schain-jc Commit - r1035:b65644e03ac2

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José Chávez -

r1035:b65644e03ac2

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r1035:b65644e03ac2

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schainpy/scripts/julia_mp.py created 644 +94 0

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	1	import argparse
	2
	3	from schainpy.controller import Project, multiSchain
	4
	5	desc = "HF_EXAMPLE"
	6
	7	def fiber(cursor, skip, q, dt):
	8
	9	controllerObj = Project()
	10
	11	controllerObj.setup(id='191', name='test01', description=desc)
	12
	13	readUnitConfObj = controllerObj.addReadUnit(datatype='SpectraReader',
	14	path='/home/nanosat/data/julia',
	15	startDate=dt,
	16	endDate=dt,
	17	startTime="00:00:00",
	18	endTime="23:59:59",
	19	online=0,
	20	#set=1426485881,
	21	delay=10,
	22	walk=1,
	23	queue=q,
	24	cursor=cursor,
	25	skip=skip,
	26	#timezone=-5*3600
	27	)
	28
	29	# #opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
	30	#
	31	procUnitConfObj2 = controllerObj.addProcUnit(datatype='Spectra', inputId=readUnitConfObj.getId())
	32	# procUnitConfObj2.addParameter(name='nipp', value='5', format='int')
	33
	34	# procUnitConfObj3 = controllerObj.addProcUnit(datatype='ParametersProc', inputId=readUnitConfObj.getId())
	35	# opObj11 = procUnitConfObj3.addOperation(name='SpectralMoments', optype='other')
	36
	37	#
	38	opObj11 = procUnitConfObj2.addOperation(name='RTIPlot', optype='other')
	39	opObj11.addParameter(name='id', value='1000', format='int')
	40	opObj11.addParameter(name='wintitle', value='HF_Jicamarca_Spc', format='str')
	41	opObj11.addParameter(name='xmin', value='0', format='int')
	42	opObj11.addParameter(name='xmax', value='24', format='int')
	43
	44	# opObj11 = procUnitConfObj3.addOperation(name='Parameters1Plot', optype='other')
	45	# opObj11.addParameter(name='channelList', value='0', format='intList')
	46	#
	47	# opObj11.addParameter(name='id', value='2000', format='int')
	48	# # opObj11.addParameter(name='colormap', value='0', format='bool')
	49	# opObj11.addParameter(name='onlySNR', value='1', format='bool')
	50	# opObj11.addParameter(name='DOP', value='0', format='bool')
	51	# opObj11.addParameter(name='showSNR', value='1', format='bool')
	52	# opObj11.addParameter(name='SNRthresh', value='0', format='int')
	53	# opObj11.addParameter(name='SNRmin', value='-10', format='int')
	54	# opObj11.addParameter(name='SNRmax', value='30', format='int')
	55
	56	# opObj11.addParameter(name='showSNR', value='1', format='int')
	57	# # opObj11.addParameter(name='channelList', value='0', format='intlist')
	58	# # opObj11.addParameter(name='xmin', value='0', format='float')
	59	# opObj11.addParameter(name='xmin', value='0', format='float')
	60	# opObj11.addParameter(name='xmax', value='24', format='float')
	61
	62	# opObj11.addParameter(name='zmin', value='-110', format='float')
	63	# opObj11.addParameter(name='zmax', value='-70', format='float')
	64	# opObj11.addParameter(name='save', value='0', format='int')
	65	# # opObj11.addParameter(name='figpath', value='/tmp/', format='str')
	66	#
	67	# opObj12 = procUnitConfObj2.addOperation(name='PublishData', optype='other')
	68	# opObj12.addParameter(name='zeromq', value=1, format='int')
	69	# opObj12.addParameter(name='server', value='tcp://10.10.10.82:7000', format='str')
	70
	71
	72	# opObj13 = procUnitConfObj3.addOperation(name='PublishData', optype='other')
	73	# opObj13.addParameter(name='zeromq', value=1, format='int')
	74	# opObj13.addParameter(name='server', value="juanca", format='str')
	75
	76	# opObj12.addParameter(name='delay', value=1, format='int')
	77
	78
	79	# print "Escribiendo el archivo XML"
	80	# controllerObj.writeXml(filename)
	81	# print "Leyendo el archivo XML"
	82	# controllerObj.readXml(filename)
	83
	84
	85	# timeit.timeit('controllerObj.run()', number=2)
	86
	87	controllerObj.start()
	88
	89
	90	if __name__ == '__main__':
	91	parser = argparse.ArgumentParser(description='Set number of parallel processes')
	92	parser.add_argument('--nProcess', default=1, type=int)
	93	args = parser.parse_args()
	94	multiSchain(fiber, nProcess=args.nProcess, startDate='2016/08/19', endDate='2016/08/19')

schainpy/utils/.desktop created 644 +6 0

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	1	[Desktop Entry]
	2	Encoding=UTF-8
	3	Name=Link to
	4	Type=Link
	5	URL=file:///home/nanosat/schain/schainpy/utils/parameters.txt
	6	Icon=text-plain

schainpy/utils/parameters.py created 644 +1177 0

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		1
		2	global_type_string = 'string'
		3	global_type_integer = 'int'
		4	global_type_floatList = 'floatList'
		5	global_type_pairsList = 'pairsList'
		6	global_type_boolean = 'bolean'
		7	global_type_float = 'float'
		8	global_type_colormap = 'colormap'
		9	global_type_list = 'list'
		10	global_type_integer_or_list = 'integer_or_list'
		11
		12	#BeaconPhase
		13	parameters = {
		14	'id': global_type_string,
		15	'wintitle': global_type_string,
		16	'pairsList': global_type_pairsList,
		17	'showprofile': global_type_boolean,
		18	'xmin': global_type_float,
		19	'xmax': global_type_float,
		20	'ymin': global_type_float,
		21	'ymax': global_type_float,
		22	'hmin': global_type_float,
		23	'hmax': global_type_float,
		24	'timerange': global_type_float,
		25	'save': global_type_boolean,
		26	'figpath': global_type_string,
		27	'figfile': global_type_string,
		28	'show': global_type_boolean,
		29	'ftp': global_type_boolean,
		30	'wr_period': global_type_integer,
		31	'server': global_type_string,
		32	'folder': global_type_string,
		33	'username': global_type_string,
		34	'password': global_type_string,
		35	'ftp_wei': global_type_integer,
		36	'exp_code': global_type_integer,
		37	'sub_exp_code': global_type_integer,
		38	'plot_pos': global_type_integer,
		39	}
		40
		41
		42	#BeamSelector
		43	parameters = {
		44	'beam': global_type_string,
		45	}
		46
		47
		48	#CohInt
		49	parameters = {
		50	'n': global_type_integer,
		51	'timeInterval': global_type_float,
		52	'overlapping': global_type_boolean,
		53	'byblock': global_type_boolean
		54	}
		55
		56
		57	#CoherenceMap
		58	parameters = {
		59	'id': global_type_string,
		60	'wintitle': global_type_string,
		61	'pairsList': global_type_pairsList,
		62	'showprofile': global_type_boolean,
		63	'xmin': global_type_float,
		64	'xmax': global_type_float,
		65	'ymin': global_type_float,
		66	'ymax': global_type_float,
		67	'zmin': global_type_float,
		68	'zmax': global_type_float,
		69	'timerange': global_type_float,
		70	'phase_min': global_type_float,
		71	'phase_max': global_type_float,
		72	'save': global_type_boolean,
		73	'figpath': global_type_string,
		74	'figfile': global_type_string,
		75	'ftp': global_type_boolean,
		76	'wr_period': global_type_integer,
		77	'coherence_cmap': global_type_colormap,
		78	'phase_cmap': global_type_colormap,
		79	'show': global_type_boolean,
		80	'server': global_type_string,
		81	'folder': global_type_string,
		82	'username': global_type_string,
		83	'password': global_type_string,
		84	'ftp_wei': global_type_integer,
		85	'exp_code': global_type_integer,
		86	'sub_exp_code': global_type_integer,
		87	'plot_pos': global_type_integer,
		88	}
		89
		90
		91	#CombineProfiles
		92	parameters = {
		93	'n': global_type_integer,
		94	}
		95
		96
		97	#CorrectSMPhases
		98	parameters = {
		99	'phaseOffsets': global_type_pairsList,
		100	'hmin': global_type_float,
		101	'hmax': global_type_float,
		102	'azimuth': global_type_float,
		103	'channelPositions': global_type_pairsList,
		104	}
		105
		106
		107	#CorrelationPlot
		108	parameters = {
		109	'id': global_type_string,
		110	'wintitle': global_type_string,
		111	'channelList': global_type_list,
		112	'showprofile': global_type_boolean,
		113	'xmin': global_type_float,
		114	'xmax': global_type_float,
		115	'ymin': global_type_float,
		116	'ymax': global_type_float,
		117	'zmin': global_type_float,
		118	'zmax': global_type_float,
		119	'save': global_type_boolean,
		120	'figpath': global_type_string,
		121	'figfile': global_type_string,
		122	'show': global_type_boolean,
		123	'ftp': global_type_boolean,
		124	'wr_period': global_type_integer,
		125	'server': global_type_string,
		126	'folder': global_type_string,
		127	'username': global_type_string,
		128	'password': global_type_string,
		129	'ftp_wei': global_type_integer,
		130	'exp_code': global_type_integer,
		131	'sub_exp_code': global_type_integer,
		132	'plot_pos': global_type_integer,
		133	'realtime': global_type_boolean,
		134	}
		135
		136
		137	#CrossSpectraPlot
		138	parameters = {
		139	'id': global_type_string,
		140	'wintitle': global_type_string,
		141	'pairsList': global_type_pairsList,
		142	'xmin': global_type_float,
		143	'xmax': global_type_float,
		144	'ymin': global_type_float,
		145	'ymax': global_type_float,
		146	'zmin': global_type_float,
		147	'zmax': global_type_float,
		148	'coh_min': global_type_float,
		149	'coh_max': global_type_float,
		150	'phase_min': global_type_float,
		151	'phase_max': global_type_float,
		152	'save': global_type_boolean,
		153	'figpath': global_type_string,
		154	'figfile': global_type_string,
		155	'ftp': global_type_boolean,
		156	'wr_period': global_type_integer,
		157	'power_cmap': global_type_colormap,
		158	'coherence_cmap': global_type_colormap,
		159	'phase_cmap': global_type_colormap,
		160	'show': global_type_boolean,
		161	'server': global_type_string,
		162	'folder': global_type_string,
		163	'username': global_type_string,
		164	'password': global_type_string,
		165	'ftp_wei': global_type_integer,
		166	'exp_code': global_type_integer,
		167	'sub_exp_code': global_type_integer,
		168	'plot_pos': global_type_integer,
		169	'xaxis': global_type_string,
		170	}
		171
		172
		173	#Decoder
		174	parameters = {
		175	'code': global_type_list,
		176	'nCode': global_type_integer,
		177	'nBaud': global_type_integer,
		178	'mode': global_type_integer,
		179	'osamp': global_type_float,
		180	}
		181
		182
		183	#EWDriftsEstimation
		184	parameters = {
		185	'zenith': global_type_list,
		186	'zenithCorrection': global_type_float,
		187	}
		188
		189
		190	#EWDriftsPlot
		191	parameters = {
		192	'id': global_type_string,
		193	'wintitle': global_type_string,
		194	'channelList': global_type_list,
		195	'xmin': global_type_float,
		196	'xmax': global_type_float,
		197	'ymin': global_type_float,
		198	'ymax': global_type_float,
		199	'zmin': global_type_float,
		200	'zmax': global_type_float,
		201	'zmaxVertfloat': global_type_float,
		202	'zminVertfloat': global_type_float,
		203	'zmaxZonafloat': global_type_float,
		204	'zminZonafloat': global_type_float,
		205	'timerange': global_type_float,
		206	'SNRthresh': global_type_float,
		207	'SNRmin': global_type_float,
		208	'SNRmax': global_type_float,
		209	'SNR_1': global_type_boolean,
		210	'save': global_type_boolean,
		211	'figpath': global_type_string,
		212	'lastone': global_type_float,
		213	'figfile': global_type_string,
		214	'ftp': global_type_string,
		215	'wr_period': global_type_integer,
		216	'show': global_type_string,
		217	'server': global_type_string,
		218	'folder': global_type_string,
		219	'username': global_type_string,
		220	'password': global_type_string,
		221	'ftp_wei': global_type_integer,
		222	'exp_code': global_type_integer,
		223	'sub_exp_code': global_type_integer,
		224	'plot_pos': global_type_integer,
		225	}
		226
		227
		228	Figure
		229	# parameters = {
		230	# : global_type_string,
		231	# }
		232
		233
		234	#FitsWriter
		235	parameters = {
		236	'path': global_type_string,
		237	'dataBlocksPerFile': global_type_integer,
		238	'metadatafile': global_type_string,
		239	}
		240
		241
		242	#IncohInt
		243	parameters = {
		244	'n': global_type_float,
		245	'timeInterval': global_type_integer,
		246	'overlapping': global_type_boolean,
		247	}
		248
		249
		250	#IncohInt4SpectraHeis
		251	parameters = {
		252	'n': global_type_float,
		253	'timeInterval': global_type_integer,
		254	'overlapping': global_type_boolean,
		255	}
		256
		257
		258	#MomentsPlot
		259	parameters = {
		260	'id': global_type_string,
		261	'wintitle': global_type_string,
		262	'channelList': global_type_list,
		263	'showprofile': global_type_boolean,
		264	'xmin': global_type_float,
		265	'xmax': global_type_float,
		266	'ymin': global_type_float,
		267	'ymax': global_type_float,
		268	'zmin': global_type_float,
		269	'zmax': global_type_float,
		270	'save': global_type_boolean,
		271	'figpath': global_type_string,
		272	'figfile': global_type_string,
		273	'show': global_type_boolean,
		274	'ftp': global_type_boolean,
		275	'wr_period': global_type_integer,
		276	'server': global_type_string,
		277	'folder': global_type_string,
		278	'username': global_type_string,
		279	'password': global_type_string,
		280	'ftp_wei': global_type_string,
		281	'exp_code': global_type_integer,
		282	'sub_exp_code': global_type_integer,
		283	'plot_pos': global_type_integer,
		284	'realtime': global_type_boolean,
		285	}
		286
		287
		288	#NSMeteorDetection1Plot
		289	parameters = {
		290	'id': global_type_string,
		291	'wintitle': global_type_string,
		292	'channelList': global_type_list,
		293	'showprofile': global_type_boolean,
		294	'xmin': global_type_float,
		295	'xmax': global_type_float,
		296	'ymin': global_type_float,
		297	'ymax': global_type_float,
		298	'SNRmin': global_type_float,
		299	'SNRmax': global_type_float,
		300	'vmin': global_type_float,
		301	'vmax': global_type_float,
		302	'wmin': global_type_float,
		303	'wmax': global_type_float,
		304	'mode': global_type_string,
		305	'save': global_type_boolean,
		306	'figpath': global_type_string,
		307	'figfile': global_type_string,
		308	'show': global_type_boolean,
		309	'ftp': global_type_string,
		310	'wr_period': global_type_integer,
		311	'server': global_type_string,
		312	'folder': global_type_string,
		313	'username': global_type_string,
		314	'password': global_type_string,
		315	'ftp_wei': global_type_integer,
		316	'exp_code': global_type_integer,
		317	'sub_exp_code': global_type_integer,
		318	'plot_pos': global_type_integer,
		319	'realtime': global_type_boolean,
		320	'xaxis': global_type_string,
		321	}
		322
		323
		324	#NSMeteorDetection2Plot
		325	parameters = {
		326	'id': global_type_string,
		327	'wintitle': global_type_string,
		328	'channelList': global_type_list,
		329	'showprofile': global_type_boolean,
		330	'xmin': global_type_float,
		331	'xmax': global_type_float,
		332	'ymin': global_type_float,
		333	'ymax': global_type_float,
		334	'SNRmin': global_type_float,
		335	'SNRmax': global_type_float,
		336	'vmin': global_type_float,
		337	'vmax': global_type_float,
		338	'wmin': global_type_float,
		339	'wmax': global_type_float,
		340	'mode': global_type_string,
		341	'save': global_type_boolean,
		342	'figpath': global_type_string,
		343	'figfile': global_type_string,
		344	'show': global_type_string,
		345	'ftp': global_type_boolean,
		346	'wr_period': global_type_integer,
		347	'server': global_type_string,
		348	'folder': global_type_string,
		349	'username': global_type_string,
		350	'password': global_type_string,
		351	'ftp_wei': global_type_integer,
		352	'exp_code': global_type_integer,
		353	'sub_exp_code': global_type_integer,
		354	'plot_pos': global_type_integer,
		355	'realtime': global_type_boolean,
		356	'xaxis': global_type_string,
		357	}
		358
		359
		360	#Noise
		361	parameters = {
		362	'id': global_type_string,
		363	'wintitle': global_type_string,
		364	'channelList': global_type_list,
		365	'showprofile': global_type_boolean,
		366	'xmin': global_type_float,
		367	'xmax': global_type_float,
		368	'ymin': global_type_float,
		369	'ymax': global_type_float,
		370	'timerange': global_type_float,
		371	'save': global_type_boolean,
		372	'figpath': global_type_string,
		373	'figfile': global_type_string,
		374	'show': global_type_boolean,
		375	'ftp': global_type_boolean,
		376	'wr_period': global_type_integer,
		377	'server': global_type_string,
		378	'folder': global_type_string,
		379	'username': global_type_string,
		380	'password': global_type_string,
		381	'ftp_wei': global_type_integer,
		382	'exp_code': global_type_integer,
		383	'sub_exp_code': global_type_integer,
		384	'plot_pos': global_type_integer,
		385	}
		386
		387
		388	#NonSpecularMeteorDetection
		389	parameters = {
		390	'mode': global_type_string,
		391	'SNRthresh': global_type_float,
		392	'phaseDerThresh': global_type_float,
		393	'cohThresh': global_type_float,
		394	'allData': global_type_boolean,
		395	}
		396
		397
		398	Operation
		399	parameters = {
		400	'dataIn': global_type_string,
		401	}
		402
		403
		404	#ParamWriter
		405	parameters = {
		406	'path': global_type_string,
		407	'blocksPerFile':global_type_integer,
		408	'metadataList': global_type_list,
		409	'dataList': global_type_list,
		410	'mode': global_type_integer,
		411	}
		412
		413
		414	#Parameters1Plot
		415	parameters = {
		416	'id': global_type_string,
		417	'wintitle': global_type_string,
		418	'channelList': global_type_list,
		419	'showprofile': global_type_boolean,
		420	'xmin': global_type_float,
		421	'xmax': global_type_float,
		422	'ymin': global_type_float,
		423	'ymax': global_type_float,
		424	'zmin': global_type_float,
		425	'zmax': global_type_float,
		426	'timerange': global_type_float,
		427	'parameterIndex': global_type_float,
		428	'onlyPositive': global_type_boolean,
		429	'SNRthresh': global_type_float,
		430	'SNR': global_type_boolean,
		431	'SNRmin': global_type_float,
		432	'SNRmax': global_type_float,
		433	'onlySNR': global_type_boolean,
		434	'DOP': global_type_boolean,
		435	'zlabel': global_type_string,
		436	'parameterName': global_type_string,
		437	'parameterObject': global_type_string,
		438	'save': global_type_boolean,
		439	'figpath': global_type_string,
		440	'lastone': global_type_integer,
		441	'figfile': global_type_string,
		442	'ftp': global_type_boolean,
		443	'wr_period': global_type_integer,
		444	'show': global_type_string,
		445	'server': global_type_string,
		446	'folder': global_type_string,
		447	'username': global_type_string,
		448	'password': global_type_string,
		449	'ftp_wei': global_type_integer,
		450	'exp_code': global_type_integer,
		451	'sub_exp_code': global_type_integer,
		452	'plot_pos': global_type_integer,
		453	}
		454
		455
		456	#ParametersPlot
		457	parameters = {
		458	'id': global_type_string,
		459	'wintitle': global_type_string,
		460	'channelList': global_type_list,
		461	'paramIndex': global_type_integer,
		462	'colormap': global_type_colormap,
		463	'xmin': global_type_float,
		464	'xmax': global_type_float,
		465	'ymin': global_type_float,
		466	'ymax': global_type_float,
		467	'zmin': global_type_float,
		468	'zmax': global_type_float,
		469	'timerange': global_type_float,
		470	'showSNR': global_type_boolean,
		471	'SNRthresh': global_type_float,
		472	'SNRmin': global_type_float,
		473	'SNRmax': global_type_float,
		474	'save': global_type_boolean,
		475	'figpath': global_type_string,
		476	'lastone': global_type_integer,
		477	'figfile': global_type_string,
		478	'ftp': global_type_boolean,
		479	'wr_period': global_type_integer,
		480	'show': global_type_boolean,
		481	'server': global_type_string,
		482	'folder': global_type_string,
		483	'username': global_type_string,
		484	'password': global_type_string,
		485	'ftp_wei': global_type_integer,
		486	'exp_code': global_type_integer,
		487	'sub_exp_code': global_type_integer,
		488	'plot_pos': global_type_integer,
		489	}
		490
		491
		492	#PhasePlot
		493	parameters = {
		494	'id': global_type_string,
		495	'wintitle': global_type_string,
		496	'pairsList': global_type_pairsList,
		497	'showprofile': global_type_boolean,
		498	'xmin': global_type_float,
		499	'xmax': global_type_float,
		500	'ymin': global_type_float,
		501	'ymax': global_type_float,
		502	'timerange': global_type_float,
		503	'save': global_type_boolean,
		504	'figpath': global_type_string,
		505	'figfile': global_type_string,
		506	'show': global_type_boolean,
		507	'ftp': global_type_boolean,
		508	'wr_period': global_type_integer,
		509	'server': global_type_string,
		510	'folder': global_type_string,
		511	'username': global_type_string,
		512	'password': global_type_string,
		513	'ftp_wei': global_type_integer,
		514	'exp_code': global_type_integer,
		515	'sub_exp_code': global_type_integer,
		516	'plot_pos': global_type_integer,
		517	}
		518
		519
		520	PlotCOHData
		521	parameters = {
		522	: global_type_string,
		523	}
		524
		525
		526	PlotCrossSpectraData
		527	parameters = {
		528	: global_type_string,
		529	}
		530
		531
		532	PlotDOPData
		533	parameters = {
		534	: global_type_string,
		535	}
		536
		537
		538	PlotData
		539	parameters = {
		540	: global_type_string,
		541	}
		542
		543
		544	PlotNoiseData
		545	parameters = {
		546	: global_type_string,
		547	}
		548
		549
		550	PlotPHASEData
		551	parameters = {
		552	: global_type_string,
		553	}
		554
		555
		556	PlotRTIData
		557	parameters = {
		558	: global_type_string,
		559	}
		560
		561
		562	PlotSNRData
		563	parameters = {
		564	: global_type_string,
		565	}
		566
		567
		568	PlotSpectraData
		569	parameters = {
		570	: global_type_string,
		571	}
		572
		573
		574	PlotSpectraMeanData
		575	parameters = {
		576	: global_type_string,
		577	}
		578
		579
		580	PlotWindProfilerData
		581	parameters = {
		582	: global_type_string,
		583	}
		584
		585
		586	PowerProfilePlot
		587	parameters = {
		588	'id': global_type_string,
		589	'wintitle': global_type_string,
		590	'channelList': global_type_list,
		591	'xmin': global_type_float,
		592	'xmax': global_type_float,
		593	'ymin': global_type_float,
		594	'ymax': global_type_float,
		595	'save': global_type_boolean,
		596	'figpath': global_type_string,
		597	'figfile': global_type_string,
		598	'show': global_type_boolean,
		599	'ftp': global_type_boolean,
		600	'wr_period': global_type_integer,
		601	'server': global_type_string,
		602	'folder': global_type_string,
		603	'username': global_type_string,
		604	'password': global_type_string,
		605	}
		606
		607
		608	PrintInfo
		609	parameters = {
		610	: global_type_string,
		611	}
		612
		613
		614	ProfileConcat
		615	parameters = {
		616	'm': global_type_string,
		617	}
		618
		619
		620	ProfileSelector
		621	parameters = {
		622	'profileList': global_type_string,
		623	'profileRangeList': global_type_string,
		624	'beam': global_type_string,
		625	'byblock': global_type_string,
		626	'rangeList': global_type_string,
		627	'nProfiles': global_type_string,
		628	}
		629
		630
		631	ProfileToChannels
		632	parameters = {
		633	: global_type_string,
		634	}
		635
		636
		637	PublishData
		638	parameters = {
		639	: global_type_string,
		640	}
		641
		642
		643	RTIPlot
		644	parameters = {
		645	'id': global_type_string,
		646	'wintitle': global_type_string,
		647	'channelList': global_type_list,
		648	'showprofile': global_type_boolean,
		649	'xmin': global_type_float,
		650	'xmax': global_type_float,
		651	'ymin': global_type_float,
		652	'ymax': global_type_float,
		653	'zmin': global_type_float,
		654	'zmax': global_type_float,
		655	'timerange': global_type_float,
		656	'save': global_type_boolean,
		657	'figpath': global_type_string,
		658	'lastone': global_type_string,
		659	'figfile': global_type_string,
		660	'ftp': global_type_boolean,
		661	'wr_period': global_type_integer,
		662	'show': global_type_boolean,
		663	'server': global_type_string,
		664	'folder': global_type_string,
		665	'username': global_type_string,
		666	'password': global_type_string,
		667	'ftp_wei': global_type_integer,
		668	'exp_code': global_type_integer,
		669	'sub_exp_code': global_type_integer,
		670	'plot_pos': global_type_integer,
		671	}
		672
		673
		674	RTIfromSpectraHeis
		675	parameters = {
		676	'id': global_type_string,
		677	'wintitle': global_type_string,
		678	'channelList': global_type_list,
		679	'showprofile': global_type_boolean,
		680	'xmin': global_type_float,
		681	'xmax': global_type_float,
		682	'ymin': global_type_float,
		683	'ymax': global_type_float,
		684	'timerange': global_type_float,
		685	'save': global_type_boolean,
		686	'figpath': global_type_string,
		687	'figfile': global_type_string,
		688	'ftp': global_type_boolean,
		689	'wr_period': global_type_integer,
		690	'show': global_type_boolean,
		691	'server': global_type_string,
		692	'folder': global_type_string,
		693	'username': global_type_string,
		694	'password': global_type_string,
		695	'ftp_wei': global_type_integer,
		696	'exp_code': global_type_integer,
		697	'sub_exp_code': global_type_integer,
		698	'plot_pos': global_type_integer,
		699	}
		700
		701
		702	Reshaper
		703	parameters = {
		704	'shape': global_type_string,
		705	'nTxs': global_type_string,
		706	}
		707
		708
		709	SALags
		710	parameters = {
		711	: global_type_string,
		712	}
		713
		714
		715	SMDetection
		716	parameters = {
		717	'hei_ref': global_type_string,
		718	'tauindex': global_type_string,
		719	'phaseOffsets': global_type_string,
		720	'cohDetection': global_type_string,
		721	'cohDet_timeStep': global_type_string,
		722	'cohDet_thresh': global_type_string,
		723	'noise_timeStep': global_type_string,
		724	'noise_multiple': global_type_string,
		725	'multDet_timeLimit': global_type_string,
		726	'multDet_rangeLimit': global_type_string,
		727	'phaseThresh': global_type_string,
		728	'SNRThresh': global_type_string,
		729	'hmin': global_type_string,
		730	'hmax': global_type_string,
		731	'azimuth': global_type_string,
		732	'channelPositions': global_type_string,
		733	}
		734
		735
		736	SMPhaseCalibration
		737	parameters = {
		738	'hmin': global_type_string,
		739	'hmax': global_type_string,
		740	'channelPositions': global_type_string,
		741	'nHours': global_type_string,
		742	}
		743
		744
		745	Scope
		746	parameters = {
		747	'id': global_type_string,
		748	'wintitle': global_type_string,
		749	'channelList': global_type_list,
		750	'xmin': global_type_float,
		751	'xmax': global_type_float,
		752	'ymin': global_type_float,
		753	'ymax': global_type_float,
		754	'save': global_type_boolean,
		755	'figpath': global_type_string,
		756	'figfile': global_type_string,
		757	'show': global_type_boolean,
		758	'wr_period': global_type_integer,
		759	'ftp': global_type_boolean,
		760	'server': global_type_string,
		761	'folder': global_type_string,
		762	'username': global_type_string,
		763	'password': global_type_string,
		764	'type': global_type_string,
		765	}
		766
		767
		768	SendByFTP
		769	parameters = {
		770	'ext': global_type_string,
		771	'localfolder': global_type_string,
		772	'remotefolder': global_type_string,
		773	'server': global_type_string,
		774	'username': global_type_string,
		775	'password': global_type_string,
		776	'period': global_type_string,
		777	}
		778
		779
		780	SkyMapPlot
		781	parameters = {
		782	'id': global_type_string,
		783	'wintitle': global_type_string,
		784	'channelList': global_type_list,
		785	'showprofile': global_type_boolean,
		786	'tmin': global_type_string,
		787	'tmax': global_type_string,
		788	'timerange': global_type_float,
		789	'save': global_type_boolean,
		790	'figpath': global_type_string,
		791	'figfile': global_type_string,
		792	'show': global_type_boolean,
		793	'ftp': global_type_boolean,
		794	'wr_period': global_type_integer,
		795	'server': global_type_string,
		796	'folder': global_type_string,
		797	'username': global_type_string,
		798	'password': global_type_string,
		799	'ftp_wei': global_type_integer,
		800	'exp_code': global_type_integer,
		801	'sub_exp_code': global_type_integer,
		802	'plot_pos': global_type_integer,
		803	'realtime': global_type_boolean,
		804	}
		805
		806
		807	SpectraCutPlot
		808	parameters = {
		809	'id': global_type_string,
		810	'wintitle': global_type_string,
		811	'channelList': global_type_list,
		812	'xmin': global_type_float,
		813	'xmax': global_type_float,
		814	'ymin': global_type_float,
		815	'ymax': global_type_float,
		816	'save': global_type_boolean,
		817	'figpath': global_type_string,
		818	'figfile': global_type_string,
		819	'show': global_type_boolean,
		820	'ftp': global_type_boolean,
		821	'wr_period': global_type_integer,
		822	'server': global_type_string,
		823	'folder': global_type_string,
		824	'username': global_type_string,
		825	'password': global_type_string,
		826	'xaxis': global_type_string,
		827	}
		828
		829
		830	SpectraHeisScope
		831	parameters = {
		832	'id': global_type_string,
		833	'wintitle': global_type_string,
		834	'channelList': global_type_list,
		835	'xmin': global_type_float,
		836	'xmax': global_type_float,
		837	'ymin': global_type_float,
		838	'ymax': global_type_float,
		839	'save': global_type_boolean,
		840	'figpath': global_type_string,
		841	'figfile': global_type_string,
		842	'ftp': global_type_boolean,
		843	'wr_period': global_type_integer,
		844	'show': global_type_boolean,
		845	'server': global_type_string,
		846	'folder': global_type_string,
		847	'username': global_type_string,
		848	'password': global_type_string,
		849	'ftp_wei': global_type_integer,
		850	'exp_code': global_type_integer,
		851	'sub_exp_code': global_type_integer,
		852	'plot_pos': global_type_integer,
		853	}
		854
		855
		856	SpectraHeisWriter
		857	parameters = {
		858	: global_type_string,
		859	}
		860
		861
		862	SpectraPlot
		863	parameters = {
		864	'id': global_type_string,
		865	'wintitle': global_type_string,
		866	'channelList': global_type_list,
		867	'showprofile': global_type_boolean,
		868	'xmin': global_type_float,
		869	'xmax': global_type_float,
		870	'ymin': global_type_float,
		871	'ymax': global_type_float,
		872	'zmin': global_type_float,
		873	'zmax': global_type_float,
		874	'save': global_type_boolean,
		875	'figpath': global_type_string,
		876	'figfile': global_type_string,
		877	'show': global_type_boolean,
		878	'ftp': global_type_boolean,
		879	'wr_period': global_type_integer,
		880	'server': global_type_string,
		881	'folder': global_type_string,
		882	'username': global_type_string,
		883	'password': global_type_string,
		884	'ftp_wei': global_type_integer,
		885	'exp_code': global_type_integer,
		886	'sub_exp_code': global_type_integer,
		887	'plot_pos': global_type_integer,
		888	'realtime': global_type_boolean,
		889	'xaxis': global_type_string,
		890	}
		891
		892
		893	SpectraWriter
		894	parameters = {
		895	'path': global_type_string,
		896	'blocksPerFile': global_type_string,
		897	'profilesPerBlock': global_type_string,
		898	'set': global_type_string,
		899	'ext': global_type_string,
		900	'datatype': global_type_string,
		901	}
		902
		903
		904	SpectralFitting
		905	parameters = {
		906	'getSNR': global_type_string,
		907	'path': global_type_string,
		908	'file': global_type_string,
		909	'groupList': global_type_string,
		910	}
		911
		912
		913	SpectralFittingPlot
		914	parameters = {
		915	'id': global_type_string,
		916	'cutHeight': global_type_string,
		917	'fit': global_type_string,
		918	'wintitle': global_type_string,
		919	'channelList': global_type_list,
		920	'showprofile': global_type_boolean,
		921	'xmin': global_type_float,
		922	'xmax': global_type_float,
		923	'ymin': global_type_float,
		924	'ymax': global_type_float,
		925	'save': global_type_boolean,
		926	'figpath': global_type_string,
		927	'figfile': global_type_string,
		928	'show': global_type_boolean,
		929	}
		930
		931
		932	SpectralMoments
		933	parameters = {
		934	: global_type_string,
		935	}
		936
		937
		938	SplitProfiles
		939	parameters = {
		940	'n': global_type_string,
		941	}
		942
		943
		944	USRPWriter
		945	parameters = {
		946	'dataIn': global_type_string,
		947	}
		948
		949
		950	VoltageWriter
		951	parameters = {
		952	'path': global_type_string,
		953	'blocksPerFile': global_type_string,
		954	'profilesPerBlock': global_type_string,
		955	'set': global_type_string,
		956	'ext': global_type_string,
		957	'datatype': global_type_string,
		958	}
		959
		960
		961	WindProfiler
		962	parameters = {
		963	'technique': global_type_string,
		964	}
		965
		966
		967	WindProfilerPlot
		968	parameters = {
		969	'id': global_type_string,
		970	'wintitle': global_type_string,
		971	'channelList': global_type_list,
		972	'showprofile': global_type_boolean,
		973	'xmin': global_type_float,
		974	'xmax': global_type_float,
		975	'ymin': global_type_float,
		976	'ymax': global_type_float,
		977	'zmin': global_type_float,
		978	'zmax': global_type_float,
		979	'zmax_ver': global_type_string,
		980	'zmin_ver': global_type_string,
		981	'SNRmin': global_type_float,
		982	'SNRmax': global_type_float,
		983	'timerange': global_type_float,
		984	'SNRthresh': global_type_string,
		985	'save': global_type_boolean,
		986	'figpath': global_type_string,
		987	'lastone': global_type_string,
		988	'figfile': global_type_string,
		989	'ftp': global_type_boolean,
		990	'wr_period': global_type_integer,
		991	'show': global_type_boolean,
		992	'server': global_type_string,
		993	'folder': global_type_string,
		994	'username': global_type_string,
		995	'password': global_type_string,
		996	'ftp_wei': global_type_integer,
		997	'exp_code': global_type_integer,
		998	'sub_exp_code': global_type_integer,
		999	'plot_pos': global_type_integer,
		1000	}
		1001
		1002
		1003	Writer
		1004	parameters = {
		1005	'dataIn': global_type_string,
		1006	}
		1007
		1008
		1009	AMISRProc
		1010	parameters = {
		1011	: global_type_string,
		1012	}
		1013
		1014
		1015	AMISRReader
		1016	parameters = {
		1017	: global_type_string,
		1018	}
		1019
		1020
		1021	CorrelationProc
		1022	parameters = {
		1023	'lags': global_type_string,
		1024	'mode': global_type_string,
		1025	'pairsList': 'pairsLists',
		1026	'fullBuffer': global_type_string,
		1027	'nAvg': global_type_string,
		1028	'removeDC': global_type_string,
		1029	'splitCF': global_type_string,
		1030	}
		1031
		1032
		1033	FitsReader
		1034	parameters = {
		1035	: global_type_string,
		1036	}
		1037
		1038
		1039	HFReader
		1040	parameters = {
		1041	: global_type_string,
		1042	}
		1043
		1044
		1045	ParamReader
		1046	parameters = {
		1047	: global_type_string,
		1048	}
		1049
		1050
		1051	ParametersProc
		1052	parameters = {
		1053	: global_type_string,
		1054	}
		1055
		1056
		1057	ProcessingUnit
		1058	parameters = {
		1059	: global_type_string,
		1060	}
		1061
		1062
		1063	ReceiverData
		1064	parameters = {
		1065	: global_type_string,
		1066	}
		1067
		1068
		1069	SendToServer
		1070	parameters = {
		1071	: global_type_string,
		1072	}
		1073
		1074
		1075	SpectraAFCProc
		1076	parameters = {
		1077	'nProfiles': global_type_string,
		1078	'nFFTPoints': global_type_string,
		1079	'pairsList': 'pairsLists',
		1080	'code': global_type_string,
		1081	'nCode': global_type_string,
		1082	'nBaud': global_type_string,
		1083	}
		1084
		1085
		1086	SpectraHeisProc
		1087	parameters = {
		1088	: global_type_string,
		1089	}
		1090
		1091
		1092	SpectraLagsProc
		1093	parameters = {
		1094	'nProfiles': global_type_string,
		1095	'nFFTPoints': global_type_string,
		1096	'pairsList': 'pairsLists',
		1097	'code': global_type_string,
		1098	'nCode': global_type_string,
		1099	'nBaud': global_type_string,
		1100	'codeFromHeader': global_type_string,
		1101	'pulseIndex': global_type_string,
		1102	}
		1103
		1104
		1105	SpectraProc
		1106	parameters = {
		1107	'nProfiles': global_type_string,
		1108	'nFFTPoints': global_type_string,
		1109	'pairsList': 'pairsLists',
		1110	'ippFactor': global_type_string,
		1111	}
		1112
		1113
		1114	SpectraReader
		1115	parameters = {
		1116	'path': global_type_string,
		1117	'startDate': global_type_string,
		1118	'endDate': global_type_string,
		1119	'startTime': global_type_string,
		1120	'endTime': global_type_string,
		1121	'set': global_type_string,
		1122	'expLabel': global_type_string,
		1123	'ext': global_type_string,
		1124	'online': global_type_string,
		1125	'delay': global_type_string,
		1126	'walk': global_type_string,
		1127	'getblock': global_type_string,
		1128	'nTxs': global_type_string,
		1129	'realtime': global_type_boolean,
		1130	'blocksize': global_type_string,
		1131	'blocktime': global_type_string,
		1132	'queue': global_type_string,
		1133	'skip': global_type_string,
		1134	'cursor': global_type_string,
		1135	'warnings': global_type_string,
		1136	'verbose': global_type_string,
		1137	}
		1138
		1139
		1140	USRPReader
		1141	parameters = {
		1142	: global_type_string,
		1143	}
		1144
		1145
		1146	VoltageProc
		1147	parameters = {
		1148	: global_type_string,
		1149	}
		1150
		1151
		1152	VoltageReader
		1153	parameters = {
		1154	'path': global_type_string,
		1155	'startDate': global_type_string,
		1156	'endDate': global_type_string,
		1157	'startTime': global_type_string,
		1158	'endTime': global_type_string,
		1159	'set': global_type_string,
		1160	'expLabel': global_type_string,
		1161	'ext': global_type_string,
		1162	'online': global_type_string,
		1163	'delay': global_type_string,
		1164	'walk': global_type_string,
		1165	'getblock': global_type_string,
		1166	'nTxs': global_type_string,
		1167	'realtime': global_type_boolean,
		1168	'blocksize': global_type_string,
		1169	'blocktime': global_type_string,
		1170	'queue': global_type_string,
		1171	'skip': global_type_string,
		1172	'cursor': global_type_string,
		1173	'warnings': global_type_string,
		1174	'verbose': global_type_string,
		1175	}
		1176
		1177

