')# NOT USE FOR THIS
                     self.rangeFromFile = fp.get('Raw11/Data/Samples/Range')
                     self.frequency =  fp.get('Rx/Frequency')
                     txAus = fp.get('Raw11/Data/Pulsewidth')
                     self.nblocks = self.pulseCount.shape[0] #nblocks
                     self.nprofiles = self.pulseCount.shape[1] #nprofile
                     self.nsa = self.nsamplesPulse[0,0] #ngates
                     self.nchannels = len(self.beamCode)
                     self.ippSeconds = (self.radacTime[0][1] -self.radacTime[0][0]) #Ipp in seconds
                     #self.__waitForNewFile = self.nblocks  # wait depending on the number of blocks since each block is 1 sec
                     self.__waitForNewFile = self.nblocks * self.nprofiles * self.ippSeconds # wait until new file is created
                     #filling radar controller header parameters
                     self.__ippKm = self.ippSeconds *.15*1e6 # in km
                     self.__txA = (txAus.value)*.15 #(ipp[us]*.15km/1us) in km
                     self.__txB = 0
                     nWindows=1
                     self.__nSamples = self.nsa
                     self.__firstHeight = self.rangeFromFile[0][0]/1000 #in km
                     self.__deltaHeight = (self.rangeFromFile[0][1] - self.rangeFromFile[0][0])/1000
                     #for now until understand why the code saved is different (code included even though code not in tuf file)
                     #self.__codeType = 0
                    # self.__nCode = None
                    # self.__nBaud = None
                     self.__code = self.code
                     self.__codeType = 0
                     if self.code != None:
                         self.__codeType = 1
                     self.__nCode = self.nCode
                     self.__nBaud = self.nBaud
                     #self.__code = 0
                     #filling system header parameters
                     self.__nSamples = self.nsa
                     self.newProfiles = self.nprofiles/self.nchannels
                     self.__channelList = list(range(self.nchannels))
                     self.__frequency = self.frequency[0][0]
                     return 1
                 def createBuffers(self):
                     pass
                 def __setParameters(self,path='', startDate='',endDate='',startTime='', endTime='', walk=''):
                     self.path = path
                     self.startDate = startDate
                     self.endDate = endDate
                     self.startTime = startTime
                     self.endTime = endTime
                     self.walk = walk
                 def __checkPath(self):
                     if os.path.exists(self.path):
                         self.status = 1
                     else:
                         self.status = 0
                         print('Path:%s does not exists'%self.path)
                     return
                 def __selDates(self, amisr_dirname_format):
                     try:
                         year = int(amisr_dirname_format[0:4])
                         month = int(amisr_dirname_format[4:6])
                         dom = int(amisr_dirname_format[6:8])
                         thisDate = datetime.date(year,month,dom)
                         if (thisDate>=self.startDate and thisDate <= self.endDate):
                             return amisr_dirname_format
                     except:
                         return None
                 def __findDataForDates(self,online=False):
                     if not(self.status):
                         return None
                     pat = '\d+.\d+'
                     dirnameList = [re.search(pat,x) for x in os.listdir(self.path)]
                     dirnameList = [x for x in dirnameList if x!=None]
                     dirnameList = [x.string for x in dirnameList]
                     if not(online):
                         dirnameList = [self.__selDates(x) for x in dirnameList]
                         dirnameList = [x for x in dirnameList if x!=None]
                     if len(dirnameList)>0:
                         self.status = 1
                         self.dirnameList = dirnameList
                         self.dirnameList.sort()
                     else:
                         self.status = 0
                         return None
                 def __getTimeFromData(self):
                     startDateTime_Reader = datetime.datetime.combine(self.startDate,self.startTime)
                     endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime)
                     print('Filtering Files from %s to %s'%(startDateTime_Reader, endDateTime_Reader))
                     print('........................................')
                     filter_filenameList = []
                     self.filenameList.sort()
                     #for i in range(len(self.filenameList)-1):
                     for i in range(len(self.filenameList)):
                         filename = self.filenameList[i]
                         fp = h5py.File(filename,'r')
                         time_str = fp.get('Time/RadacTimeString')
                         startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0]
                         #startDateTimeStr_File = "2019-12-16 09:21:11"
                         junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S')
                         startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec)
                         #endDateTimeStr_File = "2019-12-16 11:10:11"
                         endDateTimeStr_File = time_str[-1][-1].decode('UTF-8').split('.')[0]
                         junk = time.strptime(endDateTimeStr_File, '%Y-%m-%d %H:%M:%S')
                         endDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec)
                         fp.close()
                         #print("check time", startDateTime_File)
                         if self.timezone == 'lt':
                             startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300)
                             endDateTime_File = endDateTime_File - datetime.timedelta(minutes = 300)
                         if (endDateTime_File>=startDateTime_Reader and endDateTime_File<=endDateTime_Reader):
                             filter_filenameList.append(filename)
                         if (endDateTime_File>endDateTime_Reader):
                             break
                     filter_filenameList.sort()
                     self.filenameList = filter_filenameList
                     return 1
                 def __filterByGlob1(self, dirName):
                     filter_files = glob.glob1(dirName, '*.*%s'%self.extension_file)
                     filter_files.sort()
                     filterDict = {}
                     filterDict.setdefault(dirName)
                     filterDict[dirName] = filter_files
                     return filterDict
                 def __getFilenameList(self, fileListInKeys, dirList):
                     for value in fileListInKeys:
                         dirName = list(value.keys())[0]
                         for file in value[dirName]:
                             filename = os.path.join(dirName, file)
                             self.filenameList.append(filename)
                 def __selectDataForTimes(self, online=False):
                     #aun no esta implementado el filtro for tiempo
                     if not(self.status):
                         return None
                     dirList = [os.path.join(self.path,x) for x in self.dirnameList]
                     fileListInKeys = [self.__filterByGlob1(x) for x in dirList]
                     self.__getFilenameList(fileListInKeys, dirList)
                     if not(online):
                         #filtro por tiempo
                         if not(self.all):
                             self.__getTimeFromData()
                         if len(self.filenameList)>0:
                             self.status = 1
                             self.filenameList.sort()
                         else:
                             self.status = 0
                             return None
                     else:
                         #get the last file - 1
-                        self.filenameList = [self.filenameList[-1]]
+                        self.filenameList = [self.filenameList[-2]]
                     new_dirnameList = []
                     for dirname in self.dirnameList:
                         junk = numpy.array([dirname in x for x in self.filenameList])
                         junk_sum = junk.sum()
                         if junk_sum > 0:
                             new_dirnameList.append(dirname)
                     self.dirnameList = new_dirnameList
                     return 1
                 def searchFilesOnLine(self, path, startDate, endDate, startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),walk=True):
                     if endDate ==None:
                      startDate = datetime.datetime.utcnow().date()
                      endDate = datetime.datetime.utcnow().date()
                     self.__setParameters(path=path, startDate=startDate, endDate=endDate,startTime = startTime,endTime=endTime, walk=walk)
                     self.__checkPath()
                     self.__findDataForDates(online=True)
                     self.dirnameList = [self.dirnameList[-1]]
                     self.__selectDataForTimes(online=True)
                     return
                 def searchFilesOffLine(self,
                                         path,
                                         startDate,
                                         endDate,
                                         startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),
                                         walk=True):
                     self.__setParameters(path, startDate, endDate, startTime, endTime, walk)
