schain Commit - r268:43faa0eea275 · Jicamarca Repository

En jrodata.py no se considera el factor para el caso del filtro en alturas, por el momento solo se realiza la suma de los valores sin ninguna division o normalizacion de este resultado, verficar en jroprocessing.py....

Daniel Valdez -

r268:43faa0eea275

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r268:43faa0eea275

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schainpy/model/jrodata.py +1 -1

                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
-                    normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*self.windowOfFilter*pwcode
+                    normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode
                     return normFactor

schainpy/model/jrodataIO.py +7 -7

                     if self.fp != None:
                         self.fp.close()
-                    timeTuple = time.localtime( self.dataOut.dataUtcTime)
+                    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( self.readNextBlock() ):
                             return 0
-                        self.dataOut.dtype = self.dtype
+                        self.dataOut.dtype = numpy.dtype([('real','<f8'),('imag','<f8')]) #self.dtype
                         self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock
                             #desplaza a la derecha en el eje 2 determinadas posiciones
                             cspc = numpy.roll( cspc, shift, axis=2 )
-                        self.processingHeaderObj.shif_fft = True
+            #            self.processingHeaderObj.shif_fft = True
                     spc = numpy.transpose( spc, (0,2,1) )
                     self.data_spc = spc
                     self.dataOut.flagNoData = False
-                    self.dataOut.dtype = self.dtype
+                    self.dataOut.dtype = numpy.dtype([('real','<f8'),('imag','<f8')])#self.dtype
             #        self.dataOut.nChannels = self.nRdChannels
                     if self.flagIsNewFile == 0:
                         self.getBasicHeader()
-                    self.data_spc = self.dataOut.data_spc
+                    self.data_spc = self.dataOut.data_spc.copy()
-                    self.data_cspc = self.dataOut.data_cspc
+                    self.data_cspc = self.dataOut.data_cspc.copy()
-                    self.data_dc = self.dataOut.data_dc
+                    self.data_dc = self.dataOut.data_dc.copy()
                     # #self.processingHeaderObj.dataBlocksPerFile)
                     if self.hasAllDataInBuffer():

schainpy/model/jroheaderIO.py +6 -4

                     return 1
                 def write(self, fp):
+                    self.utc -= self.__LOCALTIME
                     headerTuple = (self.size,self.version,self.dataBlock,self.utc,self.miliSecond,self.timeZone,self.dstFlag,self.errorCount)
                     header = numpy.array(headerTuple,self.struct)
                     header.tofile(fp)
                         if ((self.processFlags & PROCFLAG.DEFINE_PROCESS_CODE) == PROCFLAG.DEFINE_PROCESS_CODE):
                             self.nCode = int(numpy.fromfile(fp,'<u4',1))
                             self.nBaud = int(numpy.fromfile(fp,'<u4',1))
-                            self.code = numpy.fromfile(fp,'<f4',self.nCode*self.nBaud).reshape(self.nBaud,self.nCode)
+                            self.code = numpy.fromfile(fp,'<f4',self.nCode*self.nBaud).reshape(self.nCode,self.nBaud)
                         if ((self.processFlags & PROCFLAG.SHIFT_FFT_DATA) == PROCFLAG.SHIFT_FFT_DATA):
                             self.shif_fft = True
                     if self.processFlags & PROCFLAG.DEFINE_PROCESS_CODE == PROCFLAG.DEFINE_PROCESS_CODE:
-                        nCode = self.nCode #Probar con un dato que almacene codigo, hasta el momento no se hizo la prueba
+                        nCode = numpy.array([self.nCode], numpy.dtype('u4')) #Probar con un dato que almacene codigo, hasta el momento no se hizo la prueba
                         nCode.tofile(fp)
-                        nBaud = self.nBaud
+                        nBaud = numpy.array([self.nBaud], numpy.dtype('u4'))
                         nBaud.tofile(fp)
-                        code = self.code.reshape(nCode*nBaud)
+                        code = self.code.reshape(self.nCode*self.nBaud)
+                        code = code.astype(numpy.dtype('<f4'))
                         code.tofile(fp)
                     return 1

schainpy/model/jroplot.py +22 -11

                             counter += 1
                 def run(self, dataOut, idfigure, wintitle="", pairsList=None, showprofile='True',
-                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
+                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, normalize=True,
                         save=False, figpath='./', figfile=None,
                         power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r'):
                     if len(pairsIndexList) > 4:
                         pairsIndexList = pairsIndexList[0:4]
-                    factor = dataOut.normFactor
+                    factor = 1
+                    if normalize:
+                        factor = dataOut.normFactor
                     x = dataOut.getVelRange(1)
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc[:,:,:]/factor
-            #        z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     noise = dataOut.getNoise()/factor
                             counter += 1
                 def run(self, dataOut, idfigure, wintitle="", channelList=None, showprofile='True',
-                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
+                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, normalize=True,
                         timerange=None,
                         save=False, figpath='./', figfile=None):
                     tmin = None
                     tmax = None
-                    factor = dataOut.normFactor
+                    factor = 1
+                    if normalize:
+                        factor = dataOut.normFactor
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
                             counter += 1
                 def run(self, dataOut, idfigure, wintitle="", channelList=None, showprofile='True',
-                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
+                        xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, normalize=True,
                         save=False, figpath='./', figfile=None):
                     """
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
-                    factor = dataOut.normFactor
+                    factor = 1
+                    if normalize:
+                        factor = dataOut.normFactor
                     x = dataOut.getVelRange(1)
                     y = dataOut.getHeiRange()
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                 def run(self, dataOut, idfigure, wintitle="", channelList=None,
-                        xmin=None, xmax=None, ymin=None, ymax=None,
+                        xmin=None, xmax=None, ymin=None, ymax=None, normalize=True,
                         save=False, figpath='./', figfile=None):
                     if channelList == None:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
-                    factor = dataOut.normFactor
+                    factor = 1
+                    if normalize:
+                        factor = dataOut.normFactor
                     y = dataOut.getHeiRange()
                     x = dataOut.data_spc[channelIndexList,:,:]/factor
                     x = numpy.where(numpy.isfinite(x), x, numpy.NAN)
                 def run(self, dataOut, idfigure, wintitle="", channelList=None, showprofile='True',
-                        xmin=None, xmax=None, ymin=None, ymax=None,
+                        xmin=None, xmax=None, ymin=None, ymax=None, normalize=True,
                         timerange=None,
                         save=False, figpath='./', figfile=None):
                     tmax = None
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
-                    factor = dataOut.normFactor
+                    factor = 1
+                    if normalize:
+                        factor = dataOut.normFactor
                     noise = dataOut.getNoise()/factor
                     noisedB = 10*numpy.log10(noise)

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