v0.5.0

This release comes with changes as:

Added:

• Hybrid modeling is added with an notebook example in #108 and #119
• A differentiable and vectorized version of WaterbalanceFD, supporting wofost_72_WLP_CWB in #118
• VariableKiosk is fixed to support external_state_list in #103
• The method setup() is added to Engine, making it reusable without re-instantiating in #106

Fixed:

• Fix physical parameter values in full tests in #104
• Replace coverage run with the pytest-cov, which handles parallel coverage correctly in #109
• Update documentation in #121

v0.4.0

This release comes with changes as:

Fixed:

• fix some typos in the notebooks in #80
• fix device and dtype in #86
• make the build action faster by introducing fast and full tests in #92

Added:

• implementation of a differentiable and vectorized evapotranspiration in #78
• implementation of a differentiable and vectorized stem_dynamics in #79
• implementation of a differentiable and vectorized storage_organ_dynamics in #83
• implementation of a differentiable and vectorized wofost72 in #94
• Make astro and daylenght pytorch compatible in #95
• a notebook for optimization of parameters in wofost72_pp

v0.3.0

This release comes with changes as:

Fixed:

• logo is updated in #63
• phenology tests in #64
• split the leaf_dynamics and root dynamics notebook in #69
• update documentation in #77
• fix sigmoid approximation in leaf_dynamics in #69

Added:

• use all test data in unit tests in #54
• implementation of a differentiable and vectorized root_dynamics in #55
• implementation of a differentiable and vectorized root_dynamics in #56
• implementation of a differentiable and vectorized pehnology in #57
• a configuration module in #59
• support dtype and device with GPU tests in #65
• an optimization notebook for phenology in #67
• implementation of a differentiable and vectorized partitioning in #70
• implementation of a differentiable and vectorized assimilation in #71

v0.2.0

This release comes with changes as:

Added:

• implementation of a differentiable root_dynamics w.r.t the parameter TDWI in #29
• a notebook showing how optimization of parameters in leaf_dynamics and root_dynamics can be done using pytorch in #35
• vectorize the computations in leaf_dynamics w.r.t its parameters in #36
• documentation in #38
• a logo for diffwofost package in #31

v0.1.1

Test Release (Github Workflow PyPI)