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completado op clean Rayleigh, modificada la escritura y lectura de hdf5 para potencia, cambio en gráficos para uso del ChannelList, añadir en otros pendiente

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ENV_DIR/bin/easy_install created 755 +11 0

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				1	#!/home/soporte/workspace/schain/ENV_DIR/bin/python3
				2
				3	# -- coding: utf-8 --
				4	import re
				5	import sys
				6
				7	from setuptools.command.easy_install import main
				8
				9	if __name__ == '__main__':
				10	sys.argv[0] = re.sub(r'(-script\.pyw?\|\.exe)?$', '', sys.argv[0])
				11	sys.exit(main())

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				1	#!/home/soporte/workspace/schain/ENV_DIR/bin/python3
				2
				3	# -- coding: utf-8 --
				4	import re
				5	import sys
				6
				7	from setuptools.command.easy_install import main
				8
				9	if __name__ == '__main__':
				10	sys.argv[0] = re.sub(r'(-script\.pyw?\|\.exe)?$', '', sys.argv[0])
				11	sys.exit(main())

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				1	#!/home/soporte/workspace/schain/ENV_DIR/bin/python3
				2
				3	# -- coding: utf-8 --
				4	import re
				5	import sys
				6
				7	from pip import main
				8
				9	if __name__ == '__main__':
				10	sys.argv[0] = re.sub(r'(-script\.pyw?\|\.exe)?$', '', sys.argv[0])
				11	sys.exit(main())

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				1	#!/home/soporte/workspace/schain/ENV_DIR/bin/python3
				2
				3	# -- coding: utf-8 --
				4	import re
				5	import sys
				6
				7	from pip import main
				8
				9	if __name__ == '__main__':
				10	sys.argv[0] = re.sub(r'(-script\.pyw?\|\.exe)?$', '', sys.argv[0])
				11	sys.exit(main())

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				1	#!/home/soporte/workspace/schain/ENV_DIR/bin/python3
				2
				3	# -- coding: utf-8 --
				4	import re
				5	import sys
				6
				7	from pip import main
				8
				9	if __name__ == '__main__':
				10	sys.argv[0] = re.sub(r'(-script\.pyw?\|\.exe)?$', '', sys.argv[0])
				11	sys.exit(main())

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				1	python3 No newline at end of file

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				1	/usr/bin/python3 No newline at end of file

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				1	lib No newline at end of file

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				1	home = /usr/bin
				2	include-system-site-packages = false
				3	version = 3.6.9

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schainpy/model/data/jrodata.py 0 -1

                     """
                     noise = numpy.zeros(self.nChannels)
                     for channel in range(self.nChannels):
                         daux = self.data_spc[channel,
                                              xmin_index:xmax_index, ymin_index:ymax_index]

0

schainpy/model/graphics/jroplot_base.py +1 -1

                     self.width = kwargs.get('width', None)
                     self.height = kwargs.get('height', None)
                     self.colorbar = kwargs.get('colorbar', True)
-                    self.factors = kwargs.get('factors', [1, 1, 1, 1, 1, 1, 1, 1])
+                    self.factors = kwargs.get('factors', range(18))
                     self.channels = kwargs.get('channels', None)
                     self.titles = kwargs.get('titles', [])
                     self.polar = False

0

schainpy/model/graphics/jroplot_parameters.py +5 -3

                 colormap = 'jet'
                 def update(self, dataOut):
+                    if len(self.channelList) == 0:
+                        self.channelList = dataOut.channelList
                     data = {
                         'snr': 10*numpy.log10(dataOut.data_snr)
                     }
                 colormap = 'jet'
                 def update(self, dataOut):
+                    if len(self.channelList) == 0:
+                        self.channelList = dataOut.channelList
                     data = {
                         'pow': 10*numpy.log10(dataOut.data_pow)
                     }
-                    print("data",data)
+                    #print("data",data)
                     return data, {}
             class SpectralWidthPlot(RTIPlot):

