Search Results for "numerical methods"
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Showing 94 open source projects for "numerical methods"
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basic_numerical_methods
Didactic application to aid students in learning Numerical Methods;
A practical tool (for students and engineers) to foresee the result of calculus exercises. Calculation and visualization numerical methods for nonlinear equation, ODE, integration, linear system, polynomial fitting,..... -
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Calculus.jl
Calculus functions in Julia
...You can use the Calculus package to produce approximate derivatives by several forms of finite differencing or to produce exact derivatives using symbolic differentiation. You can also compute definite integrals by different numerical methods. -
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Trixi.jl
Trixi.jl: Adaptive high-order numerical simulations of hyperbolic PDEs
Trixi.jl is a numerical simulation framework for hyperbolic conservation laws written in Julia. A key objective for the framework is to be useful to both scientists and students. Therefore, next to having an extensible design with a fast implementation, Trixi.jl is focused on being easy to use for new or inexperienced users, including the installation and postprocessing procedures. -
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MathPHP
Powerful modern math library for PHP
Math PHP is a library that brings advanced mathematical functions and data analysis capabilities to PHP applications. It covers a wide range of topics, including linear algebra, calculus, statistics, probability, and numerical analysis. Math PHP is designed for developers and data scientists who require precise and efficient mathematical computations in PHP, making it suitable for scientific computing and data processing. -
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CasADi
CasADi is a symbolic framework for numeric optimization
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT, etc. It can be used in C++, Python, or Matlab/Octave. CasADi's backbone is a symbolic framework implementing forward and reverse modes of AD on expression graphs to construct gradients, large-and-sparse Jacobians, and... -
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JupyterQuiz
An interactive Quiz generator for Jupyter notebooks and Jupyter Book
JupyterQuiz is a tool for displaying interactive self-assessment quizes in Jupyter notebooks and Jupyter Book. Important Note for JupyterLab 4 Users: Changes to the math rendering system in JupyterLab 4 have broken the LaTeX rendering in JupyterQuiz. There is not currently a simple solution, but I have opened an issue requesting that the necessary methods be made available. Math should still work in Jupyter Book. A very hacky solution is available in version 2.7.0a1, which loads MathJax 3 on... -
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Elastiknn
Elasticsearch plugin for nearest neighbor search
Elasticsearch plugin for nearest neighbor search. Store vectors and run similarity searches using exact and approximate algorithms. Methods like word2vec and convolutional neural nets can convert many data modalities (text, images, users, items, etc.) into numerical vectors, such that pairwise distance computations on the vectors correspond to semantic similarity of the original data. Elasticsearch is a ubiquitous search solution, but its support for vectors is limited. ... -
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HomotopyContinuation.jl
A Julia package for solving systems of polynomials
HomotopyContinuation.jl is a Julia package for solving systems of polynomial equations by numerical homotopy continuation. Many models in the sciences and engineering are expressed as sets of real solutions to systems of polynomial equations. We can optimize any objective whose gradient is an algebraic function using homotopy methods by computing all critical points of the objective function. An important special case is when the objective function is the euclidean distance to a given point. ... -
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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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PowerSimulations.jl
Julia for optimization simulation and modeling of PowerSystems
...Exploit Julia's capabilities to improve computational performance of large-scale power system quasi-static simulations. The flexible modeling framework is enabled through a modular set of capabilities that enable scalable power system analysis and exploration of new analysis methods. The modularity of PowerSimulations results from the structure of the simulations enabled by the package. Simulations define a set of problems that can be solved using numerical techniques. -
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The Algorithms Python
All Algorithms implemented in Python
The Algorithms-Python project is a comprehensive collection of Python implementations for a wide range of algorithms and data structures. It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting,... -
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FiniteDifferences.jl
High accuracy derivatives, estimated via numerical finite differences
FiniteDifferences.jl estimates derivatives with finite differences. See also the Python package FDM. FiniteDiff.jl and FiniteDifferences.jl are similar libraries: both calculate approximate derivatives numerically. You should definitely use one or the other, rather than the legacy Calculus.jl finite differencing, or reimplementing it yourself. At some point in the future, they might merge, or one might depend on the other. -
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Axon
Nx-powered Neural Networks
...By decoupling the APIs, Axon gives you full control over each aspect of creating and training a neural network. At the lowest-level, Axon consists of a number of modules with functional implementations of common methods in deep learning. -
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Haiku Sonnet for JAX
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. JAX is a numerical computing library that combines NumPy, automatic differentiation, and first-class GPU/TPU support. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX's pure function transformations. Haiku provides two core tools: a module abstraction, hk.Module, and a simple function transformation, hk.transform. hk.Modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs. hk.transform turns functions that use these object-oriented, functionally "impure" modules into pure functions that can be used with jax.jit, jax.grad, jax.pmap, etc. -
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Haiku
JAX-based neural network library
Haiku is a library built on top of JAX designed to provide simple, composable abstractions for machine learning research. Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used... -
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mlpack
mlpack: a scalable C++ machine learning library
mlpack is an intuitive, fast, and flexible C++ machine learning library with bindings to other languages. It is meant to be a machine learning analog to LAPACK, and aims to implement a wide array of machine learning methods and functions as a "swiss army knife" for machine learning researchers. In addition to its powerful C++ interface, mlpack also provides command-line programs, Python bindings, Julia bindings, Go bindings and R bindings. Written in C++ and built on the Armadillo linear algebra library, the ensmallen numerical optimization library, and parts of Boost. ... -
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water_hammer_simulation
A Qt application for water hammer simulation.
