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source: trunk/python/asapfitter.py @ 2666

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Last change on this file since 2666 was 2666, checked in by Malte Marquarding, 12 years ago
Ticket #173: added setting of constraints on the fitter.
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 26.9 KB

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1	import _asap
2	from asap.parameters import rcParams
3	from asap.logging import asaplog, asaplog_post_dec
4	from asap.utils import _n_bools, mask_and
5	from numpy import ndarray
6
7	class fitter:
8	"""
9	The fitting class for ASAP.
10	"""
11	def __init__(self):
12	"""
13	Create a fitter object. No state is set.
14	"""
15	self.fitter = _asap.fitter()
16	self.x = None
17	self.y = None
18	self.mask = None
19	self.fitfunc = None
20	self.fitfuncs = None
21	self.fitted = False
22	self.data = None
23	self.components = 0
24	self._fittedrow = 0
25	self._p = None
26	self._selection = None
27	self.uselinear = False
28	self._constraints = []
29
30	def set_data(self, xdat, ydat, mask=None):
31	"""
32	Set the absissa and ordinate for the fit. Also set the mask
33	indicating valid points.
34	This can be used for data vectors retrieved from a scantable.
35	For scantable fitting use 'fitter.set_scan(scan, mask)'.
36	Parameters:
37	xdat: the abcissa values
38	ydat: the ordinate values
39	mask: an optional mask
40
41	"""
42	self.fitted = False
43	self.x = xdat
44	self.y = ydat
45	if mask == None:
46	self.mask = _n_bools(len(xdat), True)
47	else:
48	self.mask = mask
49	return
50
51	@asaplog_post_dec
52	def set_scan(self, thescan=None, mask=None):
53	"""
54	Set the 'data' (a scantable) of the fitter.
55	Parameters:
56	thescan: a scantable
57	mask: a msk retrieved from the scantable
58	"""
59	if not thescan:
60	msg = "Please give a correct scan"
61	raise TypeError(msg)
62	self.fitted = False
63	self.data = thescan
64	self.mask = None
65	if mask is None:
66	self.mask = _n_bools(self.data.nchan(), True)
67	else:
68	self.mask = mask
69	return
70
71	@asaplog_post_dec
72	def set_function(self, **kwargs):
73	"""
74	Set the function to be fit.
75	Parameters:
76	poly: use a polynomial of the order given with nonlinear
77	least squares fit
78	lpoly: use polynomial of the order given with linear least
79	squares fit
80	gauss: fit the number of gaussian specified
81	lorentz: fit the number of lorentzian specified
82	sinusoid: fit the number of sinusoid specified
83	Example:
84	fitter.set_function(poly=3) # will fit a 3rd order polynomial
85	# via nonlinear method
86	fitter.set_function(lpoly=3) # will fit a 3rd order polynomial
87	# via linear method
88	fitter.set_function(gauss=2) # will fit two gaussians
89	fitter.set_function(lorentz=2) # will fit two lorentzians
90	fitter.set_function(sinusoid=3) # will fit three sinusoids
91	"""
92	#default poly order 0
93	n=0
94	if kwargs.has_key('poly'):
95	self.fitfunc = 'poly'
96	self.fitfuncs = ['poly']
97	n = kwargs.get('poly')
98	self.components = [n+1]
99	self.uselinear = False
100	elif kwargs.has_key('lpoly'):
101	self.fitfunc = 'poly'
102	self.fitfuncs = ['lpoly']
103	n = kwargs.get('lpoly')
104	self.components = [n+1]
105	self.uselinear = True
106	elif kwargs.has_key('gauss'):
107	n = kwargs.get('gauss')
108	self.fitfunc = 'gauss'
109	self.fitfuncs = [ 'gauss' for i in range(n) ]
110	self.components = [ 3 for i in range(n) ]
111	self.uselinear = False
112	elif kwargs.has_key('lorentz'):
113	n = kwargs.get('lorentz')
114	self.fitfunc = 'lorentz'
115	self.fitfuncs = [ 'lorentz' for i in range(n) ]
116	self.components = [ 3 for i in range(n) ]
117	self.uselinear = False
118	elif kwargs.has_key('sinusoid'):
119	n = kwargs.get('sinusoid')
120	self.fitfunc = 'sinusoid'
121	self.fitfuncs = [ 'sinusoid' for i in range(n) ]
122	self.components = [ 3 for i in range(n) ]
123	self.uselinear = False
124	elif kwargs.has_key('expression'):
125	self.uselinear = False
126	raise RuntimeError("Not yet implemented")
127	else:
128	msg = "Invalid function type."
