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dfbgn-0.1
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مشاهده بیشترتوضیحات
A derivative-free solver for large-scale nonlinear least-squares minimization
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dfbgn-0.1 |
| نام | dfbgn |
| نسخه کتابخانه | 0.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Lindon Roberts |
| ایمیل نویسنده | lindon.roberts@anu.edu.au |
| آدرس صفحه اصلی | https://github.com/numericalalgorithmsgroup/dfbgn/ |
| آدرس اینترنتی | https://pypi.org/project/dfbgn/ |
| مجوز | GNU GPL |
=========================================
DFBGN: Derivative-Free Block Gauss-Newton
=========================================
.. image:: https://travis-ci.org/numericalalgorithmsgroup/dfbgn.svg?branch=master
:target: https://travis-ci.org/numericalalgorithmsgroup/dfbgn
:alt: Build Status
.. image:: https://img.shields.io/badge/License-GPL%20v3-blue.svg
:target: https://www.gnu.org/licenses/gpl-3.0
:alt: GNU GPL v3 License
DFBGN is a Python package for nonlinear least-squares minimization, where derivatives are not available.
It is particularly useful when evaluations of the objective are expensive and/or noisy, and the number of variables to be optimized is large.
DFBGN is based on `DFO-LS <https://github.com/numericalalgorithmsgroup/dfols>`_, but is better-suited when there are many variables to be optimized (so the linear algebra in DFO-LS is too slow).
Unlike DFO-LS, DFBGN does not currently support bound constraints on the variables.
If you are interested in solving general optimization problems (without a least-squares structure), you may wish to try `Py-BOBYQA <https://github.com/numericalalgorithmsgroup/pybobyqa>`_.
Requirements
------------
DFBGN requires the following software to be installed:
* Python 2.7 or Python 3 (http://www.python.org/)
Additionally, the following python packages should be installed (these will be installed automatically if using *pip*, see `Installation using pip`_):
* NumPy 1.11 or higher (http://www.numpy.org/)
* SciPy 0.18 or higher (http://www.scipy.org/)
* Pandas 0.17 or higher (http://pandas.pydata.org/)
Installation using pip
----------------------
For easy installation, use `pip <http://www.pip-installer.org/>`_ as root:
.. code-block:: bash
$ [sudo] pip install dfbgn
or alternatively *easy_install*:
.. code-block:: bash
$ [sudo] easy_install dfbgn
If you do not have root privileges or you want to install DFBGN for your private use, you can use:
.. code-block:: bash
$ pip install --user dfbgn
which will install DFBGN in your home directory.
Note that if an older install of DFBGN is present on your system you can use:
.. code-block:: bash
$ [sudo] pip install --upgrade dfbgn
to upgrade DFBGN to the latest version.
Manual installation
-------------------
Alternatively, you can download the source code from `Github <https://github.com/numericalalgorithmsgroup/dfbgn>`_ and unpack as follows:
.. code-block:: bash
$ git clone https://github.com/numericalalgorithmsgroup/dfbgn
$ cd dfbgn
DFBGN is written in pure Python and requires no compilation. It can be installed using:
.. code-block:: bash
$ [sudo] pip install .
If you do not have root privileges or you want to install DFBGN for your private use, you can use:
.. code-block:: bash
$ pip install --user .
instead.
To upgrade DFBGN to the latest version, navigate to the top-level directory (i.e. the one containing :code:`setup.py`) and rerun the installation using :code:`pip`, as above:
.. code-block:: bash
$ git pull
$ [sudo] pip install . # with admin privileges
Testing
-------
If you installed DFBGN manually, you can test your installation by running:
.. code-block:: bash
$ python setup.py test
Alternatively, the HTML documentation provides some simple examples of how to run DFBGN.
Examples
--------
Examples of how to run DFBGN are given in the `documentation <https://numericalalgorithmsgroup.github.io/dfbgn/>`_, and the `examples <https://github.com/numericalalgorithmsgroup/dfbgn/tree/master/examples>`_ directory in Github.
Uninstallation
--------------
If DFBGN was installed using *pip* you can uninstall as follows:
.. code-block:: bash
$ [sudo] pip uninstall dfbgn
If DFBGN was installed manually you have to remove the installed files by hand (located in your python site-packages directory).
Bugs
----
Please report any bugs using GitHub's issue tracker.
License
-------
This algorithm is released under the GNU GPL license. Please `contact NAG <http://www.nag.com/content/worldwide-contact-information>`_ for alternative licensing.
نحوه نصب
نصب پکیج whl dfbgn-0.1:
pip install dfbgn-0.1.whl
نصب پکیج tar.gz dfbgn-0.1:
pip install dfbgn-0.1.tar.gz