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

[bugfix] adjust calculatemoments code to properly use labels #228

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

[bugfix] adjust calculatemoments code to properly use labels #228

Changes from all commits
Commits
Show all changes
1 commit
Select commit
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
83 changes: 40 additions & 43 deletions active_plugins/calculatemoments.py
100644 → 100755
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@
#################################

import numpy as np
import scipy.ndimage as scind

#################################
#
Expand All @@ -14,27 +13,27 @@
##################################

import cellprofiler_core.module as cpm
import cellprofiler_core.measurement as cpmeas
import cellprofiler_core.object as cpo
import cellprofiler_core.setting as cps
from cellprofiler_core.constants.measurement import COLTYPE_FLOAT
from cellprofiler_core.setting.do_something import DoSomething
from cellprofiler_core.setting.multichoice import MultiChoice
from cellprofiler_core.setting.subscriber import ImageSubscriber, LabelSubscriber
from cellprofiler_core.utilities.core.object import size_similarly
from centrosome.cpmorphology import fixup_scipy_ndimage_result as fix


__doc__ = """\
CalculateMoments
================

**CalculateMoments** extracts moments statistics from a given distribution of pixel values.

This module extracts a collection of quantitative measures of the shape of a distribution of pixel values.
The user can use all pixels to compute the moments or can restrict to pixels within objects.
If the image has a mask, only unmasked pixels will be used.
This module extracts a collection of quantitative measures of the shape of a distribution of
pixel values. The user can use all pixels to compute the moments or can restrict to pixels
within objects. If the image has a mask, only unmasked pixels will be used.

Available measurements:
- Mean
Available measurements:
- Mean
- Standard deviation (computed using the unbiased estimator)
- Skewness (the third moment about the mean, scaled by the standard deviation to the third power)
- Kurtosis (the fourth moment about the mean, scaled by the standard deviation to the fourth power)
Expand All @@ -50,14 +49,14 @@
"""


def get_object_moment(pixels, func):
labs = np.unique(pixels)
moms = np.zeros([np.max(labs) + 1, 1])
for l in labs:
if l != 0:
px = pixels[np.where(pixels == l)]
moms[l] = func(px)
return moms
def get_object_moment(pixels, labels, func):
labs = np.unique(labels)
moms = np.zeros(np.max(labs) + 1)
for lab in labs:
if lab != 0:
px = pixels[np.where(labels == lab)]
moms[lab] = func(px)
return moms[1:] # ignore the 0th label


def mean(pixels):
Expand All @@ -76,7 +75,6 @@ def skewness(pixels):
mean = np.mean(pixels)

num = np.sum(np.power(pixels - mean, 3))
# num=num/(len(pixels)*len(pixels[0]))
num = num / pixels.size
denom = np.std(pixels)

Expand Down Expand Up @@ -142,13 +140,17 @@ def create_settings(self):
"Moments to compute",
MOM_ALL,
MOM_ALL,
doc="""Moments are statistics describing the distribution of values in the set of pixels of interest:

- %(MOM_1)s - the first image moment, which corresponds to the central value of the collection of pixels of interest.
- %(MOM_2)s - the second image moment, which measures the amount of variation or dispersion of pixel values about its mean.
- %(MOM_3)s - a scaled version of the third moment, which measures the asymmetry of the pixel values distribution about its mean.
- %(MOM_4)s - a scaled version of the fourth moment, which measures the "peakedness" of the pixel values distribution.

doc="""Moments are statistics describing the distribution of values in the set
of pixels of interest:
- %(MOM_1)s - the first image moment, which corresponds to the central value
of the collection of pixels of interest.
- %(MOM_2)s - the second image moment, which measures the amount of variation
or dispersion of pixel values about its mean.
- %(MOM_3)s - a scaled version of the third moment, which measures the asymmetry
of the pixel values distribution about its mean.
- %(MOM_4)s - a scaled version of the fourth moment, which measures the
"peakedness" of the pixel values distribution.

Choose one or more moments to measure."""
% globals(),
)
Expand Down Expand Up @@ -205,8 +207,8 @@ def add_image_cb(self, can_remove=True):
ImageSubscriber(
"Select an image to measure",
"None",
doc="""
What did you call the grayscale images whose moments you want to calculate?""",
doc="""What did you call the grayscale images whose moments you want
to calculate?""",
),
)
if can_remove:
Expand All @@ -233,13 +235,13 @@ def add_object_cb(self, can_remove=True):
"Select objects to measure",
"None",
doc="""
What did you call the objects from which you want to calculate moments?
If you only want to calculate moments of
the image overall, you can remove all objects using the "Remove this object" button.
Objects specified here will have moments computed against *all* images specified above, which
may lead to image-object combinations that are unnecessary. If you
do not want this behavior, use multiple CalculateMoments
modules to specify the particular image-object measures that you want.""",
What did you call the objects from which you want to calculate moments?
If you only want to calculate moments of
the image overall, you can remove all objects using the "Remove this object"
button. Objects specified here will have moments computed against *all* images
specified above, which may lead to image-object combinations that are unnecessary.
If you do not want this behavior, use multiple CalculateMoments
modules to specify the particular image-object measures that you want.""",
),
)
if can_remove:
Expand Down Expand Up @@ -328,22 +330,18 @@ def run_object(self, image_name, object_name, workspace):

for name in self.moms.value.split(","):
fn = MOM_TO_F[name]
value = get_object_moment(pixels, fn)
moments = get_object_moment(pixels, labels, fn)
statistics += self.record_measurement(
workspace, image_name, object_name, name, value
workspace, image_name, object_name, name, moments
)
return statistics

def is_interactive(self):
return False

def display(self, workspace):
def display(self, workspace, figure):
statistics = workspace.display_data.statistics
figure = workspace.create_or_find_figure(
title="CalculateMoments, image cycle #%d"
% (workspace.measurements.image_set_number),
subplots=(1, 1),
)
figure.set_subplots((1, 1))
figure.subplot_table(0, 0, statistics, ratio=(0.25, 0.25, 0.25, 0.25))

def get_features(self):
Expand Down Expand Up @@ -418,8 +416,7 @@ def record_measurement(
):
"""Record the result of a measurement in the workspace's
measurements"""
# Todo: The line below previous referred to "fix", assumed this meant the numpy version
data = np.fix(result)
data = fix(result)
data[~np.isfinite(data)] = 0
workspace.add_measurement(
object_name, "%s_%s_%s" % (MOMENTS, feature_name, image_name), data
Expand Down