Numeric and Scientific

• NumPy - http://www.numpy.org/ -- Numerical Python adds a fast, compact, multidimensional array facility to Python. NumPy is the successor to both Numeric and Numarray.

  • Deprecated: Numeric -- Numerical Python adds a fast, compact, multidimensional array language facility to Python. (Note: superseded by NumPy)

  • Deprecated: NumArray - http://stsdas.stsci.edu/numarray/index.html -- Numarray is a reimplementation of Numeric which adds the ability to efficiently manipulate large numeric arrays in ways similar to Matlab and IDL. (Note: superseded by NumPy)

• SciPy - http://www.scipy.org/ SciPy is an open source library of scientific tools for Python. SciPy supplements the popular NumPy module, gathering a variety of high level science and engineering modules together as a single package. SciPy includes modules for linear algebra, optimization, integration, special functions, signal and image processing, statistics, genetic algorithms, ODE solvers, and others.

• Numba - http://numba.pydata.org/ Numba is an open source, NumPy-aware Python compiler specifically suited to scientific codes.

• ad is an open-source Python package for transparently performing first- and second-order automatic differentiation calculations with any of the base numeric types (int, float, complex, etc.). Utility functions designed for working with SciPy optimization routines.

• APM Python - http://apmonitor.com/wiki/index.php/Main/PythonApp APMonitor is a nonlinear programming and optimization environment with an interface to Python. The software is available as a web-service through Python libraries for the solution of large-scale mathematical programming problems.

• SymPy - http://www.sympy.org/ SymPy is a symbolic manipulation package, written in pure Python. Its aim is to become a full featured CAS in Python, while keeping the code as simple as possible in order to be comprehensible and easily extensible.

• ALGLIB - http://www.alglib.net/ - numerical analysis library in C++ and C#, with Python and IronPython interfaces.

• Python Data Analysis Library - http://pandas.pydata.org/ - pandas is a library providing high-performance, easy-to-use data structures and data analysis tools for the Python .

• PyGSL - http://pygsl.sourceforge.net/ -- This project provides a python interface for the GNU scientific library (gsl).

• FuncDesigner - http://openopt.org/FuncDesigner FuncDesigner is Python module to rapidly build functions and get their derivatives via automatic differentiation. Also you can perform integration, interpolation, interval analysis, uncertainty analysis, solve eigenvalue problems, systems of linear/non-linear/ODE equations and numerical optimization problems coded in FuncDesigner by OpenOpt.

• OpenOpt - http://openopt.org - a framework for numerical optimization and systems of linear/non-linear equations. Connects to dozens of solvers (some are C- or Fortran-written). Can optimize FuncDesigner models with automatic differentiation. Provides graphic output of convergence, multifactor analysis tool for scientific experiments planning and some more numerical optimization "MUST HAVE" features. Also OpenOpt has Stochastic Programming and Optimization addon (commercial yet, free for small-scaled academic and research purposes)

• SpaceFuncs - http://openopt.org/SpaceFuncs - a tool for 2D, 3D, N-dimensional geometric modeling with possibilities of parametrized calculations, numerical optimization and solving systems of geometrical equations with automatic differentiation.

• !NLopt - http://ab-initio.mit.edu/nlopt - another library for nonlinear optimization, including many local/global optimization algorithms written in C, with a Python interface (as well as interfaces for several other languages).

• jHepWork - http://jwork.org/jhepwork - a multiplatform data-analysis framework written in Java. The main programming language is Jython, a clone of Python written in Java. Contains Java libraries for numerical calculations and visualisation of scientific graphs. Contains an interactive Python prompt.

• ScientificPython - http://dirac.cnrs-orleans.fr/ScientificPython/ -- ScientificPython is a collection of Python modules that are useful for scientific computing. In this collection you will find modules that cover basic geometry (vectors, tensors, transformations, vector and tensor fields), quaternions, automatic derivatives, (linear) interpolation, polynomials, elementary statistics, nonlinear least-squares fits, unit calculations, Fortran-compatible text formatting, 3D visualization via VRML, and two Tk widgets for simple line plots and 3D wireframe models. There are also interfaces to the netCDF library (portable structured binary files), to MPI (Message Passing Interface, message-based parallel programming), and to BSPlib (Bulk Synchronous Parallel programming).

