Open Source Windows Data Visualization Software - Page 11
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Data Visualization Software for Windows
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Infiltrator.jl
No-overhead breakpoints in Julia
This package provides the @infiltrate macro, which acts as a breakpoint with negligible runtime performance overhead. Note that you cannot access other function scopes or step into further calls. Use an actual debugger if you need that level of flexibility. Running code that ends up triggering the @infiltrate REPL mode via inline evaluation in VS Code or Juno can cause issues, so it's recommended to always use the REPL directly. When the infiltration point is hit, it will drop you into an interactive REPL session that lets you inspect local variables and the call stack as well as execute arbitrary statements in the context of the current local and global scope. -
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JET.jl
An experimental code analyzer for Julia
JET employs Julia's type inference system to detect potential bugs and type instabilities. JET is tightly coupled to the Julia compiler, and so each JET release supports a limited range of Julia versions. See the Project.toml file for the range of supported Julia versions. The Julia package manager should install a version of JET compatible with the Julia version you are running. If you want to use JET on unreleased version of Julia where compatibility with JET is yet unknown, clone this git repository and dev it, such that Julia compatibility is ignored. -
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Java Tablesaw
Java dataframe and visualization library
Tablesaw is a dataframe and visualization library that supports loading, cleaning, transforming, filtering, and summarizing data. If you work with data in Java, it may save you time and effort. Tablesaw also supports descriptive statistics and can be used to prepare data for working with machine learning libraries like Smile, Tribuo, H20.ai, DL4J. Import data from RDBMS, Excel, CSV, TSV, JSON, HTML, or Fixed Width text files, whether they are local or remote (http, S3, etc.) Tablesaw supports data visualization by providing a wrapper for the Plot.ly JavaScript plotting library. Here are a few examples of the new library in action. Descriptive stats: mean, min, max, median, sum, product, standard deviation, variance, percentiles, geometric mean, skewness, kurtosis, etc. Add tablesaw-core to your project. You can find the version number for the latest release in the release notes. -
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KernelAbstractions.jl
Heterogeneous programming in Julia
KernelAbstractions (KA) is a package that enables you to write GPU-like kernels targetting different execution backends. KA is intended to be a minimal and performant library that explores ways to write heterogeneous code. -
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LatticeQCD.jl
A native Julia code for lattice QCD with dynamical fermions in 4D
This code enables you to perform lattice QCD calculations! A native Julia code for Lattice QCD. -
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LiveServer.jl
Simple development server with live-reload capability for Julia
This is a simple and lightweight development web-server written in Julia, based on HTTP.jl. It has live-reload capability, i.e. when modifying a file, every browser (tab) currently displaying the corresponding page is automatically refreshed. -
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MIRT.jl
MIRT: Michigan Image Reconstruction Toolbox (Julia version)
MIRT.jl is a collection of Julia functions for performing image reconstruction and solving related inverse problems. It is very much still under construction, although there are already enough tools to solve useful problems like compressed sensing MRI reconstruction. Trying the demos is a good way to get started. The documentation is even more still under construction. -
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MPI.jl
MPI wrappers for Julia
This is a basic Julia wrapper for the portable message-passing system Message Passing Interface (MPI). Inspiration is taken from mpi4py, although we generally follow the C and not the C++ MPI API. (The C++ MPI API is deprecated.) MPI is based on a single program, multiple data (SPMD) model, where multiple processes are launched running independent programs, which then communicate as necessary via messages. As the main entry point for users, MPI.jl provides a high-level interface which loosely follows the MPI C API and is described in details in the following sections. The syntax should look familiar if you know MPI already, but some arguments may not be needed (e.g. the type or the number of elements of arrays, which are inferred automatically), others may be placed slightly differently, and others may be optional keyword arguments (e.g. for the index of the root process, or the source and destination of point-to-point communication functions). -
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Metalhead.jl
Computer vision models for Flux
Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module. -
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ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
The ModelingToolkit Standard Library is a standard library of components to model the world and beyond. -
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MultivariatePolynomials.jl
Multivariate polynomials interface
MultivariatePolynomials.jl is an implementation-independent library for manipulating multivariate polynomials. It defines abstract types and an API for multivariate monomials, terms, and polynomials and gives default implementation for common operations on them using the API. On the one hand, This packages allows you to implement algorithms on multivariate polynomials that will be independant on the representation of the polynomial that will be chosen by the user. On the other hand, it allows the user to easily switch between different representations of polynomials to see which one is faster for the algorithm that he is using. -
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NFFT
The official NFFT library repository
NFFT is a software library, written in C, for computing non-equispaced fast Fourier transforms and related variations. -
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ODBC.jl
An ODBC interface for the Julia programming language
The ODBC.jl package provides a Julia interface for the ODBC API as implemented by various ODBC driver managers. More specifically, it provides a prebuilt copy of iODBC and unixODBC for OSX/Linux platforms, while still relying on the system-provided libraries on Windows. This means that no extra installation of a driver manager is necessary after installing the ODBC.jl package. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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Polyhedra
