Releases: WUR-AI/diffWOFOST
Releases · WUR-AI/diffWOFOST
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_dynamicsin #69
Added:
- use all test data in unit tests in #54
- implementation of a differentiable and vectorized
root_dynamicsin #55 - implementation of a differentiable and vectorized
root_dynamicsin #56 - implementation of a differentiable and vectorized
pehnologyin #57 - a configuration module in #59
- support
dtypeanddevicewith GPU tests in #65 - an optimization notebook for phenology in #67
- implementation of a differentiable and vectorized
partitioningin #70 - implementation of a differentiable and vectorized
assimilationin #71
v0.2.0
This release comes with changes as:
Added:
- implementation of a differentiable
root_dynamicsw.r.t the parameterTDWIin #29 - a notebook showing how optimization of parameters in
leaf_dynamicsandroot_dynamicscan be done using pytorch in #35 - vectorize the computations in
leaf_dynamicsw.r.t its parameters in #36 - documentation in #38
- a logo for diffwofost package in #31
v0.1.1
Test Release (Github Workflow PyPI)