Package for Igm Cosmological-Correlations Analyses

requirements:

• python 2.7
• scipy 0.17.0 or later
• iminuit 1.2 or later
• fitsio
• healpy
• numba
• multiprocessing
• configargparse
• h5py

download

git clone https://github.com/igmhub/picca.git

add to your bashrc

export PICCA_BASE=<path to your picca>

then make sure you have all required modules by running

pip install -r requirements.txt --user

and finally run

python setup.py install --user

(assuming you run as user; for a system-wide install omit --user option).

Alternatively, you can just add picca/py/ to your PYTHONPATH.

example run over 1000 spectra (the DLA catalog is not required):

picca_deltas.py
--in-dir data/
--drq ../DR14Q_v1_1.fits
--dla-vac ../dlas/DLA_DR14_v1b.dat
--out-dir deltas/
--mode pix

• --mode can be pix (Anze/Jose format), spec (spec- files) or corrected-spec (corrected-spec files)
• --in-dir points to the directory containing the data
• NOTE: reading the spec files is very slow

picca_cf.py
--in-dir deltas/
--out cf.fits.gz
--nside 32

• nside determines the healpixelization used for the subsamples. nside=32 gives ~3200 subsamples for DR12.

picca_dmat.py
--in-dir deltas/
--out dmat.fits.gz
--rej 0.95

• --rej is 1-fraction of pairs used for the calculation

Only T123 implemented

# first calculate cf_1d from data
picca_cf1d.py
--in-dir deltas/
--out cf1d.fits.gz

# then use it for wick
picca_wick.py
--in-dir deltas/
--out t123.fits.gz
--rej 0.999
--cf1d cf1d.fits.gz

## use the export script to export to picca fitter format
picca_export.py
--data cf.fits.gz
--dmat dmat.fits.gz
--out cf-exp.out.gz

The tags name follow the names of the king of France:
https://fr.wikipedia.org/wiki/Liste_des_monarques_de_France#Liste_des_monarques_de_France