Search Results for "method"
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Showing 73 open source projects for "method"
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TaylorIntegration.jl
ODE integration using Taylor's method, and more, in Julia
ODE integration using Taylor's method in Julia. -
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Stan.jl
Stan.jl illustrates the usage of the 'single method' packages
A collection of example Stan Language programs demonstrating all methods available in Stan's cmdstan executable (as an external program) from Julia. For most applications one of the "single method" packages, e.g. StanSample.jl, StanDiagnose.jl, etc., is a better choice for day-to-day use. To execute the most important method in Stan ("sample"), use StanSample.jl. Some Pluto notebook examples can be found in the repository. -
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VoronoiFVM.jl
Solution of nonlinear multiphysics partial differential equations
Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters. -
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Surrogates.jl
Surrogate modeling and optimization for scientific machine learning
A surrogate model is an approximation method that mimics the behavior of a computationally expensive simulation. In more mathematical terms: suppose we are attempting to optimize a function f(p), but each calculation of f is very expensive. It may be the case we need to solve a PDE for each point or use advanced numerical linear algebra machinery, which is usually costly. The idea is then to develop a surrogate model g which approximates f by training on previous data collected from evaluations of f. -
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Circuitscape.jl
Algorithms from circuit theory to predict connectivity
Circuitscape is an open-source program that uses circuit theory to model connectivity in heterogeneous landscapes. Its most common applications include modeling the movement and gene flow of plants and animals, as well as identifying areas important for connectivity conservation. The new Circuitscape is built entirely in the Julia language, a new programming language for technical computing. Julia is built from the ground up to be fast. As such, this offers a number of advantages over the... -
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JavaParser
Java 1-17 Parser and Abstract Syntax Tree for Java
...While JavaParser generates an Abstract Syntax Tree, JavaSymbolSolver analyzes that AST and is able to find the relation between an element and its declaration (e.g. for a variable name it could be a parameter of a method, providing information about its type, position in the AST, etc). When choosing open source technologies it is important to know your choice will be rewarded by continuous support. The JavaParser community is vibrant and active, with a weekly release cadence that supports language features up to Java 12. -
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DataEase
Data visualization analysis tool
...DataEase supports rich data source connections, can quickly create charts by dragging and dropping, and can easily share with others. Supports rich chart types (Apache ECharts / AntV), supports drag-and-drop method to quickly create dashboards. Support direct connection mode, local mode (based on Apache Doris / Kettle implementation). Support various data sources such as data warehouse/data lake, OLAP database, OLTP database, Excel data file, API, etc. Open source and open: zero threshold, quick access and installation online; quick access to user feedback, new versions released monthly. pport multiple data sharing methods to ensure data security. -
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
...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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Roots.jl
Root finding functions for Julia
...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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HCubature.jl
Pure-Julia multidimensional h-adaptive integration
...(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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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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Vizzu
Library for animated data visualizations and data stories
...Create a placeholder element that will contain the rendered chart. The Vizzu constructor has to load Vizzu's WebAssembly module asynchronously to prevent blocking the whole page. Because of this, any method except animate() will throw an exception while the library is not initialized. There is an initializing promise in the Vizzu class, which will resolve when initialization is finished. You can call all methods after this promise is resolved. -
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electricityMap
A real-time visualisation of the CO2 emissions of electricity
...Consumption-based accounting (CBA) is a very important aspect of climate policy and allows assigning responsibility to consumers instead of producers. Furthermore, this method is robust to governments relocating dirty production to neighboring countries in order to green their image while still importing from it. -
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gramm
Gramm is a complete data visualization toolbox for Matlab
