Context Navigation

source: trunk/python/asapfitter.py@ 2062

Visit:

Last change on this file since 2062 was 2047, checked in by WataruKawasaki, 14 years ago

New Development: Yes

JIRA Issue: Yes CAS-2847

Ready for Test: Yes

Interface Changes: No

What Interface Changed:

Test Programs:

Put in Release Notes: Yes

Module(s): scantable

Description: added {auto_}sinusoid_baseline() for sinusoidal baseline fitting. also minor bug fixes for asapfitter.

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

File size: 25.1 KB

Rev	Line
[113]	1	import _asap
[1826]	2	from asap.parameters import rcParams
[1862]	3	from asap.logging import asaplog, asaplog_post_dec
[1826]	4	from asap.utils import _n_bools, mask_and
[113]	5
[1826]	6
[113]	7	class fitter:
	8	"""
	9	The fitting class for ASAP.
	10	"""
	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
[1391]	27	self.uselinear = False
[113]	28
	29	def set_data(self, xdat, ydat, mask=None):
	30	"""
[158]	31	Set the absissa and ordinate for the fit. Also set the mask
[113]	32	indicationg valid points.
	33	This can be used for data vectors retrieved from a scantable.
	34	For scantable fitting use 'fitter.set_scan(scan, mask)'.
	35	Parameters:
[158]	36	xdat: the abcissa values
[113]	37	ydat: the ordinate values
	38	mask: an optional mask
[723]	39
[113]	40	"""
	41	self.fitted = False
	42	self.x = xdat
	43	self.y = ydat
	44	if mask == None:
[1295]	45	self.mask = _n_bools(len(xdat), True)
[113]	46	else:
	47	self.mask = mask
	48	return
	49
[1862]	50	@asaplog_post_dec
[113]	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
[1420]	56	mask: a msk retrieved from the scantable
[113]	57	"""
	58	if not thescan:
[723]	59	msg = "Please give a correct scan"
[1859]	60	raise TypeError(msg)
[113]	61	self.fitted = False
	62	self.data = thescan
[1075]	63	self.mask = None
[113]	64	if mask is None:
[1295]	65	self.mask = _n_bools(self.data.nchan(), True)
[113]	66	else:
	67	self.mask = mask
	68	return
	69
[1862]	70	@asaplog_post_dec
[113]	71	def set_function(self, **kwargs):
	72	"""
	73	Set the function to be fit.
	74	Parameters:
[2047]	75	poly: use a polynomial of the order given with nonlinear least squares fit
	76	lpoly: use polynomial of the order given with linear least squares fit
	77	gauss: fit the number of gaussian specified
	78	lorentz: fit the number of lorentzian specified
	79	sinusoid: fit the number of sinusoid specified
[113]	80	Example:
[1391]	81	fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method
	82	fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method
[1819]	83	fitter.set_function(gauss=2) # will fit two gaussians
	84	fitter.set_function(lorentz=2) # will fit two lorentzians
[2047]	85	fitter.set_function(sinusoid=3) # will fit three sinusoids
[113]	86	"""
[723]	87	#default poly order 0
[515]	88	n=0
[113]	89	if kwargs.has_key('poly'):
	90	self.fitfunc = 'poly'
[1938]	91	self.fitfuncs = ['poly']
[113]	92	n = kwargs.get('poly')
[1938]	93	self.components = [n+1]
[1589]	94	self.uselinear = False
[1391]	95	elif kwargs.has_key('lpoly'):
	96	self.fitfunc = 'poly'
[1938]	97	self.fitfuncs = ['lpoly']
[1391]	98	n = kwargs.get('lpoly')
[1938]	99	self.components = [n+1]
[1391]	100	self.uselinear = True
[113]	101	elif kwargs.has_key('gauss'):
	102	n = kwargs.get('gauss')
	103	self.fitfunc = 'gauss'
[515]	104	self.fitfuncs = [ 'gauss' for i in range(n) ]
	105	self.components = [ 3 for i in range(n) ]
[1589]	106	self.uselinear = False
[1819]	107	elif kwargs.has_key('lorentz'):
	108	n = kwargs.get('lorentz')
	109	self.fitfunc = 'lorentz'
	110	self.fitfuncs = [ 'lorentz' for i in range(n) ]
	111	self.components = [ 3 for i in range(n) ]
	112	self.uselinear = False
[2047]	113	elif kwargs.has_key('sinusoid'):
