def initialpars(self,parfilename):
### Deal with initial parameters from line input file
self.fitpars,self.fiterrors,self.parinfo,self.linecmts = joebvpfit.readpars(parfilename)
cfg.fitidx=joebvpfit.fitpix(self.wave, self.fitpars) #Set pixels for fit
cfg.wavegroups=[]
self.datamodel = LineParTableModel(self.fitpars,self.fiterrors,self.parinfo,linecmts=self.linecmts)
self.tableView.setModel(self.datamodel)
self.datamodel.updatedata(self.fitpars,self.fitpars,self.parinfo,self.linecmts)
def initialpars(self,parfilename):
### Deal with initial parameters from line input file
self.fitpars,self.fiterrors,self.parinfo,self.linecmts = joebvpfit.readpars(parfilename)
cfg.fitidx=joebvpfit.fitpix(self.wave, self.fitpars) #Set pixels for fit
cfg.wavegroups=[]
self.datamodel = LineParTableModel(self.fitpars,self.fiterrors,self.parinfo,linecmts=self.linecmts)
self.tableView.setModel(self.datamodel)
self.datamodel.updatedata(self.fitpars,self.fitpars,self.parinfo,self.linecmts)
def compose_model(spec,filelist,outfile):
'''
Generates full-model spectrum (XSpectrum1D) from a set of joebvp output files and writes out a file with the spectrum.
Parameters
----------
spec : string or XSpectrum1D
The spectrum to be fitted with the input lines
filelist : list of strings or str
This should be a list containing the names of VP input files or a string referring to a file simply
listing the input files.
See joebvpfit.readpars for details of file format
outfile : str
Name of model spectrum output file
'''
from joebvp import joebvpfit
### Deal with alternate input types
if isinstance(spec,str):
specobj = readspec(spec)
else:
specobj = spec
### Load essentials from spectrum
wave = specobj.wavelength.value
normsig=specobj.sig.value/specobj.co.value
cfg.wave = wave
### Concatenate all the parameter tables
concatenate_line_tables(filelist,outtablefile='compiledVPinputs.dat')
### Make the model!
fitpars, fiterrors, parinfo, linecmts = joebvpfit.readpars('compiledVPinputs.dat') # read this back in to load params
cfg.fitidx = joebvpfit.fitpix(wave, fitpars) # set the pixels in the line regions
model = joebvpfit.voigtfunc(wave,fitpars) # generate the Voigt profiles of all lines
### Instantiate XSpectrum1D object and write it out
outspec=XSpectrum1D.from_tuple((wave,model,normsig))
outspec.write_to_fits(outfile)
def batch_fit(spec, filelist, outparfile='.VP', outmodelfile='_VPmodel.fits', inspect=True, **kwargs):
"""
Takes a number of input files and fits the lines in them. The fitting algorithm will
be run until convergence for each input file. The program will then ask whether to run the failed
runs in GUI mode.
Parameters
----------
spec : string or XSpectrum1D
The spectrum to be fitted with the input lines
filelist : list of strings or str
This should be a list containing the names of VP input files or a string referring to a file simply
listing the input files.
See joebvpfit.readpars for details of file format
outparfile : str, optional
Suffix for output file for fitted line parameters.
outmodelfile: str, optional
Suffix for output fits file for fitted model as the 'flux'.
inspect : bool, optional
Whether to produce plots and model for inspection of individual parameter input files.
Default is True.
