ascii_reader.py @ 8f7936f

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 8f7936f was a7a5886, checked in by Gervaise Alina <gervyh@…>, 14 years ago
working pylint
Property mode set to `100644`
File size: 15.6 KB

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2
3	############################################################################
4	#This software was developed by the University of Tennessee as part of the
5	#Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
6	#project funded by the US National Science Foundation.
7	#If you use DANSE applications to do scientific research that leads to
8	#publication, we ask that you acknowledge the use of the software with the
9	#following sentence:
10	#This work benefited from DANSE software developed under NSF award DMR-0520547.
11	#copyright 2008, University of Tennessee
12	#############################################################################
13
14
15	import numpy
16	import os
17	from DataLoader.data_info import Data1D
18
19	# Check whether we have a converter available
20	has_converter = True
21	try:
22	from data_util.nxsunit import Converter
23	except:
24	has_converter = False
25
26	class Reader:
27	"""
28	Class to load ascii files (2, 3 or 4 columns).
29	"""
30	## File type
31	type_name = "ASCII"
32
33	## Wildcards
34	type = ["ASCII files (.txt)\|.txt",
35	"ASCII files (.dat)\|.dat",
36	"ASCII files (.abs)\|.abs"]
37	## List of allowed extensions
38	ext = ['.txt', '.TXT', '.dat', '.DAT', '.abs', '.ABS']
39
40	## Flag to bypass extension check
41	allow_all = True
42
43	def read(self, path):
44	"""
45	Load data file
46
47	:param path: file path
48
49	:return: Data1D object, or None
50
51	:raise RuntimeError: when the file can't be opened
52	:raise ValueError: when the length of the data vectors are inconsistent
53	"""
54	if os.path.isfile(path):
55	basename = os.path.basename(path)
56	_, extension = os.path.splitext(basename)
57	if self.allow_all or extension.lower() in self.ext:
58	try:
59	input_f = open(path,'r')
60	except :
61	raise RuntimeError, "ascii_reader: cannot open %s" % path
62	buff = input_f.read()
63	lines = buff.split('\n')
64
65	#Jae could not find python universal line spliter:
66	#keep the below for now
67	# some ascii data has \r line separator,
68	# try it when the data is on only one long line
69	if len(lines) < 2 :
70	lines = buff.split('\r')
71
72	x = numpy.zeros(0)
73	y = numpy.zeros(0)
74	dy = numpy.zeros(0)
75	dx = numpy.zeros(0)
76
77	#temp. space to sort data
78	tx = numpy.zeros(0)
79	ty = numpy.zeros(0)
80	tdy = numpy.zeros(0)
81	tdx = numpy.zeros(0)
82
83	output = Data1D(x, y, dy=dy, dx=dx)
84	self.filename = output.filename = basename
85
86	data_conv_q = None
87	data_conv_i = None
88
89	if has_converter == True and output.x_unit != '1/A':
90	data_conv_q = Converter('1/A')
91	# Test it
92	data_conv_q(1.0, output.x_unit)
93
94	if has_converter == True and output.y_unit != '1/cm':
95	data_conv_i = Converter('1/cm')
96	# Test it
97	data_conv_i(1.0, output.y_unit)
98
99
100	# The first good line of data will define whether
101	# we have 2-column or 3-column ascii
102	has_error_dx = None
103	has_error_dy = None
104
105	#Initialize counters for data lines and header lines.
106	is_data = False #Has more than 5 lines
107	# More than "5" lines of data is considered as actual
108	# data unless that is the only data
109	mum_data_lines = 5
110	# To count # of current data candidate lines
111	i = -1
112	# To count total # of previous data candidate lines
113	i1 = -1
114	# To count # of header lines
115	j = -1
116	# Helps to count # of header lines
117	j1 = -1
118	#minimum required number of columns of data; ( <= 4).
119	lentoks = 2
120	for line in lines:
121	toks = line.split()
122	try:
123	#Make sure that all columns are numbers.
124	for colnum in range(len(toks)):
125	float(toks[colnum])
126
127	_x = float(toks[0])
128	_y = float(toks[1])
129
130	#Reset the header line counters
131	if j == j1:
132	j = 0
133	j1 = 0
134
135	if i > 1:
136	is_data = True
137
138	if data_conv_q is not None:
139	_x = data_conv_q(_x, units=output.x_unit)
140
141	if data_conv_i is not None:
142	_y = data_conv_i(_y, units=output.y_unit)
143
144	# If we have an extra token, check
145	# whether it can be interpreted as a
146	# third column.
147	_dy = None
148	if len(toks) > 2:
149	try:
150	_dy = float(toks[2])
151
152	if data_conv_i is not None:
153	_dy = data_conv_i(_dy, units=output.y_unit)
154
155	except:
156	# The third column is not a float, skip it.
157	pass
158
159	# If we haven't set the 3rd column
160	# flag, set it now.
161	if has_error_dy == None:
162	has_error_dy = False if _dy == None else True
163
164	#Check for dx
165	_dx = None
166	if len(toks) > 3:
167	try:
168	_dx = float(toks[3])
169
170	if data_conv_i is not None:
171	_dx = data_conv_i(_dx, units=output.x_unit)
