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()