source: trunk/python/asapfitter.py@ 1838

Last change on this file since 1838 was 1826, checked in by Malte Marquarding, 14 years ago

Tidy up of imports (now imported from asap.). Also fixed some whitespace/tab issues

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 26.1 KB
Line 
1import _asap
2from asap.parameters import rcParams
3from asap.logging import asaplog, print_log, print_log_dec
4from asap.utils import _n_bools, mask_and
5
6
7class fitter:
8 """
9 The fitting class for ASAP.
10 """
11
12 def __init__(self):
13 """
14 Create a fitter object. No state is set.
15 """
16 self.fitter = _asap.fitter()
17 self.x = None
18 self.y = None
19 self.mask = None
20 self.fitfunc = None
21 self.fitfuncs = None
22 self.fitted = False
23 self.data = None
24 self.components = 0
25 self._fittedrow = 0
26 self._p = None
27 self._selection = None
28 self.uselinear = False
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 indicationg 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 def set_scan(self, thescan=None, mask=None):
52 """
53 Set the 'data' (a scantable) of the fitter.
54 Parameters:
55 thescan: a scantable
56 mask: a msk retrieved from the scantable
57 """
58 if not thescan:
59 msg = "Please give a correct scan"
60 if rcParams['verbose']:
61 #print msg
62 asaplog.push(msg)
63 print_log('ERROR')
64 return
65 else:
66 raise TypeError(msg)
67 self.fitted = False
68 self.data = thescan
69 self.mask = None
70 if mask is None:
71 self.mask = _n_bools(self.data.nchan(), True)
72 else:
73 self.mask = mask
74 return
75
76 def set_function(self, **kwargs):
77 """
78 Set the function to be fit.
79 Parameters:
80 poly: use a polynomial of the order given with nonlinear least squares fit
81 lpoly: use polynomial of the order given with linear least squares fit
82 gauss: fit the number of gaussian specified
83 lorentz: fit the number of lorentzian specified
84 Example:
85 fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method
86 fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method
87 fitter.set_function(gauss=2) # will fit two gaussians
88 fitter.set_function(lorentz=2) # will fit two lorentzians
89 """
90 #default poly order 0
91 n=0
92 if kwargs.has_key('poly'):
93 self.fitfunc = 'poly'
94 n = kwargs.get('poly')
95 self.components = [n]
96 self.uselinear = False
97 elif kwargs.has_key('lpoly'):
98 self.fitfunc = 'poly'
99 n = kwargs.get('lpoly')
100 self.components = [n]
101 self.uselinear = True
102 elif kwargs.has_key('gauss'):
103 n = kwargs.get('gauss')
104 self.fitfunc = 'gauss'
105 self.fitfuncs = [ 'gauss' for i in range(n) ]
106 self.components = [ 3 for i in range(n) ]
107 self.uselinear = False
108 elif kwargs.has_key('lorentz'):
109 n = kwargs.get('lorentz')
110 self.fitfunc = 'lorentz'
111 self.fitfuncs = [ 'lorentz' for i in range(n) ]
112 self.components = [ 3 for i in range(n) ]
113 self.uselinear = False
114 else:
115 msg = "Invalid function type."
116 if rcParams['verbose']:
117 #print msg
118 asaplog.push(msg)
119 print_log('ERROR')
120 return
121 else:
122 raise TypeError(msg)
123
124 self.fitter.setexpression(self.fitfunc,n)
125 self.fitted = False
126 return
127
128 @print_log_dec
129 def fit(self, row=0, estimate=False):
130 """
131 Execute the actual fitting process. All the state has to be set.
132 Parameters:
133 row: specify the row in the scantable
134 estimate: auto-compute an initial parameter set (default False)
135 This can be used to compute estimates even if fit was
136 called before.
