Projects tagged ‘python’ and ‘science’

Sage is mathematical software, very much in the same vein as Matlab, MAGMA, Maple, and Mathematica. Unlike these systems, every component of Sage is GPL-compatible. The interpretaive language of Sage ... [More] is Python, a mainstream programming language. Use Sage for studying a huge range of mathematics, including algebra, calculus, elementary to very advanced number theory, cryptography, numerical computation, commutative algebra, group theory, combinatorics, graph theory, and exact linear algebra. It is available for download from sagemath.org and its mirrors in source or binary form. If you have any questions and/or problems please report them to the Google groups sage-devel or sage-support. You can also drop by in #sage-devel or #sage-support in freenode. [Less]

NLTK — the Natural Language Toolkit — is a suite of open source Python modules, linguistic data and documentation for research and development in natural language processing, supporting dozens of ... [More] NLP tasks, with distributions for Windows, Mac OSX and Linux. [Less]

Python module to ease pattern classification analyses of large datasets. It provides high-level abstraction of typical processing steps (e.g. data preparation, classification, feature selection ... [More] , generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge Regressions, Sparse Multinomial Logistic Regression, GPR. RFE, I-RELIEF), and bindings to external ML libraries (libsvm, shogun, R). While it is not limited to neuroimaging data (e.g. FMRI) it is eminently suited for such datasets. [Less]

The Biopython Project is an international association of developers of freely available Python tools for computational molecular biology. It is a distributed collaborative effort to develop Python ... [More] libraries and applications which address the needs of current and future work in bioinformatics. The source code is made available under the Biopython License, which is extremely liberal and compatible with almost every license in the world. We work along with the Open Bioinformatics Foundation, who generously provide web and CVS space for the project. [Less]

This is another library for creating and manipulating graphs. There is simply no other graph library out there which can be handle graphs of the size the author is confronted with efficiently. ... [More] Whenever possible igraph tries to be also user friendly and portable. igraph started as an additional package to the GNU R statistical environment, and still some functions which are hard to implement in C are available only in R (like interactive graphics). Most functions are however now written in C and they can be compiled without R as a separate library. [Less]

A program to analyze Laue diffraction diagrams.

PyMCT Start PageIntroductionPyMCT consists of a suite of software packages necessary to build and run a Python Coupler like PyCCSM. MCT is a high performance regridding and parallel communication ... [More] package designed to address issues of coupling multiple scientific models on different scales and grids to one another. ArchitectureSystem OverviewPyMCT wraps the Fortran 90 MCT library and makes it available to Python Programmers. This wrapping is not normally possible due to complex issues with the many different interpretations of the Fortran 90 standard. However, a powrful tool, the CCA Babel project allowed us to address these issues and completely wrap the MCT functionality into Python. ComponentsThe following components are necessary to build and use MCT and PyMCT MCTFortran 90 Compiler MPI (we use MPICH2) BabelC, Java, and Fortran compilers ( Portland Group Fortran is NOT supported! ) Python Interpreter Chasm Numpy or Numeric Python array packages Python MPIThere are a number of Python bindings to MPI out there, but the only one that completely meets the requirements of our package is our own solution, MaroonMPI. Depending on your application you may have reasonable success with other bindings. NetCDFConfiguration and InstallationPlease see our InstallPyMCT page. [Less]

SatStress is a collection of software that's useful for analyzing the tidal stresses raised on icy satellites by a time varying potential, and for comparing those stresses to tectonic features mapped ... [More] on the surface of the satellite. It is based in part on the model described in "Modeling Stresses on Satellites due to Non-Synchronous Rotation and Orbital Eccentricity Using Gravitational Potential Theory"; J. Wahr, Z.A. Selvans, M.E. Mullen, A.C. Barr, G.C. Collins, M.M. Selvans, R.T. Pappalardo; Icarus (submitted 2008-03-06). [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]

C source for IAPWS95, IAPWS84 and Surface tension equations for calculating the properties of water and steam. There are other projects that implement these standard but have complicated wrappers; ... [More] this project presents simple code with very few wrappers. In addition, Python versions of IAPWS84 and IAPWS95 standards are included. The IAPWS95 code passes all the tests described in the relevant standard. The standard and tests can be found at www.iapws.org Comments, suggestions, patches and ideas for improvement are much appreciated. Please visit the download section to download the code. [Less]