Skip to main content

Numerical tool for perfroming uncertainty quantification

Project description


circleci codecov pypi readthedocs

Chaospy is a numerical tool for performing uncertainty quantification using polynomial chaos expansions and advanced Monte Carlo methods implemented in Python.

If you are using this software in work that will be published, please cite the journal article: Chaospy: An open source tool for designing methods of uncertainty quantification


Installation should be straight forward:

pip install chaospy

And you should be ready to go.

Alternatively, to get the most current experimental version, the code can be installed from Github as follows:

git clone    # first time only
cd chaospy/
git pull                                        # after the first time
pip install .

Example Usage

chaospy is created to be simple and modular. A simple script to implement point collocation method will look as follows:

import chaospy
import numpy

# your code wrapper goes here
coordinates = numpy.linspace(0, 10, 100)
def foo(coordinates, params):
    """Function to do uncertainty quantification on."""
    return params[0] * numpy.e**(-params[1]*coordinates)

# bi-variate probability distribution
distribution = chaospy.J(chaospy.Uniform(1, 2), chaospy.Uniform(0.1, 0.2))

# polynomial chaos expansion
polynomial_expansion = chaospy.generate_expansion(8, distribution)

# samples:
samples = distribution.sample(1000)

# evaluations:
evals = [foo(coordinates, sample) for sample in samples.T]

# polynomial approximation
foo_approx = chaospy.fit_regression(
    polynomial_expansion, samples, evals)

# statistical metrics
expected = chaospy.E(foo_approx, distribution)
deviation = chaospy.Std(foo_approx, distribution)

For a more extensive description of what going on, see the collection of tutorials.


Development is done using Poetry manager. Inside the repository directory, install and create a virtual environment with:

poetry install

To run tests:

poetry run pytest chaospy/ tests/ doc/ --doctest-modules

To build documentation, run:

cd doc/
make html

The documentation will be generated into the folder doc/.build/html.

Questions and Contributions

Please feel free to file an issue for:

  • bug reporting
  • asking questions related to usage
  • requesting new features
  • wanting to contribute with code

Project details

Download files

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

Files for chaospy, version 3.3.2
Filename, size File type Python version Upload date Hashes
Filename, size chaospy-3.3.2-py2.py3-none-any.whl (232.6 kB) File type Wheel Python version py2.py3 Upload date Hashes View
Filename, size chaospy-3.3.2.tar.gz (142.8 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page