0

schainpy/model/graphics/jroplot_spectra.py +5 -5

             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt, log
+            from itertools import combinations
             class SpectraPlot(Plot):
                 '''
                     data = {}
                     meta = {}
                     spc = 10*numpy.log10(dataOut.data_spc/dataOut.normFactor)
                     data['spc'] = spc
                     data['rti'] = dataOut.getPower()
                     data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
                     cspc = dataOut.data_cspc
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     rawPairs = list(combinations(list(range(dataOut.nChannels)), 2))
-                    #print(rawPairs)
                     meta['pairs'] = rawPairs
                     if self.crossPairs == None:
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
-                    print("dataChannels ",self.data.channels)
+                    #print("dataChannels ",self.data.channels)
                     self.nrows = len(self.data.channels)
                     self.nplots = len(self.data.channels)
                     self.ylabel = 'Range [km]'
                     self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95})
                     self.titles = ['{} Channel {}'.format(
                         self.CODE.upper(), x) for x in range(self.nplots)]
-                    print("SETUP")
                 def update(self, dataOut):
                     if len(self.channelList) == 0:
                         self.channelList = dataOut.channelList
                     meta = {}
                     data['rti'] = dataOut.getPower()
                     data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor)
                     return data, meta
                 def plot(self):
                     self.x = self.data.times
                     self.y = self.data.yrange
                     self.z = self.data[self.CODE]

0

schainpy/model/io/jroIO_base.py +2 -1

                             path, startDate, endDate, folderfmt, last=True)
                     else:
                         folders = path.split(',')
                     return self.find_files(
                         folders, ext, filefmt, startDate, endDate, expLabel, last=True)
                     if self.fp != None:
                         self.fp.close()
                     if not os.path.exists(path):
                         os.mkdir(path)

0

schainpy/model/io/jroIO_kamisr.py +9 -11

-            '''
+            ''''
             Created on Set 9, 2015
             @author: roj-idl71 Karim Kuyeng
                         month = int(amisr_dirname_format[4:6])
                         dom = int(amisr_dirname_format[6:8])
                         thisDate = datetime.date(year,month,dom)
+                        #margen de un día extra, igual luego se filtra for fecha y hora
-                        if (thisDate>=self.startDate and thisDate <= self.endDate):
+                        if (thisDate>=(self.startDate - datetime.timedelta(days=1)) and thisDate <= (self.endDate)+ datetime.timedelta(days=1)):
                             return amisr_dirname_format
                     except:
                         return None
                         if self.timezone == 'lt':
                             startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300)
                             endDateTime_File = endDateTime_File - datetime.timedelta(minutes = 300)
-                        if (endDateTime_File>=startDateTime_Reader and endDateTime_File<=endDateTime_Reader):
+                        if (startDateTime_File >=startDateTime_Reader and endDateTime_File<=endDateTime_Reader):
                             filter_filenameList.append(filename)
-                        if (endDateTime_File>endDateTime_Reader):
+                        if (startDateTime_File>endDateTime_Reader):
                             break
                     filter_filenameList.sort()
                     self.filenameList = filter_filenameList
                     return 1
                 def __filterByGlob1(self, dirName):
                         return None
                     dirList = [os.path.join(self.path,x) for x in self.dirnameList]
                     fileListInKeys = [self.__filterByGlob1(x) for x in dirList]
                     self.__getFilenameList(fileListInKeys, dirList)
                     if not(online):
                         #filtro por tiempo
                     indexprof = numpy.mod(self.profileIndex, self.newProfiles)
                     indexblock = self.profileIndex/self.newProfiles
                     #print (indexblock, indexprof)
-                    diffUTC = 1.8e4 #UTC diference from peru in seconds --Joab
                     diffUTC = 0
                     t_comp = (indexprof * self.ippSeconds * self.nchannels) + diffUTC #
                     #print(numpy.shape(self.timeset))
                     self.dataOut.utctime = self.timeset[numpy.int_(indexblock)] + t_comp
                     #self.dataOut.utctime = self.timeset[self.profileIndex] + t_comp
-                    #print(self.dataOut.utctime)
                     self.dataOut.profileIndex = self.profileIndex
                     #print("N profile:",self.profileIndex,self.newProfiles,self.nblocks,self.dataOut.utctime)
                     self.dataOut.flagNoData = False
-            #         if indexprof == 0:
+                    # if indexprof == 0:
-            #             print self.dataOut.utctime
+                    #     print("kamisr: ",self.dataOut.utctime)
                     self.profileIndex += 1

