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source: branches/alma/python/asapfitter.py@ 1714

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Last change on this file since 1714 was 1701, checked in by WataruKawasaki, 15 years ago

New Development: Yes

JIRA Issue: Yes (CAS-1800 + CAS-1807)

Ready to Release: Yes

Interface Changes: Yes

What Interface Changed: added new methods to scantable and fitter.

Test Programs:

Put in Release Notes: No

Module(s): sdfit, sdflag

Description: added new methods 'scantable.clip' and 'fitter.set_lorentz_parameters'.

Property svn:eol-style set to native
Property svn:keywords set to Author Date Id Revision

File size: 26.1 KB

Rev	Line
[113]	1	import _asap
[259]	2	from asap import rcParams
[723]	3	from asap import print_log
[1295]	4	from asap import _n_bools
[1603]	5	from asap import mask_and
[1614]	6	from asap import asaplog
[113]	7
	8	class fitter:
	9	"""
	10	The fitting class for ASAP.
	11	"""
[723]	12
[113]	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
[515]	22	self.fitfuncs = None
[113]	23	self.fitted = False
	24	self.data = None
[515]	25	self.components = 0
	26	self._fittedrow = 0
[113]	27	self._p = None
[515]	28	self._selection = None
[1389]	29	self.uselinear = False
[113]	30
	31	def set_data(self, xdat, ydat, mask=None):
	32	"""
[158]	33	Set the absissa and ordinate for the fit. Also set the mask
[113]	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:
[158]	38	xdat: the abcissa values
[113]	39	ydat: the ordinate values
	40	mask: an optional mask
[723]	41
[113]	42	"""
	43	self.fitted = False
	44	self.x = xdat
	45	self.y = ydat
	46	if mask == None:
[1295]	47	self.mask = _n_bools(len(xdat), True)
[113]	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
[1603]	57	mask: a msk retrieved from the scantable
[113]	58	"""
	59	if not thescan:
[723]	60	msg = "Please give a correct scan"
	61	if rcParams['verbose']:
[1612]	62	#print msg
[1614]	63	asaplog.push(msg)
	64	print_log('ERROR')
[723]	65	return
	66	else:
	67	raise TypeError(msg)
[113]	68	self.fitted = False
	69	self.data = thescan
[1075]	70	self.mask = None
[113]	71	if mask is None:
[1295]	72	self.mask = _n_bools(self.data.nchan(), True)
[113]	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:
[1389]	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
[113]	83	gauss: fit the number of gaussian specified
[1701]	84	lorentz: fit the number of lorentzian specified
[113]	85	Example:
[1389]	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
[1701]	88	fitter.set_function(gauss=2) # will fit two gaussians
	89	fitter.set_function(lorentz=2) # will fit two lorentzians
[113]	90	"""
[723]	91	#default poly order 0
[515]	92	n=0
[113]	93	if kwargs.has_key('poly'):
	94	self.fitfunc = 'poly'
	95	n = kwargs.get('poly')
[515]	96	self.components = [n]
[1389]	97	self.uselinear = False
	98	elif kwargs.has_key('lpoly'):
	99	self.fitfunc = 'poly'
	100	n = kwargs.get('lpoly')
	101	self.components = [n]
	102	self.uselinear = True
[113]	103	elif kwargs.has_key('gauss'):
	104	n = kwargs.get('gauss')
	105	self.fitfunc = 'gauss'
[515]	106	self.fitfuncs = [ 'gauss' for i in range(n) ]
	107	self.components = [ 3 for i in range(n) ]
[1389]	108	self.uselinear = False
[1701]	109	elif kwargs.has_key('lorentz'):
	110	n = kwargs.get('lorentz')
	111	self.fitfunc = 'lorentz'
	112	self.fitfuncs = [ 'lorentz' for i in range(n) ]
	113	self.components = [ 3 for i in range(n) ]
	114	self.uselinear = False
[515]	115	else:
[723]	116	msg = "Invalid function type."
	117	if rcParams['verbose']:
[1612]	118	#print msg
[1614]	119	asaplog.push(msg)
	120	print_log('ERROR')
[723]	121	return
	122	else:
	123	raise TypeError(msg)
	124
[113]	125	self.fitter.setexpression(self.fitfunc,n)
[1232]	126	self.fitted = False
[113]	127	return
[723]	128
[1075]	129	def fit(self, row=0, estimate=False):
[113]	130	"""
	131	Execute the actual fitting process. All the state has to be set.
	132	Parameters:
