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:
>>> 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 +/- 0.000277843266684Links
Home page: https://pypi.python.org/pypi/scikit-monaco
Documentation: http://scikit-monaco.readthedocs.org/en/latest/
Source code: https://github.com/scikit-monaco/scikit-monaco
Issues: https://github.com/scikit-monaco/scikit-monaco/issues
Installation
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 https://github.com/scikit-monaco/scikit-monaco.git
And run:
$ python setup.py install
in the project’s root directory.
Testing
After the installation, run $ python runtests.py 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.
1 maintainer
Metadata
1 maintainer
Release files for scikit-monaco 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| scikit-monaco-0.2.1.tar.gz | 597.9 kB | Without provenance | Details for scikit-monaco-0.2.1.tar.gz |
Release files / scikit-monaco-0.2.1.tar.gz
| Download URL | scikit-monaco-0.2.1.tar.gz |
|---|---|
| Size | 597.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bb3d4e2a7830b6af68c82fb47ce12afe6dc332bf762f1ee823ef1e6c5ac17ba3
|
|
BLAKE2b-256 checksum How to use checksums |
5609d70ffb523e8eb7b53144fbd776b759c141eda88f0dc143d81673bcb5414b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for scikit-monaco 0.2.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