With differents numerical methods this application simulate the water hammer phenomenon. -
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Bayes+Estimate is a Rust and C++ library that implement numerical algorithms for Bayesian estimation. They provide tested and consistent numerical methods and represents the wide variety of Bayesian estimation algorithms and system model.
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Calcpad
A free software for mathematical and engineering calculations
Calcpad helps engineers to create clear and traceable calculation notes. It supports real and complex numbers, phasors, units of measurement, custom variables and functions, vectors and matrices, numerical methods, function plotting, conditional execution, iterations, etc. Results are collected into professional looking Html reports for viewing and printing. You can also export them to .docx (MS Word) and .pdf files. You can also create dynamic vector drawings and animations to visualize your data. After installation, you will find a lot of examples for solving different mathematical, mechanical and structural/civil engineering problems in your documents folder. ... -
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Math Model
Code, resources, and templates for mathematical modeling
...It includes LaTeX templates for writing solutions, records of past contest problems and winning solutions, algorithm implementations in MATLAB / M scripts for optimization, intelligent algorithms, numerical methods, and model frameworks. In effect, it is a curated library of modeling code, papers, templates, and algorithm summaries tailored to competition preparation. Historical problem and solution archives from many contests. Summary of contest evaluation criteria and heuristics. -
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octave-ocl
OpenCL support for GNU Octave
...It is flexibly extendible by user-written OpenCL C programs. The Package does not, by itself, provide parallelization of higher numerical methods (like BLAS or LAPACK). The Package is also available from the corresponding Octave Forge webpage https://octave.sourceforge.io/ocl/index.html. More information on GNU Octave can be found at https://www.octave.org. -
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sequoia-dap
SEQUOIA ocean data assimilation platform (a SIROCCO suite tool)
Within the SIROCCO suite of numerical tools, the purpose of SDAP is to provide a flexible platform to carry out multivariate assimilation of geophysical data in a numerical model. The program is multi-grid (finite differences or finite elements), multi-algebra (plug-in analysis kernels), multi-model (simple standardized interface). The program supports reduced-order data assimilation methods, as well as Ensemble assimilation approaches such as the Ensemble Kalman Filter. ... -
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LabRPS
Random phenomena generator
This is an official mirror of LabRPS. Code and release files are primarily hosted on https://github.com/LabRPS/LabRPS and mirrored here LabRPS aims to be a tool for the numerical simulation of random phenomena such as stochastic wind velocity, seismic ground motion, sea surface ... etc. It can be in a wide range of uses around engineering, such as random vibration or vibration fatigue in mechanical engineering, buffeting analysis in bridge engineering.... LabRPS is mainly to assist reseachers in related fields to quickly implement new simulation methods programmatically in their new research work based on the existing works, help engineers to numerically generate random phenomena in a more realistic way, helps students and new comers to this field to learn quickly. ... -
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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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C++ Complex Calculator
C++ complex calculator with arrays, matrices, eigenvectors, functions
This is a command line C++ code which compiles and links using gnu g++. It has scientific notation, scientific functions, complex integration including path integrals, and loops with tests. User defined functions are strings. A variable may simultaneously represent a scalar, an array, and a string. Arrays up to ten dimensions are allowed. Householder reduction is used for determinants, eigenvectors, and QR matrix factorization. Class Matrix and class Polynomial facilitate finding...