Brent's method for univariate function optimization
Project description
brent-search
============
|PyPI-Status| |PyPI-Versions| |Conda-Forge-Status| |Conda-Downloads|
|Build-Status| |Codacy-Grade| |LICENCE|
Brent's method for univariate function optimization.
Example
-------
.. code:: python
from brent_search import brent
def func(x, s):
return (x - s)**2 - 0.8
r = brent(lambda x: func(x, 0), -10, 10)
print(r)
The output should be
.. code::
(0.0, -0.8, 6)
Install
-------
The recommended way of installing it is via
conda_
.. code:: bash
conda install -c conda-forge brent-search
An alternative way would be via pip_
.. code:: bash
pip install brent-search
Running the tests
-----------------
After installation, you can test it
.. code:: bash
python -c "import brent_search; brent_search.test()"
as long as you have pytest_.
Authors
-------
* `Danilo Horta`_
License
-------
This project is licensed under the MIT License - see the
LICENSE_ file for details.
.. |Build-Status| image:: https://travis-ci.org/limix/brent-search.svg?branch=master
:target: https://travis-ci.org/limix/brent-search
.. |Codacy-Grade| image:: https://api.codacy.com/project/badge/Grade/259a10b874124d91bccf61e516522607
:target: https://www.codacy.com/app/danilo.horta/brent-search?utm_source=github.com&utm_medium=referral&utm_content=limix/brent-search&utm_campaign=Badge_Grade
.. |PyPI-Status| image:: https://img.shields.io/pypi/v/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Versions| image:: https://img.shields.io/pypi/pyversions/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |Conda-Forge-Status| image:: https://anaconda.org/conda-forge/brent-search/badges/version.svg
:target: https://anaconda.org/conda-forge/brent-search
.. |Conda-Downloads| image:: https://anaconda.org/conda-forge/brent-search/badges/downloads.svg
:target: https://anaconda.org/conda-forge/brent-search
.. |LICENCE| image:: https://img.shields.io/pypi/l/brent-search.svg
:target: https://raw.githubusercontent.com/brent-search/brent-search/master/LICENCE
.. |PyTest| image:: http://docs.pytest.org/en/latest/
:target: http://docs.pytest.org/en/latest/
.. _LICENSE: https://raw.githubusercontent.com/limix/brent-search/master/LICENSE
.. _Danilo Horta: https://github.com/horta
.. _conda: http://conda.pydata.org/docs/index.html
.. _pip: https://pypi.python.org/pypi/pip
.. _pytest: http://docs.pytest.org/en/latest/
============
|PyPI-Status| |PyPI-Versions| |Conda-Forge-Status| |Conda-Downloads|
|Build-Status| |Codacy-Grade| |LICENCE|
Brent's method for univariate function optimization.
Example
-------
.. code:: python
from brent_search import brent
def func(x, s):
return (x - s)**2 - 0.8
r = brent(lambda x: func(x, 0), -10, 10)
print(r)
The output should be
.. code::
(0.0, -0.8, 6)
Install
-------
The recommended way of installing it is via
conda_
.. code:: bash
conda install -c conda-forge brent-search
An alternative way would be via pip_
.. code:: bash
pip install brent-search
Running the tests
-----------------
After installation, you can test it
.. code:: bash
python -c "import brent_search; brent_search.test()"
as long as you have pytest_.
Authors
-------
* `Danilo Horta`_
License
-------
This project is licensed under the MIT License - see the
LICENSE_ file for details.
.. |Build-Status| image:: https://travis-ci.org/limix/brent-search.svg?branch=master
:target: https://travis-ci.org/limix/brent-search
.. |Codacy-Grade| image:: https://api.codacy.com/project/badge/Grade/259a10b874124d91bccf61e516522607
:target: https://www.codacy.com/app/danilo.horta/brent-search?utm_source=github.com&utm_medium=referral&utm_content=limix/brent-search&utm_campaign=Badge_Grade
.. |PyPI-Status| image:: https://img.shields.io/pypi/v/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |PyPI-Versions| image:: https://img.shields.io/pypi/pyversions/brent-search.svg
:target: https://pypi.python.org/pypi/brent-search
.. |Conda-Forge-Status| image:: https://anaconda.org/conda-forge/brent-search/badges/version.svg
:target: https://anaconda.org/conda-forge/brent-search
.. |Conda-Downloads| image:: https://anaconda.org/conda-forge/brent-search/badges/downloads.svg
:target: https://anaconda.org/conda-forge/brent-search
.. |LICENCE| image:: https://img.shields.io/pypi/l/brent-search.svg
:target: https://raw.githubusercontent.com/brent-search/brent-search/master/LICENCE
.. |PyTest| image:: http://docs.pytest.org/en/latest/
:target: http://docs.pytest.org/en/latest/
.. _LICENSE: https://raw.githubusercontent.com/limix/brent-search/master/LICENSE
.. _Danilo Horta: https://github.com/horta
.. _conda: http://conda.pydata.org/docs/index.html
.. _pip: https://pypi.python.org/pypi/pip
.. _pytest: http://docs.pytest.org/en/latest/
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