fitting.py @ d23544dc

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 d23544dc was d23544dc, checked in by Gervaise Alina <gervyh@…>, 16 years ago
panel1d and 2 d for fitpanel refactored
Property mode set to `100644`
File size: 29.3 KB

Line
1	import os,os.path, re
2	import sys, wx, logging
3	import string, numpy, math
4
5	from copy import deepcopy
6	from danse.common.plottools.plottables import Data1D, Theory1D,Data2D
7	from danse.common.plottools.PlotPanel import PlotPanel
8	from sans.guicomm.events import NewPlotEvent, StatusEvent
9	from sans.fit.AbstractFitEngine import Model,Data,FitData1D,FitData2D
10	from fitproblem import FitProblem
11	from fitpanel import FitPanel
12
13	import models,modelpage
14	import fitpage1D,fitpage2D
15	import park
16	DEFAULT_BEAM = 0.005
17	class Plugin:
18	"""
19	Fitting plugin is used to perform fit
20	"""
21	def __init__(self):
22	## Plug-in name
23	self.sub_menu = "Fitting"
24
25	## Reference to the parent window
26	self.parent = None
27	self.menu_mng = models.ModelManager()
28	## List of panels for the simulation perspective (names)
29	self.perspective = []
30	# Start with a good default
31	self.elapsed = 0.022
32	self.fitter = None
33
34	#Flag to let the plug-in know that it is running standalone
35	self.standalone=True
36	## Fit engine
37	self._fit_engine = 'scipy'
38	self.enable_model2D=False
39	# Log startup
40	logging.info("Fitting plug-in started")
41
42	def populate_menu(self, id, owner):
43	"""
44	Create a menu for the Fitting plug-in
45	@param id: id to create a menu
46	@param owner: owner of menu
47	@ return : list of information to populate the main menu
48	"""
49	#Menu for fitting
50	self.menu1 = wx.Menu()
51	id1 = wx.NewId()
52	self.menu1.Append(id1, '&Show fit panel')
53	wx.EVT_MENU(owner, id1, self.on_perspective)
54	id3 = wx.NewId()
55	self.menu1.AppendCheckItem(id3, "park")
56	wx.EVT_MENU(owner, id3, self._onset_engine)
57
58	#menu for model
59	menu2 = wx.Menu()
60
61	self.menu_mng.populate_menu(menu2, owner)
62	id2 = wx.NewId()
63	owner.Bind(models.EVT_MODEL,self._on_model_menu)
64	#owner.Bind(modelpage.EVT_MODEL,self._on_model_menu)
65	self.fit_panel.set_owner(owner)
66	self.fit_panel.set_model_list(self.menu_mng.get_model_list())
67	owner.Bind(fitpage1D.EVT_MODEL_BOX,self._on_model_panel)
68	owner.Bind(fitpage2D.EVT_MODEL_BOX,self._on_model_panel)
69	#create menubar items
70	return [(id, self.menu1, "Fitting"),(id2, menu2, "Model")]
71
72
73	def help(self, evt):
74	"""
75	Show a general help dialog.
76	TODO: replace the text with a nice image
77	"""
78	from helpDialog import HelpWindow
79	dialog = HelpWindow(None, -1, 'HelpWindow')
80	if dialog.ShowModal() == wx.ID_OK:
81	pass
82	dialog.Destroy()
83
84
85	def get_context_menu(self, graph=None):
86	"""
87	Get the context menu items available for P(r)
88	@param graph: the Graph object to which we attach the context menu
89	@return: a list of menu items with call-back function
90	"""
91	self.graph=graph
92	for item in graph.plottables:
93	if item.__class__.__name__ is "Data2D":
94	return [["Select data for Fitting",\
95	"Dialog with fitting parameters ", self._onSelect]]
96	else:
97	if item.name==graph.selected_plottable and\
98	item.__class__.__name__ is "Data1D":
99	return [["Select data for Fitting", \
100	"Dialog with fitting parameters ", self._onSelect]]
101	return []
102
103
104	def get_panels(self, parent):
105	"""
106	Create and return a list of panel objects
107	"""
108	self.parent = parent
109	# Creation of the fit panel
110	self.fit_panel = FitPanel(self.parent, -1)
111	#Set the manager forthe main panel
112	self.fit_panel.set_manager(self)
113	# List of windows used for the perspective
114	self.perspective = []
115	self.perspective.append(self.fit_panel.window_name)
116	# take care of saving data, model and page associated with each other
117	self.page_finder = {}
118	#index number to create random model name
119	self.index_model = 0
120	#create the fitting panel
121	return [self.fit_panel]
122	def _on_show_panel(self, event):
123	print "_on_show_panel: fitting"
124
125	def get_perspective(self):
126	"""
127	Get the list of panel names for this perspective
128	"""
129	return self.perspective
130
131
132	def on_perspective(self, event):
133	"""
134	Call back function for the perspective menu item.
135	We notify the parent window that the perspective
136	has changed.
