Search Results for "level set method"
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Showing 34 open source projects for "level set method"
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
...These functions were formerly a part of Base Julia. Users with a build of Julia based on Intel's Math Kernel Library (MKL) can use MKL for FFTs by setting a preference in their top-level project by either using the FFTW.set_provider!() method, or by directly setting the preference using Preferences.jl. Note that this choice will be recorded for the current project, and other projects that wish to use MKL for FFTs should also set that same preference. Note further that MKL provides only a subset of the functionality provided by FFTW. -
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LoggingExtras.jl
Composable Loggers for the Julia Logging StdLib
LoggingExtras allows routing logged information to different places when constructing complicated "log plumbing" systems. Built upon the concept of simple parts composed together, subtyping AbstractLogger provides a powerful and flexible definition for your logging system without a need to define any custom loggers. When we talk about composability, the composition of any set of Loggers is itself a Logger, and LoggingExtras is a composable logging system. -
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ECharts
A powerful, interactive charting and visualization library for browser
ECharts is a free and open source charting and visualization library that gives you an easy way to add interactive, intuitive, custom charts to your commercial products, projects, presentations and more. It offers a rich set of features that includes rendering ability for ten-million-level data, Wechart and Powerpoint support, multi-dimension data analysis, and more. It also has a number of extensions for various applications. ECharts is written in pure JavaScript, and is based on zrender, a new and lightweight canvas library. -
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HugeGraph
A graph database that supports more than 100+ billion data
HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. Not only supports... -
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G2
Interactive data-driven visualization grammar for statistical charts
G2 is a highly interactive data-driven visualization grammar for statistical charts. with a high level of usability and scalability. It provides a set of grammar, and takes users beyond a limited set of charts to an almost unlimited world of graphical forms. With G2, you can describe the visual appearance and interactive behavior of visualization just by one statement, and generate web-based views using Canvas or SVG. We have summarized a series of story design templates from lots of real data visualization cases so that users can use them directly. ... -
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JavaParser
Java 1-17 Parser and Abstract Syntax Tree for Java
This project contains a set of libraries implementing a Java 1.0 - Java 17 Parser with advanced analysis functionalities. The project binaries are available in Maven Central. We strongly advise users to adopt Maven, Gradle or another build system for their projects. If you are not familiar with them we suggest taking a look at the maven quickstart projects. -
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SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. ... -
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G6
A Graph Visualization Framework in JavaScript
G6 is graph visualization engine with simplicity and convenience. Based on the ability to customize, it provides a set of elegant graph visualization solutions and helps developers to build up applications for graph visualization, graph analysis, and graph editor. G6 is a complete graph visualization engine, which focuses on relational data. According to practical business scenarios, we found the top solutions. Well-designed simple, flexible, and extendable interfaces will satisfy your... -
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HCubature.jl
Pure-Julia multidimensional h-adaptive integration
...Note that HCubature assumes that your function f(x) can be computed at arbitrary points in the integration domain. (This is the ideal way to do numerical integration.) If you instead have f(x) precomputed at a fixed set of points, such as a Cartesian grid, you will need to use some other method (e.g. Trapz.jl for a multidimensional trapezoidal rule). -
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InteractiveViz.jl
Interactive visualization tools for Julia
Julia already has a rich set of plotting tools in the form of the Plots and Makie ecosystems, and various backends for these. So why another plotting package? InteractiveViz is not a replacement for Plots or Makie, but rather a graphics pipeline system developed on top of Makie. It has a few objectives. To provide a simple API to visualize large or possibly infinite datasets (tens of millions of data points) easily. -
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Nebula Graph
A distributed, fast open-source graph database
...We believe that great open source projects are not built in isolation, but rather by a community of contributors. We welcome contributions to Nebula Graph from anyone regardless of skill level or background in software development. If you have an idea for a feature you would like to see added, or you have identified a bug that needs fixing, please don't hesitate to submit an issue to our Github repository. -
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GenStage
Producer and consumer actors with back-pressure for Elixir
GenStage is a specification and set of behaviours for building demand-driven data pipelines on the BEAM. It formalizes the roles of producers, consumers, and producer-consumers, using back-pressure so that fast producers don’t overwhelm downstream stages. Developers implement callbacks like handle_demand and handle_events to control how items are emitted, transformed, and consumed across asynchronous boundaries. -