                     self.__checkPath()
                     self.__findDataForDates()
                     self.__selectDataForTimes()
                     for i in range(len(self.filenameList)):
                         print("%s" %(self.filenameList[i]))
                     return
                 def __setNextFileOffline(self):
                     try:
                         self.filename = self.filenameList[self.fileIndex]
                         self.amisrFilePointer = h5py.File(self.filename,'r')
                         self.fileIndex += 1
                     except:
                         self.flagNoMoreFiles = 1
                         print("No more Files")
                         return 0
                     self.flagIsNewFile = 1
                     print("Setting the file: %s"%self.filename)
                     return 1
                 def __setNextFileOnline(self):
                     filename = self.filenameList[0]
                     if self.__filename_online != None:
                         self.__selectDataForTimes(online=True)
                         filename = self.filenameList[0]
                         wait = 0
-                        #self.__waitForNewFile=180 ## DEBUG:
+                        self.__waitForNewFile=300 ## DEBUG:
                         while self.__filename_online == filename:
                             print('waiting %d seconds to get a new file...'%(self.__waitForNewFile))
                             if wait == 5:
                                 self.flagNoMoreFiles = 1
                                 return 0
                             sleep(self.__waitForNewFile)
                             self.__selectDataForTimes(online=True)
                             filename = self.filenameList[0]
                             wait += 1
                     self.__filename_online = filename
                     self.amisrFilePointer = h5py.File(filename,'r')
                     self.flagIsNewFile = 1
                     self.filename = filename
                     print("Setting the file: %s"%self.filename)
                     return 1
                 def readData(self):
                     buffer = self.amisrFilePointer.get('Raw11/Data/Samples/Data')
                     re = buffer[:,:,:,0]
                     im = buffer[:,:,:,1]
                     dataset = re + im*1j
                     self.radacTime = self.amisrFilePointer.get('Raw11/Data/RadacHeader/RadacTime')
                     timeset = self.radacTime[:,0]
                     return dataset,timeset
                 def reshapeData(self):
                 #self.beamCodeByPulse, self.beamCode, self.nblocks, self.nprofiles, self.nsa,
                     channels = self.beamCodeByPulse[0,:]
                     nchan = self.nchannels
                     #self.newProfiles = self.nprofiles/nchan #must be defined on filljroheader
                     nblocks = self.nblocks
                     nsamples = self.nsa
                     #Dimensions : nChannels, nProfiles, nSamples
                     new_block = numpy.empty((nblocks, nchan, numpy.int_(self.newProfiles), nsamples), dtype="complex64")
                     ############################################
                     for thisChannel in range(nchan):
                         new_block[:,thisChannel,:,:] = self.dataset[:,numpy.where(channels==self.beamCode[thisChannel])[0],:]
                     new_block = numpy.transpose(new_block, (1,0,2,3))
                     new_block = numpy.reshape(new_block, (nchan,-1, nsamples))
                     return new_block
                 def updateIndexes(self):
                     pass
                 def fillJROHeader(self):
                     #fill radar controller header
                     self.dataOut.radarControllerHeaderObj = RadarControllerHeader(ipp=self.__ippKm,
                                                                                   txA=self.__txA,
                                                                                   txB=0,
                                                                                   nWindows=1,
                                                                                   nHeights=self.__nSamples,
                                                                                   firstHeight=self.__firstHeight,
                                                                                   deltaHeight=self.__deltaHeight,
                                                                                   codeType=self.__codeType,
                                                                                   nCode=self.__nCode, nBaud=self.__nBaud,
                                                                                   code = self.__code,
                                                                                   fClock=1)
                     #fill system header
                     self.dataOut.systemHeaderObj = SystemHeader(nSamples=self.__nSamples,
                                                                 nProfiles=self.newProfiles,
                                                                 nChannels=len(self.__channelList),
                                                                 adcResolution=14,
                                                                 pciDioBusWidth=32)
                     self.dataOut.type = "Voltage"
                     self.dataOut.data = None
                     self.dataOut.dtype = numpy.dtype([('real','<i8'),('imag','<i8')])
             #        self.dataOut.nChannels = 0
             #        self.dataOut.nHeights = 0
                     self.dataOut.nProfiles = self.newProfiles*self.nblocks
                     #self.dataOut.heightList = self.__firstHeigth + numpy.arange(self.__nSamples, dtype = numpy.float)*self.__deltaHeigth
                     ranges = numpy.reshape(self.rangeFromFile.value,(-1))
                     self.dataOut.heightList =  ranges/1000.0 #km
                     self.dataOut.channelList = self.__channelList
                     self.dataOut.blocksize = self.dataOut.nChannels * self.dataOut.nHeights
             #        self.dataOut.channelIndexList = None
                     self.dataOut.flagNoData = True
                     #Set to TRUE if the data is discontinuous
                     self.dataOut.flagDiscontinuousBlock = False
                     self.dataOut.utctime = None
                     #self.dataOut.timeZone = -5 #self.__timezone/60  #timezone like jroheader, difference in minutes between UTC and localtime
                     if self.timezone == 'lt':
                         self.dataOut.timeZone = time.timezone / 60. #get the timezone in minutes
                     else:
                         self.dataOut.timeZone = 0 #by default time is UTC
                     self.dataOut.dstFlag = 0
                     self.dataOut.errorCount = 0
                     self.dataOut.nCohInt = 1
                     self.dataOut.flagDecodeData = False #asumo que la data esta decodificada
                     self.dataOut.flagDeflipData = False #asumo que la data esta sin flip
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.ippSeconds = self.ippSeconds
                     #Time interval between profiles
                     #self.dataOut.timeInterval = self.dataOut.ippSeconds * self.dataOut.nCohInt
                     self.dataOut.frequency = self.__frequency
                     self.dataOut.realtime = self.online
                     pass
                 def readNextFile(self,online=False):
                     if not(online):
                         newFile = self.__setNextFileOffline()
                     else:
                         newFile = self.__setNextFileOnline()
                     if not(newFile):
                         self.dataOut.error = True
                         return 0
                     if not self.readAMISRHeader(self.amisrFilePointer):
                         self.dataOut.error = True
                         return 0
                     self.createBuffers()
                     self.fillJROHeader()
                     #self.__firstFile = False
                     self.dataset,self.timeset = self.readData()
                     if self.endDate!=None:
                      endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime)
                      time_str = self.amisrFilePointer.get('Time/RadacTimeString')
                      startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0]
                      junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S')
                      startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec)
                      if self.timezone == 'lt':
                       startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300)
                      if (startDateTime_File>endDateTime_Reader):
                          return 0
                     self.jrodataset = self.reshapeData()
                     #----self.updateIndexes()
                     self.profileIndex = 0
                     return 1
                 def __hasNotDataInBuffer(self):
                     if self.profileIndex >= (self.newProfiles*self.nblocks):
                         return 1
                     return 0
                 def getData(self):
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         return 0
                     if self.__hasNotDataInBuffer():
                         if not (self.readNextFile(self.online)):
                             return 0
                     if self.dataset is None: # setear esta condicion cuando no hayan datos por leer
                         self.dataOut.flagNoData = True
                         return 0
                     #self.dataOut.data = numpy.reshape(self.jrodataset[self.profileIndex,:],(1,-1))
                     self.dataOut.data = self.jrodataset[:,self.profileIndex,:]
