print("Index:", index)
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
job_samples = 50
tree_path_dependent_shap_interact_cache = SimpleCache(
f"tree_path_dependent_shap_interact_{index}_{job_samples}",
cache_dir=os.path.join(CACHE_DIR, "shap_interaction"),
)
@tree_path_dependent_shap_interact_cache
def get_interact_shap_values(model, X):
return get_shap_values(model, X, interaction=True)
get_interact_shap_values(
rf, X_train[index * job_samples : (index + 1) * job_samples]
)
if __name__ == "__main__":
handle_array_job_args(
Path(__file__).resolve(),
func,
ncpus=1,
mem="5gb",
walltime="10:00:00",
max_index=1,
)
fig, axes = pdp.pdp_interact_plot(
pdp_interact_out, features, x_quantile=True, figsize=(7, 8)
)
axes["pdp_inter_ax"].xaxis.set_tick_params(rotation=45)
figure_saver.save_figure(fig, "__".join(features), sub_directory="pdp_2d")
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
columns_list = list(combinations(X_train.columns, 2))
index = int(os.environ["PBS_ARRAY_INDEX"])
print("Index:", index)
print("Columns:", columns_list[index])
ncpus = get_ncpus()
print("NCPUS:", ncpus)
# Use the array index to select the desired columns.
save_pdp_plot_2d(rf, X_train, columns_list[index], ncpus)
if __name__ == "__main__":
handle_array_job_args(
Path(__file__).resolve(),
func,
ncpus=8,
mem="90gb",
walltime="50:00:00",
max_index=1224,
)
figsize=(7, 8))
axes["pdp_inter_ax"].xaxis.set_tick_params(rotation=45)
figure_saver.save_figure(fig,
"__".join(features),
sub_directory="pdp_2d")
X_train, X_test, y_train, y_test = data_split_cache.load()
results, rf = cross_val_cache.load()
columns_list = list(combinations(X_train.columns, 2))
index = int(os.environ["PBS_ARRAY_INDEX"])
print("Index:", index)
print("Columns:", columns_list[index])
ncpus = get_ncpus()
print("NCPUS:", ncpus)
# Use the array index to select the desired columns.
save_pdp_plot_2d(rf, X_train, columns_list[index], ncpus)
if __name__ == "__main__":
handle_array_job_args(
Path(__file__).resolve(),
func,
ncpus=7,
mem="60gb",
walltime="24:00:00",
max_index=104,
)
