def test_decimate_k_means():
r = numpy.random.RandomState()
r.seed(64)
img = r.uniform(size=(10, 10)) > 0.5
workspace, module = make_workspace(dict(image=img), dict(image=img.transpose()))
#
# Pick a single point for decimation - the emd should be zero
#
module.max_points._Number__minval = 1
module.max_points.value = 1
module.run(workspace)
assert (
workspace.measurements[
cellprofiler_core.measurement.IMAGE,
module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE
),
]
== 0
)
#
# Pick a large number of points to get the real EMD
#
workspace, module = make_workspace(dict(image=img), dict(image=img.transpose()))
module.max_points._Number__minval = 1
module.max_points.value = 100
module.run(workspace)
emd = workspace.measurements[
cellprofiler_core.measurement.IMAGE,
module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE
),
]
#
# The EMD after decimation is going to be randomly different,
# but not by much.
#
workspace, module = make_workspace(dict(image=img), dict(image=img.transpose()))
module.max_points._Number__minval = 1
module.max_points.value = numpy.sum(img | img.transpose()) / 2
module.run(workspace)
decimated_emd = workspace.measurements[
cellprofiler_core.measurement.IMAGE,
module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE
),
]
assert decimated_emd < emd * 2
assert decimated_emd > emd / 2
def test_zeros():
"""Test ground-truth of zeros and image of zeros"""
workspace, module = make_workspace(dict(image=numpy.ones((20, 10), bool)),
dict(image=numpy.ones((20, 10), bool)))
assert isinstance(
module, cellprofiler.modules.measureimageoverlap.MeasureImageOverlap)
module.run(workspace)
measurements = workspace.measurements
assert isinstance(measurements, cellprofiler_core.measurement.Measurements)
assert measurements.get_current_image_measurement(
"Overlap_FalseNegRate_test") == 0
features = measurements.get_feature_names("Image")
for feature in cellprofiler.modules.measureimageoverlap.FTR_ALL + [
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE
]:
field = "_".join((
cellprofiler.modules.measureimageoverlap.C_IMAGE_OVERLAP,
feature,
TEST_IMAGE_NAME,
))
assert field in features, "Missing feature: %s" % feature
ftr_emd = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE)
assert measurements["Image", ftr_emd] == 0
def test_no_emd():
workspace, module = make_workspace(dict(image=numpy.ones((20, 10), bool)),
dict(image=numpy.ones((20, 10), bool)))
module.wants_emd.value = False
module.run(workspace)
assert not workspace.measurements.has_feature(
"Image",
module.measurement_name(cellprofiler.modules.measureimageoverlap.
FTR_EARTH_MOVERS_DISTANCE),
)
def test_max_distance():
src = numpy.zeros((20, 10), bool)
dest = numpy.zeros((20, 10), bool)
src[5, 3] = True
dest[8, 7] = True
src[19, 9] = True
dest[11, 9] = True
workspace, module = make_workspace(dict(image=src), dict(image=dest))
module.max_distance.value = 6
module.run(workspace)
assert (workspace.measurements[
"Image",
module.measurement_name(cellprofiler.modules.measureimageoverlap.
FTR_EARTH_MOVERS_DISTANCE), ] == 11)
def test_one_pixel():
#
# The earth movers distance should be sqrt((8-5)**2 + (7 - 3) ** 2) = 5
#
src = numpy.zeros((20, 10), bool)
dest = numpy.zeros((20, 10), bool)
src[5, 3] = True
dest[8, 7] = True
workspace, module = make_workspace(dict(image=src), dict(image=dest))
module.run(workspace)
assert (workspace.measurements[
"Image",
module.measurement_name(cellprofiler.modules.measureimageoverlap.
FTR_EARTH_MOVERS_DISTANCE), ] == 5)
def test_decimate_skel():
#
# Mostly, this is to check that the skeleton method doesn't crash
#
i, j = numpy.mgrid[0:10, 0:20]
image1 = ((i - 4)**2) * 4 + (j - 8)**2 < 32
image2 = ((i - 6)**2) * 4 + (j - 12)**2 < 32
workspace, module = make_workspace(dict(image=image1), dict(image=image2))
module.max_points._Number__minval = 1
module.max_points.value = 5
module.decimation_method.value = cellprofiler.modules.measureimageoverlap.DM_SKEL
module.run(workspace)
emd = workspace.measurements[
"Image",
module.measurement_name(cellprofiler.modules.measureimageoverlap.