137	"""
138	self.parent.set_perspective(self.perspective)
139
140
141	def post_init(self):
142	"""
143	Post initialization call back to close the loose ends
144	[Somehow openGL needs this call]
145	"""
146	self.parent.set_perspective(self.perspective)
147
148
149	def _onSelect(self,event):
150	"""
151	when Select data to fit a new page is created .Its reference is
152	added to self.page_finder
153	"""
154	self.panel = event.GetEventObject()
155	for item in self.panel.graph.plottables:
156	if item.name == self.panel.graph.selected_plottable or\
157	item.__class__.__name__ is "Data2D":
158	#find a name for the page created for notebook
159	try:
160	page, model_name = self.fit_panel.add_fit_page(item)
161	# add data associated to the page created
162
163	if page !=None:
164
165	#create a fitproblem storing all link to data,model,page creation
166	self.page_finder[page]= FitProblem()
167	self.page_finder[page].save_model_name(model_name)
168	self.page_finder[page].add_data(item)
169	except:
170	wx.PostEvent(self.parent, StatusEvent(status="Creating Fit page: %s"\
171	%sys.exc_value))
172	def schedule_for_fit(self,value=0,fitproblem =None):
173	"""
174
175	"""
176	if fitproblem !=None:
177	fitproblem.schedule_tofit(value)
178	else:
179	current_pg=self.fit_panel.get_current_page()
180	for page, val in self.page_finder.iteritems():
181	if page ==current_pg :
182	val.schedule_tofit(value)
183	break
184
185
186	def get_page_finder(self):
187	""" @return self.page_finder used also by simfitpage.py"""
188	return self.page_finder
189
190
191	def set_page_finder(self,modelname,names,values):
192	"""
193	Used by simfitpage.py to reset a parameter given the string constrainst.
194	@param modelname: the name ot the model for with the parameter has to reset
195	@param value: can be a string in this case.
196	@param names: the paramter name
197	@note: expecting park used for fit.
198	"""
199	sim_page=self.fit_panel.get_page(0)
200	for page, value in self.page_finder.iteritems():
201	if page != sim_page:
202	list=value.get_model()
203	model=list[0]
204	#print "fitting",model.name,modelname
205	if model.name== modelname:
206	value.set_model_param(names,values)
207	break
208
209
210
211	def split_string(self,item):
212	"""
213	receive a word containing dot and split it. used to split parameterset
214	name into model name and parameter name example:
215	paramaterset (item) = M1.A
216	@return model_name =M1 , parameter name =A
217	"""
218	if string.find(item,".")!=-1:
219	param_names= re.split("\.",item)
220	model_name=param_names[0]
221	param_name=param_names[1]
222	return model_name,param_name
223
224
225	def _single_fit_completed(self,result,pars,cpage,qmin,qmax,ymin=None, ymax=None):
226	"""
