PyDigger - unearthing stuff about Python


NameVersionSummarydate
composites 0.7.0 Methods to calculate properties of laminated composite materials 2024-03-15 13:38:18
pylattica 0.1.3 pylattica is a package for fast prototyping of lattice models for chemistry and materials science 2024-03-13 18:40:32
nonrad 1.2.0 Implementation for computing nonradiative recombination rates in semiconductors 2024-03-11 23:52:35
materials-commons-cli 2.1b1 Materials Commons CLI 2024-03-08 18:12:24
bomcheckgui 1.9.6 gui for bomcheck 2024-03-07 04:10:07
bomcheck 1.9.6 Compare BOMs stored in Excel files. 2024-03-06 03:25:13
kgcnn 4.0.1 General Base Layers for Graph Convolutions with Keras 2024-02-27 12:33:31
reaction-network 8.2.1 Reaction-network is a Python package for synthesis planning and predicting chemical reaction pathways in inorganic materials synthesis. 2024-02-07 20:07:43
pychemia 0.24.2.3 Python Framework for Materials Discovery and Design 2024-02-04 15:51:37
matgl 0.9.2 MatGL is a framework for graph deep learning for materials science. 2024-01-26 21:04:48
openmsistream 1.7.9 Python applications for materials data streaming using Apache Kafka. Developed for Open MSI (NSF DMREF award #1921959) 2024-01-09 21:32:30
openmsitoolbox 1.2.3 Python utilities for OpenMSI projects Developed for Open MSI (NSF DMREF award #1921959) 2024-01-09 19:18:23
matcalc 0.0.4 Calculators for materials properties from the potential energy surface. 2024-01-01 18:51:11
scann-model 1.0 SCANN - Self-Consistent Atention-based Neural Network 2023-12-17 16:30:48
cratepy 1.0.5 CRATE: Clustering-based Nonlinear Analysis of Materials 2023-11-15 22:19:54
magentropy 0.1.6 Perform magnetoentropic mapping of magnetic materials based on DC magnetization data. 2023-11-15 09:51:15
qmflows 1.0.0 Automation of computations in quantum chemistry. 2023-10-06 21:38:33
pyoptmat 1.3.5 Statistical inference for material models 2023-09-22 16:58:19
maml 2023.9.9 maml is a machine learning library for materials science. 2023-09-09 22:24:42
dscribe 2.1.0 A Python package for creating feature transformations in applications of machine learning to materials science. 2023-09-06 05:10:15
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