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source: trunk/python/asapfitter.py @ 1232

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Last change on this file since 1232 was 1232, checked in by mar637, 18 years ago
Merge from Release2.1.0b tag
Property svn:eol-style set to `native` Property svn:keywords set to `Author Date Id Revision`
File size: 20.5 KB

Rev	Line
[113]	1	import _asap
[259]	2	from asap import rcParams
[723]	3	from asap import print_log
[1134]	4	from asap import NUM
[113]	5
	6	class fitter:
	7	"""
	8	The fitting class for ASAP.
	9	"""
[723]	10
[113]	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
[515]	20	self.fitfuncs = None
[113]	21	self.fitted = False
	22	self.data = None
[515]	23	self.components = 0
	24	self._fittedrow = 0
[113]	25	self._p = None
[515]	26	self._selection = None
[113]	27
	28	def set_data(self, xdat, ydat, mask=None):
	29	"""
[158]	30	Set the absissa and ordinate for the fit. Also set the mask
[113]	31	indicationg valid points.
	32	This can be used for data vectors retrieved from a scantable.
	33	For scantable fitting use 'fitter.set_scan(scan, mask)'.
	34	Parameters:
[158]	35	xdat: the abcissa values
[113]	36	ydat: the ordinate values
	37	mask: an optional mask
[723]	38
[113]	39	"""
	40	self.fitted = False
	41	self.x = xdat
	42	self.y = ydat
	43	if mask == None:
[1134]	44	self.mask = NUM.ones(len(xdat))
[113]	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:
[1134]	67	self.mask = NUM.ones(self.data.nchan())
[113]	68	else:
	69	self.mask = mask
	70	return
	71
	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
	77	gauss: fit the number of gaussian specified
	78	Example:
	79	fitter.set_function(gauss=2) # will fit two gaussians
	80	fitter.set_function(poly=3) # will fit a 3rd order polynomial
	81	"""
[723]	82	#default poly order 0
[515]	83	n=0
[113]	84	if kwargs.has_key('poly'):
	85	self.fitfunc = 'poly'
	86	n = kwargs.get('poly')
[515]	87	self.components = [n]
[113]	88	elif kwargs.has_key('gauss'):
	89	n = kwargs.get('gauss')
	90	self.fitfunc = 'gauss'
[515]	91	self.fitfuncs = [ 'gauss' for i in range(n) ]
	92	self.components = [ 3 for i in range(n) ]
	93	else:
[723]	94	msg = "Invalid function type."
	95	if rcParams['verbose']:
	96	print msg
	97	return
	98	else:
	99	raise TypeError(msg)
	100
[113]	101	self.fitter.setexpression(self.fitfunc,n)
[1232]	102	self.fitted = False
[113]	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:
[1232]	145	fxdpar = list(self.fitter.getfixedparameters())
	146	if len(fxdpar) and fxdpar.count(0) == 0:
	147	raise RuntimeError,"No point fitting, if all parameters are fixed."
[1075]	148	converged = self.fitter.fit()
	149	if not converged:
	150	raise RuntimeError,"Fit didn't converge."
[626]	151	except RuntimeError, msg:
[723]	152	if rcParams['verbose']:
	153	print msg
	154	else:
	155	raise
[515]	156	self._fittedrow = row
[113]	157	self.fitted = True
[723]	158	print_log()
[113]	159	return
	160
[1232]	161	def store_fit(self, filename=None):
[526]	162	"""
[1232]	163	Save the fit parameters.
	164	Parameters:
	165	filename: if specified save as an ASCII file, if None (default)
	166	store it in the scnatable
[526]	167	"""
[515]	168	if self.fitted and self.data is not None:
	169	pars = list(self.fitter.getparameters())
	170	fixed = list(self.fitter.getfixedparameters())
[975]	171	from asap.asapfit import asapfit
	172	fit = asapfit()
	173	fit.setparameters(pars)
	174	fit.setfixedparameters(fixed)
	175	fit.setfunctions(self.fitfuncs)
	176	fit.setcomponents(self.components)
	177	fit.setframeinfo(self.data._getcoordinfo())
[1232]	178	if filename is not None:
	179	import os
	180	filename = os.path.expandvars(os.path.expanduser(filename))
	181	if os.path.exists(filename):
	182	raise IOError("File '%s' exists." % filename)
	183	fit.save(filename)
	184	else:
	185	self.data._addfit(fit,self._fittedrow)
[515]	186
[1017]	187	#def set_parameters(self, params, fixed=None, component=None):
	188	def set_parameters(self,args,*kwargs):
[526]	189	"""
	190	Set the parameters to be fitted.
	191	Parameters:
	192	params: a vector of parameters
	193	fixed: a vector of which parameters are to be held fixed
	194	(default is none)
	195	component: in case of multiple gaussians, the index of the
	196	component
[1017]	197	"""
	198	component = None
	199	fixed = None
	200	params = None
[1031]	201
[1017]	202	if len(args) and isinstance(args[0],dict):
	203	kwargs = args[0]
	204	if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
	205	if kwargs.has_key("params"): params = kwargs["params"]
	206	if len(args) == 2 and isinstance(args[1], int):
	207	component = args[1]
[515]	208	if self.fitfunc is None:
[723]	209	msg = "Please specify a fitting function first."
