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source: trunk/python/asapfitter.py @ 1082

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Last change on this file since 1082 was 1075, checked in by mar637, 18 years ago
added errors to class; added fit convergence test; optional non-estimate in fit
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 19.2 KB

Rev	Line
[113]	1	import _asap
[259]	2	from asap import rcParams
[723]	3	from asap import print_log
[113]	4
	5	class fitter:
	6	"""
	7	The fitting class for ASAP.
	8	"""
[723]	9
[113]	10	def __init__(self):
	11	"""
	12	Create a fitter object. No state is set.
	13	"""
	14	self.fitter = _asap.fitter()
	15	self.x = None
	16	self.y = None
	17	self.mask = None
	18	self.fitfunc = None
[515]	19	self.fitfuncs = None
[113]	20	self.fitted = False
	21	self.data = None
[515]	22	self.components = 0
	23	self._fittedrow = 0
[113]	24	self._p = None
[515]	25	self._selection = None
[113]	26
	27	def set_data(self, xdat, ydat, mask=None):
	28	"""
[158]	29	Set the absissa and ordinate for the fit. Also set the mask
[113]	30	indicationg valid points.
	31	This can be used for data vectors retrieved from a scantable.
	32	For scantable fitting use 'fitter.set_scan(scan, mask)'.
	33	Parameters:
[158]	34	xdat: the abcissa values
[113]	35	ydat: the ordinate values
	36	mask: an optional mask
[723]	37
[113]	38	"""
	39	self.fitted = False
	40	self.x = xdat
	41	self.y = ydat
	42	if mask == None:
	43	from numarray import ones
	44	self.mask = ones(len(xdat))
	45	else:
	46	self.mask = mask
	47	return
	48
	49	def set_scan(self, thescan=None, mask=None):
	50	"""
	51	Set the 'data' (a scantable) of the fitter.
	52	Parameters:
	53	thescan: a scantable
	54	mask: a msk retireved from the scantable
	55	"""
	56	if not thescan:
[723]	57	msg = "Please give a correct scan"
	58	if rcParams['verbose']:
	59	print msg
	60	return
	61	else:
	62	raise TypeError(msg)
[113]	63	self.fitted = False
	64	self.data = thescan
[1075]	65	self.mask = None
[113]	66	if mask is None:
	67	from numarray import ones
	68	self.mask = ones(self.data.nchan())
	69	else:
	70	self.mask = mask
	71	return
	72
	73	def set_function(self, **kwargs):
	74	"""
	75	Set the function to be fit.
	76	Parameters:
	77	poly: use a polynomial of the order given
	78	gauss: fit the number of gaussian specified
	79	Example:
	80	fitter.set_function(gauss=2) # will fit two gaussians
	81	fitter.set_function(poly=3) # will fit a 3rd order polynomial
	82	"""
[723]	83	#default poly order 0
[515]	84	n=0
[113]	85	if kwargs.has_key('poly'):
	86	self.fitfunc = 'poly'
	87	n = kwargs.get('poly')
[515]	88	self.components = [n]
[113]	89	elif kwargs.has_key('gauss'):
	90	n = kwargs.get('gauss')
	91	self.fitfunc = 'gauss'
[515]	92	self.fitfuncs = [ 'gauss' for i in range(n) ]
	93	self.components = [ 3 for i in range(n) ]
	94	else:
[723]	95	msg = "Invalid function type."
	96	if rcParams['verbose']:
	97	print msg
	98	return
	99	else:
	100	raise TypeError(msg)
	101
[113]	102	self.fitter.setexpression(self.fitfunc,n)
	103	return
[723]	104
[1075]	105	def fit(self, row=0, estimate=False):
[113]	106	"""
	107	Execute the actual fitting process. All the state has to be set.
	108	Parameters:
[1075]	109	row: specify the row in the scantable
	110	estimate: auto-compute an initial parameter set (default False)
	111	This can be used to compute estimates even if fit was
	112	called before.
