.. title:: Introduction ======================================================================== (py)oscode: Oscillatory ordinary differential equation solver ======================================================================== .. image:: https://codecov.io/gh/fruzsinaagocs/oscode/branch/joss-paper/graph/badge.svg :target: https://codecov.io/gh/fruzsinaagocs/oscode .. image:: https://travis-ci.org/fruzsinaagocs/oscode.svg?branch=master :target: https://travis-ci.org/fruzsinaagocs/oscode :alt: Travis CI build status .. image:: https://readthedocs.org/projects/oscode/badge/?version=latest :target: https://oscode.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status .. image:: https://badges.gitter.im/oscode-help/community.svg :target: https://gitter.im/oscode-help/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge :alt: Chat on gitter .. image:: https://img.shields.io/badge/License-BSD%203--Clause-blue.svg :target: https://opensource.org/licenses/BSD-3-Clause :alt: BSD 3-clause license | | .. contents:: :local: | About ----- ``oscode`` is a C++ tool with a Python interface that solves **osc**\illatory **o**\rdinary **d**\ifferential **e**\quations efficiently. It is designed to deal with equations of the form .. math:: \ddot{x}(t) + 2\gamma(t)\dot{x}(t) + \omega^2(t)x(t) = 0, where :math:`\gamma(t)` and :math:`\omega(t)` can be given as arrays. ``oscode`` makes use of an analytic approximation of :math:`x(t)` embedded in a stepping procedure to skip over long regions of oscillations, giving a reduction in computing time. The approximation is valid when the frequency :math:`\omega(t)` changes slowly relative to the timescales of integration, it is therefore worth applying when this condition holds for at least some part of the integration range. For the details of the numerical method used by ``oscode``, see the Citations section. Installation ------------ Dependencies ~~~~~~~~~~~~ Basic requirements for using the C++ interface: - C++11 or later - `Eigen `__ (a header-only library included in this source) The strictly necessary Python dependencies are automatically installed when you use `pip` or the `setup.py`. They are: - `numpy `__ The *optional* dependencies are: - for tests - `scipy `__ - `pytest `__ - for examples/plotting - `matplotlib `__ - `scipy `__ - for generating offline documentation - `sphinx `__ - `doxygen `__ - `breathe `__ - `exhale `__ Python ~~~~~~ ``pyoscode`` can be installed via pip .. code:: bash pip install pyoscode or via the setup.py .. code:: bash git clone https://github.com/fruzsinaagocs/oscode cd oscode python setup.py install --user You can then import ``pyoscode`` from anywhere. Omit the ``--user`` option if you wish to install globally or in a virtual environment. If you have any difficulties, check out the FAQs_ section below. You can check that things are working by running `tests/` (also ran by Travis continuous integration): .. code:: bash pytest tests/ C++ ~~~ ``oscode`` is a header-only C++ package, it requires no installation. .. code:: bash git clone https://github.com/fruzsinaagocs/oscode and then include the relevant header files in your C++ code: .. code:: c #include "solver.hpp" #include "system.hpp" Quick start ----------- Try the following quick examples. They are available in the `examples `__. Python ~~~~~~ :Introduction to pyoscode: |intro_binder| :Cosmology examples: |cosmology_binder| .. |intro_binder| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/fruzsinaagocs/oscode/joss-paper?filepath=examples/introduction_to_pyoscode.ipynb .. |cosmology_binder| image:: https://mybinder.org/badge_logo.svg :target: https://mybinder.org/v2/gh/fruzsinaagocs/oscode/joss-paper?filepath=examples/cosmology.ipynb .. image:: https://github.com/fruzsinaagocs/oscode/raw/master/pyoscode/images/spectra.gif :width: 800 C++ ~~~ :Introduction to oscode: `examples/burst.cpp` :To plot results from `burst.cpp`: `examples/plot_burst.py` To compile and run: .. code:: bash g++ -g -Wall -std=c++11 -c -o burst.o burst.cpp g++ -g -Wall -std=c++11 -o burst burst.o ./burst Documentation ------------- Documentation is hosted at `readthedocs `__. To build your own local copy of the documentation you can run: .. code:: bash cd pyoscode/docs make html Citation -------- If you use ``oscode`` to solve equations for a publication, please cite: - `Efficient method for solving highly oscillatory ordinary differential equations with applications to physical systems `__, - `Dense output for highly oscillatory numerical solutions `__ Contributing ------------ Any comments and improvements to this project are welcome. You can contribute by: - Opening and `issue `__ to report bugs and propose new features. - Making a pull request. Further help ------------ You can get help by submitting an issue or posting a message on `Gitter `__. FAQs ---- Installation ~~~~~~~~~~~~ 1. Eigen import errors: .. code:: bash pyoscode/_pyoscode.hpp:6:10: fatal error: Eigen/Dense: No such file or directory #include ^~~~~~~~~~~~~ Try explicitly including the location of your Eigen library via the ``CPLUS_INCLUDE_PATH`` environment variable, for example: .. code:: bash CPLUS_INCLUDE_PATH=/usr/include/eigen3 python setup.py install --user # or CPLUS_INCLUDE_PATH=/usr/include/eigen3 pip install pyoscode where ``/usr/include/eigen3`` should be replaced with your system-specific eigen location. Thanks ------ Many thanks to **Will Handley**, **Lukas Hergt**, **Anthony Lasenby**, and **Mike Hobson** for their support and advice regarding the algorithm behind `oscode`. There are many packages without which some part of `oscode` (e.g. testing and examples) wouldn't run as nicely and smoothly, thank you all developers for making and maintaining these open-source projects. A special thanks goes to the devs of `exhale `__ for making the beautiful C++ documentation possible. Changelog --------- - 1.1.2: current version - Dense output bug fix at the C++ interface - 1.1.1: - Support for mac and Windows OS at CI. - 1.1.0: - Users can now define w, g as functions in Python (pyoscode) and call the solver via pyoscode.solve_fn(...) - 1.0.6: - Fix issues related to dense output not being correctly generated, e.g. when timepoints at which dense output was asked for are in descending order, etc. - 1.0.5: - Fixes related to dense output generation - Support for w, g to be given as class member functions in C++ - Switched to GH actions for continuous integration, and fixed code such that unit tests would run again - Minor tweaks - 1.0.4: - set minimally required numpy version: numpy>=1.20.0 - drop Python 2.7 support, instead support 3.8 and 3.9 in addition to 3.7 - 1.0.3: - paper accepted to JOSS - 1.0.2: - Fixed getting correct numpy include directories - 1.0.1: - Added `pyproject.toml` to handle build dependencies (numpy) - 1.0.0: - Dense output - Arrays for frequency and damping term need not be evenly spaced - Automatic C++ documentation on readthedocs - Eigen included in source for pip installability - First pip release :) - 0.1.2: - Bug that occurred when beginning and end of integration coincided corrected - 0.1.1: - Automatic detection of direction of integration - 0.1.0: - Memory leaks at python interface fixed - C++ documentation added