source: branches/casa-release-4_3/python/asapfitter.py@ 3074

Last change on this file since 3074 was 2961, checked in by Kana Sugimoto, 10 years ago

New Development: No

JIRA Issue: Yes (CAS-6587)

Ready for Test: Yes

Interface Changes: No

What Interface Changed: Please list interface changes

Test Programs:

Put in Release Notes: No

Module(s): asapfitter, asaplinefind

Description: handling of FLAGROW column in STLineFinder::findLines and asapfitter.fit.


  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 27.2 KB
Line 
1import _asap
2from asap.parameters import rcParams
3from asap.logging import asaplog, asaplog_post_dec
4from asap.utils import _n_bools, mask_and
5from numpy import ndarray
6
7class 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 if self.data._getflagrow(row):
160 raise RuntimeError,"Can not fit flagged row."
161 self.x = self.data._getabcissa(row)
162 self.y = self.data._getspectrum(row)
163 #self.mask = mask_and(self.mask, self.data._getmask(row))
164 if len(self.x) == len(self.mask):
165 self.mask = mask_and(self.mask, self.data._getmask(row))
166 else:
167 asaplog.push('lengths of data and mask are not the same. '
168 'preset mask will be ignored')
169 asaplog.post('WARN','asapfit.fit')
170 self.mask=self.data._getmask(row)
171 asaplog.push("Fitting:")
172 i = row
173 out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
174 self.data.getscan(i),
175 self.data.getbeam(i),
176 self.data.getif(i),
177 self.data.getpol(i),
178 self.data.getcycle(i))
179
180 asaplog.push(out, False)
181
182 self.fitter.setdata(self.x, self.y, self.mask)
183 if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
184 ps = self.fitter.getparameters()
185 if len(ps) == 0 or estimate:
186 self.fitter.estimate()
187 fxdpar = list(self.fitter.getfixedparameters())
188 if len(fxdpar) and fxdpar.count(0) == 0:
189 raise RuntimeError,"No point fitting, if all parameters are fixed."
190 if self._constraints:
191 for c in self._constraints:
192 self.fitter.addconstraint(c[0]+[c[-1]])
193 if self.uselinear:
194 converged = self.fitter.lfit()
195 else:
196 converged = self.fitter.fit()
197 if not converged:
198 raise RuntimeError,"Fit didn't converge."
199 self._fittedrow = row
200 self.fitted = True
201 return
202
203 def store_fit(self, filename=None):
204 """
205 Save the fit parameters.
206 Parameters:
207 filename: if specified save as an ASCII file, if None (default)
208 store it in the scnatable
209 """
210 if self.fitted and self.data is not None:
211 pars = list(self.fitter.getparameters())
212 fixed = list(self.fitter.getfixedparameters())
213 from asap.asapfit import asapfit
214 fit = asapfit()
215 fit.setparameters(pars)
216 fit.setfixedparameters(fixed)
217 fit.setfunctions(self.fitfuncs)
218 fit.setcomponents(self.components)
219 fit.setframeinfo(self.data._getcoordinfo())
220 if filename is not None:
221 import os
222 filename = os.path.expandvars(os.path.expanduser(filename))
223 if os.path.exists(filename):
224 raise IOError("File '%s' exists." % filename)
225 fit.save(filename)
226 else:
227 self.data._addfit(fit,self._fittedrow)
228
229 @asaplog_post_dec
230 def set_parameters(self,*args,**kwargs):
231 """
232 Set the parameters to be fitted.
233 Parameters:
234 params: a vector of parameters
235 fixed: a vector of which parameters are to be held fixed
236 (default is none)
237 component: in case of multiple gaussians/lorentzians/sinusoidals,
238 the index of the target component
239 """
240 component = None
241 fixed = None
242 params = None
243
244 if len(args) and isinstance(args[0],dict):
245 kwargs = args[0]
246 if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