129	raise TypeError(msg)
130
131	self.fitter.setexpression(self.fitfunc,n)
132	self._constraints = []
133	self.fitted = False
134	return
135
136	@asaplog_post_dec
137	def fit(self, row=0, estimate=False):
138	"""
139	Execute the actual fitting process. All the state has to be set.
140	Parameters:
141	row: specify the row in the scantable
142	estimate: auto-compute an initial parameter set (default False)
143	This can be used to compute estimates even if fit was
144	called before.
145	Example:
146	s = scantable('myscan.asap')
147	s.set_cursor(thepol=1) # select second pol
148	f = fitter()
149	f.set_scan(s)
150	f.set_function(poly=0)
151	f.fit(row=0) # fit first row
152	"""
153	if ((self.x is None or self.y is None) and self.data is None) \
154	or self.fitfunc is None:
155	msg = "Fitter not yet initialised. Please set data & fit function"
156	raise RuntimeError(msg)
157
158	if self.data is not None:
159	self.x = self.data._getabcissa(row)
160	self.y = self.data._getspectrum(row)
161	#self.mask = mask_and(self.mask, self.data._getmask(row))
162	if len(self.x) == len(self.mask):
163	self.mask = mask_and(self.mask, self.data._getmask(row))
164	else:
165	asaplog.push('lengths of data and mask are not the same. '
166	'preset mask will be ignored')
167	asaplog.post('WARN','asapfit.fit')
168	self.mask=self.data._getmask(row)
169	asaplog.push("Fitting:")
170	i = row
171	out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
172	self.data.getscan(i),
173	self.data.getbeam(i),
174	self.data.getif(i),
175	self.data.getpol(i),
176	self.data.getcycle(i))
177
178	asaplog.push(out, False)
179
180	self.fitter.setdata(self.x, self.y, self.mask)
181	if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
182	ps = self.fitter.getparameters()
183	if len(ps) == 0 or estimate:
184	self.fitter.estimate()
185	fxdpar = list(self.fitter.getfixedparameters())
186	if len(fxdpar) and fxdpar.count(0) == 0:
187	raise RuntimeError,"No point fitting, if all parameters are fixed."
188	if self._constraints:
189	for c in self._constraints:
190	self.fitter.addconstraint(c[0]+[c[-1]])
191	if self.uselinear:
192	converged = self.fitter.lfit()
193	else:
194	converged = self.fitter.fit()
195	if not converged:
196	raise RuntimeError,"Fit didn't converge."
197	self._fittedrow = row
198	self.fitted = True
199	return
200
201	def store_fit(self, filename=None):
202	"""
203	Save the fit parameters.
204	Parameters:
205	filename: if specified save as an ASCII file, if None (default)
206	store it in the scnatable
207	"""
208	if self.fitted and self.data is not None:
209	pars = list(self.fitter.getparameters())
210	fixed = list(self.fitter.getfixedparameters())
211	from asap.asapfit import asapfit
212	fit = asapfit()
213	fit.setparameters(pars)
214	fit.setfixedparameters(fixed)
215	fit.setfunctions(self.fitfuncs)
216	fit.setcomponents(self.components)
217	fit.setframeinfo(self.data._getcoordinfo())
218	if filename is not None:
219	import os
220	filename = os.path.expandvars(os.path.expanduser(filename))
221	if os.path.exists(filename):
222	raise IOError("File '%s' exists." % filename)
223	fit.save(filename)
224	else:
225	self.data._addfit(fit,self._fittedrow)
226
227	@asaplog_post_dec
228	def set_parameters(self,args,*kwargs):
229	"""
230	Set the parameters to be fitted.
231	Parameters:
232	params: a vector of parameters
233	fixed: a vector of which parameters are to be held fixed
234	(default is none)
235	component: in case of multiple gaussians/lorentzians/sinusoidals,
236	the index of the target component
237	"""
238	component = None
239	fixed = None
240	params = None
241
242	if len(args) and isinstance(args[0],dict):
243	kwargs = args[0]
244	if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
245	if kwargs.has_key("params"): params = kwargs["params"]
246	if len(args) == 2 and isinstance(args[1], int):
247	component = args[1]
248	if self.fitfunc is None:
249	msg = "Please specify a fitting function first."
