ascii_reader.py @ b2669f5

ESS_GUIESS_GUI_DocsESS_GUI_batch_fittingESS_GUI_bumps_abstractionESS_GUI_iss1116ESS_GUI_iss879ESS_GUI_iss959ESS_GUI_openclESS_GUI_orderingESS_GUI_sync_sascalccostrafo411magnetic_scattrelease-4.1.1release-4.1.2release-4.2.2release_4.0.1ticket-1009ticket-1094-headlessticket-1242-2d-resolutionticket-1243ticket-1249ticket885unittest-saveload

Last change on this file since b2669f5 was b699768, checked in by Piotr Rozyczko <piotr.rozyczko@…>, 9 years ago
Initial commit of the refactored SasCalc? module.
Property mode set to `100644`
File size: 15.3 KB

Rev	Line
[7d6351e]	1	"""
	2	ASCII reader
	3	"""
[0997158f]	4	############################################################################
	5	#This software was developed by the University of Tennessee as part of the
	6	#Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
	7	#project funded by the US National Science Foundation.
[7d6351e]	8	#If you use DANSE applications to do scientific research that leads to
	9	#publication, we ask that you acknowledge the use of the software with the
[0997158f]	10	#following sentence:
[7d6351e]	11	#This work benefited from DANSE software developed under NSF award DMR-0520547.
[0997158f]	12	#copyright 2008, University of Tennessee
	13	#############################################################################
	14
[8bd8ea4]	15
	16	import numpy
	17	import os
[b699768]	18	from sas.sascalc.dataloader.data_info import Data1D
[8bd8ea4]	19
[daa56d0]	20	# Check whether we have a converter available
[99d1af6]	21	has_converter = True
	22	try:
[b699768]	23	from sas.sascalc.data_util.nxsunit import Converter
[99d1af6]	24	except:
	25	has_converter = False
[da96629]	26	_ZERO = 1e-16
[99d1af6]	27
[7d6351e]	28
[8bd8ea4]	29	class Reader:
	30	"""
[0997158f]	31	Class to load ascii files (2, 3 or 4 columns).
[8bd8ea4]	32	"""
[8780e9a]	33	## File type
[28caa03]	34	type_name = "ASCII"
	35
	36	## Wildcards
[8780e9a]	37	type = ["ASCII files (.txt)\|.txt",
[470bf7e]	38	"ASCII files (.dat)\|.dat",
[ef9d209]	39	"ASCII files (.abs)\|.abs",
	40	"CSV files (.csv)\|.csv"]
[8bd8ea4]	41	## List of allowed extensions
[7d6351e]	42	ext = ['.txt', '.TXT', '.dat', '.DAT', '.abs', '.ABS', 'csv', 'CSV']
[8bd8ea4]	43
[e082e2c]	44	## Flag to bypass extension check
	45	allow_all = True
	46
[8bd8ea4]	47	def read(self, path):
[7d6351e]	48	"""
[0997158f]	49	Load data file
	50
	51	:param path: file path
	52
	53	:return: Data1D object, or None
	54
	55	:raise RuntimeError: when the file can't be opened
	56	:raise ValueError: when the length of the data vectors are inconsistent
[8bd8ea4]	57	"""
	58	if os.path.isfile(path):
[7d6351e]	59	basename = os.path.basename(path)
[a7a5886]	60	_, extension = os.path.splitext(basename)
[e082e2c]	61	if self.allow_all or extension.lower() in self.ext:
[8bd8ea4]	62	try:
[9cd0baa]	63	# Read in binary mode since GRASP frequently has no-ascii
	64	# characters that brakes the open operation
[7d6351e]	65	input_f = open(path,'rb')
	66	except:
[8bd8ea4]	67	raise RuntimeError, "ascii_reader: cannot open %s" % path
	68	buff = input_f.read()
[ef3445e2]	69	lines = buff.splitlines()
[470bf7e]	70
[8bd8ea4]	71	x = numpy.zeros(0)