0

schainpy/model/io/jroIO_param.py +4 -4

                                 self.endDate, self.expLabel, self.ext, self.walk,
                                 self.filefmt, self.folderfmt)
                             pathname, filename = os.path.split(fullpath)
-                            print(pathname,filename)
+                            #print(pathname,filename)
                             try:
                                 fullpath = next(fullpath)
                     self.interval = numpy.min(thisUtcTime[1:] - thisUtcTime[:-1])
                     thisDatetime = datetime.datetime.utcfromtimestamp(thisUtcTime[0])
                     self.startFileDatetime = thisDatetime
-                    print("datee ",self.startFileDatetime)
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     currentTime = self.dataOut.utctime
                     timeTuple = time.localtime(currentTime)
                     dataDay = timeTuple.tm_yday
+                    #print("time UTC: ",currentTime, self.dataOut.datatime)
                     if self.lastTime is None:
                         self.lastTime = currentTime
                         self.currentDay = dataDay
                     path = self.path
                     setFile = self.setFile
-                    timeTuple = time.localtime(self.dataOut.utctime)
+                    timeTuple = time.gmtime(self.dataOut.utctime)
+                    #print("path: ",timeTuple)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join(path, subfolder)

0

schainpy/model/proc/jroproc_parameters.py +1 -2

                     self.profIndex = 0
                     self.dataOut = Parameters()
                     self.setupReq = False #Agregar a todas las unidades de proc
-                    print("INIT PROC")
                 def __updateObjFromInput(self):
                     self.dataOut.inputUnit = self.dataIn.type
                     self.dataOut.elevationList = self.dataIn.elevationList
                 def run(self):
-                    print("run proc param")
                     #----------------------    Voltage Data    ---------------------------