250	raise RuntimeError(msg)
251	if (self.fitfunc == "gauss" or self.fitfunc == "lorentz"
252	or self.fitfunc == "sinusoid") and component is not None:
253	if not self.fitted and sum(self.fitter.getparameters()) == 0:
254	pars = _n_bools(len(self.components)*3, False)
255	fxd = _n_bools(len(pars), False)
256	else:
257	pars = list(self.fitter.getparameters())
258	fxd = list(self.fitter.getfixedparameters())
259	i = 3*component
260	pars[i:i+3] = params
261	fxd[i:i+3] = fixed
262	params = pars
263	fixed = fxd
264	self.fitter.setparameters(params)
265	if fixed is not None:
266	self.fitter.setfixedparameters(fixed)
267	return
268
269	@asaplog_post_dec
270	def set_gauss_parameters(self, peak, centre, fwhm,
271	peakfixed=0, centrefixed=0,
272	fwhmfixed=0,
273	component=0):
274	"""
275	Set the Parameters of a 'Gaussian' component, set with set_function.
276	Parameters:
277	peak, centre, fwhm: The gaussian parameters
278	peakfixed,
279	centrefixed,
280	fwhmfixed: Optional parameters to indicate if
281	the paramters should be held fixed during
282	the fitting process. The default is to keep
283	all parameters flexible.
284	component: The number of the component (Default is the
285	component 0)
286	"""
287	if self.fitfunc != "gauss":
288	msg = "Function only operates on Gaussian components."
289	raise ValueError(msg)
290	if 0 <= component < len(self.components):
291	d = {'params':[peak, centre, fwhm],
292	'fixed':[peakfixed, centrefixed, fwhmfixed]}
293	self.set_parameters(d, component)
294	else:
295	msg = "Please select a valid component."
296	raise ValueError(msg)
297
298	@asaplog_post_dec
299	def set_lorentz_parameters(self, peak, centre, fwhm,
300	peakfixed=0, centrefixed=0,
301	fwhmfixed=0,
302	component=0):
303	"""
304	Set the Parameters of a 'Lorentzian' component, set with set_function.
305	Parameters:
306	peak, centre, fwhm: The lorentzian parameters
307	peakfixed,
308	centrefixed,
309	fwhmfixed: Optional parameters to indicate if
310	the paramters should be held fixed during
311	the fitting process. The default is to keep
312	all parameters flexible.
313	component: The number of the component (Default is the
314	component 0)
315	"""
316	if self.fitfunc != "lorentz":
317	msg = "Function only operates on Lorentzian components."
318	raise ValueError(msg)
319	if 0 <= component < len(self.components):
320	d = {'params':[peak, centre, fwhm],
321	'fixed':[peakfixed, centrefixed, fwhmfixed]}
322	self.set_parameters(d, component)
323	else:
324	msg = "Please select a valid component."
325	raise ValueError(msg)
326
327	@asaplog_post_dec
328	def set_sinusoid_parameters(self, ampl, period, x0,
329	amplfixed=0, periodfixed=0,
330	x0fixed=0,
331	component=0):
332	"""
333	Set the Parameters of a 'Sinusoidal' component, set with set_function.
334	Parameters:
335	ampl, period, x0: The sinusoidal parameters
336	amplfixed,
337	periodfixed,
338	x0fixed: Optional parameters to indicate if
339	the paramters should be held fixed during
340	the fitting process. The default is to keep
341	all parameters flexible.
342	component: The number of the component (Default is the
343	component 0)
344	"""
345	if self.fitfunc != "sinusoid":
346	msg = "Function only operates on Sinusoidal components."
