Refactored exogenous data handling in the forward pass and training. This enabled deletion of some specialized models, which creates breaking changes.

Dual data handler added for using different datasets for low res and high res data for training. For example, low_res = ERA5 data and high_res = WTK.

GAPS integration for command line interface and job handling. Allowed removal of reV dependency.

What's Changed

• Bnb/dev by @bnb32 in #148
• WindGanDC model by @bnb32 in #150
• Bnb/bc smoothing by @bnb32 in #151
• Bnb/dev by @bnb32 in #152
• Bug fix for conditional moment with topography by @malihass in #149
• Use multi gpu for conditional moment estimation by @malihass in #157
• Bnb/log interp by @bnb32 in #155
• Gb/skill by @grantbuster in #163
• Bnb/h5 with era training by @bnb32 in #162
• Bnb/dual dh patch by @bnb32 in #164
• Bnb/ws power law by @bnb32 in #165
• bug fix on bias calc object initialization named args and cli parsing by @grantbuster in #166
• Bnb/exo refactor by @bnb32 in #167
• GAPs integration by @ppinchuk in #168
• Bnb/exo refactor plus by @bnb32 in #169
• Update version.py by @bnb32 in #170

New Contributors

• @ppinchuk made their first contribution in #168

Full Changelog: v0.1.0...v0.1.1