137 Example:
138 s = scantable('myscan.asap')
139 s.set_cursor(thepol=1) # select second pol
140 f = fitter()
141 f.set_scan(s)
142 f.set_function(poly=0)
143 f.fit(row=0) # fit first row
144 """
145 if ((self.x is None or self.y is None) and self.data is None) \
146 or self.fitfunc is None:
147 msg = "Fitter not yet initialised. Please set data & fit function"
148 if rcParams['verbose']:
149 #print msg
150 asaplog.push(msg)
151 print_log('ERROR')
152 return
153 else:
154 raise RuntimeError(msg)
155
156 else:
157 if self.data is not None:
158 self.x = self.data._getabcissa(row)
159 self.y = self.data._getspectrum(row)
160 self.mask = mask_and(self.mask, self.data._getmask(row))
161 asaplog.push("Fitting:")
162 i = row
163 out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i),
164 self.data.getbeam(i),
165 self.data.getif(i),
166 self.data.getpol(i),
167 self.data.getcycle(i))
168 asaplog.push(out,False)
169 self.fitter.setdata(self.x, self.y, self.mask)
170 if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
171 ps = self.fitter.getparameters()
172 if len(ps) == 0 or estimate:
173 self.fitter.estimate()
174 try:
175 fxdpar = list(self.fitter.getfixedparameters())
176 if len(fxdpar) and fxdpar.count(0) == 0:
177 raise RuntimeError,"No point fitting, if all parameters are fixed."
178 if self.uselinear:
179 converged = self.fitter.lfit()
180 else:
181 converged = self.fitter.fit()
182 if not converged:
183 raise RuntimeError,"Fit didn't converge."
184 except RuntimeError, msg:
185 if rcParams['verbose']:
186 #print msg
187 print_log()
188 asaplog.push(str(msg))
189 print_log('ERROR')
190 else:
191 raise
192 self._fittedrow = row
193 self.fitted = True
194 print_log()
195 return
196
197 def store_fit(self, filename=None):
198 """
199 Save the fit parameters.
200 Parameters:
201 filename: if specified save as an ASCII file, if None (default)
202 store it in the scnatable
203 """
204 if self.fitted and self.data is not None:
205 pars = list(self.fitter.getparameters())
206 fixed = list(self.fitter.getfixedparameters())
207 from asap.asapfit import asapfit
208 fit = asapfit()
209 fit.setparameters(pars)
210 fit.setfixedparameters(fixed)
211 fit.setfunctions(self.fitfuncs)
212 fit.setcomponents(self.components)
213 fit.setframeinfo(self.data._getcoordinfo())
214 if filename is not None:
215 import os
216 filename = os.path.expandvars(os.path.expanduser(filename))
217 if os.path.exists(filename):
218 raise IOError("File '%s' exists." % filename)
219 fit.save(filename)
220 else:
221 self.data._addfit(fit,self._fittedrow)
222
223 @print_log_dec
224 def set_parameters(self,*args,**kwargs):
225 """
226 Set the parameters to be fitted.
227 Parameters:
228 params: a vector of parameters
229 fixed: a vector of which parameters are to be held fixed
230 (default is none)
231 component: in case of multiple gaussians, the index of the
232 component
233 """
234 component = None
235 fixed = None
236 params = None
237
238 if len(args) and isinstance(args[0],dict):
239 kwargs = args[0]
240 if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
241 if kwargs.has_key("params"): params = kwargs["params"]
242 if len(args) == 2 and isinstance(args[1], int):
243 component = args[1]
244 if self.fitfunc is None:
245 msg = "Please specify a fitting function first."
246 if rcParams['verbose']:
247 #print msg
248 asaplog.push(msg)
249 print_log('ERROR')
250 return
251 else:
252 raise RuntimeError(msg)
253 if (self.fitfunc == "gauss" or self.fitfunc == 'lorentz') and component is not None:
254 if not self.fitted and sum(self.fitter.getparameters()) == 0:
255 pars = _n_bools(len(self.components)*3, False)
256 fxd = _n_bools(len(pars), False)
257 else:
258 pars = list(self.fitter.getparameters())
259 fxd = list(self.fitter.getfixedparameters())
260 i = 3*component
261 pars[i:i+3] = params
262 fxd[i:i+3] = fixed
263 params = pars
264 fixed = fxd
265 self.fitter.setparameters(params)
266 if fixed is not None:
267 self.fitter.setfixedparameters(fixed)
268 print_log()
269 return
270
271 def set_gauss_parameters(self, peak, centre, fwhm,
272 peakfixed=0, centrefixed=0,
273 fwhmfixed=0,
274 component=0):
275 """
276 Set the Parameters of a 'Gaussian' component, set with set_function.
277 Parameters:
278 peak, centre, fwhm: The gaussian parameters
279 peakfixed,
280 centrefixed,
281 fwhmfixed: Optional parameters to indicate if
282 the paramters should be held fixed during
283 the fitting process. The default is to keep
284 all parameters flexible.
