def test_volume(image, measurements, module, workspace):
image.set_image(skimage.morphology.ball(3), convert=False)
image.dimensions = 3
module.run(workspace)
expected = {
"Intensity_TotalIntensity_image": 123.0,
"Intensity_MeanIntensity_image": 0.358600583090379,
"Intensity_MedianIntensity_image": 0.0,
"Intensity_StdIntensity_image": 0.47958962134059907,
"Intensity_MADIntensity_image": 0.0,
"Intensity_MaxIntensity_image": 1.0,
"Intensity_MinIntensity_image": 0.0,
"Intensity_TotalArea_image": 343.0,
"Intensity_PercentMaximal_image": 35.8600583090379,
"Intensity_UpperQuartileIntensity_image": 1.0,
"Intensity_LowerQuartileIntensity_image": 0.0
}
for feature, value in expected.iteritems():
actual = measurements.get_current_measurement(
cellprofiler.measurement.IMAGE, feature)
assert actual == value, "{} expected {}, got {}".format(
feature, value, actual)
def test_volume_and_objects(image, measurements, module, objects, workspace):
object_data = skimage.morphology.ball(3, dtype=numpy.uint8)
image.set_image(numpy.ones_like(object_data, dtype=numpy.uint8),
convert=False)
image.dimensions = 3
objects.segmented = object_data
module.images[0].wants_objects.value = True
module.run(workspace)
expected = {
"Intensity_TotalIntensity_image_objects": 123.0,
"Intensity_MeanIntensity_image_objects": 1.0,
"Intensity_MedianIntensity_image_objects": 1.0,
"Intensity_StdIntensity_image_objects": 0.0,
"Intensity_MADIntensity_image_objects": 0.0,
"Intensity_MaxIntensity_image_objects": 1.0,
"Intensity_MinIntensity_image_objects": 1.0,
"Intensity_TotalArea_image_objects": 123.0,
"Intensity_PercentMaximal_image_objects": 100.0,
"Intensity_UpperQuartileIntensity_image_objects": 1.0,
"Intensity_LowerQuartileIntensity_image_objects": 1.0
}
for feature, value in expected.iteritems():
actual = measurements.get_current_measurement(
cellprofiler.measurement.IMAGE, feature)
assert actual == value, "{} expected {}, got {}".format(
feature, value, actual)
def test_volume_and_mask(image, measurements, module, workspace):
mask = skimage.morphology.ball(3, dtype=numpy.bool)
image.set_image(numpy.ones_like(mask, dtype=numpy.uint8), convert=False)
image.mask = mask
image.dimensions = 3
module.run(workspace)
expected = {
"Intensity_TotalIntensity_image": 123.0,
"Intensity_MeanIntensity_image": 1.0,
"Intensity_MedianIntensity_image": 1.0,
"Intensity_StdIntensity_image": 0.0,
"Intensity_MADIntensity_image": 0.0,
"Intensity_MaxIntensity_image": 1.0,
"Intensity_MinIntensity_image": 1.0,
"Intensity_TotalArea_image": 123.0,
"Intensity_PercentMaximal_image": 100.0,
"Intensity_UpperQuartileIntensity_image": 1.0,
"Intensity_LowerQuartileIntensity_image": 1.0,
}
for feature, value in expected.items():
actual = measurements.get_current_measurement(
cellprofiler.measurement.IMAGE, feature)
assert actual == value, "{} expected {}, got {}".format(
feature, value, actual)
def test_volume_and_objects(image, measurements, module, objects, workspace):
object_data = skimage.morphology.ball(3, dtype=numpy.uint8)
image.set_image(numpy.ones_like(object_data, dtype=numpy.uint8), convert=False)
image.dimensions = 3
objects.segmented = object_data
module.images[0].wants_objects.value = True
module.run(workspace)
expected = {
"Intensity_TotalIntensity_image_objects": 123.0,
"Intensity_MeanIntensity_image_objects": 1.0,
"Intensity_MedianIntensity_image_objects": 1.0,
"Intensity_StdIntensity_image_objects": 0.0,
"Intensity_MADIntensity_image_objects": 0.0,
"Intensity_MaxIntensity_image_objects": 1.0,
"Intensity_MinIntensity_image_objects": 1.0,
"Intensity_TotalArea_image_objects": 123.0,
"Intensity_PercentMaximal_image_objects": 100.0,
"Intensity_UpperQuartileIntensity_image_objects": 1.0,
"Intensity_LowerQuartileIntensity_image_objects": 1.0
}
for feature, value in expected.iteritems():
actual = measurements.get_current_measurement(
cellprofiler.measurement.IMAGE,
feature
)
assert actual == value, "{} expected {}, got {}".format(feature, value, actual)
def test_volume(image, measurements, module, workspace):
image.set_image(skimage.morphology.ball(3), convert=False)
image.dimensions = 3
module.run(workspace)
expected = {
"Intensity_TotalIntensity_image": 123.0,
"Intensity_MeanIntensity_image": 0.358600583090379,
"Intensity_MedianIntensity_image": 0.0,
"Intensity_StdIntensity_image": 0.47958962134059907,
"Intensity_MADIntensity_image": 0.0,
"Intensity_MaxIntensity_image": 1.0,
"Intensity_MinIntensity_image": 0.0,
"Intensity_TotalArea_image": 343.0,
"Intensity_PercentMaximal_image": 35.8600583090379,
"Intensity_UpperQuartileIntensity_image": 1.0,
"Intensity_LowerQuartileIntensity_image": 0.0
}
for feature, value in expected.iteritems():
actual = measurements.get_current_measurement(
cellprofiler.measurement.IMAGE,
feature
)
assert actual == value, "{} expected {}, got {}".format(feature, value, actual)
def volume(image):
data = numpy.zeros((11, 11, 20))
k, i, j = numpy.mgrid[-5:6, -5:6, -5:15]
data[k**2 + i**2 + j**2 <= 25] = 0.5
data[k**2 + i**2 + j**2 <= 16] = 0.25
data[k**2 + i**2 + j**2 == 0] = 1
k, i, j = numpy.mgrid[-5:6, -5:6, -15:5]
data[k**2 + i**2 + j**2 <= 9] = 0.5
data[k**2 + i**2 + j**2 <= 4] = 0.75
data[k**2 + i**2 + j**2 == 0] = 1
image.set_image(data, convert=False)
image.dimensions = 3
return image