227	Display fit result on one page of the notebook.
228	@param result: result of fit
229	@param pars: list of names of parameters fitted
230	@param current_pg: the page where information will be displayed
231	@param qmin: the minimum value of x to replot the model
232	@param qmax: the maximum value of x to replot model
233
234	"""
235	try:
236	for page, value in self.page_finder.iteritems():
237	if page==cpage :
238	#fitdata = value.get_data()
239	list = value.get_model()
240	model= list[0]
241	break
242	i = 0
243	# print "fitting: single fit pars ", pars
244	for name in pars:
245	if result.pvec.__class__==numpy.float64:
246	model.setParam(name,result.pvec)
247	else:
248	model.setParam(name,result.pvec[i])
249	# print "fitting: single fit", name, result.pvec[i]
250	i += 1
251	# print "fitting result : chisqr",result.fitness
252	# print "fitting result : pvec",result.pvec
253	# print "fitting result : stderr",result.stderr
254
255	cpage.onsetValues(result.fitness, result.pvec,result.stderr)
256	self.plot_helper(currpage=cpage,qmin=qmin,qmax=qmax,ymin=ymin, ymax=ymax)
257	except:
258	raise
259	wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value))
260
261
262	def _simul_fit_completed(self,result,qmin,qmax,ymin=None, ymax=None):
263	"""
264	Parameter estimation completed,
265	display the results to the user
266	@param alpha: estimated best alpha
267	@param elapsed: computation time
268	"""
269	try:
270	for page, value in self.page_finder.iteritems():
271	if value.get_scheduled()==1:
272	#fitdata = value.get_data()
273	list = value.get_model()
274	model= list[0]
275
276	small_out = []
277	small_cov = []
278	i = 0
279	#Separate result in to data corresponding to each page
280	for p in result.parameters:
281	model_name,param_name = self.split_string(p.name)
282	if model.name == model_name:
283	small_out.append(p.value )
284	small_cov.append(p.stderr)
285	model.setParam(param_name,p.value)
286	# Display result on each page
287	page.onsetValues(result.fitness, small_out,small_cov)
288	#Replot model
289	self.plot_helper(currpage= page,qmin= qmin,qmax= qmax,ymin=ymin, ymax=ymax)
290	except:
291	wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value))
292
293
294	def _on_single_fit(self,id=None,qmin=None,qmax=None,ymin=None,ymax=None):
295	"""
296	perform fit for the current page and return chisqr,out and cov
297	@param engineName: type of fit to be performed
298	@param id: unique id corresponding to a fit problem(model, set of data)
299	@param model: model to fit
300
301	"""
302	#print "in single fitting"
303	#set an engine to perform fit
304	from sans.fit.Fitting import Fit
305	self.fitter= Fit(self._fit_engine)
306	#Setting an id to store model and data in fit engine
307	if id==None:
308	id=0
309	self.id = id
310	page_fitted=None
311	fit_problem=None
312	#Get information (model , data) related to the page on
313	#with the fit will be perform
314	#current_pg=self.fit_panel.get_current_page()
315	#simul_pg=self.fit_panel.get_page(0)
316
317	for page, value in self.page_finder.iteritems():
318	if value.get_scheduled() ==1 :
319	metadata = value.get_data()
320	list=value.get_model()
321	model=list[0]
322	smearer= value.get_smearer()
323	#Create list of parameters for fitting used
324	pars=[]
325	templist=[]
326	try:
327	#templist=current_pg.get_param_list()
328	templist=page.get_param_list()
329	for element in templist:
330	pars.append(str(element[0].GetLabelText()))
331	pars.sort()
332	#Do the single fit
333	self.fitter.set_model(Model(model), self.id, pars)
334
335	self.fitter.set_data(metadata,self.id,smearer, qmin,qmax)
336	self.fitter.select_problem_for_fit(Uid=self.id,value=value.get_scheduled())
337	page_fitted=page
338	self.id+=1
339	self.schedule_for_fit( 0,value)
340	except:
341	wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value))
342	return
343	# make sure to keep an alphabetic order
344	#of parameter names in the list
345	try:
346	result=self.fitter.fit()
347	#self._single_fit_completed(result,pars,current_pg,qmin,qmax)