	72	y = numpy.zeros(0)
	73	dy = numpy.zeros(0)
[de1da34]	74	dx = numpy.zeros(0)
	75
[ef3445e2]	76	#temp. space to sort data
[de1da34]	77	tx = numpy.zeros(0)
	78	ty = numpy.zeros(0)
	79	tdy = numpy.zeros(0)
	80	tdx = numpy.zeros(0)
	81
	82	output = Data1D(x, y, dy=dy, dx=dx)
[8bd8ea4]	83	self.filename = output.filename = basename
[99d1af6]	84
	85	data_conv_q = None
	86	data_conv_i = None
	87
[ca10d8e]	88	if has_converter == True and output.x_unit != '1/A':
	89	data_conv_q = Converter('1/A')
[99d1af6]	90	# Test it
	91	data_conv_q(1.0, output.x_unit)
	92
[ca10d8e]	93	if has_converter == True and output.y_unit != '1/cm':
	94	data_conv_i = Converter('1/cm')
[99d1af6]	95	# Test it
	96	data_conv_i(1.0, output.y_unit)
	97
[8bd8ea4]	98	# The first good line of data will define whether
	99	# we have 2-column or 3-column ascii
[de1da34]	100	has_error_dx = None
	101	has_error_dy = None
[8bd8ea4]	102
[892f246]	103	#Initialize counters for data lines and header lines.
[7d6351e]	104	is_data = False # Has more than 5 lines
[a7a5886]	105	# More than "5" lines of data is considered as actual
	106	# data unless that is the only data
[7d6351e]	107	mum_data_lines = 5
[a7a5886]	108	# To count # of current data candidate lines
[7d6351e]	109	i = -1
	110	# To count total # of previous data candidate lines
	111	i1 = -1
	112	# To count # of header lines
[a7a5886]	113	j = -1
[7d6351e]	114	# Helps to count # of header lines
[a7a5886]	115	j1 = -1
[7d6351e]	116	#minimum required number of columns of data; ( <= 4).
	117	lentoks = 2
[8bd8ea4]	118	for line in lines:
[86d13b5]	119	# Initial try for CSV (split on ,)
[ef9d209]	120	toks = line.split(',')
[86d13b5]	121	# Now try SCSV (split on ;)
	122	if len(toks) < 2:
	123	toks = line.split(';')
	124	# Now go for whitespace
[ef9d209]	125	if len(toks) < 2:
	126	toks = line.split()
[8bd8ea4]	127	try:
[5f2d3c78]	128	#Make sure that all columns are numbers.
	129	for colnum in range(len(toks)):
	130	float(toks[colnum])
	131
[8bd8ea4]	132	_x = float(toks[0])
	133	_y = float(toks[1])
	134
[892f246]	135	#Reset the header line counters
	136	if j == j1:
	137	j = 0
	138	j1 = 0
	139
	140	if i > 1:
	141	is_data = True
[d508be9]	142
[99d1af6]	143	if data_conv_q is not None:
	144	_x = data_conv_q(_x, units=output.x_unit)
	145
	146	if data_conv_i is not None:
[7d6351e]	147	_y = data_conv_i(_y, units=output.y_unit)
[99d1af6]	148
[8bd8ea4]	149	# If we have an extra token, check
	150	# whether it can be interpreted as a
	151	# third column.
	152	_dy = None
[a7a5886]	153	if len(toks) > 2:
[8bd8ea4]	154	try:
	155	_dy = float(toks[2])
[99d1af6]	156
	157	if data_conv_i is not None:
	158	_dy = data_conv_i(_dy, units=output.y_unit)
	159
[8bd8ea4]	160	except:
	161	# The third column is not a float, skip it.
	162	pass
	163
	164	# If we haven't set the 3rd column
	165	# flag, set it now.
[de1da34]	166	if has_error_dy == None:
	167	has_error_dy = False if _dy == None else True
	168
	169	#Check for dx
	170	_dx = None
[a7a5886]	171	if len(toks) > 3:
[de1da34]	172	try:
	173	_dx = float(toks[3])
	174
	175	if data_conv_i is not None:
	176	_dx = data_conv_i(_dx, units=output.x_unit)
	177
	178	except:
	179	# The 4th column is not a float, skip it.
