Welcome to SuPyFit!

SuPyFit (Python Superfit) is a software for the spectral classification of Supernovae

Install

To install the software the user should download all the files and unzip the 30A.zip and 20A.zip files into a folder called "binnings".

To run the code for an individual object

To achieve this task the files needed are:

• Header_binnings.py
• error_routines.py
• SF_functions.py
• params.py
• run.py

In the params.py file there are three paths that the user should change.

• The "save_bin_path" to which the binned files will be saved.
• The "save_results_path" to which the results (a csv file and pdf images of the plots) will be saved.
• The "path" which is the location of the "binnings" folder.

In the run.py file the user should change the "original" path to be that of the object of interest.

Main SuPyFit function

In the run.py file we find the main function which looks like this:

all_parameter_space(redshift,extconstant,templates_sn_trunc,templates_gal_trunc, lam, resolution, n=2, plot=1, kind=kind, original=save_bin, path=path, save=save_results_path, show=show)

The inputs of the function are updated in the params.py file and are as follow:

• redshift: Can be an array or an individual number. These are the redshift values over which to optimize.
• templates_sn_trunc: truncated library of supernovae, aka: which SN types to look at when optimizing.
• templates_gal_trunc: truncated library of host galaxies, aka: which HG types to look at when optimizing.
• lam: lambda array over which to perform the fit. The default is from 3000 A to 10500 A.
• resolution: resolution at which to bin and perform the fit. The default is 20 A.
• n: this corresponds to the number of plots to show and save as a result.
• plot: either 1 or 0, to either plot or not plot.
• kind: corresponds to the type of error spectrum the user prefers, the options are 'SG':Savitsky Golay, 'linear': for obtaining the error of the spectrum by making linear fit every 10 points, and 'included': if the user wants to use the error that comes with the object itself. The default is 'SG'

The templates_sn_trunc and templates_sn_trunc are updated by changing the temp_gal_tr and temp_sn_tr lists on the params.py file, to what the user is interested in seeing (default is full library).

The rest the inputs correspond to the paths mentioned above.

Results

The results are: an astropy table that is saved as a csv file (to the specified path) and the best fit plots saved as pdf files (to the specified path)

To run

Once the parameters have been updated in the params.py file the user simply needs to run the script from the run.py file.