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'''
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File: SpectraIO.py
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Created on 20/02/2012
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@author $Author: dsuarez $
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@version $Id: SpectraIO.py 110 2012-07-19 15:18:18Z dsuarez $
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'''
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import os, sys
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import numpy
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import glob
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import fnmatch
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import time, datetime
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path = os.path.split(os.getcwd())[0]
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sys.path.append(path)
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from Model.JROHeader import *
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from Model.Spectra import Spectra
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from JRODataIO import JRODataReader
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from JRODataIO import JRODataWriter
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from JRODataIO import isNumber
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class SpectraReader(JRODataReader):
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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.dataOutObj.data
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if readerObj.flagNoMoreFiles:
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break
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"""
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dataOutObj = None
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datablock = None
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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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flag_cspc = False
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def __init__(self, dataOutObj=None):
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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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dataOutObj : 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.dataOutObj
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Return : None
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"""
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self.pts2read_SelfSpectra = 0
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self.pts2read_CrossSpectra = 0
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self.pts2read_DCs = 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()
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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 = 3 #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.ippSeconds = 0
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self.flagTimeBlock = 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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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.nChannels
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self.nPairs
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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.dataOutObj.nChannels
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self.dataOutObj.nPairs
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Return:
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None
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"""
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self.nChannels = 0
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self.nPairs = 0
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self.pairList = []
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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.nChannels = self.nChannels + 1 #par de canales iguales
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else:
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self.nPairs = self.nPairs + 1 #par de canales diferentes
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self.pairList.append( (self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1]) )
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pts2read = self.processingHeaderObj.numHeights * self.processingHeaderObj.profilesPerBlock
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self.pts2read_SelfSpectra = int(self.nChannels * 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.nPairs * 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.numChannels * self.processingHeaderObj.numHeights)
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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.datablockIndex
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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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blockOk_flag = False
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fpointer = self.fp.tell()
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spc = numpy.fromfile( self.fp, self.dataType[0], self.pts2read_SelfSpectra )
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spc = spc.reshape( (self.nChannels, self.processingHeaderObj.numHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
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if self.flag_cspc:
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cspc = numpy.fromfile( self.fp, self.dataType, self.pts2read_CrossSpectra )
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cspc = cspc.reshape( (self.nPairs, self.processingHeaderObj.numHeights, 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.dataType, self.pts2read_DCchannels ) #int(self.processingHeaderObj.numHeights*self.systemHeaderObj.numChannels) )
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dc = dc.reshape( (self.systemHeaderObj.numChannels, self.processingHeaderObj.numHeights) ) #transforma a un arreglo 2D
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if not(self.processingHeaderObj.shif_fft):
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spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
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if self.flag_cspc:
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cspc = numpy.roll( cspc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
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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.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.datablockIndex = 0
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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 getData(self):
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"""
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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.dataOutObj
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self.datablockIndex
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self.flagTimeBlock
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self.flagIsNewBlock
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"""
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if self.flagNoMoreFiles: return 0
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self.flagTimeBlock = 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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return 0
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self.updateDataHeader()
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if self.flagNoMoreFiles == 1:
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print 'Process finished'
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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_dc == None:
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self.dataOutObj.flagNoData = True
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return 0
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self.dataOutObj.flagNoData = False
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self.dataOutObj.flagTimeBlock = self.flagTimeBlock
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self.dataOutObj.data_spc = self.data_spc
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self.dataOutObj.data_cspc = self.data_cspc
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self.dataOutObj.data_dc = self.data_dc
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return 1
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class SpectraWriter(JRODataWriter):
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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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dataOutObj = None
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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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def __init__(self, dataOutObj=None):
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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.dataOutObj
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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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if dataOutObj == None:
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dataOutObj = Spectra()
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if not( isinstance(dataOutObj, Spectra) ):
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raise ValueError, "in SpectraReader, dataOutObj must be an Spectra class object"
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self.dataOutObj = dataOutObj
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self.ext = ".pdata"
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self.optchar = "P"
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self.shape_spc_Buffer = None
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self.shape_cspc_Buffer = None
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self.shape_dc_Buffer = None
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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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####################################
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self.fp = None
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self.nWriteBlocks = 0
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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.flagNoMoreFiles = 0
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self.setFile = None
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self.dataType = None
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self.path = None
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self.noMoreFiles = 0
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self.filename = None
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self.basicHeaderObj = BasicHeader()
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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):
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return 1
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def setBlockDimension(self):
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"""
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Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
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Affected:
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self.shape_spc_Buffer
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self.shape_cspc_Buffer
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self.shape_dc_Buffer
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Return: None
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"""
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self.shape_spc_Buffer = (self.dataOutObj.nChannels,
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self.processingHeaderObj.numHeights,
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self.processingHeaderObj.profilesPerBlock)
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self.shape_cspc_Buffer = (self.dataOutObj.nPairs,
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self.processingHeaderObj.numHeights,
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self.processingHeaderObj.profilesPerBlock)
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self.shape_dc_Buffer = (self.systemHeaderObj.numChannels,
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self.processingHeaderObj.numHeights)
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def writeBlock(self):
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"""
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Escribe el buffer en el file designado
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Affected:
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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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self.flagIsNewFile
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self.flagIsNewBlock
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self.nTotalBlocks
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self.nWriteBlocks
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Return: None
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"""
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spc = numpy.transpose( self.data_spc, (0,2,1) )
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if not( self.processingHeaderObj.shif_fft ):
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spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
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data = spc.reshape((-1))
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data.tofile(self.fp)
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if self.data_cspc != None:
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data = numpy.zeros( self.shape_cspc_Buffer, self.dataType )
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cspc = numpy.transpose( self.data_cspc, (0,2,1) )
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|
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if not( self.processingHeaderObj.shif_fft ):
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|
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)
|
|
|
|
|
|
data = numpy.zeros( self.shape_dc_Buffer, self.dataType )
|
|
|
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
|
|
|
|
|
|
|
|
|
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
|
|
|
"""
|
|
|
self.flagIsNewBlock = 0
|
|
|
|
|
|
if self.dataOutObj.flagNoData:
|
|
|
return 0
|
|
|
|
|
|
if self.dataOutObj.flagTimeBlock:
|
|
|
self.data_spc.fill(0)
|
|
|
self.data_cspc.fill(0)
|
|
|
self.data_dc.fill(0)
|
|
|
self.setNextFile()
|
|
|
|
|
|
self.data_spc = self.dataOutObj.data_spc
|
|
|
self.data_cspc = self.dataOutObj.data_cspc
|
|
|
self.data_dc = self.dataOutObj.data_dc
|
|
|
|
|
|
# #self.processingHeaderObj.dataBlocksPerFile)
|
|
|
if self.hasAllDataInBuffer():
|
|
|
self.getDataHeader()
|
|
|
self.writeNextBlock()
|
|
|
|
|
|
if self.flagNoMoreFiles:
|
|
|
#print 'Process finished'
|
|
|
return 0
|
|
|
|
|
|
return 1
|
