This project is in the early development stage.
Fit a model to a spectrum
$ python spec_fit.py --single_NV -k=0.870763 -z=2.235563 -c=1 -n=1e4 -p=1 -s=data/SDSS_spectra/spSpec-51993-0542-631.fit -o output/spSpec-51993-0542-631 -b=1e3
Fit a model with two-component Ly-alpha and CIV emission lines (-c=2)
$ python spec_fit.py --single_NV -k=0.870763 -z=2.235563 -c=2 -n=1e4 -p=1 -s=data/SDSS_spectra/spSpec-51993-0542-631.fit -o output/spSpec-51993-0542-631_c2 -b=1e3
Now load and plot the fit results:
(I suggest you run from an ipython --pylab session.)
>>> from quarum import powergauss >>> m = powergauss.PowerGaussMCMC.load('output/spSpec-51993-0542-631.mcmc') >>> m.plot_spectra(thin=m.len()/10)
Load and plot the 2-component fit results:
>>> m2 = powergauss.PowerGaussMCMC.load('output/spSpec-51993-0542-631_c2.mcmc') >>> m2.plot_spectra(thin=m2.len()/10)
Plot the joint distributions of widths and shifts for the Ly-alpha line:
>>> import margplot >>> al = margplot.marginal_plot([m.db.width_0[::100], m.db.vshift_0[::100]], color='k') >>> margplot.marginal_plot([m2.db.width_0[::100], m2.db.vshift_0[::100]], axeslist=al, color='b') >>> margplot.marginal_plot([m2.db.width_1[::100], m2.db.vshift_1[::100]], axeslist=al, color='g') >>> al[0].set_xlabel('Width (Ang)') >>> al[0].set_ylabel('V_Shift (km/s)')
If you aren't running from ipython --pylab, show the fits:
>>> import pylab >>> pylab.show()