348	#print "single_fit: result",result.fitness,result.pvec,result.stderr
349	#self._single_fit_completed(result,pars,page,qmin,qmax)
350	self._single_fit_completed(result,pars,page_fitted,qmin,qmax,ymin,ymax)
351	except:
352	raise
353	wx.PostEvent(self.parent, StatusEvent(status="Single Fit error: %s" % sys.exc_value))
354	return
355
356	def _on_simul_fit(self, id=None,qmin=None,qmax=None, ymin=None, ymax=None):
357	"""
358	perform fit for all the pages selected on simpage and return chisqr,out and cov
359	@param engineName: type of fit to be performed
360	@param id: unique id corresponding to a fit problem(model, set of data)
361	in park_integration
362	@param model: model to fit
363
364	"""
365	#set an engine to perform fit
366	from sans.fit.Fitting import Fit
367	self.fitter= Fit(self._fit_engine)
368
369	#Setting an id to store model and data
370	if id==None:
371	id = 0
372	self.id = id
373
374	for page, value in self.page_finder.iteritems():
375	try:
376	if value.get_scheduled()==1:
377	metadata = value.get_data()
378	list = value.get_model()
379	model= list[0]
380	#Create dictionary of parameters for fitting used
381	pars = []
382	templist = []
383	templist = page.get_param_list()
384	for element in templist:
385	try:
386	name = str(element[0].GetLabelText())
387	pars.append(name)
388	except:
389	wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value))
390	return
391	new_model=Model(model)
392	param=value.get_model_param()
393
394	if len(param)>0:
395	for item in param:
396	param_value = item[1]
397	param_name = item[0]
398	#print "fitting ", param,param_name, param_value
399
400	#new_model.set( model.getParam(param_name[0])= param_value)
401	#new_model.set( exec"%s=%s"%(param_name[0], param_value))
402	#new_model.set( exec "%s"%(param_nam) = param_value)
403	new_model.parameterset[ param_name].set( param_value )
404
405	self.fitter.set_model(new_model, self.id, pars)
406	self.fitter.set_data(metadata,self.id,qmin,qmax,ymin,ymax)
407	self.fitter.select_problem_for_fit(Uid=self.id,value=value.get_scheduled())
408	self.id += 1
409	except:
410	wx.PostEvent(self.parent, StatusEvent(status="Fitting error: %s" % sys.exc_value))
411	return
412	#Do the simultaneous fit
413	try:
414	result=self.fitter.fit()
415	self._simul_fit_completed(result,qmin,qmax,ymin,ymax)
416	except:
417	wx.PostEvent(self.parent, StatusEvent(status="Simultaneous Fitting error: %s" % sys.exc_value))
418	return
419
420
421	def _onset_engine(self,event):
422	""" set engine to scipy"""
423	if self._fit_engine== 'park':
424	self._on_change_engine('scipy')
425	else:
426	self._on_change_engine('park')
427	wx.PostEvent(self.parent, StatusEvent(status="Engine set to: %s" % self._fit_engine))
428
429
430	def _on_change_engine(self, engine='park'):
431	"""
432	Allow to select the type of engine to perform fit
433	@param engine: the key work of the engine
434	"""
435	self._fit_engine = engine
436
437
438	def _on_model_panel(self, evt):
439	"""
440	react to model selection on any combo box or model menu.plot the model
441	"""
442
443	model = evt.model
444	name = evt.name
445	sim_page=self.fit_panel.get_page(0)
446	current_pg = self.fit_panel.get_current_page()
447	selected_page = self.fit_panel.get_selected_page()
448	if current_pg != sim_page:
449	current_pg.set_panel(model)
450	model.name = self.page_finder[current_pg].get_name()
451	try:
452	metadata=self.page_finder[current_pg].get_data()
453	M_name=model.name+"= "+name+"("+metadata.group_id+")"
454	except:
455	M_name=model.name+"= "+name
456	#model.name="M"+str(self.index_model)
457	self.index_model += 1
458	# save model name
459
460	# save the name containing the data name with the appropriate model
461	self.page_finder[current_pg].set_model(model,M_name)
462	self.plot_helper(currpage= current_pg,qmin= None,qmax= None)
463	sim_page.add_model(self.page_finder)
464
465	def set_smearer(self,smearer):
466	current_pg=self.fit_panel.get_current_page()
467	self.page_finder[current_pg].set_smearer(smearer)
468
469	def redraw_model(self,qmin= None,qmax= None):
470	"""
