def test_load_v3():
with open("./tests/resources/modules/resize/v3.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 2
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.resize.Resize)
assert module.x_name == "DNA"
assert module.y_name == "ResizedDNA"
assert module.size_method == cellprofiler.modules.resize.R_TO_SIZE
assert round(abs(module.resizing_factor.value - 0.25), 7) == 0
assert module.specific_width == 141
assert module.specific_height == 169
assert module.interpolation == cellprofiler.modules.resize.I_BILINEAR
assert module.additional_image_count.value == 1
additional_image = module.additional_images[0]
assert additional_image.input_image_name == "Actin"
assert additional_image.output_image_name == "ResizedActin"
module = pipeline.modules()[1]
assert isinstance(module, cellprofiler.modules.resize.Resize)
assert module.interpolation == cellprofiler.modules.resize.I_BICUBIC
def make_tile_workspace(images):
module = cellprofiler.modules.tile.Tile()
module.set_module_num(1)
module.tile_method.value = cellprofiler.modules.tile.T_ACROSS_CYCLES
module.input_image.value = INPUT_IMAGE_NAME
module.output_image.value = OUTPUT_IMAGE_NAME
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.RunException)
pipeline.add_listener(callback)
pipeline.add_module(module)
image_set_list = cellprofiler_core.image.ImageSetList()
for i, image in enumerate(images):
image_set = image_set_list.get_image_set(i)
image_set.add(INPUT_IMAGE_NAME, cellprofiler_core.image.Image(image))
workspace = cellprofiler_core.workspace.Workspace(
pipeline,
module,
image_set_list.get_image_set(0),
cellprofiler_core.object.ObjectSet(),
cellprofiler_core.measurement.Measurements(),
image_set_list,
)
return workspace, module
def test_load_v5():
file = tests.modules.test_resources_directory(
"splitormergeobjects/v5.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.loadtxt(six.moves.StringIO(data))
module = pipeline.modules()[0]
assert module.objects_name.value == "IdentifyPrimaryObjects"
assert module.output_objects_name.value == "SplitOrMergeObjects"
assert module.relabel_option.value == "Merge"
assert module.distance_threshold.value == 0
assert not module.wants_image.value
assert module.image_name.value == "None"
assert module.minimum_intensity_fraction.value == 0.9
assert module.where_algorithm.value == "Closest point"
assert module.merge_option.value == "Distance"
assert module.parent_object.value == "None"
assert module.merging_method.value == "Disconnected"
def test_load_v5():
with open("./tests/resources/modules/displaydataonimage/v5.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(
module, cellprofiler.modules.displaydataonimage.DisplayDataOnImage
)
assert module.objects_or_image == cellprofiler.modules.displaydataonimage.OI_OBJECTS
assert module.measurement == "AreaShape_Zernike_0_0"
assert module.image_name == "DNA"
assert module.text_color == "green"
assert module.objects_name == "Nuclei"
assert module.display_image == "Zernike"
assert module.font_size == 10
assert module.decimals == 2
assert module.saved_image_contents == cellprofiler.modules.displaydataonimage.E_AXES
assert module.offset == 5
assert module.color_or_text == cellprofiler.modules.displaydataonimage.CT_COLOR
assert module.colormap == "jet"
assert not module.wants_image
assert (
module.color_map_scale_choice
== cellprofiler.modules.displaydataonimage.CMS_USE_MEASUREMENT_RANGE
)
assert module.color_map_scale.min == 0
assert module.color_map_scale.max == 1
def test_load_v1():
file = tests.modules.test_resources_directory("tile/v1.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.tile.Tile)
assert module.input_image == "ResizedColorImage"
assert module.output_image == "TiledImage"
