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schainpy/scripts/basic_proc00002.py created 644 +217 0

@@ -0,0 +1,217
	1	# Ing. AVP
	2	# 06/10/2021
	3	# ARCHIVO DE LECTURA
	4	import os, sys
	5	import datetime
	6	import time
	7	from schainpy.controller import Project
	8	#### NOTA###########################################
	9	# INPUT :
	10	# VELOCIDAD PARAMETRO : V = 2°/seg
	11	# MODO PULSE PAIR O MOMENTOS: 0 : Pulse Pair ,1 : Momentos
	12	######################################################
	13	##### PROCESAMIENTO ##################################
	14	##### OJO TENER EN CUENTA EL n= para el Pulse Pair ##
	15	##### O EL n= nFFTPoints ###
	16	######################################################
	17	######## BUSCAMOS EL numero de IPP equivalente 1°#####
	18	######## Sea V la velocidad del Pedestal en °/seg#####
	19	######## 1° sera Recorrido en un tiempo de 1/V ######
	20	######## IPP del Radar 400 useg --> 60 Km ############
	21	######## n = 1/(V(°/seg)*IPP(Km)) , NUMERO DE IPP ##
	22	######## n = 1/(V*IPP) #############################
	23	######## VELOCIDAD DEL PEDESTAL ######################
	24	print("SETUP- RADAR METEOROLOGICO")
	25	V = 10
	26	mode = 1
	27	#path = '/DATA_RM/23/6v'
	28	#path = '/DATA_RM/TEST_INTEGRACION_2M'
	29	path = '/DATA_RM/WR_20_OCT'
	30
	31	#path_ped='/DATA_RM/TEST_PEDESTAL/P20211012-082745'
	32	path_ped='/DATA_RM/TEST_PEDESTAL/P20211020-131248'
	33
	34	figpath_pp = "/home/soporte/Pictures/TEST_PP"
	35	figpath_mom = "/home/soporte/Pictures/TEST_MOM"
	36	plot = 0
	37	integration = 1
	38	save = 0
	39	if save == 1:
	40	if mode==0:
	41	path_save = '/DATA_RM/TEST_HDF5_PP_23/6v'
	42	path_save = '/DATA_RM/TEST_HDF5_PP'
	43	path_save = '/DATA_RM/TEST_HDF5_PP_100'
	44	else:
	45	path_save = '/DATA_RM/TEST_HDF5_SPEC_23_V2/6v'
	46
	47	print("* PATH data ADQ :", path)
	48	print("* Velocidad Pedestal :",V,"°/seg")
	49	############################ NRO Perfiles PROCESAMIENTO ###################
	50	V=V
	51	IPP=400*1e-6
	52	n= int(1/(V*IPP))
	53	print("* n - NRO Perfiles Proc:", n )
	54	################################## MODE ###################################
	55	print("* Modo de Operacion :",mode)
	56	if mode ==0:
	57	print("* Met. Seleccionado : Pulse Pair")
	58	else:
	59	print("* Met. Momentos : Momentos")
	60
	61	################################## MODE ###################################
	62	print("* Grabado de datos :",save)
	63	if save ==1:
	64	if mode==0:
	65	ope= "Pulse Pair"
	66	else:
	67	ope= "Momentos"
	68	print("* Path-Save Data -", ope , path_save)
	69
	70	print("* Integracion de datos :",integration)
	71
	72	time.sleep(15)
	73	#remotefolder = "/home/wmaster/graficos"
	74	#######################################################################
	75	################# RANGO DE PLOTEO######################################
	76	dBmin = '1'
	77	dBmax = '85'
	78	xmin = '15'
	79	xmax = '15.25'
	80	ymin = '0'
	81	ymax = '600'
	82	#######################################################################
	83	########################FECHA##########################################
	84	str = datetime.date.today()
	85	today = str.strftime("%Y/%m/%d")
	86	str2 = str - datetime.timedelta(days=1)
	87	yesterday = str2.strftime("%Y/%m/%d")
	88	#######################################################################
	89	########################SIGNAL CHAIN ##################################
	90	#######################################################################
	91	desc = "USRP_test"
	92	filename = "USRP_processing.xml"
	93	controllerObj = Project()
	94	controllerObj.setup(id = '191', name='Test_USRP', description=desc)
	95	#######################################################################
	96	######################## UNIDAD DE LECTURA#############################
	97	#######################################################################
	98	readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
	99	path=path,
	100	startDate="2021/01/01",#today,
	101	endDate="2021/12/30",#today,
	102	startTime='00:00:00',
	103	endTime='23:59:59',
	104	delay=0,
	105	#set=0,
	106	online=0,
	107	walk=1,
	108	ippKm = 60)
	109
	110	opObj11 = readUnitConfObj.addOperation(name='printInfo')
	111
	112	procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
	113
	114	if mode ==0:
	115	####################### METODO PULSE PAIR ######################################################################
	116	opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other')
	117	opObj11.addParameter(name='n', value=int(n), format='int')#10 VOY A USAR 250 DADO QUE LA VELOCIDAD ES 10 GRADOS
	118	#opObj11.addParameter(name='removeDC', value=1, format='int')
	119	####################### METODO Parametros ######################################################################
	120	procUnitConfObjB= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjA.getId())
	121	if plot==1:
	122	opObj11 = procUnitConfObjB.addOperation(name='GenericRTIPlot',optype='external')
	123	opObj11.addParameter(name='attr_data', value='dataPP_POW')
	124	opObj11.addParameter(name='colormap', value='jet')
	125	opObj11.addParameter(name='xmin', value=xmin)
	126	opObj11.addParameter(name='xmax', value=xmax)
	127	opObj11.addParameter(name='zmin', value=dBmin)
	128	opObj11.addParameter(name='zmax', value=dBmax)
	129	opObj11.addParameter(name='save', value=figpath_pp)
	130	opObj11.addParameter(name='showprofile', value=0)
	131	opObj11.addParameter(name='save_period', value=50)
	132
	133	####################### METODO ESCRITURA #######################################################################
	134	if save==1:
	135	opObj10 = procUnitConfObjB.addOperation(name='HDFWriter')
	136	opObj10.addParameter(name='path',value=path_save)
	137	#opObj10.addParameter(name='mode',value=0)
	138	opObj10.addParameter(name='blocksPerFile',value='100',format='int')
	139	opObj10.addParameter(name='metadataList',value='utctimeInit,timeZone,paramInterval,profileIndex,channelList,heightList,flagDataAsBlock',format='list')
	140	opObj10.addParameter(name='dataList',value='dataPP_POW,dataPP_DOP,utctime',format='list')#,format='list'
	141	if integration==1:
	142	V=10
	143	blocksPerfile=360
	144	print("* Velocidad del Pedestal:",V)
	145	tmp_blocksPerfile = 100
	146	f_a_p= int(tmp_blocksPerfile/V)
	147
	148	opObj11 = procUnitConfObjB.addOperation(name='PedestalInformation')
	149	opObj11.addParameter(name='path_ped', value=path_ped)
	150	#opObj11.addParameter(name='path_adq', value=path_adq)
	151	opObj11.addParameter(name='t_Interval_p', value='0.01', format='float')
	152	opObj11.addParameter(name='blocksPerfile', value=blocksPerfile, format='int')
	153	opObj11.addParameter(name='n_Muestras_p', value='100', format='float')
	154	opObj11.addParameter(name='f_a_p', value=f_a_p, format='int')
	155	opObj11.addParameter(name='online', value='0', format='int')
	156
	157	opObj11 = procUnitConfObjB.addOperation(name='Block360')
	158	opObj11.addParameter(name='n', value='10', format='int')
	159	opObj11.addParameter(name='mode', value=mode, format='int')
	160
	161	# este bloque funciona bien con divisores de 360 no olvidar 0 10 20 30 40 60 90 120 180
	162
	163	opObj11= procUnitConfObjB.addOperation(name='WeatherPlot',optype='other')
	164
	165
	166	else:
	167	####################### METODO SPECTROS ######################################################################
	168	procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId())
	169	procUnitConfObjB.addParameter(name='nFFTPoints', value=n, format='int')
	170	procUnitConfObjB.addParameter(name='nProfiles' , value=n, format='int')
	171
	172	procUnitConfObjC = controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjB.getId())
	173	procUnitConfObjC.addOperation(name='SpectralMoments')
	174	if plot==1:
	175	dBmin = '1'
	176	dBmax = '65'
	177	opObj11 = procUnitConfObjC.addOperation(name='PowerPlot',optype='external')
	178	opObj11.addParameter(name='xmin', value=xmin)
	179	opObj11.addParameter(name='xmax', value=xmax)
	180	opObj11.addParameter(name='zmin', value=dBmin)
	181	opObj11.addParameter(name='zmax', value=dBmax)
	182	opObj11.addParameter(name='save', value=figpath_mom)
	183	opObj11.addParameter(name='showprofile', value=0)
	184	opObj11.addParameter(name='save_period', value=100)
	185
	186	if save==1:
	187	opObj10 = procUnitConfObjC.addOperation(name='HDFWriter')
	188	opObj10.addParameter(name='path',value=path_save)
	189	#opObj10.addParameter(name='mode',value=0)
	190	opObj10.addParameter(name='blocksPerFile',value='360',format='int')
	191	#opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
	192	opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
	193	opObj10.addParameter(name='dataList',value='data_pow,data_dop,utctime',format='list')#,format='list'
	194
	195	if integration==1:
	196	V=10
	197	blocksPerfile=360
	198	print("* Velocidad del Pedestal:",V)
	199	tmp_blocksPerfile = 100
	200	f_a_p= int(tmp_blocksPerfile/V)
	201
	202	opObj11 = procUnitConfObjC.addOperation(name='PedestalInformation')
	203	opObj11.addParameter(name='path_ped', value=path_ped)
	204	#opObj11.addParameter(name='path_adq', value=path_adq)
	205	opObj11.addParameter(name='t_Interval_p', value='0.01', format='float')
	206	opObj11.addParameter(name='blocksPerfile', value=blocksPerfile, format='int')
	207	opObj11.addParameter(name='n_Muestras_p', value='100', format='float')
	208	opObj11.addParameter(name='f_a_p', value=f_a_p, format='int')
	209	opObj11.addParameter(name='online', value='0', format='int')
	210
	211	opObj11 = procUnitConfObjC.addOperation(name='Block360')
	212	opObj11.addParameter(name='n', value='30', format='int')
	213	opObj11.addParameter(name='mode', value=mode, format='int')
	214
	215	# este bloque funciona bien con divisores de 360 no olvidar 0 10 20 30 40 60 90 120 180
	216	opObj11= procUnitConfObjC.addOperation(name='WeatherPlot',optype='other')
	217	controllerObj.start()

schainpy/scripts/pp_spec_comparation_pow.txt created 644 +13 0

@@ -0,0 +1,13
	1
	2	PULSE PAIR
	3	help [[1.364 1.376 1.28 ... 1.352 1.372 1.332]
	4	[2.912 3.012 3.06 ... 3.056 2.6 2.936]]
	5	help [[1.256 1.304 1.212 ... 1.228 1.328 1.528]
	6	[2.744 2.604 2.492 ... 2.544 2.916 2.644]]
	7	help [[1.176 1.248 1.48 ... 1.388 1.396 1.216]
	8	[2.564 2.524 2.756 ... 2.772 2.7 2.684]]
	9
	10	help [[1.312 1.328 1.28 ... 1.28 1.444 1.532]
	11	[3. 2.964 3.092 ... 3.104 3.016 2.984]]
	12
	13	MOMENTOS

schainpy/scripts/pulsepair_test0001.py created 644 +69 0

@@ -0,0 +1,69
	1	# Ing. AVP
	2	# 06/10/2021
	3	# ARCHIVO DE LECTURA
	4	import os, sys
	5	import datetime
	6	import time
	7	from schainpy.controller import Project
	8
	9	print("SETUP- RADAR METEOROLOGICO")
	10	V = 10
	11	#######################################################################
	12	################# RANGO DE PLOTEO######################################
	13	dBmin = '1'
	14	dBmax = '65'
	15	xmin = '13.2'
	16	xmax = '13.5'
	17	ymin = '0'
	18	ymax = '60'
	19
	20	path = '/DATA_RM/WR_20_OCT'
	21	figpath_pp = "/home/soporte/Pictures/TEST_PP"
	22
	23
	24	IPP=400*1e-6
	25	n= int(1/(V*IPP))
	26	#n=250
	27	print("* n - NRO Perfiles Proc:", n )
	28
	29	desc = "USRP_test"
	30	filename = "USRP_processing.xml"
	31	controllerObj = Project()
	32	controllerObj.setup(id = '191', name='Test_USRP', description=desc)
	33	#######################################################################
	34	######################## UNIDAD DE LECTURA#############################
	35	#######################################################################
	36	readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
	37	path=path,
	38	startDate="2021/01/01",#today,
	39	endDate="2021/12/30",#today,
	40	startTime='00:00:00',
	41	endTime='23:59:59',
	42	delay=0,
	43	#set=0,
	44	online=0,
	45	walk=1,
	46	ippKm = 60)
	47
	48	opObj11 = readUnitConfObj.addOperation(name='printInfo')
	49
	50	procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
	51
	52	opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other')
	53	opObj11.addParameter(name='n', value=int(n), format='int')#10 VOY A USAR 250 DADO QUE LA VELOCIDAD ES 10 GRADOS
	54	#opObj11.addParameter(name='removeDC', value=1, format='int')
	55
	56	procUnitConfObjB= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjA.getId())
	57
	58	opObj11 = procUnitConfObjB.addOperation(name='GenericRTIPlot',optype='external')
	59	opObj11.addParameter(name='attr_data', value='dataPP_POWER')
	60	opObj11.addParameter(name='colormap', value='jet')
	61	opObj11.addParameter(name='xmin', value=xmin)
	62	opObj11.addParameter(name='xmax', value=xmax)
	63	opObj11.addParameter(name='zmin', value=dBmin)
	64	opObj11.addParameter(name='zmax', value=dBmax)
	65	opObj11.addParameter(name='save', value=figpath_pp)
	66	opObj11.addParameter(name='showprofile', value=0)
	67	#opObj11.addParameter(name='save_period', value=10)
	68
	69	controllerObj.start()

schainpy/scripts/specmom_test0001.py created 644 +80 0

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	1	# Ing. AVP
	2	# 06/10/2021
	3	# ARCHIVO DE LECTURA
	4	import os, sys
	5	import datetime
	6	import time
	7	from schainpy.controller import Project
	8
	9	print("SETUP- RADAR METEOROLOGICO")
	10	V = 10
	11	#######################################################################
	12	################# RANGO DE PLOTEO######################################
	13	dBmin = '1'
	14	dBmax = '65'
	15	xmin = '13.2'
	16	xmax = '13.5'
	17	ymin = '0'
	18	ymax = '60'
	19
	20	path = '/DATA_RM/WR_20_OCT'
	21	figpath_spec = "/home/soporte/Pictures/TEST_MOM"
	22
	23
	24	IPP=400*1e-6
	25	n= int(1/(V*IPP))
	26	print("* n - NRO Perfiles Proc:", n )
	27	time.sleep(5)
	28	desc = "USRP_test"
	29	filename = "USRP_processing.xml"
	30	controllerObj = Project()
	31	controllerObj.setup(id = '191', name='Test_USRP', description=desc)
	32	#######################################################################
	33	######################## UNIDAD DE LECTURA#############################
	34	#######################################################################
	35	readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
	36	path=path,
	37	startDate="2021/01/01",#today,
	38	endDate="2021/12/30",#today,
	39	startTime='00:00:00',
	40	endTime='23:59:59',
	41	delay=0,
	42	#set=0,
	43	online=0,
	44	walk=1,
	45	ippKm = 60)
	46
	47	opObj11 = readUnitConfObj.addOperation(name='printInfo')
	48
	49	procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
	50
	51	procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId())
	52	procUnitConfObjB.addParameter(name='nFFTPoints', value=n, format='int')
	53	procUnitConfObjB.addParameter(name='nProfiles' , value=n, format='int')
	54	'''
	55	opObj11 = procUnitConfObjB.addOperation(name='RTIPlot', optype='external')
	56	#.addParameter(name='id', value='2', format='int')
	57	opObj11.addParameter(name='wintitle', value='RTIPlot', format='str')
	58	opObj11.addParameter(name='xmin', value=xmin)
	59	opObj11.addParameter(name='xmax', value=xmax)
	60	opObj11.addParameter(name='zmin', value=dBmin, format='int')
	61	opObj11.addParameter(name='zmax', value=dBmax, format='int')
	62	'''
	63	#opObj13 = procUnitConfObjB.addOperation(name='removeDC')
	64	#opObj13.addParameter(name='mode', value='2', format='int')
	65
	66	procUnitConfObjC = controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjB.getId())
	67	procUnitConfObjC.addOperation(name='SpectralMoments')
	68
	69	dBmin = '1'
	70	dBmax = '65'
	71	opObj11 = procUnitConfObjC.addOperation(name='PowerPlot',optype='external')
	72	opObj11.addParameter(name='xmin', value=xmin)
	73	opObj11.addParameter(name='xmax', value=xmax)
	74	opObj11.addParameter(name='zmin', value=dBmin)
	75	opObj11.addParameter(name='zmax', value=dBmax)
	76	opObj11.addParameter(name='save', value=figpath_spec)
	77	opObj11.addParameter(name='showprofile', value=0)
	78	#opObj11.addParameter(name='save_period', value=10)
	79
	80	controllerObj.start()