471	Draw a theory according to model changes or data range.
472	@param qmin: the minimum value plotted for theory
473	@param qmax: the maximum value plotted for theory
474	"""
475	current_pg=self.fit_panel.get_current_page()
476	for page, value in self.page_finder.iteritems():
477	if page ==current_pg :
478	break
479	self.plot_helper(currpage=page,qmin= qmin,qmax= qmax)
480
481	def plot_helper(self,currpage,qmin=None,qmax=None,ymin=None,ymax=None):
482	"""
483	Plot a theory given a model and data
484	@param model: the model from where the theory is derived
485	@param currpage: page in a dictionary referring to some data
486	"""
487	if self.fit_panel.get_page_count() >1:
488	for page in self.page_finder.iterkeys():
489	if page==currpage :
490	data=self.page_finder[page].get_data()
491	list=self.page_finder[page].get_model()
492	model=list[0]
493	break
494
495	if data!=None and data.__class__.__name__ != 'Data2D':
496	theory = Theory1D(x=[], y=[])
497	theory.name = model.name
498	theory.group_id = data.group_id
499	theory.id = "Model"
500	x_name, x_units = data.get_xaxis()
501	y_name, y_units = data.get_yaxis()
502	theory.xaxis(x_name, x_units)
503	theory.yaxis(y_name, y_units)
504	if qmin == None :
505	qmin = min(data.x)
506	if qmax == None :
507	qmax = max(data.x)
508	try:
509	tempx = qmin
510	tempy = model.run(qmin)
511	theory.x.append(tempx)
512	theory.y.append(tempy)
513	except :
514	wx.PostEvent(self.parent, StatusEvent(status="fitting \
515	skipping point x %g %s" %(qmin, sys.exc_value)))
516
517	for i in range(len(data.x)):
518	try:
519	if data.x[i]> qmin and data.x[i]< qmax:
520	tempx = data.x[i]
521	tempy = model.run(tempx)
522	theory.x.append(tempx)
523	theory.y.append(tempy)
524
525	except:
526	wx.PostEvent(self.parent, StatusEvent(status="fitting \
527	skipping point x %g %s" %(data.x[i], sys.exc_value)))
528	try:
529	tempx = qmax
530	tempy = model.run(qmax)
531	theory.x.append(tempx)
532	theory.y.append(tempy)
533	except:
534	wx.PostEvent(self.parent, StatusEvent(status="fitting \
535	skipping point x %g %s" %(qmax, sys.exc_value)))
536
537	else:
538	theory=Data2D(data.data, data.err_data)
539	theory.name= model.name
540	theory.id= "Model"
541	theory.group_id= "Model"+data.name
542	theory.x_bins= data.x_bins
543	theory.y_bins= data.y_bins
544	tempy=[]
545	if qmin==None:
546	qmin=data.xmin
547	if qmax==None:
548	qmax=data.xmax
549	if ymin==None:
550	ymin=data.ymin
551	if ymax==None:
552	ymax=data.ymax
553
554	theory.data = numpy.zeros((len(data.y_bins),len(data.x_bins)))
555	for i in range(len(data.y_bins)):
556	if data.y_bins[i]>= ymin and data.y_bins[i]<= ymax:
557	for j in range(len(data.x_bins)):
558	if data.x_bins[i]>= qmin and data.x_bins[i]<= qmax:
559	theory.data[j][i]=model.runXY([data.x_bins[j],data.y_bins[i]])
560
561	#print "fitting : plot_helper:", theory.image
562	#print data.image
563	#print "fitting : plot_helper:",theory.image
564	theory.detector= data.detector
565	theory.source= data.source
566	theory.zmin= data.zmin
567	theory.zmax= data.zmax
568	theory.xmin= qmin
569	theory.xmax= qmax
570	theory.ymin= ymin
571	theory.ymax= ymax
572
573	wx.PostEvent(self.parent, NewPlotEvent(plot=theory,
574	title="Analytical model %s"%str(data.name)))
575
576
577	def _on_model_menu(self, evt):
578	"""
579	Plot a theory from a model selected from the menu
580	"""
581	name = evt.model.__name__
582	if hasattr(evt.model, "name"):
583	name = evt.model.name
584	model=evt.model()
585	#name="Model View"
586	#print "mon menu",model.name
587	description=model.description
588	#self.fit_panel.add_model_page(model,description,name)
589
590	self.draw_model(model=model,name=name)
591
592	def draw_model(self,model,name ,description=None,enable1D=True, enable2D=False,qmin=None, qmax=None,qstep=None):
593	"""
594	draw model with default data value
595	"""
596
