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fixed TODOs regardin numpy index start > stop

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augustin_s
2025-10-31 18:10:54 +01:00
parent 59cb9a8235
commit 90e6fbe51a
3 changed files with 15 additions and 16 deletions
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20
dap/algos/radprof.py
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@@ -24,18 +24,14 @@ def calc_radial_integration(results, data, pixel_mask):
silent_min = results.get("radial_integration_silent_min", None) silent_min = results.get("radial_integration_silent_min", None)
silent_max = results.get("radial_integration_silent_max", None) silent_max = results.get("radial_integration_silent_max", None)
if ( if silent_min is not None and silent_max is not None:
silent_min is not None and # if start > stop, numpy returns an empty array -- better to ensure start < stop by switching them if needed
silent_max is not None and silent_min, silent_max = sorted((silent_min, silent_max))
#TODO: skipping entirely is a guess, but not obvious -- better to ensure the order min < max by switching them if needed if silent_min > r_min and silent_max < r_max:
silent_max > silent_min and silent_region = rp[silent_min:silent_max]
silent_min > r_min and integral_silent_region = np.sum(silent_region)
silent_max < r_max rp = rp / integral_silent_region
): results["radint_normalised"] = [silent_min, silent_max]
silent_region = rp[silent_min:silent_max]
integral_silent_region = np.sum(silent_region)
rp = rp / integral_silent_region
results["radint_normalised"] = [silent_min, silent_max]
results["radint_I"] = rp[r_min:].tolist() #TODO: why not stop at r_max? results["radint_I"] = rp[r_min:].tolist() #TODO: why not stop at r_max?
results["radint_q"] = [r_min, r_max] results["radint_q"] = [r_min, r_max]

5
dap/algos/roi.py
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@@ -25,7 +25,10 @@ def calc_roi(results, data):
roi_intensities_proj_x = [] roi_intensities_proj_x = []
for ix1, ix2, iy1, iy2 in zip(roi_x1, roi_x2, roi_y1, roi_y2): for ix1, ix2, iy1, iy2 in zip(roi_x1, roi_x2, roi_y1, roi_y2):
#TODO: if start > stop, numpy returns an empty array, which is not obvious -- better to ensure the order start < stop by switching them if needed # if start > stop, numpy returns an empty array -- better to ensure start < stop by switching them if needed
ix1, ix2 = sorted((ix1, ix2))
iy1, iy2 = sorted((iy1, iy2))
data_roi = data[iy1:iy2, ix1:ix2] data_roi = data[iy1:iy2, ix1:ix2]
roi_sum = np.nansum(data_roi, dtype=float) # data_roi is np.float32, which cannot be json serialized roi_sum = np.nansum(data_roi, dtype=float) # data_roi is np.float32, which cannot be json serialized

6
dap/algos/thresh.py
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@@ -25,10 +25,10 @@ def threshold(data, vmin, vmax, replacement):
""" """
threshold data in place by replacing values < vmin and values > vmax with replacement threshold data in place by replacing values < vmin and values > vmax with replacement
""" """
# if vmin > vmax, data will be overwritten entirely -- better to ensure vmin < vmax by switching them if needed
vmin, vmax = sorted((vmin, vmax))
data[data < vmin] = replacement data[data < vmin] = replacement
#TODO: skipping max is a guess, but not obvious/symmetric -- better to ensure the order min < max by switching them if needed data[data > vmax] = replacement
if vmax > vmin:
data[data > vmax] = replacement