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The octave-forge package is the result of The GNU Octave Repositry project, which is intended to be a central location for custom scripts, functions and extensions for GNU Octave. contains the source for all the functions plus build and install scripts. This is level-set. Routines for calculating the time-evolution of the level-set equation and extracting geometric information from the level-set function.

Bit::ShiftReg is a perl module that implements rotate left, rotate right, arithmetic shift left, and logical shift right operations with carry flag for all C integer types. The results depend on the number of bits with that the integer types unsigned char, unsigned short, unsigned int, and unsigned long have on your machine. The module automatically determines the number of bits of each integer type and adjusts its internal constants accordingly.

This module provides a perl interface to the DCDFLIB. See the section on DCDFLIB for more information. Functions are available for 7 continuous distributions (Beta, Chi-square, F, Gamma, Normal, Poisson and T-distribution) and for two discrete distributions (Binomial and Negative Binomial). Optional non-centrality parameters are available for the Chi-square, F and T-distributions. Cumulative probabilities are available for all 9 distributions and quantile functions are available for the 7 continuous distributions.

RPy is a very simple, yet robust, Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions). All the errors from the R language are converted to Python exceptions. Any module that later were installed on the R system, can easily be used from within Python, without introducing any changes.

Set::IntSpan manages sets of integers. It is optimized for sets that have long runs of consecutive integers. These arise, for example, in .newsrc files, which maintain lists of articles: alt.foo: 1-21,28,31 alt.bar: 1-14192,14194,14196-14221 Sets are stored internally in a run-length coded form. This provides for both compact storage and efficient computation. In particular, set operations can be performed directly on the encoded representation.

This module provides basic functions used in descriptive statistics. It has an object oriented design and supports two different types of data storage and calculation objects: sparse and full. With the sparse method, none of the data is stored and only a few statistical measures are available. Using the full method, the entire data set is retained and additional functions are available. -Anton <tobez@FreeBSD.org>

The Statistics::LineFit module does weighted or unweighted least-squares line fitting to two-dimensional data (y = a + b * x). (This is also called linear regression.) In addition to the slope and y-intercept, the module can return the square of the correlation coefficient (R squared), the Durbin-Watson statistic, the mean squared error, sigma, the t statistics, the variance of the estimates of the slope and y-intercept, the predicted y values and the residuals of the y values.

The Set::IntSpan module represents sets of integers as a number of inclusive ranges, for example '1-10,19-23,45-48'. Because many of its operations involve linear searches of the list of ranges its overall performance tends to be proportional to the number of distinct ranges. This is fine for small sets but suffers compared to other possible set representations (bit vectors, hash keys) when the number of ranges grows large. Set::IntSpan::Fast tries to fix that.

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.

Mpmath is a pure-Python library for multiprecision floating-point arithmetic. It provides an extensive set of transcendental functions, unlimited exponent sizes, complex numbers, interval arithmetic, numerical integration and differentiation, root-finding, linear algebra, and much more. Almost any calculation can be performed just as well at 10-digit or 1000-digit precision, and in many cases mpmath implements asymptotically fast algorithms that scale well for extremely high precision work. If available, mpmath will (optionally) use gmpy to speed up high precision operations.