597	self.fit_panel.add_model_page(model=model,description=model.description,page_title=name)
598	self._draw_model2D(model=model,
599	description=model.description,
600	enable2D= enable2D,
601	qmin=qmin,
602	qmax=qmax,
603	qstep=None)
604	self._draw_model1D(model,name,model.description, enable1D,qmin,qmax, qstep)
605
606	def _draw_model1D(self,model,name,description=None, enable1D=True,qmin=None,qmax=None, qstep=None):
607
608	if enable1D:
609	if qmin==None:
610	qmin= 0.001
611	if qmax==None:
612	qmax= 1.0
613	if qstep ==None:
614	qstep =100
615
616	#print "x in data1D",qmin,qmax
617	#x = numpy.arange(qmin, qmax, qstep)
618	x= numpy.linspace(start= qmin,
619	stop= qmax,
620	num= qstep,
621	endpoint=True
622	)
623	xlen= len(x)
624	y = numpy.zeros(xlen)
625	if not enable1D:
626	for i in range(xlen):
627	y[i] = model.run(x[i])
628
629	try:
630	new_plot = Theory1D(x, y)
631	new_plot.name = name
632	new_plot.xaxis("\\rm{Q}", 'A^{-1}')
633	new_plot.yaxis("\\rm{Intensity} ","cm^{-1}")
634	new_plot.id = "Model"
635	new_plot.group_id ="Model"
636	wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot, title="Analytical model 1D"))
637
638	except:
639	raise
640	else:
641	for i in range(xlen):
642	y[i] = model.run(x[i])
643	#print x, y
644	try:
645	new_plot = Theory1D(x, y)
646	new_plot.name = name
647	new_plot.xaxis("\\rm{Q}", 'A^{-1}')
648	new_plot.yaxis("\\rm{Intensity} ","cm^{-1}")
649	new_plot.id ="Model"
650	new_plot.group_id ="Model"
651	wx.PostEvent(self.parent, NewPlotEvent(plot=new_plot,
652	title="Analytical model 1D " ))
653
654	except:
655	raise
656	def update(self, output,elapsed):
657	print "Got an update", elapsed
658	wx.PostEvent(self.parent, StatusEvent(status="Plot \
659	updating ... %g sec" % elapsed))
660
661	def complete(self, output, elapsed, model, qmin, qmax):
662	#printEVT("Calc complete in %g sec" % elapsed)
663	wx.PostEvent(self.parent, StatusEvent(status="Calc \
664	complete in %g sec" % elapsed))
665	#print "complete",output, model,qmin, qmax
666	data = output
667	theory= Data2D(data)
668	#print data.detector
669	#theory.detector= data.detector
670	from DataLoader.data_info import Detector, Source
671
672	detector = Detector()
673	theory.detector=[]
674	theory.detector.append(detector)
675
676	theory.detector[0].pixel_size.x= 5.0
677	theory.detector[0].pixel_size.y= 5.0
678	theory.source= Source()
679	theory.source.wavelength= 8.4
680	theory.detector[0].beam_center.x= 0
681	theory.detector[0].beam_center.y= 0
682	theory.detector[0].distance= 13705.0
683
684	theory.name= model.name
685	theory.group_id ="Model"
686	theory.id ="Model"
687	theory.xmin= -qmax
688	theory.xmax= qmax
689	theory.ymin= -qmax
690	theory.ymax= qmax
691	print "model draw comptele xmax",theory.xmax
692	wx.PostEvent(self.parent, NewPlotEvent(plot=theory,
693	title="Analytical model 2D %s" %str(model.name)))
694
695
696
697	def _draw_model2D(self,model,description=None, enable2D=False,qmin=None,qmax=None, qstep=None):
698	if qmin==None:
699	qmin= 0.0
700	if qmax==None:
701	qmax= 0.05
702	if qstep ==None:
703	qstep =100
704
705	x= numpy.linspace(start= -1*qmax,
706	stop= qmax,
707	num= qstep,
708	endpoint=True )
709	y = numpy.linspace(start= -1*qmax,
710	stop= qmax,
711	num= qstep,
712	endpoint=True )
713
714	lx = len(x)
715	#print x
716	data=numpy.zeros([len(x),len(y)])
717	self.model= model
718	if enable2D:
719	from model_thread import Calc2D
720	self.calc_thread = Calc2D(parent =self.parent,x=x,
721	y=y,model= self.model,
722	qmin=qmin,
723	qmax=qmax,
724	completefn=self.complete,
725	updatefn=self.update)
726	self.calc_thread.queue()
727	self.calc_thread.ready(2.5)
728
729
730	if __name__ == "__main__":
731	i = Plugin()
732
733
734
735

Note: See TracBrowser for help on using the repository browser.

SasView

source: sasview/sansview/perspectives/fitting/fitting.py @ d23544dc

Download in other formats: