##// END OF EJS Templates
schain
RSS
last update spectra, spectra_acf, spectra_voltage, plotting_codes
avaldez -
r1243:ba521cb345c7
parent child
Show More
Side by Side Unified
Context file:
r1243:ba521cb345c7 Loading diff...:
Show file before | Show file after | Hide comments
@@ -634,8 +634,9 class Spectra(JROData):
634 return freqrange
634 return freqrange
635
635
636 def getAcfRange(self, extrapoints=0):
636 def getAcfRange(self, extrapoints=0):
637
637 #print "miay",self.ippFactor
638 deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
638 deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
639 #print deltafreq
639 freqrange = deltafreq * \
640 freqrange = deltafreq * \
640 (numpy.arange(self.nFFTPoints + extrapoints) -
641 (numpy.arange(self.nFFTPoints + extrapoints) -
641 self.nFFTPoints / 2.) - deltafreq / 2
642 self.nFFTPoints / 2.) - deltafreq / 2
Show file before | Show file after | Hide comments
@@ -234,10 +234,10 class ACFPlot(Figure):
234 self.isConfig = False
234 self.isConfig = False
235 self.__nsubplots = 1
235 self.__nsubplots = 1
236
236
237 self.PLOT_CODE = POWER_CODE
237 self.PLOT_CODE = ACF_CODE
238
238
239 self.WIDTH = 700
239 self.WIDTH = 900
240 self.HEIGHT = 500
240 self.HEIGHT = 700
241 self.counter_imagwr = 0
241 self.counter_imagwr = 0
242
242
243 def getSubplots(self):
243 def getSubplots(self):
@@ -266,7 +266,8 class ACFPlot(Figure):
266 for x in range(ncol):
266 for x in range(ncol):
267 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
267 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
268
268
269 def run(self, dataOut, id, wintitle="", channelList=None,
269 def run(self, dataOut, id, wintitle="", channelList=None,channel=None,nSamples=None,
270 nSampleList= None,resolutionFactor=None,
270 xmin=None, xmax=None, ymin=None, ymax=None,
271 xmin=None, xmax=None, ymin=None, ymax=None,
271 save=False, figpath='./', figfile=None, show=True,
272 save=False, figpath='./', figfile=None, show=True,
272 ftp=False, wr_period=1, server=None,
273 ftp=False, wr_period=1, server=None,
@@ -274,6 +275,25 class ACFPlot(Figure):
274 xaxis="frequency"):
275 xaxis="frequency"):
275
276
276
277
278 channel0 = channel
279 nSamples = nSamples
280 resFactor = resolutionFactor
281
282 if nSamples == None:
283 nSamples = 20
284
285 if resFactor == None:
286 resFactor = 5
287 #else:
288 # if nSamples not in dataOut.channelList:
289 # raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList)
290
291 if channel0 == None:
292 channel0 = 0
293 else:
294 if channel0 not in dataOut.channelList:
295 raise ValueError, "Channel %d is not in %s dataOut.channelList"%(channel0, dataOut.channelList)
296
277 if channelList == None:
297 if channelList == None:
278 channelIndexList = dataOut.channelIndexList
298 channelIndexList = dataOut.channelIndexList
279 channelList = dataOut.channelList
299 channelList = dataOut.channelList
@@ -284,53 +304,70 class ACFPlot(Figure):
284 raise ValueError, "Channel %d is not in dataOut.channelList"
304 raise ValueError, "Channel %d is not in dataOut.channelList"
285 channelIndexList.append(dataOut.channelList.index(channel))
305 channelIndexList.append(dataOut.channelList.index(channel))
286
306
307 #z = dataOut.data_spc/factor
287 factor = dataOut.normFactor
308 factor = dataOut.normFactor
288
289 y = dataOut.getHeiRange()
309 y = dataOut.getHeiRange()
290
291 #z = dataOut.data_spc/factor
292 deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
310 deltaHeight = dataOut.heightList[1]-dataOut.heightList[0]
293 print deltaHeight
311 z = dataOut.data_acf
294 z = dataOut.data_spc
295
296 #z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
312 #z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
297 shape = dataOut.data_spc.shape
313 shape = dataOut.data_acf.shape
314 hei_index = numpy.arange(shape[2])
315 hei_plot = numpy.arange(nSamples)*resFactor
316 #print hei_plot
317 #import matplotlib.pyplot as plt
318 #c=z[0,:,0]*15+15
319 #plt.plot(c)
320 #plt.show()
321 #print "HOLA#
322
323 if nSampleList is not None:
324 for nsample in nSampleList:
325 if nsample not in dataOut.heightList/deltaHeight:
326 raise ValueError, "nsample %d is not in %s dataOut.heightList"%(nsample,dataOut.heightList)
327
328 if nSampleList is not None:
329 hei_plot = numpy.array(nSampleList)*resFactor
330
331 if hei_plot[-1] >= hei_index[-1]:
