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https://github.com/bjodah/pycvodes

Python wrapper around cvodes (from the sundials library)

https://github.com/bjodah/pycvodes

Science Score: 36.0%

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    CITATION.cff file
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    Links to: zenodo.org
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    Scientific vocabulary similarity
    Low similarity (14.6%) to scientific vocabulary

Keywords from Contributors

sde
Last synced: 10 months ago · JSON representation

Repository

Python wrapper around cvodes (from the sundials library)

Basic Info
  • Host: GitHub
  • Owner: bjodah
  • License: bsd-2-clause
  • Language: C++
  • Default Branch: master
  • Size: 10.1 MB
Statistics
  • Stars: 35
  • Watchers: 5
  • Forks: 5
  • Open Issues: 8
  • Releases: 61
Created almost 11 years ago · Last pushed 10 months ago
Metadata Files
Readme Changelog License Authors

README.rst 

pycvodes
========

.. image:: http://hera.physchem.kth.se:9090/api/badges/bjodah/pycvodes/status.svg
   :target: http://hera.physchem.kth.se:9090/bjodah/pycvodes
   :alt: Build status on private Drone server
.. image:: https://circleci.com/gh/bjodah/pycvodes.svg?style=svg
   :target: https://circleci.com/gh/bjodah/pycvodes
   :alt: Build status on CircleCI
.. image:: https://secure.travis-ci.org/bjodah/pycvodes.svg?branch=master
   :target: http://travis-ci.org/bjodah/pycvodes
   :alt: Build status on Travis-CI
.. image:: https://img.shields.io/pypi/v/pycvodes.svg
   :target: https://pypi.python.org/pypi/pycvodes
   :alt: PyPI version
.. image:: https://img.shields.io/pypi/l/pycvodes.svg
   :target: https://github.com/bjodah/pycvodes/blob/master/LICENSE
   :alt: License
.. image:: https://zenodo.org/badge/43224425.svg
   :target: https://zenodo.org/badge/latestdoi/43224425

`pycvodes `_ provides a
`Python `_ binding to the
`Ordinary Differential Equation `_
integration routines from `cvodes `_ in the
`SUNDIALS suite `_. ``pycvodes`` allows a user to numerically integrate
(systems of) differential equations. Note that routines for sensitivity analysis is not yet exposed in this binding (which makes
the functionality essentially the same as cvode). 

The following multistep methods are available:

- ``bdf``: Backward differentiation formula (of order 1 to 5)
- ``adams``: implicit Adams method (order 1 to 12)

Note that bdf (as an implicit stepper) requires a user supplied
callback for calculating the jacobian.

You may also want to know that you can use ``pycvodes`` from
`pyodesys `_
which can e.g. derive the Jacobian analytically (using SymPy). Pyodesys also provides
plotting functions, C++ code-generation and more.

Documentation
-------------
Autogenerated API documentation for latest stable release is found here:
``_
(and the development version for the current master branch are found here:
``_).

Installation
------------
Simplest way to install is to use the `conda package manager `_
and install the prebuilt binary from the `Conda Forge `_
channel. We recommend installing into a conda environment with only packages from
Conda Forge::

   $ conda create -n pycvodes -c conda-forge pycvodes pytest
   $ conda activate pycvodes
   (pycvodes)$ python -m pytest --pyargs pycvodes

tests should pass.

