schain Commit - r1668:8880a814f9ea · Jicamarca Repository

Update jroproc_base.py Queue size y jroproc_spectra.py

Alexander Valdez -

r1668:8880a814f9ea

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r1668:8880a814f9ea

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schainpy/model/proc/jroproc_base.py +1 -1

              must be used in plotting and writing operations to allow to run as an
              external process.
              '''
+             # repositorio master
              import inspect
              import zmq
              import time

schainpy/model/proc/jroproc_spectra.py +46 -13

              import time
              import itertools
              import numpy
              # repositorio
              from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation
                          if self.dataIn.flagDataAsBlock:
                              nVoltProfiles = self.dataIn.data.shape[1]
                              if nVoltProfiles == nProfiles:
                                  self.buffer = self.dataIn.data.copy()
                                  self.profIndex = nVoltProfiles
                                  self.profIndex += nVoltProfiles
                                  self.id_min += nVoltProfiles
                                  self.id_max += nVoltProfiles
+                             elif nVoltProfiles > nProfiles:
+                                 self.reader.bypass = True
+                                 if self.profIndex == 0:
+                                     self.id_min = 0
+                                     self.id_max = nProfiles
+                                 self.buffer = self.dataIn.data[:, self.id_min:self.id_max,:]
+                                 self.profIndex += nProfiles
+                                 self.id_min += nProfiles
+                                 self.id_max += nProfiles
+                                 if self.id_max == nVoltProfiles:
+                                     self.reader.bypass = False
                              else:
                                  raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % (
                                      self.dataIn.type, self.dataIn.data.shape[1], nProfiles))
                              self.__getFft()
                              self.dataOut.flagNoData = False
                              self.firstdatatime = None
-                             self.profIndex = 0
+                             if not self.reader.bypass:
+                                 self.profIndex = 0
                      else:
                          raise ValueError("The type of input object '%s' is not valid".format(
                              self.dataIn.type))
                      return
-                 def selectFFTs(self, minFFT, maxFFT ):
+                 def selectFFTs(self, minFFT, maxFFT):
                      """
                      Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango
                      minFFT<= FFT <= maxFFT
                          if val >= beacon_dB[0]:
                              beacon_heiIndexList.append(avg_dB.tolist().index(val))
-                     #data_spc = data_spc[:,:,beacon_heiIndexList]
                      data_cspc = None
                      if self.dataOut.data_cspc is not None:
                          data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
-                         #data_cspc = data_cspc[:,:,beacon_heiIndexList]
                      data_dc = None
                      if self.dataOut.data_dc is not None:
                          data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
-                         #data_dc = data_dc[:,beacon_heiIndexList]
                      self.dataOut.data_spc = data_spc
                      self.dataOut.data_cspc = data_cspc
                      for i in range(cspc.shape[0]):
                          LinePower= numpy.sum(realCspc[i], axis=0)
                          Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)]
-                         SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ]
-                         InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 )
+                         SelectedHeights = Heights[ numpy.where(LinePower < Threshold) ]
+                         InterferenceSum = numpy.sum(realCspc[i,:,SelectedHeights],axis=0)
                          InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)]
                          InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)]
-                         InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) )
+                         InterferenceRange = numpy.where(([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) )
                          #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax]))
                          if len(InterferenceRange)<int(cspc.shape[1]*0.3):
                              cspc[i,InterferenceRange,:] = numpy.NaN
                      self.dataOut.data_cspc = cspc
-                 def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None):
+                 def removeInterference(self, interf=2, hei_interf=None, nhei_interf=None, offhei_interf=None):
                      jspectra = self.dataOut.data_spc
                      jcspectra = self.dataOut.data_cspc
                      return 1
-                 def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1):
+                 def run(self, dataOut, interf=2,hei_interf=None, nhei_interf=None, offhei_interf=None, mode=1):
                      self.dataOut = dataOut
                      if mode == 1:
-                         self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None)
+                         self.removeInterference(interf=2,hei_interf=None, nhei_interf=None, offhei_interf=None)
                      elif mode == 2:
                          self.removeInterference2()
                      return self.dataOut
+             class deflip(Operation):
+                 def run(self, dataOut):
+                     # arreglo 1: (num_chan, num_profiles, num_heights)
+                     self.dataOut = dataOut
+                     # JULIA-oblicua, indice 2
+                     # arreglo 2: (num_profiles, num_heights)
+                     jspectra = self.dataOut.data_spc[2]
+                     jspectra_tmp=numpy.zeros(jspectra.shape)
+                     num_profiles=jspectra.shape[0]
+                     freq_dc = int(num_profiles / 2)
+                     # Flip con for
+                     for j in range(num_profiles):
+                      jspectra_tmp[num_profiles-j-1]= jspectra[j]
+                     # Intercambio perfil de DC con perfil inmediato anterior
+                     jspectra_tmp[freq_dc-1]= jspectra[freq_dc-1]
+                     jspectra_tmp[freq_dc]= jspectra[freq_dc]
+                     # canal modificado es re-escrito en el arreglo de canales
+                     self.dataOut.data_spc[2] = jspectra_tmp
+                     return self.dataOut
              class IncohInt(Operation):
                  __profIndex = 0

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