Metadata-Version: 1.1
Name: pycvodes
Version: 0.4.2
Summary: Python binding for cvodes from the sundials library.
Home-page: https://github.com/bjodah/pycvodes
Author: Björn Dahlgren
Author-email: bjodah@DELETEMEgmail.com
License: BSD
Description: pycvodes
        ========
        
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           :alt: PyPI version
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           :alt: License
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           :alt: coverage
        
        
        `pycvodes <https://github.com/bjodah/pycvodes>`_ provides a
        `Python <http://www.python.org>`_ binding to the
        `Ordinary Differential Equation <https://en.wikipedia.org/wiki/Ordinary_differential_equation>`_
        integration routines from `cvodes <https://computation.llnl.gov/casc/sundials/description/description.html#descr_cvodes>`_ in the
        `SUNDIALS suite <https://computation.llnl.gov/casc/sundials/main.html>`_. ``pcyvodes`` 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
        - adams
        
        Note that bdf (as an implicit stepper) require a user supplied
        callback for calculating the jacobian.
        
        Documentation
        -------------
        Autogenerated API documentation for latest stable release is found here:
        `<https://pythonhosted.org/pycvodes>`_
        (and development docs for the current master branch are found here:
        `<http://hera.physchem.kth.se/~pycvodes/branches/master/html>`_).
        
        Installation
        ------------
        Simplest way to install is to use the `conda package manager <http://conda.pydata.org/docs/>`_:
        
        ::
        
           $ conda install -c bjodah pycvodes pytest
           $ python -m pytest --pyargs pycvodes
        
        tests should pass.
        
        Binary distribution is available here:
        `<https://anaconda.org/bjodah/pycvodes>`_
        
        Source distribution is available here:
        `<https://pypi.python.org/pypi/pycvodes>`_
        
        Examples
        --------
        The classic van der Pol oscillator (see `examples/van_der_pol.py <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/ <https://github.com/bjodah/pycvodes/tree/master/examples>`_, and rendered jupyter notebooks here:
        `<http://hera.physchem.kth.se/~pycvodes/branches/master/examples>`_
        
        
        License
        -------
        The source code is Open Source and is released under the simplified 2-clause BSD license. See `LICENSE <LICENSE>`_ for further details.
        
        Contributors are welcome to suggest improvements at https://github.com/bjodah/pycvodes
        
        Author
        ------
        Björn I. Dahlgren, contact:
        
        - gmail address: bjodah
        - kth.se address: bda
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
