Search Results for "graph"

...PyTensor is based on Theano, which has been powering large-scale computationally intensive scientific investigations since 2007. A hackable, pure-Python codebase. Extensible graph framework is suitable for rapid development of custom operators and symbolic optimizations. Implements an extensible graph transpilation framework that currently provides compilation via C, JAX, and Numba. Based on one of the most widely-used Python tensor libraries: Theano.

...It supports an agentic proving workflow where the system behaves more like an interactive mathematical engineer than a one-shot text generator. MathCode also includes visualization-oriented tooling such as theorem graph generation for Obsidian knowledge workflows. Its main value is bridging natural-language mathematics with formal verification systems in a way that is more automated, inspectable, and iterative than traditional theorem-proving pipelines.

It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of...

Gato (Graph Animation Toolbox): Animate graph algorithms for example for computing shortest paths, minimal spanning trees, maximum flows or maximal cardinality or weight matchings. Create your own animations using the Animated Data Structures (ADS).

... - Implemented a 3d surface plot (GLSurface) based on OpenGL (ScienPlot v1.3.2 and above) - ColorMap surface, trisurface, Pie, Polar plots, and 3D height field, 3dBar, scatter plots (under developing), and more - Column by column plotting/calculation - LaTex commands enclosed by $ symbols can be used for the labels in Graph - Accept txt(Text) and csv(Comma separated values) formatted data - Save, copy, print Graph - Use spread sheets to display data - Textboard to organize the results - Graphs in a publishable quality - Source codes based on: Python Numpy Scipy Matplotlib WxPython Visvis etc. - Special functions - Drag and drop data files - Python console is back (since v1.3.3), capable of reusing column data - Debye and Guinier models for SANS / SAX data - More apps in our Web below

This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.

An easy to use mathematical function graph plotter written in Python and GTK.

pyGraph is tool that hopefully will help graph theory students by analizing,transforming and creating graphs Dependencies: python and pygame

A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.

PetriKit is a modular toolkit for Petri Net analysis. It allows the extraction of basic properties, extraction of invariants, and generation of reachability graph. Results can be formatted in plain text, HTML or XML files.

Python library for a fast and flexible graph data structure.

C++ and Python based open source graph visualization and analysis software, primarily intended for use in the analysis of social networks (other applications are also conceivable).

Function graph drawing/rendering application for use with audio applications. Exports .wav files. Dependencies: wxPython & Numeric(not in 1.10)

boost_graph tried to wrap the C++ Boost Graph library in Python, providing graph algorithms like Breadth First Search, DFS, Shortest Path, Topological sort. This project is dead (http://bayleshanks.com/pamv1)

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.

This application is designed to solve problems of transshipment. This problem of the graph theory consists in finding a negative stream on the arcs which minimizes the total cost of the transport in a network R(V,E,b,c) where : - V = vertex - E

Package for general implementation of graphs in Python. Provides generic data structures, graph operators, and common algorithms.