| Name | Version | Summary | date |
| l0-python |
0.1.0 |
L0 regularization for sparse neural networks and intelligent sampling |
2025-08-18 09:17:06 |
| forecast-pert |
0.3.5 |
Calibrated three-point (PERT) distributions with empirical-Bayes bias correction |
2025-08-17 20:12:27 |
| tunax |
0.2.5 |
Differential calibrator of the vertical ocean turbulence closures. |
2025-08-12 17:00:14 |
| punchbowl |
0.0.18 |
PUNCH science calibration code |
2025-08-06 19:18:51 |
| pyCANape |
0.8.1 |
Pythonic wrapper around the VECTOR CANape API |
2025-07-26 12:13:58 |
| adao |
9.15.0.1 |
ADAO: A module for Data Assimilation and Optimization |
2025-07-19 15:12:55 |
| pyhail |
3.3.0 |
Python hail retreivals |
2025-07-18 04:06:03 |
| evopt |
0.14.3 |
User Friendly Data-Driven Numerical Optimization |
2025-03-18 21:03:10 |
| spotpy |
1.6.6 |
A Statistical Parameter Optimization Tool. |
2025-02-18 09:55:48 |
| gpcal |
0.9.6.0 |
A generalized instrumental polarization calibration pipeline for VLBI data |
2025-01-25 15:42:51 |
| icc-generator |
0.8.0 |
A Python module that lets the users to create Printer Profiles with Argyll CMS and X-Rite ColorMunki Photo and X-Rite i1Pro 2/3 |
2025-01-23 09:42:45 |
| pyxel-sim |
2.8.1 |
Pyxel detector simulation framework. |
2025-01-16 12:16:32 |
| adafruit-circuitpython-as7341 |
1.2.20 |
CircuitPython library for use with the Adafruit AS7341 breakout |
2025-01-08 19:23:35 |
| reftools |
2.2.0 |
HST reference files tools |
2024-09-16 16:28:56 |
| dtscalibration |
3.1.0 |
Load Distributed Temperature Sensing (DTS) files, calibrate the temperature and estimate its uncertainty. |
2024-09-13 13:30:49 |
| ctdcal |
0.1.5b1.dev0 |
CTD and bottle data processing package from UCSD ODF |
2024-09-12 18:56:27 |
| acstools |
3.7.2 |
Python Tools for HST ACS |
2024-09-11 13:53:21 |
| venn-abers |
1.4.6 |
Venn-ABERS calibration package |
2024-09-10 21:39:22 |
| dirichletcal |
0.5.2 |
Python code for Dirichlet calibration |
2024-08-05 18:52:13 |
| thetis |
0.2.1 |
Service to examine data processing pipelines (e.g., machine learning or deep learning pipelines) for uncertainty consistency (calibration), fairness, and other safety-relevant aspects. |
2024-06-11 14:26:21 |