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

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-06-17 14:45:27 +02:00
parent d402cdace3
commit 9e97fb8159
3 changed files with 13 additions and 13 deletions
+6 -6
View File
@@ -297,18 +297,18 @@ def predict(
"pre_y": chunk["pre_pos"][:, 1],
"pre_z": chunk["pre_pos"][:, 2],
"pre_E": chunk["pre_E"],
"pre_dir_x": chunk["pre_dir"][:, 0],
"pre_dir_y": chunk["pre_dir"][:, 1],
"pre_dir_z": chunk["pre_dir"][:, 2],
"pre_dx": chunk["pre_dir"][:, 0],
"pre_dy": chunk["pre_dir"][:, 1],
"pre_dz": chunk["pre_dir"][:, 2],
"material": chunk["material"],
"layer_id": chunk["layer_id"],
"n_sec": chunk["n_sec"],
"step_length": step_length,
"delta_e": delta_e,
"edep": edep,
"post_dir_x": post_dir_world[:, 0],
"post_dir_y": post_dir_world[:, 1],
"post_dir_z": post_dir_world[:, 2],
"post_dx": post_dir_world[:, 0],
"post_dy": post_dir_world[:, 1],
"post_dz": post_dir_world[:, 2],
})
if writer is None:
+4 -4
View File
@@ -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),
+3 -3
View File
@@ -8,9 +8,9 @@ _TARGET_NAMES = [
"log_step_length",
"log_delta_e",
"log_edep",
"post_dir_x",
"post_dir_y",
"post_dir_z",
"post_dx",
"post_dy",
"post_dz",
]