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

             # Copyright (c) 2012-2020 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """Definition of diferent Data objects for different types of data
             Here you will find the diferent data objects for the different types
             of data, this data objects must be used as dataIn or dataOut objects in
             processing units and operations. Currently the supported data objects are:
             Voltage, Spectra, SpectraHeis, Fits, Correlation and Parameters
             """
             import copy
             import numpy
             import datetime
             import json
             import schainpy.admin
             from schainpy.utils import log
             from .jroheaderIO import SystemHeader, RadarControllerHeader
             from schainpy.model.data import _noise
             def getNumpyDtype(dataTypeCode):
                 if dataTypeCode == 0:
                     numpyDtype = numpy.dtype([('real', '<i1'), ('imag', '<i1')])
                 elif dataTypeCode == 1:
                     numpyDtype = numpy.dtype([('real', '<i2'), ('imag', '<i2')])
                 elif dataTypeCode == 2:
                     numpyDtype = numpy.dtype([('real', '<i4'), ('imag', '<i4')])
                 elif dataTypeCode == 3:
                     numpyDtype = numpy.dtype([('real', '<i8'), ('imag', '<i8')])
                 elif dataTypeCode == 4:
                     numpyDtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')])
                 elif dataTypeCode == 5:
                     numpyDtype = numpy.dtype([('real', '<f8'), ('imag', '<f8')])
                 else:
                     raise ValueError('dataTypeCode was not defined')
                 return numpyDtype
             def getDataTypeCode(numpyDtype):
                 if numpyDtype == numpy.dtype([('real', '<i1'), ('imag', '<i1')]):
                     datatype = 0
                 elif numpyDtype == numpy.dtype([('real', '<i2'), ('imag', '<i2')]):
                     datatype = 1
                 elif numpyDtype == numpy.dtype([('real', '<i4'), ('imag', '<i4')]):
                     datatype = 2
                 elif numpyDtype == numpy.dtype([('real', '<i8'), ('imag', '<i8')]):
                     datatype = 3
                 elif numpyDtype == numpy.dtype([('real', '<f4'), ('imag', '<f4')]):
                     datatype = 4
                 elif numpyDtype == numpy.dtype([('real', '<f8'), ('imag', '<f8')]):
                     datatype = 5
                 else:
                     datatype = None
                 return datatype
             def hildebrand_sekhon(data, navg):
                 """
                 This method is for the objective determination of the noise level in Doppler spectra. This
                 implementation technique is based on the fact that the standard deviation of the spectral
                 densities is equal to the mean spectral density for white Gaussian noise
                 Inputs:
                     Data    :    heights
                     navg    :    numbers of averages
                 Return:
                     mean    :    noise's level
                 """
                 sortdata = numpy.sort(data, axis=None)
                 '''
                 lenOfData = len(sortdata)
                 nums_min = lenOfData*0.2
                 if nums_min <= 5:
                     nums_min = 5
                 sump = 0.
                 sumq = 0.
                 j = 0
                 cont = 1
                 while((cont == 1)and(j < lenOfData)):
                     sump += sortdata[j]
                     sumq += sortdata[j]**2
                     if j > nums_min:
                         rtest = float(j)/(j-1) + 1.0/navg
                         if ((sumq*j) > (rtest*sump**2)):
                             j = j - 1
                             sump = sump - sortdata[j]
                             sumq = sumq - sortdata[j]**2
                             cont = 0
                     j += 1
                 lnoise = sump / j
                 '''
                 return _noise.hildebrand_sekhon(sortdata, navg)
             class Beam:
                 def __init__(self):
                     self.codeList = []
                     self.azimuthList = []
                     self.zenithList = []
             class GenericData(object):
                 flagNoData = True
                 def copy(self, inputObj=None):
                     if inputObj == None:
                         return copy.deepcopy(self)
                     for key in list(inputObj.__dict__.keys()):
                         attribute = inputObj.__dict__[key]
                         # If this attribute is a tuple or list
                         if type(inputObj.__dict__[key]) in (tuple, list):
                             self.__dict__[key] = attribute[:]
                             continue
                         # If this attribute is another object or instance
                         if hasattr(attribute, '__dict__'):
                             self.__dict__[key] = attribute.copy()
                             continue
                         self.__dict__[key] = inputObj.__dict__[key]
                 def deepcopy(self):
                     return copy.deepcopy(self)
                 def isEmpty(self):
                     return self.flagNoData
                 def isReady(self):
                     return not self.flagNoData
             class JROData(GenericData):
                 systemHeaderObj = SystemHeader()
                 radarControllerHeaderObj = RadarControllerHeader()
                 type = None
                 datatype = None  # dtype but in string
                 nProfiles = None
                 heightList = None
                 channelList = None
                 flagDiscontinuousBlock = False
                 useLocalTime = False
                 utctime = None
                 timeZone = None
                 dstFlag = None
                 errorCount = None
                 blocksize = None
                 flagDecodeData = False  # asumo q la data no esta decodificada
                 flagDeflipData = False  # asumo q la data no esta sin flip
                 flagShiftFFT = False
                 nCohInt = None
                 windowOfFilter = 1
                 C = 3e8
                 frequency = 49.92e6
                 realtime = False
                 beacon_heiIndexList = None
                 last_block = None
                 blocknow = None
                 azimuth = None
                 zenith = None
                 beam = Beam()
                 profileIndex = None
                 error = None
                 data = None
                 nmodes = None
                 metadata_list = ['heightList', 'timeZone', 'type']
                 def __str__(self):
                     return '{} - {}'.format(self.type, self.datatime())
                 def getNoise(self):
                     raise NotImplementedError
                 @property
                 def nChannels(self):
                     return len(self.channelList)
                 @property
                 def channelIndexList(self):
                     return list(range(self.nChannels))
                 @property
                 def nHeights(self):
                     return len(self.heightList)
                 def getDeltaH(self):
                     return self.heightList[1] - self.heightList[0]
                 @property
                 def ltctime(self):
                     if self.useLocalTime:
                         return self.utctime - self.timeZone * 60
                     return self.utctime
                 @property
                 def datatime(self):
                     datatimeValue = datetime.datetime.utcfromtimestamp(self.ltctime)
                     return datatimeValue
                 def getTimeRange(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.timeInterval + 1)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getFmaxTimeResponse(self):
                     period = (10**-6) * self.getDeltaH() / (0.15)
                     PRF = 1. / (period * self.nCohInt)
                     fmax = PRF
                     return fmax
                 def getFmax(self):
                     PRF = 1. / (self.ippSeconds * self.nCohInt)
                     fmax = PRF
                     return fmax
                 def getVmax(self):
                     _lambda = self.C / self.frequency
                     vmax = self.getFmax() * _lambda / 2
                     return vmax
                 @property
                 def ippSeconds(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.ippSeconds
                 @ippSeconds.setter
                 def ippSeconds(self, ippSeconds):
                     '''
                     '''
                     self.radarControllerHeaderObj.ippSeconds = ippSeconds
                 @property
                 def code(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.code
                 @code.setter
                 def code(self, code):
                     '''
                     '''
                     self.radarControllerHeaderObj.code = code
                 @property
                 def nCode(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.nCode
                 @nCode.setter
                 def nCode(self, ncode):
                     '''
                     '''
                     self.radarControllerHeaderObj.nCode = ncode
                 @property
                 def nBaud(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.nBaud
                 @nBaud.setter
                 def nBaud(self, nbaud):
                     '''
                     '''
                     self.radarControllerHeaderObj.nBaud = nbaud
                 @property
                 def ipp(self):
                     '''
                     '''
                     return self.radarControllerHeaderObj.ipp
                 @ipp.setter
                 def ipp(self, ipp):
                     '''
                     '''
                     self.radarControllerHeaderObj.ipp = ipp
                 @property
                 def metadata(self):
                     '''
                     '''
                     return {attr: getattr(self, attr) for attr in self.metadata_list}
             class Voltage(JROData):
                 dataPP_POW   = None
                 dataPP_DOP   = None
                 dataPP_WIDTH = None
                 dataPP_SNR   = None
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.useLocalTime = True
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Voltage"
                     self.data = None
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.timeZone = 0
                     self.dstFlag = None
                     self.errorCount = None
                     self.nCohInt = None
                     self.blocksize = None
                     self.flagCohInt = False
                     self.flagDecodeData = False  # asumo q la data no esta decodificada
                     self.flagDeflipData = False  # asumo q la data no esta sin flip
                     self.flagShiftFFT = False
                     self.flagDataAsBlock = False  # Asumo que la data es leida perfil a perfil
                     self.profileIndex = 0
                     self.metadata_list = ['type', 'heightList', 'timeZone', 'nProfiles', 'channelList', 'nCohInt',
                         'code', 'nCode', 'nBaud', 'ippSeconds', 'ipp']
                 def getNoisebyHildebrand(self, channel=None):
                     """
                     Determino el nivel de ruido usando el metodo Hildebrand-Sekhon
                     Return:
                         noiselevel
                     """
                     if channel != None:
                         data = self.data[channel]
                         nChannels = 1
                     else:
                         data = self.data
                         nChannels = self.nChannels
                     noise = numpy.zeros(nChannels)
                     power = data * numpy.conjugate(data)
                     for thisChannel in range(nChannels):
                         if nChannels == 1:
                             daux = power[:].real
                         else:
                             daux = power[thisChannel, :].real
                         noise[thisChannel] = hildebrand_sekhon(daux, self.nCohInt)
                     return noise
                 def getNoise(self, type=1, channel=None):
                     if type == 1:
                         noise = self.getNoisebyHildebrand(channel)
                     return noise
                 def getPower(self, channel=None):
                     if channel != None:
                         data = self.data[channel]
                     else:
                         data = self.data
                     power = data * numpy.conjugate(data)
                     powerdB = 10 * numpy.log10(power.real)
                     powerdB = numpy.squeeze(powerdB)
                     return powerdB
                 @property
                 def timeInterval(self):
                     return self.ippSeconds * self.nCohInt
                 noise = property(getNoise, "I'm the 'nHeights' property.")
             class Spectra(JROData):
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.data_dc = None
                     self.data_spc = None
                     self.data_cspc = None
                     self.useLocalTime = True
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Spectra"
                     self.timeZone = 0
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.pairsList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.nCohInt = None
                     self.nIncohInt = None
                     self.blocksize = None
                     self.nFFTPoints = None
                     self.wavelength = None
                     self.flagDecodeData = False  # asumo q la data no esta decodificada
                     self.flagDeflipData = False  # asumo q la data no esta sin flip
                     self.flagShiftFFT = False
                     self.ippFactor = 1
                     self.beacon_heiIndexList = []
                     self.noise_estimation = None
                     self.metadata_list = ['type', 'heightList', 'timeZone', 'pairsList', 'channelList', 'nCohInt',
                         'code', 'nCode', 'nBaud', 'ippSeconds', 'ipp','nIncohInt', 'nFFTPoints', 'nProfiles']
                 def getNoisebyHildebrand(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None):
                     """
                     Determino el nivel de ruido usando el metodo Hildebrand-Sekhon
                     Return:
                         noiselevel
                     """
                     noise = numpy.zeros(self.nChannels)
                     for channel in range(self.nChannels):
                         daux = self.data_spc[channel,
                                              xmin_index:xmax_index, ymin_index:ymax_index]
                         noise[channel] = hildebrand_sekhon(daux, self.nIncohInt)
                     return noise
                 def getNoise(self, xmin_index=None, xmax_index=None, ymin_index=None, ymax_index=None):
                     if self.noise_estimation is not None:
                         # this was estimated by getNoise Operation defined in jroproc_spectra.py
                         return self.noise_estimation
                     else:
                         noise = self.getNoisebyHildebrand(
                             xmin_index, xmax_index, ymin_index, ymax_index)
                         return noise
                 def getFreqRangeTimeResponse(self, extrapoints=0):
                     deltafreq = self.getFmaxTimeResponse() / (self.nFFTPoints * self.ippFactor)
                     freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getAcfRange(self, extrapoints=0):
                     deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
                     freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getFreqRange(self, extrapoints=0):
                     deltafreq = self.getFmax() / (self.nFFTPoints * self.ippFactor)
                     freqrange = deltafreq * (numpy.arange(self.nFFTPoints + extrapoints) -self.nFFTPoints / 2.) - deltafreq / 2
                     return freqrange
                 def getVelRange(self, extrapoints=0):
                     deltav = self.getVmax() / (self.nFFTPoints * self.ippFactor)
                     velrange = deltav * (numpy.arange(self.nFFTPoints + extrapoints) - self.nFFTPoints / 2.)
                     if self.nmodes:
                         return velrange/self.nmodes
                     else:
                         return velrange
                 @property
                 def nPairs(self):
                     return len(self.pairsList)
                 @property
                 def pairsIndexList(self):
                     return list(range(self.nPairs))
                 @property
                 def normFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     #normFactor = min(self.nFFTPoints,self.nProfiles)*self.nIncohInt*self.nCohInt*pwcode*self.windowOfFilter
                     normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter
                     return normFactor
                 @property
                 def flag_cspc(self):
                     if self.data_cspc is None:
                         return True
                     return False
                 @property
                 def flag_dc(self):
                     if self.data_dc is None:
                         return True
                     return False
                 @property
                 def timeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt * self.nProfiles * self.ippFactor
                     if self.nmodes:
                         return self.nmodes*timeInterval
                     else:
                         return timeInterval
                 def getPower(self):
                     factor = self.normFactor
                     z = self.data_spc / factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     return 10 * numpy.log10(avg)
                 def getCoherence(self, pairsList=None, phase=False):
                     z = []
                     if pairsList is None:
                         pairsIndexList = self.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in self.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" % (
                                     pair))
                             pairsIndexList.append(self.pairsList.index(pair))
                     for i in range(len(pairsIndexList)):
                         pair = self.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(self.data_cspc[pairsIndexList[i], :, :], axis=0)
                         powa = numpy.average(self.data_spc[pair[0], :, :], axis=0)
                         powb = numpy.average(self.data_spc[pair[1], :, :], axis=0)
                         avgcoherenceComplex = ccf / numpy.sqrt(powa * powb)
                         if phase:
                             data = numpy.arctan2(avgcoherenceComplex.imag,
                                                  avgcoherenceComplex.real) * 180 / numpy.pi
                         else:
                             data = numpy.abs(avgcoherenceComplex)
                         z.append(data)
                     return numpy.array(z)
                 def setValue(self, value):
                     print("This property should not be initialized")
                     return
                 noise = property(getNoise, setValue, "I'm the 'nHeights' property.")
             class SpectraHeis(Spectra):
                 def __init__(self):
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "SpectraHeis"
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.blocksize = None
                     self.profileIndex = 0
                     self.nCohInt = 1
                     self.nIncohInt = 1
                 @property
                 def normFactor(self):
                     pwcode = 1
                     if self.flagDecodeData:
                         pwcode = numpy.sum(self.code[0]**2)
                     normFactor = self.nIncohInt * self.nCohInt * pwcode
                     return normFactor
                 @property
                 def timeInterval(self):
                     return self.ippSeconds * self.nCohInt * self.nIncohInt
             class Fits(JROData):
                 def __init__(self):
                     self.type = "Fits"
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.flagNoData = True
                     self.utctime = None
                     self.nCohInt = 1
                     self.nIncohInt = 1
                     self.useLocalTime = True
                     self.profileIndex = 0
                     self.timeZone = 0
                 def getTimeRange(self):
                     datatime = []
                     datatime.append(self.ltctime)
                     datatime.append(self.ltctime + self.timeInterval)
                     datatime = numpy.array(datatime)
                     return datatime
                 def getChannelIndexList(self):
                     return list(range(self.nChannels))
                 def getNoise(self, type=1):
                     if type == 1:
                         noise = self.getNoisebyHildebrand()
                     if type == 2:
                         noise = self.getNoisebySort()
                     if type == 3:
                         noise = self.getNoisebyWindow()
                     return noise
                 @property
                 def timeInterval(self):
                     timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     return timeInterval
                 @property
                 def ippSeconds(self):
                     '''
                     '''
                     return self.ipp_sec
                 noise = property(getNoise, "I'm the 'nHeights' property.")
             class Correlation(JROData):
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Correlation"
                     self.data = None
                     self.dtype = None
                     self.nProfiles = None
                     self.heightList = None
                     self.channelList = None
                     self.flagNoData = True
                     self.flagDiscontinuousBlock = False
                     self.utctime = None
                     self.timeZone = 0
                     self.dstFlag = None
                     self.errorCount = None
                     self.blocksize = None
                     self.flagDecodeData = False  # asumo q la data no esta decodificada
                     self.flagDeflipData = False  # asumo q la data no esta sin flip
                     self.pairsList = None
                     self.nPoints = None
                 def getPairsList(self):
                     return self.pairsList
                 def getNoise(self, mode=2):
                     indR = numpy.where(self.lagR == 0)[0][0]
                     indT = numpy.where(self.lagT == 0)[0][0]
                     jspectra0 = self.data_corr[:, :, indR, :]
                     jspectra = copy.copy(jspectra0)
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
                     freq_dc = jspectra.shape[1] / 2
                     ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc
                     if ind_vel[0] < 0:
                         ind_vel[list(range(0, 1))] = ind_vel[list(
                             range(0, 1))] + self.num_prof
                     if mode == 1:
                         jspectra[:, freq_dc, :] = (
                             jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2  # CORRECCION
                     if mode == 2:
                         vel = numpy.array([-2, -1, 1, 2])
                         xx = numpy.zeros([4, 4])
                         for fil in range(4):
                             xx[fil, :] = vel[fil]**numpy.asarray(list(range(4)))
                         xx_inv = numpy.linalg.inv(xx)
                         xx_aux = xx_inv[0, :]
                         for ich in range(num_chan):
                             yy = jspectra[ich, ind_vel, :]
                             jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy)
                             junkid = jspectra[ich, freq_dc, :] <= 0
                             cjunkid = sum(junkid)
                             if cjunkid.any():
                                 jspectra[ich, freq_dc, junkid.nonzero()] = (
                                     jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2
                     noise = jspectra0[:, freq_dc, :] - jspectra[:, freq_dc, :]
                     return noise
                 @property
                 def timeInterval(self):
                     return self.ippSeconds * self.nCohInt * self.nProfiles
                 def splitFunctions(self):
                     pairsList = self.pairsList
                     ccf_pairs = []
                     acf_pairs = []
                     ccf_ind = []
                     acf_ind = []
                     for l in range(len(pairsList)):
                         chan0 = pairsList[l][0]
                         chan1 = pairsList[l][1]
                         # Obteniendo pares de Autocorrelacion
                         if chan0 == chan1:
                             acf_pairs.append(chan0)
                             acf_ind.append(l)
                         else:
                             ccf_pairs.append(pairsList[l])
                             ccf_ind.append(l)
                     data_acf = self.data_cf[acf_ind]
                     data_ccf = self.data_cf[ccf_ind]
                     return acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf
                 @property
                 def normFactor(self):
                     acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.splitFunctions()
                     acf_pairs = numpy.array(acf_pairs)
                     normFactor = numpy.zeros((self.nPairs, self.nHeights))
                     for p in range(self.nPairs):
                         pair = self.pairsList[p]
                         ch0 = pair[0]
                         ch1 = pair[1]
                         ch0_max = numpy.max(data_acf[acf_pairs == ch0, :, :], axis=1)
                         ch1_max = numpy.max(data_acf[acf_pairs == ch1, :, :], axis=1)
                         normFactor[p, :] = numpy.sqrt(ch0_max * ch1_max)
                     return normFactor
             class Parameters(Spectra):
                 groupList = None  # List of Pairs, Groups, etc
                 data_param = None  # Parameters obtained
                 data_pre = None  # Data Pre Parametrization
                 data_SNR = None  # Signal to Noise Ratio
                 abscissaList = None  # Abscissa, can be velocities, lags or time
                 utctimeInit = None  # Initial UTC time
                 paramInterval = None  # Time interval to calculate Parameters in seconds
                 useLocalTime = True
                 # Fitting
                 data_error = None  # Error of the estimation
                 constants = None
                 library = None
                 # Output signal
                 outputInterval = None  # Time interval to calculate output signal in seconds
                 data_output = None  # Out signal
                 nAvg = None
                 noise_estimation = None
                 GauSPC = None  # Fit gaussian SPC
                 def __init__(self):
                     '''
                     Constructor
                     '''
                     self.radarControllerHeaderObj = RadarControllerHeader()
                     self.systemHeaderObj = SystemHeader()
                     self.type = "Parameters"
                     self.timeZone = 0
                 def getTimeRange1(self, interval):
                     datatime = []
                     if self.useLocalTime:
                         time1 = self.utctimeInit - self.timeZone * 60
                     else:
                         time1 = self.utctimeInit
                     datatime.append(time1)
                     datatime.append(time1 + interval)
                     datatime = numpy.array(datatime)
                     return datatime
                 @property
                 def timeInterval(self):
                     if hasattr(self, 'timeInterval1'):
                         return self.timeInterval1
                     else:
                         return self.paramInterval
                 def setValue(self, value):
                     print("This property should not be initialized")
                     return
                 def getNoise(self):
                     return self.spc_noise
                 noise = property(getNoise, setValue, "I'm the 'Noise' property.")
             class PlotterData(object):
                 '''
                 Object to hold data to be plotted
                 '''
                 MAXNUMX = 200
                 MAXNUMY = 200
                 def __init__(self, code, exp_code, localtime=True):
                     self.key = code
                     self.exp_code = exp_code
                     self.ready = False
                     self.flagNoData = False
                     self.localtime = localtime
                     self.data = {}
                     self.meta = {}
                     self.__heights = []
                 def __str__(self):
                     dum = ['{}{}'.format(key, self.shape(key)) for key in self.data]
                     return 'Data[{}][{}]'.format(';'.join(dum), len(self.times))
                 def __len__(self):
                     return len(self.data)
                 def __getitem__(self, key):
                     if isinstance(key, int):
                         return self.data[self.times[key]]
                     elif isinstance(key, str):
                         ret = numpy.array([self.data[x][key] for x in self.times])
                         if ret.ndim > 1:
                             ret = numpy.swapaxes(ret, 0, 1)
                         return ret
                 def __contains__(self, key):
                     return key in self.data[self.min_time]
                 def setup(self):
                     '''
                     Configure object
                     '''
                     self.type = ''
                     self.ready = False
                     del self.data
                     self.data = {}
                     self.__heights = []
                     self.__all_heights = set()
                 def shape(self, key):
                     '''
                     Get the shape of the one-element data for the given key
                     '''
                     if len(self.data[self.min_time][key]):
                         return self.data[self.min_time][key].shape
                     return (0,)
                 def update(self, data, tm, meta={}):
                     '''
                     Update data object with new dataOut
                     '''
                     self.data[tm] = data
                     for key, value in meta.items():
                         setattr(self, key, value)
                 def normalize_heights(self):
                     '''
                     Ensure same-dimension of the data for different heighList
                     '''
                     H = numpy.array(list(self.__all_heights))
                     H.sort()
                     for key in self.data:
                         shape = self.shape(key)[:-1] + H.shape
                         for tm, obj in list(self.data[key].items()):
                             h = self.__heights[self.times.tolist().index(tm)]
                             if H.size == h.size:
                                 continue
                             index = numpy.where(numpy.in1d(H, h))[0]
                             dummy = numpy.zeros(shape) + numpy.nan
                             if len(shape) == 2:
                                 dummy[:, index] = obj
                             else:
                                 dummy[index] = obj
                             self.data[key][tm] = dummy
                     self.__heights = [H for tm in self.times]
                 def jsonify(self, tm, plot_name, plot_type, decimate=False):
                     '''
                     Convert data to json
                     '''
                     meta = {}
                     meta['xrange'] = []
                     dy = int(len(self.yrange)/self.MAXNUMY) + 1
                     tmp = self.data[tm][self.key]
                     shape = tmp.shape
                     if len(shape) == 2:
                         data = self.roundFloats(self.data[tm][self.key][::, ::dy].tolist())
                     elif len(shape) == 3:
                         dx = int(self.data[tm][self.key].shape[1]/self.MAXNUMX) + 1
                         data = self.roundFloats(
                             self.data[tm][self.key][::, ::dx, ::dy].tolist())
                         meta['xrange'] = self.roundFloats(self.xrange[2][::dx].tolist())
                     else:
                         data = self.roundFloats(self.data[tm][self.key].tolist())
                     ret = {
                         'plot': plot_name,
                         'code': self.exp_code,
                         'time': float(tm),
                         'data': data,
                         }
                     meta['type'] = plot_type
                     meta['interval'] = float(self.interval)
                     meta['localtime'] = self.localtime
                     meta['yrange'] = self.roundFloats(self.yrange[::dy].tolist())
                     meta.update(self.meta)
                     ret['metadata'] = meta
                     return json.dumps(ret)
                 @property
                 def times(self):
                     '''
                     Return the list of times of the current data
                     '''
                     ret = [t for t in self.data]
                     ret.sort()
                     return numpy.array(ret)
                 @property
                 def min_time(self):
                     '''
                     Return the minimun time value
                     '''
                     return self.times[0]
                 @property
                 def max_time(self):
                     '''
                     Return the maximun time value
                     '''
                     return self.times[-1]
                 # @property
                 # def heights(self):
                 #     '''
                 #     Return the list of heights of the current data
                 #     '''
                 #     return numpy.array(self.__heights[-1])
                 @staticmethod
                 def roundFloats(obj):
                     if isinstance(obj, list):
                         return list(map(PlotterData.roundFloats, obj))
                     elif isinstance(obj, float):
                         return round(obj, 2)

