CHANGELOG.md

3.5.1

General

• Use of vector parameters now documented (PR #191; inspired by @lukashergt, thanks!)

Cosmology

• Added DESI 1yr BAO data and SN from Pantheon Plus, DESY5 and Union3 (thanks DESI team, @adematti, @rubind, @WillMatt4 and @rodri981)

3.5 – 2024-02-16

General

• Updated UGE sample job submission template (for cobaya-job-run and cobaya-grid-run)
• Clarify log feedback when using oversample_thin
• Fixed #345, #346, #347, #348

Grid scripts

• Support for running grids of models, including grid getdist, PDF tables, importance sampling, minimization (almost all features of CosmoMC grid now available in Cobaya). See the new doc pages.

Minimization

• Support for iminuit minimizer and getting best-fits for all mpi runs (#332, thanks @ggalloni)
• Support for minimization with an importance-sampled input yaml config

3.4.1 – 2023-10-12

General

• Fixed a packaging bug after migration to pyproject.toml

Cosmology

CLASS

• Min version update to 3.2.1 (solves #305; thanks to the CLASS developers)

3.4 – 2023-10-11

General

• Python 3.12 support (removed all dependence on distutils)
• Improved .products() method for samplers (MCMC and PolyChord) and post-processing: samples can now retrieved simultaneously for all MPI processes, and converted to GetDist. Also added .samples() methods to retrieve just the samples.

Collections

• Created a general load_samples function to load Cobaya results natively or as GetDist MCSamples.
• Collections are now aware of whether they are part of a parallel batch, and warn if trying to reweight/detemper individually (fixes #321).
• Fixed a bug with overzealous checks when loading samples (#306, thanks @mishakb for reporting).

MCMC

• Fixed a bug with mpi runs partly stalling when run with many chains (#308, thanks @vivianmiranda @lukashergt for reporting and testing).
• When oversample_thin is used, avg thinned weights now reported instead of acceptance rate (#310, thanks @vivianmiranda for reporting)

Cosmology

BAO

• Added 1-d grid LSS likelihood and BAO-only ELG and QSO (PR #266; thanks @msyriac)

CLASS

• Updated manual installation instructions and fixed some dependencies.
• Made more derived parameters available, and documented how to access even more.
• Fixed #292: wrong normalization for the Cl cross-spectra (thanks @carlosggarcia)

3.3.2 – 2023-07-28

General

• Class instance methods can now be used as external likelihoods.
• Fix _prior_tries_warning bug
• Fix over-stringent temperature test reading in chains

PolyChord

• products method revamped; can produce GetDist chains directly.

Cosmology

• updated CAMB min version to 1.5, fixing bug with Cobaya sampling
• cobaya-install cosmo now installs set of Planck NPIPE (PR4) python likelihoods
• added planck_2018_lowl.EE_sroll2 low-E Planck likelihood
• added startup warning if initial points are very over-dispersed compared to the proposal covariance
• Requesting CAMBdata from camb now a copy for exact initial power spectrum/non-linear model
• CAMB now supports using sigma8 as an input parameter (thanks @tilmantroester)

3.3.1 – 2023-04-04

• Updates for Pandas 2 compatibility
• Fixed bug in MCMC oversampling and simplified proposal code (#288) (thanks @JiangJQ2000)

3.3 – 2023-03-29

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

3.2.2 – 2022-11-03

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

3.2.1 – 2022-05-17

General

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

3.2 – 2022-05-13

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)

3.1.1 – 2021-07-22

• 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

3.1 – 2021-06-04

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)

3.0.4 – 2021-03-10

General

• Added current-state-related properties to Theory (current_state replacing _current_state attribute, and current_derived replacing get_current_derived() method) and LikelihoodInterface(current_logp replacing get_current_logp).
• Reworked and simplified error propagation for Theory and Likelihood: clearer error messages and more predictable traceback printing.
• @abstract decorator for base classes: better control of which methods of a parent class have been implemented/overridden (useful e.g. for Theory classes inheriting from a more general one but not implementing all possible quantities that the parent class defines).
• For components with defaults, type annotations for class attributes now automatically recognised as possible input options (previously only class attributes definitions).
• Shorter parameter specification now possible: <param_name>: [<prior_min>,<prior_max>,<ref_loc>,<ref_scale>,<proposal_width>] , assuming a uniform prior and a normal reference pdf.
• Got up to date with changes in numpy 1.20.
• bugfix: model.add_requirements() does not overwrite previous calls any more.

