schain Commit - r1524:069b388a2dbe · Jicamarca Repository

Adicion de atributo dataPP_NOISE en el Met. PulsePair

avaldezp -

r1524:069b388a2dbe

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r1524:069b388a2dbe

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schainpy/model/proc/jroproc_parameters.py +15 -11

                         if hasattr(self.dataIn, 'dataPP_CCF'):
                             self.dataOut.dataPP_CCF = self.dataIn.dataPP_CCF
+                        if hasattr(self.dataIn, 'dataPP_NOISE'):
+                            self.dataOut.dataPP_NOISE = self.dataIn.dataPP_NOISE
                         if hasattr(self.dataIn, 'flagAskMode'):
                             self.dataOut.flagAskMode = self.dataIn.flagAskMode
                 Conversion Watt
                 Referencia
                 https://www.tek.com/en/blog/calculating-rf-power-iq-samples
                 data_param = (nCh, 8, nHeis)
                 S, V, W, SNR, Z, D, P, R
                 Power, Velocity, Spectral width, SNR, Reflectivity, Differential reflectivity, PHI DP, RHO HV
                 '''
                 isConfig  = False
                 variableList = None
                             dataOut.data_param[:,6,:] =self.getFasediferencialPhiD_P(dataOut=dataOut, phase=True)
                         if self.variableList[i] == 'R' and dataOut.nChannels>1:
                             dataOut.data_param[:,7,:] = self.getCoeficienteCorrelacionROhv_R(dataOut)
                     return dataOut
             class PedestalInformation(Operation):
                       elif sigma_ele < .5:
                         flag_mode = 'PPI'
                         break
                       elif sigma_azi < .5:
                         flag_mode = 'RHI'
                         break
                       start += sample_max
                     print("MODE: ",flag_mode)
                     return flag_mode
                 def get_values(self):
                     self.mode = mode
                     if mode is None:
                         self.flagAskMode = True
                     filelist = self.find_file(dataOut.utctime)
                     if not filelist:
                                     #Se borra el dato anterior para liberar buffer y comparar el dato actual con el siguiente
                                     self.__buffer.pop(0) #Erase first data
                                     self.__buffer2.pop(0)
                                     self.__buffer3.pop(0)
                                     self.__profIndex -= 1
                                 else: #Cuando ha estado de bajada y ha vuelto a subir
                                     #Se borra el último dato
                                     self.__buffer.pop() #Erase last data
                                     self.__buffer2.pop()
                                     self.__buffer3.pop()
                                     data_360, n, data_p, data_e  = self.pushData(data=dataOut,flagMode=flagMode,case_flag=case_flag)
                                     self.__dataReady = True
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         setattr(dataOut, attr_data, data_360 )
                         dataOut.data_azi  = data_p + 26.2
                         dataOut.data_azi[dataOut.data_azi>360] = dataOut.data_azi[dataOut.data_azi>360] - 360
                         dataOut.data_ele  = data_e

schainpy/model/proc/jroproc_voltage.py +10 -8

                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux/pwcode ,self.nCohInt)
+                    data_noise       = self.noise
                     self.noise       = self.noise.reshape(self.__nch,1)
                     self.noise       = numpy.tile(self.noise,[1,self.__nHeis])
                     noise_buffer     = self.noise.reshape(self.__nch,1,self.__nHeis)
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = data_power
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/((self.n-1)*pwcode*self.nCohInt)
                     R1               = numpy.abs(lag_1)
                     self.__buffer    = numpy.zeros((self.__nch, self.__nProf,self.__nHeis),  dtype='complex')
                     self.__profIndex = 0
-                    return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n
+                    return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,data_noise,n
                 def pulsePairbyProfiles(self,dataOut,n):
                     data_specwidth       =  None
                     data_snrPP           =  None
                     data_ccf             =  None
+                    data_noise           =  None
                     if dataOut.flagDataAsBlock:
                         self.putDataByBlock(data=dataOut.data,n=n)
                     else:
                         self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
-                        data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n   = self.pushData(dataOut=dataOut)
+                        data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf,data_noise, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
-                    return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf
+                    return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf,data_noise
                 def pulsePairOp(self, dataOut, n, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
-                    data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n)
+                    data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf,data_noise = self.pulsePairbyProfiles(dataOut,n)
                     self.__lastdatatime           = datatime
                     if data_power is None:
-                        return None, None, None,None,None,None,None
+                        return None, None, None,None,None,None,None,None
                     avgdatatime    = self.__initime
                     deltatime      = datatime - self.__lastdatatime
                     self.__initime = datatime
-                    return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime
+                    return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, data_noise, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,wradar=False,**kwargs):
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , wradar=wradar,**kwargs)
                         self.isConfig   = True
-                    data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime)
+                    data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, data_noise,avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.dataPP_CCF      = data_ccf
+                        dataOut.dataPP_NOISE    = data_noise
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime

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