                     #print("R_t",self.timeset)
                     #self.dataOut.utctime = self.jrotimeset[self.profileIndex]
                     #verificar basic header de jro data y ver si es compatible con este valor
                     #self.dataOut.utctime = self.timeset + (self.profileIndex * self.ippSeconds * self.nchannels)
                     indexprof = numpy.mod(self.profileIndex, self.newProfiles)
                     indexblock = self.profileIndex/self.newProfiles
                     #print (indexblock, indexprof)
                     diffUTC = 1.8e4 #UTC diference from peru in seconds --Joab
                     diffUTC = 0
                     t_comp = (indexprof * self.ippSeconds * self.nchannels) + diffUTC #
                     #print("utc :",indexblock," __ ",t_comp)
                     #print(numpy.shape(self.timeset))
                     self.dataOut.utctime = self.timeset[numpy.int_(indexblock)] + t_comp
                     #self.dataOut.utctime = self.timeset[self.profileIndex] + t_comp
                     #print(self.dataOut.utctime)
                     self.dataOut.profileIndex = self.profileIndex
+                    #print("N profile:",self.profileIndex,self.newProfiles,self.nblocks,self.dataOut.utctime)
                     self.dataOut.flagNoData = False
             #         if indexprof == 0:
             #             print self.dataOut.utctime
                     self.profileIndex += 1
-                    return self.dataOut.data
+                    #return self.dataOut.data
                 def run(self, **kwargs):
                     '''
                     This method will be called many times so here you should put all your code
                     '''
                     #print("running kamisr")
                     if not self.isConfig:
                         self.setup(**kwargs)
                         self.isConfig = True
                     self.getData()
+                    return(self.dataOut.data)

schainpy/model/proc/jroproc_heispectra.py 0 -1

             import numpy
             from .jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import SpectraHeis
             from schainpy.utils import log
             class SpectraHeisProc(ProcessingUnit):
                 def __init__(self):#, **kwargs):
                     ProcessingUnit.__init__(self)#, **kwargs)
             #        self.buffer = None
             #        self.firstdatatime = None
             #        self.profIndex = 0
                     self.dataOut = SpectraHeis()
                 def __updateObjFromVoltage(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 = self.dataIn.dtype
                     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 = 1
                     self.dataOut.ippFactor = 1
                     self.dataOut.noise_estimation = None
             #        self.dataOut.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.nFFTPoints = self.dataIn.nHeights
             #        self.dataOut.channelIndexList = self.dataIn.channelIndexList
             #        self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.dataIn.utctime
             #        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.nIncohInt
             #        self.dataOut.set=self.dataIn.set
             #        self.dataOut.deltaHeight=self.dataIn.deltaHeight
                 def __updateObjFromFits(self):
                     self.dataOut.utctime = self.dataIn.utctime
             #         self.dataOut.channelIndexList = self.dataIn.channelIndexList
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.data_spc = self.dataIn.data
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = self.dataIn.nIncohInt
             #         self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.useLocalTime = True
             #         self.dataOut.
             #         self.dataOut.
                 def __getFft(self):
                     fft_volt = numpy.fft.fft(self.dataIn.data, axis=1)
                     fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
                     spc = numpy.abs(fft_volt * numpy.conjugate(fft_volt))/(self.dataOut.nFFTPoints)
                     self.dataOut.data_spc = spc
                 def run(self):
                     self.dataOut.flagNoData = True
                     if self.dataIn.type == "Fits":
                         self.__updateObjFromFits()
                         self.dataOut.flagNoData = False
                         return
                     if self.dataIn.type == "SpectraHeis":
                         self.dataOut.copy(self.dataIn)
                         return
                     if self.dataIn.type == "Voltage":
                         self.__updateObjFromVoltage()
                         self.__getFft()
                         self.dataOut.flagNoData = False
                         return
                     raise ValueError("The type object %s is not valid"%(self.dataIn.type))
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in 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
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                         self.dataOut.m_ProcessingHeader.totalSpectra
                         self.dataOut.systemHeaderObj.numChannels
                         self.dataOut.m_ProcessingHeader.blockSize
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError("The value %d in channelIndexList is not valid" %channelIndex)
                     data_spc = self.dataOut.data_spc[channelIndexList,:]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                     return 1
             class IncohInt4SpectraHeis(Operation):
                 isConfig = False
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 n = None
                 def __init__(self):#, **kwargs):
                     Operation.__init__(self)#, **kwargs)
             #         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 = 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 #* 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverapping = True
                         self.__buffer = None
                     else:
                         self.__withOverapping = False
                         self.__buffer = 0
                     self.__profIndex = 0
                 def putData(self, data):
                     """
                     Add a profile to the __buffer and increase in one the __profileIndex
                     """
                     if not self.__withOverapping:
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
                     data = numpy.reshape(data, (1, nChannels, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer is None:
                         self.__buffer = data
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer = numpy.vstack((self.__buffer, data))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
                     self.__buffer[self.n-1] = data
                     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
                     """
                     if not self.__withOverapping:
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
             #         n = None
                     self.putData(data)
                     if self.__profIndex == self.n:
                         avgdata, n = self.pushData()
                         self.__dataReady = True
                     return avgdata
                 def byTime(self, data, datatime):
                     self.__dataReady = False
                     avgdata = None
                     n = None
                     self.putData(data)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata
                 def integrate(self, data, datatime=None):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata = self.byTime(data, datatime)
                     else:
                         avgdata = self.byProfiles(data)
                     self.__lastdatatime = datatime
                     if avgdata is None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime -self.__lastdatatime
                     if not self.__withOverapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, timeInterval=timeInterval, overlapping=overlapping)
                         self.isConfig = True
                     avgdata, avgdatatime = self.integrate(dataOut.data_spc, dataOut.utctime)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data_spc = avgdata
                         dataOut.nIncohInt *= self.n
             #            dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
             #             dataOut.timeInterval = dataOut.ippSeconds * dataOut.nIncohInt
             #            dataOut.timeInterval = self.__timeInterval*self.n
                         dataOut.flagNoData = False
                     return dataOut

schainpy/model/proc/jroproc_spectra.py +559 0

             # Copyright (c) 2012-2020 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """Spectra processing Unit and operations
             Here you will find the processing unit `SpectraProc` and several operations
             to work with Spectra data type
             """
             import time
             import itertools
             import numpy
+            import math
             from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation
             from schainpy.model.data.jrodata import Spectra
             from schainpy.model.data.jrodata import hildebrand_sekhon
             from schainpy.utils import log
+            from scipy.optimize import curve_fit
             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
                     self.setupReq = False #Agregar a todas las unidades de proc
                 def __updateSpecFromVoltage(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
                     try:
                         self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy()
                     except:
                         pass
