77 lines
3.5 KiB
ReStructuredText
77 lines
3.5 KiB
ReStructuredText
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Release notes
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=============
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This file only lists the most important changes to each version. We try to follow semantic versioning:
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- Major release means API incompatibilities
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- Minor release means API compatibilities, but significant feature differences
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- Bugfix release only fixes bugs
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Release 2.1
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-----------
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- An option to control the verbosity in log file has been added ("system/logfile_verbose_level", v2.1.3)
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Forward related
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^^^^^^^^^^^^^^^
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- Add a way of transforming all bias models into a forward deterministic transition. It means more flexibility at the cost of losing performance/memory by doing
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more computations than required. For example, each subcatalog needs its own bias which could trigger quite a lot of recomputation and/or caching.
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- PMv2 optimization when sampling.
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- Implement a simple (non-MPI) haar transform.
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- Add EnforceMass model element to articifially fix the mass conservation.
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- Forward models may support a new behavior for adjointModel_v2. They can accumulate all adjoint vectors that are provided to them through
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adjointModel_v2. The new behavior must be requested by calling BORGForwardModel::accumulateAdjoint. In that case, the user is explicitly
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requested to clear the adjoint gradient when the computation is done by calling BORGForwardModel::clearAdjointGradient.
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That behavior has been ported to pyborg. If the mode is not supported, an exception will be triggered.
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- Merged Altair code.
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- Bind ClassCosmo to ARES. Python binding is also active and vectorized for get_Tk.
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Sampler related
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^^^^^^^^^^^^^^^
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- Add CG89 "higher order" symplectic integrator.
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API related:
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^^^^^^^^^^^^
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- ManyPower bias model needs a likelihood info entry now to set the width of the prior on parameters. The name is ManyPower_prior_width in [info].
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- Code cleanup in velocity field estimator. It also now supports Simplex-In-Cell (no adjoint gradient yet and only non-MPI).
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- Models accept a broader range of parameters using BORGForwardModel::setModelParams.
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Python related:
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^^^^^^^^^^^^^^^
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- *NEW tool* hades_python which supports a full deterministic transition written in python/tensorflow/jax. Data loading is still work in progress and
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may need hacking at the moment
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- Python extension is supporting LikelihoodInfo and the bias as forward model element.
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- Add a 'setup.py' to support compiling the BORG python module directly with pip and packaging as a wheel file.
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- Samplers fully supported from Python.
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Build related
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^^^^^^^^^^^^^
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- build.sh only downloads the dependency if the file is not already there
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- Error reporting include a full C++ stacktrace on supported platforms (cmake flag is STACKTRACE_USE_BACKTRACE=ON, experimental at the moment
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It can be turned off).
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- Added GIT hooks to check on basic text elements (like formatting) before running commits.
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clang-formatter absence may be overridden using ARES_CLANG_OVERRIDE=1
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Release 2.0alpha
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----------------
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- Use a prior that is purely gaussian unit variance (Fourier) in HMC now. The cosmology is completely moved as a BORGForwardModel.
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- BORGForwardModel adds the v2 API to executes model: forwardModel_v2, and adjointModel_v2. This relies heavily on the mechanics of ModelIO
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- Deterministic models are now self-registering and the available lists can be dynamically queried.
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- Add a hook to optionally dump extra bias fields.
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- Add QLPT and QLPT_RSD forward model in extra/borg
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- Lots of documentation reorganization
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- Added the lyman alpha model in extra/borg
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- Merged the EFT likelihood effort in extra/borg
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Release 1.0
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-----------
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Initial release
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