Cosmology:

• Interfaced sigma8 for arbitrary redshift (PR #144; thanks @Pablo-Lemos)
• Standardised naming conventions of base classes (CamelCasing, no leading underscores, simpler names). Added workarounds and deprecation notices for some of the old names.
• Updated cosmology Model example in docs.
• Added A. Lewis' CMB forecast data generator in CMBlikes definition file.
• Boltzmann: added unlensed Cl's with CAMB and CLASS.
• CMBlikes: small improvements, fixes, and docs.
• InstallableLikelihood now works with no install_options defined (local data).
• bugfix: bad handling of CMB polarisation capitalisation in Boltzmann.
• bugfix: bad if condition when retrieving sigmaR from camb (thanks @gcanasherrera and @matmartinelli)
• bugfix: unnecessary camb recomputations when setting some parameters as extra_args; fixes #142 (thanks @kimmywu)

3.0.3 – 2021-01-16

General

• Bugfixes when using cobaya.sample.get_sampler()
• More informative error tracebacks; fixes #121 (thanks @msyriac)
• Uniform priors can now be specified simply as [<min>, <max>]
• Likelihoods can now be renamed and used mutiple times simultaneously; fixes #126 (thanks @Pablo-Lemos)

Bibliography tools

• Bibtex files can now be specified via a class attribute, making inheritance easier (used to remove duplication)
• Component description now separate from bibtex code; by default, the component class docstring is used as description.
• Descriptions can be overridden to account for component input options (e.g. the actual method used in the minimizer).

Installation scripts

• Several bugs fixed: #123, #127 and others (thanks @timothydmorton, @xgarrido)

Minimize

• MCMC checkpoints are not deleted any more (was preventing resuming); fixes #124 (thanks @misharash)

Cosmological likelihoods and theory codes

BAO

• Added Hubble distance and fix to bao.generic (Thanks @Pablo-Lemos)

H0

• Added Riess 2020 and Freedman et al 2020
• Normalisation changed to chi2; fixes #105 (thanks @jcolinhill)

CAMB

• Fixed wrong sigma8 when z=0 not requested; fixes #128, #130, #132 (thanks @Pablo-Lemos and @msyriac)

CLASS

• Fixed ignoring l_max_scalars (thanks Florian Stadtmann)
• Fixed #106 (thanks @lukashergt)
• Adds min gcc version check for 6.4 (thanks @williamjameshandley)

cosmo-generator

• Fixed PySide2 problem in newer systems; fixes #114 (thanks @talabadi)
• Fixed missing Sampler combo box (thanks @williamjameshandley)

3.0.2 – 2020-10-16

General

• Installation bug fix.

3.0.1 – 2020-10-15

General

• Cobaya can (and should!) now be called as python -m cobaya run instead of cobaya-run , and the same for the rest of the scripts.

Installation scripts

• File downloader function now uses requests instead of wget (less prone to segfaults) , and stores intermediate files in a tmp folder.
• Added --skip-global option to cobaya-install: skips local installation of codes when the corresponding python package is available globally.
• path=global available for some components: forces global-scope import, even when installed with cobaya-install.
• Added --skip-not-installed to pytest command, to allow tests of non-installed components to fail.
• Installable components can define a class method is_compatible determining OS compatibility (assumed compatible by default). Installation of OS-incompatible components is skipped.

Minimize

• Results shared with all MPI processes.
• [prefix].updated.yaml is now [prefix].minimize.updated.yaml (GetDist needs to know the original sampler).
• Loads covmat correcly when starting from PolyChord sample.

Collections

• Collections are picklable again.
• Slices with omitted limits, e.g. [::2], now work.
• Slicing now returns a copy of the Collection, instead of a raw pandas.DataFrame.

MCMC

• Better MPI error handling: will now fail gracefully when called inside a user's script ( as opposed to cobaya-run).

3.0 – 2020-05-12

General

• Python 2 support removed, now requires Python 3.6+. Uses dict rather than OrderedDict.
• Significant internal refactoring including support for multiple inter-dependent theory codes.
• Greatly reduced Python overhead timing, faster for fast likelihoods.
• New base classes CobayaComponent and ComponentCollection, with support for standalone instantiation of all CobayaComponent.
• .yaml can now reference class names rather than modules, allowing multiple classes in one module.
• .yaml default files are now entirely at the class level, with no kind:module: embedding.
• inheritance of yaml and class attributes (with normal dict update, so e.g. all inherited nuisance parameters can be removed using params:). Each class can either define a .yaml or class attributes, or neither, but not both.
• The .theory member of likelihoods is now Provider class instance.
• Global stop_at_error option to stop at error in any component.
• Fix for more accurate timing with Python 3.
• Updates for GetDist 1.x.
• Module version information stored and checked.
• cobaya-run --no-mpi option to enable testing without mpi even on nodes with mpi4py installed.
• cobaya-run-job command to make a single job script and submit.
• docs include inheritance diagrams for key classes.
• renames path_install to packages_path, -m command line options to -p.
• cobaya-install saves the installation folder in a local config file. It does not need to be specified later at running, reinstalling, etc. Use cobaya-install --show-packages-path to show current one.
• Added cobaya-install --skip keyword1 keyword2 ... to skip components according to a list of keywords.
• Added citation info of Cobaya paper: arXiv:2005.05290
• Lots of other minor fixes and enhancements.