schainpy/utils/paramsFinder.py created 644 +81 0

@@ -0,0 +1,81
	1	import schainpy
	2	from schainpy.model import Operation, ProcessingUnit
	3	from importlib import import_module
	4	from pydoc import locate
	5
	6	def clean_modules(module):
	7	noEndsUnder = [x for x in module if not x.endswith('__')]
	8	noStartUnder = [x for x in noEndsUnder if not x.startswith('__')]
	9	noFullUpper = [x for x in noStartUnder if not x.isupper()]
	10	return noFullUpper
	11
	12	def check_module(possible, instance):
	13	def check(x):
	14	try:
	15	instancia = locate('schainpy.model.{}'.format(x))
	16	return isinstance(instancia(), instance)
	17	except Exception as e:
	18	return False
	19	clean = clean_modules(possible)
	20	return [x for x in clean if check(x)]
	21
	22
	23	def getProcs():
	24	module = dir(import_module('schainpy.model'))
	25	procs = check_module(module, ProcessingUnit)
	26	try:
	27	procs.remove('ProcessingUnit')
	28	except Exception as e:
	29	pass
	30	return procs
	31
	32	def getOperations():
	33	module = dir(import_module('schainpy.model'))
	34	noProcs = [x for x in module if not x.endswith('Proc')]
	35	operations = check_module(noProcs, Operation)
	36	try:
	37	operations.remove('Operation')
	38	except Exception as e:
	39	pass
	40	return operations
	41
	42	def getArgs(op):
	43	module = locate('schainpy.model.{}'.format(op))
	44	args = module().getAllowedArgs()
	45	try:
	46	args.remove('self')
	47	except Exception as e:
	48	pass
	49	try:
	50	args.remove('dataOut')
	51	except Exception as e:
	52	pass
	53	return args
	54
	55	def getAll():
	56	allModules = dir(import_module('schainpy.model'))
	57	modules = check_module(allModules, Operation)
	58	modules.extend(check_module(allModules, ProcessingUnit))
	59	return modules
	60
	61	def formatArgs(op):
	62	args = getArgs(op)
	63
	64	argsAsKey = ["\t'{}'".format(x) for x in args]
	65	argsFormatted = ": 'string',\n".join(argsAsKey)
	66
	67	print op
	68	print "parameters = { \n" + argsFormatted + ": 'string',\n }"
	69	print '\n'
	70
	71
	72	if __name__ == "__main__":
	73	getAll()
	74	[formatArgs(x) for x in getAll()]
	75
	76	'''
	77	parameters = {
	78	'id': ,
	79	'wintitle': ,
	80	}
	81	''' No newline at end of file

schainpy/utils/trash created 644 +1 0

	@@ -0,0 +1,1
				1	You should install "digital_rf_hdf5" module if you want to read USRP data

schaincli/cli.py +7 -28

             import click
             import schainpy
             import subprocess
             import os
             import sys
             import glob
             save_stdout = sys.stdout
             sys.stdout = open('trash', 'w')
             from multiprocessing import cpu_count
             from schaincli import templates
             from schainpy import controller_api
             from schainpy.model import Operation, ProcessingUnit
             from schainpy.utils import log
             from importlib import import_module
             from pydoc import locate
             from fuzzywuzzy import process
+            from schainpy.utils import paramsFinder
             sys.stdout = save_stdout
             def print_version(ctx, param, value):
                 if not value or ctx.resilient_parsing:
                     return
                 click.echo(schainpy.__version__)
                 ctx.exit()
             cliLogger = log.makelogger('schain cli')
             PREFIX = 'experiment'
             @click.command()
             @click.option('--version', '-v', is_flag=True, callback=print_version, help='SChain version', type=str)
             @click.option('--xml', '-x', default=None, help='run an XML file', type=click.Path(exists=True, resolve_path=True))
             @click.argument('command', default='run', required=True)
             @click.argument('nextcommand', default=None, required=False, type=str)
             def main(command, nextcommand, version, xml):
                 """COMMAND LINE INTERFACE FOR SIGNAL CHAIN - JICAMARCA RADIO OBSERVATORY \n
                     Available commands.\n
                     --xml: runs a schain XML generated file\n
                     run: runs any python script starting 'experiment_'\n
                     generate: generates a template schain script\n
                     search: return avilable operations, procs or arguments of the give operation/proc\n"""
                 if xml is not None:
                     runFromXML(xml)
                 elif command == 'generate':
                     generate()
                 elif command == 'test':
                     test()
                 elif command == 'run':
                     runschain(nextcommand)
                 elif command == 'search':
                     search(nextcommand)
                 else:
                     log.error('Command {} is not defined'.format(command))
             def check_module(possible, instance):
                 def check(x):
                     try:
                         instancia = locate('schainpy.model.{}'.format(x))
                         return isinstance(instancia(), instance)
                     except Exception as e:
                         return False
                 clean = clean_modules(possible)
                 return [x for x in clean if check(x)]
             def clean_modules(module):
                 noEndsUnder = [x for x in module if not x.endswith('__')]
                 noStartUnder = [x for x in noEndsUnder if not x.startswith('__')]
                 noFullUpper = [x for x in noStartUnder if not x.isupper()]
                 return noFullUpper
             def search(nextcommand):
                 if nextcommand is None:
                     log.error('There is no Operation/ProcessingUnit to search')
                 elif nextcommand == 'procs':
-                    module = dir(import_module('schainpy.model'))
+                    procs = paramsFinder.getProcs()
-                    procs = check_module(module, ProcessingUnit)
-                    try:
-                        procs.remove('ProcessingUnit')
-                    except Exception as e:
-                        pass
                     log.success('Current ProcessingUnits are:\n\033[1m{}\033[0m'.format('\n'.join(procs)))
                 elif nextcommand == 'operations':
-                    module = dir(import_module('schainpy.model'))
+                    operations = paramsFinder.getOperations()
-                    noProcs = [x for x in module if not x.endswith('Proc')]
-                    operations = check_module(noProcs, Operation)
-                    try:
-                        operations.remove('Operation')
-                    except Exception as e:
-                        pass
                     log.success('Current Operations are:\n\033[1m{}\033[0m'.format('\n'.join(operations)))
                 else:
                     try:
-                        module = locate('schainpy.model.{}'.format(nextcommand))
+                        args = paramsFinder.getArgs(nextcommand)
-                        args = module().getAllowedArgs()
                         log.warning('Use this feature with caution. It may not return all the allowed arguments')
-                        try:
-                            args.remove('self')
-                        except Exception as e:
-                            pass
-                        try:
-                            args.remove('dataOut')
-                        except Exception as e:
-                            pass
                         if len(args) == 0:
                             log.success('{} has no arguments'.format(nextcommand))
                         else:
                             log.success('Showing arguments of {} are:\n\033[1m{}\033[0m'.format(nextcommand, '\n'.join(args)))
                     except Exception as e:
                         log.error('Module {} does not exists'.format(nextcommand))
-                        allModules = dir(import_module('schainpy.model'))
+                        allModules = paramsFinder.getAll()
-                        module = check_module(allModules, Operation)
+                        similar = process.extractOne(nextcommand, allModules)[0]
-                        module.extend(check_module(allModules, ProcessingUnit))
+                        log.success('Showing {} instead'.format(similar))
-                        similar = process.extractOne(nextcommand, module)[0]
-                        log.success('Searching {} instead'.format(similar))
                         search(similar)
             def runschain(nextcommand):
                 if nextcommand is None:
                     currentfiles = glob.glob('./{}_*.py'.format(PREFIX))
                     numberfiles = len(currentfiles)
                     if numberfiles > 1:
                         log.error('There is more than one file to run')
                     elif numberfiles == 1:
                         subprocess.call(['python ' + currentfiles[0]], shell=True)
                     else:
                         log.error('There is no file to run')
                 else:
                     try:
                         subprocess.call(['python ' + nextcommand], shell=True)
                     except Exception as e:
                         log.error("I cannot run the file. Does it exists?")
             def basicInputs():
                 inputs = {}
                 inputs['desc'] = click.prompt('Enter a description', default="A schain project", type=str)
                 inputs['name'] = click.prompt('Name of the project', default="project", type=str)
                 inputs['path'] = click.prompt('Data path', default=os.getcwd(), type=click.Path(exists=True, resolve_path=True))
                 inputs['startDate'] = click.prompt('Start date', default='1970/01/01', type=str)
                 inputs['endDate'] = click.prompt('End date', default='2017/12/31', type=str)
                 inputs['startHour'] = click.prompt('Start hour', default='00:00:00', type=str)
                 inputs['endHour'] = click.prompt('End hour', default='23:59:59', type=str)
                 inputs['figpath'] = inputs['path'] + '/figs'
                 return inputs
             def generate():
                 inputs = basicInputs()
                 inputs['multiprocess'] = click.confirm('Is this a multiprocess script?')
                 if inputs['multiprocess']:
                     inputs['nProcess'] = click.prompt('How many process?', default=cpu_count(), type=int)
                     current = templates.multiprocess.format(**inputs)
                 else:
                     current = templates.basic.format(**inputs)
                 scriptname = '{}_{}.py'.format(PREFIX, inputs['name'])
                 script = open(scriptname, 'w')
                 try:
                     script.write(current)
                     log.success('Script {} generated'.format(scriptname))
                 except Exception as e:
                     log.error('I cannot create the file. Do you have writing permissions?')
             def test():
                 log.warning('testing')
             def runFromXML(filename):
                 controller = controller_api.ControllerThread()
                 if not controller.readXml(filename):
                     return
                 plotterObj = controller.useExternalPlotter()
                 controller.start()
                 plotterObj.start()
                 cliLogger("Finishing all processes")
                 controller.join(5)
                 cliLogger("End of script")
                 return

schainpy/model/__init__.py +10 0

             #from schainpy.model.data.jrodata import *
             # from schainpy.model.io.jrodataIO import *
             # from schainpy.model.proc.jroprocessing import *
             # from schainpy.model.graphics.jroplot import *
             # from schainpy.model.utils.jroutils import *
             # from schainpy.serializer import *
             from data import *
             from io import *
             from proc import *
             from graphics import *
             from utils import *
+            global_type_string = 'string'
+            global_type_integer = 'int'
+            global_type_floatList = 'floatList'
+            global_type_pairsList = 'pairsList'
+            global_type_boolean = 'bolean'
+            global_type_float = 'float'
+            global_type_colormap = 'colormap'
+            global_type_list = 'list'
+            global_type_float = 'float'

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

             import os
             import numpy
             import time, datetime
             import mpldriver
             from schainpy.model.proc.jroproc_base import Operation
             def isTimeInHourRange(datatime, xmin, xmax):
                 if xmin == None or xmax == None:
                     return 1
                 hour = datatime.hour + datatime.minute/60.0
                 if xmin < (xmax % 24):
                     if hour >= xmin and hour <= xmax:
                         return 1
                     else:
                         return 0
                 else:
                     if hour >= xmin or hour <= (xmax % 24):
                         return 1
                     else:
                         return 0
                 return 0
             def isRealtime(utcdatatime):
                 utcnow = time.mktime(time.localtime())
                 delta = abs(utcnow - utcdatatime) # abs
                 if delta >= 30.:
                     return False
                 return True
             class Figure(Operation):
                 __driver = mpldriver
                 fig = None
                 id = None
                 wintitle = None
                 width = None
                 height = None
                 nplots = None
                 timerange = None
                 axesObjList = []
                 WIDTH = 300
                 HEIGHT = 200
                 PREFIX = 'fig'
                 xmin = None
                 xmax = None
                 counter_imagwr = 0
                 figfile = None
                 created = False
+                parameters = {}
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                 def __del__(self):
                     self.__driver.closeFigure()
                 def getFilename(self, name, ext='.png'):
                     path = '%s%03d' %(self.PREFIX, self.id)
                     filename = '%s_%s%s' %(self.PREFIX, name, ext)
                     return os.path.join(path, filename)
                 def getAxesObjList(self):
                     return self.axesObjList
                 def getSubplots(self):
                     raise NotImplementedError
                 def getScreenDim(self, widthplot, heightplot):
                     nrow, ncol = self.getSubplots()
                     widthscreen = widthplot*ncol
                     heightscreen = heightplot*nrow
                     return widthscreen, heightscreen
                 def getTimeLim(self, x, xmin=None, xmax=None, timerange=None):
             #         if self.xmin != None and self.xmax != None:
             #             if timerange == None:
             #                 timerange = self.xmax - self.xmin
             #             xmin = self.xmin + timerange
             #             xmax = self.xmax + timerange
             #
             #             return xmin, xmax
                     if timerange == None and (xmin==None or xmax==None):
                         timerange = 14400   #seconds
                     if timerange != None:
                         txmin = x[0] #- x[0] % min(timerange/10, 10*60)
                     else:
                         txmin = x[0] #- x[0] % 10*60
                     thisdatetime = datetime.datetime.utcfromtimestamp(txmin)
                     thisdate = datetime.datetime.combine(thisdatetime.date(), datetime.time(0,0,0))
                     if timerange != None:
                         xmin = (thisdatetime - thisdate).seconds/(60*60.)
                         xmax = xmin + timerange/(60*60.)
                     d1970 = datetime.datetime(1970,1,1)
                     mindt = thisdate + datetime.timedelta(hours=xmin) #- datetime.timedelta(seconds=time.timezone)
                     xmin_sec = (mindt - d1970).total_seconds() #time.mktime(mindt.timetuple()) - time.timezone
                     maxdt = thisdate + datetime.timedelta(hours=xmax) #- datetime.timedelta(seconds=time.timezone)
                     xmax_sec = (maxdt - d1970).total_seconds() #time.mktime(maxdt.timetuple()) - time.timezone
                     return xmin_sec, xmax_sec
                 def init(self, id, nplots, wintitle):
                     raise NotImplementedError, "This method has been replaced by createFigure"
                 def createFigure(self, id, wintitle, widthplot=None, heightplot=None, show=True):
                     """
                     Crea la figura de acuerdo al driver y parametros seleccionados seleccionados.
                     Las dimensiones de la pantalla es calculada a partir de los atributos self.WIDTH
                     y self.HEIGHT y el numero de subplots (nrow, ncol)
                     Input:
                         id    :    Los parametros necesarios son
                         wintitle    :
                     """
                     if widthplot == None:
                         widthplot = self.WIDTH
                     if heightplot == None:
                         heightplot = self.HEIGHT
                     self.id = id
                     self.wintitle = wintitle
                     self.widthscreen, self.heightscreen = self.getScreenDim(widthplot, heightplot)
             #         if self.created:
             #             self.__driver.closeFigure(self.fig)
                     if not self.created:
                         self.fig = self.__driver.createFigure(id=self.id,
                                                               wintitle=self.wintitle,
                                                               width=self.widthscreen,
                                                               height=self.heightscreen,
                                                               show=show)
                     else:
                         self.__driver.clearFigure(self.fig)
                     self.axesObjList = []
                     self.counter_imagwr = 0
                     self.created = True
                 def setDriver(self, driver=mpldriver):
                     self.__driver = driver
                 def setTitle(self, title):
                     self.__driver.setTitle(self.fig, title)
                 def setWinTitle(self, title):
                     self.__driver.setWinTitle(self.fig, title=title)
                 def setTextFromAxes(self, text):
                     raise NotImplementedError, "This method has been replaced with Axes.setText"
                 def makeAxes(self, nrow, ncol, xpos, ypos, colspan, rowspan):
                     raise NotImplementedError, "This method has been replaced with Axes.addAxes"
                 def addAxes(self, *args):
                     """
                     Input:
                         *args    :    Los parametros necesarios son
                                       nrow, ncol, xpos, ypos, colspan, rowspan
                     """
                     axesObj = Axes(self.fig, *args)
                     self.axesObjList.append(axesObj)
                 def saveFigure(self, figpath, figfile, *args):
                     filename = os.path.join(figpath, figfile)
                     fullpath = os.path.split(filename)[0]
                     if not os.path.exists(fullpath):
                         subpath = os.path.split(fullpath)[0]
                         if not os.path.exists(subpath):
                             os.mkdir(subpath)
                         os.mkdir(fullpath)
                     self.__driver.saveFigure(self.fig, filename, *args)
                 def save(self, figpath, figfile=None, save=True, ftp=False, wr_period=1, thisDatetime=None, update_figfile=True):
                     self.counter_imagwr += 1
                     if self.counter_imagwr < wr_period:
                         return
                     self.counter_imagwr = 0
                     if save:
                         if not figfile:
                             if not thisDatetime:
                                 raise ValueError, "Saving figure: figfile or thisDatetime should be defined"
                                 return
                             str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                             figfile = self.getFilename(name = str_datetime)
                         if self.figfile == None:
                             self.figfile = figfile
                         if update_figfile:
                             self.figfile = figfile
                         # store png plot to local folder
                         self.saveFigure(figpath, self.figfile)
                     if not ftp:
                         return
                     if not thisDatetime:
                         return
                     # store png plot to FTP server according to RT-Web format
                     ftp_filename = self.getNameToFtp(thisDatetime, self.FTP_WEI, self.EXP_CODE, self.SUB_EXP_CODE, self.PLOT_CODE, self.PLOT_POS)
             #         ftp_filename = os.path.join(figpath, name)
                     self.saveFigure(figpath, ftp_filename)
                 def getNameToFtp(self, thisDatetime, FTP_WEI, EXP_CODE, SUB_EXP_CODE, PLOT_CODE, PLOT_POS):
                     YEAR_STR = '%4.4d'%thisDatetime.timetuple().tm_year
                     DOY_STR = '%3.3d'%thisDatetime.timetuple().tm_yday
                     FTP_WEI = '%2.2d'%FTP_WEI
                     EXP_CODE = '%3.3d'%EXP_CODE
                     SUB_EXP_CODE = '%2.2d'%SUB_EXP_CODE
                     PLOT_CODE = '%2.2d'%PLOT_CODE
                     PLOT_POS = '%2.2d'%PLOT_POS
                     name = YEAR_STR + DOY_STR + FTP_WEI + EXP_CODE + SUB_EXP_CODE + PLOT_CODE + PLOT_POS
                     return name
                 def draw(self):
                     self.__driver.draw(self.fig)
                 def run(self):
                     raise NotImplementedError
                 def close(self, show=False):
                     self.__driver.closeFigure(show=show, fig=self.fig)
                 axesList = property(getAxesObjList)
             class Axes:
                 __driver = mpldriver
                 fig = None
                 ax = None
                 plot = None
                 __missing = 1E30
                 __firsttime = None
                 __showprofile = False
                 xmin = None
                 xmax = None
                 ymin = None
                 ymax = None
                 zmin = None
                 zmax = None
                 x_buffer = None
                 z_buffer = None
                 decimationx = None
                 decimationy = None
                 __MAXNUMX = 200
                 __MAXNUMY = 400
                 __MAXNUMTIME = 500
                 def __init__(self, *args):
                     """
                     Input:
                         *args    :    Los parametros necesarios son
                                       fig, nrow, ncol, xpos, ypos, colspan, rowspan
                     """
                     ax = self.__driver.createAxes(*args)
                     self.fig = args[0]
                     self.ax = ax
                     self.plot = None
                     self.__firsttime = True
                     self.idlineList = []
                     self.x_buffer = numpy.array([])
                     self.z_buffer = numpy.array([])
                 def setText(self, text):
                     self.__driver.setAxesText(self.ax, text)
                 def setXAxisAsTime(self):
                     pass
                 def pline(self, x, y,
                            xmin=None, xmax=None,
                            ymin=None, ymax=None,
                            xlabel='', ylabel='',
                            title='',
                            **kwargs):
                     """
                     Input:
                         x        :
                         y        :
                         xmin    :
                         xmax    :
                         ymin    :
                         ymax    :
                         xlabel    :
                         ylabel    :
                         title    :
                         **kwargs :    Los parametros aceptados son
                                       ticksize
                                       ytick_visible
                     """
                     if self.__firsttime:
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         self.plot = self.__driver.createPline(self.ax, x, y,
                                                               xmin, xmax,
                                                               ymin, ymax,
                                                               xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title,
                                                               **kwargs)
                         self.idlineList.append(0)
                         self.__firsttime = False
                         return
                     self.__driver.pline(self.plot, x, y, xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title)
             #         self.__driver.pause()
                 def addpline(self, x, y, idline, **kwargs):
                     lines = self.ax.lines
                     if idline in self.idlineList:
                         self.__driver.set_linedata(self.ax, x, y, idline)
                     if  idline not in(self.idlineList):
                         self.__driver.addpline(self.ax, x, y, **kwargs)
                         self.idlineList.append(idline)
                     return
                 def pmultiline(self, x, y,
                                xmin=None, xmax=None,
                                ymin=None, ymax=None,
                                xlabel='', ylabel='',
                                title='',
                                **kwargs):
                     if self.__firsttime:
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         self.plot = self.__driver.createPmultiline(self.ax, x, y,
                                                               xmin, xmax,
                                                               ymin, ymax,
                                                               xlabel=xlabel,
                                                               ylabel=ylabel,
                                                               title=title,
                                                               **kwargs)
                         self.__firsttime = False
                         return
                     self.__driver.pmultiline(self.plot, x, y, xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title)
             #         self.__driver.pause()
                 def pmultilineyaxis(self, x, y,
                                xmin=None, xmax=None,
                                ymin=None, ymax=None,
                                xlabel='', ylabel='',
                                title='',
                                **kwargs):
                     if self.__firsttime:
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         self.plot = self.__driver.createPmultilineYAxis(self.ax, x, y,
                                                               xmin, xmax,
                                                               ymin, ymax,
                                                               xlabel=xlabel,
                                                               ylabel=ylabel,
                                                               title=title,
                                                               **kwargs)
                         if self.xmin == None: self.xmin = xmin
                         if self.xmax == None: self.xmax = xmax
                         if self.ymin == None: self.ymin = ymin
                         if self.ymax == None: self.ymax = ymax
                         self.__firsttime = False
                         return
                     self.__driver.pmultilineyaxis(self.plot, x, y, xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title)
             #         self.__driver.pause()
                 def pcolor(self, x, y, z,
                            xmin=None, xmax=None,
                            ymin=None, ymax=None,
                            zmin=None, zmax=None,
                            xlabel='', ylabel='',
                            title='', colormap='jet',
                            **kwargs):
                     """
                     Input:
                         x        :
                         y        :
                         x        :
                         xmin    :
                         xmax    :
                         ymin    :
                         ymax    :
                         zmin    :
                         zmax    :
                         xlabel    :
                         ylabel    :
                         title    :
                         **kwargs :    Los parametros aceptados son
                                       ticksize=9,
                                       cblabel=''
                     """
                     #Decimating data
                     xlen = len(x)
                     ylen = len(y)
                     decimationx = int(xlen/self.__MAXNUMX) + 1
                     decimationy = int(ylen/self.__MAXNUMY) + 1
                     x_buffer = x#[::decimationx]
                     y_buffer = y#[::decimationy]
                     z_buffer = z#[::decimationx, ::decimationy]
                     #===================================================
                     if self.__firsttime:
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(z)
                         if zmax == None: zmax = numpy.nanmax(z)
                         self.plot = self.__driver.createPcolor(self.ax, x_buffer,
                                                                y_buffer,
                                                                z_buffer,
                                                                xmin, xmax,
                                                                ymin, ymax,
                                                                zmin, zmax,
                                                                xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title,
                                                                 colormap=colormap,
                                                                 **kwargs)
                         if self.xmin == None: self.xmin = xmin
                         if self.xmax == None: self.xmax = xmax
                         if self.ymin == None: self.ymin = ymin
                         if self.ymax == None: self.ymax = ymax
                         if self.zmin == None: self.zmin = zmin
                         if self.zmax == None: self.zmax = zmax
                         self.__firsttime = False
                         return
                     self.__driver.pcolor(self.plot,
                                          z_buffer,
                                          xlabel=xlabel,
                                          ylabel=ylabel,
                                          title=title)
             #         self.__driver.pause()
                 def pcolorbuffer(self, x, y, z,
                            xmin=None, xmax=None,
                            ymin=None, ymax=None,
                            zmin=None, zmax=None,
                            xlabel='', ylabel='',
                            title='', rti = True, colormap='jet',
                            maxNumX = None, maxNumY = None,
                            **kwargs):
                     if maxNumX == None:
                         maxNumX = self.__MAXNUMTIME
                     if maxNumY == None:
                         maxNumY = self.__MAXNUMY
                     if self.__firsttime:
                         self.z_buffer = z
                         self.x_buffer = numpy.hstack((self.x_buffer, x))
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(z)
                         if zmax == None: zmax = numpy.nanmax(z)
                         self.plot = self.__driver.createPcolor(self.ax, self.x_buffer, y, z,
                                                                xmin, xmax,
                                                                ymin, ymax,
                                                                zmin, zmax,
                                                                xlabel=xlabel,
                                                                 ylabel=ylabel,
                                                                 title=title,
                                                                 colormap=colormap,
                                                                 **kwargs)
                         if self.xmin == None: self.xmin = xmin
                         if self.xmax == None: self.xmax = xmax
                         if self.ymin == None: self.ymin = ymin
                         if self.ymax == None: self.ymax = ymax
                         if self.zmin == None: self.zmin = zmin
                         if self.zmax == None: self.zmax = zmax
                         self.__firsttime = False
                         return
                     self.x_buffer = numpy.hstack((self.x_buffer[:-1], x[0], x[-1]))
                     self.z_buffer = numpy.hstack((self.z_buffer, z))
                     z_buffer = self.z_buffer.reshape(-1,len(y))
                     #Decimating data
                     xlen = len(self.x_buffer)
                     ylen = len(y)
                     decimationx = int(xlen/maxNumX) + 1
                     decimationy = int(ylen/maxNumY) + 1
                     x_buffer = self.x_buffer#[::decimationx]
                     y_buffer = y#[::decimationy]
                     z_buffer = z_buffer#[::decimationx, ::decimationy]
                     #===================================================
                     x_buffer, y_buffer, z_buffer = self.__fillGaps(x_buffer, y_buffer, z_buffer)
                     self.__driver.addpcolorbuffer(self.ax, x_buffer, y_buffer, z_buffer, self.zmin, self.zmax,
                                             xlabel=xlabel,
                                             ylabel=ylabel,
                                             title=title,
                                             colormap=colormap)
             #         self.__driver.pause()
                 def polar(self, x, y,
                            title='', xlabel='',ylabel='',**kwargs):
                     if self.__firsttime:
                         self.plot = self.__driver.createPolar(self.ax, x, y, title = title, xlabel = xlabel, ylabel = ylabel)
                         self.__firsttime = False
                         self.x_buffer = x
                         self.y_buffer = y
                         return
                     self.x_buffer = numpy.hstack((self.x_buffer,x))
                     self.y_buffer = numpy.hstack((self.y_buffer,y))
                     self.__driver.polar(self.plot, self.x_buffer, self.y_buffer, xlabel=xlabel,
                                                         ylabel=ylabel,
                                                         title=title)
             #         self.__driver.pause()
                 def __fillGaps(self, x_buffer, y_buffer, z_buffer):
                     if x_buffer.shape[0] < 2:
                         return x_buffer, y_buffer, z_buffer
                     deltas = x_buffer[1:] - x_buffer[0:-1]
                     x_median = numpy.median(deltas)
                     index = numpy.where(deltas > 5*x_median)
                     if len(index[0]) != 0:
                         z_buffer[index[0],::] = self.__missing
                         z_buffer = numpy.ma.masked_inside(z_buffer,0.99*self.__missing,1.01*self.__missing)
                     return x_buffer, y_buffer, z_buffer

schainpy/model/graphics/jroplot_correlation.py +28 -1

             import os
             import datetime
             import numpy
             import copy
+            from schainpy.model import *
             from figure import Figure, isRealtime
             class CorrelationPlot(Figure):
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_string,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                    'realtime': global_type_boolean,
+                }
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'corr'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 280
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = 1
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=False, show=True):
                     showprofile = False
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 3
                         colspan = 2
                         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()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=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, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return None
                     if realtime:
                         if not(isRealtime(utcdatatime = dataOut.utctime)):
                             print 'Skipping this plot function'
                             return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     lenfactor = factor.shape[1]
                     x = dataOut.getLagTRange(1)
                     y = dataOut.getHeiRange()
                     z = copy.copy(dataOut.data_corr[:,:,0,:])
                     for i in range(dataOut.data_corr.shape[0]):
                         z[i,:,:] = z[i,:,:]/factor[i,:]
                     zdB = numpy.abs(z)
                     avg = numpy.average(z, axis=1)
             #         avg = numpy.nanmean(z, axis=1)
             #         noise = dataOut.noise/factor
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Correlation"
                     xlabel = "Lag T (s)"
                     ylabel = "Range (Km)"
                     if not self.isConfig:
                         nplots = dataOut.data_corr.shape[0]
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = 0
                         if zmax == None: zmax = 1
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d and %d: : %s" %(dataOut.pairsList[i][0],dataOut.pairsList[i][1] , str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[i,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, cblabel='')
             #             if self.__showprofile:
             #                 axes = self.axesList[i*self.__nsubplots +1]
             #                 axes.pline(avgdB[i], y,
             #                         xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
             #                         xlabel='dB', ylabel='', title='',
             #                         ytick_visible=False,
             #                         grid='x')
             #
             #                 noiseline = numpy.repeat(noisedB[i], len(y))
             #                 axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)

