imputer_method = 'simple'
ale_path = '/work/mflora/ML_DATA/ALE_RESULTS'
start_time = datetime.datetime.now()
for combo in combos:
model_name, target, resample_method, normalize_method, time = combo
results_fname = join(
ale_path,
f'ale_results_{model_name}_{target}_{time}{drop_opt}{resample_method}.nc'
)
myInterpreter = InterpretToolkit()
myInterpreter.load_results(results_fname)
results = myInterpreter.calc_ale_variance(model_names=model_name)
save_fname = join(
ale_path,
f'ale_var_results_{model_name.replace("_under", "")}_{resample_method}_{target}_{time}{drop_opt}.nc'
)
print(f'Saving {save_fname}...')
myInterpreter.save_results(fname=save_fname, data=results)
duration = datetime.datetime.now() - start_time
seconds = duration.total_seconds()
hours = seconds // 3600
minutes = (seconds % 3600) // 60
seconds = seconds % 60
message = f"""
for combo in combos:
model_name, target, resample_method, normalize_method, time = combo
results_fname = join(ale_path, f'ale_2d_results_{model_name}_{target}_{time}{drop_opt}{resample_method}.nc')
myInterpreter = InterpretToolkit()
results_2d = myInterpreter.load_results(results_fname)
#if resample_method == 'under':
# model_name +='_under'
# Load the permutation important results from the saved pickle file
with open(f'IMPORTANT_FEATURES_ALL_MODELS_{target}_{time}.pkl', 'rb') as pkl_file:
important_vars = pickle.load(pkl_file)
features = list(itertools.combinations(important_vars, r=2))
results = myInterpreter.calc_ale_variance(ale_data=results_2d, features=features, interaction=True)
results_fname = join(ale_path, f'ale_interaction_results_{model_name.replace("_under", "")}_{resample_method}_{target}_{time}{drop_opt}.nc')
print(f'Saving {results_fname}...')
myInterpreter.save_results(fname=results_fname, data=results)
results_2d.close()
del results_2d
duration = datetime.datetime.now() - start_time
seconds = duration.total_seconds()
hours = seconds // 3600
minutes = (seconds % 3600) // 60
seconds = seconds % 60
message = f"""
