schain Commit - r276:98940ac0422d · Jicamarca Repository

Modificaciones del tipo de dato

Daniel Valdez -

r276:98940ac0422d

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r276:98940ac0422d

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schainpy/model/jrodataIO.py +4 -3

             '''
             $Author: murco $
             $Id: JRODataIO.py 169 2012-11-19 21:57:03Z murco $
             '''
             import os, sys
             import glob
             import time
             import numpy
             import fnmatch
             import time, datetime
             from jrodata import *
             from jroheaderIO import *
             from jroprocessing import *
             LOCALTIME = -18000
             def isNumber(str):
                 """
                 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( str )
                     return True
                 except:
                     return False
             def isThisFileinRange(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:
                     raise IOError, "The file %s can't be opened" %(filename)
                 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 isFileinThisTime(filename, 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)
                     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:
                     raise IOError, "The file %s can't be opened" %(filename)
                 basicHeaderObj = BasicHeader(LOCALTIME)
                 sts = basicHeaderObj.read(fp)
                 fp.close()
                 thisTime = basicHeaderObj.datatime.time()
                 if not(sts):
                     print "Skipping the file %s because it has not a valid header" %(filename)
                     return 0
                 if not ((startTime <= thisTime) and (endTime > thisTime)):
                     return 0
                 return 1
             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 file in fileList:
                     try:
                         year = int(file[1:5])
                         doy  = int(file[5:8])
                     except:
                         continue
                     if (os.path.splitext(file)[-1].lower() != ext.lower()):
                         continue
                     validFilelist.append(file)
                 if validFilelist:
                     validFilelist = sorted( validFilelist, key=str.lower )
                     return validFilelist[-1]
                 return None
             def checkForRealPath(path, year, doy, set, ext):
                 """
                 Por ser Linux Case Sensitive entonces checkForRealPath encuentra el nombre correcto de un path,
                 Prueba por varias combinaciones de nombres entre mayusculas y minusculas para determinar
                 el path exacto de un determinado file.
                 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:
                     Si encuentra la cobinacion adecuada devuelve el path completo y el nombre del file
                     caso contrario devuelve None como path y el la ultima combinacion de nombre en mayusculas
                     para el filename
                 """
                 fullfilename = None
                 find_flag = False
                 filename = None
                 prefixDirList = [None,'d','D']
                 if ext.lower() == ".r": #voltage
                     prefixFileList = ['d','D']
                 elif ext.lower() == ".pdata": #spectra
                     prefixFileList = ['p','P']
                 else:
                     return None, filename
                 #barrido por las combinaciones posibles
                 for prefixDir in prefixDirList:
                     thispath = path
                     if prefixDir != None:
                         #formo el nombre del directorio xYYYYDDD (x=d o x=D)
                         thispath = os.path.join(path, "%s%04d%03d" % ( prefixDir, year, doy ))
                     for prefixFile in prefixFileList: #barrido por las dos combinaciones posibles de "D"
                         filename = "%s%04d%03d%03d%s" % ( prefixFile, year, doy, set, ext ) #formo el nombre del file xYYYYDDDSSS.ext
                         fullfilename = os.path.join( thispath, filename ) #formo el path completo
                         if os.path.exists( fullfilename ): #verifico que exista
                             find_flag = True
                             break
                     if find_flag:
                         break
                 if not(find_flag):
                     return None, filename
                 return fullfilename, filename
             class JRODataIO:
                 c = 3E8
                 isConfig = False
                 basicHeaderObj = BasicHeader(LOCALTIME)
                 systemHeaderObj = SystemHeader()
                 radarControllerHeaderObj = RadarControllerHeader()
                 processingHeaderObj = ProcessingHeader()
                 online = 0
                 dtype = None
                 pathList = []
                 filenameList = []
                 filename = None
                 ext = None
                 flagIsNewFile = 1
                 flagTimeBlock = 0
                 flagIsNewBlock = 0
                 fp = None
                 firstHeaderSize = 0
                 basicHeaderSize = 24
                 versionFile = 1103
                 fileSize = None
                 ippSeconds = None
                 fileSizeByHeader = None
                 fileIndex = None
                 profileIndex = None
                 blockIndex = None
                 nTotalBlocks = None
                 maxTimeStep = 30
                 lastUTTime = None
                 datablock = None
                 dataOut = None
                 blocksize = None
                 def __init__(self):
                     raise ValueError, "Not implemented"
                 def run(self):
                     raise ValueError, "Not implemented"
                 def getOutput(self):
                     return self.dataOut
             class JRODataReader(JRODataIO, ProcessingUnit):
                 nReadBlocks = 0
                 delay  = 10   #number of seconds waiting a new file
                 nTries  = 3  #quantity tries
                 nFiles = 3   #number of files for searching
                 flagNoMoreFiles = 0
                 def __init__(self):
                     """
                     """
                     raise ValueError, "This method has not been implemented"
                 def createObjByDefault(self):
                     """
                     """
                     raise ValueError, "This method has not been implemented"
                 def getBlockDimension(self):
                     raise ValueError, "No implemented"
                 def __searchFilesOffLine(self,
                                         path,
                                         startDate,
                                         endDate,
                                         startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),
                                         set=None,
                                         expLabel='',
                                         ext='.r',
                                         walk=True):
                     pathList = []
                     if not walk:
                         pathList.append(path)
                     else:
                         dirList = []
                         for thisPath in os.listdir(path):
                             if os.path.isdir(os.path.join(path,thisPath)):
                                 dirList.append(thisPath)
                         if not(dirList):
                             return None, None
                         thisDate = startDate
                         while(thisDate <= endDate):
                             year = thisDate.timetuple().tm_year
                             doy = thisDate.timetuple().tm_yday
                             match = fnmatch.filter(dirList, '?' + '%4.4d%3.3d' % (year,doy))
                             if len(match) == 0:
                                 thisDate += datetime.timedelta(1)
                                 continue
                             pathList.append(os.path.join(path,match[0],expLabel))
                             thisDate += datetime.timedelta(1)
                     if pathList == []:
                         print "Any folder was found for the date range: %s-%s" %(startDate, endDate)
                         return None, None
                     print "%d folder(s) was(were) found for the date range: %s-%s" %(len(pathList), startDate, endDate)
                     filenameList = []
                     for thisPath in pathList:
                         fileList = glob.glob1(thisPath, "*%s" %ext)
                         fileList.sort()
                         for file in fileList:
                             filename = os.path.join(thisPath,file)
                             if isFileinThisTime(filename, startTime, endTime):
                                 filenameList.append(filename)
                     if not(filenameList):
                         print "Any file was found for the time range %s - %s" %(startTime, endTime)
                         return None, None
                     print "%d file(s) was(were) found for the time range: %s - %s" %(len(filenameList), startTime, endTime)
                     self.filenameList = filenameList
                     return pathList, filenameList
                 def __searchFilesOnLine(self, path, expLabel = "", ext = None, walk=True):
                     """
                     Busca el ultimo archivo de la ultima carpeta (determinada o no por startDateTime) y
                     devuelve el archivo encontrado ademas de otros datos.
                     Input:
                         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:
                         directory   :    eL directorio donde esta el file encontrado
                         filename    :    el ultimo file de una determinada carpeta
                         year        :    el anho
                         doy         :    el numero de dia del anho
                         set         :    el set del archivo
                     """
                     dirList = []
                     if walk:
                         #Filtra solo los directorios
                         for thisPath in os.listdir(path):
                             if os.path.isdir(os.path.join(path, thisPath)):
                                 dirList.append(thisPath)
                         if not(dirList):
                             return None, None, None, None, None
                         dirList = sorted( dirList, key=str.lower )
                         doypath = dirList[-1]
                         fullpath = os.path.join(path, doypath, expLabel)
                     else:
                         fullpath = path
                     filename = getlastFileFromPath(fullpath, ext)
                     if not(filename):
                         return None, None, None, None, None
                     if not(self.__verifyFile(os.path.join(fullpath, filename))):
                         return None, None, None, None, None
                     year = int( filename[1:5] )
                     doy  = int( filename[5:8] )
                     set  = int( filename[8:11] )
                     return fullpath, filename, year, doy, set
                 def __setNextFileOffline(self):
                     idFile = self.fileIndex
                     while (True):
                         idFile += 1
                         if not(idFile < len(self.filenameList)):
                             self.flagNoMoreFiles = 1
                             print "No more Files"
                             return 0
                         filename = self.filenameList[idFile]
                         if not(self.__verifyFile(filename)):
                             continue
                         fileSize = os.path.getsize(filename)
                         fp = open(filename,'rb')
                         break
                     self.flagIsNewFile = 1
                     self.fileIndex = idFile
                     self.filename = filename
                     self.fileSize = fileSize
                     self.fp = fp
                     print "Setting the file: %s"%self.filename
                     return 1
                 def __setNextFileOnline(self):
                     """
                     Busca el siguiente file que tenga suficiente data para ser leida, dentro de un folder especifico, si
                     no encuentra un file valido espera un tiempo determinado y luego busca en los posibles n files
                     siguientes.