	210	if rcParams['verbose']:
	211	print msg
	212	return
	213	else:
	214	raise RuntimeError(msg)
[515]	215	if self.fitfunc == "gauss" and component is not None:
[1017]	216	if not self.fitted and sum(self.fitter.getparameters()) == 0:
[1134]	217	pars = list(NUM.zeros(len(self.components)*3))
	218	fxd = list(NUM.zeros(len(pars)))
[515]	219	else:
[723]	220	pars = list(self.fitter.getparameters())
[515]	221	fxd = list(self.fitter.getfixedparameters())
	222	i = 3*component
	223	pars[i:i+3] = params
	224	fxd[i:i+3] = fixed
	225	params = pars
[723]	226	fixed = fxd
[113]	227	self.fitter.setparameters(params)
	228	if fixed is not None:
	229	self.fitter.setfixedparameters(fixed)
[723]	230	print_log()
[113]	231	return
[515]	232
[1217]	233	def set_gauss_parameters(self, peak, centre, fwhm,
[1017]	234	peakfixed=0, centerfixed=0,
[1217]	235	fwhmfixed=0,
[515]	236	component=0):
[113]	237	"""
[515]	238	Set the Parameters of a 'Gaussian' component, set with set_function.
	239	Parameters:
[1232]	240	peak, centre, fwhm: The gaussian parameters
[515]	241	peakfixed,
	242	centerfixed,
[1217]	243	fwhmfixed: Optional parameters to indicate if
[515]	244	the paramters should be held fixed during
	245	the fitting process. The default is to keep
	246	all parameters flexible.
[526]	247	component: The number of the component (Default is the
	248	component 0)
[515]	249	"""
	250	if self.fitfunc != "gauss":
[723]	251	msg = "Function only operates on Gaussian components."
	252	if rcParams['verbose']:
	253	print msg
	254	return
	255	else:
	256	raise ValueError(msg)
[515]	257	if 0 <= component < len(self.components):
[1217]	258	d = {'params':[peak, centre, fwhm],
	259	'fixed':[peakfixed, centerfixed, fwhmfixed]}
[1017]	260	self.set_parameters(d, component)
[515]	261	else:
[723]	262	msg = "Please select a valid component."
	263	if rcParams['verbose']:
	264	print msg
	265	return
	266	else:
	267	raise ValueError(msg)
	268
[975]	269	def get_area(self, component=None):
	270	"""
	271	Return the area under the fitted gaussian component.
	272	Parameters:
	273	component: the gaussian component selection,
	274	default (None) is the sum of all components
	275	Note:
	276	This will only work for gaussian fits.
	277	"""
	278	if not self.fitted: return
	279	if self.fitfunc == "gauss":
	280	pars = list(self.fitter.getparameters())
	281	from math import log,pi,sqrt
	282	fac = sqrt(pi/log(16.0))
	283	areas = []
	284	for i in range(len(self.components)):
	285	j = i*3
	286	cpars = pars[j:j+3]
	287	areas.append(fac * cpars[0] * cpars[2])
	288	else:
	289	return None
	290	if component is not None:
	291	return areas[component]
	292	else:
	293	return sum(areas)
	294
[1075]	295	def get_errors(self, component=None):
[515]	296	"""
[1075]	297	Return the errors in the parameters.
	298	Parameters:
	299	component: get the errors for the specified component
	300	only, default is all components
	301	"""
	302	if not self.fitted:
	303	msg = "Not yet fitted."
	304	if rcParams['verbose']:
	305	print msg
	306	return
	307	else:
	308	raise RuntimeError(msg)
	309	errs = list(self.fitter.geterrors())
	310	cerrs = errs
	311	if component is not None:
	312	if self.fitfunc == "gauss":
	313	i = 3*component
	314	if i < len(errs):
	315	cerrs = errs[i:i+3]
	316	return cerrs
	317
	318	def get_parameters(self, component=None, errors=False):
	319	"""
[113]	320	Return the fit paramters.
[526]	321	Parameters:
	322	component: get the parameters for the specified component
	323	only, default is all components
[113]	324	"""
	325	if not self.fitted:
[723]	326	msg = "Not yet fitted."
