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@@ -7,3 +7,4 @@ testing/ | |
| testing* | ||
| *.pyc | ||
| null/ | ||
| .idea/ | ||
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| @@ -0,0 +1,13 @@ | ||
| #!/usr/bin/env python | ||
| import sys | ||
| from drevalpy.utils import get_parser, check_arguments | ||
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| def main(argv=None): | ||
| """Coordinate argument parsing and program execution.""" | ||
| args = get_parser().parse_args(argv) | ||
| check_arguments(args) | ||
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| if __name__ == "__main__": | ||
| sys.exit(main()) |
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| #!/usr/bin/env python | ||
| import argparse | ||
| import pandas as pd | ||
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| from drevalpy.visualization.utils import prep_results, write_results | ||
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| def get_parser(): | ||
| parser = argparse.ArgumentParser(description="Collect results and write to single files.") | ||
| parser.add_argument("--outfiles", type=str, nargs="+", required=True, help="Output files.") | ||
| return parser | ||
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| def parse_results(args): | ||
| # get all files with the pattern f'{model_name}_evaluation_results.csv' from args.outfiles | ||
| result_files = [file for file in args.outfiles if "evaluation_results.csv" in file] | ||
| # get all files with the pattern f'{model_name}_evaluation_results_per_drug.csv' from args.outfiles | ||
| result_per_drug_files = [file for file in args.outfiles if "evaluation_results_per_drug.csv" in file] | ||
| # get all files with the pattern f'{model_name}_evaluation_results_per_cl.csv' from args.outfiles | ||
| result_per_cl_files = [file for file in args.outfiles if "evaluation_results_per_cl.csv" in file] | ||
| # get all files with the pattern f'{model_name}_true_vs_pred.csv' from args.outfiles | ||
| t_vs_pred_files = [file for file in args.outfiles if "true_vs_pred.csv" in file] | ||
| return result_files, result_per_drug_files, result_per_cl_files, t_vs_pred_files | ||
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| def collapse_file(files): | ||
| out_df = None | ||
| for file in files: | ||
| if out_df is None: | ||
| out_df = pd.read_csv(file, index_col=0) | ||
| else: | ||
| out_df = pd.concat([out_df, pd.read_csv(file, index_col=0)]) | ||
| return out_df | ||
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| if __name__ == "__main__": | ||
| args = get_parser().parse_args() | ||
| # parse the results from args.outfiles | ||
| eval_result_files, eval_result_per_drug_files, eval_result_per_cl_files, true_vs_pred_files = parse_results(args) | ||
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| # collapse the results into single dataframes | ||
| eval_results = collapse_file(eval_result_files) | ||
| eval_results_per_drug = collapse_file(eval_result_per_drug_files) | ||
| eval_results_per_cell_line = collapse_file(eval_result_per_cl_files) | ||
| t_vs_p = collapse_file(true_vs_pred_files) | ||
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| # prepare the results through introducing new columns algorithm, rand_setting, LPO_LCO_LDO, split, CV_split | ||
| eval_results, eval_results_per_drug, eval_results_per_cell_line, t_vs_p = prep_results( | ||
| eval_results, eval_results_per_drug, eval_results_per_cell_line, t_vs_p | ||
| ) | ||
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| # save the results to csv files | ||
| write_results( | ||
| path_out="", | ||
| eval_results=eval_results, | ||
| eval_results_per_drug=eval_results_per_drug, | ||
| eval_results_per_cl=eval_results_per_cell_line, | ||
| t_vs_p=t_vs_p, | ||
| ) |
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| @@ -0,0 +1,50 @@ | ||
| #!/usr/bin/env python | ||
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| import os | ||
| import argparse | ||
| from drevalpy.models import MODEL_FACTORY | ||
| from drevalpy.experiment import consolidate_single_drug_model_predictions | ||
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| def get_parser(): | ||
| parser = argparse.ArgumentParser(description="Consolidate results for SingleDrugModels") | ||
| parser.add_argument('--run_id', type=str, required=True, help="Run ID") | ||