347	raise ValueError(msg)
348	if 0 <= component < len(self.components):
349	d = {'params':[ampl, period, x0],
350	'fixed': [amplfixed, periodfixed, x0fixed]}
351	self.set_parameters(d, component)
352	else:
353	msg = "Please select a valid component."
354	raise ValueError(msg)
355
356
357	def add_constraint(self, xpar, y):
358	"""Add parameter constraints to the fit. This is done by setting up
359	linear equations for the related parameters.
360
361	For example a two component gaussian fit where the amplitudes are
362	constraint by amp1 = 2*amp2
363	needs a constraint
364
365	add_constraint([1, 0, 0, -2, 0, 0, 0], 0)
366
367	a velocity difference of v2-v1=17
368
369	add_constraint([0.,-1.,0.,0.,1.,0.], 17.)
370
371	"""
372	self._constraints.append((xpar, y))
373
374
375	def get_area(self, component=None):
376	"""
377	Return the area under the fitted gaussian/lorentzian component.
378	Parameters:
379	component: the gaussian/lorentzian component selection,
380	default (None) is the sum of all components
381	Note:
382	This will only work for gaussian/lorentzian fits.
383	"""
384	if not self.fitted: return
385	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
386	pars = list(self.fitter.getparameters())
387	from math import log,pi,sqrt
388	if self.fitfunc == "gauss":
389	fac = sqrt(pi/log(16.0))
390	elif self.fitfunc == "lorentz":
391	fac = pi/2.0
392	areas = []
393	for i in range(len(self.components)):
394	j = i*3
395	cpars = pars[j:j+3]
396	areas.append(fac * cpars[0] * cpars[2])
397	else:
398	return None
399	if component is not None:
400	return areas[component]
401	else:
402	return sum(areas)
403
404	@asaplog_post_dec
405	def get_errors(self, component=None):
406	"""
407	Return the errors in the parameters.
408	Parameters:
409	component: get the errors for the specified component
410	only, default is all components
411	"""
412	if not self.fitted:
413	msg = "Not yet fitted."
414	raise RuntimeError(msg)
415	errs = list(self.fitter.geterrors())
416	cerrs = errs
417	if component is not None:
418	if self.fitfunc == "gauss" or self.fitfunc == "lorentz" \
419	or self.fitfunc == "sinusoid":
420	i = 3*component
421	if i < len(errs):
422	cerrs = errs[i:i+3]
423	return cerrs
424
425
426	@asaplog_post_dec
427	def get_parameters(self, component=None, errors=False):
428	"""
429	Return the fit paramters.
430	Parameters:
431	component: get the parameters for the specified component
432	only, default is all components
433	"""
434	if not self.fitted:
435	msg = "Not yet fitted."
436	raise RuntimeError(msg)
437	pars = list(self.fitter.getparameters())
438	fixed = list(self.fitter.getfixedparameters())
439	errs = list(self.fitter.geterrors())
440	area = []
441	if component is not None:
442	if self.fitfunc == "poly" or self.fitfunc == "lpoly":
443	cpars = pars
444	cfixed = fixed
445	cerrs = errs
446	else:
447	i = 3*component
448	cpars = pars[i:i+3]
449	cfixed = fixed[i:i+3]
450	cerrs = errs[i:i+3]
451	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
452	a = self.get_area(component)
453	area = [a for i in range(3)]
454	else:
455	cpars = pars
456	cfixed = fixed
457	cerrs = errs
458	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
459	for c in range(len(self.components)):
460	a = self.get_area(c)
461	area += [a for i in range(3)]
462	fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
463	asaplog.push(fpars)
464	return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
465	'errors':cerrs}
466
467	def _format_pars(self, pars, fixed, errors, area):
468	out = ''
469	if self.fitfunc == "poly" or self.fitfunc == "lpoly":
470	c = 0
471	for i in range(len(pars)):
472	fix = ""
473	if len(fixed) and fixed[i]: fix = "(fixed)"
474	out += " p%d%s= %3.6f" % (c, fix, pars[i])
475	if errors : out += " (%1.6f)" % errors[i]
476	out += ","
477	c+=1
478	out = out[:-1] # remove trailing ','
479	else:
480	i = 0
481	c = 0
482	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
483	pnam = ["peak", "centre", "FWHM"]
484	elif self.fitfunc == "sinusoid":
485	pnam = ["amplitude", "period", "x0"]
486	aunit = ""
487	ounit = ""
488	if self.data:
489	aunit = self.data.get_unit()
490	ounit = self.data.get_fluxunit()
491	while i < len(pars):
492	fix0 = fix1 = fix2 = ""
493	if i < len(fixed)-2:
494	if fixed[i]: fix0 = "(fixed)"
495	if fixed[i+1]: fix1 = "(fixed)"
496	if fixed[i+2]: fix2 = "(fixed)"
497	out += " %2d: " % c
498	out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit)
499	out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit)
500	out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit)
501	if len(area): out += " area = %3.3f %s %s\n" % (area[i],
502	ounit,
503	aunit)
504	c+=1
505	i+=3
506	return out
507
508
509	@asaplog_post_dec
510	def get_estimate(self):
511	"""
