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Se agregaron las propiedades flag_cspc y flag_dc a la clase Spectra...
Miguel Valdez -
r266:ab6d630dba95
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@@ -483,9 +483,25 class Spectra(JROData):
483 483
484 484 return normFactor
485 485
486 def getFlagCspc(self):
487
488 if self.data_cspc == None:
489 return True
490
491 return False
492
493 def getFlagDc(self):
494
495 if self.data_dc == None:
496 return True
497
498 return False
499
486 500 nPairs = property(getNPairs, "I'm the 'nPairs' property.")
487 501 pairsIndexList = property(getPairsIndexList, "I'm the 'pairsIndexList' property.")
488 502 normFactor = property(getNormFactor, "I'm the 'getNormFactor' property.")
503 flag_cspc = property(getFlagCspc)
504 flag_dc = property(getFlagDc)
489 505
490 506 class SpectraHeis(JROData):
491 507
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@@ -1965,7 +1965,8 class SpectraReader(JRODataReader):
1965 1965 if self.processingHeaderObj.flag_cspc:
1966 1966 #desplaza a la derecha en el eje 2 determinadas posiciones
1967 1967 cspc = numpy.roll( cspc, shift, axis=2 )
1968
1968
1969 self.processingHeaderObj.shif_fft = True
1969 1970
1970 1971 spc = numpy.transpose( spc, (0,2,1) )
1971 1972 self.data_spc = spc
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@@ -829,7 +829,128 class SpectraProc(ProcessingUnit):
829 829
830 830 return 1
831 831
832 def selectHeights(self, minHei, maxHei):
833 """
834 Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
835 minHei <= height <= maxHei
836
837 Input:
838 minHei : valor minimo de altura a considerar
839 maxHei : valor maximo de altura a considerar
840
841 Affected:
842 Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
843
844 Return:
845 1 si el metodo se ejecuto con exito caso contrario devuelve 0
846 """
847 if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
848 raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
849
850 if (maxHei > self.dataOut.heightList[-1]):
851 maxHei = self.dataOut.heightList[-1]
852 # raise ValueError, "some value in (%d,%d) is not valid" % (minHei, maxHei)
853
854 minIndex = 0
855 maxIndex = 0
856 heights = self.dataOut.heightList
857
858 inda = numpy.where(heights >= minHei)
859 indb = numpy.where(heights <= maxHei)
860
861 try:
862 minIndex = inda[0][0]
863 except:
864 minIndex = 0
865
866 try:
867 maxIndex = indb[0][-1]
868 except:
869 maxIndex = len(heights)
870
871 self.selectHeightsByIndex(minIndex, maxIndex)
872
873 return 1
874
875
876 def selectHeightsByIndex(self, minIndex, maxIndex):
877 """
878 Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
879 minIndex <= index <= maxIndex
880
881 Input:
882 minIndex : valor de indice minimo de altura a considerar
883 maxIndex : valor de indice maximo de altura a considerar
884
885 Affected:
886 self.dataOut.data_spc
887 self.dataOut.data_cspc
888 self.dataOut.data_dc
889 self.dataOut.heightList
890
891 Return:
892 1 si el metodo se ejecuto con exito caso contrario devuelve 0
893 """
894
895 if (minIndex < 0) or (minIndex > maxIndex):
896 raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
897
898 if (maxIndex >= self.dataOut.nHeights):
899 maxIndex = self.dataOut.nHeights-1
900 # raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
901
902 nHeights = maxIndex - minIndex + 1
832 903
904 #Spectra
905 data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
906
907 data_cspc = None
908 if self.dataOut.data_cspc != None:
909 data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
910
911 data_dc = None
912 if self.dataOut.data_dc != None:
913 data_dc = self.dataOut.data_dc[:,:,minIndex:maxIndex+1]
914
915 self.dataOut.data_spc = data_spc
916 self.dataOut.data_cspc = data_cspc
917 self.dataOut.data_dc = data_dc
918
919 self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex+1]
920
921 return 1
922
923 def removeDC(self, mode = 1):
924
925 dc_index = 0
926 freq_index = numpy.array([-2,-1,1,2])
927 data_spc = self.dataOut.data_spc
928 data_cspc = self.dataOut.data_cspc
929 data_dc = self.dataOut.data_dc
930
931 if self.dataOut.flagShiftFFT:
932 dc_index += self.dataOut.nFFTPoints/2
933 freq_index += self.dataOut.nFFTPoints/2
934
935 if mode == 1:
936 data_spc[dc_index] = (data_spc[:,freq_index[1],:] + data_spc[:,freq_index[2],:])/2
937 if data_cspc != None:
938 data_cspc[dc_index] = (data_cspc[:,freq_index[1],:] + data_cspc[:,freq_index[2],:])/2
939 return 1
940
941 if mode == 2:
942 pass
943
944 if mode == 3:
945 pass
946
947 raise ValueError, "mode parameter has to be 1, 2 or 3"
948
949 def removeInterference(self):
950
951 pass
952
953
833 954 class IncohInt(Operation):
834 955
835 956
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