                     Affected:
                         self.flagIsNewFile
                         self.filename
                         self.fileSize
                         self.fp
                         self.set
                         self.flagNoMoreFiles
                     Return:
 : si luego de una busqueda del siguiente file valido este no pudo ser encontrado
 : si el file fue abierto con exito y esta listo a ser leido
                     Excepciones:
                         Si un determinado file no puede ser abierto
                     """
                     nFiles = 0
                     fileOk_flag = False
                     firstTime_flag = True
                     self.set += 1
                     #busca el 1er file disponible
                     fullfilename, filename = checkForRealPath( self.path, self.year, self.doy, self.set, self.ext )
                     if fullfilename:
                         if self.__verifyFile(fullfilename, False):
                             fileOk_flag = True
                     #si no encuentra un file entonces espera y vuelve a buscar
                     if not(fileOk_flag):
                         for nFiles in range(self.nFiles+1): #busco en los siguientes self.nFiles+1 files posibles
                             if firstTime_flag: #si es la 1era vez entonces hace el for self.nTries veces
                                 tries = self.nTries
                             else:
                                 tries = 1 #si no es la 1era vez entonces solo lo hace una vez
                             for nTries in range( tries ):
                                 if firstTime_flag:
                                     print "\tWaiting %0.2f sec for the file \"%s\" , try %03d ..." % ( self.delay, filename, nTries+1 )
                                     time.sleep( self.delay )
                                 else:
                                     print "\tSearching next \"%s%04d%03d%03d%s\" file ..." % (self.optchar, self.year, self.doy, self.set, self.ext)
                                 fullfilename, filename = checkForRealPath( self.path, self.year, self.doy, self.set, self.ext )
                                 if fullfilename:
                                     if self.__verifyFile(fullfilename):
                                         fileOk_flag = True
                                         break
                             if fileOk_flag:
                                 break
                             firstTime_flag = False
                             print "\tSkipping the file \"%s\" due to this file doesn't exist" % filename
                             self.set += 1
                             if nFiles == (self.nFiles-1): #si no encuentro el file buscado cambio de carpeta y busco en la siguiente carpeta
                                 self.set = 0
                                 self.doy += 1
                     if fileOk_flag:
                         self.fileSize = os.path.getsize( fullfilename )
                         self.filename = fullfilename
                         self.flagIsNewFile = 1
                         if self.fp != None: self.fp.close()
                         self.fp = open(fullfilename, 'rb')
                         self.flagNoMoreFiles = 0
                         print 'Setting the file: %s' % fullfilename
                     else:
                         self.fileSize = 0
                         self.filename = None
                         self.flagIsNewFile = 0
                         self.fp = None
                         self.flagNoMoreFiles = 1
                         print 'No more Files'
                     return fileOk_flag
                 def setNextFile(self):
                     if self.fp != None:
                         self.fp.close()
                     if self.online:
                         newFile = self.__setNextFileOnline()
                     else:
                         newFile = self.__setNextFileOffline()
                     if not(newFile):
                         return 0
                     self.__readFirstHeader()
                     self.nReadBlocks = 0
                     return 1
                 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.__rdBasicHeader()
                             return 1
                         print "\tWaiting %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:
                         return 1
                     self.lastUTTime = self.basicHeaderObj.utc
                     currentSize = self.fileSize - self.fp.tell()
                     neededSize = self.processingHeaderObj.blockSize + self.basicHeaderSize
                     if (currentSize >= neededSize):
                         self.__rdBasicHeader()
                         return 1
                     if self.__waitNewBlock():
                         return 1
                     if not(self.setNextFile()):
                         return 0
                     deltaTime = self.basicHeaderObj.utc - self.lastUTTime #
                     self.flagTimeBlock = 0
                     if deltaTime > self.maxTimeStep:
                         self.flagTimeBlock = 1
                     return 1
                 def readNextBlock(self):
                     if not(self.__setNewBlock()):
                         return 0
                     if not(self.readBlock()):
                         return 0
                     return 1
                 def __rdProcessingHeader(self, fp=None):
                     if fp == None:
                         fp = self.fp
                     self.processingHeaderObj.read(fp)
                 def __rdRadarControllerHeader(self, fp=None):
                     if fp == None:
                         fp = self.fp
                     self.radarControllerHeaderObj.read(fp)
                 def __rdSystemHeader(self, fp=None):
                     if fp == None:
                         fp = self.fp
                     self.systemHeaderObj.read(fp)
                 def __rdBasicHeader(self, fp=None):
                     if fp == None:
                         fp = self.fp
                     self.basicHeaderObj.read(fp)
                 def __readFirstHeader(self):
                     self.__rdBasicHeader()
                     self.__rdSystemHeader()
                     self.__rdRadarControllerHeader()
                     self.__rdProcessingHeader()
                     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, msgFlag=True):
                     msg = None
                     try:
                         fp = open(filename, 'rb')
                         currentPosition = fp.tell()
                     except:
                         if msgFlag:
                             print "The file %s can't be opened" % (filename)
                         return False
                     neededSize = self.processingHeaderObj.blockSize + self.firstHeaderSize
                     if neededSize == 0:
                         basicHeaderObj = BasicHeader(LOCALTIME)
                         systemHeaderObj = SystemHeader()
                         radarControllerHeaderObj = RadarControllerHeader()
                         processingHeaderObj = ProcessingHeader()
                         try:
                             if not( basicHeaderObj.read(fp) ): raise IOError
                             if not( systemHeaderObj.read(fp) ): raise IOError
                             if not( radarControllerHeaderObj.read(fp) ): raise IOError
                             if not( processingHeaderObj.read(fp) ): raise IOError
                             data_type = int(numpy.log2((processingHeaderObj.processFlags & PROCFLAG.DATATYPE_MASK))-numpy.log2(PROCFLAG.DATATYPE_CHAR))
                             neededSize = processingHeaderObj.blockSize + basicHeaderObj.size
                         except:
                             if msgFlag:
                                 print "\tThe file %s is empty or it hasn't enough data" % filename
                             fp.close()
                             return False
                     else:
                         msg = "\tSkipping the file %s due to it hasn't enough data" %filename
                     fp.close()
                     fileSize = os.path.getsize(filename)
                     currentSize = fileSize - currentPosition
                     if currentSize < neededSize:
                         if msgFlag and (msg != None):
                             print msg #print"\tSkipping the file %s due to it hasn't enough data" %filename
                         return False
                     return True
                 def setup(self,
                             path=None,
                             startDate=None,
                             endDate=None,
                             startTime=datetime.time(0,0,0),
                             endTime=datetime.time(23,59,59),
                             set=0,
                             expLabel = "",
                             ext = None,
                             online = False,
                             delay = 60,
                             walk = True):
                     if path == None:
                         raise ValueError, "The path is not valid"
                     if ext == None:
                         ext = self.ext
                     if online:
                         print "Searching files in online mode..."
                         for nTries in range( self.nTries ):
                             fullpath, file, year, doy, set = self.__searchFilesOnLine(path=path, expLabel=expLabel, ext=ext, walk=walk)
                             if fullpath:
                                 break
                             print '\tWaiting %0.2f sec for an valid file in %s: try %02d ...' % (self.delay, path, nTries+1)
                             time.sleep( self.delay )
                         if not(fullpath):
                             print "There 'isn't valied files in %s" % path
                             return None
                         self.year = year
                         self.doy  = doy
                         self.set  = set - 1
                         self.path = path
                     else:
                         print "Searching files in offline mode ..."
                         pathList, filenameList = self.__searchFilesOffLine(path, startDate=startDate, endDate=endDate,
                                                                            startTime=startTime, endTime=endTime,
                                                                            set=set, expLabel=expLabel, ext=ext,
                                                                            walk=walk)
                         if not(pathList):
                             print "No *%s files into the folder %s \nfor the range: %s - %s"%(ext, path,
                                                                     datetime.datetime.combine(startDate,startTime).ctime(),
                                                                     datetime.datetime.combine(endDate,endTime).ctime())
                             sys.exit(-1)
                         self.fileIndex = -1
                         self.pathList = pathList
                         self.filenameList = filenameList
                     self.online = online
                     self.delay = delay
                     ext = ext.lower()
                     self.ext = ext
                     if not(self.setNextFile()):
                         if (startDate!=None) and (endDate!=None):
                             print "No files in range: %s - %s" %(datetime.datetime.combine(startDate,startTime).ctime(), datetime.datetime.combine(endDate,endTime).ctime())
                         elif startDate != None:
                             print "No files in range: %s" %(datetime.datetime.combine(startDate,startTime).ctime())
                         else:
                             print "No files"
                         sys.exit(-1)
             #        self.updateDataHeader()
                     return self.dataOut
                 def getData():
                     raise ValueError, "This method has not been implemented"
                 def hasNotDataInBuffer():
                     raise ValueError, "This method has not been implemented"
                 def readBlock():
                     raise ValueError, "This method has not been implemented"
                 def isEndProcess(self):
                     return self.flagNoMoreFiles
                 def printReadBlocks(self):
                     print "Number of read blocks per file %04d" %self.nReadBlocks
                 def printTotalBlocks(self):
                     print "Number of read blocks %04d" %self.nTotalBlocks
                 def printNumberOfBlock(self):
                     if self.flagIsNewBlock:
                         print "Block No. %04d, Total blocks %04d" %(self.basicHeaderObj.dataBlock, self.nTotalBlocks)
                 def printInfo(self):
                     print self.basicHeaderObj.printInfo()
                     print self.systemHeaderObj.printInfo()
                     print self.radarControllerHeaderObj.printInfo()
                     print self.processingHeaderObj.printInfo()
                 def run(self, **kwargs):
                     if not(self.isConfig):
             #            self.dataOut = dataOut
                         self.setup(**kwargs)
                         self.isConfig = True
                     self.getData()
             class JRODataWriter(JRODataIO, Operation):
                 """
                 Esta clase permite escribir datos a archivos procesados (.r o ,pdata). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 blockIndex = 0
                 path = None
                 setFile = None
                 profilesPerBlock = None
                 blocksPerFile = None
                 nWriteBlocks = 0
                 def __init__(self, dataOut=None):
                     raise ValueError, "Not implemented"
                 def hasAllDataInBuffer(self):
                     raise ValueError, "Not implemented"
                 def setBlockDimension(self):
                     raise ValueError, "Not implemented"
                 def writeBlock(self):
                     raise ValueError, "No implemented"
                 def putData(self):
                     raise ValueError, "No implemented"
                 def getDataHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.basicHeaderObj
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.processingHeaderObj self.