	180	pass
	181
	182	# If we haven't set the 3rd column
	183	# flag, set it now.
	184	if has_error_dx == None:
	185	has_error_dx = False if _dx == None else True
[892f246]	186
[7d6351e]	187	#After talked with PB, we decided to take care of only
[a7a5886]	188	# 4 columns of data for now.
[d508be9]	189	#number of columns in the current line
[7d6351e]	190	#To remember the # of columns in the current
[a7a5886]	191	#line of data
[0e5e586]	192	new_lentoks = len(toks)
[d508be9]	193
[7d6351e]	194	#If the previous columns not equal to the current,
	195	#mark the previous as non-data and reset the dependents.
	196	if lentoks != new_lentoks:
[272b107]	197	if is_data == True:
	198	break
	199	else:
[d508be9]	200	i = -1
	201	i1 = 0
	202	j = -1
	203	j1 = -1
	204
[a7a5886]	205	#Delete the previously stored lines of data candidates
	206	# if is not data.
	207	if i < 0 and -1 < i1 < mum_data_lines and \
	208	is_data == False:
[892f246]	209	try:
[a7a5886]	210	x = numpy.zeros(0)
	211	y = numpy.zeros(0)
[892f246]	212	except:
	213	pass
	214
[ef3445e2]	215	x = numpy.append(x, _x)
[7d6351e]	216	y = numpy.append(y, _y)
[892f246]	217
[de1da34]	218	if has_error_dy == True:
[a7a5886]	219	#Delete the previously stored lines of
	220	# data candidates if is not data.
	221	if i < 0 and -1 < i1 < mum_data_lines and \
	222	is_data == False:
[892f246]	223	try:
[7d6351e]	224	dy = numpy.zeros(0)
[892f246]	225	except:
[7d6351e]	226	pass
[8bd8ea4]	227	dy = numpy.append(dy, _dy)
[892f246]	228
[de1da34]	229	if has_error_dx == True:
[a7a5886]	230	#Delete the previously stored lines of
	231	# data candidates if is not data.
	232	if i < 0 and -1 < i1 < mum_data_lines and \
	233	is_data == False:
[892f246]	234	try:
[7d6351e]	235	dx = numpy.zeros(0)
[892f246]	236	except:
[7d6351e]	237	pass
[de1da34]	238	dx = numpy.append(dx, _dx)
	239
	240	#Same for temp.
[a7a5886]	241	#Delete the previously stored lines of data candidates
	242	# if is not data.
	243	if i < 0 and -1 < i1 < mum_data_lines and\
	244	is_data == False:
[892f246]	245	try:
	246	tx = numpy.zeros(0)
	247	ty = numpy.zeros(0)
	248	except:
[7d6351e]	249	pass
[892f246]	250
[7d6351e]	251	tx = numpy.append(tx, _x)
	252	ty = numpy.append(ty, _y)
[892f246]	253
[de1da34]	254	if has_error_dy == True:
[a7a5886]	255	#Delete the previously stored lines of
	256	# data candidates if is not data.
	257	if i < 0 and -1 < i1 < mum_data_lines and \
	258	is_data == False:
[892f246]	259	try:
	260	tdy = numpy.zeros(0)
	261	except:
[7d6351e]	262	pass
[de1da34]	263	tdy = numpy.append(tdy, _dy)
	264	if has_error_dx == True:
[a7a5886]	265	#Delete the previously stored lines of
	266	# data candidates if is not data.