0

schainpy/model/proc/jroproc_spectra.py +52 -134

	@@ -643,11 +643,12 class CleanRayleigh(Operation):
	643			643
	644	def cleanRayleigh(self,dataOut,spectra,cspectra,factor_stdv):		644	def cleanRayleigh(self,dataOut,spectra,cspectra,factor_stdv):
	645	#print("OP cleanRayleigh")		645	#print("OP cleanRayleigh")
	646	import matplotlib.pyplot as plt		646	#import matplotlib.pyplot as plt
	647	#for k in range(149):		647	#for k in range(149):
	648	channelsProcssd = []		648	#channelsProcssd = []
	649	channelA_ok = False		649	#channelA_ok = False
	650	rfunc = cspectra.copy() #self.bloques		650	#rfunc = cspectra.copy() #self.bloques
				651	rfunc = spectra.copy()
	651	#rfunc = cspectra		652	#rfunc = cspectra
	652	#val_spc = spectra0.0 #self.bloque00.0		653	#val_spc = spectra0.0 #self.bloque00.0
	653	#val_cspc = cspectra0.0 #self.bloques0.0		654	#val_cspc = cspectra0.0 #self.bloques0.0
	@@ -672,22 +673,27 class CleanRayleigh(Operation):
	672	gauss_fit, covariance = None, None		673	gauss_fit, covariance = None, None
	673	for ih in range(self.minAltInd,self.maxAltInd):		674	for ih in range(self.minAltInd,self.maxAltInd):
	674	for ifreq in range(self.nFFTPoints):		675	for ifreq in range(self.nFFTPoints):
				676	'''
	675	###ONLY FOR TEST:		677	###ONLY FOR TEST:
	676	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY		678	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY
	677	fig, axs = plt.subplots(raxs, caxs)		679	fig, axs = plt.subplots(raxs, caxs)
	678	fig2, axs2 = plt.subplots(raxs, caxs)		680	fig2, axs2 = plt.subplots(raxs, caxs)
	679	col_ax = 0		681	col_ax = 0
	680	row_ax = 0		682	row_ax = 0
				683	'''
	681	#print(self.nPairs)		684	#print(self.nPairs)
	682	for ii in range(self.n~~Pairs~~): #PARES DE CANALES SELF y CROSS		685	for ii in range(self.nChan): #PARES DE CANALES SELF y CROSS
	683	if self.crosspairs[ii][1]-self.crosspairs[ii][0] > 1: # APLICAR SOLO EN PARES CONTIGUOS		686	# if self.crosspairs[ii][1]-self.crosspairs[ii][0] > 1: # APLICAR SOLO EN PARES CONTIGUOS
	684	continue		687	# continue
	685	if not self.crosspairs[ii][0] in channelsProcssd:		688	# if not self.crosspairs[ii][0] in channelsProcssd:
	686	channelA_ok = True		689	# channelA_ok = True
	687	#print("pair: ",self.crosspairs[ii])		690	#print("pair: ",self.crosspairs[ii])
	688	if (col_ax%caxs==0 and col_ax!=0 and self.nPairs !=1): ###ONLY FOR TEST:		691	'''
				692	###ONLY FOR TEST:
				693	if (col_ax%caxs==0 and col_ax!=0 and self.nPairs !=1):
	689	col_ax = 0		694	col_ax = 0
	690	row_ax += 1		695	row_ax += 1
				696	'''
	691	func2clean = 10*numpy.log10(numpy.absolute(rfunc[:,ii,ifreq,ih])) #Potencia?		697	func2clean = 10*numpy.log10(numpy.absolute(rfunc[:,ii,ifreq,ih])) #Potencia?
	692	#print(func2clean.shape)		698	#print(func2clean.shape)
	693	val = (numpy.isfinite(func2clean)==True).nonzero()		699	val = (numpy.isfinite(func2clean)==True).nonzero()
	@@ -718,31 +724,31 class CleanRayleigh(Operation):
	718	mode = gauss_fit[1]		724	mode = gauss_fit[1]
	719	stdv = gauss_fit[2]		725	stdv = gauss_fit[2]
	720	#print(" FIT OK",gauss_fit)		726	#print(" FIT OK",gauss_fit)
	721			727	'''
	722	###ONLY FOR TEST:		728	###ONLY FOR TEST:
	723	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY		729	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY
	724	newY = fit_func(x_dist,gauss_fit[0],gauss_fit[1],gauss_fit[2])		730	newY = fit_func(x_dist,gauss_fit[0],gauss_fit[1],gauss_fit[2])
	725	axs[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')		731	axs[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')