                     Return:
                         None
                     """
                     raise ValueError, "No implemented"
                 def getBasicHeader(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 = 0
                     self.basicHeaderObj.dstFlag = 0
                     self.basicHeaderObj.errorCount = 0
                 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)
                     self.dtype = self.dataOut.dtype
                 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()
                     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()
                     timeTuple = time.localtime( self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         self.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] ):
                                 self.setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 self.setFile = -1
                         else:
                             self.setFile = -1 #inicializo mi contador de seteo
                     setFile = self.setFile
                     setFile += 1
                     file = '%s%4.4d%3.3d%3.3d%s' % (self.optchar,
                                                     timeTuple.tm_year,
                                                     timeTuple.tm_yday,
                                                     setFile,
                                                     ext )
                     filename = os.path.join( path, subfolder, file )
                     fp = open( filename,'wb' )
                     self.blockIndex = 0
                     #guardando atributos
                     self.filename = filename
                     self.subfolder = subfolder
                     self.fp = fp
                     self.setFile = setFile
                     self.flagIsNewFile = 1
                     self.getDataHeader()
                     print 'Writing the file: %s'%self.filename
                     self.__writeFirstHeader()
                     return 1
                 def setup(self, dataOut, path, blocksPerFile, profilesPerBlock=None, set=0, ext=None):
                     """
                     Setea el tipo de formato en la cual sera guardada la data y escribe el First Header
                     Inputs:
                         path      :    el path destino en el cual se escribiran los files a crear
                         format    :    formato en el cual sera salvado un file
                         set       :    el setebo del file
                     Return:
 :    Si no realizo un buen seteo
 :    Si realizo un buen seteo
                     """
                     if ext == None:
                         ext = self.ext
                     ext = ext.lower()
                     self.ext = ext
                     self.path = path
                     self.setFile = set - 1
                     self.blocksPerFile = blocksPerFile
                     self.profilesPerBlock = profilesPerBlock
                     self.dataOut = dataOut
                     if not(self.setNextFile()):
                         print "There isn't a next file"
                         return 0
                     self.setBlockDimension()
                     return 1
                 def run(self, dataOut, **kwargs):
                     if not(self.isConfig):
                         self.setup(dataOut, **kwargs)
                         self.isConfig = True
                     self.putData()
             class VoltageReader(JRODataReader):
                 """
                 Esta clase permite leer datos de voltage desde archivos en formato rawdata (.r). La lectura
                 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones:
                 perfiles*alturas*canales) son almacenados en la variable "buffer".
                                          perfiles * alturas * canales
                 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
                 RadarControllerHeader y Voltage. Los tres primeros se usan para almacenar informacion de la
                 cabecera de datos (metadata), y el cuarto (Voltage) para obtener y almacenar un perfil de
                 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
                 Example:
                     dpath = "/home/myuser/data"
                     startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
                     endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
                     readerObj = VoltageReader()
                     readerObj.setup(dpath, startTime, endTime)
                     while(True):
                         #to get one profile
                         profile =  readerObj.getData()
                         #print the profile
                         print profile
                         #If you want to see all datablock
                         print readerObj.datablock
                         if readerObj.flagNoMoreFiles:
                             break
                 """
                 ext = ".r"
                 optchar = "D"
                 dataOut = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageReader para la lectura de datos de voltage.
                     Input:
                         dataOut    :    Objeto de la clase Voltage. Este objeto sera utilizado para
                                           almacenar un perfil de datos cada vez que se haga un requerimiento
                                           (getData). El perfil sera obtenido a partir del buffer de datos,
                                           si el buffer esta vacio se hara un nuevo proceso de lectura de un
                                           bloque de datos.
                                           Si este parametro no es pasado se creara uno internamente.
                     Variables afectadas:
                         self.dataOut
                     Return:
                         None
                     """
                     self.isConfig = False
                     self.datablock = None
                     self.utc = 0
                     self.ext = ".r"
                     self.optchar = "D"
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                     self.online = 0
                     self.fp = None
                     self.idFile = None
                     self.dtype = None
                     self.fileSizeByHeader = None
                     self.filenameList = []
                     self.filename = None
                     self.fileSize = None
                     self.firstHeaderSize = 0
                     self.basicHeaderSize = 24
                     self.pathList = []
                     self.filenameList = []
                     self.lastUTTime = 0
                     self.maxTimeStep = 30
                     self.flagNoMoreFiles = 0
                     self.set = 0
                     self.path = None
                     self.profileIndex = 9999
                     self.delay  = 3   #seconds
                     self.nTries  = 3  #quantity tries
                     self.nFiles = 3   #number of files for searching
                     self.nReadBlocks = 0
                     self.flagIsNewFile = 1
                     self.ippSeconds = 0
                     self.flagTimeBlock = 0
                     self.flagIsNewBlock = 0
                     self.nTotalBlocks = 0
                     self.blocksize = 0
                     self.dataOut = self.createObjByDefault()
                 def createObjByDefault(self):
                     dataObj = Voltage()
                     return dataObj
                 def __hasNotDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def getBlockDimension(self):
                     """
                     Obtiene la cantidad de puntos a leer por cada bloque de datos
                     Affected:
                         self.blocksize
                     Return:
                         None
                     """
                     pts2read = self.processingHeaderObj.profilesPerBlock * self.processingHeaderObj.nHeights * self.systemHeaderObj.nChannels
                     self.blocksize = pts2read
                 def readBlock(self):
                     """
                     readBlock lee el bloque de datos desde la posicion actual del puntero del archivo
                     (self.fp) y actualiza todos los parametros relacionados al bloque de datos
                     (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
                     es seteado a 0
                     Inputs:
                         None
                     Return:
                         None
                     Affected:
                         self.profileIndex
                         self.datablock
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                     Exceptions:
                         Si un bloque leido no es un bloque valido
                     """
                     junk = numpy.fromfile( self.fp, self.dtype, self.blocksize )
                     try:
                         junk = junk.reshape( (self.processingHeaderObj.profilesPerBlock, self.processingHeaderObj.nHeights, self.systemHeaderObj.nChannels) )
                     except:
                         print "The read block (%3d) has not enough data" %self.nReadBlocks
                         return 0
                     junk = numpy.transpose(junk, (2,0,1))
                     self.datablock = junk['real'] + junk['imag']*1j
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def getData(self):
                     """
                     getData obtiene una unidad de datos del buffer de lectura y la copia a la clase "Voltage"
                     con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de
                     lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock"
                     Ademas incrementa el contador del buffer en 1.
                     Return:
                         data    :    retorna un perfil de voltages (alturas * canales) copiados desde el
                                      buffer. Si no hay mas archivos a leer retorna None.
                     Variables afectadas:
                         self.dataOut
                         self.profileIndex
                     Affected:
                         self.dataOut
                         self.profileIndex
                         self.flagTimeBlock
                         self.flagIsNewBlock
                     """
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagTimeBlock = 0
                     self.flagIsNewBlock = 0
                     if self.__hasNotDataInBuffer():
                         if not( self.readNextBlock() ):
                             return 0
-                        self.dataOut.dtype = numpy.dtype([('real','<f8'),('imag','<f8')]) #self.dtype
+                        self.dataOut.dtype = self.dtype
                         self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock
                         xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight
                         self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
                         self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
                         self.dataOut.flagTimeBlock = self.flagTimeBlock
                         self.dataOut.ippSeconds = self.ippSeconds
                         self.dataOut.timeInterval = self.ippSeconds * self.processingHeaderObj.nCohInt
                         self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
                         self.dataOut.flagShiftFFT = False
                         if self.radarControllerHeaderObj.code != None:
                             self.dataOut.nCode = self.radarControllerHeaderObj.nCode
                             self.dataOut.nBaud = self.radarControllerHeaderObj.nBaud
                             self.dataOut.code = self.radarControllerHeaderObj.code
                         self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
                         self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
                         self.dataOut.flagDecodeData = False #asumo q la data no esta decodificada
                         self.dataOut.flagDeflipData = False #asumo q la data no esta sin flip
                         self.dataOut.flagShiftFFT = False
             #            self.updateDataHeader()
                     #data es un numpy array de 3 dmensiones (perfiles, alturas y canales)
                     if self.datablock == None:
                         self.dataOut.flagNoData = True
                         return 0
                     self.dataOut.data = self.datablock[:,self.profileIndex,:]
                     self.dataOut.utctime = self.basicHeaderObj.utc + self.basicHeaderObj.miliSecond/1000. + self.profileIndex * self.ippSeconds
                     self.profileIndex += 1
                     self.dataOut.flagNoData = False
             #        print self.profileIndex, self.dataOut.utctime
             #        if self.profileIndex == 800:
             #            a=1
                     return self.dataOut.data
             class VoltageWriter(JRODataWriter):
                 """
                 Esta clase permite escribir datos de voltajes a archivos procesados (.r). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 ext = ".r"
                 optchar = "D"
                 shapeBuffer = None
                 def __init__(self):
                     """
                     Inicializador de la clase VoltageWriter para la escritura de datos de espectros.