285 component: The number of the component (Default is the
286 component 0)
287 """
288 if self.fitfunc != "gauss":
289 msg = "Function only operates on Gaussian components."
290 if rcParams['verbose']:
291 #print msg
292 asaplog.push(msg)
293 print_log('ERROR')
294 return
295 else:
296 raise ValueError(msg)
297 if 0 <= component < len(self.components):
298 d = {'params':[peak, centre, fwhm],
299 'fixed':[peakfixed, centrefixed, fwhmfixed]}
300 self.set_parameters(d, component)
301 else:
302 msg = "Please select a valid component."
303 if rcParams['verbose']:
304 #print msg
305 asaplog.push(msg)
306 print_log('ERROR')
307 return
308 else:
309 raise ValueError(msg)
310
311 def set_lorentz_parameters(self, peak, centre, fwhm,
312 peakfixed=0, centrefixed=0,
313 fwhmfixed=0,
314 component=0):
315 """
316 Set the Parameters of a 'Lorentzian' component, set with set_function.
317 Parameters:
318 peak, centre, fwhm: The gaussian parameters
319 peakfixed,
320 centrefixed,
321 fwhmfixed: Optional parameters to indicate if
322 the paramters should be held fixed during
323 the fitting process. The default is to keep
324 all parameters flexible.
325 component: The number of the component (Default is the
326 component 0)
327 """
328 if self.fitfunc != "lorentz":
329 msg = "Function only operates on Lorentzian components."
330 if rcParams['verbose']:
331 #print msg
332 asaplog.push(msg)
333 print_log('ERROR')
334 return
335 else:
336 raise ValueError(msg)
337 if 0 <= component < len(self.components):
338 d = {'params':[peak, centre, fwhm],
339 'fixed':[peakfixed, centrefixed, fwhmfixed]}
340 self.set_parameters(d, component)
341 else:
342 msg = "Please select a valid component."
343 if rcParams['verbose']:
344 #print msg
345 asaplog.push(msg)
346 print_log('ERROR')
347 return
348 else:
349 raise ValueError(msg)
350
351 def get_area(self, component=None):
352 """
353 Return the area under the fitted gaussian/lorentzian component.
354 Parameters:
355 component: the gaussian/lorentzian component selection,
356 default (None) is the sum of all components
357 Note:
358 This will only work for gaussian/lorentzian fits.
359 """
360 if not self.fitted: return
361 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
362 pars = list(self.fitter.getparameters())
363 from math import log,pi,sqrt
364 if self.fitfunc == "gauss":
365 fac = sqrt(pi/log(16.0))
366 elif self.fitfunc == "lorentz":
367 fac = pi/2.0
368 areas = []
369 for i in range(len(self.components)):
370 j = i*3
371 cpars = pars[j:j+3]
372 areas.append(fac * cpars[0] * cpars[2])
373 else:
374 return None
375 if component is not None:
376 return areas[component]
377 else:
378 return sum(areas)
379
380 def get_errors(self, component=None):
381 """
382 Return the errors in the parameters.
383 Parameters:
384 component: get the errors for the specified component
385 only, default is all components
386 """
387 if not self.fitted:
388 msg = "Not yet fitted."
389 if rcParams['verbose']:
390 #print msg
391 asaplog.push(msg)
392 print_log('ERROR')
393 return
394 else:
395 raise RuntimeError(msg)
396 errs = list(self.fitter.geterrors())
397 cerrs = errs
398 if component is not None:
399 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
400 i = 3*component
401 if i < len(errs):
402 cerrs = errs[i:i+3]
403 return cerrs
404
405 def get_parameters(self, component=None, errors=False):
406 """
407 Return the fit paramters.
408 Parameters:
409 component: get the parameters for the specified component
410 only, default is all components
411 """
412 if not self.fitted:
413 msg = "Not yet fitted."