schainpy/model/graphics/jroplot_parameters.py +232 0

             import os
             import datetime
             import numpy
             import inspect
             from figure import Figure, isRealtime, isTimeInHourRange
             from plotting_codes import *
             class MomentsPlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_string,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                    'realtime': global_type_boolean,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 280
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MOMENTS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 3
                         colspan = 2
                         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()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=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, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if dataOut.flagNoData:
                         return None
                     if realtime:
                         if not(isRealtime(utcdatatime = dataOut.utctime)):
                             print 'Skipping this plot function'
                             return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = dataOut.data_pre[channelIndexList,:,:]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     noise = dataOut.noise/factor
                     zdB = 10*numpy.log10(z)
                     avgdB = 10*numpy.log10(avg)
                     noisedB = 10*numpy.log10(noise)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters"
                     xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(avgdB)*0.9
                         if zmax == None: zmax = numpy.nanmax(avgdB)*0.9
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[i,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, cblabel='')
                                     #Mean Line
                         mean = dataOut.data_param[i, 1, :]
                         axes.addpline(mean, y, idline=0, color="black", linestyle="solid", lw=1)
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[i], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                             noiseline = numpy.repeat(noisedB[i], len(y))
                             axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class SkyMapPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'mmap'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
             #         self.WIDTH = 280
             #         self.HEIGHT = 250
                     self.WIDTH = 600
                     self.HEIGHT = 600
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = MSKYMAP_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=False, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH, #+ self.WIDTHPROF,
                                       heightplot = self.HEIGHT,# + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = 1,1
                     counter = 0
                     x = 0
                     y = 0
                     self.addAxes(1, 1, 0, 0, 1, 1, True)
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         tmin=0, tmax=24, 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, realtime=False):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     arrayParameters = dataOut.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
                     x1 = [dataOut.ltctime, dataOut.ltctime]
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     title = wintitle + " Parameters"
                     xlabel = "Zonal Zenith Angle (deg) "
                     ylabel = "Meridional Zenith Angle (deg)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if self.xmin is None and self.xmax is None:
                             self.xmin, self.xmax = self.getTimeLim(x1, tmin, tmax, timerange)
                         if timerange != None:
                             self.timerange = timerange
                         else:
                             self.timerange = self.xmax - self.xmin
                         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.firstdate = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         self.isConfig = True
                         update_figfile = True
                     self.setWinTitle(title)
                     i = 0
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     axes = self.axesList[i*self.__nsubplots]
                     nevents = axes.x_buffer.shape[0] + x.shape[0]
                     title = "Meteor Detection Sky Map\n %s - %s \n Number of events: %5.0f\n" %(self.firstdate,str_datetime,nevents)
                     axes.polar(x, y,
                                 title=title, xlabel=xlabel, ylabel=ylabel,
                                 ticksize=9, cblabel='')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     if dataOut.ltctime >= self.xmax:
                         self.isConfigmagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                         axes.__firsttime = True
                         self.xmin += self.timerange
                         self.xmax += self.timerange
             class WindProfilerPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'wind'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 300
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = WIND_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='False',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmax_ver = None, zmin_ver = None, SNRmin = None, SNRmax = None,
                         timerange=None, SNRthresh = None,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
             #         if timerange is not None:
             #             self.timerange = timerange
             #
             #         tmin = None
             #         tmax = None
                     x = dataOut.getTimeRange1(dataOut.outputInterval)
                     y = dataOut.heightList
                     z = dataOut.data_output.copy()
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
                     if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR
                         SNRavg = numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         if SNRthresh == None: SNRthresh = -5.0
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     #thisDatetime = datetime.datetime.now()
                     title = wintitle + "Wind"
                     xlabel = ""
                     ylabel = "Height (km)"
                     update_figfile = False
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange is not None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmax == None: zmax = numpy.nanmax(abs(z[range(2),:]))
                         #if numpy.isnan(zmax): zmax = 50
                         if zmin == None: zmin = -zmax
                         if nplotsw == 3:
                             if zmax_ver == None: zmax_ver = numpy.nanmax(abs(z[2,:]))
                             if zmin_ver == None: zmin_ver = -zmax_ver
                         if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         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
                         update_figfile = True
                     self.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal', 'Meridional', 'Vertical']
                     strCb = ['Velocity (m/s)','Velocity (m/s)','Velocity (cm/s)']
                     zmaxVector = [zmax, zmax, zmax_ver]
                     zminVector = [zmin, zmin, zmin_ver]
                     windFactor = [1,1,100]
                     for i in range(nplotsw):
                         title = "%s Wind: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))*windFactor[i]
                         #z1=numpy.ma.masked_where(z1==0.,z1)
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb[i], cbsize="1%", colormap="seismic" )
                     if dataOut.data_SNR is not None:
                         i += 1
                         title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
                     if dataOut.ltctime + dataOut.outputInterval >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
             class ParametersPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'param'
                 nplots = None
                 nchan = None
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'paramIndex': global_type_integer,
+                    'colormap': global_type_colormap,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'timerange': global_type_float,
+                    'showSNR': global_type_boolean,
+                    'SNRthresh': global_type_float,
+                    'SNRmin': global_type_float,
+                    'SNRmax': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'lastone': global_type_integer,
+                    'figfile': global_type_string,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'show': global_type_boolean,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 180
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = RTI_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None,
                         showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if colormap:
                         colormap="jet"
                     else:
                         colormap="RdBu_r"
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = range(dataOut.data_param.shape[0])
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     x = dataOut.getTimeRange1(dataOut.paramInterval)
                     y = dataOut.getHeiRange()
                     if dataOut.data_param.ndim == 3:
                         z = dataOut.data_param[channelIndexList,paramIndex,:]
                     else:
                         z = dataOut.data_param[channelIndexList,:]
                     if showSNR:
                         #SNR data
                         SNRarray = dataOut.data_SNR[channelIndexList,:]
                         SNRdB = 10*numpy.log10(SNRarray)
                         ind = numpy.where(SNRdB < SNRthresh)
                         z[ind] = numpy.nan
                     thisDatetime = dataOut.datatime
             #         thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     update_figfile = False
                     if not self.isConfig:
                         nchan = len(channelIndexList)
                         self.nchan = nchan
                         self.plotFact = 1
                         nplots = nchan
                         if showSNR:
                             nplots = nchan*2
                             self.plotFact = 2
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if timerange != None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(z)
                         if zmax == None: zmax = numpy.nanmax(z)
                         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
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nchan):
                         index = channelIndexList[i]
                         title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.plotFact]
                         z1 = z[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%",colormap=colormap)
                         if showSNR:
                             title = "Channel %d SNR: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                             axes = self.axesList[i*self.plotFact + 1]
                             SNRdB1 = SNRdB[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, SNRdB1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%",colormap='jet')
                     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)
             class Parameters1Plot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'timerange': global_type_float,
+                    'parameterIndex': global_type_float,
+                    'onlyPositive': global_type_boolean,
+                    'SNRthresh': global_type_float,
+                    'SNR': global_type_boolean,
+                    'SNRmin': global_type_float,
+                    'SNRmax': global_type_float,
+                    'onlySNR': global_type_boolean,
+                    'DOP': global_type_boolean,
+                    'zlabel': global_type_string,
+                    'parameterName': global_type_string,
+                    'parameterObject': global_type_string,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'lastone': global_type_integer,
+                    'figfile': global_type_string,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'show': global_type_string,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 180
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = PARMS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,timerange=None,
                         parameterIndex = None, onlyPositive = False,
                         SNRthresh = -numpy.inf, SNR = True, SNRmin = None, SNRmax = None, onlySNR = False,
                         DOP = True,
                         zlabel = "", parameterName = "", parameterObject = "data_param",
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     #print inspect.getargspec(self.run).args
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     data_param = getattr(dataOut, parameterObject)
                     if channelList == None:
                         channelIndexList = numpy.arange(data_param.shape[0])
                     else:
                         channelIndexList = numpy.array(channelList)
                     nchan = len(channelIndexList) #Number of channels being plotted
                     if nchan < 1:
                         return
                     nGraphsByChannel = 0
                     if SNR:
                         nGraphsByChannel += 1
                     if DOP:
                         nGraphsByChannel += 1
                     if nGraphsByChannel < 1:
                         return
                     nplots = nGraphsByChannel*nchan
                     if timerange is not None:
                         self.timerange = timerange
                     #tmin = None
                     #tmax = None
                     if parameterIndex == None:
                         parameterIndex = 1
                     x = dataOut.getTimeRange1(dataOut.paramInterval)
                     y = dataOut.heightList
                     z = data_param[channelIndexList,parameterIndex,:].copy()
                     zRange = dataOut.abscissaList
             #         nChannels = z.shape[0]    #Number of wind dimensions estimated
             #        thisDatetime = dataOut.datatime
                     if dataOut.data_SNR is not None:
                         SNRarray = dataOut.data_SNR[channelIndexList,:]
                         SNRdB = 10*numpy.log10(SNRarray)
             #             SNRavgdB = 10*numpy.log10(SNRavg)
                         ind = numpy.where(SNRdB < 10**(SNRthresh/10))
                         z[ind] = numpy.nan
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Parameters Plot" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     if (SNR and not onlySNR): nplots = 2*nplots
                     if onlyPositive:
                         colormap = "jet"
                         zmin = 0
                     else: colormap = "RdBu_r"
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.nanmin(zRange)
                         if zmax == None: zmax = numpy.nanmax(zRange)
                         if SNR:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRdB)
                         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.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     for i in range(nchan):
                         if (SNR and not onlySNR): j = 2*i
                         else: j = i
                         j = nGraphsByChannel*i
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                         if not onlySNR:
                             axes = self.axesList[j*self.__nsubplots]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                     ticksize=9, cblabel=zlabel, cbsize="1%")
                         if DOP:
                             title = "%s Channel %d: %s" %(parameterName, channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                             if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                                 title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                             axes = self.axesList[j]
                             z1 = z[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                         xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                         xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap=colormap,
                                         ticksize=9, cblabel=zlabel, cbsize="1%")
                         if SNR:
                             title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                             axes = self.axesList[(j)*self.__nsubplots]
                             if not onlySNR:
                                 axes = self.axesList[(j + 1)*self.__nsubplots]
                             axes = self.axesList[(j + nGraphsByChannel-1)]
                             z1 = SNRdB[i,:].reshape((1,-1))
                             axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,colormap="jet",
                                     ticksize=9, cblabel=zlabel, cbsize="1%")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         self.figfile = None
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=False)
             class SpectralFittingPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'prm'
                 N = None
                 ippSeconds = None
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = SPECFIT_CODE
                     self.WIDTH = 450
                     self.HEIGHT = 250
                     self.WIDTHPROF = 0
                     self.HEIGHTPROF = 0
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=False, show=True):
                     showprofile = False
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 5
                     colspan = 4
                     if showprofile:
                         ncolspan = 5
                         colspan = 4
                         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()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, cutHeight=None, fit=False, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if cutHeight==None:
                         h=270
                     heightindex = numpy.abs(cutHeight - dataOut.heightList).argmin()
                     cutHeight = dataOut.heightList[heightindex]
                     factor = dataOut.normFactor
                     x = dataOut.abscissaList[:-1]
                     #y = dataOut.getHeiRange()
                     z = dataOut.data_pre[:,:,heightindex]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     avg = numpy.average(z, axis=1)
                     listChannels = z.shape[0]
                     #Reconstruct Function
                     if fit==True:
                         groupArray = dataOut.groupList
                         listChannels = groupArray.reshape((groupArray.size))
                         listChannels.sort()
                         spcFitLine = numpy.zeros(z.shape)
                         constants = dataOut.constants
                         nGroups = groupArray.shape[0]
                         nChannels = groupArray.shape[1]
                         nProfiles = z.shape[1]
                         for f in range(nGroups):
                             groupChann = groupArray[f,:]
                             p = dataOut.data_param[f,:,heightindex]
             #                 p = numpy.array([ 89.343967,0.14036615,0.17086219,18.89835291,1.58388365,1.55099167])
                             fitLineAux = dataOut.library.modelFunction(p, constants)*nProfiles
                             fitLineAux = fitLineAux.reshape((nChannels,nProfiles))
                             spcFitLine[groupChann,:] = fitLineAux
             #             spcFitLine = spcFitLine/factor
                         z = z[listChannels,:]
                         spcFitLine = spcFitLine[listChannels,:]
                         spcFitLinedB = 10*numpy.log10(spcFitLine)
                     zdB = 10*numpy.log10(z)
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Doppler Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     xlabel = "Velocity (m/s)"
                     ylabel = "Spectrum"
                     if not self.isConfig:
                         nplots = listChannels.size
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(zdB)
                         if ymax == None: ymax = numpy.nanmax(zdB)+2
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
             #             title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i])
                         title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i])
                         axes = self.axesList[i*self.__nsubplots]
                         if fit == False:
                             axes.pline(x, zdB[i,:],
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title
                                         )
                         if fit == True:
                             fitline=spcFitLinedB[i,:]
                             y=numpy.vstack([zdB[i,:],fitline] )
                             legendlabels=['Data','Fitting']
                             axes.pmultilineyaxis(x, y,
                                         xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                                         xlabel=xlabel, ylabel=ylabel, title=title,
                                         legendlabels=legendlabels, marker=None,
                                         linestyle='solid', grid='both')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class EWDriftsPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'drift'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_string,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'zmaxVertfloat': global_type_float,
+                    'zminVertfloat': global_type_float,
+                    'zmaxZonafloat': global_type_float,
+                    'zminZonafloat': global_type_float,
+                    'timerange': global_type_float,
+                    'SNRthresh': global_type_float,
+                    'SNRmin': global_type_float,
+                    'SNRmax': global_type_float,
+                    'SNR_1': global_type_boolean,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'lastone': global_type_float,
+                    'figfile': global_type_string,
+                    'ftp': global_type_string,
+                    'wr_period': global_type_integer,
+                    'show': global_type_string,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 150
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = EWDRIFT_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         if counter >= self.nplots:
                             break
                         self.addAxes(nrow, ncol*ncolspan, y, 0, colspan, 1)
                         counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         zmaxVertical = None, zminVertical = None, zmaxZonal = None, zminZonal = None,
                         timerange=None, SNRthresh = -numpy.inf, SNRmin = None, SNRmax = None, SNR_1 = False,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if timerange is not None:
                         self.timerange = timerange
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1(dataOut.outputInterval)
             #         y = dataOut.heightList
                     y = dataOut.heightList
                     z = dataOut.data_output
                     nplots = z.shape[0]    #Number of wind dimensions estimated
                     nplotsw = nplots
                     #If there is a SNR function defined
                     if dataOut.data_SNR is not None:
                         nplots += 1
                         SNR = dataOut.data_SNR
                         if SNR_1:
                             SNR += 1
                         SNRavg = numpy.average(SNR, axis=0)
                         SNRdB = 10*numpy.log10(SNR)
                         SNRavgdB = 10*numpy.log10(SNRavg)
                         ind = numpy.where(SNRavg < 10**(SNRthresh/10))[0]
                         for i in range(nplotsw):
                             z[i,ind] = numpy.nan
                     showprofile = False
             #        thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(x[1])
                     title = wintitle + " EW Drifts"
                     xlabel = ""
                     ylabel = "Height (Km)"
                     if not self.isConfig:
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmaxZonal == None: zmaxZonal = numpy.nanmax(abs(z[0,:]))
                         if zminZonal == None: zminZonal = -zmaxZonal
                         if zmaxVertical == None: zmaxVertical = numpy.nanmax(abs(z[1,:]))
                         if zminVertical == None: zminVertical = -zmaxVertical
                         if dataOut.data_SNR is not None:
                             if SNRmin == None:  SNRmin = numpy.nanmin(SNRavgdB)
                             if SNRmax == None:  SNRmax = numpy.nanmax(SNRavgdB)
                         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.setWinTitle(title)
                     if ((self.xmax - x[1]) < (x[1]-x[0])):
                         x[1] = self.xmax
                     strWind = ['Zonal','Vertical']
                     strCb = 'Velocity (m/s)'
                     zmaxVector = [zmaxZonal, zmaxVertical]
                     zminVector = [zminZonal, zminVertical]
                     for i in range(nplotsw):
                         title = "%s Drifts: %s" %(strWind[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         z1 = z[i,:].reshape((1,-1))
                         axes.pcolorbuffer(x, y, z1,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zminVector[i], zmax=zmaxVector[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel=strCb, cbsize="1%", colormap="RdBu_r")
                     if dataOut.data_SNR is not None:
                         i += 1
                         if SNR_1:
                             title = "Signal Noise Ratio + 1 (SNR+1): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         else:
                             title = "Signal Noise Ratio (SNR): %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots]
                         SNRavgdB = SNRavgdB.reshape((1,-1))
                         axes.pcolorbuffer(x, y, SNRavgdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=SNRmin, zmax=SNRmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap="jet")
                     self.draw()
                     if x[1] >= self.axesList[0].xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         self.figfile = None
             class PhasePlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'mphase'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'pairsList': global_type_pairsList,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'timerange': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 24*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.counter_imagwr = 0
                     self.WIDTH = 600
                     self.HEIGHT = 300
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.xdata = None
                     self.ydata = None
                     self.PLOT_CODE = MPHASE_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
                 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 run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=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):
                     tmin = None
                     tmax = None
                     x = dataOut.getTimeRange1(dataOut.outputInterval)
                     y = dataOut.getHeiRange()
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     title = wintitle + " Phase of Beacon Signal" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "Local Time"
                     ylabel = "Phase"
                     #phase = numpy.zeros((len(pairsIndexList),len(dataOut.beacon_heiIndexList)))
                     phase_beacon = dataOut.data_output
                     update_figfile = False
                     if not self.isConfig:
                         self.nplots = phase_beacon.size
                         self.setup(id=id,
                                    nplots=self.nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if timerange is not None:
                             self.timerange = timerange
                         self.xmin, self.xmax = self.getTimeLim(x, xmin, xmax, timerange)
                         if ymin == None: ymin = numpy.nanmin(phase_beacon) - 10.0
                         if ymax == None: ymax = numpy.nanmax(phase_beacon) + 10.0
                         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([])
                         #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)
                         update_figfile = True
                     #store data beacon phase
                     #self.save_data(self.filename_phase, phase_beacon, thisDatetime)
                     self.setWinTitle(title)
                     title = "Phase Offset %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["phase %d"%(chan) for chan in numpy.arange(self.nplots)]
                     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()
                     self.save(figpath=figpath,
                       figfile=figfile,
                       save=save,
                       ftp=ftp,
                       wr_period=wr_period,
                       thisDatetime=thisDatetime,
                       update_figfile=update_figfile)
                     if dataOut.ltctime + dataOut.outputInterval >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
             class NSMeteorDetection1Plot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'nsm'
                 zminList = None
                 zmaxList = None
                 cmapList = None
                 titleList = None
                 nPairs = None
                 nChannels = None
                 nParam = None
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'SNRmin': global_type_float,
+                    'SNRmax': global_type_float,
+                    'vmin': global_type_float,
+                    'vmax': global_type_float,
+                    'wmin': global_type_float,
+                    'wmax': global_type_float,
+                    'mode': global_type_string,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_string,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                    'realtime': global_type_boolean,
+                    'xaxis': global_type_string,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 750
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = SPEC_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.__xfilter_ena = False
                     self.__yfilter_ena = False
                 def getSubplots(self):
                     ncol = 3
                     nrow = int(numpy.ceil(self.nplots/3.0))
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None,
                         vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA',
                         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, realtime=False,
                         xaxis="frequency"):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     #SEPARAR EN DOS PLOTS
                     nParam = dataOut.data_param.shape[1] - 3
                     utctime = dataOut.data_param[0,0]
                     tmet = dataOut.data_param[:,1].astype(int)
                     hmet = dataOut.data_param[:,2].astype(int)
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = numpy.zeros((nParam, y.size, x.size - 1))
                     z[:,:] = numpy.nan
                     z[:,hmet,tmet] = dataOut.data_param[:,3:].T
                     z[0,:,:] = 10*numpy.log10(z[0,:,:])
                     xlabel = "Time (s)"
                     ylabel = "Range (km)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     if not self.isConfig:
                         nplots = nParam
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin is None: xmin = numpy.nanmin(x)
                         if xmax is None: xmax = numpy.nanmax(x)
                         if ymin is None: ymin = numpy.nanmin(y)
                         if ymax is None: ymax = numpy.nanmax(y)
                         if SNRmin is None: SNRmin = numpy.nanmin(z[0,:])
                         if SNRmax is None: SNRmax = numpy.nanmax(z[0,:])
                         if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:]))
                         if vmin is None: vmin = -vmax
                         if wmin is None: wmin = 0
                         if wmax is None: wmax = 50
                         pairsList = dataOut.groupList
                         self.nPairs = len(dataOut.groupList)
                         zminList = [SNRmin, vmin, cmin] + [pmin]*self.nPairs
                         zmaxList = [SNRmax, vmax, cmax] + [pmax]*self.nPairs
                         titleList = ["SNR","Radial Velocity","Coherence"]
                         cmapList = ["jet","RdBu_r","jet"]
                         for i in range(self.nPairs):
                             strAux1 = "Phase Difference "+ str(pairsList[i][0]) + str(pairsList[i][1])
                             titleList = titleList + [strAux1]
                             cmapList = cmapList + ["RdBu_r"]
                         self.zminList = zminList
                         self.zmaxList = zmaxList
                         self.cmapList = cmapList
                         self.titleList = titleList
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     for i in range(nParam):
                         title = self.titleList[i] + ": " +str_datetime
                         axes = self.axesList[i]
                         axes.pcolor(x, y, z[i,:].T,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='')
                     self.draw()
                     if figfile == None:
                         str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         name = str_datetime
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
                         figfile = self.getFilename(name)
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class NSMeteorDetection2Plot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'nsm'
                 zminList = None
                 zmaxList = None
                 cmapList = None
                 titleList = None
                 nPairs = None
                 nChannels = None
                 nParam = None
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'SNRmin': global_type_float,
+                    'SNRmax': global_type_float,
+                    'vmin': global_type_float,
+                    'vmax': global_type_float,
+                    'wmin': global_type_float,
+                    'wmax': global_type_float,
+                    'mode': global_type_string,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_string,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                    'realtime': global_type_boolean,
+                    'xaxis': global_type_string,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 750
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = SPEC_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.__xfilter_ena = False
                     self.__yfilter_ena = False
                 def getSubplots(self):
                     ncol = 3
                     nrow = int(numpy.ceil(self.nplots/3.0))
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show=True):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, SNRmin=None, SNRmax=None,
                         vmin=None, vmax=None, wmin=None, wmax=None, mode = 'SA',
                         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, realtime=False,
                         xaxis="frequency"):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     #Rebuild matrix
                     utctime = dataOut.data_param[0,0]
                     cmet = dataOut.data_param[:,1].astype(int)
                     tmet = dataOut.data_param[:,2].astype(int)
                     hmet = dataOut.data_param[:,3].astype(int)
                     nParam = 3
                     nChan = len(dataOut.groupList)
                     x = dataOut.abscissaList
                     y = dataOut.heightList
                     z = numpy.full((nChan, nParam, y.size, x.size - 1),numpy.nan)
                     z[cmet,:,hmet,tmet] = dataOut.data_param[:,4:]
                     z[:,0,:,:] = 10*numpy.log10(z[:,0,:,:]) #logarithmic scale
                     z = numpy.reshape(z, (nChan*nParam, y.size, x.size-1))
                     xlabel = "Time (s)"
                     ylabel = "Range (km)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.ltctime)
                     if not self.isConfig:
                         nplots = nParam*nChan
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin is None: xmin = numpy.nanmin(x)
                         if xmax is None: xmax = numpy.nanmax(x)
                         if ymin is None: ymin = numpy.nanmin(y)
                         if ymax is None: ymax = numpy.nanmax(y)
                         if SNRmin is None: SNRmin = numpy.nanmin(z[0,:])
                         if SNRmax is None: SNRmax = numpy.nanmax(z[0,:])
                         if vmax is None: vmax = numpy.nanmax(numpy.abs(z[1,:]))
                         if vmin is None: vmin = -vmax
                         if wmin is None: wmin = 0
                         if wmax is None: wmax = 50
                         self.nChannels = nChan
                         zminList = []
                         zmaxList = []
                         titleList = []
                         cmapList = []
                         for i in range(self.nChannels):
                             strAux1 = "SNR Channel "+ str(i)
                             strAux2 = "Radial Velocity Channel "+ str(i)
                             strAux3 = "Spectral Width Channel "+ str(i)
                             titleList = titleList + [strAux1,strAux2,strAux3]
                             cmapList = cmapList + ["jet","RdBu_r","jet"]
                             zminList = zminList + [SNRmin,vmin,wmin]
                             zmaxList = zmaxList + [SNRmax,vmax,wmax]
                         self.zminList = zminList
                         self.zmaxList = zmaxList
                         self.cmapList = cmapList
                         self.titleList = titleList
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                     for i in range(self.nplots):
                         title = self.titleList[i] + ": " +str_datetime
                         axes = self.axesList[i]
                         axes.pcolor(x, y, z[i,:].T,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=self.zminList[i], zmax=self.zmaxList[i],
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=self.cmapList[i],ticksize=9, cblabel='')
                     self.draw()
                     if figfile == None:
                         str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         name = str_datetime
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
                         figfile = self.getFilename(name)
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)

schainpy/model/graphics/jroplot_spectra.py +121 0

             '''
             Created on Jul 9, 2014
             @author: roj-idl71
             '''
             import os
             import datetime
             import numpy
             from figure import Figure, isRealtime, isTimeInHourRange
             from plotting_codes import *
             class SpectraPlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spc'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 250
                     self.HEIGHT = 250
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = SPEC_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.__xfilter_ena = False
                     self.__yfilter_ena = False
                 def getSubplots(self):
                     ncol = int(numpy.sqrt(self.nplots)+0.9)
                     nrow = int(self.nplots*1./ncol + 0.9)
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 3
                         colspan = 2
                         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()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=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, realtime=False,
                         xaxis="velocity", **kwargs):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     colormap = kwargs.get('colormap','jet')
                     if realtime:
                         if not(isRealtime(utcdatatime = dataOut.utctime)):
                             print 'Skipping this plot function'
                             return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList" %channel
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     zdB = 10*numpy.log10(z)
                     avg = numpy.average(z, axis=1)
                     avgdB = 10*numpy.log10(avg)
                     noise = dataOut.getNoise()/factor
                     noisedB = 10*numpy.log10(noise)
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Spectra"
                     if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                         title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=showprofile,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         index = channelIndexList[i]
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime)
                         if len(dataOut.beam.codeList) != 0:
                             title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime)
                         axes = self.axesList[i*self.__nsubplots]
                         axes.pcolor(x, y, zdB[index,:,:],
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap,
                                     ticksize=9, cblabel='')
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[index,:], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                             noiseline = numpy.repeat(noisedB[index], len(y))
                             axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2)
                     self.draw()
                     if figfile == None:
                         str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S")
                         name = str_datetime
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith)
                         figfile = self.getFilename(name)
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class CrossSpectraPlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTH = None
                 HEIGHT = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'cspc'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'pairsList': global_type_pairsList,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'coh_min': global_type_float,
+                    'coh_max': global_type_float,
+                    'phase_min': global_type_float,
+                    'phase_max': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'power_cmap': global_type_colormap,
+                    'coherence_cmap': global_type_colormap,
+                    'phase_cmap': global_type_colormap,
+                    'show': global_type_boolean,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                    'xaxis': global_type_string,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 4
                     self.counter_imagwr = 0
                     self.WIDTH = 250
                     self.HEIGHT = 250
                     self.WIDTHPROF = 0
                     self.HEIGHTPROF = 0
                     self.PLOT_CODE = CROSS_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                 def getSubplots(self):
                     ncol = 4
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=True)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", pairsList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         coh_min=None, coh_max=None, phase_min=None, phase_max=None,
                         save=False, figpath='./', figfile=None, ftp=False, wr_period=1,
                         power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0,
                         xaxis='frequency'):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList
                     else:
                         pairsIndexList = []
                         for pair in pairsList:
                             if pair not in dataOut.pairsList:
                                 raise ValueError, "Pair %s is not in dataOut.pairsList" %str(pair)
                             pairsIndexList.append(dataOut.pairsList.index(pair))
                     if not pairsIndexList:
                         return
                     if len(pairsIndexList) > 4:
                         pairsIndexList = pairsIndexList[0:4]
                     factor = dataOut.normFactor
                     x = dataOut.getVelRange(1)
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc[:,:,:]/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     noise = dataOut.noise/factor
                     zdB = 10*numpy.log10(z)
                     noisedB = 10*numpy.log10(noise)
                     if coh_min == None:
                         coh_min = 0.0
                     if coh_max == None:
                         coh_max = 1.0
                     if phase_min == None:
                         phase_min = -180
                     if phase_max == None:
                         phase_max = 180
                     #thisDatetime = dataOut.datatime
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Cross-Spectra: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
             #         xlabel = "Velocity (m/s)"
                     ylabel = "Range (Km)"
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange(1)/1000.
                         xlabel = "Frequency (kHz)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange(1)
                         xlabel = "Time (ms)"
                     else:
                         x = dataOut.getVelRange(1)
                         xlabel = "Velocity (m/s)"
                     if not self.isConfig:
                         nplots = len(pairsIndexList)
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    showprofile=False,
                                    show=show)
                         avg = numpy.abs(numpy.average(z, axis=1))
                         avgdB = 10*numpy.log10(avg)
                         if xmin == None: xmin = numpy.nanmin(x)
                         if xmax == None: xmax = numpy.nanmax(x)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         self.FTP_WEI = ftp_wei
                         self.EXP_CODE = exp_code
                         self.SUB_EXP_CODE = sub_exp_code
                         self.PLOT_POS = plot_pos
                         self.isConfig = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         chan_index0 = dataOut.channelList.index(pair[0])
                         chan_index1 = dataOut.channelList.index(pair[1])
                         str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S"))
                         title = "Ch%d: %4.2fdB: %s" %(pair[0], noisedB[chan_index0], str_datetime)
                         zdB = 10.*numpy.log10(dataOut.data_spc[chan_index0,:,:]/factor)
                         axes0 = self.axesList[i*self.__nsubplots]
                         axes0.pcolor(x, y, zdB,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=power_cmap, cblabel='')
                         title = "Ch%d: %4.2fdB: %s" %(pair[1], noisedB[chan_index1], str_datetime)
                         zdB = 10.*numpy.log10(dataOut.data_spc[chan_index1,:,:]/factor)
                         axes0 = self.axesList[i*self.__nsubplots+1]
                         axes0.pcolor(x, y, zdB,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=power_cmap, cblabel='')
                         coherenceComplex = dataOut.data_cspc[pairsIndexList[i],:,:]/numpy.sqrt(dataOut.data_spc[chan_index0,:,:]*dataOut.data_spc[chan_index1,:,:])
                         coherence = numpy.abs(coherenceComplex)
             #            phase = numpy.arctan(-1*coherenceComplex.imag/coherenceComplex.real)*180/numpy.pi
                         phase = numpy.arctan2(coherenceComplex.imag, coherenceComplex.real)*180/numpy.pi
                         title = "Coherence Ch%d * Ch%d" %(pair[0], pair[1])
                         axes0 = self.axesList[i*self.__nsubplots+2]
                         axes0.pcolor(x, y, coherence,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=coh_min, zmax=coh_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=coherence_cmap, cblabel='')
                         title = "Phase Ch%d * Ch%d" %(pair[0], pair[1])
                         axes0 = self.axesList[i*self.__nsubplots+3]
                         axes0.pcolor(x, y, phase,
                                     xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title,
                                     ticksize=9, colormap=phase_cmap, cblabel='')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class RTIPlot(Figure):
                 __isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'rti'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = None
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 180
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = RTI_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.tmin = None
                     self.tmax = None
                     self.xmin = None
                     self.xmax = None
                     self.figfile = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         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()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             if counter >= self.nplots:
                                 break
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                             counter += 1
                 def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         timerange=None,
                         save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, **kwargs):
                     """
                     Input:
                         dataOut         :
                         id        :
                         wintitle        :
                         channelList     :
                         showProfile     :
                         xmin            :    None,
                         xmax            :    None,
                         ymin            :    None,
                         ymax            :    None,
                         zmin            :    None,
                         zmax            :    None
                     """
                     colormap = kwargs.get('colormap', 'jet')
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     if hasattr(dataOut, 'normFactor'):
                         factor = dataOut.normFactor
                     else:
                         factor = 1
             #         factor = dataOut.normFactor
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
             #         z = dataOut.data_spc/factor
             #         z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
             #         avg = numpy.average(z, axis=1)
             #         avgdB = 10.*numpy.log10(avg)
                     avgdB = dataOut.getPower()
                     thisDatetime = dataOut.datatime
             #         thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " RTI" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     update_figfile = False
                     if dataOut.ltctime >= self.xmax:
                         self.counter_imagwr = wr_period
                         self.isConfig = False
                         update_figfile = True
                     if not self.isConfig:
                         nplots = len(channelIndexList)
                         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)
                         noise = dataOut.noise/factor
                         noisedB = 10*numpy.log10(noise)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3
                         if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3
                         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
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         index = channelIndexList[i]
                         title = "Channel %d: %s" %(dataOut.channelList[index], thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                         if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)):
                             title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith)
                         axes = self.axesList[i*self.__nsubplots]
                         zdB = avgdB[index].reshape((1,-1))
                         axes.pcolorbuffer(x, y, zdB,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', cbsize="1%", colormap=colormap)
                         if self.__showprofile:
                             axes = self.axesList[i*self.__nsubplots +1]
                             axes.pline(avgdB[index], y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='dB', ylabel='', title='',
                                     ytick_visible=False,
                                     grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime,
                               update_figfile=update_figfile)
             class CoherenceMap(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'cmap'
+                parameters = {
+                    'id': 'string',
+                    'wintitle': 'string',
+                    'pairsList': 'pairsLists',
+                    'showprofile': 'boolean',
+                    'xmin': 'float',
+                    'xmax': 'float',
+                    'ymin': 'float',
+                    'ymax': 'float',
+                    'zmin': 'float',
+                    'zmax': 'float',
+                    'timerange': 'float',
+                    'phase_min': 'float',
+                    'phase_max': 'float',
+                    'save': 'boolean',
+                    'figpath': 'string',
+                    'figfile': 'string',
+                    'ftp': 'boolean',
+                    'wr_period': 'int',
+                    'coherence_cmap': 'colormap',
+                    'phase_cmap': 'colormap',
+                    'show': 'boolean',
+                    'server': 'string',
+                    'folder': 'string',
+                    'username': 'string',
+                    'password': 'string',
+                    'ftp_wei': 'int',
+                    'exp_code': 'int',
+                    'sub_exp_code': 'int',
+                    'plot_pos': 'int',
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.timerange = 2*60*60
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.WIDTH = 800
                     self.HEIGHT = 180
                     self.WIDTHPROF = 120
                     self.HEIGHTPROF = 0
                     self.counter_imagwr = 0
                     self.PLOT_CODE = COH_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.counter_imagwr = 0
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = self.nplots*2
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, showprofile=True, show=True):
                     self.__showprofile = showprofile
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     if showprofile:
                         ncolspan = 7
                         colspan = 6
                         self.__nsubplots = 2
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH + self.WIDTHPROF,
                                       heightplot = self.HEIGHT + self.HEIGHTPROF,
                                       show=True)
                     nrow, ncol = self.getSubplots()
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                             if showprofile:
                                 self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1)
                 def run(self, dataOut, id, wintitle="", pairsList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None,
                         timerange=None, phase_min=None, phase_max=None,
                         save=False, figpath='./', figfile=None, ftp=False, wr_period=1,
                         coherence_cmap='jet', phase_cmap='RdBu_r', show=True,
                         server=None, folder=None, username=None, password=None,
                         ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
                     if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if pairsList == None:
                         pairsIndexList = dataOut.pairsIndexList
                     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]
                     if phase_min == None:
                         phase_min = -180
                     if phase_max == None:
                         phase_max = 180
                     x = dataOut.getTimeRange()
                     y = dataOut.getHeiRange()
                     thisDatetime = dataOut.datatime
                     title = wintitle + " CoherenceMap" #: %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Range (Km)"
                     update_figfile = False
                     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 = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if zmin == None: zmin = 0.
                         if zmax == None: zmax = 1.
                         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
                         update_figfile = True
                     self.setWinTitle(title)
                     for i in range(self.nplots):
                         pair = dataOut.pairsList[pairsIndexList[i]]
                         ccf = numpy.average(dataOut.data_cspc[pairsIndexList[i],:,:],axis=0)
                         powa = numpy.average(dataOut.data_spc[pair[0],:,:],axis=0)
                         powb = numpy.average(dataOut.data_spc[pair[1],:,:],axis=0)
                         avgcoherenceComplex = ccf/numpy.sqrt(powa*powb)
                         coherence = numpy.abs(avgcoherenceComplex)
                         z = coherence.reshape((1,-1))
                         counter = 0
                         title = "Coherence Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots*2]
                         axes.pcolorbuffer(x, y, z,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', colormap=coherence_cmap, cbsize="1%")
                         if self.__showprofile:
                             counter += 1
                             axes = self.axesList[i*self.__nsubplots*2 + counter]
                             axes.pline(coherence, y,
                                     xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax,
                                     xlabel='', ylabel='', title='', ticksize=7,
                                     ytick_visible=False, nxticks=5,
                                     grid='x')
                         counter += 1
                         phase = numpy.arctan2(avgcoherenceComplex.imag, avgcoherenceComplex.real)*180/numpy.pi
                         z = phase.reshape((1,-1))
                         title = "Phase Ch%d * Ch%d: %s" %(pair[0], pair[1], thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                         axes = self.axesList[i*self.__nsubplots*2 + counter]
                         axes.pcolorbuffer(x, y, z,
                                     xmin=self.xmin, xmax=self.xmax, ymin=ymin, ymax=ymax, zmin=phase_min, zmax=phase_max,
                                     xlabel=xlabel, ylabel=ylabel, title=title, rti=True, XAxisAsTime=True,
                                     ticksize=9, cblabel='', colormap=phase_cmap, cbsize="1%")
                         if self.__showprofile:
                             counter += 1
                             axes = self.axesList[i*self.__nsubplots*2 + counter]
                             axes.pline(phase, y,
                                     xmin=phase_min, xmax=phase_max, ymin=ymin, ymax=ymax,
                                     xlabel='', ylabel='', title='', ticksize=7,
                                     ytick_visible=False, nxticks=4,
                                     grid='x')
                     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)
             class PowerProfilePlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spcprofile'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = POWER_CODE
                     self.WIDTH = 300
                     self.HEIGHT = 500
                     self.counter_imagwr = 0
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH,
                                       heightplot = self.HEIGHT,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True,
                         ftp=False, wr_period=1, server=None,
                         folder=None, username=None, password=None):
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     y = dataOut.getHeiRange()
                     #for voltage
                     if dataOut.type == 'Voltage':
                         x = dataOut.data[channelIndexList,:] * numpy.conjugate(dataOut.data[channelIndexList,:])
                         x = x.real
                         x = numpy.where(numpy.isfinite(x), x, numpy.NAN)
                     #for spectra
                     if dataOut.type == 'Spectra':
                         x = dataOut.data_spc[channelIndexList,:,:]/factor
                         x = numpy.where(numpy.isfinite(x), x, numpy.NAN)
                         x = numpy.average(x, axis=1)
                     xdB = 10*numpy.log10(x)
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Power Profile %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = "dB"
                     ylabel = "Range (Km)"
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if ymin == None: ymin = numpy.nanmin(y)
                         if ymax == None: ymax = numpy.nanmax(y)
                         if xmin == None: xmin = numpy.nanmin(xdB)*0.9
                         if xmax == None: xmax = numpy.nanmax(xdB)*1.1
                         self.isConfig = True
                     self.setWinTitle(title)
                     title = "Power Profile: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     axes = self.axesList[0]
                     legendlabels = ["channel %d"%x for x in channelList]
                     axes.pmultiline(xdB, y,
                             xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                             xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels,
                             ytick_visible=True, nxticks=5,
                             grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class SpectraCutPlot(Figure):
                 isConfig = None
                 __nsubplots = None
                 WIDTHPROF = None
                 HEIGHTPROF = None
                 PREFIX = 'spc_cut'
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     self.isConfig = False
                     self.__nsubplots = 1
                     self.PLOT_CODE = POWER_CODE
                     self.WIDTH = 700
                     self.HEIGHT = 500
                     self.counter_imagwr = 0
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def setup(self, id, nplots, wintitle, show):
                     self.nplots = nplots
                     ncolspan = 1
                     colspan = 1
                     self.createFigure(id = id,
                                       wintitle = wintitle,
                                       widthplot = self.WIDTH,
                                       heightplot = self.HEIGHT,
                                       show=show)
                     nrow, ncol = self.getSubplots()
                     counter = 0
                     for y in range(nrow):
                         for x in range(ncol):
                             self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1)
                 def run(self, dataOut, id, wintitle="", channelList=None,
                         xmin=None, xmax=None, ymin=None, ymax=None,
                         save=False, figpath='./', figfile=None, show=True,
                         ftp=False, wr_period=1, server=None,
                         folder=None, username=None, password=None,
                         xaxis="frequency"):
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     factor = dataOut.normFactor
                     y = dataOut.getHeiRange()
                     z = dataOut.data_spc/factor
                     z = numpy.where(numpy.isfinite(z), z, numpy.NAN)
                     hei_index = numpy.arange(25)*3 + 20
                     if xaxis == "frequency":
                         x = dataOut.getFreqRange()/1000.
                         zdB = 10*numpy.log10(z[0,:,hei_index])
                         xlabel = "Frequency (kHz)"
                         ylabel = "Power (dB)"
                     elif xaxis == "time":
                         x = dataOut.getAcfRange()
                         zdB = z[0,:,hei_index]
                         xlabel = "Time (ms)"
                         ylabel = "ACF"
                     else:
                         x = dataOut.getVelRange()
                         zdB = 10*numpy.log10(z[0,:,hei_index])
                         xlabel = "Velocity (m/s)"
                         ylabel = "Power (dB)"
                     thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0])
                     title = wintitle + " Range Cuts %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     if not self.isConfig:
                         nplots = 1
                         self.setup(id=id,
                                    nplots=nplots,
                                    wintitle=wintitle,
                                    show=show)
                         if xmin == None: xmin = numpy.nanmin(x)*0.9
                         if xmax == None: xmax = numpy.nanmax(x)*1.1
                         if ymin == None: ymin = numpy.nanmin(zdB)
                         if ymax == None: ymax = numpy.nanmax(zdB)
                         self.isConfig = True
                     self.setWinTitle(title)
                     title = "Spectra Cuts: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S"))
                     axes = self.axesList[0]
                     legendlabels = ["Range = %dKm" %y[i] for i in hei_index]
                     axes.pmultilineyaxis( x, zdB,
                             xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax,
                             xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels,
                             ytick_visible=True, nxticks=5,
                             grid='x')
                     self.draw()
                     self.save(figpath=figpath,
                               figfile=figfile,
                               save=save,
                               ftp=ftp,
                               wr_period=wr_period,
                               thisDatetime=thisDatetime)
             class Noise(Figure):
                 isConfig = None
                 __nsubplots = None
                 PREFIX = 'noise'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'channelList': global_type_list,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'timerange': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     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 = NOISE_CODE
                     self.FTP_WEI = None
                     self.EXP_CODE = None
                     self.SUB_EXP_CODE = None
                     self.PLOT_POS = None
                     self.figfile = None
                     self.xmin = None
                     self.xmax = None
                 def getSubplots(self):
                     ncol = 1
                     nrow = 1
                     return nrow, ncol
                 def openfile(self, filename):
                     dirname = os.path.dirname(filename)
                     if not os.path.exists(dirname):
                         os.mkdir(dirname)
                     f = open(filename,'w+')
                     f.write('\n\n')
                     f.write('JICAMARCA RADIO OBSERVATORY - Noise \n')
                     f.write('DD MM YYYY  HH MM SS   Channel0    Channel1    Channel2    Channel3\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)
                     data_msg = ''
                     for i in range(len(data)):
                         data_msg += str(data[i]) + '  '
                     f.write(day+' '+month+' '+year+'  '+hour+' '+minute+' '+second+'   ' + data_msg + '\n')
                     f.close()
                 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 run(self, dataOut, id, wintitle="", channelList=None, showprofile='True',
                         xmin=None, xmax=None, ymin=None, ymax=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 not isTimeInHourRange(dataOut.datatime, xmin, xmax):
                         return
                     if channelList == None:
                         channelIndexList = dataOut.channelIndexList
                         channelList = dataOut.channelList
                     else:
                         channelIndexList = []
                         for channel in channelList:
                             if channel not in dataOut.channelList:
                                 raise ValueError, "Channel %d is not in dataOut.channelList"
                             channelIndexList.append(dataOut.channelList.index(channel))
                     x = dataOut.getTimeRange()
                     #y = dataOut.getHeiRange()
                     factor = dataOut.normFactor
                     noise = dataOut.noise[channelIndexList]/factor
                     noisedB = 10*numpy.log10(noise)
                     thisDatetime = dataOut.datatime
                     title = wintitle + " Noise" # : %s" %(thisDatetime.strftime("%d-%b-%Y"))
                     xlabel = ""
                     ylabel = "Intensity (dB)"
                     update_figfile = False
                     if not self.isConfig:
                         nplots = 1
                         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 = numpy.floor(numpy.nanmin(noisedB)) - 10.0
                         if ymax == None: ymax = numpy.nanmax(noisedB) + 10.0
                         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)
                         noise_file = os.path.join(path,'%s.txt'%self.name)
                         self.filename_noise = os.path.join(figpath,noise_file)
                     self.setWinTitle(title)
                     title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S"))
                     legendlabels = ["channel %d"%(idchannel) for idchannel in channelList]
                     axes = self.axesList[0]
                     self.xdata = numpy.hstack((self.xdata, x[0:1]))
                     if len(self.ydata)==0:
                         self.ydata = noisedB.reshape(-1,1)
                     else:
                         self.ydata = numpy.hstack((self.ydata, noisedB.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)
                     #store data beacon phase
                     if save:
                         self.save_data(self.filename_noise, noisedB, thisDatetime)
             class BeaconPhase(Figure):
                 __isConfig = None
                 __nsubplots = None
                 PREFIX = 'beacon_phase'
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'pairsList': global_type_pairsList,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'hmin': global_type_float,
+                    'hmax': global_type_float,
+                    'timerange': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'show': global_type_boolean,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Figure.__init__(self, **kwargs)
                     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 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 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()
                     #y = dataOut.getHeiRange()
                     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
                         #print "Phase %d%d" %(pair[0], pair[1])
                         #print phase[dataOut.beacon_heiIndexList]
                         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)

