Design-of-experiment (DOE) generator for science, engineering, and statistics
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Updated
Apr 3, 2024 - Jupyter Notebook
Design-of-experiment (DOE) generator for science, engineering, and statistics
Bayesian Optimization and Design of Experiments
Design of Experiment Generator. Read the docs at: https://doepy.readthedocs.io/en/latest/
Generates and evaluates D, I, A, Alias, E, T, G, and custom optimal designs. Supports generation and evaluation of mixture and split/split-split/N-split plot designs. Includes parametric and Monte Carlo power evaluation functions. Provides a framework to evaluate power using functions provided in other packages or written by the user.
Framework for Data-Driven Design & Analysis of Structures & Materials (F3DASM)
Experimental design and Bayesian optimization library in Python/PyTorch
BASM - 2017 Spring
Design of Experiments in Julia
python experiment management toolset
Curated list of resources for the Design of Experiments (DOE)
Python library for Design and Analysis of Experiments
Python package for flexible generation of D-optimal experimental designs
Design of Experiments and Analysis
Simulation and Analysis Tool for TAP Reactor Systems
Open-source constructor of surrogates and metamodels
Blocking and randomization for experimental design
A tool for remote experiment management
ChemDesign: DWSIM Experiment Toolkit
Simple implementation of Latin Hypercube Sampling.
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