                     Affected:
                         self.dataOut
                     Return: None
                     """
                     self.nTotalBlocks = 0
                     self.profileIndex = 0
                     self.isConfig = False
                     self.fp = None
                     self.flagIsNewFile = 1
                     self.nTotalBlocks = 0
                     self.flagIsNewBlock = 0
                     self.setFile = None
                     self.dtype = None
                     self.path = None
                     self.filename = None
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                 def hasAllDataInBuffer(self):
                     if self.profileIndex >= self.processingHeaderObj.profilesPerBlock:
                         return 1
                     return 0
                 def setBlockDimension(self):
                     """
                     Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
                     Affected:
                         self.shape_spc_Buffer
                         self.shape_cspc_Buffer
                         self.shape_dc_Buffer
                     Return: None
                     """
                     self.shapeBuffer = (self.processingHeaderObj.profilesPerBlock,
                                         self.processingHeaderObj.nHeights,
                                         self.systemHeaderObj.nChannels)
                     self.datablock = numpy.zeros((self.systemHeaderObj.nChannels,
                                                  self.processingHeaderObj.profilesPerBlock,
                                                  self.processingHeaderObj.nHeights),
-                                                 dtype=numpy.dtype('complex'))
+                                                 dtype=numpy.dtype('complex64'))
                 def writeBlock(self):
                     """
                     Escribe el buffer en el file designado
                     Affected:
                         self.profileIndex
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.blockIndex
                     Return: None
                     """
                     data = numpy.zeros( self.shapeBuffer, self.dtype )
                     junk = numpy.transpose(self.datablock, (1,2,0))
                     data['real'] = junk.real
                     data['imag'] = junk.imag
                     data = data.reshape( (-1) )
                     data.tofile( self.fp )
                     self.datablock.fill(0)
                     self.profileIndex = 0
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.blockIndex += 1
                     self.nTotalBlocks += 1
                 def putData(self):
                     """
                     Setea un bloque de datos y luego los escribe en un file
                     Affected:
                         self.flagIsNewBlock
                         self.profileIndex
                     Return:
 :    Si no hay data o no hay mas files que puedan escribirse
 :    Si se escribio la data de un bloque en un file
                     """
                     if self.dataOut.flagNoData:
                         return 0
                     self.flagIsNewBlock = 0
                     if self.dataOut.flagTimeBlock:
                         self.datablock.fill(0)
                         self.profileIndex = 0
                         self.setNextFile()
                     if self.profileIndex == 0:
                         self.getBasicHeader()
                     self.datablock[:,self.profileIndex,:] = self.dataOut.data
                     self.profileIndex += 1
                     if self.hasAllDataInBuffer():
                         #if self.flagIsNewFile:
                         self.writeNextBlock()
             #            self.getDataHeader()
                     return 1
                 def __getProcessFlags(self):
                     processFlags = 0
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList =  [PROCFLAG.DATATYPE_CHAR,
                                        PROCFLAG.DATATYPE_SHORT,
                                        PROCFLAG.DATATYPE_LONG,
                                        PROCFLAG.DATATYPE_INT64,
                                        PROCFLAG.DATATYPE_FLOAT,
                                        PROCFLAG.DATATYPE_DOUBLE]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             dtypeValue = datatypeValueList[index]
                             break
                     processFlags += dtypeValue
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
                     if self.dataOut.code != None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nCohInt > 1:
                         processFlags += PROCFLAG.COHERENT_INTEGRATION
                     return processFlags
                 def __getBlockSize(self):
                     '''
                     Este metodos determina el cantidad de bytes para un bloque de datos de tipo Voltage
                     '''
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList = [1,2,4,8,4,8]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             datatypeValue = datatypeValueList[index]
                             break
                     blocksize = int(self.dataOut.nHeights * self.dataOut.nChannels * self.dataOut.nProfiles * datatypeValue * 2)
                     return blocksize
                 def getDataHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.dtype
                     Return:
                         None
                     """
                     self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
                     self.systemHeaderObj.nChannels = self.dataOut.nChannels
                     self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
                     self.getBasicHeader()
                     processingHeaderSize = 40 # bytes
                     self.processingHeaderObj.dtype = 0 # Voltage
                     self.processingHeaderObj.blockSize = self.__getBlockSize()
                     self.processingHeaderObj.profilesPerBlock = self.profilesPerBlock
                     self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
                     self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
                     self.processingHeaderObj.processFlags = self.__getProcessFlags()
                     self.processingHeaderObj.nCohInt = self.dataOut.nCohInt
                     self.processingHeaderObj.nIncohInt = 1 # Cuando la data de origen es de tipo Voltage
                     self.processingHeaderObj.totalSpectra = 0 # Cuando la data de origen es de tipo Voltage
                     if self.dataOut.code != None:
                         self.processingHeaderObj.code = self.dataOut.code
                         self.processingHeaderObj.nCode = self.dataOut.nCode
                         self.processingHeaderObj.nBaud = self.dataOut.nBaud
                         codesize = int(8 + 4 * self.dataOut.nCode * self.dataOut.nBaud)
                         processingHeaderSize += codesize
                     if self.processingHeaderObj.nWindows != 0:
                         self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
                         self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                         self.processingHeaderObj.nHeights = self.dataOut.nHeights
                         self.processingHeaderObj.samplesWin = self.dataOut.nHeights
                         processingHeaderSize += 12
                     self.processingHeaderObj.size = processingHeaderSize
             class SpectraReader(JRODataReader):
                 """
                 Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura
                 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones)
                 son almacenados en tres buffer's para el Self Spectra, el Cross Spectra y el DC Channel.
                                     paresCanalesIguales    * alturas * perfiles  (Self Spectra)
                                     paresCanalesDiferentes * alturas * perfiles  (Cross Spectra)
                                     canales * alturas                            (DC Channels)
                 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
                 RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la
                 cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de
                 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
                 Example:
                     dpath = "/home/myuser/data"
                     startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
                     endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
                     readerObj = SpectraReader()
                     readerObj.setup(dpath, startTime, endTime)
                     while(True):
                         readerObj.getData()
                         print readerObj.data_spc
                         print readerObj.data_cspc
                         print readerObj.data_dc
                         if readerObj.flagNoMoreFiles:
                             break
                 """
                 pts2read_SelfSpectra = 0
                 pts2read_CrossSpectra = 0
                 pts2read_DCchannels = 0
                 ext = ".pdata"
                 optchar = "P"
                 dataOut = None
                 nRdChannels = None
                 nRdPairs = None
                 rdPairList = []
                 def __init__(self):
                     """
                     Inicializador de la clase SpectraReader para la lectura de datos de espectros.
                     Inputs:
                         dataOut    :    Objeto de la clase Spectra. Este objeto sera utilizado para
                                           almacenar un perfil de datos cada vez que se haga un requerimiento
                                           (getData). El perfil sera obtenido a partir del buffer de datos,
                                           si el buffer esta vacio se hara un nuevo proceso de lectura de un
                                           bloque de datos.
                                           Si este parametro no es pasado se creara uno internamente.