schainpy/model/graphics/jroplot_parameters.py 0 -10

             import os
             import datetime
             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt
             from schainpy.model.graphics.jroplot_spectra import SpectraPlot, RTIPlot, CoherencePlot, SpectraCutPlot
             from schainpy.utils import log
             # libreria wradlib
             import wradlib as wrl
             EARTH_RADIUS = 6.3710e3
             def ll2xy(lat1, lon1, lat2, lon2):
                 p = 0.017453292519943295
                 a = 0.5 - numpy.cos((lat2 - lat1) * p)/2 + numpy.cos(lat1 * p) * \
                     numpy.cos(lat2 * p) * (1 - numpy.cos((lon2 - lon1) * p)) / 2
                 r = 12742 * numpy.arcsin(numpy.sqrt(a))
                 theta = numpy.arctan2(numpy.sin((lon2-lon1)*p)*numpy.cos(lat2*p), numpy.cos(lat1*p)
                                       * numpy.sin(lat2*p)-numpy.sin(lat1*p)*numpy.cos(lat2*p)*numpy.cos((lon2-lon1)*p))
                 theta = -theta + numpy.pi/2
                 return r*numpy.cos(theta), r*numpy.sin(theta)
             def km2deg(km):
                 '''
                 Convert distance in km to degrees
                 '''
                 return numpy.rad2deg(km/EARTH_RADIUS)
             class SpectralMomentsPlot(SpectraPlot):
                 '''
                 Plot for Spectral Moments
                 '''
                 CODE = 'spc_moments'
                 # colormap = 'jet'
                 # plot_type = 'pcolor'
             class DobleGaussianPlot(SpectraPlot):
                 '''
                 Plot for Double Gaussian Plot
                 '''
                 CODE = 'gaussian_fit'
                 # colormap = 'jet'
                 # plot_type = 'pcolor'
             class DoubleGaussianSpectraCutPlot(SpectraCutPlot):
                 '''
                 Plot SpectraCut with Double Gaussian Fit
                 '''
                 CODE = 'cut_gaussian_fit'
             class SnrPlot(RTIPlot):
                 '''
                 Plot for SNR Data
                 '''
                 CODE = 'snr'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'snr': 10*numpy.log10(dataOut.data_snr)
                     }
                     return data, {}
             class DopplerPlot(RTIPlot):
                 '''
                 Plot for DOPPLER Data (1st moment)
                 '''
                 CODE = 'dop'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'dop': 10*numpy.log10(dataOut.data_dop)
                     }
                     return data, {}
             class PowerPlot(RTIPlot):
                 '''
                 Plot for Power Data (0 moment)
                 '''
                 CODE = 'pow'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'pow': 10*numpy.log10(dataOut.data_pow/dataOut.normFactor)
                     }
                     return data, {}
             class SpectralWidthPlot(RTIPlot):
                 '''
                 Plot for Spectral Width Data (2nd moment)
                 '''
                 CODE = 'width'
                 colormap = 'jet'
                 def update(self, dataOut):
                     data = {
                         'width': dataOut.data_width
                     }
                     return data, {}
             class SkyMapPlot(Plot):
                 '''
                 Plot for meteors detection data
                 '''
                 CODE = 'param'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width = 7.2
                     self.height = 7.2
                     self.nplots = 1
                     self.xlabel = 'Zonal Zenith Angle (deg)'
                     self.ylabel = 'Meridional Zenith Angle (deg)'
                     self.polar = True
                     self.ymin = -180
                     self.ymax = 180
                     self.colorbar = False
                 def plot(self):
                     arrayParameters = numpy.concatenate(self.data['param'])
                     error = arrayParameters[:, -1]
                     indValid = numpy.where(error == 0)[0]
                     finalMeteor = arrayParameters[indValid, :]
                     finalAzimuth = finalMeteor[:, 3]
                     finalZenith = finalMeteor[:, 4]
                     x = finalAzimuth * numpy.pi / 180
                     y = finalZenith
                     ax = self.axes[0]
                     if ax.firsttime:
                         ax.plot = ax.plot(x, y, 'bo', markersize=5)[0]
                     else:
                         ax.plot.set_data(x, y)
                     dt1 = self.getDateTime(self.data.min_time).strftime('%y/%m/%d %H:%M:%S')
                     dt2 = self.getDateTime(self.data.max_time).strftime('%y/%m/%d %H:%M:%S')
                     title = 'Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n' % (dt1,
                                                                                                  dt2,
                                                                                                  len(x))
                     self.titles[0] = title
             class GenericRTIPlot(Plot):
                 '''
                 Plot for data_xxxx object
                 '''
                 CODE = 'param'
                 colormap = 'viridis'
                 plot_type = 'pcolorbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = self.data.shape('param')[0]
                     self.nplots = self.nrows
                     self.plots_adjust.update({'hspace':0.8, 'left': 0.1, 'bottom': 0.08, 'right':0.95, 'top': 0.95})
                     if not self.xlabel:
                         self.xlabel = 'Time'
                     self.ylabel = 'Range [km]'
                     if not self.titles:
                         self.titles = ['Param {}'.format(x) for x in range(self.nrows)]
                 def update(self, dataOut):
                     data = {
                         'param' : numpy.concatenate([getattr(dataOut, attr) for attr in self.attr_data], axis=0)
                     }
                     meta = {}
                     return data, meta
                 def plot(self):
                     # self.data.normalize_heights()
                     self.x = self.data.times
                     self.y = self.data.yrange
                     self.z = self.data['param']
                     self.z = 10*numpy.log10(self.z)
                     self.z = numpy.ma.masked_invalid(self.z)
                     if self.decimation is None:
                         x, y, z = self.fill_gaps(self.x, self.y, self.z)
                     else:
                         x, y, z = self.fill_gaps(*self.decimate())
                     for n, ax in enumerate(self.axes):
                         self.zmax = self.zmax if self.zmax is not None else numpy.max(
                             self.z[n])
                         self.zmin = self.zmin if self.zmin is not None else numpy.min(
                             self.z[n])
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.collections.remove(ax.collections[0])
                             ax.plt = ax.pcolormesh(x, y, z[n].T * self.factors[n],
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=self.cmaps[n]
                                                    )
             class PolarMapPlot(Plot):
                 '''
                 Plot for weather radar
                 '''
                 CODE = 'param'
                 colormap = 'seismic'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.width = 9
                     self.height = 8
                     self.mode = self.data.meta['mode']
                     if self.channels is not None:
                         self.nplots = len(self.channels)
                         self.nrows = len(self.channels)
                     else:
                         self.nplots = self.data.shape(self.CODE)[0]
                         self.nrows = self.nplots
                         self.channels = list(range(self.nplots))
                     if self.mode == 'E':
                         self.xlabel = 'Longitude'
                         self.ylabel = 'Latitude'
                     else:
                         self.xlabel = 'Range (km)'
                         self.ylabel = 'Height (km)'
                     self.bgcolor = 'white'
                     self.cb_labels = self.data.meta['units']
                     self.lat = self.data.meta['latitude']
                     self.lon = self.data.meta['longitude']
                     self.xmin, self.xmax = float(
                         km2deg(self.xmin) + self.lon), float(km2deg(self.xmax) + self.lon)
                     self.ymin, self.ymax = float(
                         km2deg(self.ymin) + self.lat), float(km2deg(self.ymax) + self.lat)
                     #  self.polar = True
                 def plot(self):
                     for n, ax in enumerate(self.axes):
                         data = self.data['param'][self.channels[n]]
                         zeniths = numpy.linspace(
 , self.data.meta['max_range'], data.shape[1])
                         if self.mode == 'E':
                             azimuths = -numpy.radians(self.data.yrange)+numpy.pi/2
                             r, theta = numpy.meshgrid(zeniths, azimuths)
                             x, y = r*numpy.cos(theta)*numpy.cos(numpy.radians(self.data.meta['elevation'])), r*numpy.sin(
                                 theta)*numpy.cos(numpy.radians(self.data.meta['elevation']))
                             x = km2deg(x) + self.lon
                             y = km2deg(y) + self.lat
                         else:
                             azimuths = numpy.radians(self.data.yrange)
                             r, theta = numpy.meshgrid(zeniths, azimuths)
                             x, y = r*numpy.cos(theta), r*numpy.sin(theta)
                         self.y = zeniths
                         if ax.firsttime:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.plt = ax.pcolormesh(  # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 vmin=self.zmin,
                                 vmax=self.zmax,
                                 cmap=self.cmaps[n])
                         else:
                             if self.zlimits is not None:
                                 self.zmin, self.zmax = self.zlimits[n]
                             ax.collections.remove(ax.collections[0])
                             ax.plt = ax.pcolormesh(  # r, theta, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 x, y, numpy.ma.array(data, mask=numpy.isnan(data)),
                                 vmin=self.zmin,
                                 vmax=self.zmax,
                                 cmap=self.cmaps[n])
                         if self.mode == 'A':
                             continue
                         # plot district names
                         f = open('/data/workspace/schain_scripts/distrito.csv')
                         for line in f:
                             label, lon, lat = [s.strip() for s in line.split(',') if s]
                             lat = float(lat)
                             lon = float(lon)
                             # ax.plot(lon, lat, '.b', ms=2)
                             ax.text(lon, lat, label.decode('utf8'), ha='center',
                                     va='bottom', size='8', color='black')
                         # plot limites
                         limites = []
                         tmp = []
                         for line in open('/data/workspace/schain_scripts/lima.csv'):
                             if '#' in line:
                                 if tmp:
                                     limites.append(tmp)
                                 tmp = []
                                 continue
                             values = line.strip().split(',')
                             tmp.append((float(values[0]), float(values[1])))
                         for points in limites:
                             ax.add_patch(
                                 Polygon(points, ec='k', fc='none', ls='--', lw=0.5))
                         # plot Cuencas
                         for cuenca in ('rimac', 'lurin', 'mala', 'chillon', 'chilca', 'chancay-huaral'):
                             f = open('/data/workspace/schain_scripts/{}.csv'.format(cuenca))
                             values = [line.strip().split(',') for line in f]
                             points = [(float(s[0]), float(s[1])) for s in values]
                             ax.add_patch(Polygon(points, ec='b', fc='none'))
                         # plot grid
                         for r in (15, 30, 45, 60):
                             ax.add_artist(plt.Circle((self.lon, self.lat),
                                                      km2deg(r), color='0.6', fill=False, lw=0.2))
                             ax.text(
                                 self.lon + (km2deg(r))*numpy.cos(60*numpy.pi/180),
                                 self.lat + (km2deg(r))*numpy.sin(60*numpy.pi/180),
                                 '{}km'.format(r),
                                 ha='center', va='bottom', size='8', color='0.6', weight='heavy')
                     if self.mode == 'E':
                         title = 'El={}$^\circ$'.format(self.data.meta['elevation'])
                         label = 'E{:02d}'.format(int(self.data.meta['elevation']))
                     else:
                         title = 'Az={}$^\circ$'.format(self.data.meta['azimuth'])
                         label = 'A{:02d}'.format(int(self.data.meta['azimuth']))
                     self.save_labels = ['{}-{}'.format(lbl, label) for lbl in self.labels]
                     self.titles = ['{} {}'.format(
                         self.data.parameters[x], title) for x in self.channels]
             class WeatherPlot(Plot):
                 CODE = 'weather'
                 plot_name = 'weather'
                 plot_type = 'ppistyle'
                 buffering = False
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots= 1
                     self.ylabel= 'Range [Km]'
                     self.titles= ['Weather']
                     self.colorbar=False
                     self.width   =8
                     self.height  =8
                     self.ini     =0
                     self.len_azi =0
                     self.buffer_ini  = None
                     self.buffer_azi   = None
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.flag    =0
                     self.indicador= 0
                 def update(self, dataOut):
                     data = {}
                     meta = {}
-                    print("aprox",dataOut.data_360[0])
                     data['weather'] = 10*numpy.log10(dataOut.data_360[0]/(250.0))
-                    #print(data['weather'])
                     data['azi']     = dataOut.data_azi
-                    print("UPDATE",data['azi'])
                     return data, meta
                 def const_ploteo(self,data_weather,data_azi,step,res):
-                    #print("data_weather",data_weather)
-                    print("data_azi",data_azi)
-                    print("step",step)
                     if self.ini==0:
                         #------- AZIMUTH
                         n     = (360/res)-len(data_azi)
                         start = data_azi[-1] + res
                         end   = data_azi[0]  - res
                         if start>end:
                             end        = end + 360
                         azi_vacia = numpy.linspace(start,end,int(n))
                         azi_vacia = numpy.where(azi_vacia>360,azi_vacia-360,azi_vacia)
                         data_azi  = numpy.hstack((data_azi,azi_vacia))
                         # RADAR
                         val_mean         = numpy.mean(data_weather[:,0])
                         data_weather_cmp = numpy.ones([(360-data_weather.shape[0]),data_weather.shape[1]])*val_mean
                         data_weather     = numpy.vstack((data_weather,data_weather_cmp))
                     else:
                         # azimuth
                         flag=0
                         start_azi = self.res_azi[0]
                         start = data_azi[0]
                         end   = data_azi[-1]
                         print("start",start)
                         print("end",end)
                         if start< start_azi:
                             start = start +360
                         if end <start_azi:
                             end  = end +360
                         print("start",start)
                         print("end",end)
                         #### AQUI SERA LA MAGIA
                         pos_ini = int((start-start_azi)/res)
                         len_azi = len(data_azi)
                         if (360-pos_ini)<len_azi:
                             if pos_ini+1==360:
                                 pos_ini=0
                             else:
                                 flag=1
                                 dif= 360-pos_ini
                                 comp= len_azi-dif
                         print(pos_ini)
                         print(len_azi)
                         print("shape",self.res_azi.shape)
                         if flag==0:
                             # AZIMUTH
                             self.res_azi[pos_ini:pos_ini+len_azi] = data_azi
                             # RADAR
                             self.res_weather[pos_ini:pos_ini+len_azi,:] = data_weather
                         else:
                             # AZIMUTH
                             self.res_azi[pos_ini:pos_ini+dif] = data_azi[0:dif]
                             self.res_azi[0:comp]              = data_azi[dif:]
                             # RADAR
                             self.res_weather[pos_ini:pos_ini+dif,:] = data_weather[0:dif,:]
                             self.res_weather[0:comp,:]              = data_weather[dif:,:]
                             flag=0
                         data_azi                                    = self.res_azi
                         data_weather                                = self.res_weather
                     return data_weather,data_azi
                 def plot(self):
                     print("--------------------------------------",self.ini,"-----------------------------------")
                     #numpy.set_printoptions(suppress=True)
                     #print(self.data.times)
                     thisDatetime = datetime.datetime.utcfromtimestamp(self.data.times[-1])
                     data         = self.data[-1]
                     # ALTURA altura_tmp_h
                     altura_h     = (data['weather'].shape[1])/10.0
                     stoprange = float(altura_h*1.5)#stoprange = float(33*1.5) por ahora 400
                     rangestep = float(0.15)
                     r      = numpy.arange(0, stoprange, rangestep)
                     self.y = 2*r
                     # RADAR
                     #data_weather = data['weather']
                     # PEDESTAL
                     #data_azi  = data['azi']
                     res     = 1
                     # STEP
                     step    = (360/(res*data['weather'].shape[0]))
                     #print("shape wr_data", wr_data.shape)
                     #print("shape wr_azi",wr_azi.shape)
                     #print("step",step)
                     print("Time---->",self.data.times[-1],thisDatetime)
                     #print("alturas", len(self.y))
                     self.res_weather, self.res_azi = self.const_ploteo(data_weather=data['weather'],data_azi=data['azi'],step=step,res=res)
                     #numpy.set_printoptions(suppress=True)
                     #print("resultado",self.res_azi)
                     ##########################################################
                     #################    PLOTEO           ###################
                     ##########################################################
                     for i,ax in enumerate(self.axes):
                         if ax.firsttime:
                             plt.clf()
                             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)
                         else:
                             plt.clf()
                             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)
                     caax = cgax.parasites[0]
                     paax = cgax.parasites[1]
                     cbar = plt.gcf().colorbar(pm, pad=0.075)
                     caax.set_xlabel('x_range [km]')
                     caax.set_ylabel('y_range [km]')
                     plt.text(1.0, 1.05, 'azimuth '+str(thisDatetime)+"step"+str(self.ini), transform=caax.transAxes, va='bottom',ha='right')
                     self.ini= self.ini+1

