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