Search Results for "python finite element"
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Showing 253 open source projects for "python finite element"
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Ferrite.jl
Finite element toolbox for Julia
A simple finite element toolbox written in Julia. -
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FinEtools.jl
Finite Element tools in Julia
FinEtools is a package for basic operations on finite element meshes: Construction, modification, selection, and evaluation of quantities defined on a mesh. Utilities are provided for maintaining mesh-based data (fields), for defining normals and loads, for working with physical units and coordinate systems, and for integrating over finite element meshes. -
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Elmer finite element software
Open source finite element software for multiphysical problems
Elmer is a finite element software for numerical solution of partial differential equations and multiphysical problems. It includes models of structural mechanics, fluid dynamics, heat transfer, electromagnetics etc. Elmer home is www.csc.fi/elmer -
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. The... -
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PhiPsi
An eXtended Finite Element Method (XFEM) Software.
PhiPsi is a 2D and 3D computational solid mechanics program, which involves the extended finite element method (XFEM), as well as the finite element method (FEM). PhiPsi is written in Fortran and compiled using the GNU Fortran compiler (gfortran). PPView is a visualization tool for PhiPsi. PPView can be used to import Abaqus inp file, view the model defined in the PhiPsi keywords file (*.kpp), edit PhiPsi keywords file, perform a PhiPsi simulation, and view the simulation result files generated by PhiPsi. ... -
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FSM for Go
Finite State Machine for Go
FSM is a finite state machine for Go. It is heavily based on two FSM implementations. Javascript Finite State Machine, and Fysom for Python. Visualize outputs a visualization of a FSM in Graphviz format. VisualizeForMermaidWithGraphType outputs a visualization of a FSM in Mermaid format as specified by the graphType. VisualizeWithType outputs a visualization of a FSM in the desired format. -
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Django friendly finite state machine
Django friendly finite state machine support
Django-fsm adds simple declarative state management for Django models. If you need parallel task execution, view, and background task code reuse over different flows - check my new project Django-view flow. Instead of adding a state field to a Django model and managing its values by hand, you use FSMField and mark model methods with the transition decorator. These methods could contain side effects of the state change. You may also take a look at the Django-fsm-admin project containing a... -
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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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libCEED
CEED Library: Code for Efficient Extensible Discretizations
libCEED provides fast algebra for element-based discretizations, designed for performance portability, run-time flexibility, and clean embedding in higher-level libraries and applications. It offers a C99 interface as well as bindings for Fortran, Python, Julia, and Rust. While our focus is on high-order finite elements, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the user manual and API implementation portion of the documentation. ... -
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FEATool Multiphysics
Physics Simulation Made Easy" (Fully Integrated FEA, FEniCS
FEATool Multiphysics (short for Finite Element Analysis Toolbox), is a fully integrated simulation platform for modeling all types of coupled physics phenomena, continuum mechanics, and engineering problems. By providing a truly easy to use and integrated all-in-one simulation platform for multi-physics analysis, makes FEATool an ideal simulation and modeling tool for everyone from students learning mathematical modeling, to researchers and engineers wishing to explore new ideas in a no fuss, simple, and convenient way. -
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nlpaug
Data augmentation for NLP
This Python library helps you with augmenting nlp for your machine learning projects. Visit this introduction to understand Data Augmentation in NLP. Augmenter is the basic element of augmentation while Flow is a pipeline to orchestra multi augmenters together. -
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Zendriver
A blazing fast, async-first, undetectable webscraping
...It features an async-first architecture that allows developers to build highly concurrent workflows, improving efficiency when handling multiple tasks or large-scale scraping operations. Zendriver also includes built-in utilities for managing cookies, browser profiles, and element selection, simplifying common automation tasks. -
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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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CssSelector Component
Converts CSS selectors to XPath expressions
XPath expressions are incredibly flexible, so there is almost always an XPath expression that will find the element you need. Unfortunately, they can also become very complicated, and the learning curve is steep. Even common operations (such as finding an element with a particular class) can require long and unwieldy expressions. CSS selectors are less powerful than XPath, but far easier to write, read and understand. Since they are less powerful, almost all CSS selectors can be converted to... -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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how-to-optim-algorithm-in-cuda
How to optimize some algorithm in cuda
how-to-optim-algorithm-in-cuda is an open educational repository focused on teaching developers how to optimize algorithms for high-performance execution on GPUs using CUDA. The project combines technical notes, code examples, and practical experiments that demonstrate how common computational kernels can be optimized to improve speed and memory efficiency. Instead of presenting only theoretical explanations, the repository includes hand-written CUDA implementations of fundamental operations... -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. It also provides methods for time integration. Gridap is extensible and modular. One can implement new FE spaces, new reference elements, use external mesh generators, linear solvers, post-processing tools, etc. See, e.g., the list of available Gridap plugins. -
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Dash
Build beautiful web-based analytic apps, no JavaScript required
...Dash apps are very lightweight, requiring only a limited number of lines of Python or R code; and every aesthetic element can be customized and rendered in the web. It’s also not just for dashboards. You have full control over the look and feel of your apps, so you can style them to look any way you want. -
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Markdown package LaTeX
Package for converting and rendering markdown documents in TeX
The Markdown package converts CommonMark markup to TeX commands. The functionality is provided both as a Lua module, and as plain TeX, LaTeX, and ConTeXt macro packages that can be used to directly typeset TeX documents containing markdown markup. Unlike other convertors, the Markdown package does not require any external programs and makes it easy to redefine how each and every markdown element is rendered. Creative abuse of the markdown syntax is encouraged. -
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VoxCPM
TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning
VoxCPM is a tokenizer-free text-to-speech system that models speech in a continuous space, aiming for extremely realistic, context-aware synthesis and true-to-life zero-shot voice cloning. Instead of converting speech into discrete tokens, it uses an end-to-end diffusion-autoregressive architecture built on the MiniCPM-4 backbone, combining hierarchical language modeling, finite scalar quantization (FSQ), and local Diffusion Transformers. This design helps decouple semantic and acoustic... -
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FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS
FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts. Installation and direct access to FEniCS via a Conda installation. Alternatively one may use their current FEniCS installation. A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. -
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Dominate
Dominate is a Python library for creating and manipulating HTML docs
Dominate is a Python library for creating and manipulating HTML documents using an elegant DOM API. It allows you to write HTML pages in pure Python very concisely, which eliminates the need to learn another template language, and lets you take advantage of the more powerful features of Python. Dominate can also use keyword arguments to append attributes onto your tags. -
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authoscope
Scriptable network authentication cracker (formerly `badtouch`)
authoscope is a scriptable network authentication cracker. While the space for common service bruteforce is already very well saturated, you may still end up writing your own python scripts when testing credentials for web applications. The scope of authoscope is specifically cracking custom services. This is done by writing scripts that are loaded into a lua runtime. Those scripts represent a single service and provide a verify(user, password) function that returns either true or false.... -
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HASS Configurator
Configuration UI for Home Assistant
The HASS Configurator is a small web app (you access it via a web browser) that provides a filesystem browser and text-editor to modify files on the machine the configurator is running on. It has been created to allow easy configuration of Home Assistant. It is powered by Ace editor, which supports syntax highlighting for various code/markup languages. YAML files (the default language for Home Assistant configuration files) will be automatically checked for syntax errors while editing. The... -
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JUDI.jl
Julia Devito inversion
...The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling operators can also be used as layers in (convolutional) neural networks to implement physics-augmented deep learning algorithms thanks to its implementation of ChainRules's rrule for the linear operators representing the discre wave equation.