• PyACTS- http://wiki.python.org/moin/PyACTS -- PyACTS is a collection of Python Modules that are very useful to Parallel Computing in a High Performance Computing environment. This packages incorporates several modules like PyBLACS (allows communication data for Linear Algebra), PyPBLAS (distributed Matrix Operations) and PyScaLAPACK (solve linear systems and get the eigenvalue problems). These libraries are part of PyACTS project that provide interfaces to the ACTS Collection. Also is provided a parallel interpreter for using this package that implements message-based parallel programming using MPI.

• PyDSTool - http://pydstool.sourceforge.net -- PyDSTool is an integrated simulation, modeling and analysis package for dynamical systems (including ODEs, DAEs, maps, and hybrid systems) and scientific data. Building on SciPy classes, the package also supports symbolic expression processing, bifurcation analysis, and enhanced arrays for "index-free" and highly contextualized scientific data manipulation. Model building tools use symbolic expression and hierarchical specification classes to ease the development and analysis of complex models. This includes automated compilation of symbolic representations of models into fast numerical code using enhanced legacy Fortran and C integrators for both stiff and non-stiff systems.

• escript - https://launchpad.net/escript-finley -- escript is a Python module to define and solve coupled, non-linear, time-dependent partial differential equations (PDEs). The user has to implement high-level time integration schemes and iteration schemes to reduce the problem to the solution of steady, linear systems of PDEs which are solved by a suitable PDE solver library. The current version uses the FEM solver library finley but the design is open and other libraries can be used. escript is parallelized for OpenMP and MPI. It is compatible with NumPy and VTK for visualization.

• PyIMSL - http://www.roguewave.com/products/imsl-numerical-libraries/pyimsl-studio.aspx -- PyIMSL is a collection of Python wrappers to the mathematical and statistical algorithms in the IMSL C Numerical Library. PyIMSL offers a quality Python interface to the largest collection of portable statistical and analytical algorithms available for Python. Developers can use Python, PyIMSL and the IMSL C Library for rapid prototyping. They can then directly deploy the Python application into production or if they choose to rewrite the application in C/C++ use the same math and stats algorithms in both development environments. PyIMSL Studio is a packaged, supported and documented development environment designed for deploying mathematics and statistics prototype models into production applications. PyIMSL Studio includes the Python language distribution and contains both open source and proprietary components that create a fully supported and documented platform for analytic prototyping and production development. PyIMSL Studio is available for download at no charge for non-commercial use or for commercial evaluation.

• PyGTS - http://pygts.sourceforge.net/ -- PyGTS is a python package used to construct, manipulate, and perform computations on 3D triangulated surfaces. It is a hand-crafted and pythonic binding for the GNU Triangulated Surface (GTS) Library (http://gts.sourceforge.net/).

• scikit-learn - http://scikit-learn.sourceforge.net/ -- machine learning and data mining in Python, using NumPy and SciPy

• mlpy - https://mlpy.fbk.eu/ -- Machine Learning PYthon -- high-performance Python module for Predictive Modeling.

• graph-tool - http://graph-tool.skewed.de -- A python module for efficient analysis of graphs (aka. networks), with algorithms implemented in C++ with the Boost Graph Library.

• sppy - http://packages.python.org/sppy/index.html -- A sparse matrix package based on Eigen.

• Quandl - https://www.quandl.com/tools/python -- An API package to access http://quandl.com datasets, as well as upload data to Quandl.

Multi precision math

• MultiprecisionSoftwareDirectory (http://crd.lbl.gov/~dhbailey/mpdist/index.html) - Python wrapping unknown

• MAPM (http://www.tc.umn.edu/~ringx004/mapm-main.html) - Python wrapping unknown

• GmPy (http://gmpy.sourceforge.net/) - GNU Multiple Precision library wrapping

• mpmath - http://mpmath.org/