schainpy/model/io/jroIO_heispectra.py +7 -3

             '''
             Created on Jul 3, 2014
             @author: roj-idl71
             '''
             import os, sys
             import time, datetime
             import numpy
             import fnmatch
             import glob
             from time import sleep
             try:
                 import pyfits
             except ImportError, e:
                 print "Fits data cannot be used. Install pyfits module"
             from xml.etree.ElementTree import ElementTree
             from jroIO_base import isRadarFolder, isNumber
             from schainpy.model.data.jrodata import Fits
             from schainpy.model.proc.jroproc_base import Operation, ProcessingUnit
             class PyFits(object):
                 name=None
                 format=None
                 array =None
                 data =None
                 thdulist=None
                 prihdr=None
                 hdu=None
                 def __init__(self):
                     pass
                 def setColF(self,name,format,array):
                     self.name=name
                     self.format=format
                     self.array=array
                     a1=numpy.array([self.array],dtype=numpy.float32)
                     self.col1 = pyfits.Column(name=self.name, format=self.format, array=a1)
                     return self.col1
             #    def setColP(self,name,format,data):
             #        self.name=name
             #        self.format=format
             #        self.data=data
             #        a2=numpy.array([self.data],dtype=numpy.float32)
             #        self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2)
             #        return self.col2
                 def writeData(self,name,format,data):
                     self.name=name
                     self.format=format
                     self.data=data
                     a2=numpy.array([self.data],dtype=numpy.float32)
                     self.col2 = pyfits.Column(name=self.name, format=self.format, array=a2)
                     return self.col2
                 def cFImage(self,idblock,year,month,day,hour,minute,second):
                     self.hdu= pyfits.PrimaryHDU(idblock)
                     self.hdu.header.set("Year",year)
                     self.hdu.header.set("Month",month)
                     self.hdu.header.set("Day",day)
                     self.hdu.header.set("Hour",hour)
                     self.hdu.header.set("Minute",minute)
                     self.hdu.header.set("Second",second)
                     return self.hdu
                 def Ctable(self,colList):
                     self.cols=pyfits.ColDefs(colList)
                     self.tbhdu = pyfits.new_table(self.cols)
                     return self.tbhdu
                 def CFile(self,hdu,tbhdu):
                     self.thdulist=pyfits.HDUList([hdu,tbhdu])
                 def wFile(self,filename):
                     if os.path.isfile(filename):
                         os.remove(filename)
                     self.thdulist.writeto(filename)
             class ParameterConf:
                 ELEMENTNAME = 'Parameter'
                 def __init__(self):
                     self.name = ''
                     self.value = ''
                 def readXml(self, parmElement):
                     self.name = parmElement.get('name')
                     self.value = parmElement.get('value')
                 def getElementName(self):
                     return self.ELEMENTNAME
             class Metadata(object):
                 def __init__(self, filename):
                     self.parmConfObjList = []
                     self.readXml(filename)
                 def readXml(self, filename):
                     self.projectElement = None
                     self.procUnitConfObjDict = {}
                     self.projectElement = ElementTree().parse(filename)
                     self.project = self.projectElement.tag
                     parmElementList = self.projectElement.getiterator(ParameterConf().getElementName())
                     for parmElement in parmElementList:
                         parmConfObj = ParameterConf()
                         parmConfObj.readXml(parmElement)
                         self.parmConfObjList.append(parmConfObj)
             class FitsWriter(Operation):
+                parameters = {
+                    'path': global_type_string,
+                    'dataBlocksPerFile': global_type_integer,
+                    'metadatafile': global_type_string,
+                }
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.isConfig = False
                     self.dataBlocksPerFile = None
                     self.blockIndex = 0
                     self.flagIsNewFile = 1
                     self.fitsObj = None
                     self.optchar = 'P'
                     self.ext = '.fits'
                     self.setFile = 0
                 def setFitsHeader(self, dataOut, metadatafile=None):
                     header_data = pyfits.PrimaryHDU()
                     header_data.header['EXPNAME'] = "RADAR DATA"
                     header_data.header['DATATYPE'] = "SPECTRA"
                     header_data.header['COMMENT'] = ""
                     if metadatafile:
                         metadata4fits = Metadata(metadatafile)
                         for parameter in metadata4fits.parmConfObjList:
                             parm_name = parameter.name
                             parm_value = parameter.value
                             header_data.header[parm_name] = parm_value
                     header_data.header['DATETIME'] = time.strftime("%b %d %Y %H:%M:%S", dataOut.datatime.timetuple())
                     header_data.header['CHANNELLIST'] = str(dataOut.channelList)
                     header_data.header['NCHANNELS'] = dataOut.nChannels
                     #header_data.header['HEIGHTS'] = dataOut.heightList
                     header_data.header['NHEIGHTS'] = dataOut.nHeights
                     header_data.header['IPPSECONDS'] = dataOut.ippSeconds
                     header_data.header['NCOHINT'] = dataOut.nCohInt
                     header_data.header['NINCOHINT'] = dataOut.nIncohInt
                     header_data.header['TIMEZONE'] = dataOut.timeZone
                     header_data.header['NBLOCK'] = self.blockIndex
                     header_data.writeto(self.filename)
                     self.addExtension(dataOut.heightList,'HEIGHTLIST')
                 def setup(self, dataOut, path, dataBlocksPerFile=100, metadatafile=None):
                     self.path = path
                     self.dataOut = dataOut
                     self.metadatafile = metadatafile
                     self.dataBlocksPerFile = dataBlocksPerFile
                 def open(self):
                     self.fitsObj = pyfits.open(self.filename, mode='update')
                 def addExtension(self, data, tagname):
                     self.open()
                     extension = pyfits.ImageHDU(data=data, name=tagname)
                     #extension.header['TAG'] = tagname
                     self.fitsObj.append(extension)
                     self.write()
                 def addData(self, data):
                     self.open()
                     extension = pyfits.ImageHDU(data=data, name=self.fitsObj[0].header['DATATYPE'])
                     extension.header['UTCTIME'] = self.dataOut.utctime
                     self.fitsObj.append(extension)
                     self.blockIndex += 1
                     self.fitsObj[0].header['NBLOCK'] = self.blockIndex
                     self.write()
                 def write(self):
                     self.fitsObj.flush(verbose=True)
                     self.fitsObj.close()
                 def setNextFile(self):
                     ext = self.ext
                     path = self.path
                     timeTuple = time.localtime( self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         self.setFile = -1 #inicializo mi contador de seteo
                     else:
                         filesList = os.listdir( fullpath )
                         if len( filesList ) > 0:
                             filesList = sorted( filesList, key=str.lower )
                             filen = filesList[-1]
                             if isNumber( filen[8:11] ):
                                 self.setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 self.setFile = -1
                         else:
                             self.setFile = -1 #inicializo mi contador de seteo
                     setFile = self.setFile
                     setFile += 1
                     thisFile = '%s%4.4d%3.3d%3.3d%s' % (self.optchar,
                                                     timeTuple.tm_year,
                                                     timeTuple.tm_yday,
                                                     setFile,
                                                     ext )
                     filename = os.path.join( path, subfolder, thisFile )
                     self.blockIndex = 0
                     self.filename = filename
                     self.setFile = setFile
                     self.flagIsNewFile = 1
                     print 'Writing the file: %s'%self.filename
                     self.setFitsHeader(self.dataOut, self.metadatafile)
                     return 1
                 def writeBlock(self):
                     self.addData(self.dataOut.data_spc)
                     self.flagIsNewFile = 0
                 def __setNewBlock(self):
                     if self.flagIsNewFile:
                         return 1
                     if self.blockIndex < self.dataBlocksPerFile:
                         return 1
                     if not( self.setNextFile() ):
                         return 0
                     return 1
                 def writeNextBlock(self):
                     if not( self.__setNewBlock() ):
                         return 0
                     self.writeBlock()
                     return 1
                 def putData(self):
                     if self.flagIsNewFile:
                         self.setNextFile()
                     self.writeNextBlock()
-                def run(self, dataOut, **kwargs):
+                def run(self, dataOut, path, dataBlocksPerFile=100, metadatafile=None, **kwargs):
                     if not(self.isConfig):
-                        self.setup(dataOut, **kwargs)
+                        self.setup(dataOut, path, dataBlocksPerFile=dataBlocksPerFile, metadatafile=metadatafile, **kwargs)
                         self.isConfig = True
                     self.putData()
             class FitsReader(ProcessingUnit):
             #     __TIMEZONE = time.timezone
                 expName = None
                 datetimestr = None
                 utc = None
                 nChannels = None
                 nSamples = None
                 dataBlocksPerFile = None
                 comments = None
                 lastUTTime = None
                 header_dict = None
                 data = None
                 data_header_dict = None
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
                     self.isConfig = False
                     self.ext = '.fits'
                     self.setFile = 0
                     self.flagNoMoreFiles = 0
                     self.flagIsNewFile = 1
                     self.flagDiscontinuousBlock = None
                     self.fileIndex = None
                     self.filename = None
                     self.fileSize = None
                     self.fitsObj = None
                     self.timeZone = None
                     self.nReadBlocks = 0
                     self.nTotalBlocks = 0
                     self.dataOut = self.createObjByDefault()
                     self.maxTimeStep = 10# deberia ser definido por el usuario usando el metodo setup()
                     self.blockIndex = 1
                 def createObjByDefault(self):
                     dataObj = Fits()
                     return dataObj
                 def isFileinThisTime(self, filename, startTime, endTime, useLocalTime=False):
                     try:
                         fitsObj = pyfits.open(filename,'readonly')
                     except:
                         print "File %s can't be opened" %(filename)
                         return None
                     header = fitsObj[0].header
                     struct_time = time.strptime(header['DATETIME'], "%b %d %Y %H:%M:%S")
                     utc = time.mktime(struct_time) - time.timezone #TIMEZONE debe ser un parametro del header FITS
                     ltc = utc
                     if useLocalTime:
                         ltc -= time.timezone
                     thisDatetime = datetime.datetime.utcfromtimestamp(ltc)
                     thisTime = thisDatetime.time()
                     if not ((startTime <= thisTime) and (endTime > thisTime)):
                         return None
                     return thisDatetime
                 def __setNextFileOnline(self):
                     raise NotImplementedError
                 def __setNextFileOffline(self):
                     idFile = self.fileIndex
                     while (True):
                         idFile += 1
                         if not(idFile < len(self.filenameList)):
                             self.flagNoMoreFiles = 1
                             print "No more Files"
                             return 0
                         filename = self.filenameList[idFile]
             #            if not(self.__verifyFile(filename)):
             #                continue
                         fileSize = os.path.getsize(filename)
                         fitsObj = pyfits.open(filename,'readonly')
                         break
                     self.flagIsNewFile = 1
                     self.fileIndex = idFile
                     self.filename = filename
                     self.fileSize = fileSize
                     self.fitsObj = fitsObj
                     self.blockIndex = 0
                     print "Setting the file: %s"%self.filename
                     return 1
                 def __setValuesFromHeader(self):
                     self.dataOut.header = self.header_dict
                     self.dataOut.expName = self.expName
                     self.dataOut.timeZone = self.timeZone
                     self.dataOut.dataBlocksPerFile = self.dataBlocksPerFile
                     self.dataOut.comments = self.comments
             #         self.dataOut.timeInterval = self.timeInterval
                     self.dataOut.channelList = self.channelList
                     self.dataOut.heightList = self.heightList
                     self.dataOut.nCohInt = self.nCohInt
                     self.dataOut.nIncohInt = self.nIncohInt
                     self.dataOut.ippSeconds = self.ippSeconds
                 def readHeader(self):
                     headerObj = self.fitsObj[0]
                     self.header_dict = headerObj.header
                     if 'EXPNAME' in headerObj.header.keys():
                         self.expName = headerObj.header['EXPNAME']
                     if 'DATATYPE' in headerObj.header.keys():
                         self.dataType = headerObj.header['DATATYPE']
                     self.datetimestr = headerObj.header['DATETIME']
                     channelList = headerObj.header['CHANNELLIST']
                     channelList = channelList.split('[')
                     channelList = channelList[1].split(']')
                     channelList = channelList[0].split(',')
                     channelList = [int(ch) for ch in channelList]
                     self.channelList = channelList
                     self.nChannels = headerObj.header['NCHANNELS']
                     self.nHeights = headerObj.header['NHEIGHTS']
                     self.ippSeconds = headerObj.header['IPPSECONDS']
                     self.nCohInt = headerObj.header['NCOHINT']
                     self.nIncohInt = headerObj.header['NINCOHINT']
                     self.dataBlocksPerFile = headerObj.header['NBLOCK']
                     self.timeZone = headerObj.header['TIMEZONE']
             #         self.timeInterval = self.ippSeconds * self.nCohInt * self.nIncohInt
                     if 'COMMENT' in headerObj.header.keys():
                         self.comments = headerObj.header['COMMENT']
                     self.readHeightList()
                 def readHeightList(self):
                     self.blockIndex = self.blockIndex + 1
                     obj = self.fitsObj[self.blockIndex]
                     self.heightList = obj.data
                     self.blockIndex = self.blockIndex + 1
                 def readExtension(self):
                     obj = self.fitsObj[self.blockIndex]
                     self.heightList = obj.data
                     self.blockIndex = self.blockIndex + 1
                 def setNextFile(self):
                     if self.online:
                         newFile = self.__setNextFileOnline()
                     else:
                         newFile = self.__setNextFileOffline()
                     if not(newFile):
                         return 0
                     self.readHeader()
                     self.__setValuesFromHeader()
                     self.nReadBlocks = 0
             #         self.blockIndex = 1
                     return 1
                 def __searchFilesOffLine(self,
                                         path,
                                         startDate,
                                         endDate,
                                         startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),
                                         set=None,
                                         expLabel='',
                                         ext='.fits',
                                         walk=True):
                     pathList = []
                     if not walk:
                         pathList.append(path)
                     else:
                         dirList = []
                         for thisPath in os.listdir(path):
                             if not os.path.isdir(os.path.join(path,thisPath)):
                                 continue
                             if not isRadarFolder(thisPath):
                                 continue
                             dirList.append(thisPath)
                         if not(dirList):
                             return None, None
                         thisDate = startDate
                         while(thisDate <= endDate):
                             year = thisDate.timetuple().tm_year
                             doy = thisDate.timetuple().tm_yday
                             matchlist = fnmatch.filter(dirList, '?' + '%4.4d%3.3d' % (year,doy) + '*')
                             if len(matchlist) == 0:
                                 thisDate += datetime.timedelta(1)
                                 continue
                             for match in matchlist:
                                 pathList.append(os.path.join(path,match,expLabel))
                             thisDate += datetime.timedelta(1)
                     if pathList == []:
                         print "Any folder was found for the date range: %s-%s" %(startDate, endDate)
                         return None, None
                     print "%d folder(s) was(were) found for the date range: %s - %s" %(len(pathList), startDate, endDate)
                     filenameList = []
                     datetimeList = []
                     for i in range(len(pathList)):
                         thisPath = pathList[i]
                         fileList = glob.glob1(thisPath, "*%s" %ext)
                         fileList.sort()
                         for thisFile in fileList:
                             filename = os.path.join(thisPath,thisFile)
                             thisDatetime = self.isFileinThisTime(filename, startTime, endTime)
                             if not(thisDatetime):
                                 continue
                             filenameList.append(filename)
                             datetimeList.append(thisDatetime)
                     if not(filenameList):
                         print "Any file was found for the time range %s - %s" %(startTime, endTime)
                         return None, None
                     print "%d file(s) was(were) found for the time range: %s - %s" %(len(filenameList), startTime, endTime)
                     print
                     for i in range(len(filenameList)):
                         print "%s -> [%s]" %(filenameList[i], datetimeList[i].ctime())
                     self.filenameList = filenameList
                     self.datetimeList = datetimeList
                     return pathList, filenameList
                 def setup(self, path=None,
                             startDate=None,
                             endDate=None,
                             startTime=datetime.time(0,0,0),
                             endTime=datetime.time(23,59,59),
                             set=0,
                             expLabel = "",
                             ext = None,
                             online = False,
                             delay = 60,
                             walk = True):
                     if path == None:
                         raise ValueError, "The path is not valid"
                     if ext == None:
                         ext = self.ext
                     if not(online):
                         print "Searching files in offline mode ..."
                         pathList, filenameList = self.__searchFilesOffLine(path, startDate=startDate, endDate=endDate,
                                                                            startTime=startTime, endTime=endTime,
                                                                            set=set, expLabel=expLabel, ext=ext,
                                                                            walk=walk)
                         if not(pathList):
                             print "No *%s files into the folder %s \nfor the range: %s - %s"%(ext, path,
                                                                     datetime.datetime.combine(startDate,startTime).ctime(),
                                                                     datetime.datetime.combine(endDate,endTime).ctime())
                             sys.exit(-1)
                         self.fileIndex = -1
                         self.pathList = pathList
                         self.filenameList = filenameList
                     self.online = online
                     self.delay = delay
                     ext = ext.lower()
                     self.ext = ext
                     if not(self.setNextFile()):
                         if (startDate!=None) and (endDate!=None):
                             print "No files in range: %s - %s" %(datetime.datetime.combine(startDate,startTime).ctime(), datetime.datetime.combine(endDate,endTime).ctime())
                         elif startDate != None:
                             print "No files in range: %s" %(datetime.datetime.combine(startDate,startTime).ctime())
                         else:
                             print "No files"
                         sys.exit(-1)
                 def readBlock(self):
                     dataObj = self.fitsObj[self.blockIndex]
                     self.data = dataObj.data
                     self.data_header_dict = dataObj.header
                     self.utc = self.data_header_dict['UTCTIME']
                     self.flagIsNewFile = 0
                     self.blockIndex += 1
                     self.nTotalBlocks += 1
                     self.nReadBlocks += 1
                     return 1
                 def __jumpToLastBlock(self):
                     raise NotImplementedError
                 def __waitNewBlock(self):
                     """
                     Return 1 si se encontro un nuevo bloque de datos, 0 de otra forma.
                     Si el modo de lectura es OffLine siempre retorn 0
                     """
                     if not self.online:
                         return 0
                     if (self.nReadBlocks >= self.dataBlocksPerFile):
                         return 0
                     currentPointer = self.fp.tell()
                     neededSize = self.processingHeaderObj.blockSize + self.basicHeaderSize
                     for nTries in range( self.nTries ):
                         self.fp.close()
                         self.fp = open( self.filename, 'rb' )
                         self.fp.seek( currentPointer )
                         self.fileSize = os.path.getsize( self.filename )
                         currentSize = self.fileSize - currentPointer
                         if ( currentSize >= neededSize ):
                             self.__rdBasicHeader()
                             return 1
                         print "\tWaiting %0.2f seconds for the next block, try %03d ..." % (self.delay, nTries+1)
                         sleep( self.delay )
                     return 0
                 def __setNewBlock(self):
                     if self.online:
                         self.__jumpToLastBlock()
                     if self.flagIsNewFile:
                         return 1
                     self.lastUTTime = self.utc
                     if self.online:
                         if self.__waitNewBlock():
                             return 1
                     if self.nReadBlocks < self.dataBlocksPerFile:
                         return 1
                     if not(self.setNextFile()):
                         return 0
                     deltaTime = self.utc - self.lastUTTime
                     self.flagDiscontinuousBlock = 0
                     if deltaTime > self.maxTimeStep:
                         self.flagDiscontinuousBlock = 1
                     return 1
                 def readNextBlock(self):
                     if not(self.__setNewBlock()):
                         return 0
                     if not(self.readBlock()):
                         return 0
                     return 1
                 def printInfo(self):
                     pass
                 def getData(self):
                     if self.flagNoMoreFiles:
                         self.dataOut.flagNoData = True
                         print 'Process finished'
                         return 0
                     self.flagDiscontinuousBlock = 0
                     self.flagIsNewBlock = 0
                     if not(self.readNextBlock()):
                         return 0
                     if self.data is None:
                         self.dataOut.flagNoData = True
                         return 0
                     self.dataOut.data = self.data
                     self.dataOut.data_header = self.data_header_dict
                     self.dataOut.utctime = self.utc
             #         self.dataOut.header = self.header_dict
             #         self.dataOut.expName = self.expName
             #         self.dataOut.nChannels = self.nChannels
             #         self.dataOut.timeZone = self.timeZone
             #         self.dataOut.dataBlocksPerFile = self.dataBlocksPerFile
             #         self.dataOut.comments = self.comments
             # #         self.dataOut.timeInterval = self.timeInterval
             #         self.dataOut.channelList = self.channelList
             #         self.dataOut.heightList = self.heightList
                     self.dataOut.flagNoData = False
                     return self.dataOut.data
                 def run(self, **kwargs):
                     if not(self.isConfig):
                         self.setup(**kwargs)
                         self.isConfig = True
                     self.getData()
             class SpectraHeisWriter(Operation):
             #    set = None
                 setFile = None
                 idblock = None
                 doypath = None
                 subfolder = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.wrObj = PyFits()
             #        self.dataOut = dataOut
                     self.nTotalBlocks=0
             #        self.set = None
                     self.setFile = None
                     self.idblock = 0
                     self.wrpath = None
                     self.doypath = None
                     self.subfolder = None
                     self.isConfig = False
                 def isNumber(str):
                     """
                     Chequea si el conjunto de caracteres que componen un string puede ser convertidos a un numero.
                     Excepciones:
                     Si un determinado string no puede ser convertido a numero
                     Input:
                     str, string al cual se le analiza para determinar si convertible a un numero o no
                     Return:
                     True    :    si el string es uno numerico
                     False   :    no es un string numerico
                     """
                     try:
                         float( str )
                         return True
                     except:
                         return False
                 def setup(self, dataOut, wrpath):
                     if not(os.path.exists(wrpath)):
                         os.mkdir(wrpath)
                     self.wrpath = wrpath
             #        self.setFile = 0
                     self.dataOut = dataOut
                 def putData(self):
                     name= time.localtime( self.dataOut.utctime)
                     ext=".fits"
                     if self.doypath == None:
                        self.subfolder = 'F%4.4d%3.3d_%d' % (name.tm_year,name.tm_yday,time.mktime(datetime.datetime.now().timetuple()))
                        self.doypath = os.path.join( self.wrpath, self.subfolder )
                        os.mkdir(self.doypath)
                     if self.setFile == None:
             #           self.set = self.dataOut.set
                        self.setFile = 0
             #        if self.set != self.dataOut.set:
             ##            self.set = self.dataOut.set
             #            self.setFile = 0
                     #make the filename
                     thisFile = 'D%4.4d%3.3d_%3.3d%s' % (name.tm_year,name.tm_yday,self.setFile,ext)
                     filename = os.path.join(self.wrpath,self.subfolder, thisFile)
                     idblock = numpy.array([self.idblock],dtype="int64")
                     header=self.wrObj.cFImage(idblock=idblock,
                                             year=time.gmtime(self.dataOut.utctime).tm_year,
                                             month=time.gmtime(self.dataOut.utctime).tm_mon,
                                             day=time.gmtime(self.dataOut.utctime).tm_mday,
                                             hour=time.gmtime(self.dataOut.utctime).tm_hour,
                                             minute=time.gmtime(self.dataOut.utctime).tm_min,
                                             second=time.gmtime(self.dataOut.utctime).tm_sec)
                     c=3E8
                     deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     freq=numpy.arange(-1*self.dataOut.nHeights/2.,self.dataOut.nHeights/2.)*(c/(2*deltaHeight*1000))
                     colList = []
                     colFreq=self.wrObj.setColF(name="freq", format=str(self.dataOut.nFFTPoints)+'E', array=freq)
                     colList.append(colFreq)
                     nchannel=self.dataOut.nChannels
                     for i in range(nchannel):
                         col = self.wrObj.writeData(name="PCh"+str(i+1),
                                                      format=str(self.dataOut.nFFTPoints)+'E',
                                                       data=10*numpy.log10(self.dataOut.data_spc[i,:]))
                         colList.append(col)
                     data=self.wrObj.Ctable(colList=colList)
                     self.wrObj.CFile(header,data)
                     self.wrObj.wFile(filename)
                     #update the setFile
                     self.setFile += 1
                     self.idblock += 1
                     return 1
                 def run(self, dataOut, **kwargs):
                     if not(self.isConfig):
                         self.setup(dataOut, **kwargs)
                         self.isConfig = True
                     self.putData()

