PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
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Updated
Jun 13, 2024 - Python
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays.
Generative Pre-Trained Physics-Informed Neural Networks Implementation
The official repository for the AiiDA code
simplified cellranger for long-read data
Useful functions and classes in Python programming.
A Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design and the creation of molecular databases.
Analysis postprocessing utilities for my molecular dynamics simulations of LiTFSI-Ether mixtures
Tools for simplifying daily work with the AiiDA workflow engine
Python scripts supporting a tutorial on the Hodgkin-Huxley model.
Crack Analysis Tool in Python (CrackPy) - automatic detection and fracture mechanical analysis of (fatigue) cracks using digital image correlation
Scripts to prepare and analyze molecular dynamics simulations
A suite of scripts and modules that perform menial, tedious and repetitive tasks and operations on VASP files that were hurriedly and haphazardly put together by some intern.
Fast, flexible tools to simplify scientific Python
Fast and robust smoothing of gridded data in multiple dimensions using the discrete cosine transform.
ReproZip is a tool that simplifies the process of creating reproducible experiments from command-line executions, a frequently-used common denominator in computational science.
This repository contains a simple particle physics simulation that demonstrates the behavior of particles with gravitational effects. The simulation is implemented using Pygame for visualization and PyOpenGL for rendering.
This is an exercise to practice computational derivation and matrix multiplication.
Python script to create and test Turring machines
Minimal working examples applying Finite Element Method with Firedrake framework
This repository contains implementations of algorithms from the course "Computational Science" at HUST
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