assert module.tile_method == cellprofiler.modules.tile.T_ACROSS_CYCLES
assert module.rows == 2
assert module.columns == 12
assert module.wants_automatic_rows
assert not module.wants_automatic_columns
assert module.place_first == cellprofiler.modules.tile.P_TOP_LEFT
assert module.tile_style == cellprofiler.modules.tile.S_ROW
assert not module.meander
assert len(module.additional_images) == 3
for g, expected in zip(
module.additional_images, ("Cytoplasm", "ColorImage", "DNA")
):
assert g.input_image_name == expected
def make_workspace(image, labels):
module = cellprofiler.modules.definegrid.DefineGrid()
module.set_module_num(1)
module.grid_image.value = GRID_NAME
module.manual_image.value = INPUT_IMAGE_NAME
module.display_image_name.value = INPUT_IMAGE_NAME
module.object_name.value = OBJECTS_NAME
module.save_image_name.value = OUTPUT_IMAGE_NAME
image_set_list = cellprofiler_core.image.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add(INPUT_IMAGE_NAME, cellprofiler_core.image.Image(image))
object_set = cellprofiler_core.object.ObjectSet()
objects = cellprofiler_core.object.Objects()
objects.segmented = labels
object_set.add_objects(objects, OBJECTS_NAME)
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
assert not isinstance(event,
cellprofiler_core.pipeline.event.RunException)
pipeline.add_listener(callback)
pipeline.add_module(module)
measurements = cellprofiler_core.measurement.Measurements()
workspace = cellprofiler_core.workspace.Workspace(pipeline, module,
image_set, object_set,
measurements,
image_set_list)
return workspace, module
def test_load_v3():
file = tests.modules.get_test_resources_directory(
"measuregranularity/v3.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(
module, cellprofiler.modules.measuregranularity.MeasureGranularity)
assert len(module.images_list.value) == 2
for image_name, subsample_size, bsize, elsize, glen, objs in (
("DNA", 0.25, 0.25, 10, 16, ("Nuclei", "Cells")),
("Actin", 0.33, 0.50, 12, 20, ("Nuclei", "Cells", "Cytoplasm")),
):
assert image_name in module.images_list.value
assert module.subsample_size.value == 0.25
assert module.image_sample_size.value == 0.25
assert module.element_size.value == 10
assert module.granular_spectrum_length.value == 16
assert len(module.objects_list.value) == 3
assert all([obj in module.objects_list.value for obj in objs])
def test_load_v4():
with open("./tests/resources/modules/loaddata/v4.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.loaddata.LoadData)
assert module.csv_file_name == "1049_Metadata.csv"
assert (
module.csv_directory.dir_choice
== cellprofiler_core.preferences.DEFAULT_INPUT_FOLDER_NAME
)
assert module.wants_images
assert module.rescale
assert not module.wants_image_groupings
assert not module.wants_rows
assert module.row_range.min == 10
assert module.row_range.max == 36
assert len(module.metadata_fields.selections) == 1
assert module.metadata_fields.selections[0] == "Well"
def test_load_v6():
with open("./tests/resources/modules/loaddata/v6.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.loaddata.LoadData)
assert module.csv_file_name == "1049_Metadata.csv"
assert module.csv_directory.dir_choice == cellprofiler_core.setting.ABSOLUTE_FOLDER_NAME
assert (
module.csv_directory.custom_path
== r"x:\projects\NightlyBuild\trunk\ExampleImages\ExampleSBSImages"
)
assert module.wants_images
assert (
module.image_directory.dir_choice
== cellprofiler_core.preferences.DEFAULT_INPUT_FOLDER_NAME
)
assert module.rescale
assert module.wants_image_groupings
assert not module.wants_rows
assert module.row_range.min == 1
assert module.row_range.max == 100000
assert len(module.metadata_fields.selections) == 2