schainpy/model/io/jroIO_param.py +21 -23

             import numpy
             import time
             import os
             import h5py
             import re
             import datetime
             from schainpy.model.data.jrodata import *
             from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
             # from jroIO_base import *
             from schainpy.model.io.jroIO_base import *
             import schainpy
             class ParamReader(ProcessingUnit):
                 '''
                 Reads HDF5 format files
                 path
                 startDate
                 endDate
                 startTime
                 endTime
                 '''
                 ext = ".hdf5"
                 optchar = "D"
                 timezone = None
                 startTime = None
                 endTime = None
                 fileIndex = None
                 utcList = None      #To select data in the utctime list
                 blockList = None    #List to blocks to be read from the file
                 blocksPerFile = None    #Number of blocks to be read
                 blockIndex = None
                 path = None
                 #List of Files
                 filenameList = None
                 datetimeList = None
                 #Hdf5 File
                 listMetaname = None
                 listMeta = None
                 listDataname = None
                 listData = None
                 listShapes = None
                 fp = None
                 #dataOut reconstruction
                 dataOut = None
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
                     self.dataOut = Parameters()
                     return
                 def setup(self, **kwargs):
                     path = kwargs['path']
                     startDate = kwargs['startDate']
                     endDate = kwargs['endDate']
                     startTime = kwargs['startTime']
                     endTime = kwargs['endTime']
                     walk = kwargs['walk']
                     if kwargs.has_key('ext'):
                         ext = kwargs['ext']
                     else:
                         ext = '.hdf5'
                     if kwargs.has_key('timezone'):
                         self.timezone = kwargs['timezone']
                     else:
                         self.timezone = 'lt'
                     print "[Reading] Searching files in offline mode ..."
                     pathList, filenameList = self.__searchFilesOffLine(path, startDate=startDate, endDate=endDate,
                                                                            startTime=startTime, endTime=endTime,
                                                                            ext=ext, walk=walk)
                     if not(filenameList):
                         print "There is no files into the folder: %s"%(path)
                         sys.exit(-1)
                     self.fileIndex = -1
                     self.startTime = startTime
                     self.endTime = endTime
                     self.__readMetadata()
                     self.__setNextFileOffline()
                     return
                 def __searchFilesOffLine(self,
                                         path,
                                         startDate=None,
                                         endDate=None,
                                         startTime=datetime.time(0,0,0),
                                         endTime=datetime.time(23,59,59),
                                         ext='.hdf5',
                                         walk=True):
                     expLabel = ''
                     self.filenameList = []
                     self.datetimeList = []
                     pathList = []
                     JRODataObj = JRODataReader()
                     dateList, pathList = JRODataObj.findDatafiles(path, startDate, endDate, expLabel, ext, walk, include_path=True)
                     if dateList == []:
                         print "[Reading] No *%s files in %s from %s to %s)"%(ext, path,
                                                                     datetime.datetime.combine(startDate,startTime).ctime(),
                                                                     datetime.datetime.combine(endDate,endTime).ctime())
                         return None, None
                     if len(dateList) > 1:
                         print "[Reading] %d days were found in date range: %s - %s" %(len(dateList), startDate, endDate)
                     else:
                         print "[Reading] data was found for the date %s" %(dateList[0])
                     filenameList = []
                     datetimeList = []
                     #----------------------------------------------------------------------------------
                     for thisPath in pathList:
             #             thisPath = pathList[pathDict[file]]
                         fileList = glob.glob1(thisPath, "*%s" %ext)
                         fileList.sort()
                         for file in fileList:
                             filename = os.path.join(thisPath,file)
                             if not isFileInDateRange(filename, startDate, endDate):
                                 continue
                             thisDatetime = self.__isFileInTimeRange(filename, startDate, endDate, startTime, endTime)
                             if not(thisDatetime):
                                 continue
                             filenameList.append(filename)
                             datetimeList.append(thisDatetime)
                     if not(filenameList):
                         print "[Reading] Any file was found int time range %s - %s" %(datetime.datetime.combine(startDate,startTime).ctime(), datetime.datetime.combine(endDate,endTime).ctime())
                         return None, None
                     print "[Reading] %d file(s) was(were) found in time range: %s - %s" %(len(filenameList), startTime, endTime)
                     print
                     for i in range(len(filenameList)):
                         print "[Reading] %s -> [%s]" %(filenameList[i], datetimeList[i].ctime())
                     self.filenameList = filenameList
                     self.datetimeList = datetimeList
                     return pathList, filenameList
                 def __isFileInTimeRange(self,filename, startDate, endDate, startTime, endTime):
                     """
                     Retorna 1 si el archivo de datos se encuentra dentro del rango de horas especificado.
                     Inputs:
                         filename            :    nombre completo del archivo de datos en formato Jicamarca (.r)
                         startDate          :    fecha inicial del rango seleccionado en formato datetime.date
                         endDate            :    fecha final del rango seleccionado en formato datetime.date
                         startTime          :    tiempo inicial del rango seleccionado en formato datetime.time
                         endTime            :    tiempo final del rango seleccionado en formato datetime.time
                     Return:
                         Boolean    :    Retorna True si el archivo de datos contiene datos en el rango de
                                         fecha especificado, de lo contrario retorna False.
                     Excepciones:
                         Si el archivo no existe o no puede ser abierto
                         Si la cabecera no puede ser leida.
                     """
                     try:
                         fp = h5py.File(filename,'r')
                         grp1 = fp['Data']
                     except IOError:
                         traceback.print_exc()
                         raise IOError, "The file %s can't be opened" %(filename)
                     #chino rata
                     #In case has utctime attribute
                     grp2 = grp1['utctime']
             #         thisUtcTime = grp2.value[0] - 5*3600 #To convert to local time
                     thisUtcTime = grp2.value[0]
                     fp.close()
                     if self.timezone == 'lt':
                         thisUtcTime -= 5*3600
                     thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
             #         thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0])
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate,startTime)- datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate,endTime)- datetime.datetime(1970, 1, 1)).total_seconds()
                     #General case
                     #           o>>>>>>>>>>>>>><<<<<<<<<<<<<<o
                     #-----------o----------------------------o-----------
                     #       startTime                     endTime
                     if endTime >= startTime:
                         thisUtcLog = numpy.logical_and(thisUtcTime > startUtcTime, thisUtcTime < endUtcTime)
                         if numpy.any(thisUtcLog):   #If there is one block between the hours mentioned
                             return thisDatetime
                         return None
                     #If endTime < startTime then endTime belongs to the next day
                     #<<<<<<<<<<<o                            o>>>>>>>>>>>
                     #-----------o----------------------------o-----------
                     #        endTime                    startTime
                     if (thisDate == startDate) and numpy.all(thisUtcTime < startUtcTime):
                         return None
                     if (thisDate == endDate) and numpy.all(thisUtcTime > endUtcTime):
                         return None
                     if numpy.all(thisUtcTime < startUtcTime) and numpy.all(thisUtcTime > endUtcTime):
                         return None
                     return thisDatetime
                 def __setNextFileOffline(self):
                     self.fileIndex += 1
                     idFile = self.fileIndex
                     if not(idFile < len(self.filenameList)):
                         print "No more Files"
                         return 0
                     filename = self.filenameList[idFile]
                     filePointer = h5py.File(filename,'r')
                     self.filename = filename
                     self.fp = filePointer
                     print "Setting the file: %s"%self.filename
             #         self.__readMetadata()
                     self.__setBlockList()
                     self.__readData()
             #         self.nRecords = self.fp['Data'].attrs['blocksPerFile']
             #         self.nRecords = self.fp['Data'].attrs['nRecords']
                     self.blockIndex = 0
                     return 1
                 def __setBlockList(self):
                     '''
                     Selects the data within the times defined
                     self.fp
                     self.startTime
                     self.endTime
                     self.blockList
                     self.blocksPerFile
                     '''
                     fp = self.fp
                     startTime = self.startTime
                     endTime = self.endTime
                     grp = fp['Data']
                     thisUtcTime = grp['utctime'].value.astype(numpy.float)[0]
                     #ERROOOOR
                     if self.timezone == 'lt':
                         thisUtcTime -= 5*3600
                     thisDatetime = datetime.datetime.fromtimestamp(thisUtcTime[0] + 5*3600)
                     thisDate = thisDatetime.date()
                     thisTime = thisDatetime.time()
                     startUtcTime = (datetime.datetime.combine(thisDate,startTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     endUtcTime = (datetime.datetime.combine(thisDate,endTime) - datetime.datetime(1970, 1, 1)).total_seconds()
                     ind = numpy.where(numpy.logical_and(thisUtcTime >= startUtcTime, thisUtcTime < endUtcTime))[0]
                     self.blockList = ind
                     self.blocksPerFile = len(ind)
                     return
                 def __readMetadata(self):
                     '''
                     Reads Metadata
                     self.pathMeta
                     self.listShapes
                     self.listMetaname
                     self.listMeta
                     '''
             #         grp = self.fp['Data']
             #         pathMeta = os.path.join(self.path, grp.attrs['metadata'])
             #
             #         if pathMeta == self.pathMeta:
             #             return
             #         else:
             #             self.pathMeta = pathMeta
             #
             #         filePointer = h5py.File(self.pathMeta,'r')
             #         groupPointer = filePointer['Metadata']
                     filename = self.filenameList[0]
                     fp = h5py.File(filename,'r')
                     gp = fp['Metadata']
                     listMetaname = []
                     listMetadata = []
                     for item in gp.items():
                         name = item[0]
                         if name=='array dimensions':
                             table = gp[name][:]
                             listShapes = {}
                             for shapes in table:
                                 listShapes[shapes[0]] = numpy.array([shapes[1],shapes[2],shapes[3],shapes[4],shapes[5]])
                         else:
                             data = gp[name].value
                             listMetaname.append(name)
                             listMetadata.append(data)
             #                 if name=='type':
             #                     self.__initDataOut(data)
                     self.listShapes = listShapes
                     self.listMetaname = listMetaname
                     self.listMeta = listMetadata
                     fp.close()
                     return
                 def __readData(self):
                     grp = self.fp['Data']
                     listdataname = []
                     listdata = []
                     for item in grp.items():
                         name = item[0]
                         listdataname.append(name)
                         array = self.__setDataArray(grp[name],self.listShapes[name])
                         listdata.append(array)
                     self.listDataname = listdataname
                     self.listData = listdata
                     return
                 def __setDataArray(self, dataset, shapes):
                     nDims = shapes[0]
                     nDim2 = shapes[1]      #Dimension 0
                     nDim1 = shapes[2]      #Dimension 1, number of Points or Parameters
                     nDim0 = shapes[3]      #Dimension 2, number of samples or ranges
                     mode = shapes[4]        #Mode of storing
                     blockList = self.blockList
                     blocksPerFile = self.blocksPerFile
                     #Depending on what mode the data was stored
                     if mode == 0:       #Divided in channels
                         arrayData = dataset.value.astype(numpy.float)[0][blockList]
                     if mode == 1:     #Divided in parameter
                         strds = 'table'
                         nDatas = nDim1
                         newShapes = (blocksPerFile,nDim2,nDim0)
                     elif mode==2:       #Concatenated in a table
                         strds = 'table0'
                         arrayData = dataset[strds].value
                         #Selecting part of the dataset
                         utctime = arrayData[:,0]
                         u, indices = numpy.unique(utctime, return_index=True)
                         if blockList.size != indices.size:
                             indMin = indices[blockList[0]]
                             if blockList[1] + 1 >= indices.size:
                                 arrayData = arrayData[indMin:,:]
                             else:
                                 indMax = indices[blockList[1] + 1]
                                 arrayData = arrayData[indMin:indMax,:]
                         return arrayData
                     #    One dimension
                     if nDims == 0:
                         arrayData = dataset.value.astype(numpy.float)[0][blockList]
                     #    Two dimensions
                     elif nDims == 2:
                         arrayData = numpy.zeros((blocksPerFile,nDim1,nDim0))
                         newShapes = (blocksPerFile,nDim0)
                         nDatas = nDim1
                         for i in range(nDatas):
                             data = dataset[strds + str(i)].value
                             arrayData[:,i,:] = data[blockList,:]
                     #    Three dimensions
                     else:
                         arrayData = numpy.zeros((blocksPerFile,nDim2,nDim1,nDim0))
                         for i in range(nDatas):
                             data = dataset[strds + str(i)].value
                             for b in range(blockList.size):
                                 arrayData[b,:,i,:] = data[:,:,blockList[b]]
                     return arrayData
                 def __setDataOut(self):
                     listMeta = self.listMeta
                     listMetaname = self.listMetaname
                     listDataname = self.listDataname
                     listData = self.listData
                     listShapes = self.listShapes
                     blockIndex = self.blockIndex
             #         blockList = self.blockList
                     for i in range(len(listMeta)):
                         setattr(self.dataOut,listMetaname[i],listMeta[i])
                     for j in range(len(listData)):
                         nShapes = listShapes[listDataname[j]][0]
                         mode = listShapes[listDataname[j]][4]
                         if nShapes == 1:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex])
                         elif nShapes > 1:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex,:])
                         elif mode==0:
                             setattr(self.dataOut,listDataname[j],listData[j][blockIndex])
                         #Mode Meteors
                         elif mode ==2:
                             selectedData = self.__selectDataMode2(listData[j], blockIndex)
                             setattr(self.dataOut, listDataname[j], selectedData)
                     return
                 def __selectDataMode2(self, data, blockIndex):
                     utctime = data[:,0]
                     aux, indices = numpy.unique(utctime, return_inverse=True)
                     selInd = numpy.where(indices == blockIndex)[0]
                     selData = data[selInd,:]
                     return selData
                 def getData(self):
             #         if self.flagNoMoreFiles:
             #             self.dataOut.flagNoData = True
             #             print 'Process finished'
             #             return 0
             #
                     if self.blockIndex==self.blocksPerFile:
                          if not( self.__setNextFileOffline() ):
                             self.dataOut.flagNoData = True
                             return 0
             #         if self.datablock == None: # setear esta condicion cuando no hayan datos por leers
             #             self.dataOut.flagNoData = True
             #             return 0
             #         self.__readData()
                     self.__setDataOut()
                     self.dataOut.flagNoData = False
                     self.blockIndex += 1
                     return
                 def run(self, **kwargs):
                     if not(self.isConfig):
                         self.setup(**kwargs)
             #             self.setObjProperties()
                         self.isConfig = True
                     self.getData()
                     return
             class ParamWriter(Operation):
                 '''
                 HDF5 Writer, stores parameters data in HDF5 format files
                 path:             path where the files will be stored
                 blocksPerFile:    number of blocks that will be saved in per HDF5 format file
                 mode:             selects the data stacking mode: '0' channels, '1' parameters, '3' table (for meteors)
                 metadataList:     list of attributes that will be stored as metadata
                 dataList:         list of attributes that will be stores as data
                 '''
                 ext = ".hdf5"
                 optchar = "D"
                 metaoptchar = "M"
                 metaFile = None
                 filename = None
                 path = None
                 setFile = None
                 fp = None
                 grp = None
                 ds = None
                 firsttime = True
                 #Configurations
                 blocksPerFile = None
                 blockIndex = None
                 dataOut = None
                 #Data Arrays
                 dataList = None
                 metadataList = None
             #     arrayDim = None
                 dsList = None   #List of dictionaries with dataset properties
                 tableDim = None
             #     dtype = [('arrayName', 'S20'),('nChannels', 'i'), ('nPoints', 'i'), ('nSamples', 'i'),('mode', 'b')]
                 dtype = [('arrayName', 'S20'),('nDimensions', 'i'), ('dim2', 'i'), ('dim1', 'i'),('dim0', 'i'),('mode', 'b')]
                 currentDay = None
                 lastTime = None
+                parameters = {
+                    'path': global_type_string,
+                    'blocksPerFile':global_type_integer,
+                    'metadataList': global_type_list,
+                    'dataList': global_type_list,
+                    'mode': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.isConfig = False
                     return
-                def setup(self, dataOut, **kwargs):
+                def setup(self, dataOut, path=None, blocksPerFile=10, metadataList=None, dataList=None, mode=None, **kwargs):
+                    self.path = path
-                    self.path = kwargs['path']
+                    self.blocksPerFile = blocksPerFile
-                    self.setType = kwargs.get('setType', None)
+                    self.metadataList = metadataList
+                    self.dataList = dataList
-                    if kwargs.has_key('blocksPerFile'):
-                        self.blocksPerFile = kwargs['blocksPerFile']
-                    else:
-                        self.blocksPerFile = 10
-                    self.metadataList = kwargs['metadataList']
-                    self.dataList = kwargs['dataList']
                     self.dataOut = dataOut
-                    if kwargs.has_key('mode'):
-                        mode = kwargs['mode']
-                        if type(mode) == int:
-                            mode = numpy.zeros(len(self.dataList)) + mode
-                    else:
-                        mode = numpy.ones(len(self.dataList))
                     self.mode = mode
+                    if self.mode is not None:
+                        self.mode = numpy.zeros(len(self.dataList)) + mode
+                    else:
+                        self.mode = numpy.ones(len(self.dataList))
                     arrayDim = numpy.zeros((len(self.dataList),5))
                     #Table dimensions
                     dtype0 = self.dtype
                     tableList = []
                     #Dictionary and list of tables
                     dsList = []
                     for i in range(len(self.dataList)):
                         dsDict = {}
                         dataAux = getattr(self.dataOut, self.dataList[i])
                         dsDict['variable'] = self.dataList[i]
                         #---------------------    Conditionals    ------------------------
                         #There is no data
                         if dataAux is None:
                             return 0
                         #Not array, just a number
                         #Mode 0
                         if type(dataAux)==float or type(dataAux)==int:
                             dsDict['mode'] = 0
                             dsDict['nDim'] = 0
                             arrayDim[i,0] = 0
                             dsList.append(dsDict)
                         #Mode 2: meteors
                         elif mode[i] == 2:
             #                 dsDict['nDim'] = 0
                             dsDict['dsName'] = 'table0'
                             dsDict['mode'] = 2      # Mode meteors
                             dsDict['shape'] = dataAux.shape[-1]
                             dsDict['nDim'] = 0
                             dsDict['dsNumber'] = 1
                             arrayDim[i,3] = dataAux.shape[-1]
                             arrayDim[i,4] = mode[i]         #Mode the data was stored
                             dsList.append(dsDict)
                         #Mode 1
                         else:
                             arrayDim0 = dataAux.shape       #Data dimensions
                             arrayDim[i,0] = len(arrayDim0)  #Number of array dimensions
                             arrayDim[i,4] = mode[i]         #Mode the data was stored
                             strtable = 'table'
                             dsDict['mode'] = 1      # Mode parameters
                             # Three-dimension arrays
                             if len(arrayDim0) == 3:
                                 arrayDim[i,1:-1] = numpy.array(arrayDim0)
                                 nTables = int(arrayDim[i,2])
                                 dsDict['dsNumber'] = nTables
                                 dsDict['shape'] = arrayDim[i,2:4]
                                 dsDict['nDim'] = 3
                                 for j in range(nTables):
                                     dsDict = dsDict.copy()
                                     dsDict['dsName'] = strtable + str(j)
                                     dsList.append(dsDict)
                             # Two-dimension arrays
                             elif len(arrayDim0) == 2:
                                 arrayDim[i,2:-1] = numpy.array(arrayDim0)
                                 nTables = int(arrayDim[i,2])
                                 dsDict['dsNumber'] = nTables
                                 dsDict['shape'] = arrayDim[i,3]
                                 dsDict['nDim'] = 2
                                 for j in range(nTables):
                                     dsDict = dsDict.copy()
                                     dsDict['dsName'] = strtable + str(j)
                                     dsList.append(dsDict)
                             # One-dimension arrays
                             elif len(arrayDim0) == 1:
                                 arrayDim[i,3] = arrayDim0[0]
                                 dsDict['shape'] = arrayDim0[0]
                                 dsDict['dsNumber'] = 1
                                 dsDict['dsName'] = strtable + str(0)
                                 dsDict['nDim'] = 1
                                 dsList.append(dsDict)
                         table = numpy.array((self.dataList[i],) + tuple(arrayDim[i,:]),dtype = dtype0)
                         tableList.append(table)
             #         self.arrayDim = arrayDim
                     self.dsList = dsList
                     self.tableDim = numpy.array(tableList, dtype = dtype0)
                     self.blockIndex = 0
                     timeTuple = time.localtime(dataOut.utctime)
                     self.currentDay = timeTuple.tm_yday
                     return 1
                 def putMetadata(self):
                     fp = self.createMetadataFile()
                     self.writeMetadata(fp)
                     fp.close()
                     return
                 def createMetadataFile(self):
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = ''
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if not( os.path.exists(fullpath) ):
                         os.mkdir(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     else:
                         filesList = os.listdir( fullpath )
                         filesList = sorted( filesList, key=str.lower )
                         if len( filesList ) > 0:
                             filesList = [k for k in filesList if 'M' in k]
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber( filen[8:11] ):
                                 setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     filename = os.path.join( path, subfolder, file )
                     self.metaFile = file
                     #Setting HDF5 File
                     fp = h5py.File(filename,'w')
                     return fp
                 def writeMetadata(self, fp):
                     grp = fp.create_group("Metadata")
                     grp.create_dataset('array dimensions', data = self.tableDim, dtype = self.dtype)
                     for i in range(len(self.metadataList)):
                         grp.create_dataset(self.metadataList[i], data=getattr(self.dataOut, self.metadataList[i]))
                     return
                 def timeFlag(self):
                     currentTime = self.dataOut.utctime
                     if self.lastTime is None:
                         self.lastTime = currentTime
                     #Day
                     timeTuple = time.localtime(currentTime)
                     dataDay = timeTuple.tm_yday
                     #Time
                     timeDiff = currentTime - self.lastTime
                     #Si el dia es diferente o si la diferencia entre un dato y otro supera la hora
                     if dataDay != self.currentDay:
                         self.currentDay = dataDay
                         return True
                     elif timeDiff > 3*60*60:
                         self.lastTime = currentTime
                         return True
                     else:
                         self.lastTime = currentTime
                         return False
                 def setNextFile(self):
                     ext = self.ext
                     path = self.path
                     setFile = self.setFile
                     mode = self.mode
                     timeTuple = time.localtime(self.dataOut.utctime)
                     subfolder = 'd%4.4d%3.3d' % (timeTuple.tm_year,timeTuple.tm_yday)
                     fullpath = os.path.join( path, subfolder )
                     if os.path.exists(fullpath):
                         filesList = os.listdir( fullpath )
                         filesList = [k for k in filesList if 'D' in k]
                         if len( filesList ) > 0:
                             filesList = sorted( filesList, key=str.lower )
                             filen = filesList[-1]
                             # el filename debera tener el siguiente formato
                             # 0 1234 567 89A BCDE (hex)
                             # x YYYY DDD SSS .ext
                             if isNumber( filen[8:11] ):
                                 setFile = int( filen[8:11] ) #inicializo mi contador de seteo al seteo del ultimo file
                             else:
                                 setFile = -1
                         else:
                             setFile = -1 #inicializo mi contador de seteo
                     else:
                         os.makedirs(fullpath)
                         setFile = -1 #inicializo mi contador de seteo
                     if self.setType is None:
                         setFile += 1
                         file = '%s%4.4d%3.3d%03d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     else:
                         setFile = timeTuple.tm_hour*60+timeTuple.tm_min
                         file = '%s%4.4d%3.3d%04d%s' % (self.metaoptchar,
                                                        timeTuple.tm_year,
                                                        timeTuple.tm_yday,
                                                        setFile,
                                                        ext )
                     filename = os.path.join( path, subfolder, file )
                     #Setting HDF5 File
                     fp = h5py.File(filename,'w')
                     #write metadata
                     self.writeMetadata(fp)
                     #Write data
                     grp = fp.create_group("Data")
             #         grp.attrs['metadata'] = self.metaFile
             #         grp.attrs['blocksPerFile'] = 0
                     ds = []
                     data = []
                     dsList = self.dsList
                     i = 0
                     while i < len(dsList):
                         dsInfo = dsList[i]
                         #One-dimension data
                         if dsInfo['mode'] == 0:
             #                 ds0 = grp.create_dataset(self.dataList[i], (1,1), maxshape=(1,self.blocksPerFile) , chunks = True, dtype='S20')
                             ds0 = grp.create_dataset(dsInfo['variable'], (1,1), maxshape=(1,self.blocksPerFile) , chunks = True, dtype=numpy.float64)
                             ds.append(ds0)
                             data.append([])
                             i += 1
                             continue
             #                 nDimsForDs.append(nDims[i])
                         elif dsInfo['mode'] == 2:
                             grp0 = grp.create_group(dsInfo['variable'])
                             ds0 = grp0.create_dataset(dsInfo['dsName'], (1,dsInfo['shape']), data = numpy.zeros((1,dsInfo['shape'])) , maxshape=(None,dsInfo['shape']), chunks=True)
                             ds.append(ds0)
                             data.append([])
                             i += 1
                             continue
                         elif dsInfo['mode'] == 1:
                             grp0 = grp.create_group(dsInfo['variable'])
                             for j in range(dsInfo['dsNumber']):
                                 dsInfo = dsList[i]
                                 tableName = dsInfo['dsName']
                                 shape = int(dsInfo['shape'])
                                 if dsInfo['nDim'] == 3:
                                     ds0 = grp0.create_dataset(tableName, (shape[0],shape[1],1) , data = numpy.zeros((shape[0],shape[1],1)), maxshape = (None,shape[1],None), chunks=True)
                                 else:
                                     ds0 = grp0.create_dataset(tableName, (1,shape), data = numpy.zeros((1,shape)) , maxshape=(None,shape), chunks=True)
                                 ds.append(ds0)
                                 data.append([])
                                 i += 1
             #                     nDimsForDs.append(nDims[i])
                     fp.flush()
                     fp.close()
             #         self.nDatas = nDatas
             #         self.nDims = nDims
             #         self.nDimsForDs = nDimsForDs
                     #Saving variables
                     print 'Writing the file: %s'%filename
                     self.filename = filename
             #         self.fp = fp
             #         self.grp = grp
             #         self.grp.attrs.modify('nRecords', 1)
                     self.ds = ds
                     self.data = data
             #         self.setFile = setFile
                     self.firsttime = True
                     self.blockIndex = 0
                     return
                 def putData(self):
                     if self.blockIndex == self.blocksPerFile or self.timeFlag():
                         self.setNextFile()
             #         if not self.firsttime:
                     self.readBlock()
                     self.setBlock()     #Prepare data to be written
                     self.writeBlock()   #Write data
                     return
                 def readBlock(self):
                     '''
                     data Array configured
                     self.data
                     '''
                     dsList = self.dsList
                     ds = self.ds
                             #Setting HDF5 File
                     fp = h5py.File(self.filename,'r+')
                     grp = fp["Data"]
                     ind = 0
             #         grp.attrs['blocksPerFile'] = 0
                     while ind < len(dsList):
                         dsInfo = dsList[ind]
                         if dsInfo['mode'] == 0:
                             ds0 = grp[dsInfo['variable']]
                             ds[ind] = ds0
                             ind += 1
                         else:
                             grp0 = grp[dsInfo['variable']]
                             for j in range(dsInfo['dsNumber']):
                                 dsInfo = dsList[ind]
                                 ds0 = grp0[dsInfo['dsName']]
                                 ds[ind] = ds0
                                 ind += 1
                     self.fp = fp
                     self.grp = grp
                     self.ds = ds
                     return
                 def setBlock(self):
                     '''
                     data Array configured
                     self.data
                     '''
                     #Creating Arrays
                     dsList = self.dsList
                     data = self.data
                     ind = 0
                     while ind < len(dsList):
                         dsInfo = dsList[ind]
                         dataAux = getattr(self.dataOut, dsInfo['variable'])
                         mode = dsInfo['mode']
                         nDim = dsInfo['nDim']
                         if mode == 0 or mode == 2 or nDim == 1:
                             data[ind] = dataAux
                             ind += 1
             #             elif nDim == 1:
             #                 data[ind] = numpy.reshape(dataAux,(numpy.size(dataAux),1))
             #                 ind += 1
                         elif nDim == 2:
                             for j in range(dsInfo['dsNumber']):
                                 data[ind] = dataAux[j,:]
                                 ind += 1
                         elif nDim == 3:
                             for j in range(dsInfo['dsNumber']):
                                 data[ind] = dataAux[:,j,:]
                                 ind += 1
                     self.data = data
                     return
                 def writeBlock(self):
                     '''
                     Saves the block in the HDF5 file
                     '''
                     dsList = self.dsList
                     for i in range(len(self.ds)):
                         dsInfo = dsList[i]
                         nDim = dsInfo['nDim']
                         mode = dsInfo['mode']
                         #    First time
                         if self.firsttime:
             #                 self.ds[i].resize(self.data[i].shape)
             #                 self.ds[i][self.blockIndex,:] = self.data[i]
                             if type(self.data[i]) == numpy.ndarray:
                                 if nDim == 3:
                                     self.data[i] = self.data[i].reshape((self.data[i].shape[0],self.data[i].shape[1],1))
                                     self.ds[i].resize(self.data[i].shape)
                                 if mode == 2:
                                     self.ds[i].resize(self.data[i].shape)
                             self.ds[i][:] = self.data[i]
                         else:
                         #    From second time
                             #    Meteors!
                             if mode == 2:
                                 dataShape = self.data[i].shape
                                 dsShape = self.ds[i].shape
                                 self.ds[i].resize((self.ds[i].shape[0] + dataShape[0],self.ds[i].shape[1]))
                                 self.ds[i][dsShape[0]:,:] = self.data[i]
                             #    No dimension
                             elif mode == 0:
                                 self.ds[i].resize((self.ds[i].shape[0], self.ds[i].shape[1] + 1))
                                 self.ds[i][0,-1] = self.data[i]
                             #    One dimension
                             elif nDim == 1:
                                 self.ds[i].resize((self.ds[i].shape[0] + 1, self.ds[i].shape[1]))
                                 self.ds[i][-1,:] = self.data[i]
                             #    Two dimension
                             elif nDim == 2:
                                 self.ds[i].resize((self.ds[i].shape[0] + 1,self.ds[i].shape[1]))
                                 self.ds[i][self.blockIndex,:] = self.data[i]
                             #    Three dimensions
                             elif nDim == 3:
                                 self.ds[i].resize((self.ds[i].shape[0],self.ds[i].shape[1],self.ds[i].shape[2]+1))
                                 self.ds[i][:,:,-1] = self.data[i]
                     self.firsttime = False
                     self.blockIndex += 1
                     #Close to save changes
                     self.fp.flush()
                     self.fp.close()
                     return
-                def run(self, dataOut, **kwargs):
+                def run(self, dataOut, path=None, blocksPerFile=10, metadataList=None, dataList=None, mode=None, **kwargs):
                     if not(self.isConfig):
-                        flagdata = self.setup(dataOut, **kwargs)
+                        flagdata = self.setup(dataOut, path=path, blocksPerFile=blocksPerFile,
+                                              metadataList=metadataList, dataList=dataList, mode=mode, **kwargs)
                         if not(flagdata):
                             return
                         self.isConfig = True
             #             self.putMetadata()
                         self.setNextFile()
                     self.putData()
                     return

schainpy/model/proc/jroproc_amisr.py +3 0

             '''
             @author: Daniel Suarez
             '''
             import numpy
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jroamisr import AMISR
             class AMISRProc(ProcessingUnit):
                 def __init__(self):
                     ProcessingUnit.__init__(self)
                     self.objectDict = {}
                     self.dataOut = AMISR()
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.dataOut.copy(self.dataIn)
             class PrintInfo(Operation):
                 def __init__(self):
                     self.__isPrinted = False
                 def run(self, dataOut):
                     if not self.__isPrinted:
                         print 'Number of Records by File: %d'%dataOut.nRecords
                         print 'Number of Pulses: %d'%dataOut.nProfiles
                         print 'Number of Pulses by Frame: %d'%dataOut.npulseByFrame
                         print 'Number of Samples by Pulse: %d'%len(dataOut.heightList)
                         print 'Ipp Seconds: %f'%dataOut.ippSeconds
                         print 'Number of Beams: %d'%dataOut.nBeams
                         print 'BeamCodes:'
                         beamStrList = ['Beam %d -> Code=%d, azimuth=%2.2f,  zenith=%2.2f, gain=%2.2f'%(k,v[0],v[1],v[2],v[3]) for k,v in dataOut.beamCodeDict.items()]
                         for b in beamStrList:
                             print b
                         self.__isPrinted = True
                     return
             class BeamSelector(Operation):
                 profileIndex = None
                 nProfiles = None
+                parameters = {
+            	    'beam': global_type_string,
+                }
                 def __init__(self):
                     self.profileIndex = 0
                     self.__isConfig = False
                 def incIndex(self):
                     self.profileIndex += 1
                     if self.profileIndex >= self.nProfiles:
                         self.profileIndex = 0
                 def isProfileInRange(self, minIndex, maxIndex):
                     if self.profileIndex < minIndex:
                         return False
                     if self.profileIndex > maxIndex:
                         return False
                     return True
                 def isProfileInList(self, profileList):
                     if self.profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut, beam=None):
                     dataOut.flagNoData = True
                     if not(self.__isConfig):
                         self.nProfiles = dataOut.nProfiles
                         self.profileIndex = dataOut.profileIndex
                         self.__isConfig = True
                     if beam != None:
                         if self.isProfileInList(dataOut.beamRangeDict[beam]):
                             beamInfo = dataOut.beamCodeDict[beam]
                             dataOut.azimuth = beamInfo[1]
                             dataOut.zenith = beamInfo[2]
                             dataOut.gain = beamInfo[3]
                             dataOut.flagNoData = False
                         self.incIndex()
                         return 1
                     else:
                         raise ValueError, "BeamSelector needs beam value"
                     return 0
             class ProfileToChannels(Operation):
                 def __init__(self):
                     self.__isConfig = False
                     self.__counter_chan = 0
                     self.buffer = None
                 def isProfileInList(self, profileList):
                     if self.profileIndex not in profileList:
                         return False
                     return True
                 def run(self, dataOut):
                     dataOut.flagNoData = True
                     if not(self.__isConfig):
                         nchannels = len(dataOut.beamRangeDict.keys())
                         nsamples = dataOut.nHeights
                         self.buffer = numpy.zeros((nchannels, nsamples), dtype = 'complex128')
                         dataOut.beam.codeList = [dataOut.beamCodeDict[x][0] for x in range(nchannels)]
                         dataOut.beam.azimuthList = [dataOut.beamCodeDict[x][1] for x in range(nchannels)]
                         dataOut.beam.zenithList = [dataOut.beamCodeDict[x][2] for x in range(nchannels)]
                         self.__isConfig = True
                     for i in range(self.buffer.shape[0]):
                         if dataOut.profileIndex in dataOut.beamRangeDict[i]:
                             self.buffer[i,:] = dataOut.data
                             break
                     self.__counter_chan += 1
                     if self.__counter_chan >= self.buffer.shape[0]:
                         self.__counter_chan = 0
                         dataOut.data = self.buffer.copy()
                         dataOut.channelList = range(self.buffer.shape[0])
                         self.__isConfig = False
                         dataOut.flagNoData = False
                     pass
   No newline at end of file

schainpy/model/proc/jroproc_heispectra.py +7 -2

             import numpy
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import SpectraHeis
             class SpectraHeisProc(ProcessingUnit):
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
             #        self.buffer = None
             #        self.firstdatatime = None
             #        self.profIndex = 0
                     self.dataOut = SpectraHeis()
                 def __updateObjFromVoltage(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.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()#
                     self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()#
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
             #        self.dataOut.dtype = self.dataIn.dtype
                     self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
             #        self.dataOut.nHeights = self.dataIn.nHeights
             #        self.dataOut.nChannels = self.dataIn.nChannels
                     self.dataOut.nBaud = self.dataIn.nBaud
                     self.dataOut.nCode = self.dataIn.nCode
                     self.dataOut.code = self.dataIn.code
             #        self.dataOut.nProfiles = 1
                     self.dataOut.ippFactor = 1
                     self.dataOut.noise_estimation = None
             #        self.dataOut.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.nFFTPoints = self.dataIn.nHeights
             #        self.dataOut.channelIndexList = self.dataIn.channelIndexList
             #        self.dataOut.flagNoData = self.dataIn.flagNoData
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.dataIn.utctime
             #        self.dataOut.utctime = self.firstdatatime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
             #        self.dataOut.flagShiftFFT = self.dataIn.flagShiftFFT
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
             #         self.dataOut.ippSeconds= self.dataIn.ippSeconds
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
             #         self.dataOut.timeInterval = self.dataIn.timeInterval*self.dataOut.nIncohInt
             #        self.dataOut.set=self.dataIn.set
             #        self.dataOut.deltaHeight=self.dataIn.deltaHeight
                 def __updateObjFromFits(self):
                     self.dataOut.utctime = self.dataIn.utctime
             #         self.dataOut.channelIndexList = self.dataIn.channelIndexList
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.data_spc = self.dataIn.data
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = self.dataIn.nIncohInt
             #         self.dataOut.timeInterval = self.dataIn.timeInterval
                     self.dataOut.timeZone = self.dataIn.timeZone
                     self.dataOut.useLocalTime = True
             #         self.dataOut.
             #         self.dataOut.
                 def __getFft(self):
                     fft_volt = numpy.fft.fft(self.dataIn.data, axis=1)
                     fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
                     spc = numpy.abs(fft_volt * numpy.conjugate(fft_volt))/(self.dataOut.nFFTPoints)
                     self.dataOut.data_spc = spc
                 def run(self):
                     self.dataOut.flagNoData = True
                     if self.dataIn.type == "Fits":
                         self.__updateObjFromFits()
                         self.dataOut.flagNoData = False
                         return
                     if self.dataIn.type == "SpectraHeis":
                         self.dataOut.copy(self.dataIn)
                         return
                     if self.dataIn.type == "Voltage":
                         self.__updateObjFromVoltage()
                         self.__getFft()
                         self.dataOut.flagNoData = False
                         return
                     raise ValueError, "The type object %s is not valid"%(self.dataIn.type)
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in channelList:
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                 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:
                             print channelIndexList
                             raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
             #         nChannels = len(channelIndexList)
                     data_spc = self.dataOut.data_spc[channelIndexList,:]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList]
                     return 1
             class IncohInt4SpectraHeis(Operation):
                 isConfig = False
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 n = None
+                parameters = {
+                    'n': global_type_float,
+                    'timeInterval': global_type_integer,
+                    'overlapping': global_type_boolean,
+                }
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
             #         self.isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=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
                     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.__withOverapping = True
                         self.__buffer = None
                     else:
                         self.__withOverapping = 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.__withOverapping:
                         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.__withOverapping:
                         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)
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
             #         n = None
                     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 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.__withOverapping:
                         self.__initime = datatime
                     else:
                         self.__initime += deltatime
                     return avgdata, avgdatatime
-                def run(self, dataOut, **kwargs):
+                def run(self, dataOut, n=None, timeInterval=None, overlapping=False, **kwargs):
                     if not self.isConfig:
-                        self.setup(**kwargs)
+                        self.setup(n=n, timeInterval=timeInterval, overlapping=overlapping)
                         self.isConfig = True
                     avgdata, avgdatatime = self.integrate(dataOut.data_spc, dataOut.utctime)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data_spc = avgdata
                         dataOut.nIncohInt *= self.n
             #            dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
             #             dataOut.timeInterval = dataOut.ippSeconds * dataOut.nIncohInt
             #            dataOut.timeInterval = self.__timeInterval*self.n
                         dataOut.flagNoData = False

