red2d_reader.py @ 095ab1b

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 095ab1b was 3cd95c8, checked in by Jae Cho <jhjcho@…>, 15 years ago
new sans qmap 2D reader that enables reading TOF sans data as well as some other type of detector data
Property mode set to `100644`
File size: 10.9 KB

Line
1	"""
2	TXT/IGOR 2D Q Map file reader
3	"""
4
5	"""
6	This software was developed by the University of Tennessee as part of the
7	Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
8	project funded by the US National Science Foundation.
9
10	If you use DANSE applications to do scientific research that leads to
11	publication, we ask that you acknowledge the use of the software with the
12	following sentence:
13
14	"This work benefited from DANSE software developed under NSF award DMR-0520547."
15
16	copyright 2008, University of Tennessee
17	"""
18
19	import os, sys
20	import numpy
21	import math, logging
22	from DataLoader.data_info import Data2D, Detector
23
24	# Look for unit converter
25	has_converter = True
26	try:
27	from data_util.nxsunit import Converter
28	except:
29	has_converter = False
30
31	class Reader:
32	""" Simple data reader for Igor data files """
33	## File type
34	type_name = "IGOR/DAT 2D Q_map"
35	## Wildcards
36	type = ["IGOR/DAT 2D file in Q_map (.dat)\|.DAT"]
37	## Extension
38	ext=['.DAT', '.dat']
39
40	def read(self,filename=None):
41	""" Read file """
42	if not os.path.isfile(filename):
43	raise ValueError, \
44	"Specified file %s is not a regular file" % filename
45
46	# Read file
47	f = open(filename,'r')
48	buf = f.read()
49
50	# Instantiate data object
51	output = Data2D()
52	output.filename = os.path.basename(filename)
53	detector = Detector()
54	if len(output.detector)>0: print str(output.detector[0])
55	output.detector.append(detector)
56
57	# Get content
58	dataStarted = False
59
60	## Defaults
61	lines = buf.split('\n')
62	itot = 0
63	x = []
64	y = []
65
66	ncounts = 0
67
68	wavelength = None
69	distance = None
70	transmission = None
71
72	pixel_x = None
73	pixel_y = None
74
75	i_x = 0
76	i_y = -1
77	pixels = 0
78
79	isInfo = False
80	isCenter = False
81
82	data_conv_q = None
83	data_conv_i = None
84
85	# Set units: This is the unit assumed for Q and I in the data file.
86	if has_converter == True and output.Q_unit != '1/A':
87	data_conv_q = Converter('1/A')
88	# Test it
89	data_conv_q(1.0, output.Q_unit)
90
91	if has_converter == True and output.I_unit != '1/cm':
92	data_conv_i = Converter('1/cm')
93	# Test it
94	data_conv_i(1.0, output.I_unit)
95
96	#Set the space for data
97	data = numpy.zeros(0)
98	qx_data = numpy.zeros(0)
99	qy_data = numpy.zeros(0)
100	q_data = numpy.zeros(0)
101	dqx_data = numpy.zeros(0)
102	dqy_data = numpy.zeros(0)
103	mask = numpy.zeros(0,dtype=bool)
104
105	#Read Header and 2D data
106	for line in lines:
107	## Reading the header applies only to IGOR/NIST 2D q_map data files
108	# Find setup info line
109	if isInfo:
110	isInfo = False
111	line_toks = line.split()
112	# Wavelength in Angstrom
113	try:
114	wavelength = float(line_toks[1])
115	# Units
116	if has_converter==True and output.source.wavelength_unit != 'A':
117	conv = Converter('A')
118	wavelength = conv(wavelength, units=output.source.wavelength_unit)
119	except:
120	#Not required
121	pass
122	# Distance in mm
123	try:
124	distance = float(line_toks[3])
125	# Units
126	if has_converter==True and detector.distance_unit != 'm':
127	conv = Converter('m')
128	distance = conv(distance, units=detector.distance_unit)
129	except:
130	#Not required
131	pass
132
133	# Distance in meters
134	try:
135	transmission = float(line_toks[4])
136	except:
137	#Not required
138	pass
139
140	if line.count("LAMBDA")>0:
141	isInfo = True
142
143	# Find center info line
144	if isCenter:
145	isCenter = False
146	line_toks = line.split()
147	# Center in bin number
148	center_x = float(line_toks[0])
149	center_y = float(line_toks[1])
150
151	if line.count("BCENT")>0:
152	isCenter = True
153
154	# Find data start
155	if line.count("Data columns") or line.count("ASCII data")>0:
156	dataStarted = True
157	continue
158
159	## Read and get data.
160	if dataStarted == True:
161	line_toks = line.split()
162	if len(line_toks) == 0:
163	#empty line
164	continue
165	elif len(line_toks) < 2:
166	#Q-map 2d require 3 or more columns of data
167	raise ValueError,"Igor_Qmap_Reader: Can't read this file: Not a proper file format"
