| Name | Version | Summary | date |
| invrs-opt |
0.10.1 |
Algorithms for inverse design |
2024-12-18 00:39:45 |
| invrs-gym |
1.4.4 |
A collection of inverse design challenges |
2024-12-12 17:05:25 |
| pyats.topology |
24.11 |
pyATS Topology: Topology Objects and Testbed YAMLs |
2024-11-27 21:46:07 |
| mantra-dataset |
0.0.6 |
A package for working with higher-order datasets like manifold triangulations. |
2024-11-12 16:14:53 |
| topology |
1.19.1 |
Topology is a framework for building and testing network topologies, with support for pytest. |
2024-11-05 21:22:44 |
| finite-topology |
0.1.13 |
A Python library for defining and manipulating topologies on finite sets. |
2024-10-27 07:59:44 |
| invrs-utils |
1.4.0 |
Miscellaneous utilities for the invrs-io ecosystem |
2024-09-10 20:05:36 |
| totypes |
0.8.0 |
Custom datatypes useful in a topology optimization context |
2024-08-08 19:25:41 |
| DGtal |
1.4.1 |
Digital Geometry Tools and Algorithm Library |
2024-07-24 12:44:49 |
| mogutda |
0.4.2 |
Topological Data Analysis in Python |
2024-07-16 17:56:40 |
| imageruler |
0.3.0 |
Measure minimum sollid/void lengthscales in binary images. |
2024-07-12 20:31:26 |
| Shapely-cellvit |
1.8.5.post1 |
Geometric objects, predicates, and operations |
2024-07-03 21:59:46 |
| grid2fp |
0.0.10 |
A tool to eat grid diagrams and generate its front projection. |
2024-05-31 07:10:26 |
| tightbinder |
0.2 |
Slater-Koster tight-binding library for crystalline and disordered solids |
2024-01-12 11:49:29 |
| SolidsOpt |
0.1 |
This package is made to perfome topology optimization of 2D solids |
2024-01-03 17:52:41 |
| gentopo |
0.0.1 |
Generate network topologies and underlying sequences of interactions that lead to them. |
2023-11-28 16:54:55 |
| h-signature |
0.0.5 |
Topological H-signature |
2023-09-25 01:44:50 |
| ccsd |
0.3.3 |
CCSD (Combinatorial Complex Score-based Diffusion) is a sophisticated score-based diffusion model designed to generate Combinatorial Complexes using Stochastic Differential Equations. This cutting-edge approach enables the generation of complex objects with higher-order structures and relations, thereby enhancing our ability to learn underlying distributions and produce more realistic objects. |
2023-09-18 09:25:22 |
| epitools |
0.0.12 |
Quantifying 2D cell shape and epithelial tissue dynamics |
2023-08-15 11:18:17 |
| snappy |
3.1.1 |
Studying the topology and geometry of 3-manifolds, with a focus on hyperbolic structures. |
2023-06-14 01:49:00 |