[113]	113	Example:
[515]	114	s = scantable('myscan.asap')
	115	s.set_cursor(thepol=1) # select second pol
[113]	116	f = fitter()
	117	f.set_scan(s)
	118	f.set_function(poly=0)
[723]	119	f.fit(row=0) # fit first row
[113]	120	"""
	121	if ((self.x is None or self.y is None) and self.data is None) \
	122	or self.fitfunc is None:
[723]	123	msg = "Fitter not yet initialised. Please set data & fit function"
	124	if rcParams['verbose']:
	125	print msg
	126	return
	127	else:
	128	raise RuntimeError(msg)
	129
[113]	130	else:
	131	if self.data is not None:
[515]	132	self.x = self.data._getabcissa(row)
	133	self.y = self.data._getspectrum(row)
[723]	134	from asap import asaplog
	135	asaplog.push("Fitting:")
[943]	136	i = row
	137	out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i),self.data.getbeam(i),self.data.getif(i),self.data.getpol(i), self.data.getcycle(i))
[1075]	138	asaplog.push(out,False)
[515]	139	self.fitter.setdata(self.x, self.y, self.mask)
[113]	140	if self.fitfunc == 'gauss':
	141	ps = self.fitter.getparameters()
[1075]	142	if len(ps) == 0 or estimate:
[113]	143	self.fitter.estimate()
[626]	144	try:
[1075]	145	converged = self.fitter.fit()
	146	if not converged:
	147	raise RuntimeError,"Fit didn't converge."
[626]	148	except RuntimeError, msg:
[723]	149	if rcParams['verbose']:
	150	print msg
	151	else:
	152	raise
[515]	153	self._fittedrow = row
[113]	154	self.fitted = True
[723]	155	print_log()
[113]	156	return
	157
[515]	158	def store_fit(self):
[526]	159	"""
	160	Store the fit parameters in the scantable.
	161	"""
[515]	162	if self.fitted and self.data is not None:
	163	pars = list(self.fitter.getparameters())
	164	fixed = list(self.fitter.getfixedparameters())
[975]	165	from asap.asapfit import asapfit
	166	fit = asapfit()
	167	fit.setparameters(pars)
	168	fit.setfixedparameters(fixed)
	169	fit.setfunctions(self.fitfuncs)
	170	fit.setcomponents(self.components)
	171	fit.setframeinfo(self.data._getcoordinfo())
	172	self.data._addfit(fit,self._fittedrow)
[515]	173
[1017]	174	#def set_parameters(self, params, fixed=None, component=None):
	175	def set_parameters(self,args,*kwargs):
[526]	176	"""
	177	Set the parameters to be fitted.
	178	Parameters:
	179	params: a vector of parameters
	180	fixed: a vector of which parameters are to be held fixed
	181	(default is none)
	182	component: in case of multiple gaussians, the index of the
	183	component
[1017]	184	"""
	185	component = None
	186	fixed = None
	187	params = None
[1031]	188
[1017]	189	if len(args) and isinstance(args[0],dict):
	190	kwargs = args[0]
	191	if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
	192	if kwargs.has_key("params"): params = kwargs["params"]
	193	if len(args) == 2 and isinstance(args[1], int):
	194	component = args[1]
[515]	195	if self.fitfunc is None:
[723]	196	msg = "Please specify a fitting function first."
	197	if rcParams['verbose']:
	198	print msg
	199	return
	200	else:
	201	raise RuntimeError(msg)
[515]	202	if self.fitfunc == "gauss" and component is not None:
[1017]	203	if not self.fitted and sum(self.fitter.getparameters()) == 0:
[515]	204	from numarray import zeros
	205	pars = list(zeros(len(self.components)*3))
	206	fxd = list(zeros(len(pars)))
	207	else:
[723]	208	pars = list(self.fitter.getparameters())
[515]	209	fxd = list(self.fitter.getfixedparameters())
	210	i = 3*component
	211	pars[i:i+3] = params
	212	fxd[i:i+3] = fixed
	213	params = pars
[723]	214	fixed = fxd
[113]	215	self.fitter.setparameters(params)
	216	if fixed is not None:
	217	self.fitter.setfixedparameters(fixed)
[723]	218	print_log()
[113]	219	return
[515]	220
	221	def set_gauss_parameters(self, peak, centre, fhwm,
[1017]	222	peakfixed=0, centerfixed=0,
	223	fhwmfixed=0,
[515]	224	component=0):
[113]	225	"""
[515]	226	Set the Parameters of a 'Gaussian' component, set with set_function.
