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@@ -395,7 +395,15 class WeatherPlot(Plot):
395 395
396 396 data = {}
397 397 meta = {}
398 data['weather'] = 10*numpy.log10(dataOut.data_360[0]/(250.0))
398 if hasattr(dataOut, 'dataPP_POWER'):
399 factor = 1
400
401 if hasattr(dataOut, 'nFFTPoints'):
402 factor = dataOut.normFactor
403
404 print("factor",factor)
405 data['weather'] = 10*numpy.log10(dataOut.data_360[0]/(factor))
406 print("weather",data['weather'])
399 407 data['azi'] = dataOut.data_azi
400 408 return data, meta
401 409
@@ -498,7 +506,7 class WeatherPlot(Plot):
498 506 cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=1, vmax=60)
499 507 else:
500 508 plt.clf()
501 cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=0, vmax=60)
509 cgax, pm = wrl.vis.plot_ppi(self.res_weather,r=r,az=self.res_azi,fig=self.figures[0], proj='cg', vmin=1, vmax=60)
502 510 caax = cgax.parasites[0]
503 511 paax = cgax.parasites[1]
504 512 cbar = plt.gcf().colorbar(pm, pad=0.075)
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@@ -1286,7 +1286,6 class SpectralMoments(Operation):
1286 1286 vec_snr = numpy.zeros(oldspec.shape[1])
1287 1287
1288 1288 # oldspec = numpy.ma.masked_invalid(oldspec)
1289
1290 1289 for ind in range(oldspec.shape[1]):
1291 1290
1292 1291 spec = oldspec[:,ind]
@@ -1325,7 +1324,7 class SpectralMoments(Operation):
1325 1324 ss1 = m
1326 1325
1327 1326 valid = numpy.arange(int(m + bb0 - ss1 + 1)) + ss1
1328
1327 #valid = numpy.arange(1,oldspec.shape[0])# valid perfil completo igual pulsepair
1329 1328 signal_power = ((spec2[valid] - n0) * fwindow[valid]).mean() # D. Scipión added with correct definition
1330 1329 total_power = (spec2[valid] * fwindow[valid]).mean() # D. Scipión added with correct definition
1331 1330 power = ((spec2[valid] - n0) * fwindow[valid]).sum()
@@ -4099,7 +4098,7 class PedestalInformation(Operation):
4099 4098 #print(len(self.list_adq))
4100 4099 utc_ped_list=[]
4101 4100 for i in range(len(self.list_pedestal)):
4102 print(i)
4101 #print(i)# OJO IDENTIFICADOR DE SINCRONISMO
4103 4102 utc_ped_list.append(self.gettimeutcfromDirFilename(path=self.path_ped,file=self.list_pedestal[i]))
4104 4103
4105 4104 #utc_ped_list= utc_ped_list
@@ -4384,7 +4383,7 class Block360(Operation):
4384 4383 #print("line 4049",data.dataPP_POW.shape,data.dataPP_POW[:10])
4385 4384 #print("line 4049",data.azimuth.shape,data.azimuth)
4386 4385 if self.mode==0:
4387 self.__buffer[:,self.__profIndex,:]= data.dataPP_POW
4386 self.__buffer[:,self.__profIndex,:]= data.dataPP_POWER# PRIMER MOMENTO
4388 4387 if self.mode==1:
4389 4388 self.__buffer[:,self.__profIndex,:]= data.data_pow
4390 4389 #print("me casi",self.index,data.azimuth[self.index])
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@@ -118,7 +118,7 class SpectraProc(ProcessingUnit):
118 118 self.dataOut.flagShiftFFT = False
119 119
120 120 def run(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None, shift_fft=False):
121
121
122 122 if self.dataIn.type == "Spectra":
123 123 self.dataOut.copy(self.dataIn)
124 124 if shift_fft:
@@ -144,7 +144,7 class SpectraProc(ProcessingUnit):
144 144
145 145 if ippFactor == None:
146 146 self.dataOut.ippFactor = 1
147
147
148 148 self.dataOut.nFFTPoints = nFFTPoints
149 149
150 150 if self.buffer is None:
@@ -214,13 +214,13 class SpectraProc(ProcessingUnit):
214 214 self.dataOut.pairsList = pairs
215 215
216 216 return
217
217
218 218 def selectFFTs(self, minFFT, maxFFT ):
219 219 """
220 Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango
220 Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango
221 221 minFFT<= FFT <= maxFFT
222 222 """
223
223
224 224 if (minFFT > maxFFT):
225 225 raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT))
226 226
@@ -250,7 +250,7 class SpectraProc(ProcessingUnit):
250 250 self.selectFFTsByIndex(minIndex, maxIndex)
251 251
252 252 return 1
253
253
254 254 def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None):
255 255 newheis = numpy.where(
256 256 self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex])
@@ -295,7 +295,7 class SpectraProc(ProcessingUnit):
295 295
296 296 def selectFFTsByIndex(self, minIndex, maxIndex):
297 297 """
298
298
299 299 """
300 300
301 301 if (minIndex < 0) or (minIndex > maxIndex):
@@ -318,7 +318,7 class SpectraProc(ProcessingUnit):
318 318 self.dataOut.data_spc = data_spc
319 319 self.dataOut.data_cspc = data_cspc
320 320 self.dataOut.data_dc = data_dc
321
321
322 322 self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1])