512	Return the parameter estimates (for non-linear functions).
513	"""
514	pars = self.fitter.getestimate()
515	fixed = self.fitter.getfixedparameters()
516	asaplog.push(self._format_pars(pars,fixed,None,None))
517	return pars
518
519	@asaplog_post_dec
520	def get_residual(self):
521	"""
522	Return the residual of the fit.
523	"""
524	if not self.fitted:
525	msg = "Not yet fitted."
526	raise RuntimeError(msg)
527	return self.fitter.getresidual()
528
529	@asaplog_post_dec
530	def get_chi2(self):
531	"""
532	Return chi^2.
533	"""
534	if not self.fitted:
535	msg = "Not yet fitted."
536	raise RuntimeError(msg)
537	ch2 = self.fitter.getchi2()
538	asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
539	return ch2
540
541	@asaplog_post_dec
542	def get_fit(self):
543	"""
544	Return the fitted ordinate values.
545	"""
546	if not self.fitted:
547	msg = "Not yet fitted."
548	raise RuntimeError(msg)
549	return self.fitter.getfit()
550
551	@asaplog_post_dec
552	def commit(self):
553	"""
554	Return a new scan where the fits have been commited (subtracted)
555	"""
556	if not self.fitted:
557	msg = "Not yet fitted."
558	raise RuntimeError(msg)
559	from asap import scantable
560	if not isinstance(self.data, scantable):
561	msg = "Not a scantable"
562	raise TypeError(msg)
563	scan = self.data.copy()
564	scan._setspectrum(self.fitter.getresidual())
565	return scan
566
567	@asaplog_post_dec
568	def plot(self, residual=False, components=None, plotparms=False,
569	filename=None):
570	"""
571	Plot the last fit.
572	Parameters:
573	residual: an optional parameter indicating if the residual
574	should be plotted (default 'False')
575	components: a list of components to plot, e.g [0,1],
576	-1 plots the total fit. Default is to only
577	plot the total fit.
578	plotparms: Inidicates if the parameter values should be present
579	on the plot
580	"""
581	from matplotlib import rc as rcp
582	if not self.fitted:
583	return
584	#if not self._p or self._p.is_dead:
585	if not (self._p and self._p._alive()):
586	from asap.asapplotter import new_asaplot
587	del self._p
588	self._p = new_asaplot(rcParams['plotter.gui'])
589	self._p.hold()
590	self._p.clear()
591	rcp('lines', linewidth=1)
592	self._p.set_panels()
593	self._p.palette(0)
594	tlab = 'Spectrum'
595	xlab = 'Abcissa'
596	ylab = 'Ordinate'
597	from numpy import ma,logical_not,logical_and,array
598	m = self.mask
599	if self.data:
600	tlab = self.data._getsourcename(self._fittedrow)
601	xlab = self.data._getabcissalabel(self._fittedrow)
602	if self.data._getflagrow(self._fittedrow):
603	m = [False]
604	else:
605	m = logical_and(self.mask,
606	array(self.data._getmask(self._fittedrow),
607	copy=False))
608
609	ylab = self.data._get_ordinate_label()
610
611	colours = ["#777777","#dddddd","red","orange","purple","green",
612	"magenta", "cyan"]
613	nomask=True
614	for i in range(len(m)):
615	nomask = nomask and m[i]
616	if len(m) == 1:
617	m = m[0]
618	invm = (not m)
619	else:
620	invm = logical_not(m)
621	label0='Masked Region'
622	label1='Spectrum'
623	if ( nomask ):
624	label0=label1
625	else:
626	y = ma.masked_array( self.y, mask = m )
627	self._p.palette(1,colours)