332 print ("La cantidad de puntos en altura es %d y la resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
333 raise ValueError, "resFactor %d multiplicado por el valor de %d nSamples es mayor a %d cantidad total de puntos"%(resFactor,nSamples,hei_index[-1])
334
335 #escalamiento -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight
336 min = numpy.min(z[0,:,0])
337 max =numpy.max(z[0,:,0])
338
298 for i in range(shape[0]):
339 for i in range(shape[0]):
299 for j in range(shape[2]):
340 for j in range(shape[2]):
300 z[i,:,j]= (z[i,:,j]+1.0)*deltaHeight*5/2.0 + j*deltaHeight
341 z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight)
301 #z[i,:,j]= (z[i,:,j]+1.0)*deltaHeight*dataOut.step/2.0 + j*deltaHeight*dataOut.step
342 #z[i,:,j]= (z[i,:,j]+1.0)*deltaHeight*dataOut.step/2.0 + j*deltaHeight*dataOut.step
302
343
303 hei_index = numpy.arange(shape[2])
344 #print deltaHeight
304 #print hei_index.shape
345 #print resFactor
305 #b = []
346 #print numpy.max(z[0,:,0])
306 #for i in range(hei_index.shape[0]):
347 #import matplotlib.pyplot as plt
307 # if hei_index[i]%30 == 0:
348 #plt.plot((z[0,:,0])*deltaHeight)
308 # b.append(hei_index[i])
349 #plt.show()
309
350
310 #hei_index= numpy.array(b)
311 hei_index = hei_index[300:320]
312 #hei_index = numpy.arange(20)*30+80
313 hei_index= numpy.arange(20)*5
314 if xaxis == "frequency":
351 if xaxis == "frequency":
315 x = dataOut.getFreqRange()/1000.
352 x = dataOut.getFreqRange()/1000.
316 zdB = 10*numpy.log10(z[0,:,hei_index])
353 zdB = 10*numpy.log10(z[channel0,:,hei_plot])
317 xlabel = "Frequency (kHz)"
354 xlabel = "Frequency (kHz)"
318 ylabel = "Power (dB)"
355 ylabel = "Power (dB)"
319
356
320 elif xaxis == "time":
357 elif xaxis == "time":
321 x = dataOut.getAcfRange()
358 x = dataOut.getAcfRange()
322 zdB = z[0,:,hei_index]
359 zdB = z[channel0,:,hei_plot]
323 xlabel = "Time (ms)"
360 xlabel = "Time (ms)"
324 ylabel = "ACF"
361 ylabel = "ACF"
325
362
326 else:
363 else:
327 x = dataOut.getVelRange()
364 x = dataOut.getVelRange()
328 zdB = 10*numpy.log10(z[0,:,hei_index])
365 zdB = 10*numpy.log10(z[channel0,:,hei_plot])
329 xlabel = "Velocity (m/s)"
366 xlabel = "Velocity (m/s)"
330 ylabel = "Power (dB)"
367 ylabel = "Power (dB)"
331
368
332 thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
369 thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
333 title = wintitle + " ACF Plot %s" %(thisDatetime.strftime("%d-%b-%Y"))
370 title = wintitle + " ACF Plot Ch %s %s" %(channel0,thisDatetime.strftime("%d-%b-%Y"))
334
371
335 if not self.isConfig:
372 if not self.isConfig:
336
373
@@ -346,14 +383,18 class ACFPlot(Figure):
346 if ymin == None: ymin = numpy.nanmin(zdB)
383 if ymin == None: ymin = numpy.nanmin(zdB)
347 if ymax == None: ymax = numpy.nanmax(zdB)
384 if ymax == None: ymax = numpy.nanmax(zdB)
348
385
386 print ("El parametro resFactor es %d y la resolucion en altura es %d"%(resFactor,deltaHeight ))
387 print ("La cantidad de puntos en altura es %d y la nueva resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
388 print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight ))
389
349 self.isConfig = True
390 self.isConfig = True
350
391
351 self.setWinTitle(title)
392 self.setWinTitle(title)
352
393
353 title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
394 title = "ACF Plot: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
354 axes = self.axesList[0]
395 axes = self.axesList[0]
355
396
356 legendlabels = ["Range = %dKm" %y[i] for i in hei_index]
397 legendlabels = ["Range = %dKm" %y[i] for i in hei_plot]
357
398
358 axes.pmultilineyaxis( x, zdB,
399 axes.pmultilineyaxis( x, zdB,
359 xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
400 xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
@@ -363,6 +404,13 class ACFPlot(Figure):
363
404
364 self.draw()
405 self.draw()
365
406
407 if figfile == None:
408 str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
409 name = str_datetime
410 if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
411 name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
412 figfile = self.getFilename(name)
413
366 self.save(figpath=figpath,
414 self.save(figpath=figpath,
367 figfile=figfile,
415 figfile=figfile,
368 save=save,
416 save=save,
Show file before | Show file after | Hide comments
@@ -12,7 +12,7 TOTAL_CODE = 6 #Total Power.