[1075]	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.
[113]	137	Example:
[515]	138	s = scantable('myscan.asap')
	139	s.set_cursor(thepol=1) # select second pol
[113]	140	f = fitter()
	141	f.set_scan(s)
	142	f.set_function(poly=0)
[723]	143	f.fit(row=0) # fit first row
[113]	144	"""
	145	if ((self.x is None or self.y is None) and self.data is None) \
	146	or self.fitfunc is None:
[723]	147	msg = "Fitter not yet initialised. Please set data & fit function"
	148	if rcParams['verbose']:
[1612]	149	#print msg
[1614]	150	asaplog.push(msg)
	151	print_log('ERROR')
[723]	152	return
	153	else:
	154	raise RuntimeError(msg)
	155
[113]	156	else:
	157	if self.data is not None:
[515]	158	self.x = self.data._getabcissa(row)
	159	self.y = self.data._getspectrum(row)
[1603]	160	self.mask = mask_and(self.mask, self.data._getmask(row))
[723]	161	asaplog.push("Fitting:")
[943]	162	i = row
[1603]	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))
[1075]	168	asaplog.push(out,False)
[515]	169	self.fitter.setdata(self.x, self.y, self.mask)
[1701]	170	if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
[113]	171	ps = self.fitter.getparameters()
[1075]	172	if len(ps) == 0 or estimate:
[113]	173	self.fitter.estimate()
[1628]	174	try:
	175	fxdpar = list(self.fitter.getfixedparameters())
[1232]	176	if len(fxdpar) and fxdpar.count(0) == 0:
	177	raise RuntimeError,"No point fitting, if all parameters are fixed."
[1389]	178	if self.uselinear:
	179	converged = self.fitter.lfit()
	180	else:
	181	converged = self.fitter.fit()
[1075]	182	if not converged:
	183	raise RuntimeError,"Fit didn't converge."
[626]	184	except RuntimeError, msg:
[723]	185	if rcParams['verbose']:
[1612]	186	#print msg
[1614]	187	print_log()
[1676]	188	asaplog.push(str(msg))
[1614]	189	print_log('ERROR')
[723]	190	else:
	191	raise
[515]	192	self._fittedrow = row
[113]	193	self.fitted = True
[723]	194	print_log()
[113]	195	return
	196
[1232]	197	def store_fit(self, filename=None):
[526]	198	"""
[1232]	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
[526]	203	"""
[515]	204	if self.fitted and self.data is not None:
	205	pars = list(self.fitter.getparameters())
	206	fixed = list(self.fitter.getfixedparameters())
[975]	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())
[1232]	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)
[515]	222
[1017]	223	#def set_parameters(self, params, fixed=None, component=None):
	224	def set_parameters(self,args,*kwargs):
[526]	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
[1017]	233	"""
	234	component = None
	235	fixed = None
	236	params = None
[1031]	237
[1017]	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]
[515]	244	if self.fitfunc is None:
[723]	245	msg = "Please specify a fitting function first."
	246	if rcParams['verbose']:
[1612]	247	#print msg
[1614]	248	asaplog.push(msg)
	249	print_log('ERROR')
[723]	250	return
	251	else:
	252	raise RuntimeError(msg)
[1701]	253	if (self.fitfunc == "gauss" or self.fitfunc == 'lorentz') and component is not None:
[1017]	254	if not self.fitted and sum(self.fitter.getparameters()) == 0:
[1295]	255	pars = _n_bools(len(self.components)*3, False)
	256	fxd = _n_bools(len(pars), False)
[515]	257	else:
[723]	258	pars = list(self.fitter.getparameters())
[515]	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
[723]	264	fixed = fxd
[113]	265	self.fitter.setparameters(params)
	266	if fixed is not None:
	267	self.fitter.setfixedparameters(fixed)
[723]	268	print_log()
[113]	269	return
[515]	270
[1217]	271	def set_gauss_parameters(self, peak, centre, fwhm,
[1603]	272	peakfixed=0, centrefixed=0,
[1217]	273	fwhmfixed=0,
[515]	274	component=0):
[113]	275	"""
[515]	276	Set the Parameters of a 'Gaussian' component, set with set_function.
	277	Parameters:
[1232]	278	peak, centre, fwhm: The gaussian parameters
[515]	279	peakfixed,
[1603]	280	centrefixed,
[1217]	281	fwhmfixed: Optional parameters to indicate if
[515]	282	the paramters should be held fixed during
