/halowlsz

Estimating the correlation function of lensing vs SZ using halo model

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Temporarily run this code using these steps
1. cd halowlsz
2. Change parameters in config.py
3. python demo_halomodel.py


1. Dir /media/luna1/vinu/Lensing/DES/Kappa_map/SVA1/des_sz
2. Use run_des_sz_cc.py and use des_emap, des_bmap, sz_map etc variables
3. des_emap, des_bmap can be shapes of galaxies or PSF
4. Shear catalogs or Mass maps are in /media/luna1/vinu/DES_Catalogs/DES_catalogs/Y1
5. Sims are in /media/luna1/vinu/des_sz in datastar, /global/project/projectdirs/des/vinu/des_sz on cori or edison etc 
6. halowlsz/generate_some_correlations.py gives correlation function using difference source redshift distributions
7.