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