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https://github.com/CMA-ES/pycma

Python implementation of CMA-ES
https://github.com/CMA-ES/pycma

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Python implementation of CMA-ES

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README 

        
# pycma         

[![CircleCI](https://circleci.com/gh/CMA-ES/pycma/tree/master.svg?style=shield)](https://circleci.com/gh/CMA-ES/pycma/tree/master)

[![Build status](https://ci.appveyor.com/api/projects/status/1rge11pwyt55b26k?svg=true)](https://ci.appveyor.com/project/nikohansen/pycma)

[![Downloads](https://static.pepy.tech/badge/cma/week)](https://pepy.tech/project/cma)

[![DOI](https://zenodo.org/badge/68926339.svg)](https://doi.org/10.5281/zenodo.2559634)

[[BibTeX](https://github.com/CMA-ES/CMA-ES.github.io/blob/master/pycmabibtex.bib)] cite as:

> Nikolaus Hansen, Youhei Akimoto, and Petr Baudis. CMA-ES/pycma on Github. Zenodo, [DOI:10.5281/zenodo.2559634](https://doi.org/10.5281/zenodo.2559634), February 2019. 

---



  

``pycma`` is a Python implementation of [CMA-ES](http://cma-es.github.io/) and a few related numerical optimization tools.



The [Covariance Matrix Adaptation Evolution Strategy](https://en.wikipedia.org/wiki/CMA-ES) 

([CMA-ES](http://cma-es.github.io/)) is a stochastic derivative-free numerical optimization

algorithm for difficult (non-convex, ill-conditioned, multi-modal, rugged, noisy) optimization

problems in continuous search spaces.



Useful links:



* [A quick start guide with a few usage examples](https://pypi.python.org/pypi/cma)



* [The above `notebooks` folder has some example code in Jupyter notebooks](https://github.com/CMA-ES/pycma/tree/master/notebooks)



* [The API Documentation](http://cma-es.github.io/apidocs-pycma)



* [Hints for how to use this (kind of) optimization module in practice](http://cma-es.github.io/cmaes_sourcecode_page.html#practical)



* [FAQs and HowTos (under development)](https://github.com/CMA-ES/pycma/issues?q=is:issue+label:FAQ).



## Installation of the [latest release](https://pypi.python.org/pypi/cma)



In a system shell, type



```sh

    python -m pip install cma

```



to install the [latest release](https://pypi.python.org/pypi/cma)

from the [Python Package Index (PyPI)](https://pypi.python.org/pypi). The [release link](https://pypi.python.org/pypi/cma) also provides more installation hints and a quick start guide.



```sh

    conda install --channel cma-es cma

```



installs from the conda cloud channel `cma-es`. CAVEAT: this distribution is currently not updated!



## Installation from Github



The quick way (this requires [`git`](https://git-scm.com) to be installed): to install the code from, for example, the `master` branch, copy-paste



```sh

    pip install git+https://github.com/CMA-ES/pycma.git@master

```



The long way:



- get the package



  - either download and unzip the code by clicking the green button above

  - or, with [`git`](https://git-scm.com) installed, type ``git clone https://github.com/CMA-ES/pycma.git``



- "install" the package



  - either copy (or move) the ``cma`` source code folder into a folder which is in the

    [Python path](https://docs.python.org/3/library/sys.html#sys.path) (e.g. the current folder)



  - or modify the [Python path](https://docs.python.org/3/library/sys.html#sys.path) to point

    to the folder where the ``cma`` package folder can be found.

    In both cases, ``import cma`` works without any further installation.



  - or install the ``cma`` package by typing



    ```sh

        pip install -e cma

    ```

    in the folder where the ``cma`` package folder can be found.

    Moving the ``cma`` folder away from its location invalidates this

    installation.



It may be necessary to replace ``pip`` with ``python -m pip`` and/or prefixing

either of these with ``sudo``.



