This Python script demonstrates a process for generating premixed stellar models by reading parameters from a namelist (.nml) file, using the pysep and f90nml libraries. It reads a set of parameters such as stellar mass, composition, and other critical variables from a 'poly.nml' file and then utilizes these parameters to generate a stellar model through a function 'generatepremsmodel'. This script is likely used in computational astrophysics, particularly in studies involving stellar evolution or structure.

from pysep.newpoly.generateNML import format_elem
from pysep.newpoly.runNewpoly import generate_prems_model
from f90nml.namelist import Namelist as nml
import f90nml
 
with open('poly.nml', 'r') as nml_file:
    rnml = f90nml.read(nml_file)
 
data = rnml['data']
generate_prems_model(data['sumass'],
                     data['X'],
                     data['Z'],
                     data['cmixl'],
                     data['beta'],
                     data['fmass1'],
                     data['fmass2'],
                     data['ddage'],
                     data['pn'],
                     data['elem'],
                     data['lexcom'],
                     'C',
                     'C')