This site contains the results of calculations performed for different 
model variations discussed in the paper:
'Metallicity of stars formed throughout the cosmic history based on the 
observational properties of star forming galaxies' 
by Martyna Chruslinska & Gijs Nelemans, MNRAS, 2019 (DOI: 10.1093/mnras/stz2057)
https://ui.adsabs.harvard.edu/abs/2019MNRAS.tmp.1974C/abstract
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DATA FILES:
 The data files for the three main variations discussed in the paper are:
-high-Z_extreme_FOH_z_dM.dat (the high metallicity extreme)
-low-Z_extreme_FOH_z_dM.dat (the low metallicity extreme)
-moderate_FOH_z_dM.dat (example moderate variation)
 The other variations described in the paper (as well as the three 
 variations mentioned above) can be found in:
-variations.tar.gz
 the file DESCRIPTION contained within the archive explains the naming convention.

 The values in each file correspond to stellar mass density (comoving; Msun/Mpc^3) 
 formed in a given metallicity 12+log(O/H) (columns) bin and between two redshifts 
 (rows). 

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PYTHON SCRIPTS:
 The attached python script plot_SFRD_Z_z.py can be used to visualize the data:
- plot the distribution of the star formation rate density over metallicities 
  and redshift SFRD(Z,z) (e.g. as in Fig. 6 from the paper)
- plot the cumulative fractions of total star formation at a chosen redshift
  happening below a certain metallicity (as in Fig. 13 from the paper)
 The second python script sample_metallicity.py can be used to draw metallicity 
 from the (star formation rate density weighted) metallicity distribution at a 
 chosen redshift.

 Both scripts need as input: 
-Time_redshift_deltaT.dat 
-the data file for the selected model variation 
 (i.e. one of the *_FOH_z_dM.dat files; input_file in the script)
 The example use is shown at the bottom of each of the python scripts.