	283	the fitting process. The default is to keep
	284	all parameters flexible.
[526]	285	component: The number of the component (Default is the
	286	component 0)
[515]	287	"""
	288	if self.fitfunc != "gauss":
[723]	289	msg = "Function only operates on Gaussian components."
	290	if rcParams['verbose']:
[1612]	291	#print msg
[1614]	292	asaplog.push(msg)
	293	print_log('ERROR')
[723]	294	return
	295	else:
	296	raise ValueError(msg)
[515]	297	if 0 <= component < len(self.components):
[1217]	298	d = {'params':[peak, centre, fwhm],
[1603]	299	'fixed':[peakfixed, centrefixed, fwhmfixed]}
[1017]	300	self.set_parameters(d, component)
[515]	301	else:
[723]	302	msg = "Please select a valid component."
	303	if rcParams['verbose']:
[1612]	304	#print msg
[1614]	305	asaplog.push(msg)
	306	print_log('ERROR')
[723]	307	return
	308	else:
	309	raise ValueError(msg)
	310
[1701]	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
[975]	351	def get_area(self, component=None):
	352	"""
[1701]	353	Return the area under the fitted gaussian/lorentzian component.
[975]	354	Parameters:
[1701]	355	component: the gaussian/lorentzian component selection,
[975]	356	default (None) is the sum of all components
	357	Note:
[1701]	358	This will only work for gaussian/lorentzian fits.
[975]	359	"""
	360	if not self.fitted: return
[1701]	361	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[975]	362	pars = list(self.fitter.getparameters())
	363	from math import log,pi,sqrt
[1701]	364	if self.fitfunc == "gauss":
	365	fac = sqrt(pi/log(16.0))
	366	elif self.fitfunc == "lorentz":
	367	fac = pi/2.0
[975]	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
[1075]	380	def get_errors(self, component=None):
[515]	381	"""
[1075]	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']:
[1612]	390	#print msg
[1614]	391	asaplog.push(msg)
	392	print_log('ERROR')
[1075]	393	return
	394	else:
	395	raise RuntimeError(msg)
	396	errs = list(self.fitter.geterrors())
	397	cerrs = errs
	398	if component is not None:
[1701]	399	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[1075]	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	"""
[113]	407	Return the fit paramters.
[526]	408	Parameters:
	409	component: get the parameters for the specified component
	410	only, default is all components
[113]	411	"""
	412	if not self.fitted:
[723]	413	msg = "Not yet fitted."
	414	if rcParams['verbose']:
[1612]	415	#print msg
[1614]	416	asaplog.push(msg)
	417	print_log('ERROR')
[723]	418	return
	419	else:
	420	raise RuntimeError(msg)
[113]	421	pars = list(self.fitter.getparameters())
	422	fixed = list(self.fitter.getfixedparameters())
[1075]	423	errs = list(self.fitter.geterrors())
[1039]	424	area = []
[723]	425	if component is not None:
[1701]	426	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[515]	427	i = 3*component
	428	cpars = pars[i:i+3]
	429	cfixed = fixed[i:i+3]
[1075]	430	cerrs = errs[i:i+3]
[1039]	431	a = self.get_area(component)
	432	area = [a for i in range(3)]
[515]	433	else:
	434	cpars = pars
[723]	435	cfixed = fixed
[1075]	436	cerrs = errs
[515]	437	else:
	438	cpars = pars
	439	cfixed = fixed
[1075]	440	cerrs = errs
[1701]	441	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[1039]	442	for c in range(len(self.components)):
	443	a = self.get_area(c)
	444	area += [a for i in range(3)]
[1088]	445	fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
[723]	446	if rcParams['verbose']:
[1612]	447	#print fpars
[1614]	448	asaplog.push(fpars)
	449	print_log()
[1075]	450	return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
	451	'errors':cerrs}
[723]	452
[1075]	453	def _format_pars(self, pars, fixed, errors, area):
[113]	454	out = ''
	455	if self.fitfunc == 'poly':
	456	c = 0
[515]	457	for i in range(len(pars)):
	458	fix = ""
[1232]	459	if len(fixed) and fixed[i]: fix = "(fixed)"
[1088]	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])
[113]	464	c+=1
[515]	465	out = out[:-1] # remove trailing ','
[1701]	466	elif self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