assert module.metadata_fields.selections[0] == "Column"
assert module.metadata_fields.selections[1] == "Row"
def test_load_v3():
with open("./tests/resources/modules/flagimages/v3.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.flagimage.FlagImage)
expected = (
(
"QCFlag",
cellprofiler.modules.flagimage.C_ANY,
False,
(
("Intensity_MaxIntensity_DNA", None, 0.95, "foo.txt"),
("Intensity_MinIntensity_Cytoplasm", 0.05, None, "bar.txt"),
("Intensity_MeanIntensity_DNA", 0.1, 0.9, "baz.txt"),
),
),
(
"HighCytoplasmIntensity",
None,
True,
(("Intensity_MeanIntensity_Cytoplasm", None, 0.8, "dunno.txt"), ),
),
)
assert len(expected) == module.flag_count.value
for flag, (feature_name, combine, skip,
measurements) in zip(module.flags, expected):
assert isinstance(flag, cellprofiler_core.setting.SettingsGroup)
assert flag.category == "Metadata"
assert flag.feature_name == feature_name
assert flag.wants_skip == skip
if combine is not None:
assert flag.combination_choice == combine
assert len(measurements) == flag.measurement_count.value
for (measurement, (measurement_name, min_value, max_value,
rules_file)) in zip(flag.measurement_settings,
measurements):
assert isinstance(measurement,
cellprofiler_core.setting.SettingsGroup)
assert measurement.source_choice == cellprofiler.modules.flagimage.S_IMAGE
assert measurement.measurement == measurement_name
assert measurement.wants_minimum.value == (min_value is not None)
if measurement.wants_minimum.value:
assert round(abs(measurement.minimum_value.value - min_value),
7) == 0
assert measurement.wants_maximum.value == (max_value is not None)
if measurement.wants_maximum.value:
assert round(abs(measurement.maximum_value.value - max_value),
7) == 0
assert measurement.rules_file_name == rules_file
assert measurement.rules_class == "1"
def test_load_v3():
"""
Tests a pipeline that was produced with module revision 3.
The channel names are named according to the schema:
Channel(#new_imagenumber)_(#channel_number),
e.g. Channel3_2 would be the image number 3 that contains channel
number 2.
Thus it can be easily checked via the new image name, if the channel
number is correctly parsed.
"""
with open("./tests/resources/modules/colortogray/v3.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.colortogray.ColorToGray)
assert module.image_name == "DNA"
assert module.channel_count.value == 8
for i in range(module.channel_count.value):
c = module.channels[i].image_name.value.split("_")[1]
assert module.channels[i].channel_choice.value == int(c)
assert module.channels[6].image_name.value == "Channel7_7"
def test_load_v2():
path = tests.modules.get_test_resources_directory(
"calculatestatistics/v2.pipeline")
with open(path, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(
module, cellprofiler.modules.calculatestatistics.CalculateStatistics)
assert module.grouping_values == "Metadata_Controls"
assert len(module.dose_values) == 1
dv = module.dose_values[0]
assert dv.measurement == "Metadata_SBS_Doses"
assert not dv.log_transform
assert dv.wants_save_figure
assert dv.figure_name == "DoseResponsePlot"
assert (dv.pathname.dir_choice ==
cellprofiler_core.preferences.DEFAULT_OUTPUT_FOLDER_NAME)
assert dv.pathname.custom_path == "Test"
def test_load_v2():
file = tests.modules.get_test_resources_directory(
"measureobjectneighbors/v2.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(
module,
cellprofiler.modules.measureobjectneighbors.MeasureObjectNeighbors)
assert module.object_name == "glia"
assert module.neighbors_name == "neurites"
assert (module.distance_method ==
cellprofiler.modules.measureobjectneighbors.D_EXPAND)
assert module.distance == 2
assert not module.wants_count_image
assert module.count_image_name == "countimage"