172
173	except:
174	# The 4th column is not a float, skip it.
175	pass
176
177	# If we haven't set the 3rd column
178	# flag, set it now.
179	if has_error_dx == None:
180	has_error_dx = False if _dx == None else True
181
182	#After talked with PB, we decided to take care of only
183	# 4 columns of data for now.
184	#number of columns in the current line
185	#To remember the # of columns in the current
186	#line of data
187	new_lentoks = len(toks)
188
189	#If the previous columns not equal to the current,
190	#mark the previous as non-data and reset the dependents.
191	if lentoks != new_lentoks :
192	if is_data == True:
193	break
194	else:
195	i = -1
196	i1 = 0
197	j = -1
198	j1 = -1
199
200
201	#Delete the previously stored lines of data candidates
202	# if is not data.
203	if i < 0 and -1 < i1 < mum_data_lines and \
204	is_data == False:
205	try:
206	x = numpy.zeros(0)
207	y = numpy.zeros(0)
208	except:
209	pass
210
211	x = numpy.append(x, _x)
212	y = numpy.append(y, _y)
213
214	if has_error_dy == True:
215	#Delete the previously stored lines of
216	# data candidates if is not data.
217	if i < 0 and -1 < i1 < mum_data_lines and \
218	is_data == False:
219	try:
220	dy = numpy.zeros(0)
221	except:
222	pass
223	dy = numpy.append(dy, _dy)
224
225	if has_error_dx == True:
226	#Delete the previously stored lines of
227	# data candidates if is not data.
228	if i < 0 and -1 < i1 < mum_data_lines and \
229	is_data == False:
230	try:
231	dx = numpy.zeros(0)
232	except:
233	pass
234	dx = numpy.append(dx, _dx)
235
236	#Same for temp.
237	#Delete the previously stored lines of data candidates
238	# if is not data.
239	if i < 0 and -1 < i1 < mum_data_lines and\
240	is_data == False:
241	try:
242	tx = numpy.zeros(0)
243	ty = numpy.zeros(0)
244	except:
245	pass
246
247	tx = numpy.append(tx, _x)
248	ty = numpy.append(ty, _y)
249
250	if has_error_dy == True:
251	#Delete the previously stored lines of
252	# data candidates if is not data.
253	if i < 0 and -1 < i1 < mum_data_lines and \
254	is_data == False:
255	try:
256	tdy = numpy.zeros(0)
257	except:
258	pass
259	tdy = numpy.append(tdy, _dy)
260	if has_error_dx == True:
261	#Delete the previously stored lines of
262	# data candidates if is not data.
263	if i < 0 and -1 < i1 < mum_data_lines and \
264	is_data == False:
265	try:
266	tdx = numpy.zeros(0)
267	except:
268	pass
269	tdx = numpy.append(tdx, _dx)
270
271	#reset i1 and flag lentoks for the next
272	if lentoks < new_lentoks:
273	if is_data == False:
274	i1 = -1
275	#To remember the # of columns on the current line
276	# for the next line of data
277	lentoks = len(toks)
278
279	#Reset # of header lines and counts #
280	# of data candidate lines
281	if j == 0 and j1 == 0:
282	i1 = i + 1
283	i += 1
284	except:
285
286	# It is data and meet non - number, then stop reading
287	if is_data == True:
288	break
289	lentoks = 2
290	#Counting # of header lines
291	j += 1
292	if j == j1 + 1:
293	j1 = j
294	else:
295	j = -1
296	#Reset # of lines of data candidates
297	i = -1
298
299	# Couldn't parse this line, skip it
300	pass
301
302	input_f.close()
303	# Sanity check
304	if has_error_dy == True and not len(y) == len(dy):
305	msg = "ascii_reader: y and dy have different length"
306	raise RuntimeError, msg
307	if has_error_dx == True and not len(x) == len(dx):
308	msg = "ascii_reader: y and dy have different length"
309	raise RuntimeError, msg
310	# If the data length is zero, consider this as
311	# though we were not able to read the file.
312	if len(x) == 0:
313	raise RuntimeError, "ascii_reader: could not load file"
314
315	#Let's re-order the data to make cal.
316	# curve look better some cases
317	ind = numpy.lexsort((ty, tx))
318	for i in ind:
319	x[i] = tx[ind[i]]
320	y[i] = ty[ind[i]]
321	if has_error_dy == True:
322	dy[i] = tdy[ind[i]]
323	if has_error_dx == True:
324	dx[i] = tdx[ind[i]]
325	#Data
326	output.x = x
327	output.y = y
328	output.dy = dy if has_error_dy == True else numpy.zeros(len(y))
329	output.dx = dx if has_error_dx == True else numpy.zeros(len(x))
330
331	if data_conv_q is not None:
332	output.xaxis("\\rm{Q}", output.x_unit)
333	else:
334	output.xaxis("\\rm{Q}", 'A^{-1}')
335	if data_conv_i is not None:
336	output.yaxis("\\rm{Intensity}", output.y_unit)
337	else:
338	output.yaxis("\\rm{Intensity}","cm^{-1}")
339
340	# Store loading process information
341	output.meta_data['loader'] = self.type_name
342
343	return output
344
345	else:
346	raise RuntimeError, "%s is not a file" % path
347	return None
348
349	if __name__ == "__main__":
350	reader = Reader()
351	#print reader.read("../test/test_3_columns.txt")
352	print reader.read("../test/empty.txt")
353
354
355

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source: sasview/DataLoader/readers/ascii_reader.py @ 8f7936f

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