Merge pull request #98 from cheymans/DESY3_KiDS-1000

DES-Y3+KiDS-1000

.github/workflows/ci.yml

@@ -222,6 +222,13 @@ jobs:
           cosmosis examples/des-y3.ini -v halo_model_parameters.logT_AGN=8.2 -p camb.halofit_version=mead2020_feedback | tee output/des-y3-mead.log
           grep -e 'Likelihood =  6049.94' -e 'Likelihood =  6049.00' output/des-y3-mead.log
 
+      - name: Joint DES Y3 and KiDS-1000 likelihood
+        shell: bash -l {0}
+        run: |
+          source cosmosis-configure
+          cosmosis examples/des-y3_and_kids-1000.ini | tee output/des-y3_and_kids-1000.log
+          grep 'Likelihood =  -199.409' output/des-y3_and_kids-1000.log
+          
       - uses: actions/cache@v2
         name: ACT Data Cache
         id: cache-act

.gitignore

@@ -23,3 +23,4 @@ likelihood/planck2015/plc-2.0/buildir/
 likelihood/planck2015/plc-2.0/include/
 likelihood/planck2015/plc-2.0/lib/
 likelihood/planck2015/plc-2.0/share/
+shear/cosebis/modules/besselzero04.h

boltzmann/README

@@ -1,4 +1,4 @@
-This repo will contain Boltzmann and similar codes for structure evolution and od other cosmological predictions.
+This repo contains Boltzmann and similar codes for structure evolution and od other cosmological predictions.
 
-The camb directory contains, for now, an unmodified version of CAMB from January 2012.
+The camb directory contains camb_interface.py which imports and interfaces with the python version of CAMB
 

examples/des-y3-LCDM-optimised-scale-cuts.ini

@@ -0,0 +1,56 @@
+; For DES Y3 aficionados this file was previously named scales_3x2pt_0.5_8_6_v0.4_agg.ini
+; This has been renamed for easier access to DES Y3 newbies
+; This file lists the scale cuts used in the Amon et al / Secco, Samuroff et al 2022
+; for their "LCDM Optimised" cosmic shear analysis
+
+[2pt_like]
+angle_range_xip_1_1 = 2.475 999.0
+angle_range_xip_1_2 = 2.475 999.0
+angle_range_xip_1_3 = 3.116 999.0
+angle_range_xip_1_4 = 2.475 999.0
+angle_range_xip_2_2 = 3.923 999.0
+angle_range_xip_2_3 = 4.938 999.0
+angle_range_xip_2_4 = 4.938 999.0
+angle_range_xip_3_3 = 3.923 999.0
+angle_range_xip_3_4 = 4.938 999.0
+angle_range_xip_4_4 = 3.923 999.0
+
+angle_range_xim_1_1 = 24.750 999.0
+angle_range_xim_1_2 = 19.660 999.0
+angle_range_xim_1_3 = 24.750 999.0
+angle_range_xim_1_4 = 19.660 999.0
+angle_range_xim_2_2 = 31.158 999.0
+angle_range_xim_2_3 = 39.226 999.0
+angle_range_xim_2_4 = 39.226 999.0
+angle_range_xim_3_3 = 49.383 999.0
+angle_range_xim_3_4 = 49.383 999.0
+angle_range_xim_4_4 = 39.226 999.0
+
+angle_range_gammat_1_1 = 24.75 999.0
+angle_range_gammat_1_2 = 24.75 999.0
+angle_range_gammat_1_3 = 24.75 999.0
+angle_range_gammat_1_4 = 24.75 999.0
+angle_range_gammat_2_1 = 15.61619428 999.0
+angle_range_gammat_2_2 = 15.61619428 999.0
+angle_range_gammat_2_3 = 15.61619428 999.0
+angle_range_gammat_2_4 = 15.61619428 999.0
+angle_range_gammat_3_1 = 12.40438403 999.0
+angle_range_gammat_3_2 = 12.40438403 999.0
+angle_range_gammat_3_3 = 12.40438403 999.0
+angle_range_gammat_3_4 = 12.40438403 999.0
+angle_range_gammat_4_1 = 12.40438403 999.0
+angle_range_gammat_4_2 = 12.40438403 999.0
+angle_range_gammat_4_3 = 12.40438403 999.0
+angle_range_gammat_4_4 = 12.40438403 999.0
+angle_range_gammat_5_1 = 9.85315247 999.0
+angle_range_gammat_5_2 = 9.85315247 999.0
+angle_range_gammat_5_3 = 9.85315247 999.0
+angle_range_gammat_5_4 = 9.85315247 999.0
+
+angle_range_wtheta_1_1 = 39.22610651 999.0
+angle_range_wtheta_2_2 = 24.75 999.0
+angle_range_wtheta_3_3 = 19.65962381 999.0
+angle_range_wtheta_4_4 = 15.61619428 999.0
+angle_range_wtheta_5_5 = 12.40438403 999.0 
+
+