schainpy/model/graphics/jroplot_spectra.py 0 -2

             # Copyright (c) 2012-2021 Jicamarca Radio Observatory
             # All rights reserved.
             #
             # Distributed under the terms of the BSD 3-clause license.
             """Classes to plot Spectra data
             """
             import os
             import numpy
             from schainpy.model.graphics.jroplot_base import Plot, plt, log
             class SpectraPlot(Plot):
                 '''
                 Plot for Spectra data
                 '''
                 CODE = 'spc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 buffering = False
                 def setup(self):
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.height = 2.6 * self.nrows
                     self.cb_label = 'dB'
                     if self.showprofile:
                         self.width = 4 * self.ncols
                     else:
                         self.width = 3.5 * self.ncols
                     self.plots_adjust.update({'wspace': 0.4, 'hspace':0.4, 'left': 0.1, 'right': 0.9, 'bottom': 0.08})
                     self.ylabel = 'Range [km]'
                 def update(self, dataOut):
                     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)
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     if self.CODE == 'spc_moments':
                         data['moments'] = dataOut.moments
                         # data['spc'] = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor)
                     if self.CODE == 'gaussian_fit':
                         # data['moments'] = dataOut.moments
                         data['gaussfit'] = dataOut.DGauFitParams
                         # data['spc'] = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor)
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     if (self.CODE == 'spc_moments') | (self.CODE == 'gaussian_fit'):
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     self.y = y
                     data = self.data[-1]
                     z = data['spc']
                     for n, ax in enumerate(self.axes):
                         noise = data['noise'][n]
                         if self.CODE == 'spc_moments':
                             mean = data['moments'][n, 1]
                         if self.CODE == 'gaussian_fit':
                             # mean = data['moments'][n, 1]
                             gau0 = data['gaussfit'][n][2,:,0]
                             gau1 = data['gaussfit'][n][2,:,1]
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.zmin = self.zmin if self.zmin else numpy.nanmin(z)
                             self.zmax = self.zmax if self.zmax else numpy.nanmax(z)
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plt_profile = self.pf_axes[n].plot(
                                     data['rti'][n], y)[0]
                                 ax.plt_noise = self.pf_axes[n].plot(numpy.repeat(noise, len(y)), y,
                                                                     color="k", linestyle="dashed", lw=1)[0]
                             if self.CODE == 'spc_moments':
                                 ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0]
                             if self.CODE == 'gaussian_fit':
                                 # ax.plt_mean = ax.plot(mean, y, color='k', lw=1)[0]
                                 ax.plt_gau0 = ax.plot(gau0, y, color='r', lw=1)[0]
                                 ax.plt_gau1 = ax.plot(gau1, y, color='y', lw=1)[0]
                         else:
                             ax.plt.set_array(z[n].T.ravel())
                             if self.showprofile:
                                 ax.plt_profile.set_data(data['rti'][n], y)
                                 ax.plt_noise.set_data(numpy.repeat(noise, len(y)), y)
                             if self.CODE == 'spc_moments':
                                 ax.plt_mean.set_data(mean, y)
                             if self.CODE == 'gaussian_fit':
                                 # ax.plt_mean.set_data(mean, y)
                                 ax.plt_gau0.set_data(gau0, y)
                                 ax.plt_gau1.set_data(gau1, y)
                         self.titles.append('CH {}: {:3.2f}dB'.format(n, noise))
             class CrossSpectraPlot(Plot):
                 CODE = 'cspc'
                 colormap = 'jet'
                 plot_type = 'pcolor'
                 zmin_coh = None
                 zmax_coh = None
                 zmin_phase = None
                 zmax_phase = None
                 def setup(self):
                     self.ncols = 4
                     self.nplots = len(self.data.pairs) * 2
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.width = 3.1 * self.ncols
                     self.height = 2.6 * self.nrows
                     self.ylabel = 'Range [km]'
                     self.showprofile = False
                     self.plots_adjust.update({'left': 0.08, 'right': 0.92, 'wspace': 0.5, 'hspace':0.4, 'top':0.95, 'bottom': 0.08})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = dataOut.data_spc
                     cspc = dataOut.data_cspc
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     meta['pairs'] = dataOut.pairsList
                     tmp = []
                     for n, pair in enumerate(meta['pairs']):
                         out = cspc[n] / numpy.sqrt(spc[pair[0]] * spc[pair[1]])
                         coh = numpy.abs(out)
                         phase = numpy.arctan2(out.imag, out.real) * 180 / numpy.pi
                         tmp.append(coh)
                         tmp.append(phase)
                     data['cspc'] = numpy.array(tmp)
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     self.y = y
                     data = self.data[-1]
                     cspc = data['cspc']
                     for n in range(len(self.data.pairs)):
                         pair = self.data.pairs[n]
                         coh = cspc[n*2]
                         phase = cspc[n*2+1]
                         ax = self.axes[2 * n]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, coh.T,
                                                    vmin=0,
                                                    vmax=1,
                                                    cmap=plt.get_cmap(self.colormap_coh)
                                                    )
                         else:
                             ax.plt.set_array(coh.T.ravel())
                         self.titles.append(
                             'Coherence Ch{} * Ch{}'.format(pair[0], pair[1]))
                         ax = self.axes[2 * n + 1]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, phase.T,
                                                    vmin=-180,
                                                    vmax=180,
                                                    cmap=plt.get_cmap(self.colormap_phase)
                                                    )
                         else:
                             ax.plt.set_array(phase.T.ravel())
                         self.titles.append('Phase CH{} * CH{}'.format(pair[0], pair[1]))
             class RTIPlot(Plot):
                 '''
                 Plot for RTI data
                 '''
                 CODE = 'rti'
                 colormap = 'jet'
                 plot_type = 'pcolorbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
-                    print("ch",self.data.channels)
                     self.nrows = len(self.data.channels)
                     self.nplots = len(self.data.channels)
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time'
                     self.cb_label = 'dB'
                     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.nrows)]
                 def update(self, dataOut):
                     data = {}
                     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]
                     self.z = numpy.ma.masked_invalid(self.z)
                     if self.decimation is None:
                         x, y, z = self.fill_gaps(self.x, self.y, self.z)
                     else:
                         x, y, z = self.fill_gaps(*self.decimate())
                     for n, ax in enumerate(self.axes):
                         self.zmin = self.zmin if self.zmin else numpy.min(self.z)
                         self.zmax = self.zmax if self.zmax else numpy.max(self.z)
                         data = self.data[-1]
                         if ax.firsttime:
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
-                                print("test-------------------------------------1")
                                 ax.plot_profile = self.pf_axes[n].plot(
                                     data['rti'][n], self.y)[0]
                                 ax.plot_noise = self.pf_axes[n].plot(numpy.repeat(data['noise'][n], len(self.y)), self.y,
                                                                      color="k", linestyle="dashed", lw=1)[0]
                         else:
                             ax.collections.remove(ax.collections[0])
                             ax.plt = ax.pcolormesh(x, y, z[n].T,
                                                    vmin=self.zmin,
                                                    vmax=self.zmax,
                                                    cmap=plt.get_cmap(self.colormap)
                                                    )
                             if self.showprofile:
                                 ax.plot_profile.set_data(data['rti'][n], self.y)
                                 ax.plot_noise.set_data(numpy.repeat(
                                     data['noise'][n], len(self.y)), self.y)
             class CoherencePlot(RTIPlot):
                 '''
                 Plot for Coherence data
                 '''
                 CODE = 'coh'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = len(self.data.pairs)
                     self.nplots = len(self.data.pairs)
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Time'
                     self.plots_adjust.update({'hspace':0.6, 'left': 0.1, 'bottom': 0.1,'right':0.95})
                     if self.CODE == 'coh':
                         self.cb_label = ''
                         self.titles = [
                             'Coherence Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
                     else:
                         self.cb_label = 'Degrees'
                         self.titles = [
                             'Phase Map Ch{} * Ch{}'.format(x[0], x[1]) for x in self.data.pairs]
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['coh'] = dataOut.getCoherence()
                     meta['pairs'] = dataOut.pairsList
                     return data, meta
             class PhasePlot(CoherencePlot):
                 '''
                 Plot for Phase map data
                 '''
                 CODE = 'phase'
                 colormap = 'seismic'
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['phase'] = dataOut.getCoherence(phase=True)
                     meta['pairs'] = dataOut.pairsList
                     return data, meta
             class NoisePlot(Plot):
                 '''
                 Plot for noise
                 '''
                 CODE = 'noise'
                 plot_type = 'scatterbuffer'
                 def setup(self):
                     self.xaxis = 'time'
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.ylabel = 'Intensity [dB]'
                     self.xlabel = 'Time'
                     self.titles = ['Noise']
                     self.colorbar = False
                     self.plots_adjust.update({'right': 0.85 })
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor).reshape(dataOut.nChannels, 1)
                     meta['yrange'] = numpy.array([])
                     return data, meta
                 def plot(self):
                     x = self.data.times
                     xmin = self.data.min_time
                     xmax = xmin + self.xrange * 60 * 60
                     Y = self.data['noise']
                     if self.axes[0].firsttime:
                         self.ymin = numpy.nanmin(Y) - 5
                         self.ymax = numpy.nanmax(Y) + 5
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].plot(x, y, lw=1, label='Ch{}'.format(ch))
                         plt.legend(bbox_to_anchor=(1.18, 1.0))
                     else:
                         for ch in self.data.channels:
                             y = Y[ch]
                             self.axes[0].lines[ch].set_data(x, y)
             class PowerProfilePlot(Plot):
                 CODE = 'pow_profile'
                 plot_type = 'scatter'
                 def setup(self):
                     self.ncols = 1
                     self.nrows = 1
                     self.nplots = 1
                     self.height = 4
                     self.width = 3
                     self.ylabel = 'Range [km]'
                     self.xlabel = 'Intensity [dB]'
                     self.titles = ['Power Profile']
                     self.colorbar = False
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     data[self.CODE] = dataOut.getPower()
                     return data, meta
                 def plot(self):
                     y = self.data.yrange
                     self.y = y
                     x = self.data[-1][self.CODE]
                     if self.xmin is None: self.xmin = numpy.nanmin(x)*0.9
                     if self.xmax is None: self.xmax = numpy.nanmax(x)*1.1
                     if self.axes[0].firsttime:
                         for ch in self.data.channels:
                             self.axes[0].plot(x[ch], y, lw=1, label='Ch{}'.format(ch))
                         plt.legend()
                     else:
                         for ch in self.data.channels:
                             self.axes[0].lines[ch].set_data(x[ch], y)
             class SpectraCutPlot(Plot):
                 CODE = 'spc_cut'
                 plot_type = 'scatter'
                 buffering = False
                 def setup(self):
                     self.nplots = len(self.data.channels)
                     self.ncols = int(numpy.sqrt(self.nplots) + 0.9)
                     self.nrows = int((1.0 * self.nplots / self.ncols) + 0.9)
                     self.width = 3.4 * self.ncols + 1.5
                     self.height = 3 * self.nrows
                     self.ylabel = 'Power [dB]'
                     self.colorbar = False
                     self.plots_adjust.update({'left':0.1, 'hspace':0.3, 'right': 0.75, 'bottom':0.08})
                 def update(self, dataOut):
                     data = {}
                     meta = {}
                     spc = 10*numpy.log10(dataOut.data_pre[0]/dataOut.normFactor)
                     data['spc'] = spc
                     meta['xrange'] = (dataOut.getFreqRange(1)/1000., dataOut.getAcfRange(1), dataOut.getVelRange(1))
                     if self.CODE == 'cut_gaussian_fit':
                         data['gauss_fit0'] = 10*numpy.log10(dataOut.GaussFit0/dataOut.normFactor)
                         data['gauss_fit1'] = 10*numpy.log10(dataOut.GaussFit1/dataOut.normFactor)
                     return data, meta
                 def plot(self):
                     if self.xaxis == "frequency":
                         x = self.data.xrange[0][1:]
                         self.xlabel = "Frequency (kHz)"
                     elif self.xaxis == "time":
                         x = self.data.xrange[1]
                         self.xlabel = "Time (ms)"
                     else:
                         x = self.data.xrange[2][:-1]
                         self.xlabel = "Velocity (m/s)"
                     if self.CODE == 'cut_gaussian_fit':
                         x = self.data.xrange[2][:-1]
                         self.xlabel = "Velocity (m/s)"
                     self.titles = []
                     y = self.data.yrange
                     data = self.data[-1]
                     z = data['spc']
                     if self.height_index:
                         index = numpy.array(self.height_index)
                     else:
                         index = numpy.arange(0, len(y), int((len(y))/9))
                     for n, ax in enumerate(self.axes):
                         if self.CODE == 'cut_gaussian_fit':
                             gau0 = data['gauss_fit0']
                             gau1 = data['gauss_fit1']
                         if ax.firsttime:
                             self.xmax = self.xmax if self.xmax else numpy.nanmax(x)
                             self.xmin = self.xmin if self.xmin else -self.xmax
                             self.ymin = self.ymin if self.ymin else numpy.nanmin(z)
                             self.ymax = self.ymax if self.ymax else numpy.nanmax(z)
                             ax.plt = ax.plot(x, z[n, :, index].T, lw=0.25)
                             if self.CODE == 'cut_gaussian_fit':
                                 ax.plt_gau0 = ax.plot(x, gau0[n, :, index].T, lw=1, linestyle='-.')
                                 for i, line in enumerate(ax.plt_gau0):
                                     line.set_color(ax.plt[i].get_color())
                                 ax.plt_gau1 = ax.plot(x, gau1[n, :, index].T, lw=1, linestyle='--')
                                 for i, line in enumerate(ax.plt_gau1):
                                     line.set_color(ax.plt[i].get_color())
                             labels = ['Range = {:2.1f}km'.format(y[i]) for i in index]
                             self.figures[0].legend(ax.plt, labels, loc='center right')
                         else:
                             for i, line in enumerate(ax.plt):
                                 line.set_data(x, z[n, :, index[i]].T)
                             for i, line in enumerate(ax.plt_gau0):
                                 line.set_data(x, gau0[n, :, index[i]].T)
                                 line.set_color(ax.plt[i].get_color())
                             for i, line in enumerate(ax.plt_gau1):
                                 line.set_data(x, gau1[n, :, index[i]].T)
                                 line.set_color(ax.plt[i].get_color())
                         self.titles.append('CH {}'.format(n))
             class BeaconPhase(Plot):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'beacon_phase'
                 def __init__(self):
                     Plot.__init__(self)
                     self.timerange = 24*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 800
                     self.HEIGHT = 400
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = BEACON_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.filename_phase = None
                     self.figfile = None
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 7
                     colspan = 6
                     self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH+self.WIDTHPROF,
                                       heightplot = self.HEIGHT+self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1)
                 def save_phase(self, filename_phase):
                     f = open(filename_phase,'w+')
                     f.write('\n\n')
                     f.write('JICAMARCA RADIO OBSERVATORY - Beacon Phase \n')
                     f.write('DD MM YYYY  HH MM SS   pair(2,0) pair(2,1) pair(2,3) pair(2,4)\n\n' )
                     f.close()
                 def save_data(self, filename_phase, data, data_datetime):
                     f=open(filename_phase,'a')
                     timetuple_data = data_datetime.timetuple()
                     day = str(timetuple_data.tm_mday)
                     month = str(timetuple_data.tm_mon)
                     year = str(timetuple_data.tm_year)
                     hour = str(timetuple_data.tm_hour)
                     minute = str(timetuple_data.tm_min)
                     second = str(timetuple_data.tm_sec)
                     f.write(day+' '+month+' '+year+'  '+hour+' '+minute+' '+second+'   '+str(data[0])+'   '+str(data[1])+'   '+str(data[2])+'   '+str(data[3])+'\n')
                     f.close()
                 def plot(self):
                     log.warning('TODO: Not yet implemented...')
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, hmin=None, hmax=None,
                         timerange=None,
                         save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if dataOut.flagNoData:
                         return dataOut
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList[:10]
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError("Pair %s is not in dataOut.pairsList" %(pair))
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if pairsIndexList == []:
                         return
              #         if len(pairsIndexList) > 4:
              #             pairsIndexList = pairsIndexList[0:4]
                     hmin_index = None
                     hmax_index = None
                     if hmin != None and hmax != None:
                         indexes = numpy.arange(dataOut.nHeights)
                         hmin_list = indexes[dataOut.heightList >= hmin]
                         hmax_list = indexes[dataOut.heightList <= hmax]
                         if hmin_list.any():
                             hmin_index = hmin_list[0]
                         if hmax_list.any():
                             hmax_index = hmax_list[-1]+1
                     x = dataOut.getTimeRange()
                     thisDatetime = dataOut.datatime
                     title = wintitle + " Signal Phase" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase (degrees)"
                     update_figfile = False
                     nplots = len(pairsIndexList)
                     #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = numpy.zeros(len(pairsIndexList))
                     for i in range(nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i], :, hmin_index:hmax_index], axis=0)
                         powa = numpy.average(dataOut.data_spc[pair[0], :, hmin_index:hmax_index], axis=0)
                         powb = numpy.average(dataOut.data_spc[pair[1], :, hmin_index:hmax_index], axis=0)
                         avgcoherenceComplex = ccf/numpy.sqrt(powa*powb)
                         phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi
                         if dataOut.beacon_heiIndexList:
                             phase_beacon[i] = numpy.average(phase[dataOut.beacon_heiIndexList])
                         else:
                             phase_beacon[i] = numpy.average(phase)
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = 0
                         if ymax == None: ymax = 360
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.name = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         self.isConfig = True
                         self.figfile = figfile
                         self.xdata = numpy.array([])
                         self.ydata = numpy.array([])
                         update_figfile = True
                         #open file beacon phase
                         path = '%s%03d' %(self.PREFIX, self.id)
                         beacon_file = os.path.join(path,'%s.txt'%self.name)
                         self.filename_phase = os.path.join(figpath,beacon_file)
                         #self.save_phase(self.filename_phase)
                     #store data beacon phase
                     #self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Plot %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["Pair (%d,%d)"%(pair[0], pair[1]) for pair in dataOut.pairsList]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata)==0:
                         self.ydata = phase_beacon.reshape(-1,1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, phase_beacon.reshape(-1,1)))
                     axes.pmultilineyaxis(x=self.xdata, y=self.ydata,
                                 xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax,
                                 xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='x', markersize=8, linestyle="solid",
                                 XAxisAsTime=True, grid='both'
                                 )
                     self.draw()
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     return dataOut