                     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.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.firstdatatime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
                     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=None, ippFactor=None, shift_fft=False):
                     if self.dataIn.type == "Spectra":
                         self.dataOut.copy(self.dataIn)
                         if shift_fft:
                             #desplaza a la derecha en el eje 2 determinadas posiciones
                             shift = int(self.dataOut.nFFTPoints/2)
                             self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1)
                             if self.dataOut.data_cspc is not None:
                                 #desplaza a la derecha en el eje 2 determinadas posiciones
                                 self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1)
                         if pairsList:
                             self.__selectPairs(pairsList)
                     elif self.dataIn.type == "Voltage":
                         self.dataOut.flagNoData = True
                         if nFFTPoints == None:
                             raise ValueError("This SpectraProc.run() need nFFTPoints input variable")
                         if nProfiles == None:
                             nProfiles = nFFTPoints
                         if ippFactor == None:
                             self.dataOut.ippFactor = 1
                         self.dataOut.nFFTPoints = nFFTPoints
                         if self.buffer is None:
                             self.buffer = numpy.zeros((self.dataIn.nChannels,
                                                        nProfiles,
                                                        self.dataIn.nHeights),
                                                       dtype='complex')
                         if self.dataIn.flagDataAsBlock:
                             nVoltProfiles = self.dataIn.data.shape[1]
                             if nVoltProfiles == nProfiles:
                                 self.buffer = self.dataIn.data.copy()
                                 self.profIndex = nVoltProfiles
                             elif nVoltProfiles < nProfiles:
                                 if self.profIndex == 0:
                                     self.id_min = 0
                                     self.id_max = nVoltProfiles
                                 self.buffer[:, self.id_min:self.id_max,
                                             :] = self.dataIn.data
                                 self.profIndex += nVoltProfiles
                                 self.id_min += nVoltProfiles
                                 self.id_max += nVoltProfiles
                             else:
                                 raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % (
                                     self.dataIn.type, self.dataIn.data.shape[1], nProfiles))
                                 self.dataOut.flagNoData = True
                         else:
                             self.buffer[:, self.profIndex, :] = self.dataIn.data.copy()
                             self.profIndex += 1
                         if self.firstdatatime == None:
                             self.firstdatatime = self.dataIn.utctime
                         if self.profIndex == nProfiles:
                             self.__updateSpecFromVoltage()
                             if pairsList == None:
                                 self.dataOut.pairsList = [pair for pair in itertools.combinations(self.dataOut.channelList, 2)]
                             else:
                                 self.dataOut.pairsList = pairsList
                             self.__getFft()
                             self.dataOut.flagNoData = False
                             self.firstdatatime = None
                             self.profIndex = 0
                     else:
                         raise ValueError("The type of input object '%s' is not valid".format(
                             self.dataIn.type))
                 def __selectPairs(self, pairsList):
                     if not pairsList:
                         return
                     pairs = []
                     pairsIndex = []
                     for pair in pairsList:
                         if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList:
                             continue
                         pairs.append(pair)
                         pairsIndex.append(pairs.index(pair))
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex]
                     self.dataOut.pairsList = pairs
                     return
                 def selectFFTs(self, minFFT, maxFFT ):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango
                     minFFT<= FFT <= maxFFT
                     """
                     if (minFFT > maxFFT):
                         raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT))
                     if (minFFT < self.dataOut.getFreqRange()[0]):
                         minFFT = self.dataOut.getFreqRange()[0]
                     if (maxFFT > self.dataOut.getFreqRange()[-1]):
                         maxFFT = self.dataOut.getFreqRange()[-1]
                     minIndex = 0
                     maxIndex = 0
                     FFTs = self.dataOut.getFreqRange()
                     inda = numpy.where(FFTs >= minFFT)
                     indb = numpy.where(FFTs <= maxFFT)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(FFTs)
                     self.selectFFTsByIndex(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 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 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 selectFFTsByIndex(self, minIndex, maxIndex):
                     """
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex))
                     if (maxIndex >= self.dataOut.nProfiles):
                         maxIndex = self.dataOut.nProfiles-1
                     #Spectra
                     data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:]
                     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 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.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1])
                     self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1]
                     self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1]
                     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, :, :]
                         sortdata = numpy.sort(daux, axis=None)
                         noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt)
                     self.dataOut.noise_estimation = noise.copy()
                     return 1
             class removeDC(Operation):
                 def run(self, dataOut, mode=2):
                     self.dataOut = dataOut
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
                     if jcspectra is not None:
                         jcspectraExist = True
                         num_pairs = jcspectra.shape[0]
                     else:
                         jcspectraExist = False
                     freq_dc = int(jspectra.shape[1] / 2)
                     ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc
                     ind_vel = ind_vel.astype(int)
                     if ind_vel[0] < 0:
                         ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof
                     if mode == 1:
                         jspectra[:, freq_dc, :] = (
                             jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2  # CORRECCION
                         if 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(list(range(4)))
                         xx_inv = numpy.linalg.inv(xx)
                         xx_aux = xx_inv[0, :]
                         for ich in range(num_chan):
                             yy = jspectra[ich, ind_vel, :]
                             jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy)
                             junkid = jspectra[ich, freq_dc, :] <= 0
                             cjunkid = sum(junkid)
                             if cjunkid.any():
                                 jspectra[ich, freq_dc, junkid.nonzero()] = (
                                     jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2
                         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 self.dataOut
+            # import matplotlib.pyplot as plt
+            def fit_func( x, a0, a1, a2): #, a3, a4, a5):
+                z = (x - a1) / a2
+                y = a0 * numpy.exp(-z**2 / a2)  #+ a3 + a4 * x + a5 * x**2
+                return y
+            class CleanRayleigh(Operation):
+                def __init__(self):
+                    Operation.__init__(self)
+                    self.i=0
+                    self.isConfig = False
+                    self.__dataReady = False
+                    self.__profIndex = 0
+                    self.byTime = False
+                    self.byProfiles = False
+                    self.bloques =  None
+                    self.bloque0 = None
+                    self.index = 0
+                    self.buffer = 0
+                    self.buffer2 = 0
+                    self.buffer3 = 0
+                    #self.min_hei = None
+                    #self.max_hei = None
+                def setup(self,dataOut,min_hei,max_hei,n, timeInterval,factor_stdv):
+                    self.nChannels = dataOut.nChannels
+                    self.nProf = dataOut.nProfiles
+                    self.nPairs = dataOut.data_cspc.shape[0]
+                    self.pairsArray = numpy.array(dataOut.pairsList)
+                    self.spectra = dataOut.data_spc
+                    self.cspectra = dataOut.data_cspc