247 if kwargs.has_key("params"): params = kwargs["params"]
248 if len(args) == 2 and isinstance(args[1], int):
249 component = args[1]
250 if self.fitfunc is None:
251 msg = "Please specify a fitting function first."
252 raise RuntimeError(msg)
253 if (self.fitfunc == "gauss" or self.fitfunc == "lorentz"
254 or self.fitfunc == "sinusoid") and component is not None:
255 if not self.fitted and sum(self.fitter.getparameters()) == 0:
256 pars = _n_bools(len(self.components)*3, False)
257 fxd = _n_bools(len(pars), False)
258 else:
259 pars = list(self.fitter.getparameters())
260 fxd = list(self.fitter.getfixedparameters())
261 i = 3*component
262 pars[i:i+3] = params
263 fxd[i:i+3] = fixed
264 params = pars
265 fixed = fxd
266 self.fitter.setparameters(params)
267 if fixed is not None:
268 self.fitter.setfixedparameters(fixed)
269 return
270
271 @asaplog_post_dec
272 def set_gauss_parameters(self, peak, centre, fwhm,
273 peakfixed=0, centrefixed=0,
274 fwhmfixed=0,
275 component=0):
276 """
277 Set the Parameters of a 'Gaussian' component, set with set_function.
278 Parameters:
279 peak, centre, fwhm: The gaussian parameters
280 peakfixed,
281 centrefixed,
282 fwhmfixed: Optional parameters to indicate if
283 the paramters should be held fixed during
284 the fitting process. The default is to keep
285 all parameters flexible.
286 component: The number of the component (Default is the
287 component 0)
288 """
289 if self.fitfunc != "gauss":
290 msg = "Function only operates on Gaussian components."
291 raise ValueError(msg)
292 if 0 <= component < len(self.components):
293 d = {'params':[peak, centre, fwhm],
294 'fixed':[peakfixed, centrefixed, fwhmfixed]}
295 self.set_parameters(d, component)
296 else:
297 msg = "Please select a valid component."
298 raise ValueError(msg)
299
300 @asaplog_post_dec
301 def set_lorentz_parameters(self, peak, centre, fwhm,
302 peakfixed=0, centrefixed=0,
303 fwhmfixed=0,
304 component=0):
305 """
306 Set the Parameters of a 'Lorentzian' component, set with set_function.
307 Parameters:
308 peak, centre, fwhm: The lorentzian parameters
309 peakfixed,
310 centrefixed,
311 fwhmfixed: Optional parameters to indicate if
312 the paramters should be held fixed during
313 the fitting process. The default is to keep
314 all parameters flexible.
315 component: The number of the component (Default is the
316 component 0)
317 """
318 if self.fitfunc != "lorentz":
319 msg = "Function only operates on Lorentzian components."
320 raise ValueError(msg)
321 if 0 <= component < len(self.components):
322 d = {'params':[peak, centre, fwhm],
323 'fixed':[peakfixed, centrefixed, fwhmfixed]}
324 self.set_parameters(d, component)
325 else:
326 msg = "Please select a valid component."
327 raise ValueError(msg)
328
329 @asaplog_post_dec
330 def set_sinusoid_parameters(self, ampl, period, x0,
331 amplfixed=0, periodfixed=0,
332 x0fixed=0,
333 component=0):
334 """
335 Set the Parameters of a 'Sinusoidal' component, set with set_function.
336 Parameters:
337 ampl, period, x0: The sinusoidal parameters
338 amplfixed,
339 periodfixed,
340 x0fixed: Optional parameters to indicate if
341 the paramters should be held fixed during
342 the fitting process. The default is to keep
343 all parameters flexible.
344 component: The number of the component (Default is the
345 component 0)
346 """
347 if self.fitfunc != "sinusoid":
348 msg = "Function only operates on Sinusoidal components."
349 raise ValueError(msg)
350 if 0 <= component < len(self.components):
351 d = {'params':[ampl, period, x0],
352 'fixed': [amplfixed, periodfixed, x0fixed]}
353 self.set_parameters(d, component)
354 else:
355 msg = "Please select a valid component."
