Open Source Mac Data Visualization Software - Page 50

This package provides general guidelines to represent non-linear programming (NLP) problems in Julia and a standardized API to evaluate the functions and their derivatives. The main objective is to be able to rely on that API when designing optimization solvers in Julia.

This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently.

NanoGraph is a java component for graph visualisation. It aims to visualize domain oriented object models without requiring code changes to these models. Design goals include a small footprint and Swing/SWT/SVG support.

Narvik is a tool for conducting numerical and visual analysis in cartography.

NecJGui is an antennas design tool, interface for Numerical Electromagnetic Code. It allows easily making NEC input files, and viewing them in 3D. It also contains a version of the simulator, so it's complete IDE for full-wave EM simulation.

Nemo is a computer algebra package for the Julia programming language. It aims to cover commutative algebra, number theory and group theory. Julia bindings for various mathematical libraries (including flint2)

Nested pie chart is for tree visualization. Each node of the tree has a size and color attribute, enabling the chart to be used as a heatmap. Linear arrangement of the nodes in decreasing order of size is an advantage over rectangular heatmaps.

NetCDF support for the Julia programming language, there is a high-level and a medium-level interface for writing and reading netcdf files. The dimensions "x1" and "t" of the variable are called "x1" and "t" in this example. If the dimensions do not exist yet in the file, they will be created. The dimension "x1" will be of length 10 and have the values 11..20, and the dimension "t" will have length 20 and the attribute "units" with the value "s".

NetGraph is a collection of java classes and beans that can visualize common network and dependency graphs. These graphs are built of nodes and connections between the nodes. See homepage for details.

Interactive multiformat graph viewer

NetVis 2D (NV2D) is a social network visualization application that can be embedded in a browser or run as a standalone applcation.

The NetVis Module is a free open source web-based tool designed to simulate, analyze, and visualize social networks using data from csv files, online surveys, and geographically dispersed work teams. Built using php, mysql, and java for visualization.

Network Visualization is a mature part of computer science that is enjoying a good deal of growth, partially fueled by Bioinformatics. Network is a synonym for Graph, and both refer to a collection of nodes and edges.

The Neural Assembly Simulation Environment (NASE) is a collection of routines written in the Interactive Data Language (IDL) by Research Systems Inc. It provides routines to simulate neural networks and to visualize those networks' behavior.

Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function spaces. The kernel can be trained on different geometry, which is learned from a graph. Fourier neural operator learns a neural operator with Dirichlet kernel to form a Fourier transformation. It performs Fourier transformation across infinite-dimensional function spaces and learns better than neural operators. Markov neural operator learns a neural operator with Fourier operators.

The NeuroEvolution Visualization Toolkit is a suite of XSL style sheets, DTDs, shell scripts/bat files used to generate graphical output in the form of SVG (Scalable Vector Graphics) for data associated with neuroevolution implementations.

Neuroglancer is a WebGL-based visualization tool designed for exploring large-scale volumetric and neuroimaging datasets directly in the browser. It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools.

It's a free-roaming 3D racing game featuring advanced terrain rendering. For small file-size, a 4k x 4k terrain is available, sampled meter-by-meter so it's very smooth. Lightweight program. This is the form in which I wished to do the first release of the terrain rendering Algorithm I have developed throughout almost 2 years. Written in C++, featuring multithreading (2 threads): a total remake of the first 3D game I did years ago, CTruck3D_Simplex and sequels. This works better, thought the basic idea is the seme. Similar to the old games Terep2 and "1nsane". I am an algorithmist, not a game developer: so it was hard for me to put this togather. But I did this tribute to videogames. Have lots of fun! KEYS: mouse: primary camera control arrows: drive vehicle ; SHIFT: turbo ; TAB: change car. o: change camera ; 1,2: zoom-in/out ; 3,4 : horizontal and vertical camera placement (internal view) u: respawn car c,v,f,r :secondary camera control. 8,9:plane drv

A very lightweight advanced terrain-rendering and 3D map rendering system. Minimal dependencies: OpenGL, SDL. It's distrib in 2-3 separate modules: 1. the C++ implementation of the terrain- and/or surface- rendering Algorithms I have developed: both a multithread and a non-multithread variant is relaeased. 2. Seme as at point 1. , but with a road-network rendering and collision-detection module I wrote before. It also adds some trees at the top of the terrain. (multitread vesion not released yet) 3. Seme as point 2.. Multithread terrain-rendering, roads on it, and vehicles to go around. The most important part is terrain-rendering. The Algorithm at the heart of it features my first and second theorem abut polygonal surface approximation. It took something like 2 years to develop it. It's technically a view-dependent, continuous dynamic level-of-detail rendering algorithm. Main features are simplicity and documentation. Does easily a 4k x 4k terrain, but also much more.

Nexplorer is a web-based phylogenetic browser, used to view and edit comparative data, and ideal for creating publication-quality views in which the tips of a tree are aligned with the rows of a character matrix (e.g., a sequence alignment).

An all-in-one observability solution that aims to combine the advantages of Prometheus and Grafana. It manages alert rules and visualizes metrics, logs, and traces in a beautiful web UI.

Simulates a biologically diverse tropical island, and the ape inhabitants cognitive processes. For MacOS X, iPad, Windows and Linux. Features a non-polygonal graphics engine and a command-line version

A MATLAB toolbox for linear and nonlinear static and dynamic finite element analysis.

Fast implementations of root-finding algorithms in Julia that satisfy the SciML common interface. For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation that contains the unreleased features. NonlinearSolve.jl is a unified interface for the nonlinear solving packages of Julia. The package includes its own high-performance nonlinear solvers which include the ability to swap out to fast direct and iterative linear solvers, along with the ability to use sparse automatic differentiation for Jacobian construction and Jacobian-vector products. NonlinearSolve.jl interfaces with other packages of the Julia ecosystem to make it easy to test alternative solver packages and pass small types to control algorithm swapping. It also interfaces with the ModelingToolkit.jl world of symbolic modeling to allow for automatically generating high-performance code.

Nounou is a Java library for handling optical imaging data. The core consists of a modular stream of "filter blocks" that each modify or display the data. It is easily called from Mathematica and Matlab, for advanced figure output.