12 DRIFT_CODE = 7 #Drifts graphics.
12 DRIFT_CODE = 7 #Drifts graphics.
13 HEIGHT_CODE = 8 #Height profile.
13 HEIGHT_CODE = 8 #Height profile.
14 PHASE_CODE = 9 #Signal Phase.
14 PHASE_CODE = 9 #Signal Phase.
15 AFC_CODE = 10 #Autocorrelation function.
15 ACF_CODE = 10 #Autocorrelation function.
16
16
17 POWER_CODE = 16
17 POWER_CODE = 16
18 NOISE_CODE = 17
18 NOISE_CODE = 17
Show file before | Show file after | Hide comments
@@ -65,7 +65,7 class SpectraProc(ProcessingUnit):
65 self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
65 self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
66 self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
66 self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
67
67
68 self.dataOut.step = self.dataIn.step
68 self.dataOut.step = self.dataIn.step #
69
69
70 def __getFft(self):
70 def __getFft(self):
71 """
71 """
@@ -87,10 +87,8 class SpectraProc(ProcessingUnit):
87
87
88 # calculo de self-spectra
88 # calculo de self-spectra
89 fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
89 fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
90 #print "spec dtype 0",fft_volt.dtype
91 spc = fft_volt * numpy.conjugate(fft_volt)
90 spc = fft_volt * numpy.conjugate(fft_volt)
92 spc = spc.real
91 spc = spc.real
93 #print "spec dtype 1",spc.dtype
94
92
95 blocksize = 0
93 blocksize = 0
96 blocksize += dc.size
94 blocksize += dc.size
@@ -127,10 +125,7 class SpectraProc(ProcessingUnit):
127
125
128 if self.dataIn.type == "Spectra":
126 if self.dataIn.type == "Spectra":
129 self.dataOut.copy(self.dataIn)
127 self.dataOut.copy(self.dataIn)
130 # if not pairsList:
128 print "hi",self.dataOut.ippSeconds
131 # pairsList = itertools.combinations(self.dataOut.channelList, 2)
132 # if self.dataOut.data_cspc is not None:
133 # self.__selectPairs(pairsList)
134 if shift_fft:
129 if shift_fft:
135 #desplaza a la derecha en el eje 2 determinadas posiciones
130 #desplaza a la derecha en el eje 2 determinadas posiciones
136 shift = int(self.dataOut.nFFTPoints/2)
131 shift = int(self.dataOut.nFFTPoints/2)
@@ -164,16 +159,11 class SpectraProc(ProcessingUnit):
164 self.dataIn.heightList.shape[0]),
159 self.dataIn.heightList.shape[0]),
165 dtype='complex')
160 dtype='complex')
166
161
167 #print self.buffer.shape,"spec2"
162
168 #print self.dataIn.heightList.shape[0],"spec3"
169
163
170 if self.dataIn.flagDataAsBlock:
164 if self.dataIn.flagDataAsBlock:
171 # data dimension: [nChannels, nProfiles, nSamples]
172 nVoltProfiles = self.dataIn.data.shape[1]
165 nVoltProfiles = self.dataIn.data.shape[1]
173 # nVoltProfiles = self.dataIn.nProfiles
174
166
175 #print nVoltProfiles,"spec1"
176 #print nProfiles
177 if nVoltProfiles == nProfiles:
167 if nVoltProfiles == nProfiles:
178 self.buffer = self.dataIn.data.copy()
168 self.buffer = self.dataIn.data.copy()
179 self.profIndex = nVoltProfiles
169 self.profIndex = nVoltProfiles
@@ -196,7 +186,6 class SpectraProc(ProcessingUnit):
196 else:
186 else:
197 self.buffer[:, self.profIndex, :] = self.dataIn.data.copy()
187 self.buffer[:, self.profIndex, :] = self.dataIn.data.copy()
198 self.profIndex += 1
188 self.profIndex += 1
199 #print self.profIndex,"spectra D"
200
189
201 if self.firstdatatime == None:
190 if self.firstdatatime == None:
202 self.firstdatatime = self.dataIn.utctime
191 self.firstdatatime = self.dataIn.utctime
Show file before | Show file after | Hide comments