	114	n = kwargs.get('sinusoid')
	115	self.fitfunc = 'sinusoid'
	116	self.fitfuncs = [ 'sinusoid' for i in range(n) ]
	117	self.components = [ 3 for i in range(n) ]
	118	self.uselinear = False
[515]	119	else:
[723]	120	msg = "Invalid function type."
[1859]	121	raise TypeError(msg)
[723]	122
[113]	123	self.fitter.setexpression(self.fitfunc,n)
[1232]	124	self.fitted = False
[113]	125	return
[723]	126
[1862]	127	@asaplog_post_dec
[1075]	128	def fit(self, row=0, estimate=False):
[113]	129	"""
	130	Execute the actual fitting process. All the state has to be set.
	131	Parameters:
[1075]	132	row: specify the row in the scantable
	133	estimate: auto-compute an initial parameter set (default False)
	134	This can be used to compute estimates even if fit was
	135	called before.
[113]	136	Example:
[515]	137	s = scantable('myscan.asap')
	138	s.set_cursor(thepol=1) # select second pol
[113]	139	f = fitter()
	140	f.set_scan(s)
	141	f.set_function(poly=0)
[723]	142	f.fit(row=0) # fit first row
[113]	143	"""
	144	if ((self.x is None or self.y is None) and self.data is None) \
	145	or self.fitfunc is None:
[723]	146	msg = "Fitter not yet initialised. Please set data & fit function"
[1859]	147	raise RuntimeError(msg)
[723]	148
[113]	149	else:
	150	if self.data is not None:
[515]	151	self.x = self.data._getabcissa(row)
	152	self.y = self.data._getspectrum(row)
[1536]	153	self.mask = mask_and(self.mask, self.data._getmask(row))
[723]	154	asaplog.push("Fitting:")
[943]	155	i = row
[1536]	156	out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i),
	157	self.data.getbeam(i),
	158	self.data.getif(i),
[1589]	159	self.data.getpol(i),
[1536]	160	self.data.getcycle(i))
[1075]	161	asaplog.push(out,False)
[515]	162	self.fitter.setdata(self.x, self.y, self.mask)
[1819]	163	if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
[113]	164	ps = self.fitter.getparameters()
[1075]	165	if len(ps) == 0 or estimate:
[113]	166	self.fitter.estimate()
[1859]	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."
[515]	176	self._fittedrow = row
[113]	177	self.fitted = True
	178	return
	179
[1232]	180	def store_fit(self, filename=None):
[526]	181	"""
[1232]	182	Save the fit parameters.
	183	Parameters:
	184	filename: if specified save as an ASCII file, if None (default)
	185	store it in the scnatable
[526]	186	"""
[515]	187	if self.fitted and self.data is not None:
	188	pars = list(self.fitter.getparameters())
	189	fixed = list(self.fitter.getfixedparameters())
[975]	190	from asap.asapfit import asapfit
	191	fit = asapfit()
	192	fit.setparameters(pars)
	193	fit.setfixedparameters(fixed)
	194	fit.setfunctions(self.fitfuncs)
	195	fit.setcomponents(self.components)
	196	fit.setframeinfo(self.data._getcoordinfo())
[1232]	197	if filename is not None:
	198	import os
	199	filename = os.path.expandvars(os.path.expanduser(filename))
	200	if os.path.exists(filename):
	201	raise IOError("File '%s' exists." % filename)
	202	fit.save(filename)
	203	else:
	204	self.data._addfit(fit,self._fittedrow)
[515]	205
[1862]	206	@asaplog_post_dec
[1017]	207	def set_parameters(self,args,*kwargs):
[526]	208	"""
	209	Set the parameters to be fitted.
	210	Parameters:
	211	params: a vector of parameters
	212	fixed: a vector of which parameters are to be held fixed
	213	(default is none)
[2047]	214	component: in case of multiple gaussians/lorentzians/sinusoidals,
	215	the index of the target component
[1017]	216	"""
	217	component = None
	218	fixed = None
	219	params = None
[1031]	220
[1017]	221	if len(args) and isinstance(args[0],dict):
	222	kwargs = args[0]
	223	if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
	224	if kwargs.has_key("params"): params = kwargs["params"]
	225	if len(args) == 2 and isinstance(args[1], int):