Polyhedral Computation Interface
Polyhedra provides an unified interface for Polyhedral Computation Libraries such as CDDLib.jl. This manipulation notably includes the transformation from (resp. to) an inequality representation of a polyhedron to (resp. from) its generator representation (convex hull of points + conic hull of rays) and projection/elimination of a variable with e.g. Fourier-Motzkin. -
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Polynomials.jl
Polynomial manipulations in Julia
Basic arithmetic, integration, differentiation, evaluation, root finding, and fitting for univariate polynomials in Julia. -
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PowerSystems.jl
Data structures in Julia to enable power systems analysis
The PowerSystems.jl package provides a rigorous data model using Julia structures to enable power systems analysis and modeling. In addition to stand-alone system analysis tools and data model building, the PowerSystems.jl package is used as the foundational data container for the PowerSimulations.jl and PowerSimulationsDynamics.jl packages. PowerSystems.jl supports a limited number of data file formats for parsing. -
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Profile Summary
Tool for visualizing GitHub profiles
Profile Summary for GitHub is a web application for turning a public GitHub account into a more visual overview of its development activity. It uses the GitHub API to collect profile and repository information and present it as summary graphics and statistics. Its visualizations include repository distribution by programming language and commit distribution by language. Users can generate summaries for GitHub usernames through the web interface. The project can also be self-hosted and configured with GitHub API tokens to increase request capacity. Built with Kotlin and Javalin, it provides a compact way to inspect a developer's GitHub presence beyond the standard profile layout. -
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PyCall.jl
Package to call Python functions from the Julia language
Package to call Python functions from the Julia language. This package provides the ability to directly call and fully interoperate with Python from the Julia language. You can import arbitrary Python modules from Julia, call Python functions (with automatic conversion of types between Julia and Python), define Python classes from Julia methods, and share large data structures between Julia and Python without copying them. -
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ReachabilityAnalysis.jl
Compute reachable states of dynamical systems
Reachability analysis is concerned with computing rigorous approximations of the set of states reachable by a dynamical system. In the scope of this package are systems modeled by continuous or hybrid dynamical systems, where the dynamics change with discrete events. Systems are modeled by ordinary differential equations (ODEs) or semi-discrete partial differential equations (PDEs), with uncertain initial states, uncertain parameters or non-deterministic inputs. -
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React Lifecycle Methods diagram
Interactive React Lifecycle Methods diagram
React Lifecycle Methods Diagram is an interactive educational visualization of React component lifecycle methods. It is based on a lifecycle diagram originally shared by Dan Abramov and was rebuilt as a React web application. The diagram organizes methods according to when they run during component mounting, updating, and unmounting. Clicking a method opens its corresponding official React documentation for deeper reference. Commonly used methods are visually emphasized while related lifecycle actions are distinguished separately. Accessibility was designed for keyboard users and screen readers rather than relying only on visual interaction. The project also supports localization and can accommodate alternate diagram versions as React lifecycle APIs evolve. -
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ReactiveMP.jl
High-performance reactive message-passing based Bayesian engine
ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets. -
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Roots.jl
Root finding functions for Julia
This package contains simple routines for finding roots, or zeros, of scalar functions of a single real variable using floating-point math. The find_zero function provides the primary interface. The basic call is find_zero(f, x0, [M], [p]; kws...) where, typically, f is a function, x0 a starting point or bracketing interval, M is used to adjust the default algorithms used, and p can be used to pass in parameters. Bisection-like algorithms. For functions where a bracketing interval is known (one where f(a) and f(b) have alternate signs), a bracketing method, like Bisection, can be specified. The default is Bisection, for most floating point number types, employed in a manner exploiting floating point storage conventions. For other number types (e.g. BigFloat), an algorithm of Alefeld, Potra, and Shi is used by default. These default methods are guaranteed to converge. Other bracketing methods are available. -
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RxMarbles
Interactive diagrams of Rx Observables
RxMarbles is an open-source interactive web application that teaches reactive programming through animated marble diagrams. It visualizes how ReactiveX operators transform sequences of events over time. Each diagram displays input streams, operator behavior, and resulting output streams. Users can drag individual marbles along a timeline to observe how different event positions affect the results. The application includes examples of operators used for mapping, filtering, combining, and delaying observable sequences. Individual diagrams can be shared through direct links for demonstrations or educational discussions. Built using Cycle.js, it also serves as an example of reactive interface development. The repository is archived, but the educational website remains accessible. -
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ScottPlot
Interactive Plotting Library for .NET
ScottPlot is a free and open-source plotting library for .NET that makes it easy to interactively display large datasets. Line plots, bar charts, pie graphs, scatter plots, and more can be created with just a few lines of code. The ScottPlot Cookbook demonstrates how to create line plots, bar charts, pie graphs, scatter plots, and more with just a few lines of code. The ScottPlot Demo is a click-to-run application that demonstrates mouse-interactive versions of every cookbook recipe. ScottPlot does not require a GUI so it can be used to create plots in cloud applications. The images below are regenerated hourly using Azure Functions to update star metrics from the GitHub API and download count from the NuGet API. The data is plotted with ScottPlot and saved as an image file in blob storage.