628	self._p.set_line( label = label1 )
629	self._p.plot( self.x, y )
630	self._p.palette(0,colours)
631	self._p.set_line(label=label0)
632	y = ma.masked_array(self.y,mask=invm)
633	self._p.plot(self.x, y)
634	if residual:
635	self._p.palette(7)
636	self._p.set_line(label='Residual')
637	y = ma.masked_array(self.get_residual(),
638	mask=invm)
639	self._p.plot(self.x, y)
640	self._p.palette(2)
641	if components is not None:
642	cs = components
643	if isinstance(components,int): cs = [components]
644	if plotparms:
645	self._p.text(0.15,0.15,
646	str(self.get_parameters()['formatted']),size=8)
647	n = len(self.components)
648	self._p.palette(3)
649	for c in cs:
650	if 0 <= c < n:
651	lab = self.fitfuncs[c]+str(c)
652	self._p.set_line(label=lab)
653	y = ma.masked_array(self.fitter.evaluate(c), mask=invm)
654
655	self._p.plot(self.x, y)
656	elif c == -1:
657	self._p.palette(2)
658	self._p.set_line(label="Total Fit")
659	y = ma.masked_array(self.fitter.getfit(),
660	mask=invm)
661	self._p.plot(self.x, y)
662	else:
663	self._p.palette(2)
664	self._p.set_line(label='Fit')
665	y = ma.masked_array(self.fitter.getfit(),mask=invm)
666	self._p.plot(self.x, y)
667	xlim=[min(self.x),max(self.x)]
668	self._p.axes.set_xlim(xlim)
669	self._p.set_axes('xlabel',xlab)
670	self._p.set_axes('ylabel',ylab)
671	self._p.set_axes('title',tlab)
672	self._p.release()
673	if (not rcParams['plotter.gui']):
674	self._p.save(filename)
675
676	@asaplog_post_dec
677	def auto_fit(self, insitu=None, plot=False):
678	"""
679	Return a scan where the function is applied to all rows for
680	all Beams/IFs/Pols.
681
682	"""
683	from asap import scantable
684	if not isinstance(self.data, scantable) :
685	msg = "Data is not a scantable"
686	raise TypeError(msg)
687	if insitu is None: insitu = rcParams['insitu']
688	if not insitu:
689	scan = self.data.copy()
690	else:
691	scan = self.data
692	rows = xrange(scan.nrow())
693	# Save parameters of baseline fits as a class attribute.
694	# NOTICE: This does not reflect changes in scantable!
695	if len(rows) > 0: self.blpars=[]
696	asaplog.push("Fitting:")
697	for r in rows:
698	out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
699	scan.getscan(r),
700	scan.getbeam(r),
701	scan.getif(r),
702	scan.getpol(r),
703	scan.getcycle(r)
704	)
705	asaplog.push(out, False)
706	self.x = scan._getabcissa(r)
707	self.y = scan._getspectrum(r)
708	#self.mask = mask_and(self.mask, scan._getmask(r))
709	if len(self.x) == len(self.mask):
710	self.mask = mask_and(self.mask, self.data._getmask(row))
711	else:
712	asaplog.push('lengths of data and mask are not the same. '
713	'preset mask will be ignored')
714	asaplog.post('WARN','asapfit.fit')
715	self.mask=self.data._getmask(row)
716	self.data = None
717	self.fit()
718	x = self.get_parameters()
719	fpar = self.get_parameters()
720	if plot:
721	self.plot(residual=True)
722	x = raw_input("Accept fit ([y]/n): ")
723	if x.upper() == 'N':
724	self.blpars.append(None)
725	continue
726	scan._setspectrum(self.fitter.getresidual(), r)
727	self.blpars.append(fpar)
728	if plot:
729	self._p.quit()
730	del self._p
731	self._p = None
732	return scan

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