	226	component = args[1]
[515]	227	if self.fitfunc is None:
[723]	228	msg = "Please specify a fitting function first."
[1859]	229	raise RuntimeError(msg)
[2047]	230	if (self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid") and component is not None:
[1017]	231	if not self.fitted and sum(self.fitter.getparameters()) == 0:
[1295]	232	pars = _n_bools(len(self.components)*3, False)
[2047]	233	fxd = _n_bools(len(pars), False)
[515]	234	else:
[723]	235	pars = list(self.fitter.getparameters())
[2047]	236	fxd = list(self.fitter.getfixedparameters())
[515]	237	i = 3*component
	238	pars[i:i+3] = params
[2047]	239	fxd[i:i+3] = fixed
[515]	240	params = pars
[2047]	241	fixed = fxd
[113]	242	self.fitter.setparameters(params)
	243	if fixed is not None:
	244	self.fitter.setfixedparameters(fixed)
	245	return
[515]	246
[1862]	247	@asaplog_post_dec
[1217]	248	def set_gauss_parameters(self, peak, centre, fwhm,
[1409]	249	peakfixed=0, centrefixed=0,
[1217]	250	fwhmfixed=0,
[515]	251	component=0):
[113]	252	"""
[515]	253	Set the Parameters of a 'Gaussian' component, set with set_function.
	254	Parameters:
[1232]	255	peak, centre, fwhm: The gaussian parameters
[515]	256	peakfixed,
[1409]	257	centrefixed,
[1217]	258	fwhmfixed: Optional parameters to indicate if
[515]	259	the paramters should be held fixed during
	260	the fitting process. The default is to keep
	261	all parameters flexible.
[526]	262	component: The number of the component (Default is the
	263	component 0)
[515]	264	"""
	265	if self.fitfunc != "gauss":
[723]	266	msg = "Function only operates on Gaussian components."
[1859]	267	raise ValueError(msg)
[515]	268	if 0 <= component < len(self.components):
[1217]	269	d = {'params':[peak, centre, fwhm],
[1409]	270	'fixed':[peakfixed, centrefixed, fwhmfixed]}
[1017]	271	self.set_parameters(d, component)
[515]	272	else:
[723]	273	msg = "Please select a valid component."
[1859]	274	raise ValueError(msg)
[723]	275
[1862]	276	@asaplog_post_dec
[1819]	277	def set_lorentz_parameters(self, peak, centre, fwhm,
	278	peakfixed=0, centrefixed=0,
	279	fwhmfixed=0,
	280	component=0):
	281	"""
	282	Set the Parameters of a 'Lorentzian' component, set with set_function.
	283	Parameters:
[1927]	284	peak, centre, fwhm: The lorentzian parameters
[1819]	285	peakfixed,
	286	centrefixed,
	287	fwhmfixed: Optional parameters to indicate if
	288	the paramters should be held fixed during
	289	the fitting process. The default is to keep
	290	all parameters flexible.
	291	component: The number of the component (Default is the
	292	component 0)
	293	"""
	294	if self.fitfunc != "lorentz":
	295	msg = "Function only operates on Lorentzian components."
[1859]	296	raise ValueError(msg)
[1819]	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."
[1859]	303	raise ValueError(msg)
[1819]	304
[2047]	305	@asaplog_post_dec
	306	def set_sinusoid_parameters(self, ampl, period, x0,
	307	amplfixed=0, periodfixed=0,
	308	x0fixed=0,
	309	component=0):
	310	"""
	311	Set the Parameters of a 'Sinusoidal' component, set with set_function.
	312	Parameters:
	313	ampl, period, x0: The sinusoidal parameters
	314	amplfixed,
	315	periodfixed,
	316	x0fixed: Optional parameters to indicate if
	317	the paramters should be held fixed during
	318	the fitting process. The default is to keep
	319	all parameters flexible.
	320	component: The number of the component (Default is the
	321	component 0)
	322	"""
	323	if self.fitfunc != "sinusoid":
	324	msg = "Function only operates on Sinusoidal components."
	325	raise ValueError(msg)
	326	if 0 <= component < len(self.components):
	327	d = {'params':[ampl, period, x0],
	328	'fixed': [amplfixed, periodfixed, x0fixed]}
	329	self.set_parameters(d, component)
	330	else:
	331	msg = "Please select a valid component."