FTR_EARTH_MOVERS_DISTANCE), ]
assert emd > numpy.sum(image1) * 3
assert emd < numpy.sum(image1) * 6
def test_missing_penalty():
#
# Test that the missing penalty works
#
src = numpy.zeros((20, 10), bool)
dest = numpy.zeros((20, 10), bool)
src[2, 2] = True
dest[2, 2] = True
dest[8, 7] = True
dest[2, 6] = True
workspace, module = make_workspace(dict(image=src), dict(image=dest))
module.penalize_missing.value = True
module.max_distance.value = 8
module.run(workspace)
assert (workspace.measurements[
"Image",
module.measurement_name(cellprofiler.modules.measureimageoverlap.
FTR_EARTH_MOVERS_DISTANCE), ] == 16)
def test_test_measure_overlap_no_objects():
# Regression test of issue #934 - no objects
workspace, module = make_obj_workspace(
numpy.zeros((0, 3), int),
numpy.zeros((0, 3), int),
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)),
)
module.run(workspace)
m = workspace.measurements
for feature in cellprofiler.modules.measureobjectoverlap.FTR_ALL:
mname = module.measurement_name(feature)
value = m["Image", mname, 1]
if feature == cellprofiler.modules.measureobjectoverlap.FTR_TRUE_NEG_RATE:
assert value == 1
elif feature == cellprofiler.modules.measureobjectoverlap.FTR_FALSE_POS_RATE:
assert value == 0
else:
assert numpy.isnan(value), "%s was %f. not nan" % (mname, value)
#
# Make sure they don't crash
#
workspace, module = make_obj_workspace(
numpy.zeros((0, 3), int),
numpy.ones((1, 3), int),
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)),
)
module.run(workspace)
workspace, module = make_obj_workspace(
numpy.ones((1, 3), int),
numpy.zeros((0, 3), int),
dict(image=numpy.zeros((20, 10), bool)),
dict(image=numpy.zeros((20, 10), bool)),
)
module.run(workspace)
def test_3D_no_overlap():
ground_truth_image_data = numpy.zeros((10, 100, 100), dtype=numpy.bool_)
ground_truth_image_data[4:6, 30:40, 30:40] = True
ground_truth_image_data[7:10, 50:60, 50:60] = True
test_image_data = numpy.zeros((10, 100, 100), dtype=numpy.bool_)
test_image_data[7:9, 30:40, 30:40] = True
test_image_data[7:10, 70:80, 70:80] = True
workspace, module = make_workspace(
ground_truth={"image": ground_truth_image_data},
test={"image": test_image_data},
dimensions=3,
)
module.run(workspace)
measurements = workspace.measurements
ftr_true_pos_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_TRUE_POS_RATE)
ftr_true_pos_rate_measurement = measurements.get_current_image_measurement(
ftr_true_pos_rate)
assert round(abs(ftr_true_pos_rate_measurement - 0), 7) == 0
ftr_false_pos_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_FALSE_POS_RATE)
ftr_false_pos_rate_measurement = measurements.get_current_image_measurement(
ftr_false_pos_rate)
assert round(abs(ftr_false_pos_rate_measurement - 0.005025125628141),
7) == 0
ftr_true_neg_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_TRUE_NEG_RATE)
ftr_true_neg_rate_measurement = measurements.get_current_image_measurement(
ftr_true_neg_rate)
assert round(abs(ftr_true_neg_rate_measurement - 0.994974874371859),
7) == 0
ftr_false_neg_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_FALSE_NEG_RATE)
ftr_false_neg_rate_measurement = measurements.get_current_image_measurement(
ftr_false_neg_rate)
assert round(abs(ftr_false_neg_rate_measurement - 1), 7) == 0
ftr_precision = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_PRECISION)
ftr_precision_measurement = measurements.get_current_image_measurement(
ftr_precision)
assert round(abs(ftr_precision_measurement - 0), 7) == 0
ftr_recall = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_RECALL)
ftr_recall_measurement = measurements.get_current_image_measurement(
ftr_recall)