	726	axs[row_ax,col_ax].plot(binstep[:-1],newY,color='red')		732	axs[row_ax,col_ax].plot(binstep[:-1],newY,color='red')
	727	axs[row_ax,col_ax].set_title("~~Pair~~ "+str(self.c~~rosspair~~s[ii]))		733	axs[row_ax,col_ax].set_title("CH "+str(self.channels[ii]))
	728			734	'''
	729	except:		735	except:
	730	mode = mean		736	mode = mean
	731	stdv = sigma		737	stdv = sigma
	732	#print("FIT FAIL")		738	#print("FIT FAIL")
	733	continue		739	#continue
	734			740
	735			741
	736	#print(mode,stdv)		742	#print(mode,stdv)
	737	#Removing echoes greater than mode + std_factor*stdv		743	#Removing echoes greater than mode + std_factor*stdv
	738	noval = (abs(func2clean - mode)>=(factor_stdv*stdv)).nonzero()		744	noval = (abs(func2clean - mode)>=(factor_stdv*stdv)).nonzero()
	739	#noval tiene los indices que se van a remover		745	#noval tiene los indices que se van a remover
	740	#print("~~Pair~~ ",ii," novals: ",len(noval[0]))		746	#print("Chan ",ii," novals: ",len(noval[0]))
	741	if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N)		747	if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N)
	742	novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero()		748	novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero()
	743	#print(novall)		749	#print(novall)
	744	#print(" ",self.pairsArray[ii])		750	#print(" ",self.pairsArray[ii])
	745	cross_pairs = self.pairsArray[ii]		751	#cross_pairs = self.pairsArray[ii]
	746	#Getting coherent echoes which are removed.		752	#Getting coherent echoes which are removed.
	747	# if len(novall[0]) > 0:		753	# if len(novall[0]) > 0:
	748	#		754	#
	@@ -750,30 +756,39 class CleanRayleigh(Operation):
	750	# val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1		756	# val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1
	751	# val_cspc[novall[0],ii,ifreq,ih] = 1		757	# val_cspc[novall[0],ii,ifreq,ih] = 1
	752	#print("OUT NOVALL 1")		758	#print("OUT NOVALL 1")
	753			759	try:
	754	new_a = numpy.delete(cspectra[:,ii,ifreq,ih], noval[0])		760	pair = (self.channels[ii],self.channels[ii + 1])
	755	cspectra[noval,ii,ifreq,ih] = numpy.mean(new_a) #mean CrossSpectra		761	except:
	756			762	pair = (99,99)
	757	if ~~channelA_ok~~:		763	#print("par ", pair)
	758	~~chA~~ = self.~~channels~~.~~index~~(cross_pairs[0])		764	if ( pair in self.crosspairs):
	759	new_b = numpy.delete(spectra[:,chA,ifreq,ih], noval[0])		765	q = self.crosspairs.index(pair)
	760	spectra[noval,chA,ifreq,ih] = numpy.mean(new_b) #mean Spectra Pair A		766	#print("está aqui: ", q, (ii,ii + 1))
	761	channelA_ok = False		767	new_a = numpy.delete(cspectra[:,q,ifreq,ih], noval[0])
	762	chB = self.channels.index(cross_pairs[1])		768	cspectra[noval,q,ifreq,ih] = numpy.mean(new_a) #mean CrossSpectra
	763	new_c = numpy.delete(spectra[:,chB,ifreq,ih], noval[0])		769
	764	spectra[noval,chB,ifreq,ih] = numpy.mean(new_c) #mean Spectra Pair B		770	#if channelA_ok:
	765			771	#chA = self.channels.index(cross_pairs[0])
	766	channelsProcssd.append(self.crosspairs[ii][0]) # save channel A		772	new_b = numpy.delete(spectra[:,ii,ifreq,ih], noval[0])
	767	channelsProcssd.append(self.crosspairs[ii][1]) # save channel B		773	spectra[noval,ii,ifreq,ih] = numpy.mean(new_b) #mean Spectra Pair A
	768			774	#channelA_ok = False
				775
				776	# chB = self.channels.index(cross_pairs[1])
				777	# new_c = numpy.delete(spectra[:,chB,ifreq,ih], noval[0])
				778	# spectra[noval,chB,ifreq,ih] = numpy.mean(new_c) #mean Spectra Pair B
				779	#
				780	# channelsProcssd.append(self.crosspairs[ii][0]) # save channel A