168
169	# defaults
170	dqx_value = None
171	dqy_value = None
172	qz_value = None
173	mask_value = 0
174
175	##Read and get data values
176	qx_value = float(line_toks[0])
177	qy_value = float(line_toks[1])
178	value = float(line_toks[2])
179
180	try:
181	#Read qz_value if exist on 4th column
182	qz_value = float(line_toks[3])
183	except:
184	# Found a non-float entry, skip it: Not required.
185	pass
186	try:
187	#Read qz_value if exist on 5th column
188	dqx_value = float(line_toks[4])
189	except:
190	# Found a non-float entry, skip it: Not required.
191	pass
192	try:
193	#Read qz_value if exist on 6th column
194	dqy_value = float(line_toks[5])
195	except:
196	# Found a non-float entry, skip it: Not required.
197	pass
198	try:
199	#Read beam block mask if exist on 7th column
200	mask_value = float(line_toks[6])
201	except:
202	# Found a non-float entry, skip it
203	pass
204
205	# get data
206	data = numpy.append(data, value)
207	qx_data = numpy.append(qx_data, qx_value)
208	qy_data = numpy.append(qy_data, qy_value)
209
210	# optional data
211	if dqx_value != None and numpy.isfinite(dqx_value):
212	dqx_data = numpy.append(dqx_data, dqx_value)
213	if dqy_value != None and numpy.isfinite(dqy_value):
214	dqy_data = numpy.append(dqy_data, dqy_value)
215
216	# default data
217	if qz_value == None or not numpy.isfinite(qz_value):
218	qz_value = 0
219	if not numpy.isfinite(mask_value)or mask_value ==0 :
220	mask_value = 1
221	q_data = numpy.append(q_data,numpy.sqrt(qx_value2+qy_value2+qz_value**2))
222	# Note: For convenience, mask = False stands for masked while mask = True for unmasked
223	mask = numpy.append(mask,(mask_value>=1))
224
225	# Store limits of the image in q space
226	xmin = numpy.min(qx_data)
227	xmax = numpy.max(qx_data)
228	ymin = numpy.min(qy_data)
229	ymax = numpy.max(qy_data)
230
231	# units
232	if has_converter == True and output.Q_unit != '1/A':
233	xmin = data_conv_q(xmin, units=output.Q_unit)
234	xmax = data_conv_q(xmax, units=output.Q_unit)
235	ymin = data_conv_q(ymin, units=output.Q_unit)
236	ymax = data_conv_q(ymax, units=output.Q_unit)
237
238	## calculate the range of the qx and qy_data
239	x_size = math.fabs(xmax - xmin)
240	y_size = math.fabs(ymax - ymin)
241
242	# calculate the number of pixels in the each axes
243	npix_y = math.floor(math.sqrt(len(data)))
244	npix_x = math.floor(len(data)/npix_y)
245
246	# calculate the size of bins
247	xstep = x_size/(npix_x-1)
248	ystep = y_size/(npix_y-1)
249
250	# store x and y axis bin centers in q space
251	x_bins = numpy.arange(xmin,xmax+xstep,xstep)
252	y_bins = numpy.arange(ymin,ymax+ystep,ystep)
253
254	# get the limits of q values
255	xmin = xmin - xstep/2
256	xmax = xmax + xstep/2
257	ymin = ymin - ystep/2
258	ymax = ymax + ystep/2
259
260	#Store data in outputs
261	#TODO: Check the lengths
262	output.data = data
263	output.err_data = numpy.sqrt(numpy.abs(data))
264	output.qx_data = qx_data
265	output.qy_data = qy_data
266	output.q_data = q_data
267	output.mask = mask
268
269	output.x_bins = x_bins
270	output.y_bins = y_bins
271
272	output.xmin = xmin
273	output.xmax = xmax
274	output.ymin = ymin
275	output.ymax = ymax
276
277	output.source.wavelength = wavelength
278
279	# Store pixel size in mm
280	detector.pixel_size.x = pixel_x
281	detector.pixel_size.y = pixel_y
282
283	# Store the sample to detector distance
284	detector.distance = distance
285
286	# optional data: if any of dq data == 0, do not pass to output
287	if len(dqx_data) == len(qx_data):
288	output.dqx_data = dqx_data
289	if len(dqy_data) == len(qy_data):
290	output.dqy_data = dqy_data
291
292	# Units of axes
293	if data_conv_q is not None:
294	output.xaxis("\\rm{Q_{x}}", output.Q_unit)
295	output.yaxis("\\rm{Q_{y}}", output.Q_unit)
296	else:
297	output.xaxis("\\rm{Q_{x}}", 'A^{-1}')
298	output.yaxis("\\rm{Q_{y}}", 'A^{-1}')
299	if data_conv_i is not None:
300	output.zaxis("\\rm{Intensity}", output.I_unit)
301	else:
302	output.zaxis("\\rm{Intensity}","cm^{-1}")
303
304	# Store loading process information
305	output.meta_data['loader'] = self.type_name
306
307	return output
308
309	if __name__ == "__main__":
310	reader = Reader()
311	print reader.read("../test/exp18_14_igor_2dqxqy.dat")
312

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source: sasview/DataLoader/readers/red2d_reader.py @ 095ab1b

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