assert module.count_colormap == "pink"
assert not module.wants_percent_touching_image
assert module.touching_image_name == "touchingimage"
assert module.touching_colormap == "purple"
def test_load_v3():
with open("./tests/resources/modules/measurecolocalization/v3.pipeline", "r") as fd:
data = fd.read()
fd = six.moves.StringIO(data)
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(fd)
assert len(pipeline.modules()) == 1
module = pipeline.modules()[-1]
assert (
module.images_or_objects.value
== cellprofiler.modules.measurecolocalization.M_IMAGES_AND_OBJECTS
)
assert len(module.images_list.value) == 2
assert module.thr == 25.0
for name in module.images_list.value:
assert name in ["DNA", "Cytoplasm"]
assert len(module.objects_list.value) == 2
for name in module.objects_list.value:
assert name in ["Nuclei", "Cells"]
def test_load_v4():
data = """CellProfiler Pipeline: http://www.cellprofiler.org
Version:3
DateRevision:20141015195823
GitHash:051040e
ModuleCount:1
HasImagePlaneDetails:False
MeasureImageOverlap:[module_num:1|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False]
Compare segmented objects, or foreground/background?:Foreground/background segmentation
Select the image to be used as the ground truth basis for calculating the amount of overlap:Foo
Select the image to be used to test for overlap:Bar
Select the objects to be used as the ground truth basis for calculating the amount of overlap:Cell2_0
Select the objects to be tested for overlap against the ground truth:Cell2_1
Calculate earth mover\'s distance?:Yes
Maximum # of points:101
Point selection method:Skeleton
Maximum distance:102
Penalize missing pixels:Yes
"""
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
module = pipeline.modules()[0]
assert isinstance(
module, cellprofiler.modules.measureimageoverlap.MeasureImageOverlap)
assert module.ground_truth == "Foo"
assert module.test_img == "Bar"
def make_workspace(pixel_data, mask=None):
image = cellprofiler_core.image.Image(pixel_data, mask)
image_set_list = cellprofiler_core.image.ImageSetList()
image_set = image_set_list.get_image_set(0)
image_set.add(IMAGE_NAME, image)
module = cellprofiler.modules.identifydeadworms.IdentifyDeadWorms()
module.set_module_num(1)
module.image_name.value = IMAGE_NAME
module.object_name.value = OBJECTS_NAME
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
assert not isinstance(event, cellprofiler_core.pipeline.event.RunException)
pipeline.add_listener(callback)
pipeline.add_module(module)
workspace = cellprofiler_core.workspace.Workspace(
pipeline,
module,
image_set,
cellprofiler_core.object.ObjectSet(),
cellprofiler_core.measurement.Measurements(),
image_set_list,
)
return workspace, module
def test_load_v5():
pipeline_file = os.path.join(get_data_directory(),
"modules/metadata/v5.pipeline")
with open(pipeline_file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
em0, em1 = module.extraction_methods
assert (em0.csv_location.get_dir_choice() ==
cellprofiler_core.preferences.ABSOLUTE_FOLDER_NAME)
assert em0.csv_location.get_custom_path() == "/imaging/analysis"
assert em0.csv_filename.value == "metadata.csv"
assert (em1.csv_location.get_dir_choice() ==
cellprofiler_core.preferences.URL_FOLDER_NAME)
assert em1.csv_location.get_custom_path() == "https://cellprofiler.org"
assert em1.csv_filename.value == "metadata.csv"
def test_load_v3():
file = tests.modules.test_resources_directory("filterobjects/v3.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[-1]
assert isinstance(module, cellprofiler.modules.filterobjects.FilterObjects)
assert module.x_name == "Things"
assert module.y_name == "FilteredThings"