schainpy/model/proc/jroproc_parameters.py +7 0

             import numpy
             import math
             from scipy import optimize, interpolate, signal, stats, ndimage
             import re
             import datetime
             import copy
             import sys
             import importlib
             import itertools
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon
             class ParametersProc(ProcessingUnit):
                 nSeconds = None
                 def __init__(self):
                     ProcessingUnit.__init__(self)
             #         self.objectDict = {}
                     self.buffer = None
                     self.firstdatatime = None
                     self.profIndex = 0
                     self.dataOut = Parameters()
                 def __updateObjFromInput(self):
                     self.dataOut.inputUnit = self.dataIn.type
                     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.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
                     self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
             #         self.dataOut.nHeights = self.dataIn.nHeights
             #         self.dataOut.nChannels = self.dataIn.nChannels
                     self.dataOut.nBaud = self.dataIn.nBaud
                     self.dataOut.nCode = self.dataIn.nCode
                     self.dataOut.code = self.dataIn.code
             #        self.dataOut.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
             #         self.dataOut.utctime = self.firstdatatime
                     self.dataOut.utctime = self.dataIn.utctime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
                     self.dataOut.nCohInt = self.dataIn.nCohInt
             #        self.dataOut.nIncohInt = 1
                     self.dataOut.ippSeconds = self.dataIn.ippSeconds
             #        self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
                     self.dataOut.timeInterval1 = self.dataIn.timeInterval
                     self.dataOut.heightList = self.dataIn.getHeiRange()
                     self.dataOut.frequency = self.dataIn.frequency
                     #self.dataOut.noise = self.dataIn.noise
                 def run(self):
                     #----------------------    Voltage Data    ---------------------------
                     if self.dataIn.type == "Voltage":
                         self.__updateObjFromInput()
                         self.dataOut.data_pre = self.dataIn.data.copy()
                         self.dataOut.flagNoData = False
                         self.dataOut.utctimeInit = self.dataIn.utctime
                         self.dataOut.paramInterval = self.dataIn.nProfiles*self.dataIn.nCohInt*self.dataIn.ippSeconds
                         return
                     #----------------------    Spectra Data    ---------------------------
                     if self.dataIn.type == "Spectra":
                         self.dataOut.data_pre = (self.dataIn.data_spc, self.dataIn.data_cspc)
                         self.dataOut.data_spc = self.dataIn.data_spc
                         self.dataOut.data_cspc = self.dataIn.data_cspc
                         self.dataOut.nProfiles = self.dataIn.nProfiles
                         self.dataOut.nIncohInt = self.dataIn.nIncohInt
                         self.dataOut.nFFTPoints = self.dataIn.nFFTPoints
                         self.dataOut.ippFactor = self.dataIn.ippFactor
                         #self.dataOut.normFactor = self.dataIn.getNormFactor()
                         self.dataOut.pairsList = self.dataIn.pairsList
                         self.dataOut.groupList = self.dataIn.pairsList
                         self.dataOut.abscissaList = self.dataIn.getVelRange(1)
                         self.dataOut.flagNoData = False
                     #----------------------    Correlation Data    ---------------------------
                     if self.dataIn.type == "Correlation":
                         acf_ind, ccf_ind, acf_pairs, ccf_pairs, data_acf, data_ccf = self.dataIn.splitFunctions()
                         self.dataOut.data_pre = (self.dataIn.data_cf[acf_ind,:], self.dataIn.data_cf[ccf_ind,:,:])
                         self.dataOut.normFactor = (self.dataIn.normFactor[acf_ind,:], self.dataIn.normFactor[ccf_ind,:])
                         self.dataOut.groupList = (acf_pairs, ccf_pairs)
                         self.dataOut.abscissaList = self.dataIn.lagRange
                         self.dataOut.noise = self.dataIn.noise
                         self.dataOut.data_SNR = self.dataIn.SNR
                         self.dataOut.flagNoData = False
                         self.dataOut.nAvg = self.dataIn.nAvg
                     #----------------------    Parameters Data    ---------------------------
                     if self.dataIn.type == "Parameters":
                         self.dataOut.copy(self.dataIn)
                         self.dataOut.utctimeInit = self.dataIn.utctime
                         self.dataOut.flagNoData = False
                         return True
                     self.__updateObjFromInput()
                     self.dataOut.utctimeInit = self.dataIn.utctime
                     self.dataOut.paramInterval = self.dataIn.timeInterval
                     return
             class SpectralMoments(Operation):
                 '''
                     Function SpectralMoments()
                     Calculates moments (power, mean, standard deviation) and SNR of the signal
                     Type of dataIn:    Spectra
                     Configuration Parameters:
                         dirCosx    :     Cosine director in X axis
                         dirCosy    :     Cosine director in Y axis
                         elevation  :
                         azimuth    :
                     Input:
                         channelList    :    simple channel list to select e.g. [2,3,7]
                         self.dataOut.data_pre        :    Spectral data
                         self.dataOut.abscissaList    :    List of frequencies
                         self.dataOut.noise           :    Noise level per channel
                     Affected:
                         self.dataOut.data_param      :    Parameters per channel
                         self.dataOut.data_SNR        :    SNR per channel
                 '''
                 def run(self, dataOut):
                     #dataOut.data_pre = dataOut.data_pre[0]
                     data = dataOut.data_pre[0]
                     absc = dataOut.abscissaList[:-1]
                     noise = dataOut.noise
                     nChannel = data.shape[0]
                     data_param = numpy.zeros((nChannel, 4, data.shape[2]))
                     for ind in range(nChannel):
                         data_param[ind,:,:] = self.__calculateMoments(data[ind,:,:], absc, noise[ind])
                     dataOut.data_param = data_param[:,1:,:]
                     dataOut.data_SNR = data_param[:,0]
                     dataOut.data_DOP = data_param[:,1]
                     dataOut.data_MEAN = data_param[:,2]
                     dataOut.data_STD = data_param[:,3]
                     return
                 def __calculateMoments(self, oldspec, oldfreq, n0, nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None):
                     if (nicoh is None): nicoh = 1
                     if (graph is None): graph = 0
                     if (smooth is None): smooth = 0
                     elif (self.smooth < 3): smooth = 0
                     if (type1 is None): type1 = 0
                     if (fwindow is None): fwindow = numpy.zeros(oldfreq.size) + 1
                     if (snrth is None): snrth = -3
                     if (dc is None): dc = 0
                     if (aliasing is None): aliasing = 0
                     if (oldfd is None): oldfd = 0
                     if (wwauto is None): wwauto = 0
                     if (n0 < 1.e-20):   n0 = 1.e-20
                     freq = oldfreq
                     vec_power = numpy.zeros(oldspec.shape[1])
                     vec_fd = numpy.zeros(oldspec.shape[1])
                     vec_w = numpy.zeros(oldspec.shape[1])
                     vec_snr = numpy.zeros(oldspec.shape[1])
                     for ind in range(oldspec.shape[1]):
                         spec = oldspec[:,ind]
                         aux = spec*fwindow
                         max_spec = aux.max()
                         m = list(aux).index(max_spec)
                         #Smooth
                         if (smooth == 0):   spec2 = spec
                         else:   spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth)
                         #    Calculo de Momentos
                         bb = spec2[range(m,spec2.size)]
                         bb = (bb<n0).nonzero()
                         bb = bb[0]
                         ss = spec2[range(0,m + 1)]
                         ss = (ss<n0).nonzero()
                         ss = ss[0]
                         if (bb.size == 0):
                             bb0 = spec.size - 1 - m
                         else:
                             bb0 = bb[0] - 1
                             if (bb0 < 0):
                                 bb0 = 0
                         if (ss.size == 0):   ss1 = 1
                         else: ss1 = max(ss) + 1
                         if (ss1 > m):   ss1 = m
                         valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1
                         power = ((spec2[valid] - n0)*fwindow[valid]).sum()
                         fd = ((spec2[valid]- n0)*freq[valid]*fwindow[valid]).sum()/power
                         w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power)
                         snr = (spec2.mean()-n0)/n0
                         if (snr < 1.e-20) :
                             snr = 1.e-20
                         vec_power[ind] = power
                         vec_fd[ind] = fd
                         vec_w[ind] = w
                         vec_snr[ind] = snr
                     moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w))
                     return moments
                 #------------------    Get SA Parameters    --------------------------
                 def GetSAParameters(self):
                     #SA en frecuencia
                     pairslist = self.dataOut.groupList
                     num_pairs = len(pairslist)
                     vel = self.dataOut.abscissaList
                     spectra = self.dataOut.data_pre[0]
                     cspectra = self.dataOut.data_pre[1]
                     delta_v = vel[1] - vel[0]
                     #Calculating the power spectrum
                     spc_pow = numpy.sum(spectra, 3)*delta_v
                     #Normalizing Spectra
                     norm_spectra = spectra/spc_pow
                     #Calculating the norm_spectra at peak
                     max_spectra = numpy.max(norm_spectra, 3)
                     #Normalizing Cross Spectra
                     norm_cspectra = numpy.zeros(cspectra.shape)
                     for i in range(num_chan):
                         norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:])
                     max_cspectra = numpy.max(norm_cspectra,2)
                     max_cspectra_index = numpy.argmax(norm_cspectra, 2)
                     for i in range(num_pairs):
                         cspc_par[i,:,:] = __calculateMoments(norm_cspectra)
                 #-------------------    Get Lags    ----------------------------------
             class SALags(Operation):
                 '''
                 Function GetMoments()
                 Input:
                     self.dataOut.data_pre
                     self.dataOut.abscissaList
                     self.dataOut.noise
                     self.dataOut.normFactor
                     self.dataOut.data_SNR
                     self.dataOut.groupList
                     self.dataOut.nChannels
                 Affected:
                     self.dataOut.data_param
                 '''
                 def run(self, dataOut):
                     data_acf = dataOut.data_pre[0]
                     data_ccf = dataOut.data_pre[1]
                     normFactor_acf = dataOut.normFactor[0]
                     normFactor_ccf = dataOut.normFactor[1]
                     pairs_acf = dataOut.groupList[0]
                     pairs_ccf = dataOut.groupList[1]
                     nHeights = dataOut.nHeights
                     absc = dataOut.abscissaList
                     noise = dataOut.noise
                     SNR = dataOut.data_SNR
                     nChannels = dataOut.nChannels
             #         pairsList = dataOut.groupList
             #         pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels)
                     for l in range(len(pairs_acf)):
                         data_acf[l,:,:] = data_acf[l,:,:]/normFactor_acf[l,:]
                     for l in range(len(pairs_ccf)):
                         data_ccf[l,:,:] = data_ccf[l,:,:]/normFactor_ccf[l,:]
                     dataOut.data_param = numpy.zeros((len(pairs_ccf)*2 + 1, nHeights))
                     dataOut.data_param[:-1,:] = self.__calculateTaus(data_acf, data_ccf, absc)
                     dataOut.data_param[-1,:] = self.__calculateLag1Phase(data_acf, absc)
                     return
             #     def __getPairsAutoCorr(self, pairsList, nChannels):
             #
             #         pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan
             #
             #         for l in range(len(pairsList)):
             #             firstChannel = pairsList[l][0]
             #             secondChannel = pairsList[l][1]
             #
             #             #Obteniendo pares de Autocorrelacion
             #             if firstChannel == secondChannel:
             #                 pairsAutoCorr[firstChannel] = int(l)
             #
             #         pairsAutoCorr = pairsAutoCorr.astype(int)
             #
             #         pairsCrossCorr = range(len(pairsList))
             #         pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr)
             #
             #         return pairsAutoCorr, pairsCrossCorr
                 def __calculateTaus(self, data_acf, data_ccf, lagRange):
                     lag0 = data_acf.shape[1]/2
                     #Funcion de Autocorrelacion
                     mean_acf = stats.nanmean(data_acf, axis = 0)
                     #Obtencion Indice de TauCross
                     ind_ccf = data_ccf.argmax(axis = 1)
                     #Obtencion Indice de TauAuto
                     ind_acf = numpy.zeros(ind_ccf.shape,dtype = 'int')
                     ccf_lag0 = data_ccf[:,lag0,:]
                     for i in range(ccf_lag0.shape[0]):
                         ind_acf[i,:] = numpy.abs(mean_acf - ccf_lag0[i,:]).argmin(axis = 0)
                     #Obtencion de TauCross y TauAuto
                     tau_ccf = lagRange[ind_ccf]
                     tau_acf  = lagRange[ind_acf]
                     Nan1, Nan2 = numpy.where(tau_ccf == lagRange[0])
                     tau_ccf[Nan1,Nan2] = numpy.nan
                     tau_acf[Nan1,Nan2] = numpy.nan
                     tau = numpy.vstack((tau_ccf,tau_acf))
                     return tau
                 def __calculateLag1Phase(self, data, lagTRange):
                     data1 = stats.nanmean(data, axis = 0)
                     lag1 = numpy.where(lagTRange == 0)[0][0] + 1
                     phase = numpy.angle(data1[lag1,:])
                     return phase
             class SpectralFitting(Operation):
                 '''
                     Function GetMoments()
                     Input:
                     Output:
                     Variables modified:
                 '''
                 def run(self, dataOut, getSNR = True, path=None, file=None, groupList=None):
                     if path != None:
                         sys.path.append(path)
                     self.dataOut.library = importlib.import_module(file)
                     #To be inserted as a parameter
                     groupArray = numpy.array(groupList)
             #         groupArray = numpy.array([[0,1],[2,3]])
                     self.dataOut.groupList = groupArray
                     nGroups = groupArray.shape[0]
                     nChannels = self.dataIn.nChannels
                     nHeights=self.dataIn.heightList.size
                     #Parameters Array
                     self.dataOut.data_param = None
                     #Set constants
                     constants = self.dataOut.library.setConstants(self.dataIn)
                     self.dataOut.constants = constants
                     M = self.dataIn.normFactor
                     N = self.dataIn.nFFTPoints
                     ippSeconds = self.dataIn.ippSeconds
                     K = self.dataIn.nIncohInt
                     pairsArray = numpy.array(self.dataIn.pairsList)
                     #List of possible combinations
                     listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2)
                     indCross = numpy.zeros(len(list(listComb)), dtype = 'int')
                     if getSNR:
                         listChannels = groupArray.reshape((groupArray.size))
                         listChannels.sort()
                         noise = self.dataIn.getNoise()
                         self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels])
                     for i in range(nGroups):
                         coord = groupArray[i,:]
                         #Input data array
                         data = self.dataIn.data_spc[coord,:,:]/(M*N)
                         data = data.reshape((data.shape[0]*data.shape[1],data.shape[2]))
                         #Cross Spectra data array for Covariance Matrixes
                         ind = 0
                         for pairs in listComb:
                             pairsSel = numpy.array([coord[x],coord[y]])
                             indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0])
                             ind += 1
                         dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N)
                         dataCross = dataCross**2/K
                         for h in range(nHeights):
             #                 print self.dataOut.heightList[h]
                             #Input
                             d = data[:,h]
                             #Covariance Matrix
                             D = numpy.diag(d**2/K)
                             ind = 0
                             for pairs in listComb:
                                 #Coordinates in Covariance Matrix
                                 x = pairs[0]
                                 y = pairs[1]
                                 #Channel Index
                                 S12 = dataCross[ind,:,h]
                                 D12 = numpy.diag(S12)
                                 #Completing Covariance Matrix with Cross Spectras
                                 D[x*N:(x+1)*N,y*N:(y+1)*N] = D12
                                 D[y*N:(y+1)*N,x*N:(x+1)*N] = D12
                                 ind += 1
                             Dinv=numpy.linalg.inv(D)
                             L=numpy.linalg.cholesky(Dinv)
                             LT=L.T
                             dp = numpy.dot(LT,d)
                             #Initial values
                             data_spc = self.dataIn.data_spc[coord,:,h]
                             if (h>0)and(error1[3]<5):
                                 p0 = self.dataOut.data_param[i,:,h-1]
                             else:
                                 p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i))
                             try:
                                 #Least Squares
                                 minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True)
             #                   minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants))
                                 #Chi square error
                                 error0 = numpy.sum(infodict['fvec']**2)/(2*N)
                                 #Error with Jacobian
                                 error1 = self.dataOut.library.errorFunction(minp,constants,LT)
                             except:
                                 minp = p0*numpy.nan
                                 error0 = numpy.nan
                                 error1 = p0*numpy.nan
                             #Save
                             if self.dataOut.data_param is None:
                                 self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan
                                 self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan
                             self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1))
                             self.dataOut.data_param[i,:,h] = minp
                     return
                 def __residFunction(self, p, dp, LT, constants):
                     fm = self.dataOut.library.modelFunction(p, constants)
                     fmp=numpy.dot(LT,fm)
                     return  dp-fmp
                 def __getSNR(self, z, noise):
                     avg = numpy.average(z, axis=1)
                     SNR = (avg.T-noise)/noise
                     SNR = SNR.T
                     return SNR
                 def __chisq(p,chindex,hindex):
                     #similar to Resid but calculates CHI**2
                     [LT,d,fm]=setupLTdfm(p,chindex,hindex)
                     dp=numpy.dot(LT,d)
                     fmp=numpy.dot(LT,fm)
                     chisq=numpy.dot((dp-fmp).T,(dp-fmp))
                     return chisq
             class WindProfiler(Operation):
                 __isConfig = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 __firstdata = None
                 n = None
                 def __calculateCosDir(self, elev, azim):
                     zen = (90 - elev)*numpy.pi/180
                     azim = azim*numpy.pi/180
                     cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2)))
                     cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2)
                     signX = numpy.sign(numpy.cos(azim))
                     signY = numpy.sign(numpy.sin(azim))
                     cosDirX = numpy.copysign(cosDirX, signX)
                     cosDirY = numpy.copysign(cosDirY, signY)
                     return cosDirX, cosDirY
                 def __calculateAngles(self, theta_x, theta_y, azimuth):
                     dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2)
                     zenith_arr = numpy.arccos(dir_cosw)
                     azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180
                     dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr)
                     dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr)
                     return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw
                 def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly):
             #
                     if horOnly:
                         A = numpy.c_[dir_cosu,dir_cosv]
                     else:
                         A = numpy.c_[dir_cosu,dir_cosv,dir_cosw]
                     A = numpy.asmatrix(A)
                     A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose()
                     return A1
                 def __correctValues(self, heiRang, phi, velRadial, SNR):
                     listPhi = phi.tolist()
                     maxid = listPhi.index(max(listPhi))
                     minid = listPhi.index(min(listPhi))
                     rango = range(len(phi))
                #     rango = numpy.delete(rango,maxid)
                     heiRang1 = heiRang*math.cos(phi[maxid])
                     heiRangAux = heiRang*math.cos(phi[minid])
                     indOut = (heiRang1 < heiRangAux[0]).nonzero()
                     heiRang1 = numpy.delete(heiRang1,indOut)
                     velRadial1 = numpy.zeros([len(phi),len(heiRang1)])
                     SNR1 = numpy.zeros([len(phi),len(heiRang1)])
                     for i in rango:
                         x = heiRang*math.cos(phi[i])
                         y1 = velRadial[i,:]
                         f1 = interpolate.interp1d(x,y1,kind = 'cubic')
                         x1 = heiRang1
                         y11 = f1(x1)
                         y2 = SNR[i,:]
                         f2 = interpolate.interp1d(x,y2,kind = 'cubic')
                         y21 = f2(x1)
                         velRadial1[i,:] = y11
                         SNR1[i,:] = y21
                     return heiRang1, velRadial1, SNR1
                 def __calculateVelUVW(self, A, velRadial):
                     #Operacion Matricial
             #         velUVW = numpy.zeros((velRadial.shape[1],3))
             #         for ind in range(velRadial.shape[1]):
             #             velUVW[ind,:] = numpy.dot(A,velRadial[:,ind])
             #         velUVW = velUVW.transpose()
                     velUVW = numpy.zeros((A.shape[0],velRadial.shape[1]))
                     velUVW[:,:] = numpy.dot(A,velRadial)
                     return velUVW
             #     def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0):
                 def techniqueDBS(self, kwargs):
                     """
                     Function that implements Doppler Beam Swinging (DBS) technique.
                     Input:    Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth,
                                 Direction correction (if necessary), Ranges and SNR
                     Output:    Winds estimation (Zonal, Meridional and Vertical)
                     Parameters affected:    Winds, height range, SNR
                     """
                     velRadial0 = kwargs['velRadial']
                     heiRang = kwargs['heightList']
                     SNR0 = kwargs['SNR']
                     if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'):
                         theta_x = numpy.array(kwargs['dirCosx'])
                         theta_y = numpy.array(kwargs['dirCosy'])
                     else:
                         elev = numpy.array(kwargs['elevation'])
                         azim = numpy.array(kwargs['azimuth'])
                         theta_x, theta_y = self.__calculateCosDir(elev, azim)
                     azimuth = kwargs['correctAzimuth']
                     if kwargs.has_key('horizontalOnly'):
                         horizontalOnly = kwargs['horizontalOnly']
                     else:   horizontalOnly = False
                     if kwargs.has_key('correctFactor'):
                         correctFactor = kwargs['correctFactor']
                     else:   correctFactor = 1
                     if kwargs.has_key('channelList'):
                         channelList = kwargs['channelList']
                         if len(channelList) == 2:
                             horizontalOnly = True
                         arrayChannel = numpy.array(channelList)
                         param = param[arrayChannel,:,:]
                         theta_x = theta_x[arrayChannel]
                         theta_y = theta_y[arrayChannel]
                     azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(theta_x, theta_y, azimuth)
                     heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correctFactor*velRadial0, SNR0)
                     A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly)
                     #Calculo de Componentes de la velocidad con DBS
                     winds = self.__calculateVelUVW(A,velRadial1)
                     return winds, heiRang1, SNR1
                 def __calculateDistance(self, posx, posy, pairs_ccf, azimuth = None):
                     nPairs = len(pairs_ccf)
                     posx = numpy.asarray(posx)
                     posy = numpy.asarray(posy)
                     #Rotacion Inversa para alinear con el azimuth
                     if azimuth!= None:
                         azimuth = azimuth*math.pi/180
                         posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth)
                         posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth)
                     else:
                         posx1 = posx
                         posy1 = posy
                     #Calculo de Distancias
                     distx = numpy.zeros(nPairs)
                     disty = numpy.zeros(nPairs)
                     dist = numpy.zeros(nPairs)
                     ang = numpy.zeros(nPairs)
                     for i in range(nPairs):
                         distx[i] = posx1[pairs_ccf[i][1]] - posx1[pairs_ccf[i][0]]
                         disty[i] = posy1[pairs_ccf[i][1]] - posy1[pairs_ccf[i][0]]
                         dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2)
                         ang[i] = numpy.arctan2(disty[i],distx[i])
                     return distx, disty, dist, ang
                     #Calculo de Matrices
             #         nPairs = len(pairs)
             #         ang1 = numpy.zeros((nPairs, 2, 1))
             #         dist1 = numpy.zeros((nPairs, 2, 1))
             #
             #         for j in range(nPairs):
             #             dist1[j,0,0] = dist[pairs[j][0]]
             #             dist1[j,1,0] = dist[pairs[j][1]]
             #             ang1[j,0,0] = ang[pairs[j][0]]
             #             ang1[j,1,0] = ang[pairs[j][1]]
             #
             #         return distx,disty, dist1,ang1
                 def __calculateVelVer(self, phase, lagTRange, _lambda):
                     Ts = lagTRange[1] - lagTRange[0]
                     velW = -_lambda*phase/(4*math.pi*Ts)
                     return velW
                 def __calculateVelHorDir(self, dist, tau1, tau2, ang):
                     nPairs = tau1.shape[0]
                     nHeights = tau1.shape[1]
                     vel = numpy.zeros((nPairs,3,nHeights))
                     dist1 = numpy.reshape(dist, (dist.size,1))
                     angCos = numpy.cos(ang)
                     angSin = numpy.sin(ang)
                     vel0 = dist1*tau1/(2*tau2**2)
                     vel[:,0,:] = (vel0*angCos).sum(axis = 1)
                     vel[:,1,:] = (vel0*angSin).sum(axis = 1)
                     ind = numpy.where(numpy.isinf(vel))
                     vel[ind] = numpy.nan
                     return vel
             #     def __getPairsAutoCorr(self, pairsList, nChannels):
             #
             #         pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan
             #
             #         for l in range(len(pairsList)):
             #             firstChannel = pairsList[l][0]
             #             secondChannel = pairsList[l][1]
             #
             #             #Obteniendo pares de Autocorrelacion
             #             if firstChannel == secondChannel:
             #                 pairsAutoCorr[firstChannel] = int(l)
             #
             #         pairsAutoCorr = pairsAutoCorr.astype(int)
             #
             #         pairsCrossCorr = range(len(pairsList))
             #         pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr)
             #
             #         return pairsAutoCorr, pairsCrossCorr
             #     def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor):
                 def techniqueSA(self, kwargs):
                     """
                     Function that implements Spaced Antenna (SA) technique.
                     Input:    Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth,
                                 Direction correction (if necessary), Ranges and SNR
                     Output:    Winds estimation (Zonal, Meridional and Vertical)
                     Parameters affected:    Winds
                     """
                     position_x = kwargs['positionX']
                     position_y = kwargs['positionY']
                     azimuth = kwargs['azimuth']
                     if kwargs.has_key('correctFactor'):
                         correctFactor = kwargs['correctFactor']
                     else:
                         correctFactor = 1
                     groupList = kwargs['groupList']
                     pairs_ccf = groupList[1]
                     tau = kwargs['tau']
                     _lambda = kwargs['_lambda']
                     #Cross Correlation pairs obtained
             #         pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairssList, nChannels)
             #         pairsArray = numpy.array(pairsList)[pairsCrossCorr]
             #         pairsSelArray = numpy.array(pairsSelected)
             #         pairs = []
             #
             #         #Wind estimation pairs obtained
             #         for i in range(pairsSelArray.shape[0]/2):
             #             ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0]
             #             ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0]
             #             pairs.append((ind1,ind2))
                     indtau = tau.shape[0]/2
                     tau1 = tau[:indtau,:]
                     tau2 = tau[indtau:-1,:]
             #         tau1 = tau1[pairs,:]
             #         tau2 = tau2[pairs,:]
                     phase1 = tau[-1,:]
                     #---------------------------------------------------------------------
                     #Metodo Directo
                     distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairs_ccf,azimuth)
                     winds = self.__calculateVelHorDir(dist, tau1, tau2, ang)
                     winds = stats.nanmean(winds, axis=0)
                     #---------------------------------------------------------------------
                     #Metodo General
             #         distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth)
             #         #Calculo Coeficientes de Funcion de Correlacion
             #         F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n)
             #         #Calculo de Velocidades
             #         winds = self.calculateVelUV(F,G,A,B,H)
                     #---------------------------------------------------------------------
                     winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda)
                     winds = correctFactor*winds
                     return winds
                 def __checkTime(self, currentTime, paramInterval, outputInterval):
                     dataTime = currentTime + paramInterval
                     deltaTime = dataTime - self.__initime
                     if deltaTime >= outputInterval or deltaTime < 0:
                         self.__dataReady = True
                     return
                 def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax, binkm=2):
                     '''
                     Function that implements winds estimation technique with detected meteors.
                     Input:    Detected meteors, Minimum meteor quantity to wind estimation
                     Output:    Winds estimation (Zonal and Meridional)
                     Parameters affected:    Winds
                     '''
             #         print arrayMeteor.shape
                     #Settings
                     nInt = (heightMax - heightMin)/binkm
             #         print nInt
                     nInt = int(nInt)
             #         print nInt
                     winds = numpy.zeros((2,nInt))*numpy.nan
                     #Filter errors
                     error = numpy.where(arrayMeteor[:,-1] == 0)[0]
                     finalMeteor = arrayMeteor[error,:]
                     #Meteor Histogram
                     finalHeights = finalMeteor[:,2]
                     hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax))
                     nMeteorsPerI = hist[0]
                     heightPerI = hist[1]
                     #Sort of meteors
                     indSort = finalHeights.argsort()
                     finalMeteor2 = finalMeteor[indSort,:]
                     #    Calculating winds
                     ind1 = 0
                     ind2 = 0
                     for i in range(nInt):
                         nMet = nMeteorsPerI[i]
                         ind1 = ind2
                         ind2 = ind1 + nMet
                         meteorAux = finalMeteor2[ind1:ind2,:]
                         if meteorAux.shape[0] >= meteorThresh:
                             vel = meteorAux[:, 6]
                             zen = meteorAux[:, 4]*numpy.pi/180
                             azim = meteorAux[:, 3]*numpy.pi/180
                             n = numpy.cos(zen)
                     #         m = (1 - n**2)/(1 - numpy.tan(azim)**2)
                     #         l = m*numpy.tan(azim)
                             l = numpy.sin(zen)*numpy.sin(azim)
                             m = numpy.sin(zen)*numpy.cos(azim)
                             A = numpy.vstack((l, m)).transpose()
                             A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose())
                             windsAux = numpy.dot(A1, vel)
                             winds[0,i] = windsAux[0]
                             winds[1,i] = windsAux[1]
                     return winds, heightPerI[:-1]
                 def techniqueNSM_SA(self, **kwargs):
                     metArray = kwargs['metArray']
                     heightList = kwargs['heightList']
                     timeList = kwargs['timeList']
                     rx_location = kwargs['rx_location']
                     groupList = kwargs['groupList']
                     azimuth = kwargs['azimuth']
                     dfactor = kwargs['dfactor']
                     k = kwargs['k']
                     azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth)
                     d = dist*dfactor
                     #Phase calculation
                     metArray1 = self.__getPhaseSlope(metArray, heightList, timeList)
                     metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities
                     velEst = numpy.zeros((heightList.size,2))*numpy.nan
                     azimuth1 = azimuth1*numpy.pi/180
                     for i in range(heightList.size):
                         h = heightList[i]
                         indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0]
                         metHeight = metArray1[indH,:]
                         if metHeight.shape[0] >= 2:
                             velAux = numpy.asmatrix(metHeight[:,-2]).T    #Radial Velocities
                             iazim = metHeight[:,1].astype(int)
                             azimAux = numpy.asmatrix(azimuth1[iazim]).T    #Azimuths
                             A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux)))
                             A = numpy.asmatrix(A)
                             A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose()
                             velHor = numpy.dot(A1,velAux)
                             velEst[i,:] = numpy.squeeze(velHor)
                     return velEst
                 def __getPhaseSlope(self, metArray, heightList, timeList):
                     meteorList = []
                     #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2
                     #Putting back together the meteor matrix
                     utctime = metArray[:,0]
                     uniqueTime = numpy.unique(utctime)
                     phaseDerThresh = 0.5
                     ippSeconds = timeList[1] - timeList[0]
                     sec = numpy.where(timeList>1)[0][0]
                     nPairs = metArray.shape[1] - 6
                     nHeights = len(heightList)
                     for t in uniqueTime:
                         metArray1 = metArray[utctime==t,:]
             #         phaseDerThresh = numpy.pi/4 #reducir Phase thresh
                         tmet = metArray1[:,1].astype(int)
                         hmet = metArray1[:,2].astype(int)
                         metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1))
                         metPhase[:,:] = numpy.nan
                         metPhase[:,hmet,tmet] = metArray1[:,6:].T
                         #Delete short trails
                         metBool = ~numpy.isnan(metPhase[0,:,:])
                         heightVect = numpy.sum(metBool, axis = 1)
                         metBool[heightVect<sec,:] = False
                         metPhase[:,heightVect<sec,:] = numpy.nan
                         #Derivative
                         metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1])
                         phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh))
                         metPhase[phDerAux] = numpy.nan
                         #--------------------------METEOR DETECTION    -----------------------------------------
                         indMet = numpy.where(numpy.any(metBool,axis=1))[0]
                         for p in numpy.arange(nPairs):
                             phase = metPhase[p,:,:]
                             phDer = metDer[p,:,:]
                             for h in indMet:
                                 height = heightList[h]
                                 phase1 = phase[h,:] #82
                                 phDer1 = phDer[h,:]
                                 phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)])   #Unwrap
                                 indValid = numpy.where(~numpy.isnan(phase1))[0]
                                 initMet = indValid[0]
                                 endMet = 0
                                 for i in range(len(indValid)-1):
                                     #Time difference
                                     inow = indValid[i]
                                     inext = indValid[i+1]
                                     idiff = inext - inow
                                     #Phase difference
                                     phDiff = numpy.abs(phase1[inext] - phase1[inow])
                                     if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]:   #End of Meteor
                                         sizeTrail = inow - initMet + 1
                                         if sizeTrail>3*sec:  #Too short meteors
                                             x = numpy.arange(initMet,inow+1)*ippSeconds
                                             y = phase1[initMet:inow+1]
                                             ynnan = ~numpy.isnan(y)
                                             x = x[ynnan]
                                             y = y[ynnan]
                                             slope, intercept, r_value, p_value, std_err = stats.linregress(x,y)
                                             ylin = x*slope + intercept
                                             rsq = r_value**2
                                             if rsq > 0.5:
                                                 vel = slope#*height*1000/(k*d)
                                                 estAux = numpy.array([utctime,p,height, vel, rsq])
                                                 meteorList.append(estAux)
                                         initMet = inext
                     metArray2 = numpy.array(meteorList)
                     return metArray2
                 def __calculateAzimuth1(self, rx_location, pairslist, azimuth0):
                     azimuth1 = numpy.zeros(len(pairslist))
                     dist = numpy.zeros(len(pairslist))
                     for i in range(len(rx_location)):
                         ch0 = pairslist[i][0]
                         ch1 = pairslist[i][1]
                         diffX = rx_location[ch0][0] - rx_location[ch1][0]
                         diffY = rx_location[ch0][1] - rx_location[ch1][1]
                         azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi
                         dist[i] = numpy.sqrt(diffX**2 + diffY**2)
                     azimuth1 -= azimuth0
                     return azimuth1, dist
                 def techniqueNSM_DBS(self, **kwargs):
                     metArray = kwargs['metArray']
                     heightList = kwargs['heightList']
                     timeList = kwargs['timeList']
                     azimuth = kwargs['azimuth']
                     theta_x = numpy.array(kwargs['theta_x'])
                     theta_y = numpy.array(kwargs['theta_y'])
                     utctime = metArray[:,0]
                     cmet = metArray[:,1].astype(int)
                     hmet = metArray[:,3].astype(int)
                     SNRmet = metArray[:,4]
                     vmet = metArray[:,5]
                     spcmet = metArray[:,6]
                     nChan = numpy.max(cmet) + 1
                     nHeights = len(heightList)
                     azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(theta_x, theta_y, azimuth)
                     hmet = heightList[hmet]
                     h1met = hmet*numpy.cos(zenith_arr[cmet])      #Corrected heights
                     velEst = numpy.zeros((heightList.size,2))*numpy.nan
                     for i in range(nHeights - 1):
                         hmin = heightList[i]
                         hmax = heightList[i + 1]
                         thisH = (h1met>=hmin) & (h1met<hmax) & (cmet!=2) & (SNRmet>8) & (vmet<50) & (spcmet<10)
                         indthisH = numpy.where(thisH)
                         if numpy.size(indthisH) > 3:
                             vel_aux = vmet[thisH]
                             chan_aux = cmet[thisH]
                             cosu_aux = dir_cosu[chan_aux]
                             cosv_aux = dir_cosv[chan_aux]
                             cosw_aux = dir_cosw[chan_aux]
                             nch = numpy.size(numpy.unique(chan_aux))
                             if  nch > 1:
                                 A = self.__calculateMatA(cosu_aux, cosv_aux, cosw_aux, True)
                                 velEst[i,:] = numpy.dot(A,vel_aux)
                     return velEst
                 def run(self, dataOut, technique, nHours=1, hmin=70, hmax=110, **kwargs):
                     param = dataOut.data_param
                     if dataOut.abscissaList != None:
                         absc = dataOut.abscissaList[:-1]
                     # noise = dataOut.noise
                     heightList = dataOut.heightList
                     SNR = dataOut.data_SNR
                     if technique == 'DBS':
                         kwargs['velRadial'] = param[:,1,:] #Radial velocity
                         kwargs['heightList'] = heightList
                         kwargs['SNR'] = SNR
                         dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(kwargs) #DBS Function
                         dataOut.utctimeInit = dataOut.utctime
                         dataOut.outputInterval = dataOut.paramInterval
                     elif technique == 'SA':
                         #Parameters
             #             position_x = kwargs['positionX']
             #             position_y = kwargs['positionY']
             #             azimuth = kwargs['azimuth']
             #
             #             if kwargs.has_key('crosspairsList'):
             #                 pairs = kwargs['crosspairsList']
             #             else:
             #                 pairs = None
             #
             #             if kwargs.has_key('correctFactor'):
             #                 correctFactor = kwargs['correctFactor']
             #             else:
             #                 correctFactor = 1
             #             tau = dataOut.data_param
             #             _lambda = dataOut.C/dataOut.frequency
             #             pairsList = dataOut.groupList
             #             nChannels = dataOut.nChannels
                         kwargs['groupList'] = dataOut.groupList
                         kwargs['tau'] = dataOut.data_param
                         kwargs['_lambda'] = dataOut.C/dataOut.frequency
             #             dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor)
                         dataOut.data_output = self.techniqueSA(kwargs)
                         dataOut.utctimeInit = dataOut.utctime
                         dataOut.outputInterval = dataOut.timeInterval
                     elif technique == 'Meteors':
                         dataOut.flagNoData = True
                         self.__dataReady = False
                         if kwargs.has_key('nHours'):
                             nHours = kwargs['nHours']
                         else:
                             nHours = 1
                         if kwargs.has_key('meteorsPerBin'):
                             meteorThresh = kwargs['meteorsPerBin']
                         else:
                             meteorThresh = 6
                         if kwargs.has_key('hmin'):
                             hmin = kwargs['hmin']
                         else:   hmin = 70
                         if kwargs.has_key('hmax'):
                             hmax = kwargs['hmax']
                         else:   hmax = 110
                         if kwargs.has_key('BinKm'):
                             binkm = kwargs['BinKm']
                         else:
                             binkm = 2
                         dataOut.outputInterval = nHours*3600
                         if self.__isConfig == False:
             #                 self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03)
                             #Get Initial LTC time
                             self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime)
                             self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds()
                             self.__isConfig = True
                         if self.__buffer is None:
                             self.__buffer = dataOut.data_param
                             self.__firstdata = copy.copy(dataOut)
                         else:
                             self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param))
                         self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready
                         if self.__dataReady:
                             dataOut.utctimeInit = self.__initime
                             self.__initime += dataOut.outputInterval #to erase time offset
                             dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax, binkm)
                             dataOut.flagNoData = False
                             self.__buffer = None
                     elif technique == 'Meteors1':
                         dataOut.flagNoData = True
                         self.__dataReady = False
                         if kwargs.has_key('nMins'):
                             nMins = kwargs['nMins']
                         else: nMins = 20
                         if kwargs.has_key('rx_location'):
                             rx_location = kwargs['rx_location']
                         else: rx_location = [(0,1),(1,1),(1,0)]
                         if kwargs.has_key('azimuth'):
                             azimuth = kwargs['azimuth']
                         else: azimuth = 51.06
                         if kwargs.has_key('dfactor'):
                             dfactor = kwargs['dfactor']
                         if kwargs.has_key('mode'):
                             mode = kwargs['mode']
                         if kwargs.has_key('theta_x'):
                             theta_x = kwargs['theta_x']
                         if kwargs.has_key('theta_y'):
                             theta_y = kwargs['theta_y']
                         else: mode = 'SA'
                         #Borrar luego esto
                         if dataOut.groupList is None:
                             dataOut.groupList = [(0,1),(0,2),(1,2)]
                         groupList = dataOut.groupList
                         C = 3e8
                         freq = 50e6
                         lamb = C/freq
                         k = 2*numpy.pi/lamb
                         timeList = dataOut.abscissaList
                         heightList = dataOut.heightList
                         if self.__isConfig == False:
                             dataOut.outputInterval = nMins*60
             #                 self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03)
                             #Get Initial LTC time
                             initime = datetime.datetime.utcfromtimestamp(dataOut.utctime)
                             minuteAux = initime.minute
                             minuteNew = int(numpy.floor(minuteAux/nMins)*nMins)
                             self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds()
                             self.__isConfig = True
                         if self.__buffer is None:
                             self.__buffer = dataOut.data_param
                             self.__firstdata = copy.copy(dataOut)
                         else:
                             self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param))
                         self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready
                         if self.__dataReady:
                             dataOut.utctimeInit = self.__initime
                             self.__initime += dataOut.outputInterval #to erase time offset
                             metArray = self.__buffer
                             if mode == 'SA':
                                 dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList)
                             elif mode == 'DBS':
                                 dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList, azimuth=azimuth, theta_x=theta_x, theta_y=theta_y)
                             dataOut.data_output = dataOut.data_output.T
                             dataOut.flagNoData = False
                             self.__buffer = None
                     return
             class EWDriftsEstimation(Operation):
                 def __correctValues(self, heiRang, phi, velRadial, SNR):
                     listPhi = phi.tolist()
                     maxid = listPhi.index(max(listPhi))
                     minid = listPhi.index(min(listPhi))
                     rango = range(len(phi))
                #     rango = numpy.delete(rango,maxid)
                     heiRang1 = heiRang*math.cos(phi[maxid])
                     heiRangAux = heiRang*math.cos(phi[minid])
                     indOut = (heiRang1 < heiRangAux[0]).nonzero()
                     heiRang1 = numpy.delete(heiRang1,indOut)
                     velRadial1 = numpy.zeros([len(phi),len(heiRang1)])
                     SNR1 = numpy.zeros([len(phi),len(heiRang1)])
                     for i in rango:
                         x = heiRang*math.cos(phi[i])
                         y1 = velRadial[i,:]
                         f1 = interpolate.interp1d(x,y1,kind = 'cubic')
                         x1 = heiRang1
                         y11 = f1(x1)
                         y2 = SNR[i,:]
                         f2 = interpolate.interp1d(x,y2,kind = 'cubic')
                         y21 = f2(x1)
                         velRadial1[i,:] = y11
                         SNR1[i,:] = y21
                     return heiRang1, velRadial1, SNR1
                 def run(self, dataOut, zenith, zenithCorrection):
                     heiRang = dataOut.heightList
                     velRadial = dataOut.data_param[:,3,:]
                     SNR = dataOut.data_SNR
                     zenith = numpy.array(zenith)
                     zenith -= zenithCorrection
                     zenith *= numpy.pi/180
                     heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR)
                     alp = zenith[0]
                     bet = zenith[1]
                     w_w = velRadial1[0,:]
                     w_e = velRadial1[1,:]
                     w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp))
                     u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp))
                     winds = numpy.vstack((u,w))
                     dataOut.heightList = heiRang1
                     dataOut.data_output = winds
                     dataOut.data_SNR = SNR1
                     dataOut.utctimeInit = dataOut.utctime
                     dataOut.outputInterval = dataOut.timeInterval
                     return
             #---------------    Non Specular Meteor    ----------------
             class NonSpecularMeteorDetection(Operation):
                 def run(self, dataOut, mode, SNRthresh=8, phaseDerThresh=0.5, cohThresh=0.8, allData = False):
                     data_acf = dataOut.data_pre[0]
                     data_ccf = dataOut.data_pre[1]
                     pairsList = dataOut.groupList[1]
                     lamb = dataOut.C/dataOut.frequency
                     tSamp = dataOut.ippSeconds*dataOut.nCohInt
                     paramInterval = dataOut.paramInterval
                     nChannels = data_acf.shape[0]
                     nLags = data_acf.shape[1]
                     nProfiles = data_acf.shape[2]
                     nHeights = dataOut.nHeights
                     nCohInt = dataOut.nCohInt
                     sec = numpy.round(nProfiles/dataOut.paramInterval)
                     heightList = dataOut.heightList
                     ippSeconds = dataOut.ippSeconds*dataOut.nCohInt*dataOut.nAvg
                     utctime = dataOut.utctime
                     dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds)
                     #------------------------    SNR    --------------------------------------
                     power = data_acf[:,0,:,:].real
                     noise = numpy.zeros(nChannels)
                     SNR = numpy.zeros(power.shape)
                     for i in range(nChannels):
                         noise[i] = hildebrand_sekhon(power[i,:], nCohInt)
                         SNR[i] = (power[i]-noise[i])/noise[i]
                     SNRm = numpy.nanmean(SNR, axis = 0)
                     SNRdB = 10*numpy.log10(SNR)
                     if mode == 'SA':
                         dataOut.groupList = dataOut.groupList[1]
                         nPairs = data_ccf.shape[0]
                         #----------------------    Coherence and Phase   --------------------------
                         phase = numpy.zeros(data_ccf[:,0,:,:].shape)
             #             phase1 = numpy.copy(phase)
                         coh1 = numpy.zeros(data_ccf[:,0,:,:].shape)
                         for p in range(nPairs):
                             ch0 = pairsList[p][0]
                             ch1 = pairsList[p][1]
                             ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:])
                             phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter
             #                 phase1[p,:,:] = numpy.angle(ccf) #median filter
                             coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter
             #                 coh1[p,:,:] = numpy.abs(ccf) #median filter
                         coh = numpy.nanmax(coh1, axis = 0)
             #             struc = numpy.ones((5,1))
             #             coh = ndimage.morphology.grey_dilation(coh, size=(10,1))
                         #----------------------    Radial Velocity    ----------------------------
                         phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0)
                         velRad = phaseAux*lamb/(4*numpy.pi*tSamp)
                         if allData:
                             boolMetFin = ~numpy.isnan(SNRm)
             #                 coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0)
                         else:
                             #------------------------    Meteor mask    ---------------------------------
             #                 #SNR mask
             #                 boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB))
             #
             #                 #Erase small objects
             #                 boolMet1 = self.__erase_small(boolMet, 2*sec, 5)
             #
             #                 auxEEJ = numpy.sum(boolMet1,axis=0)
             #                 indOver = auxEEJ>nProfiles*0.8  #Use this later
             #                 indEEJ = numpy.where(indOver)[0]
             #                 indNEEJ = numpy.where(~indOver)[0]
             #
             #                 boolMetFin = boolMet1
             #
             #                 if indEEJ.size > 0:
             #                     boolMet1[:,indEEJ] = False  #Erase heights with EEJ
             #
             #                     boolMet2 = coh > cohThresh
             #                     boolMet2 = self.__erase_small(boolMet2, 2*sec,5)
             #
             #                     #Final Meteor mask
             #                     boolMetFin = boolMet1|boolMet2
                             #Coherence mask
                             boolMet1 = coh > 0.75
                             struc = numpy.ones((30,1))
                             boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc)
                             #Derivative mask
                             derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0)
                             boolMet2 = derPhase < 0.2
             #                 boolMet2 = ndimage.morphology.binary_opening(boolMet2)
             #                 boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1)))
                             boolMet2 = ndimage.median_filter(boolMet2,size=5)
                             boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool)))
             #                 #Final mask
             #                 boolMetFin = boolMet2
                             boolMetFin = boolMet1&boolMet2
             #                 boolMetFin = ndimage.morphology.binary_dilation(boolMetFin)
                         #Creating data_param
                         coordMet = numpy.where(boolMetFin)
                         tmet = coordMet[0]
                         hmet = coordMet[1]
                         data_param = numpy.zeros((tmet.size, 6 + nPairs))
                         data_param[:,0] = utctime
                         data_param[:,1] = tmet
                         data_param[:,2] = hmet
                         data_param[:,3] = SNRm[tmet,hmet]
                         data_param[:,4] = velRad[tmet,hmet]
                         data_param[:,5] = coh[tmet,hmet]
                         data_param[:,6:] = phase[:,tmet,hmet].T
                     elif mode == 'DBS':
                         dataOut.groupList = numpy.arange(nChannels)
                         #Radial Velocities
                         phase = numpy.angle(data_acf[:,1,:,:])
             #             phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1))
                         velRad = phase*lamb/(4*numpy.pi*tSamp)
                         #Spectral width
             #             acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1))
             #             acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1))
                         acf1 = data_acf[:,1,:,:]
                         acf2 = data_acf[:,2,:,:]
                         spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2))
             #             velRad = ndimage.median_filter(velRad, size = (1,5,1))
                         if allData:
                             boolMetFin = ~numpy.isnan(SNRdB)
                         else:
                             #SNR
                             boolMet1 = (SNRdB>SNRthresh) #SNR mask
                             boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5))
                             #Radial velocity
                             boolMet2 = numpy.abs(velRad) < 20
                             boolMet2 = ndimage.median_filter(boolMet2, (1,5,5))
                             #Spectral Width
                             boolMet3 = spcWidth < 30
                             boolMet3 = ndimage.median_filter(boolMet3, (1,5,5))
             #                 boolMetFin = self.__erase_small(boolMet1, 10,5)
                             boolMetFin = boolMet1&boolMet2&boolMet3
                         #Creating data_param
                         coordMet = numpy.where(boolMetFin)
                         cmet = coordMet[0]
                         tmet = coordMet[1]
