Matplotlib is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. Matplotlib can be used in Python scripts, the python and ipython shell, web application servers, and six graphical user interface toolkits.

This package provides an implementation of importlib.resources for older versions of Python.

Enum34 is the new Python stdlib enum module available in Python 3.4 backported for previous versions of Python from 2.4 to 3.3.

The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.

This module is primarily a backport of the Python 3.2 contextlib to earlier Python versions. Like contextlib, it provides utilities for common tasks involving decorators and context managers. It also contains additional features that are not part of the standard library.

Pyro is a Distributed Object Technology system written in Python that is designed to be easy to use. It resembles Java's Remote Method Invocation (RMI). It has less similarity to CORBA, which is a system and language independent Distributed Object Technology and has much more to offer than Pyro or RMI. Pyro 3.x is no longer maintained. New projects should use Pyro4 instead, which is the new Pyro version that is actively developed.

The goal of pathlib2 is to provide a backport of standard pathlib module which tracks the standard library module, so all the newest features of the standard pathlib can be used also on older Python versions.

Pathlib offers a set of classes to handle file system paths. It offers the following advantages over using string objects:

1. No more cumbersome use of os and os.path functions. Everything can be done easily through operators, attribute accesses, and method calls.

2. Embodies the semantics of different path types. For example, comparing Windows paths ignores casing.

3. Well-defined semantics, eliminating any inconsistencies or ambiguities (forward vs. backward slashes, etc.).

Library for atomic file writes using platform dependent tools for atomic file system operations.

Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. Six supports every Python version since 2.5. It is contained in only one Python file, so it can be easily copied into your project.

Qt is a cross-platform application and UI framework for developers using C++ or QML, a CSS & JavaScript like language.

The Georgia Tech Network Simulator (GTNets) is designed to allow network researchers to conduct simulation-based experiments to observe the behavior of moderate to large scale computer networks under a variety of conditions. The GTNets environment allows the creation of simulation network topologies (consisting of nodes and their associated communication links), and end–user applications describing the flow of data over the simulated topology.

SimGrid is a scientific instrument to study the behavior of large-scale distributed systems such as grids, "clouds", HPC, and P2P systems. It can be used to evaluate heuristics, prototype applications or even assess legacy MPI applications.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

This package provides classes and methods for dense and sparse matrices and operations on them using LAPACK and SuiteSparse.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

This package provides functions and datasets for the book "Modern Applied Statistics with S" (4th edition, 2002) by Venables and Ripley.

The lattice package provides a powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.