PyDigger - unearthing stuff about Python


NameVersionSummarydate
swiglpk 5.0.12 swiglpk - Simple swig bindings for the GNU Linear Programming Kit 2024-11-25 14:04:41
mozjpeg-lossless-optimization 1.1.5 Optimize JPEGs losslessly using MozJPEG 2024-11-22 14:54:14
qpalm 1.2.5 Proximal Augmented Lagrangian method for Quadratic Programs 2024-11-22 00:11:35
flowty 2.1.0 Flowty Network Optimization Solver 2024-11-21 10:59:30
gurobi-modelanalyzer 2.1.0 Model analysis tools for explaining ill-conditioning and analyzing solutions. 2024-11-12 13:27:33
fcmaes 1.6.11 A Python 3 gradient-free optimization library. 2024-11-07 11:02:08
SplitFXM 0.4.6 1D Finite-Difference/Volume Split Newton Solver 2024-10-24 17:52:48
xpressinsight 1.12.0 FICO Xpress - Insight Python package 2024-10-22 10:54:11
pulp-utils 0.1.7 pulp_utils is a library with utility tools for PuLP 2024-10-14 06:59:42
optimas 0.7.1 Optimization at scale, powered by libEnsemble 2024-09-20 21:16:10
qpax 0.0.9 Differentiable QP solver in JAX. 2024-09-16 17:04:00
pysors 1.0.0 Fork of second-order-random-search with scipy.minimize-like interface. 2024-09-14 08:35:26
findi-descent 0.2.0 FinDi: Finite Difference Gradient Descent can optimize any function, including the ones without analytic form, by employing finite difference numerical differentiation within a gradient descent algorithm. 2024-09-14 03:48:51
eesrep 0.1.5 EESREP is a component based energy system optimisation python module. 2024-09-03 08:36:16
cma 4.0.0 CMA-ES, Covariance Matrix Adaptation Evolution Strategy for non-linear numerical optimization in Python 2024-09-03 07:46:12
stelladb 0.2.13 Includes functions to upload DESC and VMEC data to the stellarator database. 2024-08-28 04:57:54
fortoptim 0.0.10 Another optimization package 2024-08-24 14:29:23
FortOptim 0.0.4 My custom optimization package 2024-08-24 08:09:14
pyhms 0.1.1 The HMS (Hierarchic Memetic Strategy) is a composite global optimization strategy consisting of a multi-population evolutionary strategy and some auxiliary methods. The HMS makes use of a tree with a fixed maximal height and variable internal node degree. Each component population is governed by a particular evolutionary engine. This package provides a simple python implementation with examples of using different population engines. 2024-08-22 15:44:21
obsidian-apo 0.8.3 Automated experiment design and black-box optimization 2024-08-22 02:33:14
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