Available Functions as of v1.0 release -
- get_maggy( ): Convert the measurements of flux in magnitudes to maggies for use with kcorrect_python
- get_maggy_inv_var( ): Convert the magnitude errors to maggy inverse variances for use with kcorrect_python
- get_rest_mag( ): Convert the measured apparent magnitudes into rest-frame magnitudes using the catalogue data and output from kcorrect_python functions
- get_volume( ): Convert the survey area in square degrees and respective redshift of each data point into comoving volumes. So, estimate Vmax from Zmax values
- get_binned_phi( ): Bin and weigh galaxy counts per magnitude by 1/Vmax
- get_patch_centers( ): First, divide uniformly and randomly simulated data points over the survey area into equally distributed and equally sized patches
- get_patch_labels( ): Then, use the patch centers to label the survey data points by equally distributed and equally sized patches
- get_binned_phi_error( ): Finally, use the patch labels to compute the spatial variances of phi
- get_plot( ): Perform get_binned_phi() , get_patch_labels() and get_binned_phi_error() functions using only one composite function and visualise the luminsoity function
- filter_plot_by_colour( ): Study the luminosity function by colour properties by specifying the colour dichotomy
- SchechterMagModel( )
- DoubleSchechterMagModel( )
- get_gof( ): Estimate the goodness of the fit by the reduced chi square
- get_schechter_phi( ): Least square fit single Schechter function on data and plot
- get_double_schechter_phi( ): Least square fit double Schechter function on data and plot