414 if rcParams['verbose']:
415 #print msg
416 asaplog.push(msg)
417 print_log('ERROR')
418 return
419 else:
420 raise RuntimeError(msg)
421 pars = list(self.fitter.getparameters())
422 fixed = list(self.fitter.getfixedparameters())
423 errs = list(self.fitter.geterrors())
424 area = []
425 if component is not None:
426 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
427 i = 3*component
428 cpars = pars[i:i+3]
429 cfixed = fixed[i:i+3]
430 cerrs = errs[i:i+3]
431 a = self.get_area(component)
432 area = [a for i in range(3)]
433 else:
434 cpars = pars
435 cfixed = fixed
436 cerrs = errs
437 else:
438 cpars = pars
439 cfixed = fixed
440 cerrs = errs
441 if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
442 for c in range(len(self.components)):
443 a = self.get_area(c)
444 area += [a for i in range(3)]
445 fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
446 if rcParams['verbose']:
447 #print fpars
448 asaplog.push(fpars)
449 print_log()
450 return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
451 'errors':cerrs}
452
453 def _format_pars(self, pars, fixed, errors, area):
454 out = ''
455 if self.fitfunc == 'poly':
456 c = 0
457 for i in range(len(pars)):
458 fix = ""
459 if len(fixed) and fixed[i]: fix = "(fixed)"
460 if errors :
461 out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])
462 else:
463 out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
464 c+=1
465 out = out[:-1] # remove trailing ','
466 elif self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
467 i = 0
468 c = 0
469 aunit = ''
470 ounit = ''
471 if self.data:
472 aunit = self.data.get_unit()
473 ounit = self.data.get_fluxunit()
474 while i < len(pars):
475 if len(area):
476 out += ' %2d: peak = %3.3f %s , centre = %3.3f %s, FWHM = %3.3f %s\n area = %3.3f %s %s\n' % (c,pars[i],ounit,pars[i+1],aunit,pars[i+2],aunit, area[i],ounit,aunit)
477 else:
478 out += ' %2d: peak = %3.3f %s , centre = %3.3f %s, FWHM = %3.3f %s\n' % (c,pars[i],ounit,pars[i+1],aunit,pars[i+2],aunit,ounit,aunit)
479 c+=1
480 i+=3
481 return out
482
483 def get_estimate(self):
484 """
485 Return the parameter estimates (for non-linear functions).
486 """
487 pars = self.fitter.getestimate()
488 fixed = self.fitter.getfixedparameters()
489 if rcParams['verbose']:
490 #print self._format_pars(pars,fixed,None)
491 asaplog.push(self._format_pars(pars,fixed,None))
492 print_log()
493 return pars
494
495 def get_residual(self):
496 """
497 Return the residual of the fit.
498 """
499 if not self.fitted:
500 msg = "Not yet fitted."
501 if rcParams['verbose']:
502 #print msg
503 asaplog.push(msg)
504 print_log('ERROR')
505 return
506 else:
507 raise RuntimeError(msg)
508 return self.fitter.getresidual()
509
510 def get_chi2(self):
511 """
512 Return chi^2.
513 """
514 if not self.fitted:
515 msg = "Not yet fitted."
516 if rcParams['verbose']:
517 #print msg
518 asaplog.push(msg)
519 print_log('ERROR')
520 return
521 else:
522 raise RuntimeError(msg)
523 ch2 = self.fitter.getchi2()
524 if rcParams['verbose']:
525 #print 'Chi^2 = %3.3f' % (ch2)
526 asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
527 print_log()
528 return ch2
529
530 def get_fit(self):
531 """
532 Return the fitted ordinate values.
533 """
534 if not self.fitted:
535 msg = "Not yet fitted."
536 if rcParams['verbose']:
537 #print msg
538 asaplog.push(msg)
539 print_log('ERROR')
540 return
541 else:
542 raise RuntimeError(msg)
543 return self.fitter.getfit()
544
545 @print_log_dec
546 def commit(self):
547 """
548 Return a new scan where the fits have been commited (subtracted)
549 """
550 if not self.fitted:
551 msg = "Not yet fitted."
