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flatten the code; early exit

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augustin_s
2024-08-09 15:54:54 +02:00
parent 2103583aca
commit 5f055c8718
1 changed files with 13 additions and 8 deletions
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21
dap/algos/radprof.py
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@ -64,16 +64,21 @@ def radial_profile(data, rad, norm, keep_pixels):
def calc_apply_threshold(results, data):
apply_threshold = results.get("apply_threshold", False)
if not apply_threshold:
return
for k in ("threshold_min", "threshold_max"):
if k not in results:
return
#TODO: this is duplicated in calc_apply_threshold and calc_force_send
if apply_threshold and all(k in results for k in ("threshold_min", "threshold_max")):
threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"])
data = data.copy() # do the following in-place changes on a copy
data[data < threshold_min] = np.nan
#TODO: skipping max is a guess, but not obvious/symmetric -- better to ensure the order min < max by switching them if needed
if threshold_max > threshold_min:
data[data > threshold_max] = np.nan
threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"])
data = data.copy() # do the following in-place changes on a copy
data[data < threshold_min] = np.nan
#TODO: skipping max is a guess, but not obvious/symmetric -- better to ensure the order min < max by switching them if needed
if threshold_max > threshold_min:
data[data > threshold_max] = np.nan
return data