Search Results for "python distributed list"

... a catalog of change types so callers can interpret or filter specific transformations. It is distributed via npm and requires Node.js greater than version 6, with a straightforward API that fits neatly into web or server environments. The repository includes tests and contribution guidelines, making it approachable for developers who want to extend or adapt the behavior for their own applications.

The General Mission Analysis Tool (GMAT) is an open-source tool for space mission design and navigation. GMAT is developed by a team of NASA, private industry, and public and private contributors. The GMAT development team is pleased to announce the release of GMAT version R2025a. For a complete list of new features, compatibility changes, and bug fixes, see the R2025a Release Notes in the Users Guide.

NZMATH is a Python calculator on number theory. It is freely available and distributed under the BSD license. All programs are written only by Python so that you can easily see their algorithmic number theory. You can get NZMATH with a single command: % python -m pip install -U nzmath Here % is the command line prompt of Windows or Unix/macOS. This release contains several program corrections and additions obtained by writing a programming "notebook" of the book 'Lectures...

PyDQP implementes 11 different dual decomposition schemes, both first and second order, in order to solve quadratic programs in a distributed fashion.

The Felo rating system provides an objective fencing strength estimate for each individual fencer in a group, just like the Elo rating in chess. This program calculates the Felo numbers by analysing a bout result list created by the user.

Moved to Google Code, see http://code.google.com/p/pythonequations/downloads/list

TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.

RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.