Cobaya

General

- Minimum Python version updated to 3.8
- `Prior.bounds()` can now return bounds at particular confidence levels when passed `confidence<1`.
- `SampleCollection` slicing now allows for advanced pandas slicing, e.g. `samples[samples["param"] > value]`.
- Fixed bug when setting reference pdf in MPI runs (thanks schoeneberg!)
- Components in yaml files referring to external Python modules can now give `package_install` settings to specify whether installed from pip, github or URL when cobaya-install is run.
- Fix for `post` when likelihoods return different number of derived parameters (285) (thanks zhaoruiyang98)

MCMC

- Added tempered sampling.
- `products` method revamped; can produce GetDist chains directly.

Cosmology

- Replaced default planck_2018_lowl.EE and planck_2018_low.TT with native versions, and using GitHub-hosted clik version.
- Updated planck likelihoods to all load calibration parameter from same yaml
- Removed clik version of planck 2018 CamSpec, defaults to native (avoids inconsistent calibration parameter naming)
- GUI inclues latest NPIPE fully Python likelihood configuration

General

- Deprecated `debug_file` in input, in favour of `debug: [filename]`.
- `Prior` now has method `set_reference`, to update the reference pdf's if needed (MPI-aware).
- Warning for stuck chains not more tolerant of many fast prior rejections
- Environment variables supported in input .yaml files, and {YAML_ROOT} placeholder for paths.
- Improved error messages for .yaml boolean options and install logs
- Fixes for max_tries .inf and old version checks
- fix for 'KeyError: _manual' bug caused by unmet requirements. 275 (thanks HTJense)

Cosmology

- Added CAMBspec NPIPE Planck 2020 likelihood (271) ) (thanks earosenberg)
- Added native version of `planck_2018_lowl.EE`.
- Added native version of `planck_2018_low.TT`. (thanks eirikgje)
- Added links to external likelihoods Planck PR4 Lensing, pyWMAP.
- GUI now support PySide6
- Fixed bug in BAO likelihood (250, thanks Pablo-Lemos)
- Added files for the BAO DR12 and DR16 LRG likelihoods (PR 235; thanks markm42)
- Test updates for CAMB 1.4 with updated constants, BBN model and neutrino nnu=3.044

General

- Fixed PyPI installation error (thanks Paul Shah!).
- Cleaner logging and better advice and error messages for missing component requirements.

General

- Documented uses of `Model` class in general contexts (previously only cosmo)
- `Model` methods to compute log-probabilities and derived parameters now have an `as_dict` keyword (default `False`), for more informative return value.

Cosmological likelihoods and theory codes

- `Pk_interpolator`: added extrapolation up to `extrap_kmin` and improved robustness

CAMB

- Removed problematic `zrei: zre` alias (fixes 199, thanks pcampeti)
- Added `Omega_b|cdm|nu_massive(z)` and `angular_diameter_distance_2`
- Returned values for `get_sigma_R` changed from `R, z, sigma(z, R)` to `z, R, sigma(z, R)`.
- Support setting individual Accuracy parameters, e.g. Accuracy.AccurateBB
- Calculate accurate BB when tensors are requested
- Fix for using derived parameters with post-processing
- Added `ignore_obsolete` option to be able to run with user-modified older CAMB versions.

CLASS

- Updated to v3.2.0
- Added `Omega_b|cdm|nu_massive(z)`, `angular_diameter_distance_2`, `sigmaR(z)`, `sigma8(z)`, `fsgima8(z)` and Weyl potential power spectrum.
- Added `ignore_obsolete` option to be able to run with user-modified older CLASS versions.
- Added direct access to some CLASS computation products, via new requisites `CLASS_[background|thermodynamics|primordial|perturbations|sources]`.
- Changed behaviour for `non_linear`: if not present in `extra_args`, uses the current default non-linear code (HMcode) instead of no non-linear code. To impose no non-linear corrections, pass `non_linear: False`.