+                    self.heights = dataOut.heightList #alturas totales
+                    self.nHeights =  len(self.heights)
+                    self.min_hei = min_hei
+                    self.max_hei = max_hei
+                    if (self.min_hei == None):
+                        self.min_hei = 0
+                    if (self.max_hei == None):
+                        self.max_hei = dataOut.heightList[-1]
+                    self.hval = ((self.max_hei>=self.heights) & (self.heights >= self.min_hei)).nonzero()
+                    self.heightsClean = self.heights[self.hval] #alturas filtradas
+                    self.hval = self.hval[0] # forma (N,), an solo N elementos -> Indices de alturas
+                    self.nHeightsClean = len(self.heightsClean)
+                    self.channels = dataOut.channelList
+                    self.nChan = len(self.channels)
+                    self.nIncohInt = dataOut.nIncohInt
+                    self.__initime = dataOut.utctime
+                    self.maxAltInd = self.hval[-1]+1
+                    self.minAltInd = self.hval[0]
+                    self.crosspairs = dataOut.pairsList
+                    self.nPairs = len(self.crosspairs)
+                    self.normFactor = dataOut.normFactor
+                    self.nFFTPoints = dataOut.nFFTPoints
+                    self.ippSeconds = dataOut.ippSeconds
+                    self.currentTime = self.__initime
+                    self.pairsArray = numpy.array(dataOut.pairsList)
+                    self.factor_stdv = factor_stdv
+                    if n != None :
+                        self.byProfiles = True
+                        self.nIntProfiles = n
+                    else:
+                        self.__integrationtime = timeInterval
+                    self.__dataReady = False
+                    self.isConfig = True
+                def run(self, dataOut,min_hei=None,max_hei=None, n=None, timeInterval=10,factor_stdv=2.5):
+                    #print (dataOut.utctime)
+                    if not self.isConfig :
+                        #print("Setting config")
+                        self.setup(dataOut, min_hei,max_hei,n,timeInterval,factor_stdv)
+                        #print("Config Done")
+                    tini=dataOut.utctime
+                    if self.byProfiles:
+                        if self.__profIndex ==  self.nIntProfiles:
+                            self.__dataReady = True
+                    else:
+                        if (tini - self.__initime) >= self.__integrationtime:
+                            #print(tini - self.__initime,self.__profIndex)
+                            self.__dataReady = True
+                            self.__initime = tini
+                    #if (tini.tm_min % 2) == 0 and (tini.tm_sec < 5 and self.fint==0):
+                    if self.__dataReady:
+                        print("Data ready",self.__profIndex)
+                        self.__profIndex = 0
+                        jspc = self.buffer
+                        jcspc = self.buffer2
+                        #jnoise = self.buffer3
+                        self.buffer = dataOut.data_spc
+                        self.buffer2 = dataOut.data_cspc
+                        #self.buffer3 = dataOut.noise
+                        self.currentTime = dataOut.utctime
+                        if numpy.any(jspc) :
+                            #print( jspc.shape, jcspc.shape)
+                            jspc = numpy.reshape(jspc,(int(len(jspc)/self.nChannels),self.nChannels,self.nFFTPoints,self.nHeights))
+                            jcspc= numpy.reshape(jcspc,(int(len(jcspc)/self.nPairs),self.nPairs,self.nFFTPoints,self.nHeights))
+                            self.__dataReady = False
+                            #print( jspc.shape, jcspc.shape)
+                            dataOut.flagNoData = False
+                        else:
+                            dataOut.flagNoData = True
+                            self.__dataReady = False
+                            return dataOut
+                    else:
+                        #print( len(self.buffer))
+                        if numpy.any(self.buffer):
+                            self.buffer = numpy.concatenate((self.buffer,dataOut.data_spc), axis=0)
+                            self.buffer2 = numpy.concatenate((self.buffer2,dataOut.data_cspc), axis=0)
+                            self.buffer3 += dataOut.data_dc
+                        else:
+                            self.buffer = dataOut.data_spc
+                            self.buffer2 = dataOut.data_cspc
+                            self.buffer3 = dataOut.data_dc
+                        #print self.index, self.fint
+                        #print self.buffer2.shape
+                        dataOut.flagNoData = True                   ## NOTE: ?? revisar LUEGO
+                        self.__profIndex += 1
+                        return dataOut                             ## NOTE: REV
+                    # if self.index == 0 and self.fint == 1 :
+                    #    if jspc != None:
+                    #        print len(jspc), jspc.shape
+                    #        jspc= numpy.reshape(jspc,(4,128,63,len(jspc)/4))
+                    #        print jspc.shape
+                    # dataOut.flagNoData = True
+                    # return dataOut
+                    # if path != None:
+                    #     sys.path.append(path)
+                    # self.library = importlib.import_module(file)
+                    #
+                    # To be inserted as a parameter
+                    #Set constants
+                    #constants = self.library.setConstants(dataOut)
+                    #dataOut.constants = constants
+                    #snrth= 20
+                    #crosspairs = dataOut.groupList
+                    #noise = dataOut.noise
+                    #print( nProf,heights)
+                    #print( jspc.shape, jspc.shape[0])
+                    #print noise
+                    #print jnoise[len(jnoise)-1,:], numpy.nansum(jnoise,axis=0)/len(jnoise)
+                    #jnoise = jnoise/N
+                    #noise = numpy.nansum(jnoise,axis=0)#/len(jnoise)
+                    #print( noise)
+                    #power = numpy.sum(spectra, axis=1)
+                    #print power[0,:]
+                    #print("CROSSPAIRS",crosspairs)
+                    #nPairs = len(crosspairs)
+                    #print(numpy.shape(dataOut.data_spc))
+                    #absc = dataOut.abscissaList[:-1]
+                    #print absc.shape
+                    #nBlocks=149
+                    #print('spectra', spectra.shape)
+                    #print('noise print', crosspairs)
+                    #print('spectra', spectra.shape)
+                    #print('cspectra', cspectra.shape)
+                    #print numpy.array(dataOut.data_pre[1]).shape
+                    #spec, cspec = self.__DiffCoherent(snrth, spectra, cspectra, nProf, heights,nChan, nHei, nPairs, channels, noise*nProf, crosspairs)
+                    #index = tini.tm_hour*12+tini.tm_min/5
+                    # jspc = jspc/self.nFFTPoints/self.normFactor
+                    # jcspc = jcspc/self.nFFTPoints/self.normFactor
+                    #dataOut.data_spc,dataOut.data_cspc = self.CleanRayleigh(dataOut,jspc,jcspc,crosspairs,heights,channels,nProf,nHei,nChan,nPairs,nIncohInt,nBlocks=nBlocks)
+                    #tmp_spectra,tmp_cspectra,sat_spectra,sat_cspectra = self.cleanRayleigh(dataOut,jspc,jcspc,self.min_hei,self.max_hei)
+                    tmp_spectra,tmp_cspectra = self.cleanRayleigh(dataOut,jspc,jcspc,self.factor_stdv)
+                    #jspectra = tmp_spectra*len(jspc[:,0,0,0])
+                    #jcspectra = tmp_cspectra*len(jspc[:,0,0,0])
+                    dataOut.data_spc = tmp_spectra
+                    dataOut.data_cspc = tmp_cspectra
+                    dataOut.data_dc = self.buffer3
+                    dataOut.nIncohInt *= self.nIntProfiles
+                    dataOut.utctime = self.currentTime             #tiempo promediado
+                    print("Time: ",time.localtime(dataOut.utctime))
+                    # dataOut.data_spc = sat_spectra
+                    # dataOut.data_cspc = sat_cspectra
+                    self.buffer = 0
+                    self.buffer2 = 0
+                    self.buffer3 = 0
+                    return dataOut
+                def cleanRayleigh(self,dataOut,spectra,cspectra,factor_stdv):
+                    print("OP cleanRayleigh")
+                    #import matplotlib.pyplot as plt
+                    #for k in range(149):
+                    rfunc = cspectra.copy() #self.bloques
+                    val_spc = spectra*0.0 #self.bloque0*0.0
+                    val_cspc = cspectra*0.0 #self.bloques*0.0
+                    in_sat_spectra = spectra.copy()  #self.bloque0
+                    in_sat_cspectra = cspectra.copy()  #self.bloques
+                    raxs = math.ceil(math.sqrt(self.nPairs))
+                    caxs = math.ceil(self.nPairs/raxs)
+                    #print(self.hval)
+                    #print numpy.absolute(rfunc[:,0,0,14])
+                    for ih in range(self.minAltInd,self.maxAltInd):
+                        for ifreq in range(self.nFFTPoints):
+                            # fig, axs = plt.subplots(raxs, caxs)
+                            # fig2, axs2 = plt.subplots(raxs, caxs)
+                            col_ax = 0
+                            row_ax = 0
+                            for ii in range(self.nPairs):                       #PARES DE CANALES SELF y CROSS
+                                #print("ii: ",ii)
+                                if (col_ax%caxs==0 and col_ax!=0):
+                                    col_ax = 0
+                                    row_ax += 1
+                                func2clean = 10*numpy.log10(numpy.absolute(rfunc[:,ii,ifreq,ih]))           #Potencia?