                         hmet = coordMet[2]
                         data_param = numpy.zeros((tmet.size, 7))
                         data_param[:,0] = utctime
                         data_param[:,1] = cmet
                         data_param[:,2] = tmet
                         data_param[:,3] = hmet
                         data_param[:,4] = SNR[cmet,tmet,hmet].T
                         data_param[:,5] = velRad[cmet,tmet,hmet].T
                         data_param[:,6] = spcWidth[cmet,tmet,hmet].T
             #         self.dataOut.data_param = data_int
                     if len(data_param) == 0:
                         dataOut.flagNoData = True
                     else:
                         dataOut.data_param = data_param
                 def __erase_small(self, binArray, threshX, threshY):
                     labarray, numfeat = ndimage.measurements.label(binArray)
                     binArray1 = numpy.copy(binArray)
                     for i in range(1,numfeat + 1):
                         auxBin = (labarray==i)
                         auxSize = auxBin.sum()
                         x,y = numpy.where(auxBin)
                         widthX = x.max() - x.min()
                         widthY = y.max() - y.min()
                         #width X: 3 seg -> 12.5*3
                         #width Y:
                         if (auxSize < 50) or (widthX < threshX) or (widthY < threshY):
                             binArray1[auxBin] = False
                     return binArray1
             #---------------    Specular Meteor    ----------------
             class SMDetection(Operation):
                 '''
                     Function DetectMeteors()
                         Project developed with paper:
                         HOLDSWORTH ET AL. 2004
                     Input:
                         self.dataOut.data_pre
                         centerReceiverIndex:      From the channels, which is the center receiver
                         hei_ref:                  Height reference for the Beacon signal extraction
                         tauindex:
                         predefinedPhaseShifts:    Predefined phase offset for the voltge signals
                         cohDetection:             Whether to user Coherent detection or not
                         cohDet_timeStep:          Coherent Detection calculation time step
                         cohDet_thresh:            Coherent Detection phase threshold to correct phases
                         noise_timeStep:           Noise calculation time step
                         noise_multiple:           Noise multiple to define signal threshold
                         multDet_timeLimit:        Multiple Detection Removal time limit in seconds
                         multDet_rangeLimit:       Multiple Detection Removal range limit in km
                         phaseThresh:              Maximum phase difference between receiver to be consider a meteor
                         SNRThresh:                Minimum SNR threshold of the meteor signal to be consider a meteor
                         hmin:                     Minimum Height of the meteor to use it in the further wind estimations
                         hmax:                     Maximum Height of the meteor to use it in the further wind estimations
                         azimuth:                  Azimuth angle correction
                     Affected:
                         self.dataOut.data_param
                     Rejection Criteria (Errors):
 : No error; analysis OK
 : SNR < SNR threshold
 : angle of arrival (AOA) ambiguously determined
 : AOA estimate not feasible
 : Large difference in AOAs obtained from different antenna baselines
 : echo at start or end of time series
 : echo less than 5 examples long; too short for analysis
 : echo rise exceeds 0.3s
 : echo decay time less than twice rise time
 : large power level before echo
 : large power level after echo
 : poor fit to amplitude for estimation of decay time
 : poor fit to CCF phase variation for estimation of radial drift velocity
 : height unresolvable echo: not valid height within 70 to 110 km
 : height ambiguous echo: more then one possible height within 70 to 110 km
 : radial drift velocity or projected horizontal velocity exceeds 200 m/s
 : oscilatory echo, indicating event most likely not an underdense echo
 : phase difference in meteor Reestimation
                     Data Storage:
                         Meteors for Wind Estimation   (8):
                         Utc Time   |    Range    Height
                         Azimuth    Zenith    errorCosDir
                         VelRad    errorVelRad
                         Phase0 Phase1 Phase2 Phase3
                         TypeError
                      '''
                 def run(self, dataOut, hei_ref = None, tauindex = 0,
                                   phaseOffsets = None,
                                   cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25,
                                   noise_timeStep = 4, noise_multiple = 4,
                                   multDet_timeLimit = 1, multDet_rangeLimit = 3,
                                   phaseThresh = 20, SNRThresh = 5,
                                   hmin = 50, hmax=150, azimuth = 0,
                                   channelPositions = None) :
                     #Getting Pairslist
                     if channelPositions is None:
             #             channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)]   #T
                         channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)]   #Estrella
                     meteorOps = SMOperations()
                     pairslist0, distances = meteorOps.getPhasePairs(channelPositions)
                     heiRang = dataOut.getHeiRange()
                     #Get Beacon signal - No Beacon signal anymore
             #         newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
             #
             #         if hei_ref != None:
             #             newheis = numpy.where(self.dataOut.heightList>hei_ref)
             #
                     #****************REMOVING HARDWARE PHASE DIFFERENCES***************
                     # see if the user put in pre defined phase shifts
                     voltsPShift = dataOut.data_pre.copy()
             #         if predefinedPhaseShifts != None:
             #             hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180
             #
             # #         elif beaconPhaseShifts:
             # #             #get hardware phase shifts using beacon signal
             # #             hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10)
             # #             hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0)
             #
             #         else:
             #             hardwarePhaseShifts = numpy.zeros(5)
             #
             #         voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex')
             #         for i in range(self.dataOut.data_pre.shape[0]):
             #             voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i])
                     #******************END OF REMOVING HARDWARE PHASE DIFFERENCES*********
                     #Remove DC
                     voltsDC = numpy.mean(voltsPShift,1)
                     voltsDC = numpy.mean(voltsDC,1)
                     for i in range(voltsDC.shape[0]):
                         voltsPShift[i] = voltsPShift[i] - voltsDC[i]
                     #Don't considerate last heights, theyre used to calculate Hardware Phase Shift
             #         voltsPShift = voltsPShift[:,:,:newheis[0][0]]
                     #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) **********
                     #Coherent Detection
                     if cohDetection:
                         #use coherent detection to get the net power
                         cohDet_thresh = cohDet_thresh*numpy.pi/180
                         voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, dataOut.timeInterval, pairslist0, cohDet_thresh)
                     #Non-coherent detection!
                     powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0)
                     #********** END OF COH/NON-COH POWER CALCULATION**********************
                     #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS ****************
                     #Get noise
                     noise, noise1 = self.__getNoise(powerNet, noise_timeStep, dataOut.timeInterval)
             #         noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval)
                     #Get signal threshold
                     signalThresh = noise_multiple*noise
                     #Meteor echoes detection
                     listMeteors = self.__findMeteors(powerNet, signalThresh)
                     #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION **********
                     #************** REMOVE MULTIPLE DETECTIONS (3.5) ***************************
                     #Parameters
                     heiRange = dataOut.getHeiRange()
                     rangeInterval = heiRange[1] - heiRange[0]
                     rangeLimit = multDet_rangeLimit/rangeInterval
                     timeLimit = multDet_timeLimit/dataOut.timeInterval
                     #Multiple detection removals
                     listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit)
                     #************ END OF REMOVE MULTIPLE DETECTIONS **********************
                     #*********************     METEOR REESTIMATION  (3.7, 3.8, 3.9, 3.10)   ********************
                     #Parameters
                     phaseThresh = phaseThresh*numpy.pi/180
                     thresh = [phaseThresh, noise_multiple, SNRThresh]
                     #Meteor reestimation  (Errors N 1, 6, 12, 17)
                     listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist0, thresh, noise, dataOut.timeInterval, dataOut.frequency)
             #         listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise)
                     #Estimation of decay times (Errors N 7, 8, 11)
                     listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, dataOut.timeInterval, dataOut.frequency)
                     #*******************     END OF METEOR REESTIMATION    *******************
                     #*********************    METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13)    **************************
                     #Calculating Radial Velocity (Error N 15)
                     radialStdThresh = 10
                     listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist0, dataOut.timeInterval)
                     if len(listMeteors4) > 0:
                         #Setting New Array
                         date = dataOut.utctime
                         arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang)
                         #Correcting phase offset
                         if phaseOffsets != None:
                             phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180
                             arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets)
                         #Second Pairslist
                         pairsList = []
                         pairx = (0,1)
                         pairy = (2,3)
                         pairsList.append(pairx)
                         pairsList.append(pairy)
                         jph = numpy.array([0,0,0,0])
                         h = (hmin,hmax)
                         arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph)
             #             #Calculate AOA (Error N 3, 4)
             #             #JONES ET AL. 1998
             #             error = arrayParameters[:,-1]
             #             AOAthresh = numpy.pi/8
             #             phases = -arrayParameters[:,9:13]
             #             arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth)
             #
             #             #Calculate Heights (Error N 13 and 14)
             #             error = arrayParameters[:,-1]
             #             Ranges = arrayParameters[:,2]
             #             zenith = arrayParameters[:,5]
             #             arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax)
             #             error = arrayParameters[:,-1]
                     #*********************    END OF PARAMETERS CALCULATION    **************************
                     #***************************+     PASS DATA TO NEXT STEP    **********************
             #             arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1]))
                         dataOut.data_param = arrayParameters
                         if arrayParameters is None:
                             dataOut.flagNoData = True
                     else:
                         dataOut.flagNoData = True
                     return
                 def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n):
                     minIndex = min(newheis[0])
                     maxIndex = max(newheis[0])
                     voltage = voltage0[:,:,minIndex:maxIndex+1]
                     nLength = voltage.shape[1]/n
                     nMin = 0
                     nMax = 0
                     phaseOffset = numpy.zeros((len(pairslist),n))
                     for i in range(n):
                         nMax += nLength
                         phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0]))
                         phaseCCF = numpy.mean(phaseCCF, axis = 2)
                         phaseOffset[:,i] = phaseCCF.transpose()
                         nMin = nMax
             #         phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist)
                     #Remove Outliers
                     factor = 2
                     wt = phaseOffset - signal.medfilt(phaseOffset,(1,5))
                     dw = numpy.std(wt,axis = 1)
                     dw = dw.reshape((dw.size,1))
                     ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor))
                     phaseOffset[ind] = numpy.nan
                     phaseOffset = stats.nanmean(phaseOffset, axis=1)
                     return phaseOffset
                 def __shiftPhase(self, data, phaseShift):
                     #this will shift the phase of a complex number
                     dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j)
                     return dataShifted
                 def __estimatePhaseDifference(self, array, pairslist):
                     nChannel = array.shape[0]
                     nHeights = array.shape[2]
                     numPairs = len(pairslist)
             #         phaseCCF = numpy.zeros((nChannel, 5, nHeights))
                     phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2]))
                     #Correct phases
                     derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:]
                     indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi)
                     if indDer[0].shape[0] > 0:
                         for i in range(indDer[0].shape[0]):
                             signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]])
                             phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi
             #         for j in range(numSides):
             #             phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2])
             #             phaseCCF[j,:,:] = numpy.angle(phaseCCFAux)
             #
                     #Linear
                     phaseInt = numpy.zeros((numPairs,1))
                     angAllCCF = phaseCCF[:,[0,1,3,4],0]
                     for j in range(numPairs):
                         fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:])
                         phaseInt[j] = fit[1]
                     #Phase Differences
                     phaseDiff = phaseInt - phaseCCF[:,2,:]
                     phaseArrival = phaseInt.reshape(phaseInt.size)
                     #Dealias
                     phaseArrival = numpy.angle(numpy.exp(1j*phaseArrival))
             #         indAlias = numpy.where(phaseArrival > numpy.pi)
             #         phaseArrival[indAlias] -= 2*numpy.pi
             #         indAlias = numpy.where(phaseArrival < -numpy.pi)
             #         phaseArrival[indAlias] += 2*numpy.pi
                     return phaseDiff, phaseArrival
                 def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh):
                     #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power
                     #find the phase shifts of each channel over 1 second intervals
                     #only look at ranges below the beacon signal
                     numProfPerBlock = numpy.ceil(timeSegment/timeInterval)
                     numBlocks = int(volts.shape[1]/numProfPerBlock)
                     numHeights = volts.shape[2]
                     nChannel = volts.shape[0]
                     voltsCohDet = volts.copy()
                     pairsarray = numpy.array(pairslist)
                     indSides = pairsarray[:,1]
             #         indSides = numpy.array(range(nChannel))
             #         indSides = numpy.delete(indSides, indCenter)
             #
             #         listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0)
                     listBlocks = numpy.array_split(volts, numBlocks, 1)
                     startInd = 0
                     endInd = 0
                     for i in range(numBlocks):
                         startInd = endInd
                         endInd = endInd + listBlocks[i].shape[1]
                         arrayBlock = listBlocks[i]
             #             arrayBlockCenter = listCenter[i]
                         #Estimate the Phase Difference
                         phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist)
                         #Phase Difference RMS
                         arrayPhaseRMS = numpy.abs(phaseDiff)
                         phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0)
                         indPhase = numpy.where(phaseRMSaux==4)
                         #Shifting
                         if indPhase[0].shape[0] > 0:
                             for j in range(indSides.size):
                                 arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose())
                             voltsCohDet[:,startInd:endInd,:] = arrayBlock
                     return voltsCohDet
                 def __calculateCCF(self, volts, pairslist ,laglist):
                     nHeights = volts.shape[2]
                     nPoints = volts.shape[1]
                     voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex')
                     for i in range(len(pairslist)):
                         volts1 = volts[pairslist[i][0]]
                         volts2 = volts[pairslist[i][1]]
                         for t in range(len(laglist)):
                             idxT = laglist[t]
                             if idxT >= 0:
                                 vStacked = numpy.vstack((volts2[idxT:,:],
                                                        numpy.zeros((idxT, nHeights),dtype='complex')))
                             else:
                                 vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'),
                                                        volts2[:(nPoints + idxT),:]))
                             voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0)
                             vStacked = None
                     return voltsCCF
                 def __getNoise(self, power, timeSegment, timeInterval):
                     numProfPerBlock = numpy.ceil(timeSegment/timeInterval)
                     numBlocks = int(power.shape[0]/numProfPerBlock)
                     numHeights = power.shape[1]
                     listPower = numpy.array_split(power, numBlocks, 0)
                     noise = numpy.zeros((power.shape[0], power.shape[1]))
                     noise1 = numpy.zeros((power.shape[0], power.shape[1]))
                     startInd = 0
                     endInd = 0
                     for i in range(numBlocks):             #split por canal
                         startInd = endInd
                         endInd = endInd + listPower[i].shape[0]
                         arrayBlock = listPower[i]
                         noiseAux = numpy.mean(arrayBlock, 0)
             #             noiseAux = numpy.median(noiseAux)
             #             noiseAux = numpy.mean(arrayBlock)
                         noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux
                         noiseAux1 = numpy.mean(arrayBlock)
                         noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1
                     return noise, noise1
                 def __findMeteors(self, power, thresh):
                     nProf = power.shape[0]
                     nHeights = power.shape[1]
                     listMeteors = []
                     for i in range(nHeights):
                         powerAux = power[:,i]
                         threshAux = thresh[:,i]
                         indUPthresh = numpy.where(powerAux > threshAux)[0]
                         indDNthresh = numpy.where(powerAux <= threshAux)[0]
                         j = 0
                         while (j < indUPthresh.size - 2):
                             if (indUPthresh[j + 2] == indUPthresh[j] + 2):
                                 indDNAux = numpy.where(indDNthresh > indUPthresh[j])
                                 indDNthresh = indDNthresh[indDNAux]
                                 if (indDNthresh.size > 0):
                                     indEnd = indDNthresh[0] - 1
                                     indInit = indUPthresh[j] if isinstance(indUPthresh[j], (int, float)) else indUPthresh[j][0] ##CHECK!!!!
                                     meteor = powerAux[indInit:indEnd + 1]
                                     indPeak = meteor.argmax() + indInit
                                     FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0)))
                                     listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!!
                                     j = numpy.where(indUPthresh == indEnd)[0] + 1
                                 else: j+=1
                             else: j+=1
                     return listMeteors
                 def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit):
                     arrayMeteors = numpy.asarray(listMeteors)
                     listMeteors1 = []
                     while arrayMeteors.shape[0] > 0:
                         FLAs = arrayMeteors[:,4]
                         maxFLA = FLAs.argmax()
                         listMeteors1.append(arrayMeteors[maxFLA,:])
                         MeteorInitTime = arrayMeteors[maxFLA,1]
                         MeteorEndTime = arrayMeteors[maxFLA,3]
                         MeteorHeight = arrayMeteors[maxFLA,0]
                         #Check neighborhood
                         maxHeightIndex = MeteorHeight + rangeLimit
                         minHeightIndex = MeteorHeight - rangeLimit
                         minTimeIndex = MeteorInitTime - timeLimit
                         maxTimeIndex = MeteorEndTime + timeLimit
                         #Check Heights
                         indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex)
                         indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex)
                         indBoth = numpy.where(numpy.logical_and(indTime,indHeight))
                         arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0)
                     return listMeteors1
                 def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency):
                     numHeights = volts.shape[2]
                     nChannel = volts.shape[0]
                     thresholdPhase = thresh[0]
                     thresholdNoise = thresh[1]
                     thresholdDB = float(thresh[2])
                     thresholdDB1 = 10**(thresholdDB/10)
                     pairsarray = numpy.array(pairslist)
                     indSides = pairsarray[:,1]
                     pairslist1 = list(pairslist)
                     pairslist1.append((0,4))
                     pairslist1.append((1,3))
                     listMeteors1 = []
                     listPowerSeries = []
                     listVoltageSeries = []
                     #volts has the war data
                     if frequency == 30.175e6:
                         timeLag = 45*10**-3
                     else:
                         timeLag = 15*10**-3
                     lag = int(numpy.ceil(timeLag/timeInterval))
                     for i in range(len(listMeteors)):
                         ######################   3.6 - 3.7 PARAMETERS REESTIMATION    #########################
                         meteorAux = numpy.zeros(16)
                         #Loading meteor Data (mHeight, mStart, mPeak, mEnd)
                         mHeight = int(listMeteors[i][0])
                         mStart = int(listMeteors[i][1])
                         mPeak = int(listMeteors[i][2])
                         mEnd = int(listMeteors[i][3])
                         #get the volt data between the start and end times of the meteor
                         meteorVolts = volts[:,mStart:mEnd+1,mHeight]
                         meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1)
                         #3.6. Phase Difference estimation
                         phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist)
                         #3.7. Phase difference removal & meteor start, peak and end times reestimated
                         #meteorVolts0.- all Channels, all Profiles
                         meteorVolts0 = volts[:,:,mHeight]
                         meteorThresh = noise[:,mHeight]*thresholdNoise
                         meteorNoise = noise[:,mHeight]
                         meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting
                         powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0)  #Power
                         #Times reestimation
                         mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0]
                         if mStart1.size > 0:
                             mStart1 = mStart1[-1] + 1
                         else:
                             mStart1 = mPeak
                         mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1
                         mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0]
                         if mEndDecayTime1.size == 0:
                             mEndDecayTime1 = powerNet0.size
                         else:
                             mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1
             #             mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax()
                         #meteorVolts1.- all Channels, from start to end
                         meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1]
                         meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1]
                         if meteorVolts2.shape[1] == 0:
                             meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1]
                         meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1)
                         meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1)
                         #####################    END PARAMETERS REESTIMATION    #########################
                         #####################   3.8 PHASE DIFFERENCE REESTIMATION  ########################
             #             if mEnd1 - mStart1 > 4:       #Error Number 6: echo less than 5 samples long; too short for analysis
                         if meteorVolts2.shape[1] > 0:
                             #Phase Difference re-estimation
                             phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1)   #Phase Difference Estimation
             #                 phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist)
                             meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1])
                             phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1))
                             meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4])     #Phase Shifting
                             #Phase Difference RMS
                             phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1)))
                             powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0)
                             #Data from Meteor
                             mPeak1 = powerNet1.argmax() + mStart1
                             mPeakPower1 = powerNet1.max()
                             noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight])
                             mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux
                             Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1])
                             Meteor1 = numpy.hstack((Meteor1,phaseDiffint))
                             PowerSeries  = powerNet0[mStart1:mEndDecayTime1 + 1]
                             #Vectorize
                             meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]
                             meteorAux[7:11] = phaseDiffint[0:4]
                             #Rejection Criterions
                             if phaseRMS1 > thresholdPhase:  #Error Number 17: Phase variation
                                 meteorAux[-1] = 17
                             elif mSNR1 < thresholdDB1:      #Error Number 1: SNR < threshold dB
                                 meteorAux[-1] = 1
                         else:
                             meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd]
                             meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis
                             PowerSeries = 0
                         listMeteors1.append(meteorAux)
                         listPowerSeries.append(PowerSeries)
                         listVoltageSeries.append(meteorVolts1)
                     return listMeteors1, listPowerSeries, listVoltageSeries
                 def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency):
                     threshError = 10
                     #Depending if it is 30 or 50 MHz
                     if frequency == 30.175e6:
                         timeLag = 45*10**-3
                     else:
                         timeLag = 15*10**-3
                     lag = int(numpy.ceil(timeLag/timeInterval))
                     listMeteors1 = []
                     for i in range(len(listMeteors)):
                         meteorPower = listPower[i]
                         meteorAux = listMeteors[i]
                         if meteorAux[-1] == 0:
                             try:
                                 indmax = meteorPower.argmax()
                                 indlag = indmax + lag
                                 y = meteorPower[indlag:]
                                 x = numpy.arange(0, y.size)*timeLag
                                 #first guess
                                 a = y[0]
                                 tau = timeLag
                                 #exponential fit
                                 popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau])
                                 y1 = self.__exponential_function(x, *popt)
                                 #error estimation
                                 error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size))
                                 decayTime = popt[1]
                                 riseTime = indmax*timeInterval
                                 meteorAux[11:13] = [decayTime, error]
                                 #Table items 7, 8 and 11
                                 if (riseTime > 0.3):            #Number 7: Echo rise exceeds 0.3s
                                     meteorAux[-1] = 7
                                 elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time
                                     meteorAux[-1] = 8
                                 if (error > threshError):       #Number 11: Poor fit to amplitude for estimation of decay time
                                     meteorAux[-1] = 11
                             except:
                                 meteorAux[-1] = 11
                         listMeteors1.append(meteorAux)
                     return listMeteors1
                 #Exponential Function
                 def __exponential_function(self, x, a, tau):
                     y = a*numpy.exp(-x/tau)
                     return y
                 def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist,  timeInterval):
                     pairslist1 = list(pairslist)
                     pairslist1.append((0,4))
                     pairslist1.append((1,3))
                     numPairs = len(pairslist1)
                     #Time Lag
                     timeLag = 45*10**-3
                     c = 3e8
                     lag = numpy.ceil(timeLag/timeInterval)
                     freq = 30.175e6
                     listMeteors1 = []
                     for i in range(len(listMeteors)):
                         meteorAux = listMeteors[i]
                         if meteorAux[-1] == 0:
                             mStart = listMeteors[i][1]
                             mPeak = listMeteors[i][2]
                             mLag = mPeak - mStart + lag
                             #get the volt data between the start and end times of the meteor
                             meteorVolts = listVolts[i]
                             meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1)
                             #Get CCF
                             allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2])
                             #Method 2
                             slopes = numpy.zeros(numPairs)
                             time = numpy.array([-2,-1,1,2])*timeInterval
                             angAllCCF = numpy.angle(allCCFs[:,[0,4,2,3],0])
                             #Correct phases
                             derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1]
                             indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi)
                             if indDer[0].shape[0] > 0:
                                 for i in range(indDer[0].shape[0]):
                                     signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]])
                                     angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi
             #                     fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]]))
                             for j in range(numPairs):
                                 fit = stats.linregress(time, angAllCCF[j,:])
                                 slopes[j] = fit[0]
                             #Remove Outlier
             #                 indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes)))
             #                 slopes = numpy.delete(slopes,indOut)
             #                 indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes)))
             #                 slopes = numpy.delete(slopes,indOut)
                             radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq)
                             radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq)
                             meteorAux[-2] = radialError
                             meteorAux[-3] = radialVelocity
                             #Setting Error
                             #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s
                             if numpy.abs(radialVelocity) > 200:
                                 meteorAux[-1] = 15
                             #Number 12: Poor fit to CCF variation for estimation of radial drift velocity
                             elif radialError > radialStdThresh:
                                 meteorAux[-1] = 12
                         listMeteors1.append(meteorAux)
                     return listMeteors1
                 def __setNewArrays(self, listMeteors, date, heiRang):
                     #New arrays
                     arrayMeteors = numpy.array(listMeteors)
                     arrayParameters = numpy.zeros((len(listMeteors), 13))
                     #Date inclusion
             #         date = re.findall(r'\((.*?)\)', date)
             #         date = date[0].split(',')
             #         date = map(int, date)
             #
             #         if len(date)<6:
             #             date.append(0)
             #
             #         date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]]
             #         arrayDate = numpy.tile(date, (len(listMeteors), 1))
                     arrayDate = numpy.tile(date, (len(listMeteors)))
                     #Meteor array
             #         arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)]
             #         arrayMeteors = numpy.hstack((arrayDate, arrayMeteors))
                     #Parameters Array
                     arrayParameters[:,0] = arrayDate #Date
                     arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range
                     arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error
                     arrayParameters[:,8:12] = arrayMeteors[:,7:11]  #Phases
                     arrayParameters[:,-1] = arrayMeteors[:,-1]  #Error
                     return arrayParameters
             class CorrectSMPhases(Operation):
+                parameters = {
+                    'phaseOffsets': global_type_pairsList,
+                    'hmin': global_type_float,
+                    'hmax': global_type_float,
+                    'azimuth': global_type_float,
+                    'channelPositions': global_type_pairsList,
+                }
                 def run(self, dataOut, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45, channelPositions = None):
                     arrayParameters = dataOut.data_param
                     pairsList = []
                     pairx = (0,1)
                     pairy = (2,3)
                     pairsList.append(pairx)
                     pairsList.append(pairy)
                     jph = numpy.zeros(4)
                     phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180
                 #         arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets)
                     arrayParameters[:,8:12] = numpy.angle(numpy.exp(1j*(arrayParameters[:,8:12] + phaseOffsets)))
                     meteorOps = SMOperations()
                     if channelPositions is None:
                 #             channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)]   #T
                         channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)]   #Estrella
                     pairslist0, distances = meteorOps.getPhasePairs(channelPositions)
                     h = (hmin,hmax)
                     arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph)
                     dataOut.data_param = arrayParameters
                     return
             class SMPhaseCalibration(Operation):
                 __buffer = None
                 __initime = None
                 __dataReady = False
                 __isConfig = False
                 def __checkTime(self, currentTime, initTime, paramInterval, outputInterval):
                     dataTime = currentTime + paramInterval
                     deltaTime = dataTime - initTime
                     if deltaTime >= outputInterval or deltaTime < 0:
                         return True
                     return False
                 def __getGammas(self, pairs, d, phases):
                     gammas = numpy.zeros(2)
                     for i in range(len(pairs)):
                         pairi = pairs[i]
                         phip3 = phases[:,pairi[0]]
                         d3 = d[pairi[0]]
                         phip2 = phases[:,pairi[1]]
                         d2 = d[pairi[1]]
                         #Calculating gamma
             #             jdcos = alp1/(k*d1)
             #             jgamma = numpy.angle(numpy.exp(1j*(d0*alp1/d1 - alp0)))
                         jgamma = -phip2*d3/d2 - phip3
                         jgamma = numpy.angle(numpy.exp(1j*jgamma))
             #             jgamma[jgamma>numpy.pi] -= 2*numpy.pi
             #             jgamma[jgamma<-numpy.pi] += 2*numpy.pi
                         #Revised distribution
                         jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi))
                         #Histogram
                         nBins = 64
                         rmin = -0.5*numpy.pi
                         rmax = 0.5*numpy.pi
                         phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax))
                         meteorsY = phaseHisto[0]
                         phasesX = phaseHisto[1][:-1]
                         width = phasesX[1] - phasesX[0]
                         phasesX += width/2
                         #Gaussian aproximation
                         bpeak = meteorsY.argmax()
                         peak = meteorsY.max()
                         jmin = bpeak - 5
                         jmax = bpeak + 5 + 1
                         if jmin<0:
                             jmin = 0
                             jmax = 6
                         elif jmax > meteorsY.size:
                             jmin = meteorsY.size - 6
                             jmax = meteorsY.size
                         x0 = numpy.array([peak,bpeak,50])
                         coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax]))
                         #Gammas
                         gammas[i] = coeff[0][1]
                     return gammas
                 def __residualFunction(self, coeffs, y, t):
                     return y - self.__gauss_function(t, coeffs)
                 def __gauss_function(self, t, coeffs):
                     return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2)
                 def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray):
                     meteorOps = SMOperations()
                     nchan = 4
                     pairx = pairsList[0] #x es 0
                     pairy = pairsList[1] #y es 1
                     center_xangle = 0
                     center_yangle = 0
                     range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4])
                     ntimes = len(range_angle)
                     nstepsx = 20
                     nstepsy = 20
                     for iz in range(ntimes):
                         min_xangle = -range_angle[iz]/2 + center_xangle
                         max_xangle = range_angle[iz]/2 + center_xangle
                         min_yangle = -range_angle[iz]/2 + center_yangle
                         max_yangle = range_angle[iz]/2 + center_yangle
                         inc_x = (max_xangle-min_xangle)/nstepsx
                         inc_y = (max_yangle-min_yangle)/nstepsy
                         alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle
                         alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle
                         penalty = numpy.zeros((nstepsx,nstepsy))
                         jph_array = numpy.zeros((nchan,nstepsx,nstepsy))
                         jph = numpy.zeros(nchan)
                         # Iterations looking for the offset
                         for iy in range(int(nstepsy)):
                             for ix in range(int(nstepsx)):
                                 d3 = d[pairsList[1][0]]
                                 d2 = d[pairsList[1][1]]
                                 d5 = d[pairsList[0][0]]
                                 d4 = d[pairsList[0][1]]
                                 alp2 = alpha_y[iy]  #gamma 1
                                 alp4 = alpha_x[ix]  #gamma 0
                                 alp3 = -alp2*d3/d2 - gammas[1]
                                 alp5 = -alp4*d5/d4 - gammas[0]
             #                     jph[pairy[1]] = alpha_y[iy]
             #                     jph[pairy[0]] = -gammas[1] - alpha_y[iy]*d[pairy[1]]/d[pairy[0]]
             #                     jph[pairx[1]] = alpha_x[ix]
             #                     jph[pairx[0]] = -gammas[0] - alpha_x[ix]*d[pairx[1]]/d[pairx[0]]
                                 jph[pairsList[0][1]] = alp4
                                 jph[pairsList[0][0]] = alp5
                                 jph[pairsList[1][0]] = alp3
                                 jph[pairsList[1][1]] = alp2
                                 jph_array[:,ix,iy] = jph
             #                     d = [2.0,2.5,2.5,2.0]
                                 #falta chequear si va a leer bien  los meteoros
                                 meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, d, jph)
                                 error = meteorsArray1[:,-1]
                                 ind1 = numpy.where(error==0)[0]
                                 penalty[ix,iy] = ind1.size
                         i,j = numpy.unravel_index(penalty.argmax(), penalty.shape)
                         phOffset = jph_array[:,i,j]
                         center_xangle = phOffset[pairx[1]]
                         center_yangle = phOffset[pairy[1]]
                     phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j]))
                     phOffset = phOffset*180/numpy.pi
                     return phOffset
                 def run(self, dataOut, hmin, hmax, channelPositions=None, nHours = 1):
                     dataOut.flagNoData = True
                     self.__dataReady = False
                     dataOut.outputInterval = nHours*3600
                     if self.__isConfig == False:
             #                 self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03)
                         #Get Initial LTC time
                         self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime)
                         self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds()
                         self.__isConfig = True
                     if self.__buffer is None:
                         self.__buffer = dataOut.data_param.copy()
                     else:
                         self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param))
                     self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready
                     if self.__dataReady:
                         dataOut.utctimeInit = self.__initime
                         self.__initime += dataOut.outputInterval #to erase time offset
                         freq = dataOut.frequency
                         c = dataOut.C #m/s
                         lamb = c/freq
                         k = 2*numpy.pi/lamb
                         azimuth = 0
                         h = (hmin, hmax)
             #             pairs = ((0,1),(2,3)) #Estrella
             #             pairs = ((1,0),(2,3)) #T
                         if channelPositions is None:
             #             channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)]   #T
                             channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)]   #Estrella
                         meteorOps = SMOperations()
                         pairslist0, distances = meteorOps.getPhasePairs(channelPositions)
                         #Checking correct order of pairs
                         pairs = []
                         if distances[1] > distances[0]:
                             pairs.append((1,0))
                         else:
                             pairs.append((0,1))
                         if distances[3] > distances[2]:
                             pairs.append((3,2))
                         else:
                             pairs.append((2,3))
             #             distances1 = [-distances[0]*lamb, distances[1]*lamb, -distances[2]*lamb, distances[3]*lamb]
                         meteorsArray = self.__buffer
                         error = meteorsArray[:,-1]
                         boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14)
                         ind1 = numpy.where(boolError)[0]
                         meteorsArray = meteorsArray[ind1,:]
                         meteorsArray[:,-1] = 0
                         phases = meteorsArray[:,8:12]
                         #Calculate Gammas
                         gammas = self.__getGammas(pairs, distances, phases)
             #             gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180
                         #Calculate Phases
                         phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray)
                         phasesOff = phasesOff.reshape((1,phasesOff.size))
                         dataOut.data_output = -phasesOff
                         dataOut.flagNoData = False
                         dataOut.channelList = pairslist0
                         self.__buffer = None
                     return
             class SMOperations():
                 def __init__(self):
                     return
                 def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, distances, jph):
                     arrayParameters = arrayParameters0.copy()
                     hmin = h[0]
                     hmax = h[1]
                     #Calculate AOA (Error N 3, 4)
                     #JONES ET AL. 1998
                     AOAthresh = numpy.pi/8
                     error = arrayParameters[:,-1]
                     phases = -arrayParameters[:,8:12] + jph
             #         phases = numpy.unwrap(phases)
                     arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, distances, error, AOAthresh, azimuth)
                     #Calculate Heights (Error N 13 and 14)
                     error = arrayParameters[:,-1]
                     Ranges = arrayParameters[:,1]
                     zenith = arrayParameters[:,4]
                     arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax)
                     #----------------------- Get Final data    ------------------------------------
             #         error = arrayParameters[:,-1]
             #         ind1 = numpy.where(error==0)[0]
             #         arrayParameters = arrayParameters[ind1,:]
                     return arrayParameters
                 def __getAOA(self, phases, pairsList, directions, error, AOAthresh, azimuth):
                     arrayAOA = numpy.zeros((phases.shape[0],3))
                     cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList,directions)
                     arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth)
                     cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1)
                     arrayAOA[:,2] = cosDirError
                     azimuthAngle = arrayAOA[:,0]
                     zenithAngle = arrayAOA[:,1]
                     #Setting Error
                     indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0]
                     error[indError] = 0
                     #Number 3: AOA not fesible
                     indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0]
                     error[indInvalid] = 3
                     #Number 4: Large difference in AOAs obtained from different antenna baselines
                     indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0]
                     error[indInvalid] = 4
                     return arrayAOA, error
                 def __getDirectionCosines(self, arrayPhase, pairsList, distances):
                     #Initializing some variables
                     ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi
                     ang_aux = ang_aux.reshape(1,ang_aux.size)
                     cosdir = numpy.zeros((arrayPhase.shape[0],2))
                     cosdir0 = numpy.zeros((arrayPhase.shape[0],2))
                     for i in range(2):
                         ph0 = arrayPhase[:,pairsList[i][0]]
                         ph1 = arrayPhase[:,pairsList[i][1]]
                         d0 = distances[pairsList[i][0]]
                         d1 = distances[pairsList[i][1]]
                         ph0_aux = ph0 + ph1
                         ph0_aux = numpy.angle(numpy.exp(1j*ph0_aux))
             #             ph0_aux[ph0_aux > numpy.pi] -= 2*numpy.pi
             #             ph0_aux[ph0_aux < -numpy.pi] += 2*numpy.pi
                         #First Estimation
                         cosdir0[:,i] = (ph0_aux)/(2*numpy.pi*(d0 - d1))
                         #Most-Accurate Second Estimation
                         phi1_aux =  ph0 - ph1
                         phi1_aux = phi1_aux.reshape(phi1_aux.size,1)
                         #Direction Cosine 1
                         cosdir1 = (phi1_aux + ang_aux)/(2*numpy.pi*(d0 + d1))
                         #Searching the correct Direction Cosine
                         cosdir0_aux = cosdir0[:,i]
                         cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1)
                         #Minimum Distance
                         cosDiff = (cosdir1 - cosdir0_aux)**2
                         indcos = cosDiff.argmin(axis = 1)
                         #Saving Value obtained
                         cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos]
                     return cosdir0, cosdir
                 def __calculateAOA(self, cosdir, azimuth):
                     cosdirX = cosdir[:,0]
                     cosdirY = cosdir[:,1]
                     zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi
                     azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth#0 deg north, 90 deg east
                     angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose()
                     return angles
                 def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight):
                     Ramb = 375  #Ramb = c/(2*PRF)
                     Re = 6371   #Earth Radius
                     heights = numpy.zeros(Ranges.shape)
                     R_aux = numpy.array([0,1,2])*Ramb
                     R_aux = R_aux.reshape(1,R_aux.size)
                     Ranges = Ranges.reshape(Ranges.size,1)
                     Ri = Ranges + R_aux
                     hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re
                     #Check if there is a height between 70 and 110 km
                     h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1)
                     ind_h = numpy.where(h_bool == 1)[0]
                     hCorr = hi[ind_h, :]
                     ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight))
                     hCorr = hi[ind_hCorr][:len(ind_h)]
                     heights[ind_h] = hCorr
                     #Setting Error
                     #Number 13: Height unresolvable echo: not valid height within 70 to 110 km
                     #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km
                     indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0]
                     error[indError] = 0
                     indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0]
                     error[indInvalid2] = 14
                     indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0]
                     error[indInvalid1] = 13
                     return heights, error
                 def getPhasePairs(self, channelPositions):
                     chanPos = numpy.array(channelPositions)
                     listOper = list(itertools.combinations(range(5),2))
                     distances = numpy.zeros(4)
                     axisX = []
                     axisY = []
                     distX = numpy.zeros(3)
                     distY = numpy.zeros(3)
                     ix = 0
                     iy = 0
                     pairX = numpy.zeros((2,2))
                     pairY = numpy.zeros((2,2))
                     for i in range(len(listOper)):
                         pairi = listOper[i]
                         posDif = numpy.abs(chanPos[pairi[0],:] - chanPos[pairi[1],:])
                         if posDif[0] == 0:
                             axisY.append(pairi)
                             distY[iy] = posDif[1]
                             iy += 1
                         elif posDif[1] == 0:
                             axisX.append(pairi)
                             distX[ix] = posDif[0]
                             ix += 1
                     for i in range(2):
                         if i==0:
                             dist0 = distX
                             axis0 = axisX
                         else:
                             dist0 = distY
                             axis0 = axisY
                         side = numpy.argsort(dist0)[:-1]
                         axis0 = numpy.array(axis0)[side,:]
                         chanC = int(numpy.intersect1d(axis0[0,:], axis0[1,:])[0])
                         axis1 = numpy.unique(numpy.reshape(axis0,4))
                         side = axis1[axis1 != chanC]
                         diff1 = chanPos[chanC,i] - chanPos[side[0],i]
                         diff2 = chanPos[chanC,i] - chanPos[side[1],i]
                         if diff1<0:
                             chan2 = side[0]
                             d2 = numpy.abs(diff1)
                             chan1 = side[1]
                             d1 = numpy.abs(diff2)
                         else:
                             chan2 = side[1]
                             d2 = numpy.abs(diff2)
                             chan1 = side[0]
                             d1 = numpy.abs(diff1)
                         if i==0:
                             chanCX = chanC
                             chan1X = chan1
                             chan2X = chan2
                             distances[0:2] = numpy.array([d1,d2])
                         else:
                             chanCY = chanC
                             chan1Y = chan1
                             chan2Y = chan2
                             distances[2:4] = numpy.array([d1,d2])
             #         axisXsides = numpy.reshape(axisX[ix,:],4)
             #
             #         channelCentX = int(numpy.intersect1d(pairX[0,:], pairX[1,:])[0])
             #         channelCentY = int(numpy.intersect1d(pairY[0,:], pairY[1,:])[0])
             #
             #         ind25X = numpy.where(pairX[0,:] != channelCentX)[0][0]
             #         ind20X = numpy.where(pairX[1,:] != channelCentX)[0][0]
             #         channel25X = int(pairX[0,ind25X])
             #         channel20X = int(pairX[1,ind20X])
             #         ind25Y = numpy.where(pairY[0,:] != channelCentY)[0][0]
             #         ind20Y = numpy.where(pairY[1,:] != channelCentY)[0][0]
             #         channel25Y = int(pairY[0,ind25Y])
             #         channel20Y = int(pairY[1,ind20Y])
             #         pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)]
                     pairslist = [(chanCX, chan1X),(chanCX, chan2X),(chanCY,chan1Y),(chanCY, chan2Y)]
                     return pairslist, distances
             #     def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth):
             #
             #         arrayAOA = numpy.zeros((phases.shape[0],3))
             #         cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList)
             #
             #         arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth)
             #         cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1)
             #         arrayAOA[:,2] = cosDirError
             #
             #         azimuthAngle = arrayAOA[:,0]
             #         zenithAngle = arrayAOA[:,1]
             #
             #         #Setting Error
             #         #Number 3: AOA not fesible
             #         indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0]
             #         error[indInvalid] = 3
             #         #Number 4: Large difference in AOAs obtained from different antenna baselines
             #         indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0]
             #         error[indInvalid] = 4
             #         return arrayAOA, error
             #
             #     def __getDirectionCosines(self, arrayPhase, pairsList):
             #
             #         #Initializing some variables
             #         ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi
             #         ang_aux = ang_aux.reshape(1,ang_aux.size)
             #
             #         cosdir = numpy.zeros((arrayPhase.shape[0],2))
             #         cosdir0 = numpy.zeros((arrayPhase.shape[0],2))
             #
             #
             #         for i in range(2):
             #             #First Estimation
             #             phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]]
             #             #Dealias
             #             indcsi = numpy.where(phi0_aux > numpy.pi)
             #             phi0_aux[indcsi] -= 2*numpy.pi
             #             indcsi = numpy.where(phi0_aux < -numpy.pi)
             #             phi0_aux[indcsi] += 2*numpy.pi
             #             #Direction Cosine 0
             #             cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5)
             #
             #             #Most-Accurate Second Estimation
             #             phi1_aux =  arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]]
             #             phi1_aux = phi1_aux.reshape(phi1_aux.size,1)
             #             #Direction Cosine 1
             #             cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5)
             #
             #             #Searching the correct Direction Cosine
             #             cosdir0_aux = cosdir0[:,i]
             #             cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1)
             #             #Minimum Distance
             #             cosDiff = (cosdir1 - cosdir0_aux)**2
             #             indcos = cosDiff.argmin(axis = 1)
             #             #Saving Value obtained
             #             cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos]
             #
             #         return cosdir0, cosdir
             #
             #     def __calculateAOA(self, cosdir, azimuth):
             #         cosdirX = cosdir[:,0]
             #         cosdirY = cosdir[:,1]
             #
             #         zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi
             #         azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east
             #         angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose()
             #
             #         return angles
             #
             #     def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight):
             #
             #         Ramb = 375  #Ramb = c/(2*PRF)
             #         Re = 6371   #Earth Radius
             #         heights = numpy.zeros(Ranges.shape)
             #
             #         R_aux = numpy.array([0,1,2])*Ramb
             #         R_aux = R_aux.reshape(1,R_aux.size)
             #
             #         Ranges = Ranges.reshape(Ranges.size,1)
             #
             #         Ri = Ranges + R_aux
             #         hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re
             #
             #         #Check if there is a height between 70 and 110 km
             #         h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1)
             #         ind_h = numpy.where(h_bool == 1)[0]
             #
             #         hCorr = hi[ind_h, :]
             #         ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight))
             #
             #         hCorr = hi[ind_hCorr]
             #         heights[ind_h] = hCorr
             #
             #         #Setting Error
             #         #Number 13: Height unresolvable echo: not valid height within 70 to 110 km
             #         #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km
             #
             #         indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0]
             #         error[indInvalid2] = 14
             #         indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0]
             #         error[indInvalid1] = 13
             #
             #         return heights, error