                     Affected:
                         self.dataOut
                     Return      : None
                     """
                     self.isConfig = False
                     self.pts2read_SelfSpectra = 0
                     self.pts2read_CrossSpectra = 0
                     self.pts2read_DCchannels = 0
                     self.datablock = None
                     self.utc = None
                     self.ext = ".pdata"
                     self.optchar = "P"
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                     self.online = 0
                     self.fp = None
                     self.idFile = None
                     self.dtype = None
                     self.fileSizeByHeader = None
                     self.filenameList = []
                     self.filename = None
                     self.fileSize = None
                     self.firstHeaderSize = 0
                     self.basicHeaderSize = 24
                     self.pathList = []
                     self.lastUTTime = 0
                     self.maxTimeStep = 30
                     self.flagNoMoreFiles = 0
                     self.set = 0
                     self.path = None
                     self.delay  = 3   #seconds
                     self.nTries = 3  #quantity tries
                     self.nFiles = 3   #number of files for searching
                     self.nReadBlocks = 0
                     self.flagIsNewFile = 1
                     self.ippSeconds = 0
                     self.flagTimeBlock = 0
                     self.flagIsNewBlock = 0
                     self.nTotalBlocks = 0
                     self.blocksize = 0
                     self.dataOut = self.createObjByDefault()
                 def createObjByDefault(self):
                     dataObj = Spectra()
                     return dataObj
                 def __hasNotDataInBuffer(self):
                     return 1
                 def getBlockDimension(self):
                     """
                     Obtiene la cantidad de puntos a leer por cada bloque de datos
                     Affected:
                         self.nRdChannels
                         self.nRdPairs
                         self.pts2read_SelfSpectra
                         self.pts2read_CrossSpectra
                         self.pts2read_DCchannels
                         self.blocksize
                         self.dataOut.nChannels
                         self.dataOut.nPairs
                     Return:
                         None
                     """
                     self.nRdChannels = 0
                     self.nRdPairs = 0
                     self.rdPairList = []
                     for i in range(0, self.processingHeaderObj.totalSpectra*2, 2):
                         if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]:
                             self.nRdChannels = self.nRdChannels + 1 #par de canales iguales
                         else:
                             self.nRdPairs = self.nRdPairs + 1 #par de canales diferentes
                             self.rdPairList.append((self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1]))
                     pts2read = self.processingHeaderObj.nHeights * self.processingHeaderObj.profilesPerBlock
                     self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read)
                     self.blocksize = self.pts2read_SelfSpectra
                     if self.processingHeaderObj.flag_cspc:
                         self.pts2read_CrossSpectra = int(self.nRdPairs * pts2read)
                         self.blocksize += self.pts2read_CrossSpectra
                     if self.processingHeaderObj.flag_dc:
                         self.pts2read_DCchannels = int(self.systemHeaderObj.nChannels * self.processingHeaderObj.nHeights)
                         self.blocksize += self.pts2read_DCchannels
             #        self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels
                 def readBlock(self):
                     """
                     Lee el bloque de datos desde la posicion actual del puntero del archivo
                     (self.fp) y actualiza todos los parametros relacionados al bloque de datos
                     (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
                     es seteado a 0
                     Return: None
                     Variables afectadas:
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                     Exceptions:
                         Si un bloque leido no es un bloque valido
                     """
                     blockOk_flag = False
                     fpointer = self.fp.tell()
                     spc = numpy.fromfile( self.fp, self.dtype[0], self.pts2read_SelfSpectra )
                     spc = spc.reshape( (self.nRdChannels, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
                     if self.processingHeaderObj.flag_cspc:
                         cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra )
                         cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
                     if self.processingHeaderObj.flag_dc:
                         dc = numpy.fromfile( self.fp, self.dtype, self.pts2read_DCchannels ) #int(self.processingHeaderObj.nHeights*self.systemHeaderObj.nChannels) )
                         dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D
                     if not(self.processingHeaderObj.shif_fft):
                         #desplaza a la derecha en el eje 2 determinadas posiciones
                         shift = int(self.processingHeaderObj.profilesPerBlock/2)
                         spc = numpy.roll( spc, shift , axis=2 )
                         if self.processingHeaderObj.flag_cspc:
                             #desplaza a la derecha en el eje 2 determinadas posiciones
                             cspc = numpy.roll( cspc, shift, axis=2 )
             #            self.processingHeaderObj.shif_fft = True
                     spc = numpy.transpose( spc, (0,2,1) )
                     self.data_spc = spc
                     if self.processingHeaderObj.flag_cspc:
                         cspc = numpy.transpose( cspc, (0,2,1) )
                         self.data_cspc = cspc['real'] + cspc['imag']*1j
                     else:
                         self.data_cspc = None
                     if self.processingHeaderObj.flag_dc:
                         self.data_dc = dc['real'] + dc['imag']*1j
                     else:
                         self.data_dc = None
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def getData(self):
                     """
                     Copia el buffer de lectura a la clase "Spectra",
                     con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de
                     lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock"
                     Return:
 :    Si no hay mas archivos disponibles
 :    Si hizo una buena copia del buffer
                     Affected:
                         self.dataOut
                         self.flagTimeBlock
                         self.flagIsNewBlock
                     """
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagTimeBlock = 0
                     self.flagIsNewBlock = 0
                     if self.__hasNotDataInBuffer():
                         if not( self.readNextBlock() ):
                             self.dataOut.flagNoData = True
                             return 0
             #            self.updateDataHeader()
                     #data es un numpy array de 3 dmensiones (perfiles, alturas y canales)
                     if self.data_dc == None:
                         self.dataOut.flagNoData = True
                         return 0
                     self.dataOut.data_spc = self.data_spc
                     self.dataOut.data_cspc = self.data_cspc
                     self.dataOut.data_dc = self.data_dc
                     self.dataOut.flagTimeBlock = self.flagTimeBlock
                     self.dataOut.flagNoData = False
-                    self.dataOut.dtype = numpy.dtype([('real','<f8'),('imag','<f8')])#self.dtype
+                    self.dataOut.dtype = self.dtype
             #        self.dataOut.nChannels = self.nRdChannels
                     self.dataOut.nPairs = self.nRdPairs
                     self.dataOut.pairsList = self.rdPairList
             #        self.dataOut.nHeights = self.processingHeaderObj.nHeights
                     self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.nFFTPoints = self.processingHeaderObj.profilesPerBlock
                     self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
                     self.dataOut.nIncohInt = self.processingHeaderObj.nIncohInt
                     xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight
                     self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
                     self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
             #        self.dataOut.channelIndexList = range(self.systemHeaderObj.nChannels)
                     self.dataOut.utctime = self.basicHeaderObj.utc + self.basicHeaderObj.miliSecond/1000.#+ self.profileIndex * self.ippSeconds
                     self.dataOut.ippSeconds = self.ippSeconds
                     self.dataOut.timeInterval = self.ippSeconds * self.processingHeaderObj.nCohInt * self.processingHeaderObj.nIncohInt * self.dataOut.nFFTPoints
             #        self.profileIndex += 1
                     self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
                     self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
                     self.dataOut.flagShiftFFT = self.processingHeaderObj.shif_fft
                     self.dataOut.flagDecodeData = False #asumo q la data no esta decodificada
                     self.dataOut.flagDeflipData = True #asumo q la data no esta sin flip
                     if self.processingHeaderObj.code != None:
                             self.dataOut.nCode = self.processingHeaderObj.nCode
                             self.dataOut.nBaud = self.processingHeaderObj.nBaud
                             self.dataOut.code = self.processingHeaderObj.code
                             self.dataOut.flagDecodeData = True
                     return self.dataOut.data_spc
             class SpectraWriter(JRODataWriter):
                 """
                 Esta clase permite escribir datos de espectros a archivos procesados (.pdata). La escritura
                 de los datos siempre se realiza por bloques.
                 """
                 ext = ".pdata"
                 optchar = "P"
                 shape_spc_Buffer = None
                 shape_cspc_Buffer = None
                 shape_dc_Buffer = None
                 data_spc = None
                 data_cspc = None
                 data_dc = None
             #    dataOut = None
                 def __init__(self):
                     """
                     Inicializador de la clase SpectraWriter para la escritura de datos de espectros.
                     Affected:
                         self.dataOut
                         self.basicHeaderObj
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.processingHeaderObj
                     Return: None
                     """
                     self.isConfig = False
                     self.nTotalBlocks = 0
                     self.data_spc = None
                     self.data_cspc = None
                     self.data_dc = None
                     self.fp = None
                     self.flagIsNewFile = 1
                     self.nTotalBlocks = 0
                     self.flagIsNewBlock = 0
                     self.setFile = None
                     self.dtype = None
                     self.path = None
                     self.noMoreFiles = 0
                     self.filename = None
                     self.basicHeaderObj = BasicHeader(LOCALTIME)
                     self.systemHeaderObj = SystemHeader()
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.processingHeaderObj = ProcessingHeader()
                 def hasAllDataInBuffer(self):
                     return 1
                 def setBlockDimension(self):
                     """
                     Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
                     Affected:
                         self.shape_spc_Buffer
                         self.shape_cspc_Buffer
                         self.shape_dc_Buffer
                     Return: None
                     """
                     self.shape_spc_Buffer = (self.dataOut.nChannels,
                                              self.processingHeaderObj.nHeights,
                                              self.processingHeaderObj.profilesPerBlock)
                     self.shape_cspc_Buffer = (self.dataOut.nPairs,
                                               self.processingHeaderObj.nHeights,
                                               self.processingHeaderObj.profilesPerBlock)
                     self.shape_dc_Buffer = (self.dataOut.nChannels,
                                             self.processingHeaderObj.nHeights)
                 def writeBlock(self):
                     """
                     Escribe el buffer en el file designado
                     Affected:
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                         self.flagIsNewFile
                         self.flagIsNewBlock
                         self.nTotalBlocks
                         self.nWriteBlocks
                     Return: None
                     """
                     spc = numpy.transpose( self.data_spc, (0,2,1) )
                     if not( self.processingHeaderObj.shif_fft ):
                         spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
                     data = spc.reshape((-1))
+                    data = data.astype(self.dtype[0])
                     data.tofile(self.fp)
                     if self.data_cspc != None:
                         data = numpy.zeros( self.shape_cspc_Buffer, self.dtype )
                         cspc = numpy.transpose( self.data_cspc, (0,2,1) )
                         if not( self.processingHeaderObj.shif_fft ):
                             cspc = numpy.roll( cspc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
                         data['real'] = cspc.real
                         data['imag'] = cspc.imag
                         data = data.reshape((-1))