examples/des-y3_and_kids-1000-priors.ini

@@ -0,0 +1,26 @@
+; This is the priors file (https://cosmosis.readthedocs.io/en/latest/usage/parameter_files/priors_ini.html)
+; Here we set priors that aren't TopHats (as those priors are already set in the values file)
+; We set the Gaussian parameters as follows
+
+; Uncorrelated Gaussian priors on the uncertainty in the DES Y3 mean redshift per tomographic bin
+[wl_photoz_errors_des]
+bias_1 = gaussian 0.00 0.018
+bias_2 = gaussian 0.00 0.015
+bias_3 = gaussian 0.00 0.011
+bias_4 = gaussian 0.0  0.017
+
+; Uncorrelated Gaussian priors on the uncertainty in the DES Y3 shear calibration per tomographic bin
+; Note that the KiDS shear calibration uncertainty is included in the covariance matrix
+[shear_calibration_parameters]
+m1 = gaussian -0.0063 0.0091
+m2 = gaussian -0.0198 0.0078
+m3 = gaussian -0.0241 0.0076
+m4 = gaussian -0.0369 0.0076
+
+; Correlated Gaussian priors on the uncertainty between the KiDS-1000 tomographic bins
+[nofz_shifts_kids]
+uncorr_bias_1 = gaussian  0.000  1.0
+uncorr_bias_2 = gaussian -0.181  1.0
+uncorr_bias_3 = gaussian -1.110  1.0
+uncorr_bias_4 = gaussian -1.395  1.0
+uncorr_bias_5 = gaussian  1.265 1.0

examples/des-y3_and_kids-1000-values.ini

@@ -0,0 +1,71 @@
+; This is the values file (https://cosmosis.readthedocs.io/en/latest/usage/parameter_files/values_ini.html)
+; It defines the complete set of parameters for the sampler to varies over, and their limits.
+; For TopHat priors, this value file also sets the prior window.
+; Any Gaussian priors are set in the prior file, with the dummy limits defined here superseded. 
+
+; DES and KiDS take different approaches to account for uncertainty 
+; in their redshift distributions and shear calibration correction
+; We use different parameters for each survey
+
+;DES use Gaussian priors that are uncorrelated for between z-bins (see prior file)
+[wl_photoz_errors_des]
+bias_1 = -0.1   0.0   0.1
+bias_2 = -0.1   0.0   0.1
+bias_3 = -0.1   0.0   0.1
+bias_4 = -0.1   0.0   0.1
+
+;In KiDS-1000 the photo-z uncertainty is assumed to be correlated across the z-bins (see prior file)
+[nofz_shifts_kids]
+uncorr_bias_1 = -5.0   0.000  5.0
+uncorr_bias_2 = -5.0  -0.181  5.0
+uncorr_bias_3 = -5.0  -1.110  5.0
+uncorr_bias_4 = -5.0  -1.395  5.0
+uncorr_bias_5 = -5.0   1.265  5.0
+
+; The DES shear calibration values are marginalised over with a Gaussian prior (see prior file)
+; Note for KiDS the shear calibration uncertainty is included in the covariance matrix
+[shear_calibration_parameters]
+m1 = -0.1  0.0  0.1
+m2 = -0.1  0.0  0.1
+m3 = -0.1  0.0  0.1
+m4 = -0.1  0.0  0.1
+
+; The Hybrid pipeline set up uses independent IA parameters for each survey
+; Here we use Tophat priors for an NLA-z analysis, but if you wanted to analyse
+; TATT you can modify the priors on the A2, alpha2 and bias_ta parameters
+[intrinsic_alignment_parameters]
+z_piv   =  0.62
+A1_des      = -5.0   0.0  5.0
+A2_des      = 0.0
+alpha1_des  = -5.0  0.0  5.0
+alpha2_des  = 0.0
+bias_ta_des =  0.0 
+A1_kids      = -5.0   0.0  5.0
+A2_kids      = 0.0
+alpha1_kids  = -5.0  0.0  5.0
+alpha2_kids  = 0.0
+bias_ta_kids =  0.0
+A1      = 0.0
+A2      = 0.0
+alpha1  = 0.0
+alpha2  = 0.0
+bias_ta =  0.0
+
+; We use a Tophat prior to marginalise over our uncertainty on baryon feedback using HMCode2020
+[halo_model_parameters]
+logt_agn = 7.3 7.8 8.0
+
+; This is the set of cosmological parameter priors that were found to 
+; introduce the least projection effects on the marginal S8 distribution
+; Note that CosmoSIS v3 onwards can sample over S8
+[cosmological_parameters]
+omch2 = 0.051    0.11812972217650827    0.255
+ombh2 = 0.019    0.025939374402978773    0.026
+h0 =    0.64     0.7666550530735352    0.82
+n_s =  0.84    0.9007697522848085    1.1
+S_8 = 0.1  0.7567464875805479    1.3
+omega_k = 0.0
+w       = -1.0
+wa      = 0.0
+mnu     = 0.055  0.07740741  0.6
+tau     =  0.0697186