##// END OF EJS Templates
schain-jc
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-Corrections to Vmax calculation...
Julio Valdez -
r850:5a02664c0d53
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@@ -305,7 +305,7 class JROData(GenericData):
305
305
306 _lambda = self.C/self.frequency
306 _lambda = self.C/self.frequency
307
307
308 vmax = self.getFmax() * _lambda
308 vmax = self.getFmax() * _lambda/2
309
309
310 return vmax
310 return vmax
311
311
@@ -484,8 +484,10 class Voltage(JROData):
484 data = self.data
484 data = self.data
485
485
486 power = data * numpy.conjugate(data)
486 power = data * numpy.conjugate(data)
487 powerdB = 10*numpy.log10(power.real)
488 powerdB = numpy.squeeze(powerdB)
487
489
488 return 10*numpy.log10(power.real)
490 return powerdB
489
491
490 def getTimeInterval(self):
492 def getTimeInterval(self):
491
493
@@ -638,7 +640,7 class Spectra(JROData):
638 def getVelRange(self, extrapoints=0):
640 def getVelRange(self, extrapoints=0):
639
641
640 deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor)
642 deltav = self.getVmax() / (self.nFFTPoints*self.ippFactor)
641 velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) - deltav/2
643 velrange = deltav*(numpy.arange(self.nFFTPoints+extrapoints)-self.nFFTPoints/2.) #- deltav/2
642
644
643 return velrange
645 return velrange
644
646
@@ -926,33 +928,39 class Fits(JROData):
926 ltctime = property(getltctime, "I'm the 'ltctime' property")
928 ltctime = property(getltctime, "I'm the 'ltctime' property")
927 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
929 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
928
930
931
929 class Correlation(JROData):
932 class Correlation(JROData):
930
933
931 noise = None
934 noise = None
932
935
933 SNR = None
936 SNR = None
934
937
935 pairsAutoCorr = None #Pairs of Autocorrelation
936
937 #--------------------------------------------------
938 #--------------------------------------------------
938
939
939 data_corr = None
940 mode = None
941
942 split = False
940
943
941 data_volt = None
944 data_cf = None
942
945
943 lagT = None # each element value is a profileIndex
946 lags = None
944
947
945 lagR = None # each element value is in km
948 lagRange = None
946
949
947 pairsList = None
950 pairsList = None
948
951
949 calculateVelocity = None
952 normFactor = None
953
954 #--------------------------------------------------
955
956 # calculateVelocity = None
950
957
951 nPoints = None
958 nLags = None
959
960 nPairs = None
952
961
953 nAvg = None
962 nAvg = None
954
963
955 bufferSize = None
956
964
957 def __init__(self):
965 def __init__(self):
958 '''
966 '''
@@ -996,55 +1004,10 class Correlation(JROData):
996
1004
997 self.nPoints = None
1005 self.nPoints = None
998
1006
999 def getLagTRange(self, extrapoints=0):
1000
1001 lagTRange = self.lagT
1002 diff = lagTRange[1] - lagTRange[0]
1003 extra = numpy.arange(1,extrapoints + 1)*diff + lagTRange[-1]
1004 lagTRange = numpy.hstack((lagTRange, extra))
1005
1006 return lagTRange
1007
1008 def getLagRRange(self, extrapoints=0):
1009
1010 return self.lagR
1011
1012 def getPairsList(self):
1007 def getPairsList(self):
1013
1008
1014 return self.pairsList
1009 return self.pairsList
1015
1010
1016 def getCalculateVelocity(self):
1017
1018 return self.calculateVelocity
1019
1020 def getNPoints(self):
1021
1022 return self.nPoints
1023
1024 def getNAvg(self):
1025
1026 return self.nAvg
1027
1028 def getBufferSize(self):
1029
1030 return self.bufferSize
1031
1032 def getPairsAutoCorr(self):
1033 pairsList = self.pairsList
1034 pairsAutoCorr = numpy.zeros(self.nChannels, dtype = 'int')*numpy.nan
1035
1036 for l in range(len(pairsList)):
1037 firstChannel = pairsList[l][0]
1038 secondChannel = pairsList[l][1]
1039
1040 #Obteniendo pares de Autocorrelacion
1041 if firstChannel == secondChannel:
1042 pairsAutoCorr[firstChannel] = int(l)
1043
1044 pairsAutoCorr = pairsAutoCorr.astype(int)
1045
1046 return pairsAutoCorr
1047
1048 def getNoise(self, mode = 2):
1011 def getNoise(self, mode = 2):
1049
1012
1050 indR = numpy.where(self.lagR == 0)[0][0]
1013 indR = numpy.where(self.lagR == 0)[0][0]
@@ -1092,17 +1055,53 class Correlation(JROData):
1092
1055
1093 def getTimeInterval(self):
1056 def getTimeInterval(self):
1094
1057
1095 timeInterval = self.ippSeconds * self.nCohInt * self.nPoints
1058 timeInterval = self.ippSeconds * self.nCohInt * self.nProfiles
1096
1059
1097 return timeInterval
1060 return timeInterval
1098
1061
1099 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
1062 def splitFunctions(self):
1100 # pairsList = property(getPairsList, "I'm the 'pairsList' property.")
1063
1101 # nPoints = property(getNPoints, "I'm the 'nPoints' property.")
1064 pairsList = self.pairsList
1102 calculateVelocity = property(getCalculateVelocity, "I'm the 'calculateVelocity' property.")
1065 ccf_pairs = []
1103 nAvg = property(getNAvg, "I'm the 'nAvg' property.")
1066 acf_pairs = []
1104 bufferSize = property(getBufferSize, "I'm the 'bufferSize' property.")
1067 ccf_ind = []
1068 acf_ind = []
1069 for l in range(len(pairsList)):
1070 chan0 = pairsList[l][0]
1071 chan1 = pairsList[l][1]
1072
1073 #Obteniendo pares de Autocorrelacion
1074 if chan0 == chan1:
1075 acf_pairs.append(chan0)
1076 acf_ind.append(l)
1077 else:
1078 ccf_pairs.append(pairsList[l])
1079 ccf_ind.append(l)
1105
1080
1081 data_acf = self.data_cf[acf_ind]
1082 data_ccf = self.data_cf[ccf_ind]
1083
1084 return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf
1085
1086 def getNormFactor(self):
1087 acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions()
1088 acf_pairs = numpy.array(acf_pairs)
1089 normFactor = numpy.zeros((self.nPairs,self.nHeights))
1090
1091 for p in range(self.nPairs):
1092 pair = self.pairsList[p]
1093
1094 ch0 = pair[0]
1095 ch1 = pair[1]
1096
1097 ch0_max = numpy.max(data_acf[acf_pairs==ch0,:,:], axis=1)
1098 ch1_max = numpy.max(data_acf[acf_pairs==ch1,:,:], axis=1)
1099 normFactor[p,:] = numpy.sqrt(ch0_max*ch1_max)
1100
1101 return normFactor
1102
1103 timeInterval = property(getTimeInterval, "I'm the 'timeInterval' property")
1104 normFactor = property(getNormFactor, "I'm the 'normFactor property'")
1106
1105
1107 class Parameters(JROData):
1106 class Parameters(JROData):
1108
1107
@@ -1152,6 +1151,7 class Parameters(JROData):
1152
1151
1153 data_output = None #Out signal
1152 data_output = None #Out signal
1154
1153
1154 nAvg = None
1155
1155
1156
1156
1157 def __init__(self):
1157 def __init__(self):
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