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OSHMI - Open Substation HMI
SCADA HMI for substations, IoT and automation applications
...This approach makes it possible to join forces of each project (Chromium, SVG/HTML5, PHP, Lua, SQLite, Inkscape, Lib61850, OpenDNP3, Nginx, Vega, PostgreSQL, Grafana,…) to achieve a great set of open, evergreen, modular and customizable tools for building great HMIs for automation projects. This is not a toy project! It's been actually used in dozens of substations up to 230kV level and also in control centers with configurations up to 70.000 tags. Feel free to ask questions in the "Discussion" section. Help sponsoring OSHMI here https://github.com/sponsors/riclolsen. >>> Have a look also at my new SCADA project here: https://github.com/riclolsen/json-scada -
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TensorFlow.NET
.NET Standard bindings for Google's TensorFlow for developing models
...It aims to implement the complete Tensorflow API in C# which allows .NET developers to develop, train and deploy Machine Learning models with the cross-platform .NET Standard framework. TensorFlow.NET has built-in Keras high-level interface and is released as an independent package TensorFlow.Keras. SciSharp STACK's mission is to bring popular data science technology into the .NET world and to provide .NET developers with a powerful Machine Learning tool set without reinventing the wheel. Since the APIs are kept as similar as possible you can immediately adapt any existing TensorFlow code in C# or F# with a zero learning curve. ... -
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TurboVNC
High-speed, 3D-friendly, TightVNC-compatible remote desktop software
TurboVNC is a high-performance, enterprise-quality version of VNC based on TightVNC, TigerVNC, and X.org. It contains a variant of Tight encoding that is tuned for maximum performance and compression with 3D applications (VirtualGL), video, and other image-intensive workloads. TurboVNC, in combination with VirtualGL, provides a complete solution for remotely displaying 3D applications with interactive performance. TurboVNC's high-speed encoding methods have been adopted by TigerVNC and... -
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InteractiveCodeSearch.jl
Interactively search Julia code from terminal
Julia has @edit, @less, etc. which are very handy for reading the implementation of functions. However, you need to specify a "good enough" set of (type) parameters for them to find the location of the code. -
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JuliaCall for Seamless Integration of R
Embed Julia in R
Package JuliaCall is an R interface to Julia, which is a high-level, high-performance dynamic programming language for numerical computing. Below is an image for Mandelbrot set. JuliaCall brings more than 100 times speedup of the calculation. -
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ReViSP
ReViSP, a 3D volume rendering MATLAB tool for multicellular spheroids
...Computer Methods and Programs in Biomedicine, 118(2):95–106, 2015. (b) F. Piccinini, et al., Single-image based methods used for non-invasive volume estimation of cancer spheroids: a practical assessing approach based on entry-level equipment. Computer Methods and Programs in Biomedicine, 135:51-60, 2016. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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Novel Insight Scoring
Novel Insight Scoring is analytics software for scoring customers
Novel Insight Scoring is analytical CRM software for automatically scoring customers given example (scored) data. The user of the software can set optimization time and adjust risk level (pessimistic, neutral or optimistic scoring) and score new customers without detailed knowledge about data analysis and machine learning methods. The scoring results are stored in a CSV file for further processing and importing to databases etc. -
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Immerse.jl
Dive deeper into your data with interactive graphics
...Currently, Immerse supports Gadfly. The toolbar at the top supports saving your figure to a file, zooming and panning, and lasso selection. Zooming and panning uses the defaults set by GtkUtilities. The left mouse button allows you to rubberband-select a zoom region. Use your mouse wheel or arrow-keys to pan or change the zoom level. Double-click, or press the 1:1 button, to restore the full view. -
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Facets
Visualizations for machine learning datasets
...Explore Facets Overview and Facets Dive on the UCI Census Income dataset, used for predicting whether an individual’s income exceeds $50K/yr based on their census data. The census data contains features such as age, education level, and occupation for each individual. Overview gives users a quick understanding of the distribution of values across the features of their dataset(s). Uncover several uncommon and common issues such as unexpected feature values, missing feature values for a large number of observation, training/serving skew and train/test/validation set skew. -
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React-Vis
Data visualization components
React-vis is a React visualization library. React-vis components are designed to work just like other React components. They have properties, children and callbacks. They can be composed. If you can work with React components, you can work with React-Vis. You can create complex charts with a minimum amount of code and sensible defaults, however, you can also customize every aspect of your chart. React-vis handles a great number of charts, from area charts to treemaps. React-vis was built to... -
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Wally
Distributed Stream Processing
Wally is a fast-stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). ... -
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...On the top of the A.A.A.R. solution, the A.A.A.R. Analytics is a set of powerful tools to analyze data in an interactive and customizable way with a user console composed by dashboards, reports and free analysis.