				781	# channelsProcssd.append(self.crosspairs[ii][1]) # save channel B
				782	'''
	769	###ONLY FOR TEST:		783	###ONLY FOR TEST:
	770	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY		784	if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY
	771	func2clean = 10*numpy.log10(numpy.absolute(cspectra[:,ii,ifreq,ih]))		785	func2clean = 10*numpy.log10(numpy.absolute(spectra[:,ii,ifreq,ih]))
	772	y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step))		786	y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step))
	773	axs2[row_ax,col_ax].plot(binstep[:-1],newY,color='red')		787	axs2[row_ax,col_ax].plot(binstep[:-1],newY,color='red')
	774	axs2[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')		788	axs2[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green')
	775	axs2[row_ax,col_ax].set_title("~~Pair~~ "+str(self.c~~rosspair~~s[ii]))		789	axs2[row_ax,col_ax].set_title("CH "+str(self.channels[ii]))
	776			790	'''
				791	'''
	777	###ONLY FOR TEST:		792	###ONLY FOR TEST:
	778	col_ax += 1 #contador de ploteo columnas		793	col_ax += 1 #contador de ploteo columnas
	779	##print(col_ax)		794	##print(col_ax)
	@@ -784,31 +799,8 class CleanRayleigh(Operation):
	784	fig.suptitle(title)		799	fig.suptitle(title)
	785	fig2.suptitle(title2)		800	fig2.suptitle(title2)
	786	plt.show()		801	plt.show()
	787
	788
	789	'''
	790
	791	channels = channels
	792	cross_pairs = cross_pairs
	793	#print("OUT NOVALL 2")
	794
	795	vcross0 = (cross_pairs[0] == channels[ii]).nonzero()
	796	vcross1 = (cross_pairs[1] == channels[ii]).nonzero()
	797	vcross = numpy.concatenate((vcross0,vcross1),axis=None)
	798	#print('vcros =', vcross)
	799
	800	#Getting coherent echoes which are removed.
	801	if len(novall) > 0:
	802	#val_spc[novall,ii,ifreq,ih] = 1
	803	val_spc[ii,ifreq,ih,novall] = 1
	804	if len(vcross) > 0:
	805	val_cspc[vcross,ifreq,ih,novall] = 1
	806
	807	#Removing coherent from ISR data.
	808	self.bloque0[ii,ifreq,ih,noval] = numpy.nan
	809	if len(vcross) > 0:
	810	self.bloques[vcross,ifreq,ih,noval] = numpy.nan
	811	'''		802	'''
				803	##################################################################################################
	812			804
	813	#print("Getting average of the spectra and cross-spectra from incoherent echoes.")		805	#print("Getting average of the spectra and cross-spectra from incoherent echoes.")
	814	out_spectra = numpy.zeros([self.nChan,self.nFFTPoints,self.nHeights], dtype=float) #+numpy.nan		806	out_spectra = numpy.zeros([self.nChan,self.nFFTPoints,self.nHeights], dtype=float) #+numpy.nan
	@@ -827,88 +819,14 class CleanRayleigh(Operation):
	827	valid = (numpy.isfinite(tmp)==True).nonzero()		819	valid = (numpy.isfinite(tmp)==True).nonzero()
	828	if len(valid[0]) > 0:		820	if len(valid[0]) > 0:
	829	out_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0])		821	out_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0])
	830	'''
	831	# print('##########################################################')
	832	print("Removing fake coherent echoes (at least 4 points around the point)")
	833
	834	val_spectra = numpy.sum(val_spc,0)
	835	val_cspectra = numpy.sum(val_cspc,0)
	836
	837	val_spectra = self.REM_ISOLATED_POINTS(val_spectra,4)
	838	val_cspectra = self.REM_ISOLATED_POINTS(val_cspectra,4)
	839
	840	for i in range(nChan):
	841	for j in range(nProf):
	842	for k in range(nHeights):
	843	if numpy.isfinite(val_spectra[i,j,k]) and val_spectra[i,j,k] < 1 :
	844	val_spc[:,i,j,k] = 0.0
	845	for i in range(nPairs):