assert round(abs(ftr_recall_measurement - 0), 7) == 0
ftr_F_factor = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_F_FACTOR)
ftr_F_factor_measurement = measurements.get_current_image_measurement(
ftr_F_factor)
assert round(abs(ftr_F_factor_measurement - 0), 7) == 0
ftr_Earth_Movers_Distance = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE)
ftr_Earth_Movers_Distance_measurement = measurements.get_current_image_measurement(
ftr_Earth_Movers_Distance)
assert round(abs(ftr_Earth_Movers_Distance_measurement - 52785), 7) == 0
ftr_rand_index = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX)
ftr_rand_index_measurement = measurements.get_current_image_measurement(
ftr_rand_index)
assert round(abs(ftr_rand_index_measurement - 0.980199801998020), 2) == 0
ftr_adj_rand_index = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_ADJUSTED_RAND_INDEX)
ftr_adj_rand_index_measurement = measurements.get_current_image_measurement(
ftr_adj_rand_index)
numpy.testing.assert_almost_equal(ftr_adj_rand_index_measurement, 0, 2)
def test_3D_perfect_overlap():
image_data = numpy.random.rand(10, 100, 100) >= 0.5
workspace, module = make_workspace(ground_truth={"image": image_data},
test={"image": image_data},
dimensions=3)
module.run(workspace)
measurements = workspace.measurements
ftr_precision = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_PRECISION)
ftr_precision_measurement = measurements.get_current_image_measurement(
ftr_precision)
assert ftr_precision_measurement == 1.0
ftr_true_pos_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_TRUE_POS_RATE)
ftr_true_pos_rate_measurement = measurements.get_current_image_measurement(
ftr_true_pos_rate)
assert ftr_true_pos_rate_measurement == 1.0
ftr_false_pos_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_FALSE_POS_RATE)
ftr_false_pos_rate_measurement = measurements.get_current_image_measurement(
ftr_false_pos_rate)
assert ftr_false_pos_rate_measurement == 0
ftr_true_neg_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_TRUE_NEG_RATE)
ftr_true_neg_rate_measurement = measurements.get_current_image_measurement(
ftr_true_neg_rate)
assert ftr_true_neg_rate_measurement == 1.0
ftr_false_neg_rate = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_FALSE_NEG_RATE)
ftr_false_neg_rate_measurement = measurements.get_current_image_measurement(
ftr_false_neg_rate)
assert ftr_false_neg_rate_measurement == 0
ftr_precision = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_PRECISION)
ftr_precision_measurement = measurements.get_current_image_measurement(
ftr_precision)
assert round(abs(ftr_precision_measurement - 1), 7) == 0
ftr_F_factor = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_F_FACTOR)
ftr_F_factor_measurement = measurements.get_current_image_measurement(
ftr_F_factor)
assert round(abs(ftr_F_factor_measurement - 1), 7) == 0
ftr_Earth_Movers_Distance = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_EARTH_MOVERS_DISTANCE)
ftr_Earth_Movers_Distance_measurement = measurements.get_current_image_measurement(
ftr_Earth_Movers_Distance)
assert round(abs(ftr_Earth_Movers_Distance_measurement - 0), 7) == 0
ftr_rand_index = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_RAND_INDEX)
ftr_rand_index_measurement = measurements.get_current_image_measurement(
ftr_rand_index)
assert round(abs(ftr_rand_index_measurement - 1), 7) == 0
ftr_adj_rand_index = module.measurement_name(
cellprofiler.modules.measureimageoverlap.FTR_ADJUSTED_RAND_INDEX)
ftr_adj_rand_index_measurement = measurements.get_current_image_measurement(
ftr_adj_rand_index)
assert round(abs(ftr_adj_rand_index_measurement - 1), 7) == 0