assert module.mode == cellprofiler.modules.filterobjects.MODE_MEASUREMENTS
assert (
module.rules_directory.dir_choice
== cellprofiler_core.preferences.DEFAULT_OUTPUT_FOLDER_NAME
)
assert module.rules_file_name == "myrules.txt"
assert module.measurements[0].measurement == "Intensity_MeanIntensity_DNA"
assert module.filter_choice == cellprofiler.modules.filterobjects.FI_MINIMAL
def make_workspace(gridding, labels=None):
module = cellprofiler.modules.identifyobjectsingrid.IdentifyObjectsInGrid()
module.set_module_num(1)
module.grid_name.value = GRID_NAME
module.output_objects_name.value = OUTPUT_OBJECTS_NAME
module.guiding_object_name.value = GUIDING_OBJECTS_NAME
image_set_list = cellprofiler_core.image.ImageSetList()
object_set = cellprofiler_core.object.ObjectSet()
if labels is not None:
my_objects = cellprofiler_core.object.Objects()
my_objects.segmented = labels
object_set.add_objects(my_objects, GUIDING_OBJECTS_NAME)
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.RunException)
pipeline.add_listener(callback)
pipeline.add_module(module)
workspace = cellprofiler_core.workspace.Workspace(
pipeline,
module,
image_set_list.get_image_set(0),
object_set,
cellprofiler_core.measurement.Measurements(),
image_set_list,
)
workspace.set_grid(GRID_NAME, gridding)
return workspace, module
def test_load_v4():
file = tests.modules.get_test_resources_directory("displaydataonimage/v4.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(
module, cellprofiler.modules.displaydataonimage.DisplayDataOnImage
)
assert module.objects_or_image == cellprofiler.modules.displaydataonimage.OI_OBJECTS
assert module.measurement == "AreaShape_Zernike_0_0"
assert module.image_name == "DNA"
assert module.text_color == "green"
assert module.objects_name == "Nuclei"
assert module.display_image == "Zernike"
assert module.font_size == 10
assert module.decimals == 2
assert module.saved_image_contents == cellprofiler.modules.displaydataonimage.E_AXES
assert module.offset == 5
assert module.color_or_text == cellprofiler.modules.displaydataonimage.CT_COLOR
assert module.colormap == "jet"
assert module.wants_image
def test_load_v4():
file = tests.modules.get_test_resources_directory("imagemath/v4.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
module = pipeline.modules()[-1]
assert isinstance(module, cellprofiler.modules.imagemath.ImageMath)
assert module.operation == cellprofiler.modules.imagemath.O_LOG_TRANSFORM
assert module.exponent == 1.5
assert module.after_factor == 0.5
assert module.addend == 0.1
assert module.truncate_low
assert not module.truncate_high
assert module.ignore_mask
assert module.output_image_name == "LogTransformed"
assert (module.images[0].image_or_measurement ==
cellprofiler.modules.imagemath.IM_IMAGE)
assert module.images[0].image_name == "DNA"
assert module.images[0].factor == 1.2
assert (module.images[1].image_or_measurement ==
cellprofiler.modules.imagemath.IM_MEASUREMENT)
assert module.images[1].measurement == "Count_Nuclei"
assert module.images[1].factor == 1.5
def test_load_v1():
file = tests.modules.get_test_resources_directory(
"maskobjects/v1.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 4
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.maskobjects.MaskObjects)
assert module.object_name.value == "Nuclei"
assert module.mask_choice.value == cellprofiler.modules.maskobjects.MC_OBJECTS
assert module.masking_objects.value == "Wells"
assert module.remaining_objects.value == "MaskedNuclei"
assert (module.retain_or_renumber.value ==
cellprofiler.modules.maskobjects.R_RENUMBER)
assert module.overlap_choice.value == cellprofiler.modules.maskobjects.P_MASK
assert not module.wants_inverted_mask
module = pipeline.modules()[1]