| parser.add_argument("--test_mode", type=str, required=True, help="Test mode (LPO, LCO, LDO)") | ||
| parser.add_argument("--model_name", type=str, required=True, help="All Model " | ||
| "names") | ||
| parser.add_argument("--outdir_path", type=str, required=True, help="Output directory path") | ||
| parser.add_argument("--n_cv_splits", type=int, required=True, help="Number of CV splits") | ||
| parser.add_argument("--cross_study_datasets", type=str, nargs="+", help="All " | ||
| "cross-study " | ||
| "datasets") | ||
| parser.add_argument("--randomization_modes", type=str, required=True, help="All " | ||
| "randomizations") | ||
| parser.add_argument("--n_trials_robustness", type=int, required=True, help="Number of trials") | ||
| return parser | ||
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| def main(): | ||
| parser = get_parser() | ||
| args = parser.parse_args() | ||
| results_path = os.path.join( | ||
| args.outdir_path, | ||
| args.run_id, | ||
| args.test_mode, | ||
| ) | ||
| randomizations = args.randomization_modes.split('[')[1].split(']')[0].split(', ') | ||
| model = MODEL_FACTORY[args.model_name] | ||
| if args.cross_study_datasets is None: | ||
| args.cross_study_datasets = [] | ||
| consolidate_single_drug_model_predictions( | ||
| models=[model], | ||
| n_cv_splits=args.n_cv_splits, | ||
| results_path=results_path, | ||
| cross_study_datasets=args.cross_study_datasets, | ||
| randomization_mode=randomizations, | ||
| n_trials_robustness=args.n_trials_robustness, | ||
| out_path="" | ||
| ) | ||
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| if __name__ == "__main__": | ||
| main() |
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| @@ -0,0 +1,36 @@ | ||
| #!/usr/bin/env python | ||
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| import argparse | ||
| import pickle | ||
| import sys | ||
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| def get_parser(): | ||
| parser = argparse.ArgumentParser(description="Split data into CV splits") | ||
| parser.add_argument("--response", type=str, required=True, help="Path to response data") | ||
| parser.add_argument("--n_cv_splits", type=int, required=True, help="Number of CV splits") | ||
| parser.add_argument("--test_mode", type=str, default="LPO", help="Test mode (LPO, LCO, LDO)") | ||
| return parser | ||
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| def main(): | ||
| parser = get_parser() | ||
| args = parser.parse_args() | ||
| response_data = pickle.load(open(args.response, "rb")) | ||
| response_data.remove_nan_responses() | ||
| response_data.split_dataset( | ||
| n_cv_splits=args.n_cv_splits, | ||
| mode=args.test_mode, | ||
| split_validation=True, | ||
| split_early_stopping=True, | ||
| validation_ratio=0.1, | ||
| random_state=42, | ||
| ) | ||
| for split_index, split in enumerate(response_data.cv_splits): | ||
| with open(f"split_{split_index}.pkl", "wb") as f: | ||
| pickle.dump(split, f) | ||
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| if __name__ == "__main__": | ||
| main() | ||
| sys.exit(0) |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,29 @@ | ||
| #!/usr/bin/env python | ||
| import argparse | ||
| import pandas as pd | ||
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| from drevalpy.visualization.critical_difference_plot import CriticalDifferencePlot | ||
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| def get_parser(): | ||
| parser = argparse.ArgumentParser(description="Draw critical difference plots.") | ||
| parser.add_argument("--name", type=str, required=True, help="Name/Setting of plot.") | ||
| parser.add_argument("--data", type=str, required=True, help="Path to data.") | ||
| return parser | ||
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| def draw_cd(path_to_df: str, setting: str): | ||
| df = pd.read_csv(path_to_df, index_col=0) | ||
| df = df[(df["LPO_LCO_LDO"] == setting) & (df["rand_setting"] == "predictions")] | ||
| cd_plot = CriticalDifferencePlot( | ||
| eval_results_preds=df, | ||
| metric='MSE' | ||
| ) | ||
| cd_plot.draw_and_save( | ||
| out_prefix='', | ||
| out_suffix=setting | ||
| ) | ||
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| if __name__ == "__main__": | ||
| args = get_parser().parse_args() | ||
| draw_cd(path_to_df=args.data, setting=args.name) |
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