Likelihoods and Theories

• Support for external likelihoods and theories, referenced by fully qualified package name.
• Allow referencing likelihood class names directly (module.ClassName).
• Ability to instantiate Likelihood classes directly outside Cobaya (for testing of external likelihoods or use in other packages).
• Inherited likelihoods inherit .yaml file from parent if no new one is defined.
• Theories and likelihoods specify requirements and define derived products with general dependencies. get_requirements() function replaces add_theory().
• needs() method renamed to must_provide(), and can now return a dictionary of requirements conditional on those passed.
• requires and provides yaml keywords to specify which of ambiguous components handles specific requirements.
• three initialization methods: initialize (from __init__), initialize_with_params ( after parameter assignment) and initialize_with_provider (once all configured).
• Likelihood now inherits from Theory, with general cached compute and deque states.
• Likelihood and Theory can be instantiated from {external: class}.
• Derived parameters in likelihood .yaml can be explicitly tagged with derived:True.
• Renamed renames of likelihood to aliases (to avoid clash with renames for parameters).
• Added automatic aggregated chi2 for likelihoods of the same type.
• More documentation for how to make internal and external likelihood classes.
• Support for HelperTheory classes to do sub-calculations for any Theory class with separate nuisance parameters and speeds.
• classmethod get_class_options() can be used to generate class defaults dynamically based on input parameters.
• Added tests: test_dependencies.py, test_cosmo_multi_theory.py.
• External likelihood functions: changed how derived parameters are specified and returned, and how externally-provided quantities are requested and obtained at run time (see docs).

Samplers

• Samplers can now be initialized passing an already initialized model.
• Return value of cobaya-run now (updated_info, sampler_instance). Sampler products can be retrieved as sampler_instance.products().
• Sampler method now sets cache size.
• Automatic timing of likelihood and theory components to determine speed before constructing optimized blocking.
• Amount of oversampling can now be changed for MCMC and PolyChord, and it is taken into account at block sorting.
• Better dealing with files created during sampling: now all are identified and removed when --force used (using regexps).
• Added cobaya-run --test option that just initializes model and sampler.

MCMC

• Added progress tracking (incl. acceptance rate), and a plotting tool for it.
• Dragging now exploits blocks within slow and fast groups.

PolyChord

• Updated to PolyChord 1.17.1.
• Changed naming convention for raw output files, and added getdist -compatible .paramnames.
• Many defaults changes and useful documentation (Thanks Will Handley @williamjameshandley).

Minimize

• Support for auto-covmat as for mcmc.
• Fix for different starting points starting from existing chains using mpi.
• Fixes for bounds and rounding errors.
• Steps set from diagonal of inverse of covariance (still no use of correlation structure) .
• Warnings for differences between mpi starting points.

Cosmology

• Added matter_power_spectrum theory output for z,k,P(k) unsplined arrays.
• Fixed several bugs with Pk_interpolator (e.g. conflicts between likelihoods).
• Pk_interpolator calling arguments now different.
• Added sigma_R for linear rms fluctuation in sphere of radius R.
• Fixed problems with getting same background array theory results from different likelihoods.
• renamed H (array of H(z)) to Hubble.
• Boltzmann codes now consistent with varying T_CMB.
• changed use_planck_names to more general use_renames etc.
• DES likelihood now use numba if installed to give nearly twice faster performance.
• GUI input file generator allows to inspect auto-selected covariance matrices.

CAMB

• Calculation using transfer functions for speed up when only initial power spectrum and non-linear model parameters changed (even for non-linear lensing).
• Optimizations for which quantities computed.
• Option to request CAMBdata object from CAMB to access computed results directly.
• Fix for getting source windows power spectra.
• external_primordial_pk flag to optionally use a separate Cobaya Theory to return to the (binned) primordial power spectrum to CAMB.
• exposes all possible input/output parameters by introspection, making it easier to combine with other Theory classes using same parameter names.

CLASSY

• Updated to 2.9.3.
• Many small fixes.