356 raise ValueError(msg)
357
358
359 def add_constraint(self, xpar, y):
360 """Add parameter constraints to the fit. This is done by setting up
361 linear equations for the related parameters.
362
363 For example a two component gaussian fit where the amplitudes are
364 constraint by amp1 = 2*amp2 and paramaters for the two components
365 in the order [amp1,peakv1,sigma1,amp2,peakv2,sigma2]
366 needs a constraint
367
368 add_constraint([1, 0, 0, -2, 0, 0], 0)
369
370 as the linear equation is
371
372 1*amp1 + 0*peakv1 + 0*sigma1 -2*amp2 + 0*peakv2 + 0*sigma2 = 0
373
374 and similarly for a velocity difference of v2-v1=17
375
376 add_constraint([0.,-1.,0.,0.,1.,0.], 17.)
377
378 """
379 self._constraints.append((xpar, y))
380
381
382 def get_area(self, component=None):
383 """
384 Return the area under the fitted gaussian/lorentzian component.
385 Parameters:
386 component: the gaussian/lorentzian component selection,
387 default (None) is the sum of all components
388 Note:
389 This will only work for gaussian/lorentzian fits.
390 """
391 if not self.fitted: return
392 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
393 pars = list(self.fitter.getparameters())
394 from math import log,pi,sqrt
395 if self.fitfunc == "gauss":
396 fac = sqrt(pi/log(16.0))
397 elif self.fitfunc == "lorentz":
398 fac = pi/2.0
399 areas = []
400 for i in range(len(self.components)):
401 j = i*3
402 cpars = pars[j:j+3]
403 areas.append(fac * cpars[0] * cpars[2])
404 else:
405 return None
406 if component is not None:
407 return areas[component]
408 else:
409 return sum(areas)
410
411 @asaplog_post_dec
412 def get_errors(self, component=None):
413 """
414 Return the errors in the parameters.
415 Parameters:
416 component: get the errors for the specified component
417 only, default is all components
418 """
419 if not self.fitted:
420 msg = "Not yet fitted."
421 raise RuntimeError(msg)
422 errs = list(self.fitter.geterrors())
423 cerrs = errs
424 if component is not None:
425 if self.fitfunc == "gauss" or self.fitfunc == "lorentz" \
426 or self.fitfunc == "sinusoid":
427 i = 3*component
428 if i < len(errs):
429 cerrs = errs[i:i+3]
430 return cerrs
431
432
433 @asaplog_post_dec
434 def get_parameters(self, component=None, errors=False):
435 """
436 Return the fit paramters.
437 Parameters:
438 component: get the parameters for the specified component
439 only, default is all components
440 """
441 if not self.fitted:
442 msg = "Not yet fitted."
443 raise RuntimeError(msg)
444 pars = list(self.fitter.getparameters())
445 fixed = list(self.fitter.getfixedparameters())
446 errs = list(self.fitter.geterrors())
447 area = []
448 if component is not None:
449 if self.fitfunc == "poly" or self.fitfunc == "lpoly":
450 cpars = pars
451 cfixed = fixed
452 cerrs = errs
453 else:
454 i = 3*component
455 cpars = pars[i:i+3]
456 cfixed = fixed[i:i+3]
457 cerrs = errs[i:i+3]
458 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
459 a = self.get_area(component)
460 area = [a for i in range(3)]
461 else:
462 cpars = pars
463 cfixed = fixed
464 cerrs = errs
465 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
466 for c in range(len(self.components)):
467 a = self.get_area(c)
468 area += [a for i in range(3)]
469 fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
470 asaplog.push(fpars)
471 return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
472 'errors':cerrs}
473
474 def _format_pars(self, pars, fixed, errors, area):
475 out = ''
476 if self.fitfunc == "poly" or self.fitfunc == "lpoly":
477 c = 0
478 for i in range(len(pars)):
479 fix = ""
480 if len(fixed) and fixed[i]: fix = "(fixed)"
481 out += " p%d%s= %3.6f" % (c, fix, pars[i])