	227	Parameters:
	228	peak, centre, fhwm: The gaussian parameters
	229	peakfixed,
	230	centerfixed,
	231	fhwmfixed: Optional parameters to indicate if
	232	the paramters should be held fixed during
	233	the fitting process. The default is to keep
	234	all parameters flexible.
[526]	235	component: The number of the component (Default is the
	236	component 0)
[515]	237	"""
	238	if self.fitfunc != "gauss":
[723]	239	msg = "Function only operates on Gaussian components."
	240	if rcParams['verbose']:
	241	print msg
	242	return
	243	else:
	244	raise ValueError(msg)
[515]	245	if 0 <= component < len(self.components):
[1017]	246	d = {'params':[peak, centre, fhwm],
	247	'fixed':[peakfixed, centerfixed, fhwmfixed]}
	248	self.set_parameters(d, component)
[515]	249	else:
[723]	250	msg = "Please select a valid component."
	251	if rcParams['verbose']:
	252	print msg
	253	return
	254	else:
	255	raise ValueError(msg)
	256
[975]	257	def get_area(self, component=None):
	258	"""
	259	Return the area under the fitted gaussian component.
	260	Parameters:
	261	component: the gaussian component selection,
	262	default (None) is the sum of all components
	263	Note:
	264	This will only work for gaussian fits.
	265	"""
	266	if not self.fitted: return
	267	if self.fitfunc == "gauss":
	268	pars = list(self.fitter.getparameters())
	269	from math import log,pi,sqrt
	270	fac = sqrt(pi/log(16.0))
	271	areas = []
	272	for i in range(len(self.components)):
	273	j = i*3
	274	cpars = pars[j:j+3]
	275	areas.append(fac * cpars[0] * cpars[2])
	276	else:
	277	return None
	278	if component is not None:
	279	return areas[component]
	280	else:
	281	return sum(areas)
	282
[1075]	283	def get_errors(self, component=None):
[515]	284	"""
[1075]	285	Return the errors in the parameters.
	286	Parameters:
	287	component: get the errors for the specified component
	288	only, default is all components
	289	"""
	290	if not self.fitted:
	291	msg = "Not yet fitted."
	292	if rcParams['verbose']:
	293	print msg
	294	return
	295	else:
	296	raise RuntimeError(msg)
	297	errs = list(self.fitter.geterrors())
	298	cerrs = errs
	299	if component is not None:
	300	if self.fitfunc == "gauss":
	301	i = 3*component
	302	if i < len(errs):
	303	cerrs = errs[i:i+3]
	304	return cerrs
	305
	306	def get_parameters(self, component=None, errors=False):
	307	"""
[113]	308	Return the fit paramters.
[526]	309	Parameters:
	310	component: get the parameters for the specified component
	311	only, default is all components
[113]	312	"""
	313	if not self.fitted:
[723]	314	msg = "Not yet fitted."
