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⚡️ Speed up function image_rotation by 2,904% #106

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⚡️ Speed up function image_rotation by 2,904% #106

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23 changes: 15 additions & 8 deletions src/numpy_pandas/signal_processing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,14 +41,21 @@ def image_rotation(image: np.ndarray, angle_degrees: float) -> np.ndarray:
else (new_height, new_width)
)
new_center_y, new_center_x = new_height // 2, new_width // 2
for y in range(new_height):
for x in range(new_width):
offset_y = y - new_center_y
offset_x = x - new_center_x
original_y = int(offset_y * cos_theta - offset_x * sin_theta + center_y)
original_x = int(offset_y * sin_theta + offset_x * cos_theta + center_x)
if 0 <= original_y < height and 0 <= original_x < width:
rotated[y, x] = image[original_y, original_x]
y, x = np.meshgrid(np.arange(new_height), np.arange(new_width), indexing="ij")
offset_y = y - new_center_y
offset_x = x - new_center_x
original_y = (offset_y * cos_theta - offset_x * sin_theta + center_y).astype(int)
original_x = (offset_y * sin_theta + offset_x * cos_theta + center_x).astype(int)
valid_mask = (
(0 <= original_y)
& (original_y < height)
& (0 <= original_x)
& (original_x < width)
)
if len(image.shape) > 2:
rotated[valid_mask] = image[original_y[valid_mask], original_x[valid_mask], :]
else:
rotated[valid_mask] = image[original_y[valid_mask], original_x[valid_mask]]
return rotated


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