ascii_reader.py @ c69b6d5

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 c69b6d5 was 5f2d3c78, checked in by Jae Cho <jhjcho@…>, 15 years ago
data line should be composed only with numbers in any of the columns. Added unittest and testdata
Property mode set to `100644`
File size: 14.6 KB

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

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source: sasview/DataLoader/readers/ascii_reader.py @ c69b6d5

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