+                                #print(func2clean.shape)
+                                val = (numpy.isfinite(func2clean)==True).nonzero()
+                                if len(val)>0:                                                              #limitador
+                                    min_val = numpy.around(numpy.amin(func2clean)-2) #> (-40)
+                                    if min_val <= -40 :
+                                        min_val = -40
+                                    max_val = numpy.around(numpy.amax(func2clean)+2) #< 200
+                                    if max_val >= 200 :
+                                        max_val = 200
+                                    #print min_val, max_val
+                                    step = 1
+                                    #print("Getting bins and the histogram")
+                                    x_dist = min_val + numpy.arange(1 + ((max_val-(min_val))/step))*step
+                                    y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step))
+                                    #print(len(y_dist),len(binstep[:-1]))
+                                    #print(row_ax,col_ax, " ..")
+                                    #print(self.pairsArray[ii][0],self.pairsArray[ii][1])
+                                    mean = numpy.sum(x_dist * y_dist) / numpy.sum(y_dist)
+                                    sigma = numpy.sqrt(numpy.sum(y_dist * (x_dist - mean)**2) / numpy.sum(y_dist))
+                                    parg = [numpy.amax(y_dist),mean,sigma]
+                                    gauss_fit, covariance = None, None
+                                    newY = None
+                                    try :
+                                        gauss_fit, covariance = curve_fit(fit_func, x_dist, y_dist,p0=parg)
+                                        mode = gauss_fit[1]
+                                        stdv = gauss_fit[2]
+                                        #print(" FIT OK",gauss_fit)
+                                        '''
+                                        newY = fit_func(x_dist,gauss_fit[0],gauss_fit[1],gauss_fit[2])
+                                        axs[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')
+                                        axs[row_ax,col_ax].plot(binstep[:-1],newY,color='red')
+                                        axs[row_ax,col_ax].set_title("Pair "+str(self.crosspairs[ii]))'''
+                                    except:
+                                        mode = mean
+                                        stdv = sigma
+                                        #print("FIT FAIL")
+                                    #print(mode,stdv)
+                                    #Removing echoes greater than mode + 3*stdv
+                                    #factor_stdv = 2
+                                    noval = (abs(func2clean - mode)>=(factor_stdv*stdv)).nonzero()
+                                    #noval tiene los indices que se van a remover
+                                    #print("Pair ",ii," novals: ",len(noval[0]))
+                                    if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N)
+                                        novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero()
+                                        #print(novall)
+                                        #print("   ")
+                                        cross_pairs = self.pairsArray[ii]
+                                            #Getting coherent echoes which are removed.
+                                        if len(novall[0]) > 0:
+                                            val_spc[novall[0],cross_pairs[0],ifreq,ih] = 1
+                                            val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1
+                                            val_cspc[novall[0],ii,ifreq,ih] = 1
+                                            #print("OUT NOVALL 1")
+                                            #Removing coherent from ISR data
+                                        #print(spectra[:,ii,ifreq,ih])
+                                        new_a = numpy.delete(cspectra[:,ii,ifreq,ih], noval[0])
+                                        mean_cspc = numpy.mean(new_a)
+                                        new_b = numpy.delete(spectra[:,cross_pairs[0],ifreq,ih], noval[0])
+                                        mean_spc0 = numpy.mean(new_b)
+                                        new_c = numpy.delete(spectra[:,cross_pairs[1],ifreq,ih], noval[0])
+                                        mean_spc1 = numpy.mean(new_c)
+                                        spectra[noval,cross_pairs[0],ifreq,ih] = mean_spc0
+                                        spectra[noval,cross_pairs[1],ifreq,ih] = mean_spc1
+                                        cspectra[noval,ii,ifreq,ih] = mean_cspc
+                                    '''
+                                    func2clean = 10*numpy.log10(numpy.absolute(cspectra[:,ii,ifreq,ih]))
+                                    y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step))
+                                    axs2[row_ax,col_ax].plot(binstep[:-1],newY,color='red')
+                                    axs2[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')
+                                    axs2[row_ax,col_ax].set_title("Pair "+str(self.crosspairs[ii]))
+                                    '''
+                                col_ax += 1    #contador de ploteo columnas
+                                ##print(col_ax)
+                                '''
+                            title = str(dataOut.datatime)+" nFFT: "+str(ifreq)+"   Alt: "+str(self.heights[ih])+ " km"
+                            title2 = str(dataOut.datatime)+" nFFT: "+str(ifreq)+"   Alt: "+str(self.heights[ih])+ " km  CLEANED"
+                            fig.suptitle(title)
+                            fig2.suptitle(title2)
+                            plt.show()'''
+                        '''                channels = channels
+                                        cross_pairs = cross_pairs
+                                            #print("OUT NOVALL 2")
+                                        vcross0 = (cross_pairs[0] == channels[ii]).nonzero()
+                                        vcross1 = (cross_pairs[1] == channels[ii]).nonzero()
+                                        vcross = numpy.concatenate((vcross0,vcross1),axis=None)
+                                            #print('vcros =', vcross)
+                                            #Getting coherent echoes which are removed.
+                                        if len(novall) > 0:
+                                                #val_spc[novall,ii,ifreq,ih] = 1
+                                             val_spc[ii,ifreq,ih,novall] = 1
+                                             if len(vcross) > 0:
+                                                val_cspc[vcross,ifreq,ih,novall] = 1
+                                            #Removing coherent from ISR data.
+                                        self.bloque0[ii,ifreq,ih,noval] = numpy.nan
+                                        if len(vcross) > 0:
+                                            self.bloques[vcross,ifreq,ih,noval] = numpy.nan
+                        '''
+                    print("Getting average of the spectra and cross-spectra from incoherent echoes.")
