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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 interpretative language of Sage is Python, a mainstream programming language. Use Sage for studying a huge range of mathematics ... [More] , 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 #sagemath on freenode IRC. [Less]

4.72727
   
  0 reviews  |  42 users  |  630,996 lines of code  |  141 current contributors  |  Analyzed 7 days ago
 
 

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 NLP tasks, with distributions for Windows, Mac OSX and Linux.

5.0
 
  0 reviews  |  40 users  |  214,336 lines of code  |  43 current contributors  |  Analyzed 5 days ago
 
 

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, generalization testing), a number of implementations of some popular algorithms (e.g. kNN, Ridge ... [More] 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]

5.0
 
  0 reviews  |  9 users  |  113,476 lines of code  |  7 current contributors  |  Analyzed 1 day ago
 
 

Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. The source ... [More] 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 host our website, bug tracker, and mailing lists. [Less]

4.66667
   
  0 reviews  |  8 users  |  248,710 lines of code  |  31 current contributors  |  Analyzed 1 day ago
 
 

That project aims at providing a clean API, and the corresponding C++ implementation, for the basis of Airline IT Business Object Model (BOM), ie, to be used by several other Open Source projects, such as RMOL, Air-Sched, Travel-CCM, OpenTREP, etc.

4.75
   
  0 reviews  |  5 users  |  29,481 lines of code  |  4 current contributors  |  Analyzed 3 days ago
 
 
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The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets ... [More] can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. You can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets; you don't need to know anything special about HDF5 to get started. Best of all, the files you create are in a standard binary format you can exchange with other people, including those who use programs like IDL and MATLAB. [Less]

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  0 reviews  |  4 users  |  4,842 lines of code  |  2 current contributors  |  Analyzed 5 months ago
 
 

graph-tool is a python module to help with statistical analysis of graphs. Its feature set includes support for both directed and undirected graphs with arbitrary vertex and edge properties, edge/vertex filtering, correlated random graph generation and community detection. It supports also ... [More] several statistical measurements, such as: degree histogram, combined degree histogram, vertex-vertex degree correlation, average nearest neighbours degree, vertex-edge-vertex correlation, clustering coefficients, extended clustering coefficient, assortativity coefficient, betweenness centrality, average distance, component statistics and reciprocity. The core algorithms are written in C++, making use of the Boost Graph Library, and template metaprogramming techniques, with performance in mind. [Less]

5.0
 
  0 reviews  |  4 users  |  50,876 lines of code  |  1 current contributor  |  Analyzed 4 days ago
 
 
5.0
 
  0 reviews  |  3 users  |  13,087 lines of code  |  21 current contributors  |  Analyzed 1 day ago
 
 

ESPResSo++ is a highy versatile, parallelized, scientific simulation software for coarse-grained simulations of atomic and molecular systems. ESPResSo++ is the descendant of the ESPResSo simulation software. It is implemented in C++ and controlled via Python.

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  0 reviews  |  3 users  |  40,096 lines of code  |  10 current contributors  |  Analyzed 7 days ago
 
 

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. Whenever possible igraph tries to be also user friendly and portable. igraph started as an additional ... [More] 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]

5.0
 
  0 reviews  |  2 users  |  449,261 lines of code  |  5 current contributors  |  Analyzed about 17 hours ago
 
 
 
 

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