323 323 self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1]
324 324 self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1]
@@ -457,7 +457,7 class removeDC(Operation):
457 457 xx_inv = numpy.linalg.inv(xx)
458 458 xx_aux = xx_inv[0, :]
459 459
460 for ich in range(num_chan):
460 for ich in range(num_chan):
461 461 yy = jspectra[ich, ind_vel, :]
462 462 jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy)
463 463
@@ -481,12 +481,12 class removeDC(Operation):
481 481 class removeInterference(Operation):
482 482
483 483 def removeInterference2(self):
484
484
485 485 cspc = self.dataOut.data_cspc
486 486 spc = self.dataOut.data_spc
487 Heights = numpy.arange(cspc.shape[2])
487 Heights = numpy.arange(cspc.shape[2])
488 488 realCspc = numpy.abs(cspc)
489
489
490 490 for i in range(cspc.shape[0]):
491 491 LinePower= numpy.sum(realCspc[i], axis=0)
492 492 Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)]
@@ -494,15 +494,15 class removeInterference(Operation):
494 494 InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 )
495 495 InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)]
496 496 InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)]
497
498
497
498
499 499 InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) )
500 500 #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax]))
501 501 if len(InterferenceRange)<int(cspc.shape[1]*0.3):
502 502 cspc[i,InterferenceRange,:] = numpy.NaN
503
503
504 504 self.dataOut.data_cspc = cspc
505
505
506 506 def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None):
507 507
508 508 jspectra = self.dataOut.data_spc
@@ -751,7 +751,7 class IncohInt(Operation):
751 751 if n is not None:
752 752 self.n = int(n)
753 753 else:
754
754
755 755 self.__integrationtime = int(timeInterval)
756 756 self.n = None
757 757 self.__byTime = True
@@ -852,7 +852,7 class IncohInt(Operation):
852 852 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
853 853 if n == 1:
854 854 return dataOut
855
855
856 856 dataOut.flagNoData = True
857 857
858 858 if not self.isConfig:
@@ -868,7 +868,7 class IncohInt(Operation):
868 868
869 869 dataOut.data_spc = avgdata_spc
870 870 dataOut.data_cspc = avgdata_cspc
871 dataOut.data_dc = avgdata_dc
871 dataOut.data_dc = avgdata_dc
872 872 dataOut.nIncohInt *= self.n
873 873 dataOut.utctime = avgdatatime
874 874 dataOut.flagNoData = False
@@ -876,10 +876,10 class IncohInt(Operation):
876 876 return dataOut
877 877
878 878 class dopplerFlip(Operation):
879
879
880 880 def run(self, dataOut):
881 881 # arreglo 1: (num_chan, num_profiles, num_heights)
882 self.dataOut = dataOut
882 self.dataOut = dataOut
883 883 # JULIA-oblicua, indice 2
884 884 # arreglo 2: (num_profiles, num_heights)
885 885 jspectra = self.dataOut.data_spc[2]
@@ -895,4 +895,4 class dopplerFlip(Operation):
895 895 # canal modificado es re-escrito en el arreglo de canales
896 896 self.dataOut.data_spc[2] = jspectra_tmp
897 897
898 return self.dataOut No newline at end of file
898 return self.dataOut
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@@ -29,11 +29,11 mode = 1
29 29 #path = '/DATA_RM/TEST_19OCTUBRE/10MHZ'
30 30 path = '/DATA_RM/WR_20_OCT'
31 31 #### path_ped='/DATA_RM/TEST_PEDESTAL/P20211012-082745'
32 #### path_ped='/DATA_RM/TEST_PEDESTAL/P20211019-192244'
32 ####path_ped='/DATA_RM/TEST_PEDESTAL/P20211019-192244'
33 33 figpath_pp = "/home/soporte/Pictures/TEST_PP"
34 34 figpath_spec = "/home/soporte/Pictures/TEST_MOM"
35 plot = 1
36 integration = 0
35 plot = 0
36 integration = 1
37 37 save = 0
38 38 if save == 1:
39 39 if mode==0:
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@@ -69,7 +69,7 if save ==1:
69 69
70 70 print("* Integracion de datos :",integration)
71 71
72 time.sleep(15)
72 time.sleep(5)
73 73 #remotefolder = "/home/wmaster/graficos"
74 74 #######################################################################
75 75 ################# RANGO DE PLOTEO######################################
@@ -209,7 +209,7 else:
209 209 opObj11.addParameter(name='online', value='0', format='int')
210 210
211 211 opObj11 = procUnitConfObjC.addOperation(name='Block360')
212 opObj11.addParameter(name='n', value='30', format='int')
212 opObj11.addParameter(name='n', value='10', format='int')
213 213 opObj11.addParameter(name='mode', value=mode, format='int')
214 214
215 215 # este bloque funciona bien con divisores de 360 no olvidar 0 10 20 30 40 60 90 120 180
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