CLMM
1.12.0
Getting Started
Rapid overview
Installation
Using and citing CLMM
Usage Demos
Generate mock data for a cluster
Measure WL Profiles
Model WL Profiles
Generate mock data for a cluster ensemble
Using the cosmoDC2 catalog
Mass Fitting Examples
Example 1: Ideal data
Example 1b: Impact of miscentering
Example 2: Realistic data and wrong model
Example 3: Account for the n(z) of sources
Example 4: Using a real dataset (HSC)
Example 5: Using a real datasets (DES)
Other
Model WL Profiles (different redshift inputs)
Model WL Profiles (Object Oriented)
Boost factors
Weak lensing weights
Mass conversion between different mass definitions
Generate “realistic” mock data for a cluster ensemble
Reference
API Documentation
clmm.clusterensemble module
clmm.constants module
clmm.cosmology package
clmm.cosmology.ccl module
clmm.cosmology.cluster_toolkit module
clmm.cosmology.numcosmo module
clmm.cosmology.parent_class module
clmm.dataops package
clmm.galaxycluster module
clmm.gcdata module
clmm.redshift package
clmm.redshift.distributions module
clmm.redshift.tools module
clmm.theory package
clmm.theory.ccl module
clmm.theory.cluster_toolkit module
clmm.theory.func_layer module
clmm.theory.generic module
clmm.theory.numcosmo module
clmm.theory.parent_class module
clmm.plotting package
clmm.utils package
clmm.utils.beta_lens module
clmm.utils.boost module
clmm.utils.ellipticity module
clmm.utils.statistic module
clmm.utils.units module
clmm.utils.validation module
clmm.support package
clmm.support.mock_data module
clmm.support.sampler module
CLMM
API Documentation
clmm.cosmology package
clmm.cosmology.ccl module
View page source
clmm.cosmology.ccl module
@file ccl.py Cosmology using CCL