	327	if rcParams['verbose']:
	328	print msg
	329	return
	330	else:
	331	raise RuntimeError(msg)
[113]	332	pars = list(self.fitter.getparameters())
	333	fixed = list(self.fitter.getfixedparameters())
[1075]	334	errs = list(self.fitter.geterrors())
[1039]	335	area = []
[723]	336	if component is not None:
[515]	337	if self.fitfunc == "gauss":
	338	i = 3*component
	339	cpars = pars[i:i+3]
	340	cfixed = fixed[i:i+3]
[1075]	341	cerrs = errs[i:i+3]
[1039]	342	a = self.get_area(component)
	343	area = [a for i in range(3)]
[515]	344	else:
	345	cpars = pars
[723]	346	cfixed = fixed
[1075]	347	cerrs = errs
[515]	348	else:
	349	cpars = pars
	350	cfixed = fixed
[1075]	351	cerrs = errs
[1039]	352	if self.fitfunc == "gauss":
	353	for c in range(len(self.components)):
	354	a = self.get_area(c)
	355	area += [a for i in range(3)]
[1088]	356	fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
[723]	357	if rcParams['verbose']:
[515]	358	print fpars
[1075]	359	return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
	360	'errors':cerrs}
[723]	361
[1075]	362	def _format_pars(self, pars, fixed, errors, area):
[113]	363	out = ''
	364	if self.fitfunc == 'poly':
	365	c = 0
[515]	366	for i in range(len(pars)):
	367	fix = ""
[1232]	368	if len(fixed) and fixed[i]: fix = "(fixed)"
[1088]	369	if errors :
	370	out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])
	371	else:
	372	out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
[113]	373	c+=1
[515]	374	out = out[:-1] # remove trailing ','
[113]	375	elif self.fitfunc == 'gauss':
	376	i = 0
	377	c = 0
[515]	378	aunit = ''
	379	ounit = ''
[113]	380	if self.data:
[515]	381	aunit = self.data.get_unit()
	382	ounit = self.data.get_fluxunit()
[113]	383	while i < len(pars):
[1039]	384	if len(area):
	385	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]	386	else:
	387	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]	388	c+=1
	389	i+=3
	390	return out
[723]	391
[113]	392	def get_estimate(self):
	393	"""
[515]	394	Return the parameter estimates (for non-linear functions).
[113]	395	"""
	396	pars = self.fitter.getestimate()
[943]	397	fixed = self.fitter.getfixedparameters()
[723]	398	if rcParams['verbose']:
[1017]	399	print self._format_pars(pars,fixed,None)
[113]	400	return pars
	401
	402	def get_residual(self):
	403	"""
	404	Return the residual of the fit.
	405	"""
	406	if not self.fitted:
[723]	407	msg = "Not yet fitted."
	408	if rcParams['verbose']:
	409	print msg
	410	return
	411	else:
	412	raise RuntimeError(msg)
[113]	413	return self.fitter.getresidual()
	414
	415	def get_chi2(self):
	416	"""
	417	Return chi^2.
	418	"""
	419	if not self.fitted:
[723]	420	msg = "Not yet fitted."
	421	if rcParams['verbose']:
	422	print msg
	423	return
	424	else:
	425	raise RuntimeError(msg)
[113]	426	ch2 = self.fitter.getchi2()
[723]	427	if rcParams['verbose']:
[113]	428	print 'Chi^2 = %3.3f' % (ch2)
[723]	429	return ch2
[113]	430
	431	def get_fit(self):
	432	"""
	433	Return the fitted ordinate values.
	434	"""
	435	if not self.fitted:
[723]	436	msg = "Not yet fitted."
	437	if rcParams['verbose']:
	438	print msg
	439	return
	440	else:
	441	raise RuntimeError(msg)
[113]	442	return self.fitter.getfit()
	443
	444	def commit(self):
	445	"""
[526]	446	Return a new scan where the fits have been commited (subtracted)
[113]	447	"""
	448	if not self.fitted:
[723]	449	msg = "Not yet fitted."
	450	if rcParams['verbose']:
	451	print msg
	452	return
	453	else:
	454	raise RuntimeError(msg)
[975]	455	from asap import scantable
	456	if not isinstance(self.data, scantable):
[723]	457	msg = "Not a scantable"
	458	if rcParams['verbose']:
	459	print msg
	460	return
	461	else:
	462	raise TypeError(msg)
[113]	463	scan = self.data.copy()
[259]	464	scan._setspectrum(self.fitter.getresidual())
[723]	465	print_log()
[1092]	466	return scan
[113]	467
[723]	468	def plot(self, residual=False, components=None, plotparms=False, filename=None):
[113]	469	"""
	470	Plot the last fit.
	471	Parameters:
	472	residual: an optional parameter indicating if the residual
	473	should be plotted (default 'False')
[526]	474	components: a list of components to plot, e.g [0,1],
	475	-1 plots the total fit. Default is to only
	476	plot the total fit.