schainpy/model/proc/jroproc_parameters.py 0 0

	1	NO CONTENT: modified file			NO CONTENT: modified file
The requested commit or file is too big and content was truncated. Show full diff

schainpy/model/proc/jroproc_voltage.py +1 0

             import sys
             import numpy,math
             from scipy import interpolate
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator
             from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon
             from schainpy.utils import log
             from time import time
             class VoltageProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.dataOut = Voltage()
                     self.flip = 1
                     self.setupReq = False
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.__updateObjFromAmisrInput()
                     if self.dataIn.type == 'Voltage':
                         self.dataOut.copy(self.dataIn)
                 def __updateObjFromAmisrInput(self):
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.dstFlag = self.dataIn.dstFlag
                     self.dataOut.errorCount = self.dataIn.errorCount
                     self.dataOut.useLocalTime = self.dataIn.useLocalTime
                     self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.data = self.dataIn.data
                     self.dataOut.utctime = self.dataIn.utctime
                     self.dataOut.channelList = self.dataIn.channelList
                     #self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.nProfiles = self.dataIn.nProfiles
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.azimuth = self.dataIn.azimuth
                     self.dataOut.zenith = self.dataIn.zenith
                     self.dataOut.beam.codeList = self.dataIn.beam.codeList
                     self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
                     self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
             class selectChannels(Operation):
                 def run(self, dataOut, channelList):
                     channelIndexList = []
                     self.dataOut = dataOut
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList)))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                     return self.dataOut
                 def selectChannelsByIndex(self, channelIndexList):
                     """
                     Selecciona un bloque de datos en base a canales segun el channelIndexList
                     Input:
                         channelIndexList    :    lista sencilla de canales a seleccionar por ej. [2,3,7]
                     Affected:
                         self.dataOut.data
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                         self.dataOut.m_ProcessingHeader.totalSpectra
                         self.dataOut.systemHeaderObj.numChannels
                         self.dataOut.m_ProcessingHeader.blockSize
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError("The value %d in channelIndexList is not valid" %channelIndex)
                     if self.dataOut.type == 'Voltage':
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[channelIndexList,:,:]
                         else:
                             data = self.dataOut.data[channelIndexList,:]
                         self.dataOut.data = data
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                     elif self.dataOut.type == 'Spectra':
                         data_spc = self.dataOut.data_spc[channelIndexList, :]
                         data_dc = self.dataOut.data_dc[channelIndexList, :]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_dc = data_dc
                         # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                         self.dataOut.channelList = range(len(channelIndexList))
                         self.__selectPairsByChannel(channelIndexList)
                     return 1
                 def __selectPairsByChannel(self, channelList=None):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for pairIndex in self.dataOut.pairsIndexList:
                         # First pair
                         if self.dataOut.pairsList[pairIndex][0] not in channelList:
                             continue
                         # Second pair
                         if self.dataOut.pairsList[pairIndex][1] not in channelList:
                             continue
                         pairsIndexListSelected.append(pairIndex)
                     if not pairsIndexListSelected:
                         self.dataOut.data_cspc = None
                         self.dataOut.pairsList = []
                         return
                     self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected]
                     self.dataOut.pairsList = [self.dataOut.pairsList[i]
                                               for i in pairsIndexListSelected]
                     return
             class selectHeights(Operation):
                 def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None):
                     """
                     Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango
                     minHei <= height <= maxHei
                     Input:
                         minHei    :    valor minimo de altura a considerar
                         maxHei    :    valor maximo de altura a considerar
                     Affected:
                         Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     self.dataOut = dataOut
                     if minHei and maxHei:
                         if (minHei < self.dataOut.heightList[0]):
                             minHei = self.dataOut.heightList[0]
                         if (maxHei > self.dataOut.heightList[-1]):
                             maxHei = self.dataOut.heightList[-1]
                         minIndex = 0
                         maxIndex = 0
                         heights = self.dataOut.heightList
                         inda = numpy.where(heights >= minHei)
                         indb = numpy.where(heights <= maxHei)
                         try:
                             minIndex = inda[0][0]
                         except:
                             minIndex = 0
                         try:
                             maxIndex = indb[0][-1]
                         except:
                             maxIndex = len(heights)
                     self.selectHeightsByIndex(minIndex, maxIndex)
                     return self.dataOut
                 def selectHeightsByIndex(self, minIndex, maxIndex):
                     """
                     Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango
                     minIndex <= index <= maxIndex
                     Input:
                         minIndex    :    valor de indice minimo de altura a considerar
                         maxIndex    :    valor de indice maximo de altura a considerar
                     Affected:
                         self.dataOut.data
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     if self.dataOut.type == 'Voltage':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights
                         #voltage
                         if self.dataOut.flagDataAsBlock:
                             """
                             Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                             """
                             data = self.dataOut.data[:,:, minIndex:maxIndex]
                         else:
                             data = self.dataOut.data[:, minIndex:maxIndex]
                         #         firstHeight = self.dataOut.heightList[minIndex]
                         self.dataOut.data = data
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex]
                         if self.dataOut.nHeights <= 1:
                             raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights))
                     elif self.dataOut.type == 'Spectra':
                         if (minIndex < 0) or (minIndex > maxIndex):
                             raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (
                                 minIndex, maxIndex))
                         if (maxIndex >= self.dataOut.nHeights):
                             maxIndex = self.dataOut.nHeights - 1
                         # Spectra
                         data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1]
                         data_cspc = None
                         if self.dataOut.data_cspc is not None:
                             data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1]
                         data_dc = None
                         if self.dataOut.data_dc is not None:
                             data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1]
                         self.dataOut.data_spc = data_spc
                         self.dataOut.data_cspc = data_cspc
                         self.dataOut.data_dc = data_dc
                         self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1]
                     return 1
             class filterByHeights(Operation):
                 def run(self, dataOut, window):
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     if window == None:
                         window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
                     newdelta = deltaHeight * window
                     r = dataOut.nHeights % window
                     newheights = (dataOut.nHeights-r)/window
                     if newheights <= 1:
                         raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window))
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = dataOut.data[:,0:int(dataOut.nHeights-r)]
                         buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window))
                         buffer = numpy.sum(buffer,2)
                     dataOut.data = buffer
                     dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta
                     dataOut.windowOfFilter = window
                     return dataOut
             class setH0(Operation):
                 def run(self, dataOut, h0, deltaHeight = None):
                     if not deltaHeight:
                         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     nHeights = dataOut.nHeights
                     newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight
                     dataOut.heightList = newHeiRange
                     return dataOut
             class deFlip(Operation):
                 def run(self, dataOut, channelList = []):
                     data = dataOut.data.copy()
                     if dataOut.flagDataAsBlock:
                         flip = self.flip
                         profileList = list(range(dataOut.nProfiles))
                         if not channelList:
                             for thisProfile in profileList:
                                 data[:,thisProfile,:] = data[:,thisProfile,:]*flip
                                 flip *= -1.0
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 for thisProfile in profileList:
                                     data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip
                                     flip *= -1.0
                         self.flip = flip
                     else:
                         if not channelList:
                             data[:,:] = data[:,:]*self.flip
                         else:
                             for thisChannel in channelList:
                                 if thisChannel not in dataOut.channelList:
                                     continue
                                 data[thisChannel,:] = data[thisChannel,:]*self.flip
                         self.flip *= -1.
                     dataOut.data = data
                     return dataOut
             class setAttribute(Operation):
                 '''
                 Set an arbitrary attribute(s) to dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                     self._ready = False
                 def run(self, dataOut, **kwargs):
                     for key, value in kwargs.items():
                         setattr(dataOut, key, value)
                     return dataOut
             @MPDecorator
             class printAttribute(Operation):
                 '''
                 Print an arbitrary attribute of dataOut
                 '''
                 def __init__(self):
                     Operation.__init__(self)
                 def run(self, dataOut, attributes):
                     if isinstance(attributes, str):
                         attributes = [attributes]
                     for attr in attributes:
                         if hasattr(dataOut, attr):
                             log.log(getattr(dataOut, attr), attr)
             class interpolateHeights(Operation):
                 def run(self, dataOut, topLim, botLim):
                     #69 al 72 para julia
                     #82-84 para meteoros
                     if len(numpy.shape(dataOut.data))==2:
                         sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2
                         sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1)))
                         #dataOut.data[:,botLim:limSup+1] = sampInterp
                         dataOut.data[:,botLim:topLim+1] = sampInterp
                     else:
                         nHeights = dataOut.data.shape[2]
                         x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights)))
                         y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))]
                         f = interpolate.interp1d(x, y, axis = 2)
                         xnew = numpy.arange(botLim,topLim+1)
                         ynew = f(xnew)
                         dataOut.data[:,:,botLim:topLim+1]  = ynew
                     return dataOut
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __bufferStride = []
                 __dataReady = False
                 __profIndexStride = 0
                 __dataToPutStride = False
                 n = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
                         n               :    Number of coherent integrations
                         timeInterval    :    Time of integration. If the parameter "n" is selected this one does not work
                         overlapping     :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = None
                     self.__dataReady = False
                     self.byblock = byblock
                     self.stride = stride
                     if n == None and timeInterval == None:
                         raise ValueError("n or timeInterval should be specified ...")
                     if n != None:
                         self.n = n
                         self.__byTime = False
                     else:
                         self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line
                         self.n = 9999
                         self.__byTime = True
                     if overlapping:
                         self.__withOverlapping = True
                         self.__buffer = None
                     else:
                         self.__withOverlapping = False
                         self.__buffer = 0
                     self.__profIndex = 0
                 def putData(self, data):
                     """
                     Add a profile to the __buffer and increase in one the __profileIndex
                     """
                     if not self.__withOverlapping:
                         self.__buffer += data.copy()
                         self.__profIndex += 1
                         return
                     #Overlapping data
                     nChannels, nHeis = data.shape
                     data = numpy.reshape(data, (1, nChannels, nHeis))
                     #If the buffer is empty then it takes the data value
                     if self.__buffer is None:
                         self.__buffer = data
                         self.__profIndex += 1
                         return
                     #If the buffer length is lower than n then stakcing the data value
                     if self.__profIndex < self.n:
                         self.__buffer = numpy.vstack((self.__buffer, data))
                         self.__profIndex += 1
                         return
                     #If the buffer length is equal to n then replacing the last buffer value with the data value
                     self.__buffer = numpy.roll(self.__buffer, -1, axis=0)
                     self.__buffer[self.n-1] = data
                     self.__profIndex = self.n
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     if not self.__withOverlapping:
                         data = self.__buffer
                         n = self.__profIndex
                         self.__buffer = 0
                         self.__profIndex = 0
                         return data, n
                     #Integration with Overlapping
                     data = numpy.sum(self.__buffer, axis=0)
                     # print data
                     # raise
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
                     #         n = None
                     # print data
                     # raise
                     self.putData(data)
                     if self.__profIndex == self.n:
                         avgdata, n = self.pushData()
                         self.__dataReady = True
                     return avgdata
                 def byTime(self, data, datatime):
                     self.__dataReady = False
                     avgdata = None
                     n = None
                     self.putData(data)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata
                 def integrateByStride(self, data, datatime):
                     # print data
                     if self.__profIndex == 0:
                         self.__buffer = [[data.copy(), datatime]]
                     else:
                         self.__buffer.append([data.copy(),datatime])
                     self.__profIndex += 1
                     self.__dataReady = False
                     if self.__profIndex == self.n * self.stride :
                         self.__dataToPutStride = True
                         self.__profIndexStride = 0
                         self.__profIndex = 0
                         self.__bufferStride = []
                         for i in range(self.stride):
                             current = self.__buffer[i::self.stride]
                             data = numpy.sum([t[0] for t in current], axis=0)
                             avgdatatime = numpy.average([t[1] for t in current])
                             # print data
                             self.__bufferStride.append((data, avgdatatime))
                     if self.__dataToPutStride:
                         self.__dataReady = True
                         self.__profIndexStride += 1
                         if self.__profIndexStride == self.stride:
                             self.__dataToPutStride = False
                         # print self.__bufferStride[self.__profIndexStride - 1]
                         # raise
                         return self.__bufferStride[self.__profIndexStride - 1]
                     return None, None
                 def integrate(self, data, datatime=None):
                     if self.__initime == None:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata = self.byTime(data, datatime)
                     else:
                         avgdata = self.byProfiles(data)
                     self.__lastdatatime = datatime
                     if avgdata is None:
                         return None, None
                     avgdatatime = self.__initime
                     deltatime = datatime - self.__lastdatatime
                     if not self.__withOverlapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
                 def integrateByBlock(self, dataOut):
                     times = int(dataOut.data.shape[1]/self.n)
                     avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex)
                     id_min = 0
                     id_max = self.n
                     for i in range(times):
                         junk = dataOut.data[:,id_min:id_max,:]
                         avgdata[:,i,:] = junk.sum(axis=1)
                         id_min += self.n
                         id_max += self.n
                     timeInterval = dataOut.ippSeconds*self.n
                     avgdatatime = (times - 1) * timeInterval + dataOut.utctime
                     self.__dataReady = True
                     return avgdata, avgdatatime
                 def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         """
                         Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         avgdata, avgdatatime = self.integrateByBlock(dataOut)
                         dataOut.nProfiles /= self.n
                     else:
                         if stride is None:
                             avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
                         else:
                             avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime)
                     #   dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         if not dataOut.flagCohInt:
                             dataOut.nCohInt *= self.n
                             dataOut.flagCohInt = True
                         dataOut.utctime = avgdatatime
                         # print avgdata, avgdatatime
                         # raise
                         #   dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
                     return dataOut
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.times = None
                     self.osamp = None
                 #         self.__setValues = False
                     self.isConfig = False
                     self.setupReq = False
                 def setup(self, code, osamp, dataOut):
                     self.__profIndex = 0
                     self.code = code
                     self.nCode = len(code)
                     self.nBaud = len(code[0])
                     if (osamp != None) and (osamp >1):
                         self.osamp = osamp
                         self.code = numpy.repeat(code, repeats=self.osamp, axis=1)
                         self.nBaud = self.nBaud*self.osamp
                     self.__nChannels = dataOut.nChannels
                     self.__nProfiles = dataOut.nProfiles
                     self.__nHeis = dataOut.nHeights
                     if self.__nHeis < self.nBaud:
                         raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud))
                     #Frequency
                     __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex)
                     __codeBuffer[:,0:self.nBaud] = self.code
                     self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1))
                     if dataOut.flagDataAsBlock:
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex)
                     else:
                         #Time
                         self.ndatadec = self.__nHeis #- self.nBaud + 1
                         self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex)
                 def __convolutionInFreq(self, data):
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=1)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=1)
                     return data
                 def __convolutionInFreqOpt(self, data):
                     raise NotImplementedError
                 def __convolutionInTime(self, data):
                     code = self.code[self.__profIndex]
                     for i in range(self.__nChannels):
                         self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInTime(self, data):
                     repetitions = int(self.__nProfiles / self.nCode)
                     junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize))
                     junk = junk.flatten()
                     code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud))
                     profilesList = range(self.__nProfiles)
                     for i in range(self.__nChannels):
                         for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                     return self.datadecTime
                 def __convolutionByBlockInFreq(self, data):
                     raise NotImplementedError("Decoder by frequency fro Blocks not implemented")
                     fft_code = self.fft_code[self.__profIndex].reshape(1,-1)
                     fft_data = numpy.fft.fft(data, axis=2)
                     conv = fft_data*fft_code
                     data = numpy.fft.ifft(conv,axis=2)
                     return data
                 def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None):
                     if dataOut.flagDecodeData:
                         print("This data is already decoded, recoding again ...")
                     if not self.isConfig:
                         if code is None:
                             if dataOut.code is None:
                                 raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type)
                             code = dataOut.code
                         else:
                             code = numpy.array(code).reshape(nCode,nBaud)
                         self.setup(code, osamp, dataOut)
                         self.isConfig = True
                         if mode == 3:
                             sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode)
                         if times != None:
                             sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n")
                     if self.code is None:
                         print("Fail decoding: Code is not defined.")
                         return
                     self.__nProfiles = dataOut.nProfiles
                     datadec = None
                     if mode == 3:
                         mode = 0
                     if dataOut.flagDataAsBlock:
                         """
                         Decoding when data have been read as block,
                         """
                         if mode == 0:
                             datadec = self.__convolutionByBlockInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionByBlockInFreq(dataOut.data)
                     else:
                         """
                         Decoding when data have been read profile by profile
                         """
                         if mode == 0:
                             datadec = self.__convolutionInTime(dataOut.data)
                         if mode == 1:
                             datadec = self.__convolutionInFreq(dataOut.data)
                         if mode == 2:
                             datadec = self.__convolutionInFreqOpt(dataOut.data)
                     if datadec is None:
                         raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode)
                     dataOut.code = self.code
                     dataOut.nCode = self.nCode
                     dataOut.nBaud = self.nBaud
                     dataOut.data = datadec
                     dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]]
                     dataOut.flagDecodeData = True #asumo q la data esta decodificada
                     if self.__profIndex == self.nCode-1:
                         self.__profIndex = 0
                         return dataOut