	315	if rcParams['verbose']:
	316	print msg
	317	return
	318	else:
	319	raise RuntimeError(msg)
[113]	320	pars = list(self.fitter.getparameters())
	321	fixed = list(self.fitter.getfixedparameters())
[1075]	322	errs = list(self.fitter.geterrors())
[1039]	323	area = []
[723]	324	if component is not None:
[515]	325	if self.fitfunc == "gauss":
	326	i = 3*component
	327	cpars = pars[i:i+3]
	328	cfixed = fixed[i:i+3]
[1075]	329	cerrs = errs[i:i+3]
[1039]	330	a = self.get_area(component)
	331	area = [a for i in range(3)]
[515]	332	else:
	333	cpars = pars
[723]	334	cfixed = fixed
[1075]	335	cerrs = errs
[515]	336	else:
	337	cpars = pars
	338	cfixed = fixed
[1075]	339	cerrs = errs
[1039]	340	if self.fitfunc == "gauss":
	341	for c in range(len(self.components)):
	342	a = self.get_area(c)
	343	area += [a for i in range(3)]
[1075]	344	fpars = self._format_pars(cpars, cfixed, None, area)
[723]	345	if rcParams['verbose']:
[515]	346	print fpars
[1075]	347	return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
	348	'errors':cerrs}
[723]	349
[1075]	350	def _format_pars(self, pars, fixed, errors, area):
[113]	351	out = ''
	352	if self.fitfunc == 'poly':
	353	c = 0
[515]	354	for i in range(len(pars)):
	355	fix = ""
	356	if fixed[i]: fix = "(fixed)"
[1061]	357	out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
[113]	358	c+=1
[515]	359	out = out[:-1] # remove trailing ','
[113]	360	elif self.fitfunc == 'gauss':
	361	i = 0
	362	c = 0
[515]	363	aunit = ''
	364	ounit = ''
[113]	365	if self.data:
[515]	366	aunit = self.data.get_unit()
	367	ounit = self.data.get_fluxunit()
[113]	368	while i < len(pars):
[1039]	369	if len(area):
	370	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)
[1017]	371	else:
	372	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)
[113]	373	c+=1
	374	i+=3
	375	return out
[723]	376
[113]	377	def get_estimate(self):
	378	"""
[515]	379	Return the parameter estimates (for non-linear functions).
[113]	380	"""
	381	pars = self.fitter.getestimate()
[943]	382	fixed = self.fitter.getfixedparameters()
[723]	383	if rcParams['verbose']:
[1017]	384	print self._format_pars(pars,fixed,None)
[113]	385	return pars
	386
	387	def get_residual(self):
	388	"""
	389	Return the residual of the fit.
	390	"""
	391	if not self.fitted:
[723]	392	msg = "Not yet fitted."
	393	if rcParams['verbose']:
	394	print msg
	395	return
	396	else:
	397	raise RuntimeError(msg)
[113]	398	return self.fitter.getresidual()
	399
	400	def get_chi2(self):
	401	"""
	402	Return chi^2.
	403	"""
	404	if not self.fitted:
[723]	405	msg = "Not yet fitted."
	406	if rcParams['verbose']:
	407	print msg
	408	return
	409	else:
	410	raise RuntimeError(msg)
[113]	411	ch2 = self.fitter.getchi2()
[723]	412	if rcParams['verbose']:
[113]	413	print 'Chi^2 = %3.3f' % (ch2)
[723]	414	return ch2
[113]	415
	416	def get_fit(self):
	417	"""
	418	Return the fitted ordinate values.
	419	"""
	420	if not self.fitted:
[723]	421	msg = "Not yet fitted."
	422	if rcParams['verbose']:
	423	print msg
	424	return
	425	else:
	426	raise RuntimeError(msg)
[113]	427	return self.fitter.getfit()
	428
	429	def commit(self):
	430	"""
[526]	431	Return a new scan where the fits have been commited (subtracted)
[113]	432	"""
	433	if not self.fitted:
	434	print "Not yet fitted."
[723]	435	msg = "Not yet fitted."
	436	if rcParams['verbose']:
	437	print msg
	438	return
	439	else:
	440	raise RuntimeError(msg)
[975]	441	from asap import scantable
	442	if not isinstance(self.data, scantable):
[723]	443	msg = "Not a scantable"
	444	if rcParams['verbose']:
	445	print msg
	446	return
	447	else:
	448	raise TypeError(msg)
[113]	449	scan = self.data.copy()
[259]	450	scan._setspectrum(self.fitter.getresidual())
[723]	451	print_log()
[113]	452
[723]	453	def plot(self, residual=False, components=None, plotparms=False, filename=None):
[113]	454	"""
	455	Plot the last fit.
	456	Parameters:
	457	residual: an optional parameter indicating if the residual
	458	should be plotted (default 'False')
[526]	459	components: a list of components to plot, e.g [0,1],
	460	-1 plots the total fit. Default is to only
	461	plot the total fit.