	477	plotparms: Inidicates if the parameter values should be present
	478	on the plot
[113]	479	"""
	480	if not self.fitted:
	481	return
[723]	482	if not self._p or self._p.is_dead:
	483	if rcParams['plotter.gui']:
	484	from asap.asaplotgui import asaplotgui as asaplot
	485	else:
	486	from asap.asaplot import asaplot
	487	self._p = asaplot()
	488	self._p.hold()
[113]	489	self._p.clear()
[515]	490	self._p.set_panels()
[652]	491	self._p.palette(0)
[113]	492	tlab = 'Spectrum'
[723]	493	xlab = 'Abcissa'
[1017]	494	ylab = 'Ordinate'
[1217]	495	from matplotlib.numerix import ma,logical_not,array
	496	m = NUM.ones(len(self.x))
	497
[113]	498	if self.data:
[515]	499	tlab = self.data._getsourcename(self._fittedrow)
	500	xlab = self.data._getabcissalabel(self._fittedrow)
	501	m = self.data._getmask(self._fittedrow)
[626]	502	ylab = self.data._get_ordinate_label()
[515]	503
[1075]	504	colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
[652]	505	self._p.palette(0,colours)
[515]	506	self._p.set_line(label='Spectrum')
[1116]	507	y = ma.masked_array(self.y,mask=logical_not(array(m,copy=False)))
[1088]	508	self._p.plot(self.x, y)
[113]	509	if residual:
[652]	510	self._p.palette(1)
[515]	511	self._p.set_line(label='Residual')
[1116]	512	y = ma.masked_array(self.get_residual(),
	513	mask=logical_not(array(m,copy=False)))
[1088]	514	self._p.plot(self.x, y)
[652]	515	self._p.palette(2)
[515]	516	if components is not None:
	517	cs = components
	518	if isinstance(components,int): cs = [components]
[526]	519	if plotparms:
[1031]	520	self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
[515]	521	n = len(self.components)
[652]	522	self._p.palette(3)
[515]	523	for c in cs:
	524	if 0 <= c < n:
	525	lab = self.fitfuncs[c]+str(c)
	526	self._p.set_line(label=lab)
[1116]	527	y = ma.masked_array(self.fitter.evaluate(c),
	528	mask=logical_not(array(m,copy=False)))
[1088]	529
	530	self._p.plot(self.x, y)
[515]	531	elif c == -1:
[652]	532	self._p.palette(2)
[515]	533	self._p.set_line(label="Total Fit")
[1116]	534	y = ma.masked_array(self.fitter.getfit(),
	535	mask=logical_not(array(m,copy=False)))
[1088]	536	self._p.plot(self.x, y)
[515]	537	else:
[652]	538	self._p.palette(2)
[515]	539	self._p.set_line(label='Fit')
[1116]	540	y = ma.masked_array(self.fitter.getfit(),
	541	mask=logical_not(array(m,copy=False)))
[1088]	542	self._p.plot(self.x, y)
[723]	543	xlim=[min(self.x),max(self.x)]
	544	self._p.axes.set_xlim(xlim)
[113]	545	self._p.set_axes('xlabel',xlab)
	546	self._p.set_axes('ylabel',ylab)
	547	self._p.set_axes('title',tlab)
	548	self._p.release()
[723]	549	if (not rcParams['plotter.gui']):
	550	self._p.save(filename)
	551	print_log()
[113]	552
[1061]	553	def auto_fit(self, insitu=None, plot=False):
[113]	554	"""
[515]	555	Return a scan where the function is applied to all rows for
	556	all Beams/IFs/Pols.
[723]	557
[113]	558	"""
	559	from asap import scantable
[515]	560	if not isinstance(self.data, scantable) :
[723]	561	msg = "Data is not a scantable"
	562	if rcParams['verbose']:
	563	print msg
	564	return
	565	else:
	566	raise TypeError(msg)
[259]	567	if insitu is None: insitu = rcParams['insitu']
	568	if not insitu:
	569	scan = self.data.copy()
	570	else:
	571	scan = self.data
[880]	572	rows = xrange(scan.nrow())
[723]	573	from asap import asaplog
[876]	574	asaplog.push("Fitting:")
	575	for r in rows:
[1031]	576	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]	577	asaplog.push(out, False)
[876]	578	self.x = scan._getabcissa(r)
	579	self.y = scan._getspectrum(r)
	580	self.data = None
	581	self.fit()
	582	x = self.get_parameters()
[1061]	583	if plot:
	584	self.plot(residual=True)
	585	x = raw_input("Accept fit ([y]/n): ")
	586	if x.upper() == 'N':
	587	continue
[880]	588	scan._setspectrum(self.fitter.getresidual(), r)
[1061]	589	if plot:
	590	self._p.unmap()
	591	self._p = None
[876]	592	print_log()
	593	return scan
[794]	594

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