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Statistics::R will permit the control of the R (R-project) interpreter through Perl in different architectures and OS.

Regression.pm is a multivariate linear regression package. That is, it estimates the c coefficients for a line-fit of the type y= c(0)*x(0) + c(1)*x1 + c(2)*x2 + ... + c(k)*xk given a data set of N observations, each with k independent x variables and one y variable. Naturally, N must be greater than k---and preferably considerably greater. Any reasonable undergraduate statistics book will explain what a regression is. Most of the time, the user will provide a constant ('1') as x(0) for each observation in order to allow the regression package to fit an intercept.

This is the Statistical T-Test module to compare 2 independentsamples. It takes 2 array of point measures, compute the confidence intervals using the PointEstimation module (which is also included in this package) and use the T-statistic to test the null hypothesis. If the null hypothesis is rejected, the difference will be given as the lower_clm and upper_clm of the TTest object.

This python module implements constants and functions for working with IEEE754 double-precision special values. It provides constants for Not-a-Number (NaN), Positive Infinity (Inf), and Negative Infinity (-Inf), as well as functions to test for these values.

ParMETIS is an MPI-based parallel library that implements a variety of algorithms for partitioning unstructured graphs and for computing fill-reducing orderings of sparse matrices. ParMETIS extends the functionality provided by METIS and includes routines that are especially suited for parallel AMR computations and large scale numerical simulations. The algorithms implemented in ParMETIS are based on the parallel multilevel k-way graph-partitioning algorithms described in [KK95d], [KK96], [KK97], and the adaptive repartitioning algorithms described in [SKK97a], [SKK97b], [SK+98], and [SKK98].

ParMGridGen-1.0 is a highly optimized serial and parallel library for obtaining a sequence of successive coarse grids that are well suited for geometric multigrid methods. The quality of the elements of the coarse grids is optimized using a multilevel framework. The parallel library is based on MPI and is portable to a wide range of architectures.

This package provides Python bindings to CryptoMiniSat on the C++ level, i.e. when importing pycryptosat, the CryptoMiniSat solver becomes part of the Python process itself.

Numarray is a reimplementation of the original Python Numeric array module that provides Python with capbilities similar to Matlab, IDL, Octave, APL and other array-based languages. This version is still in its early stages and is not yet the official replacement for Numeric though we hope it will be before long. It is not fully backwards compatible with Numeric, particularly with regard to the C API.