AI4SIM / model-collection

This project contains a collection of deep learning models developed by the AI4Sim team with various partners. This is structured on the basis of use-cases providing canonical PyTorch Lightning pipelines allowing to train neural network models that are able to surrogate various physical processes.
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Document the ecrad-3d-correction use case #43

Closed cbovalo closed 3 hours ago

cbovalo commented 5 hours ago

The purpose of this PR is to document the 3d correction use case. It describes briefly the scientific question, the dataset and the neural architecture.

github-actions[bot] commented 5 hours ago

Coverage report for cfd/combustion/unets model project

File Coverage Missing
All files 90% :white_check_mark:
config.py 95% :white_check_mark: 38
data.py 91% :white_check_mark: 62 76 79 122 132 138
models.py 87% :white_check_mark: 41-42 45 48
trainer.py 73% :white_check_mark: 58-61 65-67 71
unet.py 96% :white_check_mark: 90 120

Minimum allowed coverage is 0%

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github-actions[bot] commented 5 hours ago

Coverage report for weather-forecast/gravity-wave-drag/cnns model project

File Coverage Missing
All files 93% :white_check_mark:
config.py 95% :white_check_mark: 37
data.py 98% :white_check_mark: 162
models.py 89% :white_check_mark: 37-40 90 99
trainer.py 84% :white_check_mark: 75-77 81

Minimum allowed coverage is 0%

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github-actions[bot] commented 5 hours ago

Coverage report for cfd/combustion/gnns model project

File Coverage Missing
All files 83% :white_check_mark:
config.py 91% :white_check_mark: 44 78-81 108
data.py 81% :white_check_mark: 109-136 163 215
inferer.py 89% :white_check_mark: 224-240
models.py 69% :white_check_mark: 85 116-139 164-168 218-222
plotters.py 92% :white_check_mark: 55-56 142-143 146-147 160 165
trainer.py 68% :white_check_mark: 67-72 81-83 87-89

Minimum allowed coverage is 0%

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github-actions[bot] commented 5 hours ago

Coverage report for weather-forecast/ecrad-3d-correction/unets model project

File Coverage Missing
All files 89% :white_check_mark:
config.py 95% :white_check_mark: 25
dataproc.py 92% :white_check_mark: 140 144-145 184-186
models.py 77% :white_check_mark: 52 62-63 66-70 94-95 98 101 104 107
trainer.py 72% :white_check_mark: 65-68 72-74 78
unet.py 94% :white_check_mark: 89 119 122

Minimum allowed coverage is 0%

Generated by :monkey: cobertura-action against e2c6b6eedbbfa8dbb4d3c0cd40228e6c2c7bc691