Search Results for "3d graph renderer"

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...

...Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and cheaply) acquired from different sources. pyntcloud enables simple and interactive exploration of point cloud data, regardless of which sensor was used to generate it or what the use case is. ...

- Save and open a Work/Project (spf) file - Single fitting/ Batch fitting (user defined custom func) - Matrix to XYZ in Tool menu - Symbol plot: makers, curve, landscape, bar, etc. - 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...

xPyder is a PyMOL plugin to analyze and visualize on the 3D structure dynamical cross-correlation matrices (DCCM), linear mutual information (LMI), communication propensities (CP), intra- and inter-molecular interactions (e.g. PSN), and more, to produce highly customizable publication-quality images. xPyder identifies networks (using concepts from graph theory, such as hubs and shortest path searching), compares matrices and focuses the analysis on relevant information by filtering the data using a modular, user-expandable plugin system that takes advantage of structural and dynamical information, contributing to bridge the gap between dynamical and mechanical properties at the molecular level.

A Java software for 3D visualization of graphs/networks. It implements many graph layout algorithms (such as force-directed methods), graph generators (such as scale-free networks) and graph modifiers. Most functions can be accessed through its GUI.