	462	plotparms: Inidicates if the parameter values should be present
	463	on the plot
[113]	464	"""
	465	if not self.fitted:
	466	return
[723]	467	if not self._p or self._p.is_dead:
	468	if rcParams['plotter.gui']:
	469	from asap.asaplotgui import asaplotgui as asaplot
	470	else:
	471	from asap.asaplot import asaplot
	472	self._p = asaplot()
	473	self._p.hold()
[113]	474	self._p.clear()
[515]	475	self._p.set_panels()
[652]	476	self._p.palette(0)
[113]	477	tlab = 'Spectrum'
[723]	478	xlab = 'Abcissa'
[1017]	479	ylab = 'Ordinate'
	480	m = None
[113]	481	if self.data:
[515]	482	tlab = self.data._getsourcename(self._fittedrow)
	483	xlab = self.data._getabcissalabel(self._fittedrow)
	484	m = self.data._getmask(self._fittedrow)
[626]	485	ylab = self.data._get_ordinate_label()
[515]	486
[1075]	487	colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
[652]	488	self._p.palette(0,colours)
[515]	489	self._p.set_line(label='Spectrum')
[113]	490	self._p.plot(self.x, self.y, m)
	491	if residual:
[652]	492	self._p.palette(1)
[515]	493	self._p.set_line(label='Residual')
[113]	494	self._p.plot(self.x, self.get_residual(), m)
[652]	495	self._p.palette(2)
[515]	496	if components is not None:
	497	cs = components
	498	if isinstance(components,int): cs = [components]
[526]	499	if plotparms:
[1031]	500	self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
[515]	501	n = len(self.components)
[652]	502	self._p.palette(3)
[515]	503	for c in cs:
	504	if 0 <= c < n:
	505	lab = self.fitfuncs[c]+str(c)
	506	self._p.set_line(label=lab)
	507	self._p.plot(self.x, self.fitter.evaluate(c), m)
	508	elif c == -1:
[652]	509	self._p.palette(2)
[515]	510	self._p.set_line(label="Total Fit")
[723]	511	self._p.plot(self.x, self.get_fit(), m)
[515]	512	else:
[652]	513	self._p.palette(2)
[515]	514	self._p.set_line(label='Fit')
	515	self._p.plot(self.x, self.get_fit(), m)
[723]	516	xlim=[min(self.x),max(self.x)]
	517	self._p.axes.set_xlim(xlim)
[113]	518	self._p.set_axes('xlabel',xlab)
	519	self._p.set_axes('ylabel',ylab)
	520	self._p.set_axes('title',tlab)
	521	self._p.release()
[723]	522	if (not rcParams['plotter.gui']):
	523	self._p.save(filename)
	524	print_log()
[113]	525
[1061]	526	def auto_fit(self, insitu=None, plot=False):
[113]	527	"""
[515]	528	Return a scan where the function is applied to all rows for
	529	all Beams/IFs/Pols.
[723]	530
[113]	531	"""
	532	from asap import scantable
[515]	533	if not isinstance(self.data, scantable) :
[723]	534	msg = "Data is not a scantable"
	535	if rcParams['verbose']:
	536	print msg
	537	return
	538	else:
	539	raise TypeError(msg)
[259]	540	if insitu is None: insitu = rcParams['insitu']
	541	if not insitu:
	542	scan = self.data.copy()
	543	else:
	544	scan = self.data
[880]	545	rows = xrange(scan.nrow())
[723]	546	from asap import asaplog
[876]	547	asaplog.push("Fitting:")
	548	for r in rows:
[1031]	549	out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),scan.getbeam(r),scan.getif(r),scan.getpol(r), scan.getcycle(r))
[880]	550	asaplog.push(out, False)
[876]	551	self.x = scan._getabcissa(r)
	552	self.y = scan._getspectrum(r)
	553	self.data = None
	554	self.fit()
	555	x = self.get_parameters()
[1061]	556	if plot:
	557	self.plot(residual=True)
	558	x = raw_input("Accept fit ([y]/n): ")
	559	if x.upper() == 'N':
	560	continue
[880]	561	scan._setspectrum(self.fitter.getresidual(), r)
[1061]	562	if plot:
	563	self._p.unmap()
	564	self._p = None
[876]	565	print_log()
	566	return scan
[794]	567

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