                         data.tofile(self.fp)
                     if self.data_dc != None:
                         data = numpy.zeros( self.shape_dc_Buffer, self.dtype )
                         dc = self.data_dc
                         data['real'] = dc.real
                         data['imag'] = dc.imag
                         data = data.reshape((-1))
                         data.tofile(self.fp)
                     self.data_spc.fill(0)
                     self.data_dc.fill(0)
                     if self.data_cspc != None:
                         self.data_cspc.fill(0)
                     self.flagIsNewFile = 0
                     self.flagIsNewBlock = 1
                     self.nTotalBlocks += 1
                     self.nWriteBlocks += 1
                     self.blockIndex += 1
                 def putData(self):
                     """
                     Setea un bloque de datos y luego los escribe en un file
                     Affected:
                         self.data_spc
                         self.data_cspc
                         self.data_dc
                     Return:
 :    Si no hay data o no hay mas files que puedan escribirse
 :    Si se escribio la data de un bloque en un file
                     """
                     if self.dataOut.flagNoData:
                         return 0
                     self.flagIsNewBlock = 0
                     if self.dataOut.flagTimeBlock:
                         self.data_spc.fill(0)
                         self.data_cspc.fill(0)
                         self.data_dc.fill(0)
                         self.setNextFile()
                     if self.flagIsNewFile == 0:
                         self.getBasicHeader()
                     self.data_spc = self.dataOut.data_spc.copy()
                     self.data_cspc = self.dataOut.data_cspc.copy()
                     self.data_dc = self.dataOut.data_dc.copy()
                     # #self.processingHeaderObj.dataBlocksPerFile)
                     if self.hasAllDataInBuffer():
             #            self.getDataHeader()
                         self.writeNextBlock()
                     return 1
                 def __getProcessFlags(self):
                     processFlags = 0
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList =  [PROCFLAG.DATATYPE_CHAR,
                                        PROCFLAG.DATATYPE_SHORT,
                                        PROCFLAG.DATATYPE_LONG,
                                        PROCFLAG.DATATYPE_INT64,
                                        PROCFLAG.DATATYPE_FLOAT,
                                        PROCFLAG.DATATYPE_DOUBLE]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             dtypeValue = datatypeValueList[index]
                             break
                     processFlags += dtypeValue
                     if self.dataOut.flagDecodeData:
                         processFlags += PROCFLAG.DECODE_DATA
                     if self.dataOut.flagDeflipData:
                         processFlags += PROCFLAG.DEFLIP_DATA
                     if self.dataOut.code != None:
                         processFlags += PROCFLAG.DEFINE_PROCESS_CODE
                     if self.dataOut.nIncohInt > 1:
                         processFlags += PROCFLAG.INCOHERENT_INTEGRATION
                     if self.dataOut.data_dc != None:
                         processFlags += PROCFLAG.SAVE_CHANNELS_DC
                     return processFlags
                 def __getBlockSize(self):
                     '''
                     Este metodos determina el cantidad de bytes para un bloque de datos de tipo Spectra
                     '''
                     dtype0 = numpy.dtype([('real','<i1'),('imag','<i1')])
                     dtype1 = numpy.dtype([('real','<i2'),('imag','<i2')])
                     dtype2 = numpy.dtype([('real','<i4'),('imag','<i4')])
                     dtype3 = numpy.dtype([('real','<i8'),('imag','<i8')])
                     dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')])
                     dtype5 = numpy.dtype([('real','<f8'),('imag','<f8')])
                     dtypeList = [dtype0, dtype1, dtype2, dtype3, dtype4, dtype5]
                     datatypeValueList = [1,2,4,8,4,8]
                     for index in range(len(dtypeList)):
                         if self.dataOut.dtype == dtypeList[index]:
                             datatypeValue = datatypeValueList[index]
                             break
                     pts2write = self.dataOut.nHeights * self.dataOut.nFFTPoints
                     pts2write_SelfSpectra = int(self.dataOut.nChannels * pts2write)
                     blocksize = (pts2write_SelfSpectra*datatypeValue)
                     if self.dataOut.data_cspc != None:
                         pts2write_CrossSpectra = int(self.dataOut.nPairs * pts2write)
                         blocksize += (pts2write_CrossSpectra*datatypeValue*2)
                     if self.dataOut.data_dc != None:
                         pts2write_DCchannels = int(self.dataOut.nChannels * self.dataOut.nHeights)
                         blocksize += (pts2write_DCchannels*datatypeValue*2)
                     blocksize = blocksize #* datatypeValue * 2 #CORREGIR ESTO
                     return blocksize
                 def getDataHeader(self):
                     """
                     Obtiene una copia del First Header
                     Affected:
                         self.systemHeaderObj
                         self.radarControllerHeaderObj
                         self.dtype
                     Return:
                         None
                     """
                     self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
                     self.systemHeaderObj.nChannels = self.dataOut.nChannels
                     self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
                     self.getBasicHeader()
                     processingHeaderSize = 40 # bytes
                     self.processingHeaderObj.dtype = 0 # Voltage
                     self.processingHeaderObj.blockSize = self.__getBlockSize()
                     self.processingHeaderObj.profilesPerBlock = self.dataOut.nFFTPoints
                     self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
                     self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
                     self.processingHeaderObj.processFlags = self.__getProcessFlags()
                     self.processingHeaderObj.nCohInt = self.dataOut.nCohInt# Se requiere para determinar el valor de timeInterval
                     self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt
                     self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels
                     if self.processingHeaderObj.totalSpectra > 0:
                         channelList = []
                         for channel in range(self.dataOut.nChannels):
                             channelList.append(channel)
                             channelList.append(channel)
                         pairsList = []
                         for pair in self.dataOut.pairsList:
                             pairsList.append(pair[0])
                             pairsList.append(pair[1])
                         spectraComb = channelList + pairsList
                         spectraComb = numpy.array(spectraComb,dtype="u1")
                         self.processingHeaderObj.spectraComb = spectraComb
                         sizeOfSpcComb = len(spectraComb)
                         processingHeaderSize += sizeOfSpcComb
                     if self.dataOut.code != None:
                         self.processingHeaderObj.code = self.dataOut.code
                         self.processingHeaderObj.nCode = self.dataOut.nCode
                         self.processingHeaderObj.nBaud = self.dataOut.nBaud
                         nCodeSize = 4 # bytes
                         nBaudSize = 4 # bytes
                         codeSize = 4 # bytes
                         sizeOfCode = int(nCodeSize + nBaudSize + codeSize * self.dataOut.nCode * self.dataOut.nBaud)
                         processingHeaderSize += sizeOfCode
                     if self.processingHeaderObj.nWindows != 0:
                         self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
                         self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                         self.processingHeaderObj.nHeights = self.dataOut.nHeights
                         self.processingHeaderObj.samplesWin = self.dataOut.nHeights
                         sizeOfFirstHeight = 4
                         sizeOfdeltaHeight = 4
                         sizeOfnHeights = 4
                         sizeOfWindows = (sizeOfFirstHeight + sizeOfdeltaHeight + sizeOfnHeights)*self.processingHeaderObj.nWindows
                         processingHeaderSize += sizeOfWindows
                     self.processingHeaderObj.size = processingHeaderSize
             class SpectraHeisWriter():
                 i=0
                 def __init__(self, dataOut):
                     self.wrObj = FITS()
                     self.dataOut = dataOut
                 def isNumber(str):
                     """
                     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( str )
                         return True
                     except:
                         return False
                 def setup(self, wrpath,):
                     if not(os.path.exists(wrpath)):
                         os.mkdir(wrpath)
                     self.wrpath = wrpath
                     self.setFile = 0
                 def putData(self):
                   # self.wrObj.writeHeader(nChannels=self.dataOut.nChannels, nFFTPoints=self.dataOut.nFFTPoints)
                     #name = self.dataOut.utctime
                     name= time.localtime( self.dataOut.utctime)
                     ext=".fits"
                     #folder='D%4.4d%3.3d'%(name.tm_year,name.tm_yday)
                     subfolder = 'D%4.4d%3.3d' % (name.tm_year,name.tm_yday)
                     fullpath = os.path.join( self.wrpath, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                     self.setFile += 1
                     file = 'D%4.4d%3.3d%3.3d%s' % (name.tm_year,name.tm_yday,self.setFile,ext)
                     filename = os.path.join(self.wrpath,subfolder, file)
                    # print self.dataOut.ippSeconds
                     freq=numpy.arange(-1*self.dataOut.nHeights/2.,self.dataOut.nHeights/2.)/(2*self.dataOut.ippSeconds)
                     col1=self.wrObj.setColF(name="freq", format=str(self.dataOut.nFFTPoints)+'E', array=freq)
                     col2=self.wrObj.writeData(name="P_Ch1",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[0,:]))
                     col3=self.wrObj.writeData(name="P_Ch2",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[1,:]))
                     col4=self.wrObj.writeData(name="P_Ch3",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[2,:]))
                     col5=self.wrObj.writeData(name="P_Ch4",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[3,:]))
                     col6=self.wrObj.writeData(name="P_Ch5",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[4,:]))
                     col7=self.wrObj.writeData(name="P_Ch6",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[5,:]))
                     col8=self.wrObj.writeData(name="P_Ch7",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[6,:]))
                     col9=self.wrObj.writeData(name="P_Ch8",format=str(self.dataOut.nFFTPoints)+'E',data=10*numpy.log10(self.dataOut.data_spc[7,:]))
                     #n=numpy.arange((100))
                     n=self.dataOut.data_spc[6,:]
                     a=self.wrObj.cFImage(n)
                     b=self.wrObj.Ctable(col1,col2,col3,col4,col5,col6,col7,col8,col9)
                     self.wrObj.CFile(a,b)
                     self.wrObj.wFile(filename)
                     return 1
             class FITS:
                 name=None
                 format=None
                 array =None
                 data =None
                 thdulist=None
                 def __init__(self):
                     pass
                 def setColF(self,name,format,array):
                     self.name=name
                     self.format=format
                     self.array=array
                     a1=numpy.array([self.array],dtype=numpy.float32)
                     self.col1 = pyfits.Column(name=self.name, format=self.format, array=a1)
                     return self.col1
             #    def setColP(self,name,format,data):
             #        self.name=name
             #        self.format=format
             #        self.data=data
             #        a2=numpy.array([self.data],dtype=numpy.float32)
             #        self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2)
             #        return self.col2
                 def writeHeader(self,):
                     pass
                 def writeData(self,name,format,data):
                     self.name=name
                     self.format=format
                     self.data=data
                     a2=numpy.array([self.data],dtype=numpy.float32)
                     self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2)
                     return self.col2
                 def cFImage(self,n):
                     self.hdu= pyfits.PrimaryHDU(n)
                     return self.hdu
                 def Ctable(self,col1,col2,col3,col4,col5,col6,col7,col8,col9):
                     self.cols=pyfits.ColDefs( [col1,col2,col3,col4,col5,col6,col7,col8,col9])
                     self.tbhdu = pyfits.new_table(self.cols)
                     return self.tbhdu
                 def CFile(self,hdu,tbhdu):
                     self.thdulist=pyfits.HDUList([hdu,tbhdu])
                 def wFile(self,filename):
                     self.thdulist.writeto(filename)

schainpy/model/jroprocessing.py +2 -1

             '''
             $Author: dsuarez $
             $Id: Processor.py 1 2012-11-12 18:56:07Z dsuarez $
             '''
             import os
             import numpy
             import datetime
             import time
             from jrodata import *
             from jrodataIO import *
             from jroplot import *
             class ProcessingUnit:
                 """
                 Esta es la clase base para el procesamiento de datos.