Gramm is a MATLAB toolbox that enables the rapid creation of complex, publication-quality figures. Its design philosophy focuses on a declarative approach, where users specify the desired end result, as opposed to the traditional imperative method involving for loops, if/else statements, etc. The MATLAB implementation of gramm is inspired by the "grammar of graphics" principles (Wilkinson 1999) and the ggplot2 library for R by Hadley Wickham. As a reference to this inspiration, gramm stands for GRAMmar of graphics for MATLAB. A similar library called Seaborn also exists for Python. ... -
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ggstatsplot
Enhancing {ggplot2} plots with statistical analysis
...In a typical exploratory data analysis workflow, data visualization and statistical modeling are two different phases: visualization informs modeling, and modeling in its turn can suggest a different visualization method, and so on and so forth. Bayesian hypothesis-testing. The central idea of {ggstatsplot} is simple: combine these two phases into one in the form of graphics with statistical details, which makes data exploration simpler and faster. Summary of statistical tests and effect sizes. -
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nichenetr
NicheNet: predict active ligand-target links between interacting cells
nichenetr: the R implementation of the NicheNet method. The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest. -
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
...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. ... -
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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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Nebula Graph
A distributed, fast open-source graph database
The graph database built for super large-scale graphs with milliseconds of latency. Optimized SUBGRAPH and FIND PATH for better performance. Optimized query paths to reduce redundant paths and time complexity. Optimized the method to get properties for better performance of MATCH statements. Nebula Graph adopts the Apache 2.0 license, one of the most permissive free software licenses in the world. Free as in freedom, because, under the Apache 2.0 license, you can use, copy, modify and redistribute Nebula Graph, even for commercial purposes, all without asking for permission. ... -
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OptiMIClass
Automatic n-dimensional data clustering tool powered by five advanced
This software is an automatic n-dimensional quantitative data clustering tool based on five optimization heuristics (GA, PSO, ACO, SA, and TS). It enables performance comparisons across heuristics and parameter testing within each method, analyzing solution quality, runtime, and convergence; it also includes a repository of benchmark test tables and an intuitive interface for research and operational use. It was developed by M.Sc. Jeffry Chavarría-Molina and M.Sc. Juan José Fallas-Monge at the Instituto Tecnológico de Costa Rica (TEC), School of Mathematics, with support from the Vice-Rectory for Research and Extension (VIE). ... -
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AtomProbeLab
Matlab-based analysis of Atom Probe Data
...For more information see the Wiki: https://sourceforge.net/p/atomprobelab/wiki/Home/ Quick overview video: https://youtu.be/8rJHce7M5UU More in-depth video using the APT school demos live script: https://www.youtube.com/watch?v=cyrLHCzZwuw For details of the maximum likelihood method used to solve peak overlaps see the following papers: https://doi.org/10.1017/S1431927616012782 and https://doi.org/10.1017/S1431927618016276 for the quantification of the uncertainty. If you are looking for Dan Haley's "weights" program, go here https://sourceforge.net/projects/apttools/files/extras/ -
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DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal... -
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Data Preprocessing Automate
Data Preprocessing Automation: A GUI for easy data cleaning & visualiz
Data Preprocessing Automation is a Python-based GUI application designed to simplify and automate data preprocessing tasks. It allows users to upload Excel files, automatically handle missing values, remove duplicates, and detect and remove outliers using statistical methods. The application provides data visualization tools, including box plots for distribution analysis and scatter plots for exploring relationships between variables. Users can download the processed data for further... -
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ProximalOperators.jl
Proximal operators for nonsmooth optimization in Julia
Proximal operators for nonsmooth optimization in Julia. This package can be used to easily implement proximal algorithms for convex and nonconvex optimization problems such as ADMM, the alternating direction method of multipliers. With using ProximalOperators the package exports the prox and prox! methods to evaluate the proximal mapping of several functions. -
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DeepH-pack
Deep neural networks for density functional theory Hamiltonian
DeepH-pack is the official implementation of the DeepH (Deep Hamiltonian) method described in the paper Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation and in the Research Briefing. DeepH-pack supports DFT results made by ABACUS, OpenMX, FHI-aims or SIESTA and will support HONPAS.
