Projects tagged ‘numerical’ and ‘science’

Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for ... [More] performing other numerical experiments. It may also be used as a batch-oriented language. [Less]

The GNU Scientific Library (GSL) is a numerical library for C and C++ programmers. The library provides a wide range of mathematical routines such as random number generators, special functions and ... [More] least-squares fitting. There are over 1000 functions in total with an extensive test suite. [Less]

DUNE, the Distributed and Unified Numerics Environment is a modular toolbox for solving partial differential equations (PDEs) with grid-based methods. It supports the easy implementation of methods ... [More] like Finite Elements (FE), Finite Volumes (FV), and also Finite Differences (FD). [Less]

The ATLAS (Automatically Tuned Linear Algebra Software) project is an ongoing research effort focusing on applying empirical techniques in order to provide portable performance. It provides C and ... [More] Fortran77 interfaces to a portably efficient BLAS implementation, as well as a few routines from LAPACK. [Less]

O2scl is an object-oriented library for numerics in C++ useful for solving, minimizing, differentiating, integrating, interpolating, fitting, and more. Classes operate on generic member functions and ... [More] generic vector types. Includes classes from GSL and CERNLIB. [Less]

Perl module for handling of numbers with arbitrary many uncertainties. Does automatic error propagation and scientific rounding. An extension for outputting the objects in LaTeX syntax is available.

XMDS is a code generator that integrates equations. You write them down in human readable form in a XML file, and it goes away and writes and compiles a C++ program that integrates those equations as ... [More] fast as it can possibly be done in your architecture. [Less]

Mastrave is a free software library written to perform vectorized computation and to be as far as possible compatible with both the GNU Octave and Matlab computing environments, offering general ... [More] purpose, portable and freely available features for the scientific community. Mastrave attempts to allow a more effective, quick interoperability between GNU Octave and Matlab users by using a reasonably well documented wrap around the main incompatibilities between those computing environments and by promoting a reasonably general idiom based on their common, stable syntagms. Mastrave is free software, which is software respecting your freedom. It is offered to the scientific community to promote the development of a free society more concerned about cooperation rather than competitiveness, heading toward knowledge and culture freedom. Copyright (C) 2005, 2006, 2007, 2008, 2009 Daniele de Rigo Verbatim copying and distribution of this entire article is permitted in any medium without royalty provided this notice is preserved. [Less]

The Finite Difference Template Library (FDTL) was created for the purposes of quickly solving partial differential equations using the finite difference method. It is implemented in C++ using both the ... [More] object oriented (OO) paradigm and generic programming techniques (templates). It is meant to be fast in the sense that the times required for theoretical preparation, software development and program execution are all small. The project was initially begun to solve a form of the Gross-Pitaevskii equation (describing the Bose-Einstein Condensate from low temperature physics) and source is available for an executable serving this purpose. [Less]

What is h5py?HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library, version 5. HDF5 is a versatile, mature scientific software library designed for the ... [More] fast, flexible storage of enormous amounts of data. From a Python programmer's perspective, HDF5 provides a robust way to store data, organized by name in a tree-like fashion. You can create datasets (arrays on disk) hundreds of gigabytes in size, and perform random-access I/O on desired sections. Datasets are organized in a filesystem-like hierarchy using containers called "groups", and accessed using the tradional POSIX /path/to/resource syntax. A generic NumPy interface to HDF5 dataH5py provides a simple, robust read/write interface to HDF5 data from Python. Existing Python and Numpy concepts are used for the interface; for example, datasets on disk are represented by a proxy class that supports slicing, and has dtype and shape attributes. HDF5 groups are presented using a dictionary metaphor, indexed by name. A major design goal of h5py is interoperability; you can read your existing data in HDF5 format, and create new files that any HDF5- aware program can understand. No Python-specific extensions are used; you're free to implement whatever file structure your application desires. Almost all HDF5 features are available from Python, including things like compound datatypes (as used with Numpy recarray types), HDF5 attributes, hyperslab and point-based I/O, and more recent features in HDF 1.8 like resizable datasets and recursive iteration over entire files. A foundation for other HDF5 applications in PythonIn addition to the NumPy-like high-level interface, the foundation of h5py is a near-complete wrapping of the HDF5 C API. It includes the majority of the API with the following major improvements: HDF5 identifiers are first-class objects which participate in Python reference counting HDF5 errors are automatically mapped to native Python exceptions Functions and methods take Python-style arguments; not all parameters are required The API closely follows existing conventions (e.g. H5Gopen() -> h5g.open()) Transparently supports both HDF5 1.6 and 1.8. Applications which want to access HDF5 data in a less-generic manner, or which need a different performance/flexibility ratio, can access HDF5 directly through this Python API. In this sense, the NumPy-like layer is itself an application written to the native HDF5 API. CompatibilityRuns on Linux, Mac OS-X and Windows Reads and writes standard HDF5 files (with no Python-specific extensions) Works with HDF5 versions 1.6.5 through 1.8.2 Here's a trivial example showing how to create a new HDF5 file and store a 100 x 20 array of floats: >>> f = h5py.File("myfile.hdf5", 'w') >>> f["MyDataset"] = numpy.ones((100,20))And to get your data back: >>> dset = f["MyDataset"] >>> subset = dset[20:80,:]See the links to the right for documentation, download and installation instructions. Contact email is "h5py" at the domain "alfven dot org". [Less]