	267	if i < 0 and -1 < i1 < mum_data_lines and \
	268	is_data == False:
[892f246]	269	try:
	270	tdx = numpy.zeros(0)
	271	except:
[7d6351e]	272	pass
[de1da34]	273	tdx = numpy.append(tdx, _dx)
[d508be9]	274
	275	#reset i1 and flag lentoks for the next
[a7a5886]	276	if lentoks < new_lentoks:
[d508be9]	277	if is_data == False:
[7d6351e]	278	i1 = -1
[a7a5886]	279	#To remember the # of columns on the current line
	280	# for the next line of data
[0e5e586]	281	lentoks = len(toks)
[8bd8ea4]	282
[7d6351e]	283	#Reset # of header lines and counts #
	284	# of data candidate lines
[a7a5886]	285	if j == 0 and j1 == 0:
[7d6351e]	286	i1 = i + 1
[a7a5886]	287	i += 1
[8bd8ea4]	288	except:
[892f246]	289	# It is data and meet non - number, then stop reading
	290	if is_data == True:
[7d6351e]	291	break
[d508be9]	292	lentoks = 2
[7d6351e]	293	#Counting # of header lines
[a7a5886]	294	j += 1
	295	if j == j1 + 1:
[7d6351e]	296	j1 = j
	297	else:
[892f246]	298	j = -1
	299	#Reset # of lines of data candidates
	300	i = -1
	301
[7d6351e]	302	# Couldn't parse this line, skip it
[8bd8ea4]	303	pass
[892f246]	304
[7d6351e]	305	input_f.close()
[8bd8ea4]	306	# Sanity check
[de1da34]	307	if has_error_dy == True and not len(y) == len(dy):
[a7a5886]	308	msg = "ascii_reader: y and dy have different length"
	309	raise RuntimeError, msg
[de1da34]	310	if has_error_dx == True and not len(x) == len(dx):
[a7a5886]	311	msg = "ascii_reader: y and dy have different length"
	312	raise RuntimeError, msg
[8bd8ea4]	313	# If the data length is zero, consider this as
	314	# though we were not able to read the file.
[a7a5886]	315	if len(x) == 0:
[daa56d0]	316	raise RuntimeError, "ascii_reader: could not load file"
[de1da34]	317
[a7a5886]	318	#Let's re-order the data to make cal.
	319	# curve look better some cases
	320	ind = numpy.lexsort((ty, tx))
[de1da34]	321	for i in ind:
	322	x[i] = tx[ind[i]]
	323	y[i] = ty[ind[i]]
	324	if has_error_dy == True:
	325	dy[i] = tdy[ind[i]]
	326	if has_error_dx == True:
	327	dx[i] = tdx[ind[i]]
[7d6351e]	328	# Zeros in dx, dy
[da96629]	329	if has_error_dx:
[7d6351e]	330	dx[dx == 0] = _ZERO
[da96629]	331	if has_error_dy:
[7d6351e]	332	dy[dy == 0] = _ZERO
	333	#Data
	334	output.x = x[x != 0]
	335	output.y = y[x != 0]
	336	output.dy = dy[x != 0] if has_error_dy == True\
	337	else numpy.zeros(len(output.y))
	338	output.dx = dx[x != 0] if has_error_dx == True\
	339	else numpy.zeros(len(output.x))
[fca90f82]	340
[99d1af6]	341	if data_conv_q is not None:
	342	output.xaxis("\\rm{Q}", output.x_unit)
	343	else:
	344	output.xaxis("\\rm{Q}", 'A^{-1}')
	345	if data_conv_i is not None:
[0e2aa40]	346	output.yaxis("\\rm{Intensity}", output.y_unit)
[99d1af6]	347	else:
[7d6351e]	348	output.yaxis("\\rm{Intensity}", "cm^{-1}")
[fe78c7b]	349
	350	# Store loading process information
[7d6351e]	351	output.meta_data['loader'] = self.type_name
[83b81b8]	352	if len(output.x) < 1:
	353	raise RuntimeError, "%s is empty" % path
[8bd8ea4]	354	return output
[892f246]	355
[8bd8ea4]	356	else:
	357	raise RuntimeError, "%s is not a file" % path
	358	return None

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source: sasview/src/sas/sascalc/dataloader/readers/ascii_reader.py @ b2669f5

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