v2.0.0rc1

This is the first v2 release candidate. v2 of CCL will have extensive API changes, documentation upgrades, and performance enhancements. The major highlights include

• support for CAMB via pycamb
• OpenMP threading where appropriate
• deprecation of the C interface
• support for mu-Sigma modified gravity
• a custom HALOFIT implementation
• improved support for tracers beyond the standard ones ("generalized tracers")
• refactored unit and benchmark test suites

CCL v1.0.0

This release includes

• Several new automated accuracy tests, particularly for angular power spectra and correlation functions.
• Further documentation regarding the benchmark codes.
• The version of the CCL paper to be submitted to ApjS.
• An updated CCL note.
• General code improvements as a result of LSST DESC Code Review.

CCL v0.9

This release includes

• Several new automated accuracy tests.
• Benchmark codes as documented in the wiki: https://github.com/LSSTDESC/CCL/wiki/Benchmarks.
• A Jupyter notebook that reproduces the plots in the CCL paper found in the examples folder.
• A draft of the CCL paper previous to the second round of LSST DESC internal review comments.
• An updated CCL note.

CCL v0.4

A new tagged version of CCL that includes halo model capabilities.

CCL v0.3.5

Includes versioning of the python module and fixes PyPi deployement

CCL v0.3.3

Includes new documentation via readthedocs and minor fixes

CCL v0.3

API changes:

Summary: the user interface for setting up cosmologies with neutrinos has been altered. Users should from now on pass Neff, the effective number of relativistic neutrino species in the early universe, and mnu, either a sum or neutrino masses or a set of 3 neutrinos masses.

C library

In ccl_core.c:

In the function, 'ccl_parameters_create', the arguements 'double N_nu_rel', and 'double N_nu_mass' have been removed. The arguments 'double Neff' and 'ccl_mnu_convention mnu_type' have been added. The argument 'mnu' has changed in type from 'double mnu' to 'double* mnu'.

Similar changes apply in 'ccl_cosmology_create_with_params' and all 'ccl_parameters_create...nu' convenience functions.

Additionally, in the function 'ccl_parameters_create' and 'ccl_cosmology_create_with_params', arguments have been added for the parameters of the BCM baryon model; these are 'double bcm_log10Mc', 'double bcm_etab', and 'double bcm_ks'.

In ccl_neutrinos.c:

The function ccl_Omeganuh2_to_Mnu has been renamed ccl_nu_masses. The arguments 'double a' and 'gsl_interp_accel* accel' have been removed. The argument 'ccl_neutrino_mass_splits mass_split' has been added.

Python wrapper

In core.py:

In the Parameters class, the arguments 'N_nu_rel', and 'N_nu_mass' have been removed. The optional arguments 'Neff', 'mnu_type', 'bcm_log10Mc', 'bcm_etab', and 'bcm_ks' have been added. Similar changes occur in the Cosmology class.

In neutrinos.py:

In the function Omeganuh2, the argument 'Neff' has been removed. It is now fixed to the length of the argument 'mnu'.
The function 'Omeganuh2_to_Mnu' has been renamed 'nu_masses'. The arguments 'a' and 'Neff' have been removed. The argument 'mass_split' has been added.

Other changes since release 0.2.1 (September 2017):

CLASS is no longer included as part of CCL; it can instead of easily downloaded via the class_install.py script and this procedure is documented.

Tutorial added for usage with MCMC

Added support for BCM baryon model

cpp compatibility improved

Python 3 support added

Added support for computing the nonlinear matter power spectrum with CosmicEmu

Added support for CMB lensing observables, including splines for cosmological quantities to higher redshift

Added the ability to return useful functions such as dNdz for a tracer Cl object.

Clarified license

CCL v 0.2.1

• Includes Travis support
• setup.py now installs also the C libraries

CCL v0.2

This version of CCL (v0.2) marks the first public release of the library. Improvements over v0.1 include: the computation of correlation functions, support for cosmologies with massive neutrinos, a docker file, extended documentation, tests and jupyter notebooks.