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Code Issues 3 Pull Requests 2 Actions Packages Projects Releases Wiki Activity

Rename direction columns from pre_dir_x/y/z to pre_dx/dy/dz

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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
lars
2026-06-17 14:45:27 +02:00
co-authored by Claude Sonnet 4.6
parent d402cdace3
commit 9e97fb8159
3 changed files with 13 additions and 13 deletions
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giant/data/loader.py
+4 -4
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@@ -22,14 +22,14 @@ def _df_to_dict(df: pd.DataFrame) -> dict[str, np.ndarray]:
"pdg": df["pdg"].to_numpy(dtype=np.int32),
"pre_pos": df[["pre_x", "pre_y", "pre_z"]].to_numpy(dtype=np.float32),
"pre_E": df["pre_E"].to_numpy(dtype=np.float32),
"pre_dir": df[["pre_dir_x", "pre_dir_y", "pre_dir_z"]].to_numpy(dtype=np.float32),
"pre_dir": df[["pre_dx", "pre_dy", "pre_dz"]].to_numpy(dtype=np.float32),
"material": df["material"].to_numpy(dtype=object),
"layer_id": df["layer_id"].to_numpy(dtype=np.int32),
"n_sec": df["child_track_ids"].apply(len).to_numpy(dtype=np.int32),
"step_length": df["step_length"].to_numpy(dtype=np.float32),
"delta_e": (df["pre_E"] - df["post_E"]).to_numpy(dtype=np.float32),
"edep": df["edep"].to_numpy(dtype=np.float32),
"post_dir": df[["post_dir_x", "post_dir_y", "post_dir_z"]].to_numpy(dtype=np.float32),
"post_dir": df[["post_dx", "post_dy", "post_dz"]].to_numpy(dtype=np.float32),
}
@@ -52,7 +52,7 @@ def iter_file_chunks(path: str | Path) -> Iterator[dict[str, np.ndarray]]:
_COND_COLS = [
"event_id", "pdg",
"pre_x", "pre_y", "pre_z", "pre_E",
"pre_dir_x", "pre_dir_y", "pre_dir_z",
"pre_dx", "pre_dy", "pre_dz",
"material", "layer_id", "child_track_ids",
]
@@ -63,7 +63,7 @@ def _cond_df_to_dict(df: pd.DataFrame) -> dict[str, np.ndarray]:
"pdg": df["pdg"].to_numpy(dtype=np.int32),
"pre_pos": df[["pre_x", "pre_y", "pre_z"]].to_numpy(dtype=np.float32),
"pre_E": df["pre_E"].to_numpy(dtype=np.float32),
"pre_dir": df[["pre_dir_x", "pre_dir_y", "pre_dir_z"]].to_numpy(dtype=np.float32),
"pre_dir": df[["pre_dx", "pre_dy", "pre_dz"]].to_numpy(dtype=np.float32),
"material": df["material"].to_numpy(dtype=object),
"layer_id": df["layer_id"].to_numpy(dtype=np.int32),
"n_sec": df["child_track_ids"].apply(len).to_numpy(dtype=np.int32),