schainpy/model/proc/jroproc_spectra.py +6 0

             import numpy
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import Spectra
             from schainpy.model.data.jrodata import hildebrand_sekhon
             class SpectraProc(ProcessingUnit):
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
                     self.buffer = None
                     self.firstdatatime = None
                     self.profIndex = 0
                     self.dataOut = Spectra()
                     self.id_min = None
                     self.id_max = None
                 def __updateSpecFromVoltage(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.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
                     self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
                     self.dataOut.channelList = self.dataIn.channelList
                     self.dataOut.heightList = self.dataIn.heightList
                     self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')])
                     self.dataOut.nBaud = self.dataIn.nBaud
                     self.dataOut.nCode = self.dataIn.nCode
                     self.dataOut.code = self.dataIn.code
                     self.dataOut.nProfiles = self.dataOut.nFFTPoints
                     self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock
                     self.dataOut.utctime = self.firstdatatime
                     self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada
                     self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip
                     self.dataOut.flagShiftFFT = False
                     self.dataOut.nCohInt = self.dataIn.nCohInt
                     self.dataOut.nIncohInt = 1
                     self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
                     self.dataOut.frequency = self.dataIn.frequency
                     self.dataOut.realtime = self.dataIn.realtime
                     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
                 def __getFft(self):
                     """
                     Convierte valores de Voltaje a Spectra
                     Affected:
                         self.dataOut.data_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                         self.profIndex
                         self.buffer
                         self.dataOut.flagNoData
                     """
                     fft_volt = numpy.fft.fft(self.buffer,n=self.dataOut.nFFTPoints,axis=1)
                     fft_volt = fft_volt.astype(numpy.dtype('complex'))
                     dc = fft_volt[:,0,:]
                     #calculo de self-spectra
                     fft_volt = numpy.fft.fftshift(fft_volt,axes=(1,))
                     spc = fft_volt * numpy.conjugate(fft_volt)
                     spc = spc.real
                     blocksize = 0
                     blocksize += dc.size
                     blocksize += spc.size
                     cspc = None
                     pairIndex = 0
                     if self.dataOut.pairsList != None:
                         #calculo de cross-spectra
                         cspc = numpy.zeros((self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex')
                         for pair in self.dataOut.pairsList:
                             if pair[0] not in self.dataOut.channelList:
                                 raise ValueError, "Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
                             if pair[1] not in self.dataOut.channelList:
                                 raise ValueError, "Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" %(str(pair), str(self.dataOut.channelList))
                             cspc[pairIndex,:,:] = fft_volt[pair[0],:,:] * numpy.conjugate(fft_volt[pair[1],:,:])
                             pairIndex += 1
                         blocksize += cspc.size
                     self.dataOut.data_spc = spc
                     self.dataOut.data_cspc = cspc
                     self.dataOut.data_dc = dc
                     self.dataOut.blockSize = blocksize
                     self.dataOut.flagShiftFFT = True
                 def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None):
                     self.dataOut.flagNoData = True
                     if self.dataIn.type == "Spectra":
                         self.dataOut.copy(self.dataIn)
             #             self.__selectPairs(pairsList)
                         return True
                     if self.dataIn.type == "Voltage":
                         if nFFTPoints == None:
                             raise ValueError, "This SpectraProc.run() need nFFTPoints input variable"
                         if nProfiles == None:
                             nProfiles = nFFTPoints
                         if ippFactor == None:
                             ippFactor = 1
                         self.dataOut.ippFactor = ippFactor
                         self.dataOut.nFFTPoints = nFFTPoints
                         self.dataOut.pairsList = pairsList
                         if self.buffer is None:
                             self.buffer = numpy.zeros( (self.dataIn.nChannels,
                                                         nProfiles,
                                                         self.dataIn.nHeights),
                                                       dtype='complex')
                         if self.dataIn.flagDataAsBlock:
                             #data dimension: [nChannels, nProfiles, nSamples]
                             nVoltProfiles = self.dataIn.data.shape[1]
             #                 nVoltProfiles = self.dataIn.nProfiles
                             if nVoltProfiles == nProfiles:
                                 self.buffer = self.dataIn.data.copy()
                                 self.profIndex = nVoltProfiles
                             elif nVoltProfiles < nProfiles:
                                 if self.profIndex == 0:
                                     self.id_min = 0
                                     self.id_max = nVoltProfiles
                                 self.buffer[:,self.id_min:self.id_max,:] = self.dataIn.data
                                 self.profIndex += nVoltProfiles
                                 self.id_min += nVoltProfiles
                                 self.id_max += nVoltProfiles
                             else:
                                 raise ValueError, "The type object %s has %d profiles, it should just has %d profiles"%(self.dataIn.type,self.dataIn.data.shape[1],nProfiles)
                                 self.dataOut.flagNoData = True
                                 return 0
                         else:
                             self.buffer[:,self.profIndex,:] = self.dataIn.data.copy()
                             self.profIndex += 1
                         if self.firstdatatime == None:
                             self.firstdatatime = self.dataIn.utctime
                         if self.profIndex == nProfiles:
                             self.__updateSpecFromVoltage()
                             self.__getFft()
                             self.dataOut.flagNoData = False
                             self.firstdatatime = None
                             self.profIndex = 0
                         return True
                     raise ValueError, "The type of input object '%s' is not valid"%(self.dataIn.type)
                 def __selectPairs(self, pairsList):
                     if channelList == None:
                         return
                     pairsIndexListSelected = []
                     for thisPair in pairsList:
                         if thisPair not in self.dataOut.pairsList:
                             continue
                         pairIndex = self.dataOut.pairsList.index(thisPair)
                         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
                 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
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     for channel in channelList:
                         if channel not in self.dataOut.channelList:
                             raise ValueError, "Error selecting channels, Channel %d is not valid.\nAvailable channels = %s" %(channel, str(self.dataOut.channelList))
                         index = self.dataOut.channelList.index(channel)
                         channelIndexList.append(index)
                     self.selectChannelsByIndex(channelIndexList)
                 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_spc
                         self.dataOut.channelIndexList
                         self.dataOut.nChannels
                     Return:
                         None
                     """
                     for channelIndex in channelIndexList:
                         if channelIndex not in self.dataOut.channelIndexList:
                             raise ValueError, "Error selecting channels: The value %d in channelIndexList is not valid.\nAvailable channel indexes = " %(channelIndex, self.dataOut.channelIndexList)
             #         nChannels = len(channelIndexList)
                     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.nChannels = nChannels
                     self.__selectPairsByChannel(self.dataOut.channelList)
                     return 1
                 def selectHeights(self, minHei, maxHei):
                     """
                     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
                     """
                     if (minHei > maxHei):
                         raise ValueError, "Error selecting heights: Height range (%d,%d) is not valid" % (minHei, 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 1
                 def getBeaconSignal(self, tauindex = 0, channelindex = 0, hei_ref=None):
                     newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex])
                     if hei_ref != None:
                         newheis = numpy.where(self.dataOut.heightList>hei_ref)
                     minIndex = min(newheis[0])
                     maxIndex = max(newheis[0])
                     data_spc = self.dataOut.data_spc[:,:,minIndex:maxIndex+1]
                     heightList = self.dataOut.heightList[minIndex:maxIndex+1]
                     # determina indices
                     nheis = int(self.dataOut.radarControllerHeaderObj.txB/(self.dataOut.heightList[1]-self.dataOut.heightList[0]))
                     avg_dB = 10*numpy.log10(numpy.sum(data_spc[channelindex,:,:],axis=0))
                     beacon_dB = numpy.sort(avg_dB)[-nheis:]
                     beacon_heiIndexList = []
                     for val in avg_dB.tolist():
                         if val >= beacon_dB[0]:
                             beacon_heiIndexList.append(avg_dB.tolist().index(val))
                     #data_spc = data_spc[:,:,beacon_heiIndexList]
                     data_cspc = None
                     if self.dataOut.data_cspc is not None:
                         data_cspc = self.dataOut.data_cspc[:,:,minIndex:maxIndex+1]
                         #data_cspc = data_cspc[:,:,beacon_heiIndexList]
                     data_dc = None
                     if self.dataOut.data_dc is not None:
                         data_dc = self.dataOut.data_dc[:,minIndex:maxIndex+1]
                         #data_dc = data_dc[:,beacon_heiIndexList]
                     self.dataOut.data_spc = data_spc
                     self.dataOut.data_cspc = data_cspc
                     self.dataOut.data_dc = data_dc
                     self.dataOut.heightList = heightList
                     self.dataOut.beacon_heiIndexList = beacon_heiIndexList
                     return 1
                 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_spc
                         self.dataOut.data_cspc
                         self.dataOut.data_dc
                         self.dataOut.heightList
                     Return:
 si el metodo se ejecuto con exito caso contrario devuelve 0
                     """
                     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
                 def removeDC(self, mode = 2):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     num_chan = jspectra.shape[0]
                     num_hei = jspectra.shape[2]
                     if jcspectra is not None:
                         jcspectraExist = True
                         num_pairs = jcspectra.shape[0]
                     else:   jcspectraExist = False
                     freq_dc = jspectra.shape[1]/2
                     ind_vel = numpy.array([-2,-1,1,2]) + freq_dc
                     if ind_vel[0]<0:
                         ind_vel[range(0,1)] = ind_vel[range(0,1)] + self.num_prof
                     if mode == 1:
                         jspectra[:,freq_dc,:] = (jspectra[:,ind_vel[1],:] + jspectra[:,ind_vel[2],:])/2 #CORRECCION
                         if jcspectraExist:
                             jcspectra[:,freq_dc,:] = (jcspectra[:,ind_vel[1],:] + jcspectra[:,ind_vel[2],:])/2
                     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(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
                         if jcspectraExist:
                             for ip in range(num_pairs):
                                 yy = jcspectra[ip,ind_vel,:]
                                 jcspectra[ip,freq_dc,:] = numpy.dot(xx_aux,yy)
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def removeInterference(self,  interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None):
                     jspectra = self.dataOut.data_spc
                     jcspectra = self.dataOut.data_cspc
                     jnoise = self.dataOut.getNoise()
                     num_incoh = self.dataOut.nIncohInt
                     num_channel  = jspectra.shape[0]
                     num_prof  = jspectra.shape[1]
                     num_hei   = jspectra.shape[2]
                     #hei_interf
                     if hei_interf is None:
                         count_hei = num_hei/2   #Como es entero no importa
                         hei_interf = numpy.asmatrix(range(count_hei)) + num_hei - count_hei
                         hei_interf = numpy.asarray(hei_interf)[0]
                     #nhei_interf
                     if (nhei_interf == None):
                         nhei_interf = 5
                     if (nhei_interf < 1):
                         nhei_interf = 1
                     if (nhei_interf > count_hei):
                         nhei_interf = count_hei
                     if (offhei_interf == None):
                         offhei_interf = 0
                     ind_hei = range(num_hei)
             #         mask_prof = numpy.asarray(range(num_prof - 2)) + 1
             #         mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1
                     mask_prof = numpy.asarray(range(num_prof))
                     num_mask_prof = mask_prof.size
                     comp_mask_prof = [0, num_prof/2]
                     #noise_exist:    Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal
                     if (jnoise.size < num_channel or numpy.isnan(jnoise).any()):
                         jnoise = numpy.nan
                     noise_exist = jnoise[0] < numpy.Inf
                     #Subrutina de Remocion de la Interferencia
                     for ich in range(num_channel):
                         #Se ordena los espectros segun su potencia (menor a mayor)
                         power = jspectra[ich,mask_prof,:]
                         power = power[:,hei_interf]
                         power = power.sum(axis = 0)
                         psort = power.ravel().argsort()
                         #Se estima la interferencia promedio en los Espectros de Potencia empleando
                         junkspc_interf = jspectra[ich,:,hei_interf[psort[range(offhei_interf, nhei_interf + offhei_interf)]]]
                         if noise_exist:
                         #    tmp_noise = jnoise[ich] / num_prof
                             tmp_noise = jnoise[ich]
                         junkspc_interf = junkspc_interf - tmp_noise
                         #junkspc_interf[:,comp_mask_prof] = 0
                         jspc_interf = junkspc_interf.sum(axis = 0) / nhei_interf
                         jspc_interf = jspc_interf.transpose()
                         #Calculando el espectro de interferencia promedio
                         noiseid =  numpy.where(jspc_interf <= tmp_noise/ numpy.sqrt(num_incoh))
                         noiseid = noiseid[0]
                         cnoiseid = noiseid.size
                         interfid = numpy.where(jspc_interf > tmp_noise/ numpy.sqrt(num_incoh))
                         interfid = interfid[0]
                         cinterfid = interfid.size
                         if (cnoiseid > 0):   jspc_interf[noiseid] = 0
                         #Expandiendo los perfiles a limpiar
                         if (cinterfid > 0):
                             new_interfid = (numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof)%num_prof
                             new_interfid = numpy.asarray(new_interfid)
                             new_interfid = {x for x in new_interfid}
                             new_interfid = numpy.array(list(new_interfid))
                             new_cinterfid = new_interfid.size
                         else: new_cinterfid = 0
                         for ip in range(new_cinterfid):
                             ind = junkspc_interf[:,new_interfid[ip]].ravel().argsort()
                             jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf/2],new_interfid[ip]]
                         jspectra[ich,:,ind_hei] = jspectra[ich,:,ind_hei] - jspc_interf #Corregir indices
                         #Removiendo la interferencia del punto de mayor interferencia
                         ListAux = jspc_interf[mask_prof].tolist()
                         maxid = ListAux.index(max(ListAux))
                         if cinterfid > 0:
                             for ip in range(cinterfid*(interf == 2) - 1):
                                 ind = (jspectra[ich,interfid[ip],:] < tmp_noise*(1 + 1/numpy.sqrt(num_incoh))).nonzero()
                                 cind = len(ind)
                                 if (cind > 0):
                                     jspectra[ich,interfid[ip],ind] = tmp_noise*(1 + (numpy.random.uniform(cind) - 0.5)/numpy.sqrt(num_incoh))
                             ind = numpy.array([-2,-1,1,2])
                             xx = numpy.zeros([4,4])
                             for id1 in range(4):
                                 xx[:,id1] = ind[id1]**numpy.asarray(range(4))
                             xx_inv = numpy.linalg.inv(xx)
                             xx = xx_inv[:,0]
                             ind = (ind + maxid + num_mask_prof)%num_mask_prof
                             yy = jspectra[ich,mask_prof[ind],:]
                             jspectra[ich,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
                         indAux = (jspectra[ich,:,:] < tmp_noise*(1-1/numpy.sqrt(num_incoh))).nonzero()
                         jspectra[ich,indAux[0],indAux[1]] = tmp_noise * (1 - 1/numpy.sqrt(num_incoh))
                     #Remocion de Interferencia en el Cross Spectra
                     if jcspectra is None: return jspectra, jcspectra
                     num_pairs = jcspectra.size/(num_prof*num_hei)
                     jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei)
                     for ip in range(num_pairs):
                         #-------------------------------------------
                         cspower = numpy.abs(jcspectra[ip,mask_prof,:])
                         cspower = cspower[:,hei_interf]
                         cspower = cspower.sum(axis = 0)
                         cspsort = cspower.ravel().argsort()
                         junkcspc_interf = jcspectra[ip,:,hei_interf[cspsort[range(offhei_interf, nhei_interf + offhei_interf)]]]
                         junkcspc_interf = junkcspc_interf.transpose()
                         jcspc_interf = junkcspc_interf.sum(axis = 1)/nhei_interf
                         ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort()
                         median_real = numpy.median(numpy.real(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
                         median_imag = numpy.median(numpy.imag(junkcspc_interf[mask_prof[ind[range(3*num_prof/4)]],:]))
                         junkcspc_interf[comp_mask_prof,:] = numpy.complex(median_real, median_imag)
                         for iprof in range(num_prof):
                             ind = numpy.abs(junkcspc_interf[iprof,:]).ravel().argsort()
                             jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf/2]]
                         #Removiendo la Interferencia
                         jcspectra[ip,:,ind_hei] = jcspectra[ip,:,ind_hei] - jcspc_interf
                         ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist()
                         maxid = ListAux.index(max(ListAux))
                         ind = numpy.array([-2,-1,1,2])
                         xx = numpy.zeros([4,4])
                         for id1 in range(4):
                             xx[:,id1] = ind[id1]**numpy.asarray(range(4))
                         xx_inv = numpy.linalg.inv(xx)
                         xx = xx_inv[:,0]
                         ind = (ind + maxid + num_mask_prof)%num_mask_prof
                         yy = jcspectra[ip,mask_prof[ind],:]
                         jcspectra[ip,mask_prof[maxid],:] = numpy.dot(yy.transpose(),xx)
                     #Guardar Resultados
                     self.dataOut.data_spc = jspectra
                     self.dataOut.data_cspc = jcspectra
                     return 1
                 def setRadarFrequency(self, frequency=None):
                     if frequency != None:
                         self.dataOut.frequency = frequency
                     return 1
                 def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None):
                     #validacion de rango
                     if minHei == None:
                         minHei = self.dataOut.heightList[0]
                     if maxHei == None:
                         maxHei = self.dataOut.heightList[-1]
                     if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei):
                         print 'minHei: %.2f is out of the heights range'%(minHei)
                         print 'minHei is setting to %.2f'%(self.dataOut.heightList[0])
                         minHei = self.dataOut.heightList[0]
                     if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei):
                         print 'maxHei: %.2f is out of the heights range'%(maxHei)
                         print 'maxHei is setting to %.2f'%(self.dataOut.heightList[-1])
                         maxHei = self.dataOut.heightList[-1]
                     # validacion de velocidades
                     velrange = self.dataOut.getVelRange(1)
                     if minVel == None:
                         minVel = velrange[0]
                     if maxVel == None:
                         maxVel = velrange[-1]
                     if (minVel < velrange[0]) or (minVel > maxVel):
                         print 'minVel: %.2f is out of the velocity range'%(minVel)
                         print 'minVel is setting to %.2f'%(velrange[0])
                         minVel = velrange[0]
                     if (maxVel > velrange[-1]) or (maxVel < minVel):
                         print 'maxVel: %.2f is out of the velocity range'%(maxVel)
                         print 'maxVel is setting to %.2f'%(velrange[-1])
                         maxVel = velrange[-1]
                     # seleccion de indices para rango
                     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)
                     if (minIndex < 0) or (minIndex > maxIndex):
                         raise ValueError, "some value in (%d,%d) is not valid" % (minIndex, maxIndex)
                     if (maxIndex >= self.dataOut.nHeights):
                         maxIndex = self.dataOut.nHeights-1
                     # seleccion de indices para velocidades
                     indminvel = numpy.where(velrange >= minVel)
                     indmaxvel = numpy.where(velrange <= maxVel)
                     try:
                         minIndexVel = indminvel[0][0]
                     except:
                         minIndexVel = 0
                     try:
                         maxIndexVel = indmaxvel[0][-1]
                     except:
                         maxIndexVel = len(velrange)
                     #seleccion del espectro
                     data_spc = self.dataOut.data_spc[:,minIndexVel:maxIndexVel+1,minIndex:maxIndex+1]
                     #estimacion de ruido
                     noise = numpy.zeros(self.dataOut.nChannels)
                     for channel in range(self.dataOut.nChannels):
                         daux = data_spc[channel,:,:]
                         noise[channel] = hildebrand_sekhon(daux, self.dataOut.nIncohInt)
                     self.dataOut.noise_estimation = noise.copy()
                     return 1
             class IncohInt(Operation):
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer_spc = None
                 __buffer_cspc = None
                 __buffer_dc = None
                 __dataReady = False
                 __timeInterval = None
+                parameters = {
+                    'n': global_type_float,
+                    'timeInterval': global_type_integer,
+                    'overlapping': global_type_boolean,
+                }
                 n = None
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
             #         self.isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=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_spc = 0
                     self.__buffer_cspc = 0
                     self.__buffer_dc = 0
                     self.__profIndex = 0
                     self.__dataReady = False
                     self.__byTime = False
                     if n is None and timeInterval is None:
                         raise ValueError, "n or timeInterval should be specified ..."
                     if n is not None:
                         self.n = int(n)
                     else:
                         self.__integrationtime = int(timeInterval) #if (type(timeInterval)!=integer) -> change this line
                         self.n = None
                         self.__byTime = True
                 def putData(self, data_spc, data_cspc, data_dc):
                     """
                     Add a profile to the __buffer_spc and increase in one the __profileIndex
                     """
                     self.__buffer_spc += data_spc
                     if data_cspc is None:
                         self.__buffer_cspc = None
                     else:
                         self.__buffer_cspc += data_cspc
                     if data_dc is None:
                         self.__buffer_dc = None
                     else:
                         self.__buffer_dc += data_dc
                     self.__profIndex += 1
                     return
                 def pushData(self):
                     """
                     Return the sum of the last profiles and the profiles used in the sum.
                     Affected:
                     self.__profileIndex
                     """
                     data_spc = self.__buffer_spc
                     data_cspc = self.__buffer_cspc
                     data_dc = self.__buffer_dc
                     n = self.__profIndex
                     self.__buffer_spc = 0
                     self.__buffer_cspc = 0
                     self.__buffer_dc = 0
                     self.__profIndex = 0
                     return data_spc, data_cspc, data_dc, n
                 def byProfiles(self, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     self.putData(*args)
                     if self.__profIndex == self.n:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def byTime(self, datatime, *args):
                     self.__dataReady = False
                     avgdata_spc = None
                     avgdata_cspc = None
                     avgdata_dc = None
                     self.putData(*args)
                     if (datatime - self.__initime) >= self.__integrationtime:
                         avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData()
                         self.n = n
                         self.__dataReady = True
                     return avgdata_spc, avgdata_cspc, avgdata_dc
                 def integrate(self, datatime, *args):
                     if self.__profIndex == 0:
                         self.__initime = datatime
                     if self.__byTime:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime(datatime, *args)
                     else:
                         avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args)
                     if not self.__dataReady:
                         return None, None, None, None
                     return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc
                 def run(self, dataOut, n=None, timeInterval=None, overlapping=False):
                     if n==1:
                         return
                     dataOut.flagNoData = True
                     if not self.isConfig:
                         self.setup(n, timeInterval, overlapping)
                         self.isConfig = True
                     avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime,
                                                                                         dataOut.data_spc,
                                                                                         dataOut.data_cspc,
                                                                                         dataOut.data_dc)
                     if self.__dataReady:
                         dataOut.data_spc = avgdata_spc
                         dataOut.data_cspc = avgdata_cspc
                         dataOut.data_dc = avgdata_dc
                         dataOut.nIncohInt *= self.n
                         dataOut.utctime = avgdatatime
                         dataOut.flagNoData = False

schainpy/model/proc/jroproc_voltage.py +45 -6

             import sys
             import numpy
             from profilehooks import profile
             from scipy import interpolate
             from schainpy import cSchain
             from jroproc_base import ProcessingUnit, Operation
             from schainpy.model.data.jrodata import Voltage
             from time import time
             class VoltageProc(ProcessingUnit):
                 def __init__(self, **kwargs):
                     ProcessingUnit.__init__(self, **kwargs)
             #         self.objectDict = {}
                     self.dataOut = Voltage()
                     self.flip = 1
                 def run(self):
                     if self.dataIn.type == 'AMISR':
                         self.__updateObjFromAmisrInput()
                     if self.dataIn.type == 'Voltage':
                         self.dataOut.copy(self.dataIn)
             #         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
             #
             #        pass#
             #
             #    def init(self):
             #
             #
             #        if self.dataIn.type == 'AMISR':
             #            self.__updateObjFromAmisrInput()
             #
             #        if self.dataIn.type == 'Voltage':
             #            self.dataOut.copy(self.dataIn)
             #        # No necesita copiar en cada init() los atributos de dataIn
             #        # la copia deberia hacerse por cada nuevo bloque de datos
                 def selectChannels(self, channelList):
                     channelIndexList = []
                     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)
                 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:
                             print channelIndexList
                             raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex
                     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.nChannels = nChannels
                     return 1
                 def selectHeights(self, minHei=None, maxHei=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
                     """
                     if minHei == None:
                         minHei = self.dataOut.heightList[0]
                     if maxHei == None:
                         maxHei = self.dataOut.heightList[-1]
                     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 1
                 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 (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)
                     return 1
                 def filterByHeights(self, window):
                     deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     if window == None:
                         window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight
                     newdelta = deltaHeight * window
                     r = self.dataOut.nHeights % window
                     newheights = (self.dataOut.nHeights-r)/window
                     if newheights <= 1:
                         raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window)
                     if self.dataOut.flagDataAsBlock:
                         """
                         Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis]
                         """
                         buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r]
                         buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window)
                         buffer = numpy.sum(buffer,3)
                     else:
                         buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r]
                         buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window)
                         buffer = numpy.sum(buffer,2)
                     self.dataOut.data = buffer
                     self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta
                     self.dataOut.windowOfFilter = window
                 def setH0(self, h0, deltaHeight = None):
                     if not deltaHeight:
                         deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
                     nHeights = self.dataOut.nHeights
                     newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight
                     self.dataOut.heightList = newHeiRange
                 def deFlip(self, channelList = []):
                     data = self.dataOut.data.copy()
                     if self.dataOut.flagDataAsBlock:
                         flip = self.flip
                         profileList = range(self.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 self.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 self.dataOut.channelList:
                                     continue
                                 data[thisChannel,:] = data[thisChannel,:]*self.flip
                         self.flip *= -1.
                     self.dataOut.data = data
                 def setRadarFrequency(self, frequency=None):
                     if frequency != None:
                         self.dataOut.frequency = frequency
                     return 1
                 def interpolateHeights(self, topLim, botLim):
                     #69 al 72 para julia
                     #82-84 para meteoros
                     if len(numpy.shape(self.dataOut.data))==2:
                         sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2
                         sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1)))
                         #self.dataOut.data[:,botLim:limSup+1] = sampInterp
                         self.dataOut.data[:,botLim:topLim+1] = sampInterp
                     else:
                         nHeights = self.dataOut.data.shape[2]
                         x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights)))
                         y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)]
                         f = interpolate.interp1d(x, y, axis = 2)
                         xnew = numpy.arange(botLim,topLim+1)
                         ynew = f(xnew)
                         self.dataOut.data[:,:,botLim:topLim+1]  = ynew
             # import collections
             class CohInt(Operation):
                 isConfig = False
                 __profIndex = 0
                 __withOverapping  = False
                 __byTime = False
                 __initime = None
                 __lastdatatime = None
                 __integrationtime = None
                 __buffer = None
                 __dataReady = False
                 n = None
+                parameters = {
+                    'id': global_type_string,
+                    'wintitle': global_type_string,
+                    'pairsList': global_type_pairsList,
+                    'showprofile': global_type_boolean,
+                    'xmin': global_type_float,
+                    'xmax': global_type_float,
+                    'ymin': global_type_float,
+                    'ymax': global_type_float,
+                    'zmin': global_type_float,
+                    'zmax': global_type_float,
+                    'timerange': global_type_float,
+                    'phase_min': global_type_float,
+                    'phase_max': global_type_float,
+                    'save': global_type_boolean,
+                    'figpath': global_type_string,
+                    'figfile': global_type_string,
+                    'ftp': global_type_boolean,
+                    'wr_period': global_type_integer,
+                    'coherence_cmap': global_type_colormap,
+                    'phase_cmap': global_type_colormap,
+                    'show': global_type_boolean,
+                    'server': global_type_string,
+                    'folder': global_type_string,
+                    'username': global_type_string,
+                    'password': global_type_string,
+                    'ftp_wei': global_type_integer,
+                    'exp_code': global_type_integer,
+                    'sub_exp_code': global_type_integer,
+                    'plot_pos': global_type_integer,
+                }
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
             #         self.isConfig = False
                 def setup(self, n=None, timeInterval=None, overlapping=False, byblock=False):
                     """
                     Set the parameters of the integration class.
                     Inputs:
-                        n        :    Number of coherent integrations
+                        n               :    Number of coherent integrations
-                        timeInterval   :    Time of integration. If the parameter "n" is selected this one does not work
+                        timeInterval    :    Time of integration. If the parameter "n" is selected this one does not work
-                        overlapping    :
+                        overlapping     :
                     """
                     self.__initime = None
                     self.__lastdatatime = 0
                     self.__buffer = None
                     self.__dataReady = False
                     self.byblock = byblock
                     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.__withOverapping = True
                         self.__buffer = None
                     else:
                         self.__withOverapping = 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.__withOverapping:
                         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.__withOverapping:
                         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)
                     n = self.__profIndex
                     return data, n
                 def byProfiles(self, data):
                     self.__dataReady = False
                     avgdata = None
             #         n = None
                     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 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.__withOverapping:
                         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, overlapping=False, byblock=False, **kwargs):
                     if not self.isConfig:
                         self.setup(n=n, 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:
                         avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime)
             #        dataOut.timeInterval *= n
                     dataOut.flagNoData = True
                     if self.__dataReady:
                         dataOut.data = avgdata
                         dataOut.nCohInt *= self.n
                         dataOut.utctime = avgdatatime
             #             dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt
                         dataOut.flagNoData = False
             class Decoder(Operation):
                 isConfig = False
                 __profIndex = 0
                 code = None
                 nCode = None
                 nBaud = None
+                parameters = {
+                    'code': global_type_list,
+                    'nCode': global_type_integer,
+                    'nBaud': global_type_integer,
+                    'mode': global_type_integer,
+                    'osamp': global_type_float,
+                }
                 def __init__(self, **kwargs):
                     Operation.__init__(self, **kwargs)
                     self.times = None
                     self.osamp = None
                 #         self.__setValues = False
                     self.isConfig = 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
                 #@profile
                 def oldCorrelate(self, i, data, code_block):
                     profilesList = xrange(self.__nProfiles)
                     for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                 #@profile
                 def __convolutionByBlockInTime(self, data):
                     repetitions = 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 = xrange(self.__nProfiles)
                     # def toVectorize(a,b):
                     #     return numpy.correlate(a,b, mode='full')
                     # vectorized = numpy.vectorize(toVectorize, signature='(n),(m)->(k)')
                     for i in range(self.__nChannels):
                     #     self.datadecTime[i,:,:] = numpy.array([numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] for j in profilesList ])
                         # def func(i, j):
                         #     self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                         # map(lambda j: func(i, j), range(self.__nProfiles))
                         #print data[i,:,:].shape
                         # self.datadecTime[i,:,:] = vectorized(data[i,:,:], code_block[:,:])[:,self.nBaud-1:]
                         for j in profilesList:
                             self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:]
                         # print data[i,:,:]
                         # print cSchain.correlateByBlock(data[i,:,:], code_block, 2)
                         # self.datadecTime[i,:,:] = cSchain.correlateByBlock(data[i,:,:], code_block, 2)
                         # print self.datadecTime[i,:,:]
                         #print self.datadecTime[i,:,:].shape
                     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 1
                     self.__profIndex += 1
                     return 1
             #        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
             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 = 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(range(minIndex, maxIndex+1))
                             dataOut.data = dataOut.data[:,profileList,:]
                         dataOut.nProfiles = len(profileList)
                         dataOut.profileIndex = dataOut.nProfiles - 1
                         dataOut.flagNoData = False
                         return True
                     """
                     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 True
                     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 True
                     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 True
                     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 True
                     raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter"
                     return False
             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
             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, 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
             class CombineProfiles(Operation):
+                parameters = {
+                    'n': global_type_integer,
+                }
                 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
             # 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

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