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Fixed type annotations in autofocus and mock stage

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I don't know why these didn't fail before - possibly because of
incomplete type information from old numpy...
I removed a few annotations because they were failing (e.g.
np.sum can return a scalar or an array), but I don't think
this should be a problem - the function inputs and return values
are still typed.
This commit is contained in:
Richard Bowman 2021-03-30 17:51:00 +01:00
parent cd5e32b843
commit e73ee8875c
2 changed files with 10 additions and 7 deletions
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15
openflexure_microscope/api/default_extensions/autofocus.py
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@ -129,18 +129,21 @@ def monitor_sharpness(microscope: Microscope):
def sharpness_sum_lap2(rgb_image: np.ndarray) -> float:
"""Return an image sharpness metric: sum(laplacian(image)**")"""
image_bw: float = np.mean(rgb_image, 2)
image_lap: float = ndimage.filters.laplace(image_bw)
return np.mean(image_lap.astype(float) ** 4)
image_bw = np.mean(rgb_image, 2)
image_lap = ndimage.filters.laplace(image_bw)
return float(np.mean(image_lap.astype(float) ** 4))
def sharpness_edge(image: np.ndarray) -> float:
"""Return a sharpness metric optimised for vertical lines"""
gray: float = np.mean(image.astype(float), 2)
gray = np.mean(image.astype(float), 2)
n: int = 20
edge: np.ndarray = np.array([[-1] * n + [1] * n])
return np.sum(
[np.sum(ndimage.filters.convolve(gray, W) ** 2) for W in [edge, edge.T]]
return float(
np.sum(
[np.sum(ndimage.filters.convolve(gray, W) ** 2)
for W in [edge, edge.T]]
)
)