| @@ -3976,8 +3976,8 class WeatherRadar(Operation): | |||
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3976 | 3976 | data_param[:,0,:] = dataOut.data_POW/(factor) |
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3977 | 3977 | data_param[:,1,:] = dataOut.data_DOP |
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3978 | 3978 | data_param[:,2,:] = dataOut.data_WIDTH |
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3979 |
data_param[:,3,:] = dataOut.data_SNR |
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3980 | ||
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3979 | data_param[:,3,:] = dataOut.data_SNR | |
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3980 | ||
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3981 | 3981 | return data_param |
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3982 | 3982 | |
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3983 | 3983 | def getCoeficienteCorrelacionROhv_R(self,dataOut): |
| @@ -4041,9 +4041,9 class WeatherRadar(Operation): | |||
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4041 | 4041 | #print("Pr last10",10*numpy.log10(Pr[0,-20:])) |
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4042 | 4042 | #print("LCTE",10*numpy.log10(self.lambda_**4/( numpy.pi**5 * self.Km**2))) |
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4043 | 4043 | if self.Pt<0.3: |
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4044 |
factor= |
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4044 | factor=17 | |
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4045 | 4045 | else: |
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4046 | factor=0 | |
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4046 | factor=30 | |
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4047 | 4047 | |
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4048 | 4048 | dBZeh = 10*numpy.log10(Zeh) + factor |
|
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4049 | 4049 | if type=='N': |
| @@ -4068,7 +4068,7 class WeatherRadar(Operation): | |||
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4068 | 4068 | self.setup(dataOut= dataOut,variableList=variableList,Pt=Pt,Gt=Gt,Gr=Gr,Glna=Glna,lambda_=lambda_, aL=aL, |
|
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4069 | 4069 | tauW= tauW,thetaT=thetaT,thetaR=thetaR,Km =Km) |
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4070 | 4070 | self.isConfig = True |
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4071 | ||
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4071 | ||
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4072 | 4072 | dataOut.data_param = self.setMoments(dataOut) |
|
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4073 | 4073 | |
|
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4074 | 4074 | for i in range(len(self.variableList)): |
| @@ -4175,7 +4175,7 class PedestalInformation(Operation): | |||
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4175 | 4175 | continue |
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4176 | 4176 | sigma_ele = numpy.nanstd(ele[start:start+sample_max]) |
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4177 | 4177 | sigma_azi = numpy.nanstd(azi[start:start+sample_max]) |
|
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4178 | ||
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4178 | ||
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4179 | 4179 | if sigma_ele<.5 and sigma_azi<.5: |
|
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4180 | 4180 | if sigma_ele<sigma_azi: |
|
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4181 | 4181 | flag_mode = 'PPI' |
| @@ -4213,7 +4213,7 class PedestalInformation(Operation): | |||
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4213 | 4213 | mode = self.find_mode(index) |
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4214 | 4214 | else: |
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4215 | 4215 | mode = self.mode |
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4216 | ||
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4216 | ||
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4217 | 4217 | if mode is not None: |
|
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4218 | 4218 | return self.fp['Data']['azi_pos'][index], self.fp['Data']['ele_pos'][index], mode |
|
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4219 | 4219 | else: |
| @@ -4309,8 +4309,8 class Block360(Operation): | |||
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4309 | 4309 | ''' |
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4310 | 4310 | Add a profile to he __buffer and increase in one the __profiel Index |
|
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4311 | 4311 | ''' |
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4312 |
tmp= getattr(data, attr) |
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4313 | ||
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4312 | tmp= getattr(data, attr) | |
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4313 | ||
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4314 | 4314 | self.__buffer.append(tmp) |
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4315 | 4315 | self.__buffer2.append(data.azimuth) |
|
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4316 | 4316 | self.__buffer3.append(data.elevation) |
| @@ -4326,8 +4326,8 class Block360(Operation): | |||
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4326 | 4326 | ''' |
|
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4327 | 4327 | Return the PULSEPAIR and the profiles used in the operation |
|
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4328 | 4328 | Affected : self.__profileIndex |
|
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4329 |
''' |
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4330 | ||
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4329 | ''' | |
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4330 | ||
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4331 | 4331 | data_360 = numpy.array(self.__buffer).transpose(1, 0, 2) |
|
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4332 | 4332 | data_snr = numpy.array(self.__buffer4).transpose(1, 0, 2) |
|
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4333 | 4333 | data_p = numpy.array(self.__buffer2) |
| @@ -4427,7 +4427,7 class Block360(Operation): | |||
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4427 | 4427 | dataOut.attr_data = attr_data |
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4428 | 4428 | dataOut.runNextOp = runNextOp |
|
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4429 | 4429 | dataOut.flagAskMode = False |
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4430 | ||
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4430 | ||
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4431 | 4431 | if dataOut.mode_op == 'PPI': |
|
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4432 | 4432 | dataOut.flagMode = 1 |
|
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4433 | 4433 | elif dataOut.mode_op == 'RHI': |
| @@ -4445,7 +4445,7 class Block360(Operation): | |||
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4445 | 4445 | setattr(dataOut, attr_data, data_360 ) |
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4446 | 4446 | dataOut.data_snr = data_snr |
|
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4447 | 4447 | dataOut.data_azi = data_p + 26.2 |
|
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4448 |
dataOut.data_azi[dataOut.data_azi>360] = dataOut.data_azi[dataOut.data_azi>360] - 360 |
|
|
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4448 | dataOut.data_azi[dataOut.data_azi>360] = dataOut.data_azi[dataOut.data_azi>360] - 360 | |
|
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4449 | 4449 | dataOut.data_ele = data_e |
|
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4450 | 4450 | dataOut.utctime = avgdatatime |
|
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4451 | 4451 | dataOut.flagNoData = False |
| @@ -4525,15 +4525,14 class MergeProc(ProcessingUnit): | |||
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4525 | 4525 | |
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4526 | 4526 | f = [getattr(data, attr_data) for data in data_inputs][0] |
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4527 | 4527 | g = [getattr(data, attr_data) for data in data_inputs][1] |
|
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4528 |
data = numpy.concatenate((f,g),axis=2) |
|
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4528 | data = numpy.concatenate((f,g),axis=2) | |
|
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4529 | 4529 | setattr(self.dataOut, attr_data, data) |
|
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4530 | 4530 | |
|
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4531 | 4531 | # snr |
|
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4532 | 4532 | self.dataOut.data_snr = numpy.concatenate((data_inputs[0].data_snr, data_inputs[1].data_snr), axis=2) |
|
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4533 | ||
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4533 | ||
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4534 | 4534 | # ranges |
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4535 | 4535 | dh = self.dataOut.heightList[1]-self.dataOut.heightList[0] |
|
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4536 | 4536 | heightList_2 = (self.dataOut.heightList[-1]+dh) + numpy.arange(g.shape[-1], dtype=numpy.float) * dh |
|
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4537 | 4537 | |
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4538 | 4538 | self.dataOut.heightList = numpy.concatenate((self.dataOut.heightList,heightList_2)) |
|
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4539 | ||
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