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early exit

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augustin_s
2025-10-31 17:25:27 +01:00
parent e1c1054977
commit 45085abfb6
1 changed files with 13 additions and 12 deletions
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dap/algos/streakfind.py
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@@ -221,18 +221,19 @@ def _calc_streakfinder_analysis(results, snr, mask):
def _get_concentric_only_mask(x_center, y_center, crop_roi, streak_lines, threshold=0.33): def _get_concentric_only_mask(x_center, y_center, crop_roi, streak_lines, threshold=0.33):
if x_center is not None and y_center is not None: if x_center is None or y_center is None:
if crop_roi is not None: return None
x_center -= crop_roi[0] if crop_roi is not None:
y_center -= crop_roi[2] x_center -= crop_roi[0]
centers = np.mean(streak_lines.reshape(-1, 2, 2), axis=1) y_center -= crop_roi[2]
norm = np.stack([streak_lines[:, 3] - streak_lines[:, 1], centers = np.mean(streak_lines.reshape(-1, 2, 2), axis=1)
streak_lines[:, 0] - streak_lines[:, 2]], axis=-1) norm = np.stack([streak_lines[:, 3] - streak_lines[:, 1],
r = centers - np.asarray([x_center, y_center]) streak_lines[:, 0] - streak_lines[:, 2]], axis=-1)
prod = np.sum(norm * r, axis=-1)[..., None] r = centers - np.asarray([x_center, y_center])
proj = r - prod * norm / np.sum(norm ** 2, axis=-1)[..., None] prod = np.sum(norm * r, axis=-1)[..., None]
streaks_mask = np.sqrt(np.sum(proj ** 2, axis=-1)) / np.sqrt(np.sum(r ** 2, axis=-1)) < threshold proj = r - prod * norm / np.sum(norm ** 2, axis=-1)[..., None]
return streaks_mask streaks_mask = np.sqrt(np.sum(proj ** 2, axis=-1)) / np.sqrt(np.sum(r ** 2, axis=-1)) < threshold
return streaks_mask