**kwargs : maxiter, itertol
These are fed on to the joebvp.fit_to_convergence() function
"""
if isinstance(spec,str):
spectofit = readspec(spec)
specfile = spectofit.filename
else:
spectofit = spec
specfile = cfg.filename
if isinstance(filelist, str):
lstarr=np.genfromtxt(filelist,dtype=None)
listofiles=lstarr.tolist()
if isinstance(listofiles,str): # In case 'listofiles' is only 1 file
listofiles=[listofiles]
else:
listofiles=filelist
wave=spectofit.wavelength.value
normflux=spectofit.flux.value/spectofit.co.value
normsig=spectofit.sig.value/spectofit.co.value
cfg.wave=wave
cfg.spectrum = spectofit # need this for defining bad pixels later
q_pass = 0
q_fail = 0
fails = [] # store failures filenames
for i,ff in enumerate(listofiles):
i += 1
fitpars, fiterrors, parinfo, linecmts = joebvpfit.readpars(ff)
cfg.wavegroups = []
try:
fitpars,fiterrors=joebvpfit.fit_to_convergence(wave,normflux,normsig,fitpars,parinfo, **kwargs)
print('VPmeasure: Fit converged:', ff)
paroutfilename = ff.split('.')[0] + outparfile
modeloutfilename = ff.split('.')[0] + outmodelfile
joebvpfit.writelinepars(fitpars, fiterrors, parinfo, specfile, paroutfilename, linecmts)
joebvpfit.writeVPmodel(modeloutfilename, wave, fitpars, normflux, normsig)
if inspect:
jbu.inspect_fits(paroutfilename, output=paroutfilename.split('.')[0]+"_inspect.pdf")
q_pass += 1
except:
print('VPmeasure: Fitting failed:', ff)
fails += [ff]
q_fail += 1
print("")
print("VPmeasure: {}/{} fits converged, {}/{} failed (see log for details).\n".format(q_pass, i, q_fail, i))
# ask whether run GUI mode on failures
if q_fail > 0:
print("VPmeasure: Failed runs are: {}\n".format(fails))
while True:
answer = raw_input("VPmeasure: Would you like to run the failed fits in GUI mode? (y/n): ")
if answer in ['y','n', 'yes','no']:
break
if answer in ['y', 'yes']:
for ff in fails:
go(spec, ff)
# Concatenate and create fits inspection files
concatenate_all(spectofit)
print("VPmeasure: Done.")
def inspect_fits(parfile,output='FitInspection.pdf',vlim=[-300,300]*u.km/u.s, **kwargs):
'''
Produce pdf of fitting results for quality check.
Parameters
----------
parfile : str
Name of the parameter file in the joebvp format
output : str,optional
Name of file to write stackplots output
vlim : Quantity array, optional
Velocity range of stackplots
e.g.: [-400,
Returns
-------
'''
from joebvp import joebvpfit
from matplotlib.backends.backend_pdf import PdfPages
llist = LineList('ISM')
pp=PdfPages(output)
#import pdb;
#pdb.set_trace()
all=abslines_from_VPfile(parfile,linelist=llist,**kwargs) # Instantiate AbsLine objects and make list
acl=abscomponents_from_abslines(all,vtoler=15.) # Instantiate AbsComponent objects from this list
fitpars,fiterrors,parinfo,linecmts = joebvpfit.readpars(parfile)
fullmodel=makevoigt.cosvoigt(all[0].analy['spec'].wavelength.value,fitpars)
### Make a stackplot for each component
for comp in acl:
fig=comp.stack_plot(ymnx=(-0.1,1.3),show=False,return_fig=True,vlim=vlim, tight_layout=True)
if (len(comp._abslines)<6):
numrow = len(comp._abslines)%6
else:
numrow = 6
height = numrow*1.0+0.5
fig.set_figheight(height)
if len(comp._abslines)<6:
fig.set_figwidth(5.)
else:
fig.set_figwidth(10.)
stackaxes = fig.axes
for i,ax in enumerate(stackaxes):
line = comp._abslines[i]
thesepars=[[line.wrest.value],[line.attrib['logN']],[line.attrib['b'].value],
[line.z],[line.attrib['vel'].value],[line.limits.vlim[0].value],[line.limits.vlim[1].value]]
try:
thismodel=makevoigt.cosvoigt(line.analy['spec'].wavelength.value,thesepars)
except:
ax.text(-100,0.05,'These pixels not used to fit this line')
continue
axlin=ax.get_lines()
veldat=axlin[0].get_data()[0]
ax.plot(veldat,fullmodel,color='red',alpha=0.8)
ax.plot(veldat,thismodel,color='purple',linestyle='dashed')
botbuf = 0.5/height
fig.subplots_adjust(bottom=botbuf,left=0.1,right=0.95,hspace=0.,wspace=0.35)
title=comp.name
fig.suptitle(title)
fig.savefig(pp,format='pdf')
plt.close(fig)
### Write out full model fits file
normflux = line.analy['spec'].flux/line.analy['spec'].co
normsig = line.analy['spec'].sig / line.analy['spec'].co
modeltab = Table([line.analy['spec'].wavelength.value, fullmodel, normflux, normsig], names=['wavelength', 'model', 'normflux', 'normsig'])
# modeltab.write(outfile, format='fits', overwrite=True)
dummycont = np.ones(len(normflux))
spec = XSpectrum1D.from_tuple((modeltab['wavelength'], modeltab['model'], modeltab['normsig'], dummycont))
spec.write_to_fits(output[:-4]+'.fits')
pp.close()
def batch_fit(spec, filelist, outparfile='.VP', outmodelfile='_VPmodel.fits', inspect=True, **kwargs):
"""
Takes a number of input files and fits the lines in them. The fitting algorithm will
be run until convergence for each input file. The program will then ask whether to run the failed
runs in GUI mode.
