Python script for Pearson correlation coefficient for time resolved serial femtosecond crystallography

In the time resolved serial femtosecond crystallography, this python code  is used to validate the experimental observed difference electron density with the calculated electron density from the excited state structure. All operations were performed using python program only.

Steps;

1. Input files observed difference electron density map and calculated difference map are prepared using as described in the Pandey et al. 2020 and Claesson et al. 2020. 
   1. Ex: 1ps.map (observed difference electron density (DED) map.
   2. 1ps_pdb.map (calculated difference electron density map from the excited state structure)
2. Prepare an input file called cal_pcc.txt with the following lines:

Observed DED map

Calculated DED map

Outmap name

Number of symmetries

Symmetry operators

Coordinates of the atom of interest

Radius of sphere around the atom of interest coordinates

1. The PCC is calculated using the same way as in Carrillo et al 2021, the pcc.py program is available in git@github.com:madanmx/GameSFX.git

In addition, for the first time, I propose to use PCC with observed DED maps at different laser power (power titration). In this analysis (unpublished dataset), the DED features around the chromophore/protein residues should have good PCC value.