| import pandas as pd |
| from pathlib import Path |
| from tqdm import tqdm |
|
|
| def find_last_true_index(interpolated_series): |
| |
| true_indices = interpolated_series[interpolated_series == True].index |
| if len(true_indices) > 0: |
| return true_indices[-1] |
| return None |
|
|
| def analyze_all_samples(data_dir): |
| |
| data_path = Path(data_dir) |
| parquet_files = sorted(data_path.glob("*.parquet")) |
| |
| results = [] |
| |
| for parquet_file in tqdm(parquet_files, desc="analyzing samples"): |
| sample_name = parquet_file.stem |
| |
| df = pd.read_parquet(parquet_file) |
| |
| if 'interpolated' not in df.columns: |
| print(f"warning: {sample_name} has no interpolated column") |
| continue |
| |
| last_true_idx = find_last_true_index(df['interpolated']) |
| |
| results.append({ |
| 'sample': sample_name, |
| 'last_true_index': last_true_idx |
| }) |
| |
| |
| results_df = pd.DataFrame(results) |
| |
| |
| output_csv = Path(data_dir).parent / 'interpolated_analysis.csv' |
| results_df.to_csv(output_csv, index=False) |
| print(f"\nresults saved to: {output_csv}") |
| |
| return results_df |
|
|
| |
| if __name__ == "__main__": |
| data_dir = "./trajectories" |
| results = analyze_all_samples(data_dir) |
| |
| print("\nanalysis results:") |
| print(results) |
| print(f"\nstatistics:") |
| print(results.describe()) |