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version 0.2.1

Python modules for Monte Carlo integration

People: Pascal Bugnion



scikit-monaco is a library for Monte Carlo integration in python. The core is
written in Cython, with process-level parallelism to squeeze the last bits of
speed out of the python interpreter.

A code snippet is worth a thousand words. Let\'s look at integrating
``sqrt(x**2 + y**2 + z**2)`` in the unit square:

.. code:: python

>>> from skmonaco import mcquad
>>> from math import sqrt
>>> result, error = mcquad(
... lambda xs: sqrt(xs[0]**2+xs[1]**2+xs[2]**2),
... npoints=1e6, xl=[0.,0.,0.], xu=[1.,1.,1.])
>>> print \"{} +/- {}\".format(result,error)
0.960695982212 +/- 0.000277843266684


* Home page:
* Documentation:
* Source code:
* Issues:


From Pypi

The easiest way to download and install scikit-monaco is from the Python
package index (pypi). Just run::

$ python easy_install scikit-monaco

Or, if you have pip::

$ pip install scikit-monaco

From source

Clone the repository using::

$ git clone

And run::

$ python install

in the project\'s root directory.


After the installation, run ``$ python`` in the package\'s root directory.

Issue reporting and contributing

Report issues using the `github issue tracker <>`_.

Read the CONTRIBUTING guide to learn how to contribute.



You can download the latest distribution from PyPI here:

Using pip

You can install scikit-monaco for yourself from the terminal by running:

pip install --user scikit-monaco

If you want to install it for all users on your machine, do:

pip install scikit-monaco
On Linux, do sudo pip install scikit-monaco.

If you don't yet have the pip tool, you can get it following these instructions.

This package was discovered in PyPI.