                     self.__profIndex += 1
                     return dataOut
                 #        dataOut.flagDeflipData = True #asumo q la data no esta sin flip
             class ProfileConcat(Operation):
                 isConfig = False
                 buffer = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def reset(self):
                     self.buffer = numpy.zeros_like(self.buffer)
                     self.start_index = 0
                     self.times = 1
                 def setup(self, data, m, n=1):
                     self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0]))
                     self.nHeights = data.shape[1]#.nHeights
                     self.start_index = 0
                     self.times = 1
                 def concat(self, data):
                     self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy()
                     self.start_index = self.start_index + self.nHeights
                 def run(self, dataOut, m):
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(dataOut.data, m, 1)
                         self.isConfig = True
                     if dataOut.flagDataAsBlock:
                         raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False")
                     else:
                         self.concat(dataOut.data)
                         self.times += 1
                         if self.times > m:
                             dataOut.data = self.buffer
                             self.reset()
                             dataOut.flagNoData = False
                             # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas
                             deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                             xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m
                             dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight)
                             dataOut.ippSeconds *= m
                     return dataOut
             class ProfileSelector(Operation):
                 profileIndex = None
                 # Tamanho total de los perfiles
                 nProfiles = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.profileIndex = 0
                 def incProfileIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isThisProfileInRange(self, profileIndex, minIndex, maxIndex):
                     if profileIndex < minIndex:
                         return False
                     if profileIndex > maxIndex:
                         return False
                     return True
                 def isThisProfileInList(self, profileIndex, profileList):
                     if profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None):
                     """
                     ProfileSelector:
                     Inputs:
                         profileList        :    Index of profiles selected. Example: profileList = (0,1,2,7,8)
                         profileRangeList    :    Minimum and maximum profile indexes. Example: profileRangeList = (4, 30)
                         rangeList            :    List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256))
                     """
                     if rangeList is not None:
                         if type(rangeList[0]) not in (tuple, list):
                             rangeList = [rangeList]
                     dataOut.flagNoData = True
                     if dataOut.flagDataAsBlock:
                         """
                         data dimension  = [nChannels, nProfiles, nHeis]
                         """
                         if profileList != None:
                             dataOut.data = dataOut.data[:,profileList,:]
                         if profileRangeList != None:
                             minIndex = profileRangeList[0]
                             maxIndex = profileRangeList[1]
                             profileList = list(range(minIndex, maxIndex+1))
                             dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:]
                         if rangeList != None:
                             profileList = []
                             for thisRange in rangeList:
                                 minIndex = thisRange[0]
                                 maxIndex = thisRange[1]
                                 profileList.extend(list(range(minIndex, maxIndex+1)))
                             dataOut.data = dataOut.data[:,profileList,:]
                         dataOut.nProfiles = len(profileList)
                         dataOut.profileIndex = dataOut.nProfiles - 1
                         dataOut.flagNoData = False
                         return dataOut
                     """
                     data dimension  = [nChannels, nHeis]
                     """
                     if profileList != None:
                         if self.isThisProfileInList(dataOut.profileIndex, profileList):
                             self.nProfiles = len(profileList)
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if profileRangeList != None:
                         minIndex = profileRangeList[0]
                         maxIndex = profileRangeList[1]
                         if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                             self.nProfiles = maxIndex - minIndex + 1
                             dataOut.nProfiles = self.nProfiles
                             dataOut.profileIndex = self.profileIndex
                             dataOut.flagNoData = False
                             self.incProfileIndex()
                         return dataOut
                     if rangeList != None:
                         nProfiles = 0
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             nProfiles += maxIndex - minIndex + 1
                         for thisRange in rangeList:
                             minIndex = thisRange[0]
                             maxIndex = thisRange[1]
                             if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex):
                                 self.nProfiles = nProfiles
                                 dataOut.nProfiles = self.nProfiles
                                 dataOut.profileIndex = self.profileIndex
                                 dataOut.flagNoData = False
                                 self.incProfileIndex()
                                 break
                         return dataOut
                     if beam != None: #beam is only for AMISR data
                         if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]):
                             dataOut.flagNoData = False
                             dataOut.profileIndex = self.profileIndex
                             self.incProfileIndex()
                         return dataOut
                     raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter")
             class Reshaper(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__buffer = None
                     self.__nitems = 0
                 def __appendProfile(self, dataOut, nTxs):
                     if self.__buffer is None:
                         shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) )
                         self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype)
                     ini = dataOut.nHeights * self.__nitems
                     end = ini + dataOut.nHeights
                     self.__buffer[:, ini:end] = dataOut.data
                     self.__nitems += 1
                     return int(self.__nitems*nTxs)
                 def __getBuffer(self):
                     if self.__nitems == int(1./self.__nTxs):
                         self.__nitems = 0
                         return self.__buffer.copy()
                     return None
                 def __checkInputs(self, dataOut, shape, nTxs):
                     if shape is None and nTxs is None:
                         raise ValueError("Reshaper: shape of factor should be defined")
                     if nTxs:
                         if nTxs < 0:
                             raise ValueError("nTxs should be greater than 0")
                         if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0:
                             raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)))
                         shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs]
                         return shape, nTxs
                     if len(shape) != 2 and len(shape) !=  3:
                         raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights))
                     if len(shape) == 2:
                         shape_tuple = [dataOut.nChannels]
                         shape_tuple.extend(shape)
                     else:
                         shape_tuple = list(shape)
                     nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles
                     return shape_tuple, nTxs
                 def run(self, dataOut, shape=None, nTxs=None):
                     shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs)
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         dataOut.data = numpy.reshape(dataOut.data, shape_tuple)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1
                     else:
                         if self.__nTxs < 1:
                             self.__appendProfile(dataOut, self.__nTxs)
                             new_data = self.__getBuffer()
                             if new_data is not None:
                                 dataOut.data = new_data
                                 dataOut.flagNoData = False
                                 profileIndex = dataOut.profileIndex*nTxs
                         else:
                             raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= self.__nTxs
                     return dataOut
             class SplitProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         if shape[2] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]))
                         new_shape = shape[0], shape[1]*n, int(shape[2]/n)
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles/n) - 1
                     else:
                         raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)")
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles*n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds /= n
                     return dataOut
             class CombineProfiles(Operation):
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.__remData = None
                     self.__profileIndex = 0
                 def run(self, dataOut, n):
                     dataOut.flagNoData = True
                     profileIndex = None
                     if dataOut.flagDataAsBlock:
                         #nchannels, nprofiles, nsamples
                         shape = dataOut.data.shape
                         new_shape = shape[0], shape[1]/n, shape[2]*n
                         if shape[1] % n != 0:
                             raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]))
                         dataOut.data = numpy.reshape(dataOut.data, new_shape)
                         dataOut.flagNoData = False
                         profileIndex = int(dataOut.nProfiles*n) - 1
                     else:
                         #nchannels, nsamples
                         if self.__remData is None:
                             newData = dataOut.data
                         else:
                             newData = numpy.concatenate((self.__remData, dataOut.data), axis=1)
                         self.__profileIndex += 1
                         if self.__profileIndex < n:
                             self.__remData = newData
                             #continue
                             return
                         self.__profileIndex = 0
                         self.__remData = None
                         dataOut.data = newData
                         dataOut.flagNoData = False
                         profileIndex = dataOut.profileIndex/n
                     deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
                     dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0]
                     dataOut.nProfiles = int(dataOut.nProfiles/n)
                     dataOut.profileIndex = profileIndex
                     dataOut.ippSeconds *= n
                     return dataOut
             class PulsePair(Operation):
                 '''
                 Function PulsePair(Signal Power, Velocity)
                 The real component of Lag[0] provides Intensity Information
                 The imag component of Lag[1] Phase provides Velocity Information
                 Configuration Parameters:
                 nPRF = Number of Several PRF
                 theta = Degree Azimuth angel Boundaries
                 Input:
                       self.dataOut
                       lag[N]
                 Affected:
                       self.dataOut.spc
                 '''
                 isConfig       = False
                 __profIndex    = 0
                 __initime      = None
                 __lastdatatime = None
                 __buffer       = None
                 noise          = None
                 __dataReady    = False
                 n              = None
                 __nch          = 0
                 __nHeis        = 0
                 removeDC       = False
                 ipp            = None
                 lambda_        = 0
                 def __init__(self,**kwargs):
                     Operation.__init__(self,**kwargs)
                 def setup(self, dataOut, n = None, removeDC=False):
                     '''
                     n= Numero de PRF's de entrada
                     '''
                     print("[INICIO]-setup  del METODO PULSE PAIR")
                     self.__initime        = None
                     self.__lastdatatime   = 0
                     self.__dataReady      = False
                     self.__buffer         = 0
                     self.__profIndex      = 0
                     self.noise            = None
                     self.__nch            = dataOut.nChannels
                     self.__nHeis          = dataOut.nHeights
                     self.removeDC         = removeDC
                     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.")
                     if n != None:
                         if n<2:
                             raise ValueError("n should be greater than 2")
                     self.n       = n
                     self.__nProf = n
                     self.__buffer = numpy.zeros((dataOut.nChannels,
                                                        n,
                                                        dataOut.nHeights),
                                                       dtype='complex')
                 def putData(self,data):
                     '''
                     Add a profile to he __buffer and increase in one the __profiel Index
                     '''
                     self.__buffer[:,self.__profIndex,:]= data
                     self.__profIndex      += 1
                     return
                 def pushData(self,dataOut):
                     '''
                     Return the PULSEPAIR and the profiles used in the operation
                     Affected :  self.__profileIndex
                     '''
                     #----------------- Remove DC-----------------------------------
                     if self.removeDC==True:
                         mean    = numpy.mean(self.__buffer,1)
                         tmp     = mean.reshape(self.__nch,1,self.__nHeis)
                         dc= numpy.tile(tmp,[1,self.__nProf,1])
                         self.__buffer = self.__buffer -  dc
                     #------------------Calculo de Potencia ------------------------
                     pair0       = self.__buffer*numpy.conj(self.__buffer)
                     pair0       = pair0.real
                     lag_0       = numpy.sum(pair0,1)
                     #------------------Calculo de Ruido x canal--------------------
                     self.noise  = numpy.zeros(self.__nch)
                     for i in range(self.__nch):
                         daux         = numpy.sort(pair0[i,:,:],axis= None)
                         self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt)
                     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)
                     noise_buffer     = numpy.tile(noise_buffer,[1,self.__nProf,1])
                     #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N--
                     #------------------   P= S+N  ,P=lag_0/N ---------------------------------
                     #-------------------- Power --------------------------------------------------
                     data_power       = lag_0/(self.n*self.nCohInt)
                     #------------------  Senal  ---------------------------------------------------
                     data_intensity   = pair0 - noise_buffer
                     data_intensity   = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt)
                     #data_intensity   = (lag_0-self.noise*self.n)*(self.n*self.nCohInt)
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_intensity[i][j]  < 0:
                                 data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j]))
                     #----------------- Calculo de Frecuencia y Velocidad doppler--------
                     pair1            = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:])
                     lag_1            = numpy.sum(pair1,1)
                     data_freq        = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1)
                     data_velocity    = (self.lambda_/2.0)*data_freq
                     #---------------- Potencia promedio estimada de la Senal-----------
                     lag_0            = lag_0/self.n
                     S                = lag_0-self.noise
                     #---------------- Frecuencia Doppler promedio ---------------------
                     lag_1            = lag_1/(self.n-1)
                     R1               = numpy.abs(lag_1)
                     #---------------- Calculo del SNR----------------------------------
                     data_snrPP       = S/self.noise
                     for i in range(self.__nch):
                         for j in range(self.__nHeis):
                             if data_snrPP[i][j]  < 1.e-20:
                                 data_snrPP[i][j] = 1.e-20
                     #----------------- Calculo del ancho espectral ----------------------
                     L                = S/R1
                     L                = numpy.where(L<0,1,L)
                     L                = numpy.log(L)
                     tmp              = numpy.sqrt(numpy.absolute(L))
                     data_specwidth   = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L)
                     n                = self.__profIndex
                     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,n
                 def pulsePairbyProfiles(self,dataOut):
                     self.__dataReady     =  False
                     data_power           =  None
                     data_intensity       =  None
                     data_velocity        =  None
                     data_specwidth       =  None
                     data_snrPP           =  None
                     self.putData(data=dataOut.data)
                     if self.__profIndex  == self.n:
                         data_power,data_intensity, data_velocity,data_snrPP,data_specwidth, n   = self.pushData(dataOut=dataOut)
                         self.__dataReady                   = True
                     return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth
                 def pulsePairOp(self, dataOut, datatime= None):
                     if self.__initime == None:
                         self.__initime = datatime
                     data_power, data_intensity, data_velocity, data_snrPP, data_specwidth = self.pulsePairbyProfiles(dataOut)
                     self.__lastdatatime           = datatime
                     if data_power is None:
                         return 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, avgdatatime
                 def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs):
                     if not self.isConfig:
                         self.setup(dataOut = dataOut, n    = n , removeDC=removeDC , **kwargs)
                         self.isConfig   = True
                     data_power, data_intensity, data_velocity,data_snrPP,data_specwidth, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime)
                     dataOut.flagNoData                         = True
                     if self.__dataReady:
                         dataOut.nCohInt        *= self.n
                         dataOut.dataPP_POW      = data_intensity # S
+                        print("help",data_power)
                         dataOut.dataPP_POWER    = data_power     # P
                         dataOut.dataPP_DOP      = data_velocity
                         dataOut.dataPP_SNR      = data_snrPP
                         dataOut.dataPP_WIDTH    = data_specwidth
                         dataOut.PRFbyAngle      = self.n         #numero de PRF*cada angulo rotado que equivale a un tiempo.
                         dataOut.nProfiles       = int(dataOut.nProfiles/n)
                         dataOut.utctime         = avgdatatime
                         dataOut.flagNoData      = False
                     return dataOut
             # import collections
             # from scipy.stats import mode
             #
             # class Synchronize(Operation):
             #
             #     isConfig = False
             #     __profIndex = 0
             #
             #     def __init__(self, **kwargs):
             #
             #         Operation.__init__(self, **kwargs)
             # #         self.isConfig = False
             #         self.__powBuffer = None
             #         self.__startIndex = 0
             #         self.__pulseFound = False
             #
             #     def __findTxPulse(self, dataOut, channel=0, pulse_with = None):
             #
             #         #Read data
             #
             #         powerdB = dataOut.getPower(channel = channel)
             #         noisedB = dataOut.getNoise(channel = channel)[0]
             #
             #         self.__powBuffer.extend(powerdB.flatten())
             #
             #         dataArray = numpy.array(self.__powBuffer)
             #
             #         filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same")
             #
             #         maxValue = numpy.nanmax(filteredPower)
             #
             #         if maxValue < noisedB + 10:
             #             #No se encuentra ningun pulso de transmision
             #             return None
             #
             #         maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0]
             #
             #         if len(maxValuesIndex) < 2:
             #             #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX
             #             return None
             #
             #         phasedMaxValuesIndex = maxValuesIndex - self.__nSamples
             #
             #         #Seleccionar solo valores con un espaciamiento de nSamples
             #         pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex)
             #
             #         if len(pulseIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         spacing = pulseIndex[1:] - pulseIndex[:-1]
             #
             #         #remover senales que se distancien menos de 10 unidades o muestras
             #         #(No deberian existir IPP menor a 10 unidades)
             #
             #         realIndex = numpy.where(spacing > 10 )[0]
             #
             #         if len(realIndex) < 2:
             #             #Solo se encontro un pulso de transmision con ancho mayor a 1
             #             return None
             #
             #         #Eliminar pulsos anchos (deja solo la diferencia entre IPPs)
             #         realPulseIndex = pulseIndex[realIndex]
             #
             #         period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0]
             #
             #         print "IPP = %d samples" %period
             #
             #         self.__newNSamples = dataOut.nHeights #int(period)
             #         self.__startIndex = int(realPulseIndex[0])
             #
             #         return 1
             #
             #
             #     def setup(self, nSamples, nChannels, buffer_size = 4):
             #
             #         self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float),
             #                                           maxlen = buffer_size*nSamples)
             #
             #         bufferList = []
             #
             #         for i in range(nChannels):
             #             bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) +  numpy.NAN,
             #                                           maxlen = buffer_size*nSamples)
             #
             #             bufferList.append(bufferByChannel)
             #
             #         self.__nSamples = nSamples
             #         self.__nChannels = nChannels
             #         self.__bufferList = bufferList
             #
             #     def run(self, dataOut, channel = 0):
             #
             #         if not self.isConfig:
             #             nSamples = dataOut.nHeights
             #             nChannels = dataOut.nChannels
             #             self.setup(nSamples, nChannels)
             #             self.isConfig = True
             #
             #         #Append new data to internal buffer
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             bufferByChannel.extend(dataOut.data[thisChannel])
             #
             #         if self.__pulseFound:
             #             self.__startIndex -= self.__nSamples
             #
             #         #Finding Tx Pulse
             #         if not self.__pulseFound:
             #             indexFound = self.__findTxPulse(dataOut, channel)
             #
             #             if indexFound == None:
             #                 dataOut.flagNoData = True
             #                 return
             #
             #             self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex)
             #             self.__pulseFound = True
             #             self.__startIndex = indexFound
             #
             #         #If pulse was found ...
             #         for thisChannel in range(self.__nChannels):
             #             bufferByChannel = self.__bufferList[thisChannel]
             #             #print self.__startIndex
             #             x = numpy.array(bufferByChannel)
             #             self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples]
             #
             #         deltaHeight = dataOut.heightList[1] - dataOut.heightList[0]
             #         dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight
             # #             dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6
             #
             #         dataOut.data = self.__arrayBuffer
             #
             #         self.__startIndex += self.__newNSamples
             #
             #         return

