Finite difference weights for any derivative order on arbitrarily spaced grids.
Project description
finitediff
==========
.. image:: http://hera.physchem.kth.se:9090/api/badges/bjodah/finitediff/status.svg
:target: http://hera.physchem.kth.se:9090/bjodah/finitediff
:alt: Build status
.. image:: https://img.shields.io/pypi/v/finitediff.svg
:target: https://pypi.python.org/pypi/finitediff
:alt: PyPI version
.. image:: https://img.shields.io/badge/python-2.7,3.4,3.5-blue.svg
:target: https://www.python.org/
:alt: Python version
.. image:: https://img.shields.io/pypi/l/finitediff.svg
:target: https://github.com/bjodah/finitediff/blob/master/LICENSE
:alt: License
.. image:: http://hera.physchem.kth.se/~finitediff/branches/master/htmlcov/coverage.svg
:target: http://hera.physchem.kth.se/~finitediff/branches/master/htmlcov
:alt: coverage
``finitediff`` containts two implementations (`Fortran 90
<src/finitediff_fort.f90>`_ and `C++ <include/finitediff_templated.hpp>`_) version of Begnt Fornberg's
formulae for generation of finite difference weights on aribtrarily
spaced one dimensional grids. The finite difference weights can be
used for optimized inter-/extrapolation data series for up to
arbitrary derivative order. Python_ bindings are provided.
.. _Python: https://www.python.org
.. _finitediff: https://github.com/bjodah/finitediff
Capabilities
============
finitediff currently provides callbacks for estimation of derivatives
or interpolation either at a single point or over an array (available
from the Python bindings).
The user may also manually generate the corresponding weights. (see
``populate_weights``)
Documentation
-------------
Autogenerated API documentation for latest stable release is found here:
`<https://pythonhosted.org/finitediff>`_
(and development docs for the current master branch are found here:
`<http://hera.physchem.kth.se/~finitediff/branches/master/html>`_).
Installation
------------
Simplest way to install finitediff is to use the
`Conda package manager <http://conda.pydata.org/docs/>`_:
::
$ conda install -c bjodah finitediff pytest
alternatively you may also use `pip`:
::
$ python -m pip install --user finitediff
(you can skip the ``--user`` flag if you have got root permissions), to run the
tests you need ``pytest`` too:
::
$ python -m pip install --user --upgrade pytest
$ python -m pytest --pyargs finitediff
Dependencies
============
You need either a C++ or a Fortran 90 compiler. On a debian based
linux system you can install it easily by typing:
``$ sudo apt-get install gfortran g++``
Optional dependencies (for Python bindings):
- Python header files (``sudo apt-get install python-dev``)
- Python_ (tested with 2.7)
- NumPy_
- Cython_
- pycompilation_ (optional: enables use from python)
- pytest_ (``sudo apt-get install python-pytest``)
- matplotlib_ (``sudo apt-get install python-matplotlib``)
See `requirements.txt <requirements.txt>`_ for detailed information of versions tested for.
For all dependencies the following command may be issued on a debian
based system:
::
$ sudo apt-get install gfortran g++ python2.7 libpython2.7-dev
python-numpy cython python-pip python-pytest python-matplotlib; sudo
pip install --upgrade -r https://raw.github.com/bjodah/finitediff/v0.1.10/requirements.txt``
.. _NumPy: http://www.numpy.org/
.. _pycompilation: https://github.com/bjodah/pycompilation
.. _pytest: http://pytest.org/
.. _matplotlib: http://matplotlib.org/
Notes
=====
There is a git subtree under finitediff, update through:
``git subtree pull --prefix finitediff/newton_interval newton_interval master --squash``
where the repo "newton_interval" is https://github.com/bjodah/newton_interval.git
First time you need to add it:
``git remote add -f newton_interval https://github.com/bjodah/newton_interval.git``
(Users of Ubuntu 12.04 who want to use git subtree, see http://stackoverflow.com/questions/17797328)
References
==========
The algortihm is a Fortran 90 rewrite of:
http://dx.doi.org/10.1137/S0036144596322507
::
@article{fornberg_classroom_1998,
title={Classroom note: Calculation of weights in finite difference formulas},
author={Fornberg, Bengt},
journal={SIAM review},
volume={40},
number={3},
pages={685--691},
year={1998},
publisher={SIAM}
doi={10.1137/S0036144596322507}
}
Which is based on an article of the same author:
http://dx.doi.org/10.1090/S0025-5718-1988-0935077-0
::
@article{fornberg_generation_1988,
title={Generation of finite difference formulas on arbitrarily spaced grids},
author={Fornberg, Bengt},
journal={Mathematics of computation},
volume={51},
number={184},
pages={699--706},
year={1988}
doi={10.1090/S0025-5718-1988-0935077-0}
}
License
=======
Open Source. Released under the very permissive "simplified
(2-clause) BSD license". See LICENSE.txt for further details.