	332	raise ValueError(msg)
	333
[975]	334	def get_area(self, component=None):
	335	"""
[1819]	336	Return the area under the fitted gaussian/lorentzian component.
[975]	337	Parameters:
[1819]	338	component: the gaussian/lorentzian component selection,
[975]	339	default (None) is the sum of all components
	340	Note:
[1819]	341	This will only work for gaussian/lorentzian fits.
[975]	342	"""
	343	if not self.fitted: return
[1819]	344	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[975]	345	pars = list(self.fitter.getparameters())
	346	from math import log,pi,sqrt
[1819]	347	if self.fitfunc == "gauss":
	348	fac = sqrt(pi/log(16.0))
	349	elif self.fitfunc == "lorentz":
	350	fac = pi/2.0
[975]	351	areas = []
	352	for i in range(len(self.components)):
	353	j = i*3
	354	cpars = pars[j:j+3]
	355	areas.append(fac * cpars[0] * cpars[2])
	356	else:
	357	return None
	358	if component is not None:
	359	return areas[component]
	360	else:
	361	return sum(areas)
	362
[1862]	363	@asaplog_post_dec
[1075]	364	def get_errors(self, component=None):
[515]	365	"""
[1075]	366	Return the errors in the parameters.
	367	Parameters:
	368	component: get the errors for the specified component
	369	only, default is all components
	370	"""
	371	if not self.fitted:
	372	msg = "Not yet fitted."
[1859]	373	raise RuntimeError(msg)
[1075]	374	errs = list(self.fitter.geterrors())
	375	cerrs = errs
	376	if component is not None:
[2047]	377	if self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid":
[1075]	378	i = 3*component
	379	if i < len(errs):
	380	cerrs = errs[i:i+3]
	381	return cerrs
	382
[1859]	383
[1862]	384	@asaplog_post_dec
[1075]	385	def get_parameters(self, component=None, errors=False):
	386	"""
[113]	387	Return the fit paramters.
[526]	388	Parameters:
	389	component: get the parameters for the specified component
	390	only, default is all components
[113]	391	"""
	392	if not self.fitted:
[723]	393	msg = "Not yet fitted."
[1859]	394	raise RuntimeError(msg)
[113]	395	pars = list(self.fitter.getparameters())
	396	fixed = list(self.fitter.getfixedparameters())
[1075]	397	errs = list(self.fitter.geterrors())
[1039]	398	area = []
[723]	399	if component is not None:
[2047]	400	if self.fitfunc == "poly" or self.fitfunc == "lpoly":
	401	cpars = pars
	402	cfixed = fixed
	403	cerrs = errs
	404	else:
[515]	405	i = 3*component
	406	cpars = pars[i:i+3]
	407	cfixed = fixed[i:i+3]
[1075]	408	cerrs = errs[i:i+3]
[2047]	409	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
	410	a = self.get_area(component)
	411	area = [a for i in range(3)]
[515]	412	else:
	413	cpars = pars
	414	cfixed = fixed
[1075]	415	cerrs = errs
[1819]	416	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
[1039]	417	for c in range(len(self.components)):
[2047]	418	a = self.get_area(c)
	419	area += [a for i in range(3)]
[1088]	420	fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
[1859]	421	asaplog.push(fpars)
[1075]	422	return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
	423	'errors':cerrs}
[723]	424
[1075]	425	def _format_pars(self, pars, fixed, errors, area):
[113]	426	out = ''
[2047]	427	if self.fitfunc == "poly" or self.fitfunc == "lpoly":
[113]	428	c = 0
[515]	429	for i in range(len(pars)):
	430	fix = ""
[1232]	431	if len(fixed) and fixed[i]: fix = "(fixed)"
[2047]	432	out += " p%d%s= %3.6f" % (c, fix, pars[i])
	433	if errors : out += " (%1.6f)" % errors[i]
	434	out += ","
[113]	435	c+=1
[515]	436	out = out[:-1] # remove trailing ','
[2047]	437	else:
[113]	438	i = 0
	439	c = 0
[2047]	440	if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
	441	pnam = ["peak", "centre", "FWHM"]
	442	elif self.fitfunc == "sinusoid":
	443	pnam = ["amplitude", "period", "x0"]
	444	aunit = ""