assert isinstance(module, cellprofiler.modules.maskobjects.MaskObjects)
assert module.object_name.value == "Cells"
assert module.mask_choice.value == cellprofiler.modules.maskobjects.MC_IMAGE
assert module.masking_image.value == "WellBoundary"
assert module.remaining_objects.value == "MaskedCells"
assert module.retain_or_renumber.value == cellprofiler.modules.maskobjects.R_RETAIN
assert module.overlap_choice.value == cellprofiler.modules.maskobjects.P_KEEP
assert not module.wants_inverted_mask
module = pipeline.modules()[2]
assert isinstance(module, cellprofiler.modules.maskobjects.MaskObjects)
assert module.object_name.value == "Cytoplasm"
assert module.mask_choice.value == cellprofiler.modules.maskobjects.MC_OBJECTS
assert module.masking_objects.value == "Cells"
assert module.remaining_objects.value == "MaskedCytoplasm"
assert (module.retain_or_renumber.value ==
cellprofiler.modules.maskobjects.R_RENUMBER)
assert module.overlap_choice.value == cellprofiler.modules.maskobjects.P_REMOVE
assert not module.wants_inverted_mask
module = pipeline.modules()[3]
assert isinstance(module, cellprofiler.modules.maskobjects.MaskObjects)
assert module.object_name.value == "Speckles"
assert module.mask_choice.value == cellprofiler.modules.maskobjects.MC_OBJECTS
assert module.masking_objects.value == "Cells"
assert module.remaining_objects.value == "MaskedSpeckles"
assert (module.retain_or_renumber.value ==
cellprofiler.modules.maskobjects.R_RENUMBER)
assert (module.overlap_choice.value ==
cellprofiler.modules.maskobjects.P_REMOVE_PERCENTAGE)
assert round(abs(module.overlap_fraction.value - 0.3), 7) == 0
assert not module.wants_inverted_mask
def test_load_v3():
with open("./tests/resources/modules/graytocolor/v3.pipeline", "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.graytocolor.GrayToColor)
assert module.scheme_choice == cellprofiler.modules.graytocolor.SCHEME_COMPOSITE
assert module.rgb_image_name == "myimage"
assert module.red_image_name == "1"
assert module.green_image_name == "2"
assert module.blue_image_name == "3"
assert module.cyan_image_name == "4"
assert module.magenta_image_name == "5"
assert module.yellow_image_name == "6"
assert module.gray_image_name == "7"
assert numpy.round(numpy.abs(module.red_adjustment_factor.value - 2.1), 7) == 0
assert numpy.round(numpy.abs(module.green_adjustment_factor.value - 2.2), 7) == 0
assert numpy.round(numpy.abs(module.blue_adjustment_factor.value - 2.3), 7) == 0
assert numpy.round(numpy.abs(module.cyan_adjustment_factor.value - 1.1), 7) == 0
assert numpy.round(numpy.abs(module.magenta_adjustment_factor.value - 1.2), 7) == 0
assert numpy.round(numpy.abs(module.yellow_adjustment_factor.value - 1.3), 7) == 0
assert numpy.round(numpy.abs(module.gray_adjustment_factor.value - 1.4), 7) == 0
assert len(module.stack_channels) == 2
assert module.stack_channels[0].image_name == "DNA"
assert module.stack_channels[1].image_name == "GFP"
assert module.stack_channels[0].color.to_rgb() == (127, 0, 255)
assert module.stack_channels[1].color.to_rgb() == (127, 255, 0)
def test_non_contiguous():
"""make sure MeasureObjectAreaShape doesn't crash if fed non-contiguous objects"""
module = cellprofiler.modules.measureobjectsizeshape.MeasureObjectAreaShape()
module.objects_list.value.append("SomeObjects")
module.calculate_zernikes.value = True
object_set = cellprofiler_core.object.ObjectSet()
labels = numpy.zeros((10, 20), int)
labels[1:9, 1:5] = 1
labels[4:6, 6:19] = 1
objects = cellprofiler_core.object.Objects()
objects.segmented = labels
object_set.add_objects(objects, "SomeObjects")
module.set_module_num(1)
image_set_list = cellprofiler_core.image.ImageSetList()
measurements = cellprofiler_core.measurement.Measurements()