Manual installation
~~~~~~~~~~~~~~~~~~~
Binary distribution is available here:
``_

Source distribution is available here:
``_

When installing from source you can choose what lapack lib to link against by setting
the environment variable ``PYCVODES_LAPACK``, your choice can later be accessed from python:

.. code:: python

   >>> from pycvodes import config
   >>> config['LAPACK']  # doctest: +SKIP
   'lapack,blas'

If you use ``pip`` to install ``pycvodes``, note that prior to installing pycvodes, you will need
to install sundials (pycvodes>=0.12.0 requires sundials>=5.1.0, pycvodes<0.12 requires sundials<5)
and its development headers, with cvodes & lapack enabled

Examples
--------
The classic van der Pol oscillator (see `examples/van_der_pol.py `_)

.. code:: python

   >>> import numpy as np
   >>> from pycvodes import integrate_predefined  # also: integrate_adaptive
   >>> mu = 1.0
   >>> def f(t, y, dydt):
   ...     dydt[0] = y[1]
   ...     dydt[1] = -y[0] + mu*y[1]*(1 - y[0]**2)
   ... 
   >>> def j(t, y, Jmat, dfdt=None, fy=None):
   ...     Jmat[0, 0] = 0
   ...     Jmat[0, 1] = 1
   ...     Jmat[1, 0] = -1 - mu*2*y[1]*y[0]
   ...     Jmat[1, 1] = mu*(1 - y[0]**2)
   ...     if dfdt is not None:
   ...         dfdt[:] = 0
   ...
   >>> y0 = [1, 0]; dt0=1e-8; t0=0.0; atol=1e-8; rtol=1e-8
   >>> tout = np.linspace(0, 10.0, 200)
   >>> yout, info = integrate_predefined(f, j, y0, tout, atol, rtol, dt0,
   ...                                   method='bdf')
   >>> import matplotlib.pyplot as plt
   >>> series = plt.plot(tout, yout)
   >>> plt.show()  # doctest: +SKIP


.. image:: https://raw.githubusercontent.com/bjodah/pycvodes/master/examples/van_der_pol.png

For more examples see `examples/ `_, and rendered jupyter notebooks here:
``_


License
-------
The source code is Open Source and is released under the simplified 2-clause BSD license. See `LICENSE `_ for further details.

Contributors are welcome to suggest improvements at https://github.com/bjodah/pycvodes

Author
------
Björn I. Dahlgren, contact:

- gmail address: bjodah

See file `AUTHORS `_ in root for a list of all authors.

Owner

  • Name: Bjorn
  • Login: bjodah
  • Kind: user

GitHub Events

Total
  • Watch event: 1
  • Delete event: 1
  • Push event: 25
  • Pull request event: 2
  • Create event: 6
Last Year
  • Watch event: 1
  • Delete event: 1
  • Push event: 25
  • Pull request event: 2
  • Create event: 6

Committers

Last synced: about 3 years ago

All Time
  • Total Commits: 449
  • Total Committers: 3
  • Avg Commits per committer: 149.667
  • Development Distribution Score (DDS): 0.165
Past Year
  • Commits: 6
  • Committers: 1
  • Avg Commits per committer: 6.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Björn Dahlgren b****h@g****m 375
spcornelius s****s@g****m 73
Shyam Saladi s****i@u****m 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 13
  • Total pull requests: 96
  • Average time to close issues: 4 months
  • Average time to close pull requests: 4 days
  • Total issue authors: 12
  • Total pull request authors: 3
  • Average comments per issue: 4.38
  • Average comments per pull request: 0.41
  • Merged pull requests: 90
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • bjodah (2)
  • spcornelius (1)
  • smsaladi (1)
  • lohex (1)
  • yurivict (1)
  • moorepants (1)
  • Whitechapel-1888 (1)
  • Tom-Y-Liu (1)
  • jeremyagray (1)
  • Bltzmn (1)
  • animesh-garg (1)
  • kmaitreys (1)
Pull Request Authors
  • bjodah (89)
  • spcornelius (10)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 431 last-month
  • Total dependent packages: 1
    (may contain duplicates)
  • Total dependent repositories: 4
    (may contain duplicates)
  • Total versions: 95
  • Total maintainers: 1
pypi.org: pycvodes

Python binding for cvodes from the sundials library.

  • Versions: 73
  • Dependent Packages: 0
  • Dependent Repositories: 2
  • Downloads: 431 Last month
Rankings
Dependent packages count: 10.0%
Stargazers count: 11.4%
Dependent repos count: 11.6%
Forks count: 15.4%
Average: 16.4%
Downloads: 33.8%
Maintainers (1)
bjodah
Last synced: 10 months ago
conda-forge.org: pycvodes
  • Versions: 22
  • Dependent Packages: 1
  • Dependent Repositories: 2
Rankings
Dependent repos count: 20.2%
Dependent packages count: 29.0%
Average: 37.4%
Stargazers count: 46.3%
Forks count: 54.1%
Last synced: 10 months ago

Dependencies

setup.py pypi
  • numpy *