+                    out_spectra = numpy.zeros([self.nChan,self.nFFTPoints,self.nHeights], dtype=float) #+numpy.nan
+                    out_cspectra = numpy.zeros([self.nPairs,self.nFFTPoints,self.nHeights], dtype=complex) #+numpy.nan
+                    for ih in range(self.nHeights):
+                        for ifreq in range(self.nFFTPoints):
+                            for ich in range(self.nChan):
+                                tmp = spectra[:,ich,ifreq,ih]
+                                valid = (numpy.isfinite(tmp[:])==True).nonzero()
+            #                     if ich == 0 and ifreq == 0 and ih == 17 :
+            #                         print tmp
+            #                         print valid
+            #                         print len(valid[0])
+                                #print('TMP',tmp)
+                                if len(valid[0]) >0 :
+                                    out_spectra[ich,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0])
+                                #for icr in range(nPairs):
+                            for icr in range(self.nPairs):
+                                tmp = numpy.squeeze(cspectra[:,icr,ifreq,ih])
+                                valid = (numpy.isfinite(tmp)==True).nonzero()
+                                if len(valid[0]) > 0:
+                                    out_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0])
+                    '''
+                   # print('##########################################################')
+                    print("Removing fake coherent echoes (at least 4 points around the point)")
+                    val_spectra = numpy.sum(val_spc,0)
+                    val_cspectra = numpy.sum(val_cspc,0)
+                    val_spectra = self.REM_ISOLATED_POINTS(val_spectra,4)
+                    val_cspectra = self.REM_ISOLATED_POINTS(val_cspectra,4)
+                    for i in range(nChan):
+                        for j in range(nProf):
+                            for k in range(nHeights):
+                                if numpy.isfinite(val_spectra[i,j,k]) and val_spectra[i,j,k] < 1 :
+                                    val_spc[:,i,j,k] = 0.0
+                    for i in range(nPairs):
+                        for j in range(nProf):
+                            for k in range(nHeights):
+                                if numpy.isfinite(val_cspectra[i,j,k]) and val_cspectra[i,j,k] < 1 :
+                                    val_cspc[:,i,j,k] = 0.0
+                    # val_spc = numpy.reshape(val_spc, (len(spectra[:,0,0,0]),nProf*nHeights*nChan))
+                    # if numpy.isfinite(val_spectra)==str(True):
+                    #    noval = (val_spectra<1).nonzero()
+                    #    if len(noval) > 0:
+                    #        val_spc[:,noval] = 0.0
+                    #        val_spc = numpy.reshape(val_spc, (149,nChan,nProf,nHeights))
+                        #val_cspc = numpy.reshape(val_spc, (149,nChan*nHeights*nProf))
+                        #if numpy.isfinite(val_cspectra)==str(True):
+                         #   noval = (val_cspectra<1).nonzero()
+                          #  if len(noval) > 0:
+                           #     val_cspc[:,noval] = 0.0
+                            #    val_cspc = numpy.reshape(val_cspc, (149,nChan,nProf,nHeights))
+                    tmp_sat_spectra = spectra.copy()
+                    tmp_sat_spectra = tmp_sat_spectra*numpy.nan
+                    tmp_sat_cspectra = cspectra.copy()
+                    tmp_sat_cspectra = tmp_sat_cspectra*numpy.nan
+                    '''
+                    # fig = plt.figure(figsize=(6,5))
+                    # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
+                    # ax = fig.add_axes([left, bottom, width, height])
+                    # cp = ax.contour(10*numpy.log10(numpy.absolute(spectra[0,0,:,:])))
+                    # ax.clabel(cp, inline=True,fontsize=10)
+                    # plt.show()
+                    '''
+                    val = (val_spc > 0).nonzero()
+                    if len(val[0]) > 0:
+                        tmp_sat_spectra[val] = in_sat_spectra[val]
+                    val = (val_cspc > 0).nonzero()
+                    if len(val[0]) > 0:
+                        tmp_sat_cspectra[val] = in_sat_cspectra[val]
+                    print("Getting average of the spectra and cross-spectra from incoherent echoes 2")
+                    sat_spectra = numpy.zeros((nChan,nProf,nHeights), dtype=float)
+                    sat_cspectra = numpy.zeros((nPairs,nProf,nHeights), dtype=complex)
+                    for ih in range(nHeights):
+                        for ifreq in range(nProf):
+                            for ich in range(nChan):
+                                tmp = numpy.squeeze(tmp_sat_spectra[:,ich,ifreq,ih])
+                                valid = (numpy.isfinite(tmp)).nonzero()
+                                if len(valid[0]) > 0:
+                                    sat_spectra[ich,ifreq,ih] = numpy.nansum(tmp)/len(valid[0])
+                            for icr in range(nPairs):
+                                tmp = numpy.squeeze(tmp_sat_cspectra[:,icr,ifreq,ih])
+                                valid = (numpy.isfinite(tmp)).nonzero()
+                                if len(valid[0]) > 0:
+                                    sat_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)/len(valid[0])
+                    '''
+                        #self.__dataReady= True
+                        #sat_spectra, sat_cspectra= sat_spectra, sat_cspectra
+                    #if not self.__dataReady:
+                        #return None, None
+                    #return out_spectra, out_cspectra ,sat_spectra,sat_cspectra
+                    return out_spectra, out_cspectra
+                def REM_ISOLATED_POINTS(self,array,rth):
+            #         import matplotlib.pyplot as plt
+                    if rth == None :
+                        rth = 4
+                    print("REM ISO")
+                    num_prof = len(array[0,:,0])
+                    num_hei = len(array[0,0,:])
+                    n2d = len(array[:,0,0])
+                    for ii in range(n2d) :
+                        #print ii,n2d
+                        tmp = array[ii,:,:]
+                        #print tmp.shape, array[ii,101,:],array[ii,102,:]
+                      # fig = plt.figure(figsize=(6,5))
+                      # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
+                      # ax = fig.add_axes([left, bottom, width, height])
+                      # x = range(num_prof)
+                      # y = range(num_hei)
+                      # cp = ax.contour(y,x,tmp)
+                      # ax.clabel(cp, inline=True,fontsize=10)
+                      # plt.show()
+                        #indxs = WHERE(FINITE(tmp) AND tmp GT 0,cindxs)
+                        tmp = numpy.reshape(tmp,num_prof*num_hei)
+                        indxs1 = (numpy.isfinite(tmp)==True).nonzero()
+                        indxs2 = (tmp > 0).nonzero()
+                        indxs1 = (indxs1[0])
+                        indxs2 = indxs2[0]
+                        #indxs1 = numpy.array(indxs1[0])
+                        #indxs2 = numpy.array(indxs2[0])
+                        indxs = None
+                        #print indxs1 , indxs2
+                        for iv in range(len(indxs2)):
+                            indv = numpy.array((indxs1 == indxs2[iv]).nonzero())
+                            #print len(indxs2), indv
+                            if len(indv[0]) > 0  :
+                                indxs =  numpy.concatenate((indxs,indxs2[iv]), axis=None)
+              #           print indxs
+                        indxs = indxs[1:]
+                        #print(indxs, len(indxs))
+                        if len(indxs) < 4 :
+                            array[ii,:,:] = 0.
