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No newaxis, still extremely slow method for white field scale; TODO: use median instead

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Dorofeeva Elizaveta (EXT)
2025-07-14 22:42:05 +02:00
parent f1828cb4b5
commit 90c0b9cf3d
1 changed files with 4 additions and 7 deletions
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dap/algos/streakfind.py
+4 -7
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@@ -106,15 +106,12 @@ def _scale_whitefield(data, mask, whitefield, std,
n_iter: int = 12, lm: float = 9.0, num_threads: int = 16
):
mask = mask & (std > 0.0)
#y = np.where(mask, data / std, 0.0)[mask] # must be newaxis
y = np.divide(data, std, out=np.zeros_like(data), where=mask)[mask] # must be newaxis
#W = np.where(mask, whitefield / std, 0.0)[mask] # must be newaxis
y = np.divide(data, std, out=np.zeros_like(data), where=mask)[mask]
W = np.divide(whitefield, std, out=np.zeros_like(data), where=mask)[mask]
W = np.divide(whitefield, std, out=np.zeros_like(data), where=mask)[mask] # must be newaxis
#W = np.where(mask, whitefield / std, 0.0)[mask] # must be newaxis
scales = robust_lsq(W=W[np.newaxis, :], y=y[np.newaxis, :], axis=1, r0=r0, r1=r1, n_iter=n_iter, lm=lm,
scales = robust_lsq(W=W, y=y, axis=0, r0=r0, r1=r1, n_iter=n_iter, lm=lm,
num_threads=num_threads)
print(f"{scales=}")
scales=np.ravel(scales)
whitefield *= scales