[113]	467	i = 0
	468	c = 0
[515]	469	aunit = ''
	470	ounit = ''
[113]	471	if self.data:
[515]	472	aunit = self.data.get_unit()
	473	ounit = self.data.get_fluxunit()
[113]	474	while i < len(pars):
[1039]	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)
[1017]	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)
[113]	479	c+=1
	480	i+=3
	481	return out
[723]	482
[113]	483	def get_estimate(self):
	484	"""
[515]	485	Return the parameter estimates (for non-linear functions).
[113]	486	"""
	487	pars = self.fitter.getestimate()
[943]	488	fixed = self.fitter.getfixedparameters()
[723]	489	if rcParams['verbose']:
[1612]	490	#print self._format_pars(pars,fixed,None)
[1614]	491	asaplog.push(self._format_pars(pars,fixed,None))
	492	print_log()
[113]	493	return pars
	494
	495	def get_residual(self):
	496	"""
	497	Return the residual of the fit.
	498	"""
	499	if not self.fitted:
[723]	500	msg = "Not yet fitted."
	501	if rcParams['verbose']:
[1612]	502	#print msg
[1614]	503	asaplog.push(msg)
	504	print_log('ERROR')
[723]	505	return
	506	else:
	507	raise RuntimeError(msg)
[113]	508	return self.fitter.getresidual()
	509
	510	def get_chi2(self):
	511	"""
	512	Return chi^2.
	513	"""
	514	if not self.fitted:
[723]	515	msg = "Not yet fitted."
	516	if rcParams['verbose']:
[1612]	517	#print msg
[1614]	518	asaplog.push(msg)
	519	print_log('ERROR')
[723]	520	return
	521	else:
	522	raise RuntimeError(msg)
[113]	523	ch2 = self.fitter.getchi2()
[723]	524	if rcParams['verbose']:
[1612]	525	#print 'Chi^2 = %3.3f' % (ch2)
[1614]	526	asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
	527	print_log()
[723]	528	return ch2
[113]	529
	530	def get_fit(self):
	531	"""
	532	Return the fitted ordinate values.
	533	"""
	534	if not self.fitted:
[723]	535	msg = "Not yet fitted."
	536	if rcParams['verbose']:
[1612]	537	#print msg
[1614]	538	asaplog.push(msg)
	539	print_log('ERROR')
[723]	540	return
	541	else:
	542	raise RuntimeError(msg)
[113]	543	return self.fitter.getfit()
	544
	545	def commit(self):
	546	"""
[526]	547	Return a new scan where the fits have been commited (subtracted)
[113]	548	"""
	549	if not self.fitted:
[723]	550	msg = "Not yet fitted."
	551	if rcParams['verbose']:
[1612]	552	#print msg
[1614]	553	asaplog.push(msg)
	554	print_log('ERROR')
[723]	555	return
	556	else:
	557	raise RuntimeError(msg)
[975]	558	from asap import scantable
	559	if not isinstance(self.data, scantable):
[723]	560	msg = "Not a scantable"
	561	if rcParams['verbose']:
[1612]	562	#print msg
[1614]	563	asaplog.push(msg)
	564	print_log('ERROR')
[723]	565	return
	566	else:
	567	raise TypeError(msg)
[113]	568	scan = self.data.copy()
[259]	569	scan._setspectrum(self.fitter.getresidual())
[723]	570	print_log()
[1092]	571	return scan
[113]	572
[723]	573	def plot(self, residual=False, components=None, plotparms=False, filename=None):
[113]	574	"""
	575	Plot the last fit.
	576	Parameters:
	577	residual: an optional parameter indicating if the residual
	578	should be plotted (default 'False')
[526]	579	components: a list of components to plot, e.g [0,1],
	580	-1 plots the total fit. Default is to only
	581	plot the total fit.
	582	plotparms: Inidicates if the parameter values should be present
	583	on the plot
[113]	584	"""
	585	if not self.fitted:
	586	return
[723]	587	if not self._p or self._p.is_dead:
	588	if rcParams['plotter.gui']:
	589	from asap.asaplotgui import asaplotgui as asaplot
	590	else:
	591	from asap.asaplot import asaplot
	592	self._p = asaplot()
	593	self._p.hold()
[113]	594	self._p.clear()
[515]	595	self._p.set_panels()
[652]	596	self._p.palette(0)
[113]	597	tlab = 'Spectrum'
[723]	598	xlab = 'Abcissa'
[1017]	599	ylab = 'Ordinate'
[1273]	600	from matplotlib.numerix import ma,logical_not,logical_and,array
	601	m = self.mask
[113]	602	if self.data:
[515]	603	tlab = self.data._getsourcename(self._fittedrow)
	604	xlab = self.data._getabcissalabel(self._fittedrow)
[1273]	605	m = logical_and(self.mask,