+                            return
+                        xpos = numpy.mod(indxs ,num_hei)
+                        ypos = (indxs / num_hei)
+                        sx = numpy.argsort(xpos) # Ordering respect to "x" (time)
+                        #print sx
+                        xpos = xpos[sx]
+                        ypos = ypos[sx]
+                 # *********************************** Cleaning isolated points **********************************
+                        ic = 0
+                        while True :
+                            r = numpy.sqrt(list(numpy.power((xpos[ic]-xpos),2)+ numpy.power((ypos[ic]-ypos),2)))
+                            #no_coh = WHERE(FINITE(r) AND (r LE rth),cno_coh)
+                            #plt.plot(r)
+                            #plt.show()
+                            no_coh1 = (numpy.isfinite(r)==True).nonzero()
+                            no_coh2 = (r <= rth).nonzero()
+                            #print r, no_coh1, no_coh2
+                            no_coh1 = numpy.array(no_coh1[0])
+                            no_coh2 = numpy.array(no_coh2[0])
+                            no_coh = None
+                            #print valid1 , valid2
+                            for iv in range(len(no_coh2)):
+                                indv = numpy.array((no_coh1 == no_coh2[iv]).nonzero())
+                                if len(indv[0]) > 0  :
+                                    no_coh =  numpy.concatenate((no_coh,no_coh2[iv]), axis=None)
+                            no_coh = no_coh[1:]
+                            #print len(no_coh), no_coh
+                            if len(no_coh) < 4 :
+                                #print xpos[ic], ypos[ic], ic
+                #                plt.plot(r)
+                #                plt.show()
+                                xpos[ic] = numpy.nan
+                                ypos[ic] = numpy.nan
+                            ic = ic + 1
+                            if  (ic == len(indxs)) :
+                                break
+                            #print( xpos, ypos)
+                        indxs = (numpy.isfinite(list(xpos))==True).nonzero()
+                        #print indxs[0]
+                        if len(indxs[0]) < 4 :
+                            array[ii,:,:] = 0.
+                            return
+                        xpos = xpos[indxs[0]]
+                        ypos = ypos[indxs[0]]
+                        for i in range(0,len(ypos)):
+                            ypos[i]=int(ypos[i])
+                        junk = tmp
+                        tmp = junk*0.0
+                        tmp[list(xpos + (ypos*num_hei))] = junk[list(xpos + (ypos*num_hei))]
+                        array[ii,:,:] = numpy.reshape(tmp,(num_prof,num_hei))
+                        #print array.shape
+                        #tmp = numpy.reshape(tmp,(num_prof,num_hei))
+                        #print tmp.shape
+                        # fig = plt.figure(figsize=(6,5))
+                        # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
+                        # ax = fig.add_axes([left, bottom, width, height])
+                        # x = range(num_prof)
+                        # y = range(num_hei)
+                        # cp = ax.contour(y,x,array[ii,:,:])
+                        # ax.clabel(cp, inline=True,fontsize=10)
+                        # plt.show()
+                    return array
             class removeInterference(Operation):
                 def removeInterference2(self):
                     cspc = self.dataOut.data_cspc
                     spc = self.dataOut.data_spc
                     Heights = numpy.arange(cspc.shape[2])
                     realCspc = numpy.abs(cspc)
                     for i in range(cspc.shape[0]):
                         LinePower= numpy.sum(realCspc[i], axis=0)
                         Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)]
                         SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ]
                         InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 )
                         InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)]
                         InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)]
                         InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) )
                         #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax]))
                         if len(InterferenceRange)<int(cspc.shape[1]*0.3):
                             cspc[i,InterferenceRange,:] = numpy.NaN
                     self.dataOut.data_cspc = cspc
                 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 is None:
                         count_hei = int(num_hei / 2)
                         hei_interf = numpy.asmatrix(list(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 = list(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(list(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[list(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 / numpy.sqrt(num_incoh))
                         noiseid = noiseid[0]
                         cnoiseid = noiseid.size
                         interfid = numpy.where(
                             jspc_interf > tmp_noise / numpy.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 / numpy.sqrt(num_incoh))).nonzero()
                                 cind = len(ind)
                                 if (cind > 0):
                                     jspectra[ich, interfid[ip], ind] = tmp_noise * \
                                         (1 + (numpy.random.uniform(cind) - 0.5) /
                                          numpy.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(list(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 / numpy.sqrt(num_incoh))).nonzero()
                         jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \
                             (1 - 1 / numpy.sqrt(num_incoh))
                     # Remocion de Interferencia en el Cross Spectra
                     if jcspectra is None:
                         return jspectra, jcspectra
                     num_pairs = int(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[list(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 = int(numpy.median(numpy.real(
                             junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :])))
                         median_imag = int(numpy.median(numpy.imag(
                             junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :])))
                         comp_mask_prof = [int(e) for e in comp_mask_prof]
                         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(list(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 run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1):
                     self.dataOut = dataOut
                     if mode == 1:
                         self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None)
                     elif mode == 2:
                         self.removeInterference2()
                     return self.dataOut
             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)
                 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 = 0
                     self.__buffer_cspc = 0
                     self.__buffer_dc = 0
                     self.__profIndex = 0
                     self.__dataReady = False
                     self.__byTime = False
                     if n is None and timeInterval is None:
                         raise ValueError("n or timeInterval should be specified ...")
                     if n is not None:
                         self.n = int(n)
                     else:
                         self.__integrationtime = int(timeInterval)
                         self.n = None
                         self.__byTime = True
                 def putData(self, data_spc, data_cspc, data_dc):
                     """
                     Add a profile to the __buffer_spc and increase in one the __profileIndex
                     """
                     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
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     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
                 def byProfiles(self, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     self.putData(*args)
                     if self.__profIndex == self.n:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         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
                     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.__profIndex == 0:
                         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)
                     if not self.__dataReady:
                         return None, None, None, None
                     return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
                     if n == 1:
                         return dataOut
                     dataOut.flagNoData = True
                     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)
                     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.flagNoData = False
                     return dataOut
             class dopplerFlip(Operation):
                 def run(self, dataOut):
                     # arreglo 1: (num_chan, num_profiles, num_heights)
                     self.dataOut = dataOut
                     # JULIA-oblicua, indice 2
                     # arreglo 2: (num_profiles, num_heights)
                     jspectra = self.dataOut.data_spc[2]
                     jspectra_tmp = numpy.zeros(jspectra.shape)
                     num_profiles = jspectra.shape[0]
                     freq_dc = int(num_profiles / 2)
                     # Flip con for
                     for j in range(num_profiles):
                         jspectra_tmp[num_profiles-j-1]= jspectra[j]
                     # Intercambio perfil de DC con perfil inmediato anterior
                     jspectra_tmp[freq_dc-1]= jspectra[freq_dc-1]
                     jspectra_tmp[freq_dc]= jspectra[freq_dc]
                     # canal modificado es re-escrito en el arreglo de canales
                     self.dataOut.data_spc[2] = jspectra_tmp
                     return self.dataOut

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