## Version History



* [Release ``3.4.0``](https://github.com/CMA-ES/pycma/releases/tag/r3.4.0)

  - fix compatibility to `numpy` 2.0 (thanks to [Sait Cakmak](https://github.com/saitcakmak))

  - improved interface to `noise_handler` argument which accepts `True` as value

  - improved interface to `ScaleCoordinates` now also with lower and upper value mapping to [0, 1], see [issue #210](https://github.com/CMA-ES/pycma/issues/210)

  - changed: `'ftarget'` triggers with <= instead of <

  - assign `surrogate` attribute (for the record) when calling `fmin_lq_surr`

  - various (minor) bug fixes

  - various (small) improvements of the plots and their usability

    - display iterations, evaluations and population size and termination

      criteria in the plots

    - subtract any recorded x from the plotted x-values by ``x_opt=index``

  - plots are now versus iteration number instead of evaluations by default

  - provide legacy `bbobbenchmarks` without downloading

  - new: `CMADataLogger.zip` allows sharing plotting data more easily by a zip file

  - new: `tolxstagnation` termination condition for when the incumbent seems stuck

  - new: collect restart terminations in `cma.evalution_strategy.all_stoppings`

  - new: `stall_sigma_change_on_divergence_iterations` option to stall

    `sigma` change when the median fitness is worsening

  - new: limit active C update for integer variables

  - new: provide a COCO single function



* [Release ``3.3.0``](https://github.com/CMA-ES/pycma/releases/tag/r3.3.0)

  implements

  - diagonal acceleration via diagonal decoding (option

    `CMA_diagonal_decoding`, by default still off).

  - `fmin_lq_surr2` for running the surrogate assisted

    [lq-CMA-ES](https://cma-es.github.io/lq-cma).

  - `optimization_tools.ShowInFolder` to facilitate rapid experimentation.

  - `verb_disp_overwrite` option starts to overwrite the last line of the

    display output instead of continuing adding lines to avoid screen

    flooding with longish runs (off by default).

  - various smallish improvements, bug fixes and additional features and

    functions.



* [Release ``3.2.2``](https://github.com/CMA-ES/pycma/releases/tag/r3.2.2)

  fixes some smallish interface and logging bugs in `ConstrainedFitnessAL`

  and a bug when printing a warning. Polishing mainly in the plotting

  functions. Added a notebook for how to use constraints.



* [Release ``3.2.1``](https://github.com/CMA-ES/pycma/releases/tag/r3.2.1)

  fixes plot of principal axes which were shown squared by mistake in version 3.2.0.



* [Release ``3.2.0``](https://github.com/CMA-ES/pycma/releases/tag/r3.2.0)

  provides a new interface for constrained optimization `ConstrainedFitnessAL`

  and `fmin_con2` and many other minor fixes and improvements.



* [Release ``3.1.0``](https://github.com/CMA-ES/pycma/releases/tag/r3.1.0)

  fixes the return value of `fmin_con`, improves its usability and provides

  a `best_feasible` attribute in `CMAEvolutionStrategy`, in addition to

  various other more minor code fixes and improvements.



* [Release ``3.0.3``](https://github.com/CMA-ES/pycma/releases/tag/r3.0.3) provides parallelization with ``OOOptimizer.optimize(..., n_jobs=...)`` (fix for ``3.0.1/2``) and improved `pickle` support.



* [Release ``3.0.0``](https://github.com/CMA-ES/pycma/releases/tag/r3.0.0) provides non-linear constraints handling, improved plotting and termination options and better resilience to injecting bad solutions, and further various fixes.



* Version ``2.7.1`` allows for a list of termination callbacks and a light copy of `CMAEvolutionStrategy` instances.



* [Release ``2.7.0``](https://github.com/CMA-ES/pycma/releases/tag/r2.7.0) logger now writes into a folder, new fitness model module, various fixes.



* [Release ``2.6.1``](https://github.com/CMA-ES/pycma/releases/tag/r2.6.1) allow possibly much larger condition numbers, fix corner case with growing more-to-write list.



* [Release ``2.6.0``](https://github.com/CMA-ES/pycma/releases/tag/r2.6.0) allows initial solution `x0` to be a callable.



* Version ``2.4.2`` added the function `cma.fmin2` which, similar to `cma.purecma.fmin`, 

  returns ``(x_best:numpy.ndarray, es:cma.CMAEvolutionStrategy)``  instead of a 10-tuple

  like `cma.fmin`. The result 10-tuple is accessible in [``es.result``](https://github.com/CMA-ES/pycma/blob/025ef1fed91c86690a21e9ed81713062d29398ff/cma/evolution_strategy.py#L942)``:``[``namedtuple``](https://docs.python.org/3/library/collections.html#collections.namedtuple).

  

* Version ``2.4.1`` included ``bbob`` testbed.



* Version ``2.2.0`` added VkD CMA-ES to the master branch.



* Version ``2.*`` is a multi-file split-up of the original module.



* Version ``1.x.*`` is a one file implementation and not available in the history of

  this repository. The latest ``1.*`` version ``1.1.7`` can be found

  [here](https://pypi.python.org/pypi/cma/1.1.7).