482 if errors : out += " (%1.6f)" % errors[i]
483 out += ","
484 c+=1
485 out = out[:-1] # remove trailing ','
486 else:
487 i = 0
488 c = 0
489 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
490 pnam = ["peak", "centre", "FWHM"]
491 elif self.fitfunc == "sinusoid":
492 pnam = ["amplitude", "period", "x0"]
493 aunit = ""
494 ounit = ""
495 if self.data:
496 aunit = self.data.get_unit()
497 ounit = self.data.get_fluxunit()
498 while i < len(pars):
499 fix0 = fix1 = fix2 = ""
500 if i < len(fixed)-2:
501 if fixed[i]: fix0 = "(fixed)"
502 if fixed[i+1]: fix1 = "(fixed)"
503 if fixed[i+2]: fix2 = "(fixed)"
504 out += " %2d: " % c
505 out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit)
506 out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit)
507 out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit)
508 if len(area): out += " area = %3.3f %s %s\n" % (area[i],
509 ounit,
510 aunit)
511 c+=1
512 i+=3
513 return out
514
515
516 @asaplog_post_dec
517 def get_estimate(self):
518 """
519 Return the parameter estimates (for non-linear functions).
520 """
521 pars = self.fitter.getestimate()
522 fixed = self.fitter.getfixedparameters()
523 asaplog.push(self._format_pars(pars,fixed,None,None))
524 return pars
525
526 @asaplog_post_dec
527 def get_residual(self):
528 """
529 Return the residual of the fit.
530 """
531 if not self.fitted:
532 msg = "Not yet fitted."
533 raise RuntimeError(msg)
534 return self.fitter.getresidual()
535
536 @asaplog_post_dec
537 def get_chi2(self):
538 """
539 Return chi^2.
540 """
541 if not self.fitted:
542 msg = "Not yet fitted."
543 raise RuntimeError(msg)
544 ch2 = self.fitter.getchi2()
545 asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
546 return ch2
547
548 @asaplog_post_dec
549 def get_fit(self):
550 """
551 Return the fitted ordinate values.
552 """
553 if not self.fitted:
554 msg = "Not yet fitted."
555 raise RuntimeError(msg)
556 return self.fitter.getfit()
557
558 @asaplog_post_dec
559 def commit(self):
560 """
561 Return a new scan where the fits have been commited (subtracted)
562 """
563 if not self.fitted:
564 msg = "Not yet fitted."
565 raise RuntimeError(msg)
566 from asap import scantable
567 if not isinstance(self.data, scantable):
568 msg = "Not a scantable"
569 raise TypeError(msg)
570 scan = self.data.copy()
571 scan._setspectrum(self.fitter.getresidual())
572 return scan
573
574 @asaplog_post_dec
575 def plot(self, residual=False, components=None, plotparms=False,
576 filename=None):
577 """
578 Plot the last fit.
579 Parameters:
580 residual: an optional parameter indicating if the residual
581 should be plotted (default 'False')
582 components: a list of components to plot, e.g [0,1],
583 -1 plots the total fit. Default is to only
584 plot the total fit.
585 plotparms: Inidicates if the parameter values should be present
586 on the plot
587 """
588 from matplotlib import rc as rcp
589 if not self.fitted:
590 return
591 #if not self._p or self._p.is_dead:
592 if not (self._p and self._p._alive()):
593 from asap.asapplotter import new_asaplot
594 del self._p
595 self._p = new_asaplot(rcParams['plotter.gui'])
596 self._p.hold()
597 self._p.clear()
598 rcp('lines', linewidth=1)
599 self._p.set_panels()
600 self._p.palette(0)
601 tlab = 'Spectrum'
602 xlab = 'Abcissa'
603 ylab = 'Ordinate'
604 from numpy import ma,logical_not,logical_and,array
605 m = self.mask
606 if self.data:
607 tlab = self.data._getsourcename(self._fittedrow)
608 xlab = self.data._getabcissalabel(self._fittedrow)
609 if self.data._getflagrow(self._fittedrow):
610 m = [False]
611 else:
612 m = logical_and(self.mask,
613 array(self.data._getmask(self._fittedrow),