BAO

- Added Boss DR16 likelihoods (185, by Pablo-Lemos)

BICEP-Keck

- Bugfix in decorrelation function 196 (by Caterina Umilta, umilta)
- Updated to 2021 data release (2018 data) and bugfix, 204 and 209 (by Dominic Beck, doicbek)

Planck

- Fixed segfault in clik when receiving NaN in the Cl's. Partially implements 231 (thanks lukashergt and williamjameshandley)

- Changes for compatibility with Pandas 1.3 (which broke convergence testing amongst other things).
- Updated docs with list of external likelihood codes, and to help avoid issues with PySide install
- Minor fixes in BAO/SN likelihoods

General

- updated and added documentation for cobaya-run-job; added cobaya-running-jobs and cobaya-delete-jobs
- Allow for more general dependencies between input parameters, derived parameters and likelihood/theory/prior inputs
- run, post and get_model can now all take inputs from a dictionary, yaml text or yaml
filename
- Support resuming of a completed run with changed convergence parameters
- run has optional arguments to set debug, force, output, etc settings
- More input and output typing for easier static error detection; added cobaya.typing for static checking of input dictionaries using TypedDict when available
- Refactoring of cobaya.conventions to remove most string literals and rename non-private constants starting with _
- Uses GetDist 1.2.2+ which fixes sign loading the logposterior value from Cobaya
collection
- Optimized calculation of Gaussian 1D priors
- run settings saved to ".updated.dill_pickle" pickle file in cases where callable/class
content cannot be preserved in yaml (install "dill")
- File locks to avoid overwriting results accidentally from multiple non-MPI processes
- Commonly-used classes can now be loaded simply using "from cobaya import Likelihood, InputDict, Theory, ..." etc., or call e.g. cobaya.run(..)
- run and post return NamedTuples (same content as before)
- Fixed handling of "type" in external likelihood functions
- bib_script and doc_script can now be called programmatically
- MPI support refactored using decorators
- requirements can now also be specified as list of name, dictionary tuples (in case name needs to be repeated)
- renamed Collection -> SampleCollection (to avoid confusion with general typing.Collection)
- allow loading of CamelCase classes from module with lowercase name. Class "file_base_name" attribute to
optionally specify the root name for yaml and bib files. Some supplied classes renamed.
- allow input likelihoods and theories to be instances (as well as classes); [provisional]

MCMC

- Fixed bug with "drag: True" that gave wrong results
- MPI reworked, now avoids ending and error deadlocks, and synchronizing exceptions
(raising OtherProcessError on non-excepting processes)
- Random number generation now using numpy 1.17 generators and MPI seeds generated using SeedSequence
(note MPI runs generally not reproducible with fixed seed due to thead timing/asynchronous mpi exchanges)
- Overhead reduced by at least 40%, thanks to caching in Collection
- Optimization of derived parameter output (for dragging, not computed at each dragging step)
- Some refactoring/simplification to pass LogPosterior instances more
- Reported acceptance rate is now only over last half chains (for MPI), or skipping first Rminus1_single_split fraction
- When no covamt or 'prosposal' setting for a parameter, the fallback proposal width is now scaled (narrower) from the ref or prior variance

Post-processing

- post function reworked to support MPI, thinning, and more general parameter-dependence
operations
- On one process operating on list of samples outputs consistent list of samples rather
than concatenating
- Output is produced incrementally, so terminated jobs still produce valid output
- No unnecessary theory recalculations
- Support for loading from CosmoMC/Getdist-format chains.
- Function in cobaya.cosmo_input.convert_cosmomc to general Cobaya-style info from
existing CosmoMC chains (some likelihood/theory information may have to be added if you
are recalculating things)

Minimize

- `PyBOBYQA` updated to 1.2, and quieter by default.
- 'best_of' parameter to probe different random starting positions (replacing seek_global_minimum for non-MPI)
- 'rhobeg' parameter larger to avoid odd hangs

Cosmology:

- Added CamSpec 2021 Planck high-l likelihoods (based on legacy maps, not NPIPE; thanks Erik Rosenberg)
- Added Riess et al H0 constraint (H0.riess2020Mb) in terms of magnitude rather than directly on H0
(use combined with sn.pantheon with use_abs_mag: True; thanks Pablo Lemos)
- Install updated Planck clik code (3.1)

Tests

- Added MPI tests and markers, synchronize errors to avoid pytest hangs on mpi errors
- Added new fast but more realistic running, resuming and post tests with and without mpi
- Fixed some randomized test inputs for more reliable running
- drag: True running test
- Coverage reporting added to Travis
- More useful traceback and console log when error raised running pytest
- added COBAYA_DEBUG env variable that can be set to force debug output (e.g. set in travis for failed build rerun)