Open Source Unix Shell Mathematics Software

AlphaGeometry, developed by Google DeepMind, is a theorem-proving system that combines symbolic reasoning with deep learning to solve challenging geometry problems, such as those found in mathematical Olympiads. The repository provides the full implementation of DDAR (Deductive Difference and Abductive Reasoning) and AlphaGeometry, two automated geometry solvers described in the 2024 Nature paper “Solving Olympiad Geometry without Human Demonstrations.” AlphaGeometry integrates a symbolic deduction engine with a transformer-based language model to propose and validate geometric constructions in a stepwise proof process. The DDAR solver focuses purely on rule-based reasoning, while AlphaGeometry enhances this by using a learned model to suggest auxiliary constructions when logical reasoning alone is insufficient. The repository includes pre-trained weights, vocabulary files, and detailed configuration options for reproducing experiments.

This project is for maintaining a linux system that concentrates on math, logic, and geometry related softwares.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

A set of Unix command line tools for quick and convenient batch processing of tabular text files (a.k.a., tab-delimited, csv, or flat file format) with a header line. Provides delimiter and compression detection, column reference by name. * tblmap: per-line ("map") computation: derive columns through an expression, delete, reorder, filter rows. * tblred: compute ("reduce") aggregations (e.g., sum, average) over groups defined by key columns. * tbldesc: Summarize columns in file (e.g., proportion of character/numeric values, min/mean/median/max, missing values, correlation with a target column). * tbljoin: Relational join without the need of pre-sorting and column matching. * ... See HostedApps/MediaWiki for examples.

That project aims at studying and comparing typical airline IT methods, for instance RM-related algorithms. It works from a Unix/Linux/Mac command-line, and exposes basic APIs. It is being developed in C++, with Python wrappers for some components.

Uma calculadora desenvolvida em C, com interface gráfica em Python.

This collection of tools forms the basis of a pipeline for the complete enumeration of the number of solutions present in a model that maximizes a single objective function.

xLaDe is a simple Python-based CLI tool built for executing and preserving Lean 4 projects. It is an ecosystem-level tool, which records the toolchain and other metadata of projects and allows the reconstruction and rebuilding of that exact environment later. Lean 4 undergoes rapid development, which can introduce backward-compatibility issues. This problem becomes more difficult as the versions accumulate over time. xLaDe is built to mitigate the practical issues of backward-compatibility problems and improve ecosystem-level tooling for the Lean 4 theorem prover. Instead of directly solving backward-compatibility issues by storing every version of Lean 4 and other tools or providing cross-version compatibility, xLaDe tries to store sufficient environment metadata such as toolchains, dependencies, and other context, and then recreates the environment for running Lean 4 projects upon request, also termed as experiments in xLaDe.