[1306]	606	array(self.data._getmask(self._fittedrow),
	607	copy=False))
[1389]	608
[626]	609	ylab = self.data._get_ordinate_label()
[515]	610
[1075]	611	colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
[1461]	612	nomask=True
	613	for i in range(len(m)):
	614	nomask = nomask and m[i]
	615	label0='Masked Region'
	616	label1='Spectrum'
	617	if ( nomask ):
	618	label0=label1
	619	else:
	620	y = ma.masked_array( self.y, mask = m )
	621	self._p.palette(1,colours)
	622	self._p.set_line( label = label1 )
	623	self._p.plot( self.x, y )
[652]	624	self._p.palette(0,colours)
[1461]	625	self._p.set_line(label=label0)
[1273]	626	y = ma.masked_array(self.y,mask=logical_not(m))
[1088]	627	self._p.plot(self.x, y)
[113]	628	if residual:
[1461]	629	self._p.palette(7)
[515]	630	self._p.set_line(label='Residual')
[1116]	631	y = ma.masked_array(self.get_residual(),
[1273]	632	mask=logical_not(m))
[1088]	633	self._p.plot(self.x, y)
[652]	634	self._p.palette(2)
[515]	635	if components is not None:
	636	cs = components
	637	if isinstance(components,int): cs = [components]
[526]	638	if plotparms:
[1031]	639	self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
[515]	640	n = len(self.components)
[652]	641	self._p.palette(3)
[515]	642	for c in cs:
	643	if 0 <= c < n:
	644	lab = self.fitfuncs[c]+str(c)
	645	self._p.set_line(label=lab)
[1116]	646	y = ma.masked_array(self.fitter.evaluate(c),
[1273]	647	mask=logical_not(m))
[1088]	648
	649	self._p.plot(self.x, y)
[515]	650	elif c == -1:
[652]	651	self._p.palette(2)
[515]	652	self._p.set_line(label="Total Fit")
[1116]	653	y = ma.masked_array(self.fitter.getfit(),
[1273]	654	mask=logical_not(m))
[1088]	655	self._p.plot(self.x, y)
[515]	656	else:
[652]	657	self._p.palette(2)
[515]	658	self._p.set_line(label='Fit')
[1116]	659	y = ma.masked_array(self.fitter.getfit(),
[1273]	660	mask=logical_not(m))
[1088]	661	self._p.plot(self.x, y)
[723]	662	xlim=[min(self.x),max(self.x)]
	663	self._p.axes.set_xlim(xlim)
[113]	664	self._p.set_axes('xlabel',xlab)
	665	self._p.set_axes('ylabel',ylab)
	666	self._p.set_axes('title',tlab)
	667	self._p.release()
[723]	668	if (not rcParams['plotter.gui']):
	669	self._p.save(filename)
	670	print_log()
[113]	671
[1061]	672	def auto_fit(self, insitu=None, plot=False):
[113]	673	"""
[515]	674	Return a scan where the function is applied to all rows for
	675	all Beams/IFs/Pols.
[723]	676
[113]	677	"""
	678	from asap import scantable
[515]	679	if not isinstance(self.data, scantable) :
[723]	680	msg = "Data is not a scantable"
	681	if rcParams['verbose']:
[1612]	682	#print msg
[1614]	683	asaplog.push(msg)
	684	print_log('ERROR')
[723]	685	return
	686	else:
	687	raise TypeError(msg)
[259]	688	if insitu is None: insitu = rcParams['insitu']
	689	if not insitu:
	690	scan = self.data.copy()
	691	else:
	692	scan = self.data
[880]	693	rows = xrange(scan.nrow())
[1446]	694	# Save parameters of baseline fits as a class attribute.
	695	# NOTICE: This does not reflect changes in scantable!
	696	if len(rows) > 0: self.blpars=[]
[876]	697	asaplog.push("Fitting:")
	698	for r in rows:
[1603]	699	out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),
	700	scan.getbeam(r),
	701	scan.getif(r),
	702	scan.getpol(r),
	703	scan.getcycle(r))
[880]	704	asaplog.push(out, False)
[876]	705	self.x = scan._getabcissa(r)
	706	self.y = scan._getspectrum(r)
[1603]	707	self.mask = mask_and(self.mask, scan._getmask(r))
[876]	708	self.data = None
	709	self.fit()
[1603]	710	x = self.get_parameters()
[1446]	711	fpar = self.get_parameters()
[1061]	712	if plot:
	713	self.plot(residual=True)
	714	x = raw_input("Accept fit ([y]/n): ")
	715	if x.upper() == 'N':
[1446]	716	self.blpars.append(None)
[1061]	717	continue
[880]	718	scan._setspectrum(self.fitter.getresidual(), r)
[1446]	719	self.blpars.append(fpar)
[1061]	720	if plot:
	721	self._p.unmap()
	722	self._p = None
[876]	723	print_log()
	724	return scan
[794]	725

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