Skip to main content

Numerical integration technique

Project description

https://raw.github.com/saullocastro/cubature/master/cubature_logo.png

Cubature

Build status

Coverage

Note: Coverage not taking into account Cython / C files

What is Cubature?

It is a numerical integration technique. From MathWorld, Ueberhuber (1997, p. 71) and Krommer and Ueberhuber (1998, pp. 49 and 155-165) use the word “quadrature” to mean numerical computation of a univariate integral, and “cubature” to mean numerical computation of a multiple integral.

Documentation

Please, see the module documentation here.

Python wrapper for the Cubature package

From the Nanostructures and Computation Wiki at MIT, Steven W. Johnson has written a simple C package for adaptive multidimensional integration (cubature) of vector-valued functions over hypercubes and this is a Python wrapper for the referred C package.

Installation

Installation from source code …

You must have Cython installed. Then do:

python setup.py install

or (usually in Linux):

python3 setup.py install

Installation from pip repository …

Just do:

pip install cubature

or (usually in Linux):

pip3 install cubature

Running the tests

To run the tests you will have to download the source code. After installing as explained above, go to the source code root folder and run:

py.test .

The Python wrapper has been proven using test integrands from the C package and some additional testing functions from Genz. The integrands were implemented in Cython and verified with Mathematica.

Citing this Python wrapper for Cubature

We kindly ask you to cite this Python library properly. Also, it would be helpful if you could cite the papers where this methods has been applied as well.

Castro, S.G.P.; Loukianov, A.; et al. “Python wrapper for Cubature: adaptive multidimensional integration”. DOI:10.5281/zenodo.2541562. Version 0.14.0, 2018.

Citing Papers using this Python wrapper for Cubature

Used to integrate tangent stiffness matrices in computational solid mechanics

Castro, S.G.P. et al. “Evaluation of non-linear buckling loads of geometrically imperfect composite cylinders and cones with the Ritz method”. Composite Structures, Vol. 122, 284-299, 2015.

Castro, S.G.P. et al. “A semi-analytical approach for linear and non-linear analysis of unstiffened laminated composite cylinders and cones under axial, torsion and pressure loads”. Thin-Walled Structures, Vol. 90, 61-73, 2015.

Examples

Some examples are given in ./examples.

Fork me!

You are welcome to fork this repository and modify it in whatever way you want. It will also be nice if you could send a pull request here in case you think your modifications are valuable for another person.

License

This wrapper follows the GNU-GPL license terms of Steven G. Johnson described in the C Package.

Project details


Download files

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

Source Distribution

cubature-0.14.1.tar.gz (280.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cubature-0.14.1-cp36-cp36m-win_amd64.whl (10.5 MB view details)

Uploaded CPython 3.6mWindows x86-64

File details

Details for the file cubature-0.14.1.tar.gz.

File metadata

  • Download URL: cubature-0.14.1.tar.gz
  • Upload date:
  • Size: 280.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.14.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/39.0.1.post20190412 requests-toolbelt/0.9.1 tqdm/4.35.0 CPython/3.6.8

File hashes

Hashes for cubature-0.14.1.tar.gz
Algorithm Hash digest
SHA256 64689ce6617e258dfec761adfc94baf6181ee5f92610578a2e0f5d5478fa6a3a
MD5 c73ded989416a2554ea72cf427185bc1
BLAKE2b-256 ac316c53f2bc01abdd34f36855ef1780d8d7bda7fbfbb8af363130da3b67e801

See more details on using hashes here.

File details

Details for the file cubature-0.14.1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: cubature-0.14.1-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 10.5 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.14.0 pkginfo/1.5.0.1 requests/2.20.1 setuptools/39.0.1.post20190412 requests-toolbelt/0.9.1 tqdm/4.35.0 CPython/3.6.8

File hashes

Hashes for cubature-0.14.1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 0dce5aa0874e025d8df1d8e302731f2c1c9790d2e2b3f70281ac0f73df985fbe
MD5 6df04b59b44915ee8a2a927b7c51feec
BLAKE2b-256 6037a146d56265cd0ed8d319cf2548a4c78fad3abdce75c370fb4396fad6e748

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page