Description of files and how to read them

488 Seeds - 1952 Mocks - 9760 Acf

Mocks Folder

Mocks / COLA_BAOsample_Y6_v1.0_seed00###_map#_DESPhoto.parquet

Mocks containing, positions, velocities, halo mass, redshifts (z_rsd and photo_z) and flag for central or satellites.

how to read:

Import pandas as pd
Catalog = pd.read_parquet(filename, engine='pyarrow')

It gives a Pandas Dataframe, then you access to each column with Catalog[0] or Catalog[‘namecolumm’]

Mocks do not have “ra” and “dec” . you must convert from positions (x,y,z) to ra dec by doing:

    ra = (180. / np.pi * np.arctan2(y , x) + 360.) % 360.
    dec = 90. - 180. / np.pi * np.arctan2( np.sqrt( x * x + y * y ) ,z)

wheta Folder

wtheta.tar.gz , tar containing all measurements (combined bins or not)

Wtheta / xi_4096_x15_v1.0_seed00###_map#_bin#_DESPhoto.da

Angular two point correlation function for each of the mock. Delta_theta = 0.05

Resolution 4096, randoms x15

Wtheta / Combination_theta / In this folder you will fine the same files descrpted above for different DeltaTheta. = [0.2 , 0.15, 0.1]

n_z Folder

n_z / COLA_BAOsample_Y6_v1.0_ndz_bin#.csv n_z /COLA_BAOsample_Y6_v1.0_ndz_photoz.csv

It contains the n(z)* for each tomographic bin and the n(photo_z) from z= 0.5 to 1.2

Each * file is a csv with ‘ ‘ separation where the first column is the center of the bin, second column is the mean n(z) of the ~2000 mocks and the following ~2000 columns are de n(z) of each of the bins.

how to read:

Import pandas as pd
bin1 = pd.read_csv(‘file_bin1.csv', sep=‘   ‘)

It gives a Pandas Dataframe, then you access to each column with bin1[0] or bin[‘namecolumm’]