614 copy=False))
615
616 ylab = self.data._get_ordinate_label()
617
618 colours = ["#777777","#dddddd","red","orange","purple","green",
619 "magenta", "cyan"]
620 nomask=True
621 for i in range(len(m)):
622 nomask = nomask and m[i]
623 if len(m) == 1:
624 m = m[0]
625 invm = (not m)
626 else:
627 invm = logical_not(m)
628 label0='Masked Region'
629 label1='Spectrum'
630 if ( nomask ):
631 label0=label1
632 else:
633 y = ma.masked_array( self.y, mask = m )
634 self._p.palette(1,colours)
635 self._p.set_line( label = label1 )
636 self._p.plot( self.x, y )
637 self._p.palette(0,colours)
638 self._p.set_line(label=label0)
639 y = ma.masked_array(self.y,mask=invm)
640 self._p.plot(self.x, y)
641 if residual:
642 self._p.palette(7)
643 self._p.set_line(label='Residual')
644 y = ma.masked_array(self.get_residual(),
645 mask=invm)
646 self._p.plot(self.x, y)
647 self._p.palette(2)
648 if components is not None:
649 cs = components
650 if isinstance(components,int): cs = [components]
651 if plotparms:
652 self._p.text(0.15,0.15,
653 str(self.get_parameters()['formatted']),size=8)
654 n = len(self.components)
655 self._p.palette(3)
656 for c in cs:
657 if 0 <= c < n:
658 lab = self.fitfuncs[c]+str(c)
659 self._p.set_line(label=lab)
660 y = ma.masked_array(self.fitter.evaluate(c), mask=invm)
661
662 self._p.plot(self.x, y)
663 elif c == -1:
664 self._p.palette(2)
665 self._p.set_line(label="Total Fit")
666 y = ma.masked_array(self.fitter.getfit(),
667 mask=invm)
668 self._p.plot(self.x, y)
669 else:
670 self._p.palette(2)
671 self._p.set_line(label='Fit')
672 y = ma.masked_array(self.fitter.getfit(),mask=invm)
673 self._p.plot(self.x, y)
674 xlim=[min(self.x),max(self.x)]
675 self._p.axes.set_xlim(xlim)
676 self._p.set_axes('xlabel',xlab)
677 self._p.set_axes('ylabel',ylab)
678 self._p.set_axes('title',tlab)
679 self._p.release()
680 if (not rcParams['plotter.gui']):
681 self._p.save(filename)
682
683 @asaplog_post_dec
684 def auto_fit(self, insitu=None, plot=False):
685 """
686 Return a scan where the function is applied to all rows for
687 all Beams/IFs/Pols.
688
689 """
690 from asap import scantable
691 if not isinstance(self.data, scantable) :
692 msg = "Data is not a scantable"
693 raise TypeError(msg)
694 if insitu is None: insitu = rcParams['insitu']
695 if not insitu:
696 scan = self.data.copy()
697 else:
698 scan = self.data
699 rows = xrange(scan.nrow())
700 # Save parameters of baseline fits as a class attribute.
701 # NOTICE: This does not reflect changes in scantable!
702 if len(rows) > 0: self.blpars=[]
703 asaplog.push("Fitting:")
704 for r in rows:
705 out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
706 scan.getscan(r),
707 scan.getbeam(r),
708 scan.getif(r),
709 scan.getpol(r),
710 scan.getcycle(r)
711 )
712 asaplog.push(out, False)
713 self.x = scan._getabcissa(r)
714 self.y = scan._getspectrum(r)
715 #self.mask = mask_and(self.mask, scan._getmask(r))
716 if len(self.x) == len(self.mask):
717 self.mask = mask_and(self.mask, self.data._getmask(row))
718 else:
719 asaplog.push('lengths of data and mask are not the same. '
720 'preset mask will be ignored')
721 asaplog.post('WARN','asapfit.fit')
722 self.mask=self.data._getmask(row)
723 self.data = None
724 self.fit()
725 x = self.get_parameters()
726 fpar = self.get_parameters()
727 if plot:
728 self.plot(residual=True)
729 x = raw_input("Accept fit ([y]/n): ")
730 if x.upper() == 'N':
731 self.blpars.append(None)
732 continue
733 scan._setspectrum(self.fitter.getresidual(), r)
734 self.blpars.append(fpar)
735 if plot:
736 self._p.quit()
737 del self._p
738 self._p = None
739 return scan
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