Authors
=======
See file `AUTHORS <AUTHORS>`_ in root.
==========
.. image:: http://hera.physchem.kth.se:9090/api/badges/bjodah/finitediff/status.svg
:target: http://hera.physchem.kth.se:9090/bjodah/finitediff
:alt: Build status
.. image:: https://img.shields.io/pypi/v/finitediff.svg
:target: https://pypi.python.org/pypi/finitediff
:alt: PyPI version
.. image:: https://img.shields.io/badge/python-2.7,3.4,3.5-blue.svg
:target: https://www.python.org/
:alt: Python version
.. image:: https://img.shields.io/pypi/l/finitediff.svg
:target: https://github.com/bjodah/finitediff/blob/master/LICENSE
:alt: License
.. image:: http://hera.physchem.kth.se/~finitediff/branches/master/htmlcov/coverage.svg
:target: http://hera.physchem.kth.se/~finitediff/branches/master/htmlcov
:alt: coverage
``finitediff`` containts two implementations (`Fortran 90
<src/finitediff_fort.f90>`_ and `C++ <include/finitediff_templated.hpp>`_) version of Begnt Fornberg's
formulae for generation of finite difference weights on aribtrarily
spaced one dimensional grids. The finite difference weights can be
used for optimized inter-/extrapolation data series for up to
arbitrary derivative order. Python_ bindings are provided.
.. _Python: https://www.python.org
.. _finitediff: https://github.com/bjodah/finitediff
Capabilities
============
finitediff currently provides callbacks for estimation of derivatives
or interpolation either at a single point or over an array (available
from the Python bindings).
The user may also manually generate the corresponding weights. (see
``populate_weights``)
Documentation
-------------
Autogenerated API documentation for latest stable release is found here:
`<https://pythonhosted.org/finitediff>`_
(and development docs for the current master branch are found here:
`<http://hera.physchem.kth.se/~finitediff/branches/master/html>`_).
Installation
------------
Simplest way to install finitediff is to use the
`Conda package manager <http://conda.pydata.org/docs/>`_:
::
$ conda install -c bjodah finitediff pytest
alternatively you may also use `pip`:
::
$ python -m pip install --user finitediff
(you can skip the ``--user`` flag if you have got root permissions), to run the
tests you need ``pytest`` too:
::
$ python -m pip install --user --upgrade pytest
$ python -m pytest --pyargs finitediff
Dependencies
============
You need either a C++ or a Fortran 90 compiler. On a debian based
linux system you can install it easily by typing:
``$ sudo apt-get install gfortran g++``
Optional dependencies (for Python bindings):
- Python header files (``sudo apt-get install python-dev``)
- Python_ (tested with 2.7)
- NumPy_
- Cython_
- pycompilation_ (optional: enables use from python)
- pytest_ (``sudo apt-get install python-pytest``)
- matplotlib_ (``sudo apt-get install python-matplotlib``)
See `requirements.txt <requirements.txt>`_ for detailed information of versions tested for.
For all dependencies the following command may be issued on a debian
based system:
::
$ sudo apt-get install gfortran g++ python2.7 libpython2.7-dev
python-numpy cython python-pip python-pytest python-matplotlib; sudo
pip install --upgrade -r https://raw.github.com/bjodah/finitediff/v0.1.10/requirements.txt``
.. _NumPy: http://www.numpy.org/
.. _pycompilation: https://github.com/bjodah/pycompilation
.. _pytest: http://pytest.org/
.. _matplotlib: http://matplotlib.org/
Notes
=====
There is a git subtree under finitediff, update through:
``git subtree pull --prefix finitediff/newton_interval newton_interval master --squash``
where the repo "newton_interval" is https://github.com/bjodah/newton_interval.git
First time you need to add it:
``git remote add -f newton_interval https://github.com/bjodah/newton_interval.git``
(Users of Ubuntu 12.04 who want to use git subtree, see http://stackoverflow.com/questions/17797328)
References
==========
The algortihm is a Fortran 90 rewrite of:
http://dx.doi.org/10.1137/S0036144596322507
::
@article{fornberg_classroom_1998,
title={Classroom note: Calculation of weights in finite difference formulas},
author={Fornberg, Bengt},
journal={SIAM review},
volume={40},
number={3},
pages={685--691},
year={1998},
publisher={SIAM}
doi={10.1137/S0036144596322507}
}
Which is based on an article of the same author:
http://dx.doi.org/10.1090/S0025-5718-1988-0935077-0
::
@article{fornberg_generation_1988,
title={Generation of finite difference formulas on arbitrarily spaced grids},
author={Fornberg, Bengt},
journal={Mathematics of computation},
volume={51},
number={184},
pages={699--706},
year={1988}
doi={10.1090/S0025-5718-1988-0935077-0}
}
License
=======
Open Source. Released under the very permissive "simplified
(2-clause) BSD license". See LICENSE.txt for further details.
Authors
=======
See file `AUTHORS <AUTHORS>`_ in root.
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