schainpy/scripts/USRP_ADQ_SPECM.py +5 -3

             #!python
             '''
             '''
             import os, sys
             import datetime
             import time
             #path = os.path.dirname(os.getcwd())
             #path = os.path.dirname(path)
             #sys.path.insert(0, path)
             from schainpy.controller import Project
             desc = "USRP_test"
             filename = "USRP_processing.xml"
             controllerObj = Project()
             controllerObj.setup(id = '191', name='Test_USRP', description=desc)
             ############## USED TO PLOT IQ VOLTAGE, POWER AND SPECTRA #############
             #######################################################################
             ######PATH DE LECTURA, ESCRITURA, GRAFICOS Y ENVIO WEB#################
             #######################################################################
             #path = '/media/data/data/vientos/57.2063km/echoes/NCO_Woodman'
             #path = '/DATA_RM/TEST_INTEGRACION'
             #path = '/DATA_RM/TEST_ONLINE'
             #path_pp = '/DATA_RM/TEST_HDF5'
             #figpath = '/home/soporte/Pictures/TEST_INTEGRACION_IMG'
             ###path = '/DATA_RM/TEST_INTEGRACION/ADQ_OFFLINE/'
             ###path_pp = '/DATA_RM/TEST_HDF5_SPEC'
             #path = '/DATA_RM/USRP_22'
-            path = '/DATA_RM/23/6v'
+            ###path = '/DATA_RM/23/6v'
+            path = '/DATA_RM/TEST_19OCTUBRE/10MHZ'
             #path_pp = '/DATA_RM/TEST_HDF5'
+            path_pp = '/DATA_RM/TEST_HDF5_19OCT'
             # UTIMO TEST 22 DE SEPTIEMBRE
             #path_pp = '/DATA_RM/TEST_HDF5_SPEC_22'
             #path_pp = '/DATA_RM/TEST_HDF5_SPEC_3v'
-            path_pp = '/DATA_RM/TEST_HDF5_SPEC_23/6v'
+            ###path_pp = '/DATA_RM/TEST_HDF5_SPEC_23/6v'
             #remotefolder = "/home/wmaster/graficos"
             #######################################################################
             ################# RANGO DE PLOTEO######################################
             #######################################################################
             dBmin = '-5'
             dBmax = '20'
             xmin = '0'
             xmax ='24'
             ymin = '0'
             ymax = '600'
             #######################################################################
             ########################FECHA##########################################
             #######################################################################
             str = datetime.date.today()
             today = str.strftime("%Y/%m/%d")
             str2 = str - datetime.timedelta(days=1)
             yesterday = str2.strftime("%Y/%m/%d")
             #######################################################################
             ######################## UNIDAD DE LECTURA#############################
             #######################################################################
             readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
                                                         path=path,
                                                         startDate="2021/01/01",#today,
                                                         endDate="2021/12/30",#today,
                                                         startTime='00:00:00',
                                                         endTime='23:59:59',
                                                         delay=0,
                                                         #set=0,
                                                         online=0,
                                                         walk=1,
                                                         ippKm = 60)
             opObj11 = readUnitConfObj.addOperation(name='printInfo')
             #opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
             #######################################################################
             ################ OPERACIONES DOMINIO DEL TIEMPO########################
             #######################################################################
-            V=6
+            V=10
             IPP=400*1e-6
             n= int(1/(V*IPP))
             print("n numero de Perfiles a procesar con nFFTPoints ", n)
             procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
             procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId())
             procUnitConfObjB.addParameter(name='nFFTPoints', value=n, format='int')
             procUnitConfObjB.addParameter(name='nProfiles' , value=n, format='int')
             #
             # codigo64='1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0,1,1,1,0,0,0,1,0,'+\
             #              '1,1,1,0,1,1,0,1,1,1,1,0,0,0,1,0,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,1,0,0,0,0,1,1,1,0,1,1,1,1,0,1,1,0,1,0,0,0,1,1,1,0,1'
             #opObj11 = procUnitConfObjA.addOperation(name='setRadarFrequency')
             #opObj11.addParameter(name='frequency', value='70312500')
             #opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other')
             #opObj11.addParameter(name='n', value='625', format='int')#10
             #opObj11.addParameter(name='removeDC', value=1, format='int')
             # Ploteo TEST
             '''
             opObj11 = procUnitConfObjA.addOperation(name='PulsepairPowerPlot', optype='other')
             opObj11 = procUnitConfObjA.addOperation(name='PulsepairSignalPlot', optype='other')
             opObj11 = procUnitConfObjA.addOperation(name='PulsepairVelocityPlot', optype='other')
             #opObj11.addParameter(name='xmax', value=8)
             opObj11 = procUnitConfObjA.addOperation(name='PulsepairSpecwidthPlot', optype='other')
             '''
             # OJO SCOPE
             #opObj10 = procUnitConfObjA.addOperation(name='ScopePlot', optype='external')
             #opObj10.addParameter(name='buffer_sizeid', value='10', format='int')
             ##opObj10.addParameter(name='xmin', value='0', format='int')
             ##opObj10.addParameter(name='xmax', value='50', format='int')
             #opObj10.addParameter(name='type', value='iq')
             ##opObj10.addParameter(name='ymin', value='-5000', format='int')
             ##opObj10.addParameter(name='ymax', value='8500', format='int')
             #opObj11.addParameter(name='save', value=figpath, format='str')
             #opObj11.addParameter(name='save_period', value=10, format='int')
             #opObj10 = procUnitConfObjA.addOperation(name='setH0')
             #opObj10.addParameter(name='h0', value='-5000', format='float')
             #opObj11 =  procUnitConfObjA.addOperation(name='filterByHeights')
             #opObj11.addParameter(name='window', value='1', format='int')
             #codigo='1,1,-1,1,1,-1,1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,-1,-1,-1,1,1,1,1,-1,-1,-1'
             #opObj11 = procUnitConfObjSousy.addOperation(name='Decoder', optype='other')
             #opObj11.addParameter(name='code', value=codigo, formatyesterday='floatlist')
             #opObj11.addParameter(name='nCode', value='1', format='int')
             #opObj11.addParameter(name='nBaud', value='28', format='int')
             #opObj11 = procUnitConfObjA.addOperation(name='CohInt', optype='other')
             #opObj11.addParameter(name='n', value='100', format='int')
             #######################################################################
             ########## OPERACIONES ParametersProc########################
             #######################################################################
             procUnitConfObjC= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjB.getId())
             procUnitConfObjC.addOperation(name='SpectralMoments')
             opObj10 = procUnitConfObjC.addOperation(name='HDFWriter')
             opObj10.addParameter(name='path',value=path_pp)
             #opObj10.addParameter(name='mode',value=0)
             opObj10.addParameter(name='blocksPerFile',value='100',format='int')
             #opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
             opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
             opObj10.addParameter(name='dataList',value='data_pow,data_dop,utctime',format='list')#,format='list'
             controllerObj.start()

