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made radprof helper memoizable

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augustin_s
2024-08-05 18:03:53 +02:00
parent 45c6d99f7a
commit 26f41b5383
1 changed files with 5 additions and 5 deletions
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10
dap/algos/radprof.py
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@ -10,7 +10,7 @@ def calc_radial_integration(results, data, pixel_mask_pf, center, rad, norm):
rad = norm = None
if rad is None or norm is None:
rad, norm = prepare_radial_profile(data, center, keep_pixels=pixel_mask_pf)
rad, norm = prepare_radial_profile(data.shape, center, pixel_mask_pf)
r_min = min(rad)
r_max = max(rad) + 1
@ -27,7 +27,7 @@ def calc_radial_integration(results, data, pixel_mask_pf, center, rad, norm):
if threshold_max > threshold_min:
data[data > threshold_max] = np.nan
rp = radial_profile(data, rad, norm, keep_pixels=pixel_mask_pf)
rp = radial_profile(data, rad, norm, pixel_mask_pf)
silent_min = results.get("radial_integration_silent_min", None)
silent_max = results.get("radial_integration_silent_max", None)
@ -51,8 +51,8 @@ def calc_radial_integration(results, data, pixel_mask_pf, center, rad, norm):
return center, rad, norm
def prepare_radial_profile(data, center, keep_pixels=None):
y, x = np.indices(data.shape)
def prepare_radial_profile(shape, center, keep_pixels):
y, x = np.indices(shape)
x0, y0 = center
rad = np.sqrt((x - x0)**2 + (y - y0)**2)
if keep_pixels is not None:
@ -62,7 +62,7 @@ def prepare_radial_profile(data, center, keep_pixels=None):
return rad, norm
def radial_profile(data, rad, norm, keep_pixels=None):
def radial_profile(data, rad, norm, keep_pixels):
if keep_pixels is not None:
data = data[keep_pixels]
data = data.ravel()