2.0.3 – 2019-09-09

Samplers

PolyChord

• Fixed too much oversampling when manual blocking (#35). Thanks Lukas Hergt (@lukashergt) , Vivian Miranda (@vivianmiranda) and Will Handley (@williamjameshandley)
• Fixed ifort compatibility (#39, PR #42). Thanks Lukas Hergt (@lukashergt)

MCMC

• Fixed: using deprecated Pandas DataFrame method (#40). Thanks Zack Li (@xzackli)

Minimize

• Added GetDist output for best-fit (ignore-prior: True)

Likelihoods

• Added stop_at_error for likelihoods -- fixes #43. Thanks Lukas Hergt (@lukashergt)

Cosmology

• Fixed high-DPI screens (#41).

2.0 – 2019-08-20

General

• Added fuzzy matching for names of modules and parameters in a few places. Now error messages show possible misspellings.
• Modules can now be nested, e.g. planck_2018_lowl.TT and planck_2018_lowl.EE as TT.py and EE.py under folder likelihoods/planck_2018_lowl.

Getting help offline: defaults, and bibliography

• cobaya-citation deprecated in favour of cobaya-bib. In addition to taking .yaml input files as below, can now take individual module names.
• cobaya-doc added to show defaults for particular modules.
• Added menu to cobaya-cosmo-generator to show defaults for modules.

I/O

• Naming conventions for output files changed! *.updated.yaml instead of *.full.yaml for updated info, *.[#].txt instead of _[#].txt for chains, etc (see Output section in documentation).

Samplers:

• New, more efficient minimizer: pyBOBYQA .

Cosmology:

• Added full suite of Planck 2018 likelihoods.
• Added late-time source Cl's as a cosmological observable (CAMB only, for now)
• Changed capitalisation of some function and requests (deprecation messages and retrocompatibility added)

1.2.2 – 2019-08-20 (archived version)

General

• Backported some bug fixes.
• Fixed versions of external codes.

Cosmology:

• Planck: Fix for calibration parameter being ignored in CMBlike version of lensing likelihood.

1.2.0 – 2019-06-18

General

• Added --version argument for cobaya-run
• Many bug-fixes for corner-cases

Post-processing (still BETA: fixing conventions)

• Importance re-weighting, adding derived parameters, etc.

Collections

• Now picklable!
• Support for skip and thin

Samplers

Evaluate

• Multiple evaluations with new N option.

PolyChord

• Updated to version 1.16
• Handles speed-blocking optimally, including oversampling (manual blocking also possible) .

Likelihoods

• Reworked input/output parameters assignment (documented in DEVEL.rst)
• Removed deprecated gaussian

Cosmo theories:

• Capitalization for observables now enforced! (fixed H=H(z) vs h ambiguity)
• CAMB and CLASS: fixed call without observables (just derived parameters)

1.1.3 – 2019-05-31

Bugfixes (thanks Andreas Finke!)

I/O

• Fuzzy-matching suggestions for options of blocks.

1.1.2 – 2019-05-02

Bugfixes (thanks Vivian Miranda!)

1.1.1 – 2019-04-26

I/O

• More liberal treatment of external Python objects, since we cannot check if they are the same between runs. So force_reproducible not needed any more! (deprecation notice left)

1.1.0 – 2019-04-12

Python 3 compatibility – lots of fixes

Cosmological likelihoods

Planck

• clik code updated for compatibility with Python 3 and modern gcc versions

Cosmological theory codes

camb

• Updated to 1.0 (installing from master branch, considered stable)

classy

• Updated to ...
• Added P(k) interpolator

Samplers

MCMC

• Manual parameter speed-blocking.

PolyChord

• Now installable with cobaya-install polychord --modules [/path]

Cosmology input generator

• Added "citation" tab.

1.0.4 – 2019-04-11 (archived version)

Many bugfixes -- special thanks to Guadalupe Cañas-Herrera and Vivian Miranda!

I/O

• More permissive resuming.

Parameterization and priors

• Made possible to fix a parameter whose only role is being an argument of a dynamically defined one.
• Likelihoods can be used in dynamical derived parameters as chi2__[name] (cosmological application: added automatic consolidated CMB and BAO likelihoods).

Samplers

General

• Seeded runs for evaluate, mcmc and polychord.

MCMC

• Small improvements to callback functions.

PolyChord

• Updated to PolyChord 1.15 and using the official GitHub repo.
• Fixed output: now -logposterior is actually that (was chi squared of posterior).
• Interfaced callback functions.

Likelihoods

Created gaussian_mixture and added deprecation notice to gaussian

Cosmological theory codes

General

• Added P(k) interpolator as an observable (was already available for CAMB, but not documented)

classy

• Updated to 2.7.1
• Added P(k) interpolator

Cosmological likelihoods

DES

• Added Y1 release likelihoods (arXiv:1708.01530)

BICEP-Keck

• Updated to 2015 data (arXiv:1810.05216) and renamed to bicep_keck_2015.