Py-BOBYQA is a flexible package for solving bound-constrained general objective minimization, without requiring derivatives of the objective. It is a Python implementation of the BOBYQA algorithm by Powell. Py-BOBYQA is particularly useful when evaluations of the objective function are expensive and/or noisy.
More details about Py-BOBYQA can be found in our paper: C. Cartis, J. Fiala, B. Marteau and L. Roberts, Improving the Flexibility and Robustness of Model-Based Derivative-Free Optimization Solvers, technical report, University of Oxford, (2018).
The original paper by Powell is: M. J. D. Powell, The BOBYQA algorithm for bound constrained optimization without derivatives, technical report DAMTP 2009/NA06, University of Cambridge (2009), and the original Fortran implementation is available here.
If you are interested in solving least-squares minimization problems, you may wish to try DFO-LS, which has the same features as Py-BOBYQA (plus some more), and exploits the least-squares problem structure, so performs better on such problems.
Documentation
See manual.pdf or here.
Requirements
Py-BOBYQA 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 as root:
$ [sudo] pip install Py-BOBYQA
or alternatively easy_install:
$ [sudo] easy_install Py-BOBYQA
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use:
$ pip install --user Py-BOBYQA
which will install Py-BOBYQA in your home directory.
Note that if an older install of Py-BOBYQA is present on your system you can use:
$ [sudo] pip install --upgrade Py-BOBYQA
to upgrade Py-BOBYQA to the latest version.
Manual installation
Alternatively, you can download the source code from Github and unpack as follows:
$ git clone https://github.com/numericalalgorithmsgroup/pybobyqa $ cd pybobyqa
Py-BOBYQA is written in pure Python and requires no compilation. It can be installed using:
$ [sudo] pip install .
If you do not have root privileges or you want to install Py-BOBYQA for your private use, you can use:
$ pip install --user .
instead.
Testing
If you installed Py-BOBYQA manually, you can test your installation by running:
$ python setup.py test
Alternatively, the HTML documentation provides some simple examples of how to run Py-BOBYQA.
Examples
Examples of how to run Py-BOBYQA are given in the documentation, and the examples directory in Github.
Uninstallation
If Py-BOBYQA was installed using pip you can uninstall as follows:
$ [sudo] pip uninstall Py-BOBYQA
If Py-BOBYQA 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.
1 maintainer
Release files for Py-BOBYQA 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Py-BOBYQA-1.0.1.tar.gz | 33.6 kB | Details |
Release files / Py-BOBYQA-1.0.1.tar.gz
| Download URL | Py-BOBYQA-1.0.1.tar.gz |
|---|---|
| Size | 33.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
660f0869803bcc748cace58b04d8866d22054f7c8a25f029bef88e5964641815
|
|
BLAKE2b-256 checksum How to use checksums |
ba8b1a8c039b14799c817c42bef80907f93867609bede2725417d5cfb86f7212
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