	846	for j in range(nProf):
	847	for k in range(nHeights):
	848	if numpy.isfinite(val_cspectra[i,j,k]) and val_cspectra[i,j,k] < 1 :
	849	val_cspc[:,i,j,k] = 0.0
	850
	851	# val_spc = numpy.reshape(val_spc, (len(spectra[:,0,0,0]),nProfnHeightsnChan))
	852	# if numpy.isfinite(val_spectra)==str(True):
	853	# noval = (val_spectra<1).nonzero()
	854	# if len(noval) > 0:
	855	# val_spc[:,noval] = 0.0
	856	# val_spc = numpy.reshape(val_spc, (149,nChan,nProf,nHeights))
	857
	858	#val_cspc = numpy.reshape(val_spc, (149,nChannHeightsnProf))
	859	#if numpy.isfinite(val_cspectra)==str(True):
	860	# noval = (val_cspectra<1).nonzero()
	861	# if len(noval) > 0:
	862	# val_cspc[:,noval] = 0.0
	863	# val_cspc = numpy.reshape(val_cspc, (149,nChan,nProf,nHeights))
	864	tmp_sat_spectra = spectra.copy()
	865	tmp_sat_spectra = tmp_sat_spectra*numpy.nan
	866	tmp_sat_cspectra = cspectra.copy()
	867	tmp_sat_cspectra = tmp_sat_cspectra*numpy.nan
	868	'''
	869	# fig = plt.figure(figsize=(6,5))
	870	# left, bottom, width, height = 0.1, 0.1, 0.8, 0.8
	871	# ax = fig.add_axes([left, bottom, width, height])
	872	# cp = ax.contour(10*numpy.log10(numpy.absolute(spectra[0,0,:,:])))
	873	# ax.clabel(cp, inline=True,fontsize=10)
	874	# plt.show()
	875	'''
	876	val = (val_spc > 0).nonzero()
	877	if len(val[0]) > 0:
	878	tmp_sat_spectra[val] = in_sat_spectra[val]
	879	val = (val_cspc > 0).nonzero()
	880	if len(val[0]) > 0:
	881	tmp_sat_cspectra[val] = in_sat_cspectra[val]
	882
	883	print("Getting average of the spectra and cross-spectra from incoherent echoes 2")
	884	sat_spectra = numpy.zeros((nChan,nProf,nHeights), dtype=float)
	885	sat_cspectra = numpy.zeros((nPairs,nProf,nHeights), dtype=complex)
	886	for ih in range(nHeights):
	887	for ifreq in range(nProf):
	888	for ich in range(nChan):
	889	tmp = numpy.squeeze(tmp_sat_spectra[:,ich,ifreq,ih])
	890	valid = (numpy.isfinite(tmp)).nonzero()
	891	if len(valid[0]) > 0:
	892	sat_spectra[ich,ifreq,ih] = numpy.nansum(tmp)/len(valid[0])
	893			822
	894	for icr in range(nPairs):
	895	tmp = numpy.squeeze(tmp_sat_cspectra[:,icr,ifreq,ih])
	896	valid = (numpy.isfinite(tmp)).nonzero()
	897	if len(valid[0]) > 0:
	898	sat_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)/len(valid[0])
	899	'''
	900	#self.__dataReady= True
	901	#sat_spectra, sat_cspectra= sat_spectra, sat_cspectra
	902	#if not self.__dataReady:
	903	#return None, None
	904	#return out_spectra, out_cspectra ,sat_spectra,sat_cspectra
	905	return out_spectra, out_cspectra		823	return out_spectra, out_cspectra
	906			824
	907	def REM_ISOLATED_POINTS(self,array,rth):		825	def REM_ISOLATED_POINTS(self,array,rth):
	908	# import matplotlib.pyplot as plt		826	# import matplotlib.pyplot as plt
	909	if rth == None :		827	if rth == None :
	910	rth = 4		828	rth = 4
	911	print("REM ISO")		829	#print("REM ISO")
	912	num_prof = len(array[0,:,0])		830	num_prof = len(array[0,:,0])
	913	num_hei = len(array[0,0,:])		831	num_hei = len(array[0,0,:])
	914	n2d = len(array[:,0,0])		832	n2d = len(array[:,0,0])

0

schainpy/model/proc/jroproc_voltage.py +1 -3

                     self.lambda_          = 3.0e8/(9345.0e6)
                     self.ippSec           = dataOut.ippSeconds
                     self.nCohInt          = dataOut.nCohInt
-                    print("IPPseconds",dataOut.ippSeconds)
-                    print("ELVALOR DE n es:", n)
                     if n == None:
                         raise ValueError("n should be specified.")

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