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augustin_s
2024-08-09 15:57:17 +02:00
parent 5f055c8718
commit 442a7dab28
3 changed files with 5 additions and 4 deletions
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2
dap/algos/forcesend.py
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@ -28,6 +28,7 @@ def calc_force_send(results, data, pixel_mask_pf, image, data_summed, n_aggregat
#TODO: this is duplicated in calc_apply_threshold and calc_radial_integration
def calc_apply_threshold(results, data):
apply_threshold = results.get("apply_threshold", False)
if not apply_threshold:
@ -37,7 +38,6 @@ def calc_apply_threshold(results, data):
if k not in results:
return
#TODO: this is duplicated in calc_apply_threshold and calc_radial_integration
threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"])
data[data < threshold_min] = 0

5
dap/algos/radprof.py
View File

@ -62,6 +62,7 @@ def radial_profile(data, rad, norm, keep_pixels):
#TODO: this is duplicated in calc_apply_threshold and calc_force_send
def calc_apply_threshold(results, data):
apply_threshold = results.get("apply_threshold", False)
if not apply_threshold:
@ -71,10 +72,10 @@ def calc_apply_threshold(results, data):
if k not in results:
return
#TODO: this is duplicated in calc_apply_threshold and calc_force_send
data = data.copy() # do the following in-place changes on a copy
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:

2
dap/algos/thresh.py
View File

@ -1,6 +1,7 @@
import numpy as np
#TODO: this is duplicated in calc_radial_integration and calc_force_send
def calc_apply_threshold(results, data):
apply_threshold = results.get("apply_threshold", False)
if not apply_threshold:
@ -13,7 +14,6 @@ def calc_apply_threshold(results, data):
threshold_value_choice = results.get("threshold_value", "NaN")
threshold_value = 0 if threshold_value_choice == "0" else np.nan #TODO
#TODO: this is duplicated in calc_radial_integration and calc_force_send
threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"])
data[data < threshold_min] = threshold_value