                 Contiene el metodo "call" para llamar operaciones. Las operaciones pueden ser:
                     - Metodos internos (callMethod)
                     - Objetos del tipo Operation (callObject). Antes de ser llamados, estos objetos
                       tienen que ser agreagados con el metodo "add".
                 """
                 # objeto de datos de entrada (Voltage, Spectra o Correlation)
                 dataIn = None
                 # objeto de datos de entrada (Voltage, Spectra o Correlation)
                 dataOut = None
                 objectDict = None
                 def __init__(self):
                     self.objectDict = {}
                 def init(self):
                     raise ValueError, "Not implemented"
                 def addOperation(self, object, objId):
                     """
                     Agrega el objeto "object" a la lista de objetos "self.objectList" y retorna el
                     identificador asociado a este objeto.
                     Input:
                         object    :    objeto de la clase "Operation"
                     Return:
                         objId    :    identificador del objeto, necesario para ejecutar la operacion
                     """
                     self.objectDict[objId] = object
                     return objId
                 def operation(self, **kwargs):
                     """
                     Operacion directa sobre la data (dataOut.data). Es necesario actualizar los valores de los
                     atributos del objeto dataOut
                     Input:
                         **kwargs    :    Diccionario de argumentos de la funcion a ejecutar
                     """
                     raise ValueError, "ImplementedError"
                 def callMethod(self, name, **kwargs):
                     """
                     Ejecuta el metodo con el nombre "name" y con argumentos **kwargs de la propia clase.
                     Input:
                         name        :    nombre del metodo a ejecutar
                         **kwargs     :    diccionario con los nombres y valores de la funcion a ejecutar.
                     """
                     if name != 'run':
                         if name == 'init' and self.dataIn.isEmpty():
                             self.dataOut.flagNoData = True
                             return False
                         if name != 'init' and self.dataOut.isEmpty():
                             return False
                     methodToCall = getattr(self, name)
                     methodToCall(**kwargs)
                     if name != 'run':
                         return True
                     if self.dataOut.isEmpty():
                         return False
                     return True
                 def callObject(self, objId, **kwargs):
                     """
                     Ejecuta la operacion asociada al identificador del objeto "objId"
                     Input:
                         objId        :    identificador del objeto a ejecutar
                         **kwargs    :    diccionario con los nombres y valores de la funcion a ejecutar.
                     Return:
                         None
                     """
                     if self.dataOut.isEmpty():
                         return False
                     object = self.objectDict[objId]
                     object.run(self.dataOut, **kwargs)
                     return True
                 def call(self, operationConf, **kwargs):
                     """
                     Return True si ejecuta la operacion "operationConf.name" con los
                     argumentos "**kwargs". False si la operacion no se ha ejecutado.
                     La operacion puede ser de dos tipos:
 . Un metodo propio de esta clase:
                             operation.type = "self"
 . El metodo "run" de un objeto del tipo Operation o de un derivado de ella:
                             operation.type = "other".
                            Este objeto de tipo Operation debe de haber sido agregado antes con el metodo:
                            "addOperation" e identificado con el operation.id
                     con el id de la operacion.
                     Input:
                         Operation    :    Objeto del tipo operacion con los atributos: name, type y id.
                     """
                     if operationConf.type == 'self':
                         sts = self.callMethod(operationConf.name, **kwargs)
                     if operationConf.type == 'other':
                         sts = self.callObject(operationConf.id, **kwargs)
                     return sts
                 def setInput(self, dataIn):
                     self.dataIn = dataIn
                 def getOutput(self):
                     return self.dataOut
             class Operation():
                 """
                 Clase base para definir las operaciones adicionales que se pueden agregar a la clase ProcessingUnit
                 y necesiten acumular informacion previa de los datos a procesar. De preferencia usar un buffer de
                 acumulacion dentro de esta clase
                 Ejemplo: Integraciones coherentes, necesita la informacion previa de los n perfiles anteriores (bufffer)
                 """
                 __buffer = None
                 __isConfig = False
                 def __init__(self):
                     pass
                 def run(self, dataIn, **kwargs):
                     """
                     Realiza las operaciones necesarias sobre la dataIn.data y actualiza los atributos del objeto dataIn.
                     Input:
                         dataIn    :    objeto del tipo JROData
                     Return:
                         None
                     Affected:
                         __buffer    :    buffer de recepcion de datos.
                     """
                     raise ValueError, "ImplementedError"
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     self.objectDict = {}
                     self.dataOut = Voltage()
                     self.flip = 1
                 def init(self):
                     self.dataOut.copy(self.dataIn)
                     # No necesita copiar en cada init() los atributos de dataIn
                     # la copia deberia hacerse por cada nuevo bloque de datos
                 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:
                             print channelIndexList
                             raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
                     nChannels = len(channelIndexList)
                     data = self.dataOut.data[channelIndexList,:]
                     self.dataOut.data = data
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
             #        self.dataOut.nChannels = nChannels
                     return 1
                 def selectHeights(self, minHei, maxHei):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     minIndex = 0
                     maxIndex = 0
                     heights = self.dataOut.heightList
                     inda = numpy.where(heights >= minHei)
                     indb = numpy.where(heights <= maxHei)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return 1
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     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
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     nHeights = maxIndex - minIndex + 1
                     #voltage
                     data = self.dataOut.data[:,minIndex:maxIndex+1]
                     firstHeight = self.dataOut.heightList[minIndex]
                     self.dataOut.data = data
                     self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
                     return 1
                 def filterByHeights(self, window):
                     deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     if window == None:
                         window = self.dataOut.radarControllerHeaderObj.txA / deltaHeight
                     newdelta = deltaHeight * window
                     r = self.dataOut.data.shape[1] % window
                     buffer = self.dataOut.data[:,0:self.dataOut.data.shape[1]-r]
                     buffer = buffer.reshape(self.dataOut.data.shape[0],self.dataOut.data.shape[1]/window,window)
                     buffer = numpy.sum(buffer,2)
                     self.dataOut.data = buffer
                     self.dataOut.heightList = numpy.arange(self.dataOut.heightList[0],newdelta*self.dataOut.nHeights/window-newdelta,newdelta)
                     self.dataOut.windowOfFilter = window
                 def deFlip(self):
                     self.dataOut.data *= self.flip
                     self.flip *= -1.
