pySOT

Surrogate Optimization Toolbox

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Project description

pySOT: Surrogate Optimization Toolbox

pySOT is an asynchronous parallel optimization toolbox for global deterministic optimization problems. The main purpose of the toolbox is for optimization of computationally expensive black-box objective functions with continuous and/or integer variables where the number of evaluations is limited. If there are several processors available it may make sense to evaluate the objective function using either asynchronous or synchronous parallel. pySOT uses the event-driven framework for asynchronous optimization strategies POAP (https://github.com/dbindel/POAP) to provide this functionality.

The toolbox is hosted on GitHub: https://github.com/dme65/pySOT

Documentation: http://pysot.readthedocs.io/

pySOT has been downloaded 17,945 times from 2015-June-4 to 2016-Dec-7

Installation

Installation instructions are available at: http://pysot.readthedocs.io/en/latest/quickstart.html

Examples

Several pySOT examples can be found at: https://github.com/dme65/pySOT/tree/master/pySOT/test

News

A two-hour short course on how to use pySOT was given at the CMWR 2016 conference in Toronto. The slides and Python notebooks can be downloaded from: https://people.cam.cornell.edu/~dme65/talks.html

Check out the new C++ implementation of pySOT: https://github.com/dme65/SOT

Check out the new pySOT documentation: http://pysot.readthedocs.io/

pySOT now has support for Python 3.

FAQ

Q: I can’t find the GUI
A: You need to install PySide

Q: I can’t find the MARS interpolant
A: You need to install py-earth in order to use MARS. More information is
available here: https://github.com/scikit-learn-contrib/py-earth

Q: Can I use pySOT with MPI?
A: Yes. You need to install mpi4py in order to use the MPIController in POAP.

Q: I used pySOT for my research and want to cite it
A: There is currently no published paper on pySOT so we recommend
citing pySOT like this: D. Eriksson, D. Bindel, and C. Shoemaker.
Surrogate Optimization Toolbox (pySOT). github.com/dme65/pySOT, 2015

Q: Is there support for Python 3?
A: Yes, as of version 0.1.31.

Project details

These details have not been verified by PyPI

Project links

Homepage

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

0.3.3

Jun 22, 2020

0.3.2

Jun 19, 2020

0.3.1

Jun 18, 2020

0.3.0

Jun 17, 2020

0.2.3

Jul 5, 2019

0.2.2

Feb 13, 2019

0.2.1

Jan 28, 2019

0.2.0

Dec 7, 2018

0.1.36

Jul 21, 2017

0.1.35

Apr 27, 2017

0.1.34

Mar 28, 2017

This version

0.1.33

Dec 26, 2016

0.1.32

Dec 7, 2016

0.1.31

Nov 24, 2016

0.1.30

Nov 19, 2016

0.1.29

Oct 20, 2016

0.1.28

Oct 20, 2016

0.1.27

Oct 18, 2016

0.1.26

Oct 16, 2016

0.1.25

Sep 14, 2016

0.1.24

Aug 4, 2016

0.1.23

Jul 28, 2016

0.1.22

Jun 28, 2016

0.1.21

Jun 23, 2016

0.1.20

Jun 18, 2016

0.1.19

Jan 30, 2016

0.1.18

Jan 25, 2016

0.1.17

Jan 13, 2016

0.1.16

Jan 7, 2016

0.1.15

Sep 23, 2015

0.1.14

Sep 22, 2015

0.1.13

Sep 3, 2015

0.1.12

Jul 23, 2015

0.1.11

Jul 22, 2015

0.1.10

Jul 14, 2015

0.1.9

Jul 13, 2015

0.1.8

Jul 1, 2015

0.1.7

Jul 1, 2015

0.1.6

Jun 29, 2015

0.1.5

Jun 28, 2015

0.1.4

Jun 27, 2015

0.1.3

Jun 26, 2015

0.1.2

Jun 25, 2015

0.1.1

Jun 23, 2015

0.1.0

Jun 4, 2015

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pySOT-0.1.33.tar.gz (662.3 kB view hashes)

Uploaded Dec 26, 2016 Source

Hashes for pySOT-0.1.33.tar.gz

Hashes for pySOT-0.1.33.tar.gz
Algorithm	Hash digest
SHA256	`382ef0a869e5ab0b5fd19295e9135168e7ef50b6f51a633141d0683406714217`
MD5	`dd41d0e69c688d936e12c60966c71895`
BLAKE2b-256	`1a201c0128693186941d995d041324fcf3103f208d212429735a552f877c8183`