All requirements can b installed by creating an environment using:
conda create --name <env> --file heartpinn_env.txt
pinn1D.py
can be run as is, the output will be the RMSE for the test data:
python pinn1D.py
´pinn2D.py' takes command line arguments train
and predict
. The code uses Pytorch as backlend, which has to be specified. For training run:
DDE_BACKEND=pytorch python pinn2D.py train
Similar to the 2D square run:
DDE_BACKEND=pytorch python heartpinn.py train