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re-use thresh function

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augustin_s
2024-08-09 19:45:32 +02:00
parent dcdacf4bdb
commit 2acf116709
3 changed files with 19 additions and 11 deletions
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8
dap/algos/forcesend.py
View File

@ -1,6 +1,7 @@
import numpy as np import numpy as np
from .mask import calc_mask_pixels from .mask import calc_mask_pixels
from .thresh import threshold
def calc_force_send(results, data, pixel_mask_pf, image, data_summed, n_aggregated_images): def calc_force_send(results, data, pixel_mask_pf, image, data_summed, n_aggregated_images):
@ -42,10 +43,9 @@ def calc_apply_threshold(results, data):
threshold_min = float(results["threshold_min"]) threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"]) threshold_max = float(results["threshold_max"])
data[data < threshold_min] = 0
#TODO: skipping max is a guess, but not obvious/symmetric -- better to ensure the order min < max by switching them if needed threshold(data, threshold_min, threshold_max, 0)
if threshold_max > threshold_min:
data[data > threshold_max] = 0
def calc_apply_aggregation(results, data, data_summed, n_aggregated_images): def calc_apply_aggregation(results, data, data_summed, n_aggregated_images):

7
dap/algos/radprof.py
View File

@ -1,5 +1,6 @@
import numpy as np import numpy as np
from .thresh import threshold
from .utils import npmemo from .utils import npmemo
@ -76,10 +77,8 @@ def calc_apply_threshold(results, data):
threshold_min = float(results["threshold_min"]) threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"]) threshold_max = float(results["threshold_max"])
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 threshold(data, threshold_min, threshold_max, np.nan)
if threshold_max > threshold_min:
data[data > threshold_max] = np.nan
return data return data

15
dap/algos/thresh.py
View File

@ -16,10 +16,19 @@ def calc_apply_threshold(results, data):
threshold_min = float(results["threshold_min"]) threshold_min = float(results["threshold_min"])
threshold_max = float(results["threshold_max"]) threshold_max = float(results["threshold_max"])
data[data < threshold_min] = threshold_value
threshold(data, threshold_min, threshold_max, threshold_value)
def threshold(data, vmin, vmax, replacement):
"""
threshold data in place by replacing values < vmin and values > vmax with 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 #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: if vmax > vmin:
data[data > threshold_max] = threshold_value data[data > vmin] = replacement