From aabc56b10ffea84a4288d2d8cb939e979dbc8a3c Mon Sep 17 00:00:00 2001 From: Tom Hall Date: Tue, 17 Dec 2024 23:38:51 +0000 Subject: [PATCH] typing fixes --- archeryutils/classifications/agb_field_classifications.py | 6 +++--- archeryutils/classifications/agb_outdoor_classifications.py | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/archeryutils/classifications/agb_field_classifications.py b/archeryutils/classifications/agb_field_classifications.py index c633464..9a27c31 100644 --- a/archeryutils/classifications/agb_field_classifications.py +++ b/archeryutils/classifications/agb_field_classifications.py @@ -32,7 +32,7 @@ class GroupData(TypedDict): classes_long: list[str] class_HC: npt.NDArray[np.float64] max_distance: int - min_dists: npt.NDArray[np.float64] + min_dists: npt.NDArray[np.int64] def _make_agb_field_classification_dict() -> dict[str, GroupData]: @@ -122,7 +122,7 @@ def _make_agb_field_classification_dict() -> dict[str, GroupData]: def _assign_dists( bowstyle: str, age: cls_funcs.AGBAgeData, -) -> list[int]: +) -> tuple[npt.NDArray[np.int64], int]: """ Assign appropriate minimum distance required for a category and classification. @@ -162,7 +162,7 @@ def _assign_dists( n_classes: int = 9 # [EMB, GMB, MB, B1, B2, B3, A1, A2, A3] - min_dists = np.empty(n_classes) + min_dists = np.zeros(n_classes, dtype=np.int64) min_dists[0:6] = min_d min_dists[6:9] = np.maximum(min_d - 10 * np.arange(1, 4), 30) diff --git a/archeryutils/classifications/agb_outdoor_classifications.py b/archeryutils/classifications/agb_outdoor_classifications.py index 41d38a3..cf25dd2 100644 --- a/archeryutils/classifications/agb_outdoor_classifications.py +++ b/archeryutils/classifications/agb_outdoor_classifications.py @@ -33,7 +33,7 @@ class GroupData(TypedDict): max_distance: list[int] classes_long: list[str] class_HC: npt.NDArray[np.float64] - min_dists: npt.NDArray[np.float64] + min_dists: npt.NDArray[np.int64] prestige_rounds: list[str] @@ -136,7 +136,7 @@ def _assign_min_dist( gender: str, age_group: str, max_dists: list[int], -) -> npt.NDArray[int]: +) -> npt.NDArray[np.int64]: """ Assign appropriate minimum distance required for a category and classification.