Parameters
----------
spec : string or XSpectrum1D
The spectrum to be fitted with the input lines
filelist : list of strings or str
This should be a list containing the names of VP input files or a string referring to a file simply
listing the input files.
See joebvpfit.readpars for details of file format
outparfile : str, optional
Suffix for output file for fitted line parameters.
outmodelfile: str, optional
Suffix for output fits file for fitted model as the 'flux'.
inspect : bool, optional
Whether to produce plots and model for inspection of individual parameter input files.
Default is True.
**kwargs : maxiter, itertol
These are fed on to the joebvp.fit_to_convergence() function
"""
if isinstance(spec,str):
spectofit = readspec(spec)
specfile = spectofit.filename
else:
spectofit = spec
specfile = cfg.filename
if isinstance(filelist, str):
lstarr=np.genfromtxt(filelist,dtype=None)
listofiles=lstarr.tolist()
if sum(1 for line in open(filelist)) == 1:
listofiles = [listofiles]
else:
listofiles=filelist
wave=spectofit.wavelength.value
normflux=spectofit.flux.value/spectofit.co.value
normsig=spectofit.sig.value/spectofit.co.value
cfg.wave=wave
cfg.spectrum = spectofit # need this for defining bad pixels later
q_pass = 0
q_fail = 0
fails = [] # store failures filenames
for i,ff in enumerate(listofiles):
if isinstance(ff,bytes):
ff = ff.decode()
i += 1
fitpars, fiterrors, parinfo, linecmts = joebvpfit.readpars(ff)
cfg.lsfs = []
cfg.fgs = []
cfg.wavegroups = []
cfg.wgidxs = []
cfg.uqwgidxs = []
try:
fitpars,fiterrors=joebvpfit.fit_to_convergence(wave,normflux,normsig,fitpars,parinfo, **kwargs)
print('VPmeasure: Fit converged:', ff)
paroutfilename = ff.split('.')[0] + outparfile
modeloutfilename = ff.split('.')[0] + outmodelfile
joebvpfit.writelinepars(fitpars, fiterrors, parinfo, specfile, paroutfilename, linecmts)
joebvpfit.writeVPmodel(modeloutfilename, wave, fitpars, normflux, normsig)
if inspect:
jbu.inspect_fits(paroutfilename, output=paroutfilename.split('.')[0]+"_inspect.pdf")
q_pass += 1
except:
print('VPmeasure: Fitting failed:', ff)
#import pdb; pdb.set_trace()
fails += [ff]
q_fail += 1
print("")
print("VPmeasure: {}/{} fits converged, {}/{} failed (see log for details).\n".format(q_pass, i, q_fail, i))
# ask whether run GUI mode on failures
if q_fail > 0:
print("VPmeasure: Failed runs are: {}\n".format(fails))
while True:
answer = input("VPmeasure: Would you like to run the failed fits in GUI mode? (y/n): ")
if answer in ['y','n', 'yes','no']:
break
if answer in ['y', 'yes']:
for ff in fails:
try:
go(spec, ff)
except:
raise ValueError('Spectrum/VP input failed to load in interactive mode.')
# Concatenate and create fits inspection files
concatenate_all(spectofit)
print("VPmeasure: Done.")