schainpy/scripts/basic_proc00001.py +17 -14

             # Ing. AVP
             # 06/10/2021
             # ARCHIVO DE LECTURA
             import os, sys
             import datetime
             import time
             from schainpy.controller import Project
             #### NOTA###########################################
             # INPUT :
             # VELOCIDAD PARAMETRO :        V = 2°/seg
             # MODO PULSE PAIR O MOMENTOS:  0 : Pulse Pair ,1 : Momentos
             ######################################################
             ##### PROCESAMIENTO ##################################
             #####  OJO TENER EN CUENTA EL n= para el Pulse Pair ##
             #####                   O EL n= nFFTPoints         ###
             ######################################################
             ######## BUSCAMOS EL numero de IPP equivalente 1°#####
             ######## Sea V la velocidad del Pedestal en °/seg#####
             ######## 1° sera Recorrido en un tiempo de  1/V ######
             ######## IPP del Radar 400 useg --> 60 Km ############
             ######## n   = 1/(V(°/seg)*IPP(Km)) , NUMERO DE IPP ##
             ######## n   = 1/(V*IPP) #############################
             ######## VELOCIDAD DEL PEDESTAL ######################
             print("SETUP- RADAR METEOROLOGICO")
             V       = 10
             mode    = 1
             #path    = '/DATA_RM/23/6v'
-            path    = '/DATA_RM/TEST_INTEGRACION_2M'
+            ####path    = '/DATA_RM/TEST_INTEGRACION_2M'
-            path_ped='/DATA_RM/TEST_PEDESTAL/P20211012-082745'
+            #path    = '/DATA_RM/TEST_19OCTUBRE/10MHZ'
+            path    = '/DATA_RM/WR_20_OCT'
+            #### path_ped='/DATA_RM/TEST_PEDESTAL/P20211012-082745'
+            #### path_ped='/DATA_RM/TEST_PEDESTAL/P20211019-192244'
             figpath_pp  = "/home/soporte/Pictures/TEST_PP"
-            figpath_mom = "/home/soporte/Pictures/TEST_MOM"
+            figpath_spec = "/home/soporte/Pictures/TEST_MOM"
-            plot        = 0
+            plot        = 1
-            integration = 1
+            integration = 0
             save        = 0
             if save == 1:
                 if mode==0:
                     path_save = '/DATA_RM/TEST_HDF5_PP_23/6v'
                     path_save = '/DATA_RM/TEST_HDF5_PP'
                     path_save = '/DATA_RM/TEST_HDF5_PP_100'
                 else:
                     path_save = '/DATA_RM/TEST_HDF5_SPEC_23_V2/6v'
             print("* PATH data ADQ        :", path)
             print("* Velocidad Pedestal   :",V,"°/seg")
             ############################ NRO Perfiles PROCESAMIENTO ###################
             V=V
             IPP=400*1e-6
             n= int(1/(V*IPP))
             print("* n - NRO Perfiles Proc:", n )
             ################################## MODE ###################################
             print("* Modo de Operacion    :",mode)
             if mode ==0:
                 print("* Met. Seleccionado    : Pulse Pair")
             else:
                 print("* Met. Momentos        : Momentos")
             ################################## MODE ###################################
             print("* Grabado de datos     :",save)
             if save ==1:
                 if mode==0:
                     ope= "Pulse Pair"
                 else:
                     ope= "Momentos"
                 print("* Path-Save Data -", ope , path_save)
             print("* Integracion de datos :",integration)
             time.sleep(15)
             #remotefolder = "/home/wmaster/graficos"
             #######################################################################
             ################# RANGO DE PLOTEO######################################
             dBmin = '1'
-            dBmax = '85'
+            dBmax = '65'
-            xmin = '15'
+            xmin = '13.2'
-            xmax = '15.25'
+            xmax = '13.5'
             ymin = '0'
-            ymax = '600'
+            ymax = '60'
             #######################################################################
             ########################FECHA##########################################
             str = datetime.date.today()
             today = str.strftime("%Y/%m/%d")
             str2 = str - datetime.timedelta(days=1)
             yesterday = str2.strftime("%Y/%m/%d")
             #######################################################################
             ########################SIGNAL CHAIN ##################################
             #######################################################################
             desc = "USRP_test"
             filename = "USRP_processing.xml"
             controllerObj = Project()
             controllerObj.setup(id = '191', name='Test_USRP', description=desc)
             #######################################################################
             ######################## UNIDAD DE LECTURA#############################
             #######################################################################
             readUnitConfObj = controllerObj.addReadUnit(datatype='DigitalRFReader',
                                                         path=path,
                                                         startDate="2021/01/01",#today,
                                                         endDate="2021/12/30",#today,
                                                         startTime='00:00:00',
                                                         endTime='23:59:59',
                                                         delay=0,
                                                         #set=0,
                                                         online=0,
                                                         walk=1,
                                                         ippKm = 60)
             opObj11 = readUnitConfObj.addOperation(name='printInfo')
             procUnitConfObjA = controllerObj.addProcUnit(datatype='VoltageProc', inputId=readUnitConfObj.getId())
             if mode ==0:
                 ####################### METODO PULSE PAIR ######################################################################
                 opObj11 = procUnitConfObjA.addOperation(name='PulsePair', optype='other')
                 opObj11.addParameter(name='n', value=int(n), format='int')#10 VOY A USAR 250 DADO  QUE LA VELOCIDAD ES 10 GRADOS
                 #opObj11.addParameter(name='removeDC', value=1, format='int')
                 ####################### METODO Parametros ######################################################################
                 procUnitConfObjB= controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjA.getId())
                 if plot==1:
                     opObj11 = procUnitConfObjB.addOperation(name='GenericRTIPlot',optype='external')
-                    opObj11.addParameter(name='attr_data', value='dataPP_POW')
+                    opObj11.addParameter(name='attr_data', value='dataPP_POWER')
                     opObj11.addParameter(name='colormap', value='jet')
                     opObj11.addParameter(name='xmin', value=xmin)
                     opObj11.addParameter(name='xmax', value=xmax)
                     opObj11.addParameter(name='zmin', value=dBmin)
                     opObj11.addParameter(name='zmax', value=dBmax)
                     opObj11.addParameter(name='save', value=figpath_pp)
                     opObj11.addParameter(name='showprofile', value=0)
-                    opObj11.addParameter(name='save_period', value=50)
+                    opObj11.addParameter(name='save_period', value=10)
                 ####################### METODO ESCRITURA #######################################################################
                 if save==1:
                     opObj10 = procUnitConfObjB.addOperation(name='HDFWriter')
                     opObj10.addParameter(name='path',value=path_save)
                     #opObj10.addParameter(name='mode',value=0)
                     opObj10.addParameter(name='blocksPerFile',value='100',format='int')
                     opObj10.addParameter(name='metadataList',value='utctimeInit,timeZone,paramInterval,profileIndex,channelList,heightList,flagDataAsBlock',format='list')
-                    opObj10.addParameter(name='dataList',value='dataPP_POW,dataPP_DOP,utctime',format='list')#,format='list'
+                    opObj10.addParameter(name='dataList',value='dataPP_POWER,dataPP_DOP,utctime',format='list')#,format='list'
                 if integration==1:
                     V=10
                     blocksPerfile=360
                     print("* Velocidad del Pedestal:",V)
                     tmp_blocksPerfile = 100
                     f_a_p= int(tmp_blocksPerfile/V)
                     opObj11 = procUnitConfObjB.addOperation(name='PedestalInformation')
                     opObj11.addParameter(name='path_ped', value=path_ped)
                     #opObj11.addParameter(name='path_adq', value=path_adq)
                     opObj11.addParameter(name='t_Interval_p', value='0.01', format='float')
                     opObj11.addParameter(name='blocksPerfile', value=blocksPerfile, format='int')
                     opObj11.addParameter(name='n_Muestras_p', value='100', format='float')
                     opObj11.addParameter(name='f_a_p', value=f_a_p, format='int')
                     opObj11.addParameter(name='online', value='0', format='int')
                     opObj11 = procUnitConfObjB.addOperation(name='Block360')
                     opObj11.addParameter(name='n', value='10', format='int')
                     opObj11.addParameter(name='mode', value=mode, format='int')
                     # este bloque funciona bien con divisores de 360 no olvidar 0 10 20 30 40 60 90 120 180
                     opObj11= procUnitConfObjB.addOperation(name='WeatherPlot',optype='other')
             else:
                 ####################### METODO SPECTROS ######################################################################
                 procUnitConfObjB = controllerObj.addProcUnit(datatype='SpectraProc', inputId=procUnitConfObjA.getId())
                 procUnitConfObjB.addParameter(name='nFFTPoints', value=n, format='int')
                 procUnitConfObjB.addParameter(name='nProfiles' , value=n, format='int')
                 procUnitConfObjC = controllerObj.addProcUnit(datatype='ParametersProc',inputId=procUnitConfObjB.getId())
                 procUnitConfObjC.addOperation(name='SpectralMoments')
                 if plot==1:
                     dBmin = '1'
                     dBmax = '65'
                     opObj11 = procUnitConfObjC.addOperation(name='PowerPlot',optype='external')
                     opObj11.addParameter(name='xmin', value=xmin)
                     opObj11.addParameter(name='xmax', value=xmax)
                     opObj11.addParameter(name='zmin', value=dBmin)
                     opObj11.addParameter(name='zmax', value=dBmax)
-                    opObj11.addParameter(name='save', value=figpath_mom)
+                    opObj11.addParameter(name='save', value=figpath_spec)
                     opObj11.addParameter(name='showprofile', value=0)
-                    opObj11.addParameter(name='save_period', value=100)
+                    opObj11.addParameter(name='save_period', value=10)
                 if save==1:
                     opObj10 = procUnitConfObjC.addOperation(name='HDFWriter')
                     opObj10.addParameter(name='path',value=path_save)
                     #opObj10.addParameter(name='mode',value=0)
                     opObj10.addParameter(name='blocksPerFile',value='360',format='int')
                     #opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
                     opObj10.addParameter(name='metadataList',value='utctimeInit,heightList,nIncohInt,nCohInt,nProfiles,channelList',format='list')#profileIndex
                     opObj10.addParameter(name='dataList',value='data_pow,data_dop,utctime',format='list')#,format='list'
                 if integration==1:
                    V=10
                    blocksPerfile=360
                    print("* Velocidad del Pedestal:",V)
                    tmp_blocksPerfile = 100
                    f_a_p= int(tmp_blocksPerfile/V)
                    opObj11 = procUnitConfObjC.addOperation(name='PedestalInformation')
                    opObj11.addParameter(name='path_ped', value=path_ped)
                    #opObj11.addParameter(name='path_adq', value=path_adq)
                    opObj11.addParameter(name='t_Interval_p', value='0.01', format='float')
                    opObj11.addParameter(name='blocksPerfile', value=blocksPerfile, format='int')
                    opObj11.addParameter(name='n_Muestras_p', value='100', format='float')
                    opObj11.addParameter(name='f_a_p', value=f_a_p, format='int')
                    opObj11.addParameter(name='online', value='0', format='int')
                    opObj11 = procUnitConfObjC.addOperation(name='Block360')
                    opObj11.addParameter(name='n', value='10', format='int')
                    opObj11.addParameter(name='mode', value=mode, format='int')
                    # este bloque funciona bien con divisores de 360 no olvidar 0 10 20 30 40 60 90 120 180
                    opObj11= procUnitConfObjC.addOperation(name='WeatherPlot',optype='other')
             controllerObj.start()

schainpy/scripts/check_pedestal.py +8 -1

             # Ing-AlexanderValdez
             # Monitoreo de Pedestal
             ############## IMPORTA LIBRERIAS ###################
             import os,numpy,h5py
             import sys,time
             import matplotlib.pyplot as plt
             ####################################################
-            path_ped = '/DATA_RM/TEST_PEDESTAL/P20211012-082745'
+            #################################################################
+            # LA FECHA 21-10-20 CORRESPONDE A LAS PRUEBAS DEL DIA MIERCOLES
+            # 1:15:51 pm hasta 3:49:32 pm
+            #################################################################
+            #path_ped = '/DATA_RM/TEST_PEDESTAL/P20211012-082745'
+            path_ped = '/DATA_RM/TEST_PEDESTAL/P20211020-131248'
             # Metodo para verificar numero
             def isNumber(str):
                 try:
                     float(str)
                     return True
                 except:
                     return False
             # Metodo para extraer el arreglo
             def getDatavaluefromDirFilename(path,file,value):
                 dir_file= path+"/"+file
                 fp      = h5py.File(dir_file,'r')
                 array    = fp['Data'].get(value)[()]
                 fp.close()
                 return array
             # LISTA COMPLETA DE ARCHIVOS HDF5 Pedestal
             LIST= sorted(os.listdir(path_ped))
             m=len(LIST)
             print("TOTAL DE ARCHIVOS DE PEDESTAL:",m)
             # Contadores temporales
             k=  0
             l=  0
             t=  0
             # Marca de tiempo temporal
             time_        = numpy.zeros([m])
             # creacion de
             for i in range(m):
+                print("order:",i)
                 tmp_azi_pos = getDatavaluefromDirFilename(path=path_ped,file=LIST[i],value="azi_pos")
                 tmp_ele_pos = getDatavaluefromDirFilename(path=path_ped,file=LIST[i],value="ele_pos")
                 tmp_azi_vel = getDatavaluefromDirFilename(path=path_ped,file=LIST[i],value="azi_vel")
                 tmp_ele_vel = getDatavaluefromDirFilename(path=path_ped,file=LIST[i],value="azi_vel")# nuevo :D
                 time_[i]    = getDatavaluefromDirFilename(path=path_ped,file=LIST[i],value="utc")
                 k=k +tmp_azi_pos.shape[0]
                 l=l +tmp_ele_pos.shape[0]
                 t=t +tmp_azi_vel.shape[0]
             print("TOTAL DE MUESTRAS, ARCHIVOS X100:",k)
             time.sleep(5)
             ######CREACION DE ARREGLOS CANTIDAD DE VALORES POR MUESTRA#################
             azi_pos     = numpy.zeros([k])
             ele_pos     = numpy.zeros([l])
             time_azi_pos= numpy.zeros([k])
             # Contadores temporales
             p=0
             r=0
             z=0
             # VARIABLES TMP para almacenar azimuth, elevacion y tiempo
             #for filename in sorted(os.listdir(path_ped)):
             # CONDICION POR LEER EN TIEMPO REAL NO OFFLINE
             for filename in LIST:
                 tmp_azi_pos   = getDatavaluefromDirFilename(path=path_ped,file=filename,value="azi_pos")
                 tmp_ele_pos   = getDatavaluefromDirFilename(path=path_ped,file=filename,value="ele_pos")
                 # CONDICION POR LEER EN TIEMPO REAL NO OFFLINE
                 if z==(m-1):
                     tmp_azi_time=numpy.arange(time_[z],time_[z]+1,1/(tmp_azi_pos.shape[0]))
                 else:
                     tmp_azi_time=numpy.arange(time_[z],time_[z+1],(time_[z+1]-time_[z])/(tmp_azi_pos.shape[0]))
                 print(filename,time_[z])
                 print(z,tmp_azi_pos.shape[0])
                 i=0
                 for i in range(tmp_azi_pos.shape[0]):
                     index=p+i
                     azi_pos[index]=tmp_azi_pos[i]
                     time_azi_pos[index]=tmp_azi_time[i]
                 p=p+tmp_azi_pos.shape[0]
                 i=0
                 for i in range(tmp_ele_pos.shape[0]):
                     index=r+i
                     ele_pos[index]=tmp_ele_pos[i]
                 r=r+tmp_ele_pos.shape[0]
                 z+=1
             ######## GRAFIQUEMOS Y VEAMOS LOS DATOS DEL Pedestal
             fig, ax = plt.subplots(figsize=(16,8))
             print(time_azi_pos.shape)
             print(azi_pos.shape)
             t=numpy.arange(time_azi_pos.shape[0])*0.01/(60.0)
             plt.plot(t,azi_pos,label='AZIMUTH_POS',color='blue')
             # AQUI ESTOY ADICIONANDO LA POSICION EN elevaciont=numpy.arange(len(ele_pos))*0.01/60.0
             t=numpy.arange(len(ele_pos))*0.01/60.0
             plt.plot(t,ele_pos,label='ELEVATION_POS',color='red')#*10
             #ax.set_xlim(0, 9)
             ax.set_ylim(-5, 400)
             plt.ylabel("Azimuth Position")
             plt.xlabel("Muestra")
             plt.title('Azimuth Position vs Muestra ', fontsize=20)
             axes = plt.gca()
             axes.yaxis.grid()
             plt.xticks(fontsize=16)
             plt.yticks(fontsize=16)
             plt.show()

schainpy/scripts/test_sim00011b.py +2 -1

             import os,sys,json
             import datetime
             import time
             from schainpy.controller import Project
             '''
             NOTA:
             Este script de prueba.
             - Unidad del lectura 'HDFReader'.
             - Unidad de procesamiento ParametersProc
             - Operacion SpectralMomentsPlot
             '''
             #######################################################################
             ################# RANGO DE PLOTEO######################################
             #######################################################################
             dBmin = '1'
             dBmax = '65'
             xmin = '0'
             xmax ='24'
             #tmmin = 16.2
             #tmmax = 16.25
             tmmin =15
             tmmax =15.5
             ymin = '0'
             ymax = '600'
             #######################################################################
             #######################################################################
             #######################################################################
             #path       = '/DATA_RM/TEST_HDF5_SPEC'
-            path       = '/DATA_RM/TEST_HDF5_SPEC_23/6v/'
+            #path       = '/DATA_RM/TEST_HDF5_SPEC_23/6v/'
+            path       = '/DATA_RM/TEST_HDF5_19OCT'
             figpath    = '/home/soporte/Downloads/23/6v'
             desc       = "Simulator Test"
             desc_data  =  {
                             'Data': {
                                 'data_pow': ['Data/data_pow/channel00','Data/data_pow/channel01'],
                                 'data_dop': ['Data/data_dop/channel00','Data/data_dop/channel01'],
                                 'utctime':'Data/utctime'
                             },
                             'Metadata': {
                                 'heightList':'Metadata/heightList',
                                 'nIncohInt' :'Metadata/nIncohInt',
                                 'nCohInt' :'Metadata/nCohInt',
                                 'nProfiles' :'Metadata/nProfiles',
                                 'channelList' :'Metadata/channelList',
                                 'utctimeInit' :'Metadata/utctimeInit'
                              }
                            }
             controllerObj   = Project()
             controllerObj.setup(id='10',name='Test Simulator',description=desc)
             readUnitConfObj = controllerObj.addReadUnit(datatype='HDFReader',
                                                         path=path,
                                                         startDate="2021/01/01",   #"2020/01/01",#today,
                                                         endDate= "2021/12/01",  #"2020/12/30",#today,
                                                         startTime='00:00:00',
                                                         endTime='23:59:59',
                                                         delay=0,
                                                         #set=0,
                                                         online=0,
                                                         walk=1,
                                                         description= json.dumps(desc_data))#1
             procUnitConfObjA = controllerObj.addProcUnit(datatype='ParametersProc',inputId=readUnitConfObj.getId())
             opObj11 = procUnitConfObjA.addOperation(name='PowerPlot',optype='external')
             opObj11.addParameter(name='xmin', value=tmmin)
             opObj11.addParameter(name='xmax', value=tmmax)
             opObj11.addParameter(name='zmin', value=dBmin)
             opObj11.addParameter(name='zmax', value=dBmax)
             opObj11.addParameter(name='save', value=figpath)
             opObj11.addParameter(name='showprofile', value=0)
             opObj11.addParameter(name='save_period', value=10)
             controllerObj.start()

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