pipeline = cellprofiler_core.pipeline.Pipeline()
pipeline.add_module(module)
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.RunException)
pipeline.add_listener(callback)
workspace = cellprofiler_core.workspace.Workspace(
pipeline,
module,
image_set_list.get_image_set(0),
object_set,
measurements,
image_set_list,
)
module.run(workspace)
values = measurements.get_current_measurement("SomeObjects", "AreaShape_Perimeter")
assert len(values) == 1
assert values[0] == 54
def test_load_v3():
file = tests.modules.get_test_resources_directory(
"maskobjects/v3.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.loadtxt(six.moves.StringIO(data))
module = pipeline.modules()[0]
assert module.object_name.value == "IdentifyPrimaryObjects"
assert module.remaining_objects.value == "MaskObjects"
assert module.mask_choice.value == "Objects"
assert module.masking_objects.value == "FilterObjects"
assert module.masking_image.value == "None"
assert module.overlap_choice.value == "Keep overlapping region"
assert module.overlap_fraction.value == 0.5
assert module.retain_or_renumber.value == "Renumber"
assert not module.wants_inverted_mask.value
def test_load_v1():
file = tests.modules.test_resources_directory("labelimages/v1.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 2
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.labelimages.LabelImages)
assert module.site_count == 3
assert module.row_count == 32
assert module.column_count == 48
assert module.order == cellprofiler.modules.labelimages.O_COLUMN
module = pipeline.modules()[1]
assert isinstance(module, cellprofiler.modules.labelimages.LabelImages)
assert module.site_count == 1
assert module.row_count == 8
assert module.column_count == 12
assert module.order == cellprofiler.modules.labelimages.O_ROW
def test_load_v2():
file = tests.modules.test_resources_directory("maskobjects/v2.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.maskobjects.MaskObjects)
assert module.object_name.value == "Nuclei"
assert module.mask_choice.value == cellprofiler.modules.maskobjects.MC_OBJECTS
assert module.masking_objects.value == "Wells"
assert module.remaining_objects.value == "MaskedNuclei"
assert (
module.retain_or_renumber.value == cellprofiler.modules.maskobjects.R_RENUMBER
)
assert module.overlap_choice.value == cellprofiler.modules.maskobjects.P_MASK
assert module.wants_inverted_mask
def test_load_v1():
file = tests.modules.test_resources_directory("straightenworms/v1.pipeline")
with open(file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event, cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(six.moves.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler.modules.straightenworms.StraightenWorms)
assert module.objects_name == "OverlappingWorms"
assert module.straightened_objects_name == "StraightenedWorms"
assert module.width == 20
assert (
module.training_set_directory.dir_choice
== cellprofiler_core.preferences.DEFAULT_OUTPUT_FOLDER_NAME
)
assert module.training_set_file_name == "TrainingSet.xml"
assert module.image_count.value == 2
for group, input_name, output_name in (
(module.images[0], "Brightfield", "StraightenedBrightfield"),
(module.images[1], "Fluorescence", "StraightenedFluorescence"),
):
assert group.image_name == input_name
assert group.straightened_image_name == output_name
def test_load_v4():
pipeline_file = os.path.join(get_data_directory(),
"modules/metadata/v4.pipeline")
with open(pipeline_file, "r") as fd:
data = fd.read()
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 1
module = pipeline.modules()[0]
assert isinstance(module, cellprofiler_core.modules.metadata.Metadata)
assert module.wants_metadata
assert (module.data_type_choice ==