552 if rcParams['verbose']:
553 #print msg
554 asaplog.push(msg)
555 print_log('ERROR')
556 return
557 else:
558 raise RuntimeError(msg)
559 from asap import scantable
560 if not isinstance(self.data, scantable):
561 msg = "Not a scantable"
562 if rcParams['verbose']:
563 #print msg
564 asaplog.push(msg)
565 print_log('ERROR')
566 return
567 else:
568 raise TypeError(msg)
569 scan = self.data.copy()
570 scan._setspectrum(self.fitter.getresidual())
571 print_log()
572 return scan
573
574 @print_log_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 if not self.fitted:
589 return
590 if not self._p or self._p.is_dead:
591 if rcParams['plotter.gui']:
592 from asap.asaplotgui import asaplotgui as asaplot
593 else:
594 from asap.asaplot import asaplot
595 self._p = asaplot()
596 self._p.hold()
597 self._p.clear()
598 self._p.set_panels()
599 self._p.palette(0)
600 tlab = 'Spectrum'
601 xlab = 'Abcissa'
602 ylab = 'Ordinate'
603 from numpy import ma,logical_not,logical_and,array
604 m = self.mask
605 if self.data:
606 tlab = self.data._getsourcename(self._fittedrow)
607 xlab = self.data._getabcissalabel(self._fittedrow)
608 m = logical_and(self.mask,
609 array(self.data._getmask(self._fittedrow),
610 copy=False))
611
612 ylab = self.data._get_ordinate_label()
613
614 colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
615 nomask=True
616 for i in range(len(m)):
617 nomask = nomask and m[i]
618 label0='Masked Region'
619 label1='Spectrum'
620 if ( nomask ):
621 label0=label1
622 else:
623 y = ma.masked_array( self.y, mask = m )
624 self._p.palette(1,colours)
625 self._p.set_line( label = label1 )
626 self._p.plot( self.x, y )
627 self._p.palette(0,colours)
628 self._p.set_line(label=label0)
629 y = ma.masked_array(self.y,mask=logical_not(m))
630 self._p.plot(self.x, y)
631 if residual:
632 self._p.palette(7)
633 self._p.set_line(label='Residual')
634 y = ma.masked_array(self.get_residual(),
635 mask=logical_not(m))
636 self._p.plot(self.x, y)
637 self._p.palette(2)
638 if components is not None:
639 cs = components
640 if isinstance(components,int): cs = [components]
641 if plotparms:
642 self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
643 n = len(self.components)
644 self._p.palette(3)
645 for c in cs:
646 if 0 <= c < n:
647 lab = self.fitfuncs[c]+str(c)
648 self._p.set_line(label=lab)
649 y = ma.masked_array(self.fitter.evaluate(c),
650 mask=logical_not(m))
651
652 self._p.plot(self.x, y)
653 elif c == -1:
654 self._p.palette(2)
655 self._p.set_line(label="Total Fit")
656 y = ma.masked_array(self.fitter.getfit(),
657 mask=logical_not(m))
658 self._p.plot(self.x, y)
659 else:
660 self._p.palette(2)
661 self._p.set_line(label='Fit')
662 y = ma.masked_array(self.fitter.getfit(),
663 mask=logical_not(m))
664 self._p.plot(self.x, y)
665 xlim=[min(self.x),max(self.x)]
666 self._p.axes.set_xlim(xlim)
667 self._p.set_axes('xlabel',xlab)
668 self._p.set_axes('ylabel',ylab)
669 self._p.set_axes('title',tlab)
670 self._p.release()
671 if (not rcParams['plotter.gui']):
672 self._p.save(filename)
673 print_log()
674
675 @print_log_dec
676 def auto_fit(self, insitu=None, plot=False):
677 """
678 Return a scan where the function is applied to all rows for
679 all Beams/IFs/Pols.
680
681 """
682 from asap import scantable
683 if not isinstance(self.data, scantable) :
684 msg = "Data is not a scantable"
685 if rcParams['verbose']:
686 #print msg
687 asaplog.push(msg)
688 print_log('ERROR')
689 return
690 else:
691 raise TypeError(msg)
692 if insitu is None: insitu = rcParams['insitu']
693 if not insitu:
694 scan = self.data.copy()
695 else:
696 scan = self.data
697 rows = xrange(scan.nrow())
698 # Save parameters of baseline fits as a class attribute.
699 # NOTICE: This does not reflect changes in scantable!
700 if len(rows) > 0: self.blpars=[]
701 asaplog.push("Fitting:")
702 for r in rows:
703 out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),
704 scan.getbeam(r),
705 scan.getif(r),
706 scan.getpol(r),
707 scan.getcycle(r))
708 asaplog.push(out, False)
709 self.x = scan._getabcissa(r)
710 self.y = scan._getspectrum(r)
711 self.mask = mask_and(self.mask, scan._getmask(r))
712 self.data = None
713 self.fit()
714 x = self.get_parameters()
715 fpar = self.get_parameters()
716 if plot:
717 self.plot(residual=True)
718 x = raw_input("Accept fit ([y]/n): ")
719 if x.upper() == 'N':
720 self.blpars.append(None)
721 continue
722 scan._setspectrum(self.fitter.getresidual(), r)
723 self.blpars.append(fpar)
724 if plot:
725 self._p.unmap()
726 self._p = None
727 print_log()
728 return scan
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