Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

added standard error of the mean to statistics_of_labelled_pixels #267

Open
wants to merge 6 commits into
base: master
Choose a base branch
from
Open

added standard error of the mean to statistics_of_labelled_pixels #267

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
61c7a31
added standard error of the mean to statistics_of_labelled_pixels
thawn Feb 27, 2023
704dc9a
use np.sqrt() instead of power()
thawn Feb 28, 2023
eab9941
fixed SEM calculation
thawn Mar 7, 2023
cddfacc
added test for standard error
thawn Mar 8, 2023
5048b66
added standard_error_intensity to push_regionprops
thawn Mar 20, 2023
ac21dc6
added tests for push_regionprops with SEM
thawn Mar 20, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 3 additions & 1 deletion pyclesperanto_prototype/_tier9/_push_regionprops.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,9 @@ def push_regionprops(props : Union[dict, RegionProperties], first_row_index : in
# MAX_DISTANCE_TO_CENTROID = 34
props['max_distance_to_centroid'],
# MAX_MEAN_DISTANCE_TO_CENTROID_RATIO = 35
props['mean_max_distance_to_centroid_ratio']
props['mean_max_distance_to_centroid_ratio'],
# STANDARD_ERROR_INTENSITY = 36
props['standard_error_intensity']
]

matrix = np.asarray(list).T
Expand Down
3 changes: 3 additions & 0 deletions pyclesperanto_prototype/_tier9/_statistics_of_labelled_pixels.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -276,6 +276,9 @@ def statistics_of_labelled_pixels(intensity_image : Image = None, label_image :
power(sum_dim, result_vector, 0.5)
region_props['standard_deviation_intensity'] = pull(result_vector)[0]

# standard error intensity
region_props['standard_error_intensity'] = region_props['standard_deviation_intensity'] / np.sqrt(region_props['area'])

crop(max_statistics, result_vector, measurements_start_x, 4, 0)
region_props['max_distance_to_centroid'] = pull(result_vector)[0]
crop(max_statistics, result_vector, measurements_start_x, 5, 0)
Expand Down
17 changes: 12 additions & 5 deletions tests/test_statistics_of_labelled_pixels.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -90,8 +90,10 @@ def test_statistics_of_labelled_pixels():
[0.65403885, 0.65403885, 0.6666667],
# MAX_DISTANCE_TO_CENTROID(34),
[0.74535596, 0.745356, 1.],
# MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35);
[1.1396203, 1.1396204, 1.5]
# MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35),
[1.1396203, 1.1396204, 1.5],
# STANDARD_ERROR_INTENSITY(36);
[0.27216553, 0.27216551, 0.4714043]
]
))

Expand Down Expand Up @@ -205,8 +207,10 @@ def test_statistics_of_labelled_pixels_3d():
[0.65403885, 0.65403885, 0.6666667],
# MAX_DISTANCE_TO_CENTROID(34),
[0.74535596, 0.745356, 1.],
# MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35);
[1.1396203, 1.1396204, 1.5]
# MAX_MEAN_DISTANCE_TO_CENTROID_RATIO(35),
[1.1396203, 1.1396204, 1.5],
# STANDARD_ERROR_INTENSITY(36);
[0.27216553, 0.27216551, 0.4714043]
]
))

Expand All @@ -226,7 +230,7 @@ def test_statistics_of_labelled_pixels_3d():
assert (np.allclose(a, b, 0.0001))


def test_standard_deviation():
def test_standard_deviation_and_standard_error():
import numpy as np

image = np.asarray([
Expand All @@ -243,11 +247,14 @@ def test_standard_deviation():

print("numpy standard deviation", np.std(image))
print("numpy variance", np.var(image))
print("numpy standard error", np.std(image) / np.sqrt(image.size))

stats = cle.statistics_of_labelled_pixels(image, labels)

print("std", stats['standard_deviation_intensity'][0])
print("sterr", stats['standard_error_intensity'][0])

from numpy import testing
testing.assert_almost_equal(stats['standard_deviation_intensity'][0], 2.58, decimal=1)
testing.assert_almost_equal(stats['standard_error_intensity'][0], 0.86, decimal=1)