@@ -99,16 +99,11 class SpectraAFCProc(ProcessingUnit):
99 dc = fft_volt[:,0,:]
99 dc = fft_volt[:,0,:]
100
100
101 #calculo de self-spectra
101 #calculo de self-spectra
102 # fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,))
103 spc = fft_volt * numpy.conjugate(fft_volt)
102 spc = fft_volt * numpy.conjugate(fft_volt)
104
105
106 data = numpy.fft.ifft(spc, axis=1)
103 data = numpy.fft.ifft(spc, axis=1)
107 data = numpy.fft.fftshift(data, axes=(1,))
104 data = numpy.fft.fftshift(data, axes=(1,))
108
105
109 spc = data.real
106 spc = data
110
111
112
107
113 blocksize = 0
108 blocksize = 0
114 blocksize += dc.size
109 blocksize += dc.size
@@ -145,29 +140,31 class SpectraAFCProc(ProcessingUnit):
145
140
146 if self.dataIn.type == "Spectra":
141 if self.dataIn.type == "Spectra":
147 self.dataOut.copy(self.dataIn)
142 self.dataOut.copy(self.dataIn)
143 #print "hi",self.dataOut.ippSeconds
144
148 spc= self.dataOut.data_spc
145 spc = self.dataOut.data_spc
149 data = numpy.fft.ifft(spc, axis=1)
146 data = numpy.fft.ifft(spc, axis=1)
150 data = numpy.fft.fftshift(data, axes=(1,))
147 data = numpy.fft.fftshift(data, axes=(1,))
151 spc = data.real
148 acf = numpy.abs(data) # Autocorrelacion LLAMAR A ESTE VALOR ACF
152 shape = spc.shape #nchannels, nprofiles, nsamples
149 #acf = data.imag
150 shape = acf.shape #nchannels, nprofiles, nsamples
153
151
154 #print spc.shape
155 for i in range(shape[0]):
156 for j in range(shape[2]):
157 spc[i,:,j]= spc[i,:,j] / numpy.max(numpy.abs(spc[i,:,j]))
158 #spc = spc[0,:,250] / numpy.max(numpy.abs(spc[0,:,250]))
159 #print spc.shape
160 #import matplotlib.pyplot as plt
152 #import matplotlib.pyplot as plt
161 #print spc[0:10]
153 #plt.plot(acf[0,:,0] / numpy.max(numpy.abs(acf[0,:,0])))
162 #plt.plot(spc[0,:,350])
163 #plt.show()
154 #plt.show()
164
155
156 # Normalizando
157 for i in range(shape[0]):
158 for j in range(shape[2]):
159 acf[i,:,j]= acf[i,:,j] / numpy.max(numpy.abs(acf[i,:,j]))
165
160
166 self.dataOut.data_spc = spc
161 #import matplotlib.pyplot as plt
162 #plt.plot(acf[0,:,0])
163 #plt.show()
167
164
165 self.dataOut.data_acf = acf
168 return True
166 return True
169
167
170
171 if code is not None:
168 if code is not None:
172 self.code = numpy.array(code).reshape(nCode,nBaud)
169 self.code = numpy.array(code).reshape(nCode,nBaud)
173 else:
170 else:
Show file before | Show file after | Hide comments
@@ -1248,8 +1248,8 class SSheightProfiles(Operation):
1248 deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
1248 deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
1249 ippSeconds = (deltaHeight*1.0e-6)/(0.15)
1249 ippSeconds = (deltaHeight*1.0e-6)/(0.15)
1250
1250
1251
1251 #print "hi",dataOut.ippSeconds
1252
1252 #print ippSeconds
1253 dataOut.data = self.sshProfiles
1253 dataOut.data = self.sshProfiles
1254 dataOut.flagNoData = False
1254 dataOut.flagNoData = False
1255 dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0]
1255 dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0]
@@ -1258,6 +1258,7 class SSheightProfiles(Operation):
1258 dataOut.flagDataAsBlock = True
1258 dataOut.flagDataAsBlock = True
1259 dataOut.ippSeconds = ippSeconds
1259 dataOut.ippSeconds = ippSeconds
1260 dataOut.step = self.step
1260 dataOut.step = self.step
1261 #print dataOut.ippSeconds
1261
1262
1262
1263
1263 # import collections
1264 # import collections
General Comments 0
You need to be logged in to leave comments. Login now