	445	ounit = ""
[113]	446	if self.data:
[515]	447	aunit = self.data.get_unit()
	448	ounit = self.data.get_fluxunit()
[113]	449	while i < len(pars):
[2047]	450	fix0 = fix1 = fix2 = ""
	451	if i < len(fixed)-2:
	452	if fixed[i]: fix0 = "(fixed)"
	453	if fixed[i+1]: fix1 = "(fixed)"
	454	if fixed[i+2]: fix2 = "(fixed)"
	455	out += " %2d: " % c
	456	out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit)
	457	out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit)
	458	out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit)
	459	if len(area): out += " area = %3.3f %s %s\n" % (area[i], ounit, aunit)
[113]	460	c+=1
	461	i+=3
	462	return out
[723]	463
[1859]	464
[1862]	465	@asaplog_post_dec
[113]	466	def get_estimate(self):
	467	"""
[515]	468	Return the parameter estimates (for non-linear functions).
[113]	469	"""
	470	pars = self.fitter.getestimate()
[943]	471	fixed = self.fitter.getfixedparameters()
[1927]	472	asaplog.push(self._format_pars(pars,fixed,None,None))
[113]	473	return pars
	474
[1862]	475	@asaplog_post_dec
[113]	476	def get_residual(self):
	477	"""
	478	Return the residual of the fit.
	479	"""
	480	if not self.fitted:
[723]	481	msg = "Not yet fitted."
[1859]	482	raise RuntimeError(msg)
[113]	483	return self.fitter.getresidual()
	484
[1862]	485	@asaplog_post_dec
[113]	486	def get_chi2(self):
	487	"""
	488	Return chi^2.
	489	"""
	490	if not self.fitted:
[723]	491	msg = "Not yet fitted."
[1859]	492	raise RuntimeError(msg)
[113]	493	ch2 = self.fitter.getchi2()
[1859]	494	asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
[723]	495	return ch2
[113]	496
[1862]	497	@asaplog_post_dec
[113]	498	def get_fit(self):
	499	"""
	500	Return the fitted ordinate values.
	501	"""
	502	if not self.fitted:
[723]	503	msg = "Not yet fitted."
[1859]	504	raise RuntimeError(msg)
[113]	505	return self.fitter.getfit()
	506
[1862]	507	@asaplog_post_dec
[113]	508	def commit(self):
	509	"""
[526]	510	Return a new scan where the fits have been commited (subtracted)
[113]	511	"""
	512	if not self.fitted:
[723]	513	msg = "Not yet fitted."
[1859]	514	raise RuntimeError(msg)
[975]	515	from asap import scantable
	516	if not isinstance(self.data, scantable):
[723]	517	msg = "Not a scantable"
[1859]	518	raise TypeError(msg)
[113]	519	scan = self.data.copy()
[259]	520	scan._setspectrum(self.fitter.getresidual())
[1092]	521	return scan
[113]	522
[1862]	523	@asaplog_post_dec
[1689]	524	def plot(self, residual=False, components=None, plotparms=False,
	525	filename=None):
[113]	526	"""
	527	Plot the last fit.
	528	Parameters:
	529	residual: an optional parameter indicating if the residual
	530	should be plotted (default 'False')
[526]	531	components: a list of components to plot, e.g [0,1],
	532	-1 plots the total fit. Default is to only
	533	plot the total fit.
	534	plotparms: Inidicates if the parameter values should be present
	535	on the plot
[113]	536	"""
	537	if not self.fitted:
	538	return
[723]	539	if not self._p or self._p.is_dead:
	540	if rcParams['plotter.gui']:
	541	from asap.asaplotgui import asaplotgui as asaplot
	542	else:
	543	from asap.asaplot import asaplot
	544	self._p = asaplot()
	545	self._p.hold()
[113]	546	self._p.clear()
[515]	547	self._p.set_panels()
[652]	548	self._p.palette(0)
[113]	549	tlab = 'Spectrum'
[723]	550	xlab = 'Abcissa'
[1017]	551	ylab = 'Ordinate'
[1739]	552	from numpy import ma,logical_not,logical_and,array
[1273]	553	m = self.mask
[113]	554	if self.data:
[515]	555	tlab = self.data._getsourcename(self._fittedrow)
	556	xlab = self.data._getabcissalabel(self._fittedrow)
[1273]	557	m = logical_and(self.mask,
[1306]	558	array(self.data._getmask(self._fittedrow),
	559	copy=False))
[1589]	560
[626]	561	ylab = self.data._get_ordinate_label()