cellprofiler_core.constants.modules.metadata.DTC_CHOOSE)
d = cellprofiler_core.setting.DataTypes.decode_data_types(
module.data_types.value_text)
for k, v in (
("Index", cellprofiler_core.setting.DataTypes.DT_NONE),
("WellRow", cellprofiler_core.setting.DataTypes.DT_TEXT),
("WellColumn", cellprofiler_core.setting.DataTypes.DT_FLOAT),
("ChannelNumber", cellprofiler_core.setting.DataTypes.DT_INTEGER),
):
assert k in d
assert d[k] == v
assert len(module.extraction_methods) == 2
em0, em1 = module.extraction_methods
assert (em0.extraction_method ==
cellprofiler_core.constants.modules.metadata.X_MANUAL_EXTRACTION)
assert em0.source == cellprofiler_core.constants.modules.metadata.XM_FILE_NAME
assert (
em0.file_regexp.value ==
r"^Channel(?P<ChannelNumber>[12])-(?P<Index>[0-9]+)-(?P<WellRow>[A-H])-(?P<WellColumn>[0-9]{2}).tif$"
)
assert em0.folder_regexp.value == r"(?P<Date>[0-9]{4}_[0-9]{2}_[0-9]{2})$"
assert (em0.filter_choice ==
cellprofiler_core.constants.modules.metadata.F_ALL_IMAGES)
assert em0.filter == 'or (file does contain "Channel2")'
assert not em0.wants_case_insensitive
assert (em1.extraction_method ==
cellprofiler_core.constants.modules.metadata.X_IMPORTED_EXTRACTION)
assert em1.source == cellprofiler_core.constants.modules.metadata.XM_FOLDER_NAME
assert (em1.filter_choice ==
cellprofiler_core.constants.modules.metadata.F_FILTERED_IMAGES)
assert (em1.csv_location.get_dir_choice() ==
cellprofiler_core.preferences.ABSOLUTE_FOLDER_NAME)
assert em1.csv_location.get_custom_path() == "/imaging/analysis"
assert em1.csv_filename.value == "metadata.csv"
assert (
em1.csv_joiner.value ==
"[{'Image Metadata': u'ChannelNumber', 'CSV Metadata': u'Wavelength'}]"
)
assert em1.wants_case_insensitive
def test_load_v3():
data = """CellProfiler Pipeline: http://www.cellprofiler.org
Version:1
SVNRevision:10865
MeasureTexture:[module_num:1|svn_version:\'1\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D]
Hidden:2
Hidden:2
Hidden:2
Select an image to measure:rawDNA
Select an image to measure:rawGFP
Select objects to measure:Cells
Select objects to measure:Nuclei
Texture scale to measure:3
Angles to measure:Horizontal,Vertical
Texture scale to measure:5
Angles to measure:Diagonal,Anti-diagonal
Measure Gabor features?:Yes
Number of angles to compute for Gabor:6
MeasureTexture:[module_num:2|svn_version:\'1\'|variable_revision_number:3|show_window:True|notes:\x5B\x5D]
Hidden:2
Hidden:2
Hidden:2
Select an image to measure:rawDNA
Select an image to measure:rawGFP
Select objects to measure:Cells
Select objects to measure:Nuclei
Texture scale to measure:3
Angles to measure:Horizontal,Vertical
Texture scale to measure:5
Angles to measure:Diagonal,Anti-diagonal
Measure Gabor features?:No
Number of angles to compute for Gabor:6
"""
pipeline = cellprofiler_core.pipeline.Pipeline()
def callback(caller, event):
assert not isinstance(event,
cellprofiler_core.pipeline.event.LoadException)
pipeline.add_listener(callback)
pipeline.load(io.StringIO(data))
assert len(pipeline.modules()) == 2
for i, wants_gabor in enumerate((True, False)):
module = pipeline.modules()[i]
assert isinstance(module,
cellprofiler.modules.measuretexture.MeasureTexture)
assert len(module.image_groups) == 2
assert module.image_groups[0].image_name.value == "rawDNA"
assert module.image_groups[1].image_name.value == "rawGFP"
assert len(module.object_groups) == 2
assert module.object_groups[0].object_name.value == "Cells"
assert module.object_groups[1].object_name.value == "Nuclei"
assert len(module.scale_groups) == 2
assert module.scale_groups[0].scale == 3
assert module.scale_groups[1].scale == 5
assert module.images_or_objects == cellprofiler.modules.measuretexture.IO_BOTH