             class CohInt(Operation):
                 __isConfig = False
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 n = None
                 def __init__(self):
                     self.__isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n        :    Number of coherent integrations
                         timeInterval   :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping    :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = 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 == 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 == 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, **kwargs):
                     if not self.__isConfig:
                         self.setup(**kwargs)
                         self.__isConfig = True
                     avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
                         dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
             class Decoder(Operation):
                 __isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self):
                     self.__isConfig = False
                 def setup(self, code):
                     self.__profIndex = 0
                     self.code = code
                     self.nCode = len(code)
                     self.nBaud = len(code[0])
                 def convolutionInFreq(self, data):
                     nchannel, ndata = data.shape
                     newcode = numpy.zeros(ndata)
                     newcode[0:self.nBaud] = self.code[self.__profIndex]
                     fft_data = numpy.fft.fft(data, axis=1)
                     fft_code = numpy.conj(numpy.fft.fft(newcode))
                     fft_code = fft_code.reshape(1,len(fft_code))
             #        conv = fft_data.copy()
             #        conv.fill(0)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=1)
                     datadec = data[:,:-self.nBaud+1]
                     ndatadec = ndata - self.nBaud + 1
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return ndatadec, datadec
                     self.__profIndex += 1
                     return ndatadec, datadec
                 def convolutionInTime(self, data):
                     nchannel, ndata = data.shape
                     newcode = self.code[self.__profIndex]
                     ndatadec = ndata - self.nBaud + 1
                     datadec = numpy.zeros((nchannel, ndatadec))
                     for i in range(nchannel):
                         datadec[i,:] = numpy.correlate(data[i,:], newcode)
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return ndatadec, datadec
                     self.__profIndex += 1
                     return ndatadec, datadec
                 def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0):
                     if not self.__isConfig:
                         if code != None:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         if code == None:
                             code = dataOut.code
                         self.setup(code)
                         self.__isConfig = True
                     if mode == 0:
                         ndatadec, datadec = self.convolutionInFreq(dataOut.data)
                     if mode == 1:
                         print "This function is not implemented"
             #            ndatadec, datadec = self.convolutionInTime(dataOut.data)
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:ndatadec]
                     dataOut.flagDecodeData = True #asumo q la data no esta decodificada
             #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class SpectraProc(ProcessingUnit):
                 def __init__(self):
                     self.objectDict = {}
                     self.buffer = None
                     self.firstdatatime = None
                     self.profIndex = 0
                     self.dataOut = Spectra()
                 def __updateObjFromInput(self):
                     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 = self.dataOut.nFFTPoints
             #        self.dataOut.channelIndexList = self.dataIn.channelIndexList
                     self.dataOut.flagTimeBlock = self.dataIn.flagTimeBlock
                     self.dataOut.utctime = self.firstdatatime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
                     self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
                     self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nFFTPoints*self.dataOut.nIncohInt
                 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,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:
                             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
                 def init(self, nFFTPoints=None, pairsList=None):
                     self.dataOut.flagNoData = True
                     if self.dataIn.type == "Spectra":
                         self.dataOut.copy(self.dataIn)
                         return
                     if self.dataIn.type == "Voltage":
                         if nFFTPoints == None:
                             raise ValueError, "This SpectraProc.init() need nFFTPoints input variable"
                         if pairsList == None:
                             nPairs = 0
                         else:
                             nPairs = len(pairsList)
                         self.dataOut.nFFTPoints = nFFTPoints
                         self.dataOut.pairsList = pairsList
                         self.dataOut.nPairs = nPairs
                         if self.buffer == None:
                             self.buffer = numpy.zeros((self.dataIn.nChannels,
                                                        self.dataOut.nFFTPoints,
                                                        self.dataIn.nHeights),
                                                        dtype='complex')
                         self.buffer[:,self.profIndex,:] = self.dataIn.data.copy()
                         self.profIndex += 1
                         if self.firstdatatime == None:
                             self.firstdatatime = self.dataIn.utctime
                         if self.profIndex == self.dataOut.nFFTPoints:
                             self.__updateObjFromInput()
                             self.__getFft()
                             self.dataOut.flagNoData = False
                             self.buffer = None
                             self.firstdatatime = None
                             self.profIndex = 0
                         return
                     raise ValuError, "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_spc
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             print channelIndexList
                             raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
                     nChannels = len(channelIndexList)
                     data_spc = self.dataOut.data_spc[channelIndexList,:]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
             #        self.dataOut.nChannels = nChannels
                     return 1
                 def selectHeights(self, minHei, maxHei):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     if (maxHei > self.dataOut.heightList[-1]):
                         maxHei = self.dataOut.heightList[-1]
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
                     minIndex = 0
                     maxIndex = 0
                     heights = self.dataOut.heightList
                     inda = numpy.where(heights >= minHei)
                     indb = numpy.where(heights <= maxHei)
                     try:
                         minIndex = inda[0][0]
                     except:
                         minIndex = 0
                     try:
                         maxIndex = indb[0][-1]
                     except:
                         maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return 1
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights-1
             #            raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     nHeights = maxIndex - minIndex + 1
                     #Spectra
                     data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
                     data_cspc = None
                     if self.dataOut.data_cspc != None:
                         data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
                     data_dc = None
                     if self.dataOut.data_dc != None:
                         data_dc = self.dataOut.data_dc[:,:,minIndex:maxIndex+1]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
                     return 1
                 def removeDC(self, mode = 1):
                     dc_index = 0
                     freq_index = numpy.array([-2,-1,1,2])
                     data_spc = self.dataOut.data_spc
                     data_cspc = self.dataOut.data_cspc
                     data_dc = self.dataOut.data_dc
                     if self.dataOut.flagShiftFFT:
                         dc_index += self.dataOut.nFFTPoints/2
                         freq_index += self.dataOut.nFFTPoints/2
                     if mode == 1:
                         data_spc[dc_index] = (data_spc[:,freq_index[1],:] + data_spc[:,freq_index[2],:])/2
                         if data_cspc != None:
                             data_cspc[dc_index] = (data_cspc[:,freq_index[1],:] + data_cspc[:,freq_index[2],:])/2
                         return 1
                     if mode == 2:
                         pass
                     if mode == 3:
                         pass
                     raise ValueError, "mode parameter has to be 1, 2 or 3"
                 def removeInterference(self):
                     pass
             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
                 n = None
                 def __init__(self):
                     self.__isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n        :    Number of coherent integrations
                         timeInterval   :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping    :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer_spc = None
                     self.__buffer_cspc = None
                     self.__buffer_dc = None
                     self.__dataReady = False
                     if n == None and timeInterval == None:
                         raise ValueError, "n or timeInterval should be specified ..."
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval * 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverapping = True
                     else:
                         self.__withOverapping = False
                         self.__buffer_spc = 0
                         self.__buffer_cspc = 0
                         self.__buffer_dc = 0
                     self.__profIndex = 0
                 def putData(self, data_spc, data_cspc, data_dc):
                     """
                     Add a profile to the __buffer_spc and increase in one the __profileIndex
                     """
                     if not self.__withOverapping:
                         self.__buffer_spc += data_spc
                         if data_cspc == None:
                             self.__buffer_cspc = None
                         else:
                             self.__buffer_cspc += data_cspc
                         if data_dc == None:
                             self.__buffer_dc = None
                         else:
                             self.__buffer_dc += data_dc
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nFFTPoints, nHeis = data_spc.shape
                     data_spc = numpy.reshape(data_spc, (1, nChannels, nFFTPoints, nHeis))
                     if data_cspc != None:
                         data_cspc = numpy.reshape(data_cspc, (1, -1, nFFTPoints, nHeis))
                     if data_dc != None:
                         data_dc = numpy.reshape(data_dc, (1, -1, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer_spc == None:
                         self.__buffer_spc = data_spc
                         if data_cspc == None:
                             self.__buffer_cspc = None
                         else:
                             self.__buffer_cspc += data_cspc
                         if data_dc == None:
                             self.__buffer_dc = None
                         else:
                             self.__buffer_dc += data_dc
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer_spc = numpy.vstack((self.__buffer_spc, data_spc))
                         if data_cspc != None:
                             self.__buffer_cspc = numpy.vstack((self.__buffer_cspc, data_cspc))
                         if data_dc != None:
                             self.__buffer_dc = numpy.vstack((self.__buffer_dc, data_dc))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer_spc = numpy.roll(self.__buffer_spc, -1, axis=0)
                     self.__buffer_spc[self.n-1] = data_spc
                     if data_cspc != None:
                         self.__buffer_cspc = numpy.roll(self.__buffer_cspc, -1, axis=0)
                         self.__buffer_cspc[self.n-1] = data_cspc
                     if data_dc != None:
                         self.__buffer_dc = numpy.roll(self.__buffer_dc, -1, axis=0)
                         self.__buffer_dc[self.n-1] = data_dc
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     data_spc = None
                     data_cspc  = None
                     data_dc = None
                     if not self.__withOverapping:
                         data_spc = self.__buffer_spc
                         data_cspc = self.__buffer_cspc
                         data_dc = self.__buffer_dc
                         n = self.__profIndex
                         self.__buffer_spc = 0
                         self.__buffer_cspc = 0
                         self.__buffer_dc = 0
                         self.__profIndex = 0
                         return data_spc, data_cspc, data_dc, n
                     #Integration with Overlapping
                     data_spc = numpy.sum(self.__buffer_spc, axis=0)
                     if self.__buffer_cspc != None:
                         data_cspc = numpy.sum(self.__buffer_cspc, axis=0)
                     if self.__buffer_dc != None:
                         data_dc = numpy.sum(self.__buffer_dc, axis=0)
                     n = self.__profIndex
                     return data_spc, data_cspc, data_dc, n
                 def byProfiles(self, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     n = None
                     self.putData(*args)
                     if self.__profIndex == self.n:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def byTime(self, datatime, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     n = None
                     self.putData(*args)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def integrate(self, datatime, *args):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
                     else:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
                     self.__lastdatatime = datatime
                     if avgdata_spc == None:
                         return None, None, None, None
                     avgdatatime = self.__initime
                     deltatime = datatime -self.__lastdatatime
                     if not self.__withOverapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
                     if not self.__isConfig:
                         self.setup(n, timeInterval, overlapping)
                         self.__isConfig = True
                     avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
                                                                                         dataOut.data_spc,
                                                                                         dataOut.data_cspc,
                                                                                         dataOut.data_dc)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data_spc = avgdata_spc
                         dataOut.data_cspc = avgdata_cspc
                         dataOut.data_dc = avgdata_dc
                         dataOut.nIncohInt *= self.n
                         dataOut.utctime = avgdatatime
                         dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt * dataOut.nIncohInt * dataOut.nFFTPoints
                         dataOut.flagNoData = False
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self):
                     self.profileIndex = 0
                 def incIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isProfileInRange(self, minIndex, maxIndex):
                     if self.profileIndex < minIndex:
                         return False
                     if self.profileIndex > maxIndex:
                         return False
                     return True
                 def isProfileInList(self, profileList):
                     if self.profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, profileList=None, profileRangeList=None):
                     dataOut.flagNoData = True
                     self.nProfiles = dataOut.nProfiles
                     if profileList != None:
                         if self.isProfileInList(profileList):
                             dataOut.flagNoData = False
                         self.incIndex()
                         return 1
                     elif profileRangeList != None:
                         minIndex = profileRangeList[0]
                         maxIndex = profileRangeList[1]
                         if self.isProfileInRange(minIndex, maxIndex):
                             dataOut.flagNoData = False
                         self.incIndex()
                         return 1
                     else:
                         raise ValueError, "ProfileSelector needs profileList or profileRangeList"
                     return 0

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