[515]	562
[1075]	563	colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
[1819]	564	nomask=True
	565	for i in range(len(m)):
	566	nomask = nomask and m[i]
	567	label0='Masked Region'
	568	label1='Spectrum'
	569	if ( nomask ):
	570	label0=label1
	571	else:
	572	y = ma.masked_array( self.y, mask = m )
	573	self._p.palette(1,colours)
	574	self._p.set_line( label = label1 )
	575	self._p.plot( self.x, y )
[652]	576	self._p.palette(0,colours)
[1819]	577	self._p.set_line(label=label0)
[1273]	578	y = ma.masked_array(self.y,mask=logical_not(m))
[1088]	579	self._p.plot(self.x, y)
[113]	580	if residual:
[1819]	581	self._p.palette(7)
[515]	582	self._p.set_line(label='Residual')
[1116]	583	y = ma.masked_array(self.get_residual(),
[1273]	584	mask=logical_not(m))
[1088]	585	self._p.plot(self.x, y)
[652]	586	self._p.palette(2)
[515]	587	if components is not None:
	588	cs = components
	589	if isinstance(components,int): cs = [components]
[526]	590	if plotparms:
[1031]	591	self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
[515]	592	n = len(self.components)
[652]	593	self._p.palette(3)
[515]	594	for c in cs:
	595	if 0 <= c < n:
	596	lab = self.fitfuncs[c]+str(c)
	597	self._p.set_line(label=lab)
[1116]	598	y = ma.masked_array(self.fitter.evaluate(c),
[1273]	599	mask=logical_not(m))
[1088]	600
	601	self._p.plot(self.x, y)
[515]	602	elif c == -1:
[652]	603	self._p.palette(2)
[515]	604	self._p.set_line(label="Total Fit")
[1116]	605	y = ma.masked_array(self.fitter.getfit(),
[1273]	606	mask=logical_not(m))
[1088]	607	self._p.plot(self.x, y)
[515]	608	else:
[652]	609	self._p.palette(2)
[515]	610	self._p.set_line(label='Fit')
[1116]	611	y = ma.masked_array(self.fitter.getfit(),
[1273]	612	mask=logical_not(m))
[1088]	613	self._p.plot(self.x, y)
[723]	614	xlim=[min(self.x),max(self.x)]
	615	self._p.axes.set_xlim(xlim)
[113]	616	self._p.set_axes('xlabel',xlab)
	617	self._p.set_axes('ylabel',ylab)
	618	self._p.set_axes('title',tlab)
	619	self._p.release()
[723]	620	if (not rcParams['plotter.gui']):
	621	self._p.save(filename)
[113]	622
[1862]	623	@asaplog_post_dec
[1061]	624	def auto_fit(self, insitu=None, plot=False):
[113]	625	"""
[515]	626	Return a scan where the function is applied to all rows for
	627	all Beams/IFs/Pols.
[723]	628
[113]	629	"""
	630	from asap import scantable
[515]	631	if not isinstance(self.data, scantable) :
[723]	632	msg = "Data is not a scantable"
[1859]	633	raise TypeError(msg)
[259]	634	if insitu is None: insitu = rcParams['insitu']
	635	if not insitu:
	636	scan = self.data.copy()
	637	else:
	638	scan = self.data
[880]	639	rows = xrange(scan.nrow())
[1826]	640	# Save parameters of baseline fits as a class attribute.
[1819]	641	# NOTICE: This does not reflect changes in scantable!
	642	if len(rows) > 0: self.blpars=[]
[876]	643	asaplog.push("Fitting:")
	644	for r in rows:
[1536]	645	out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),
	646	scan.getbeam(r),
	647	scan.getif(r),
[1589]	648	scan.getpol(r),
[1536]	649	scan.getcycle(r))
[880]	650	asaplog.push(out, False)
[876]	651	self.x = scan._getabcissa(r)
	652	self.y = scan._getspectrum(r)
[1536]	653	self.mask = mask_and(self.mask, scan._getmask(r))
[876]	654	self.data = None
	655	self.fit()
	656	x = self.get_parameters()
[1819]	657	fpar = self.get_parameters()
[1061]	658	if plot:
	659	self.plot(residual=True)
	660	x = raw_input("Accept fit ([y]/n): ")
	661	if x.upper() == 'N':
[1819]	662	self.blpars.append(None)
[1061]	663	continue
[880]	664	scan._setspectrum(self.fitter.getresidual(), r)
[1819]	665	self.blpars.append(fpar)
[1061]	666	if plot:
	667	self._p.unmap()
	668	self._p = None
[876]	669	return scan

Note: See TracBrowser for help on using the repository browser.

Download in other formats: