def test(self):
# Define the files we'll be making
testProjectName = 'test_project.ilp'
# Clean up: Remove the test data files we created last time (just in case)
for f in [testProjectName]:
try:
os.remove(f)
except:
pass
# Create an empty project
with h5py.File(testProjectName) as testProject:
testProject.create_dataset("ilastikVersion", data=0.6)
# Create an operator to work with and give it some input
graph = Graph()
operatorToSave = OpFeatureSelection(graph=graph)
# Configure scales
scales = [0.1, 0.2, 0.3, 0.4, 0.5]
operatorToSave.Scales.setValue(scales)
# Configure feature types
featureIds = ['GaussianSmoothing', 'LaplacianOfGaussian']
operatorToSave.FeatureIds.setValue(featureIds)
# All False (no features selected)
selectionMatrix = numpy.zeros((2, 5), dtype=bool)
# Change a few to True
selectionMatrix[0, 0] = True
selectionMatrix[1, 0] = True
selectionMatrix[0, 2] = True
selectionMatrix[1, 4] = True
operatorToSave.SelectionMatrix.setValue(selectionMatrix)
# Serialize!
serializer = FeatureSelectionSerializer(operatorToSave,
'FeatureSelections')
serializer.serializeToHdf5(testProject, testProjectName)
assert (
testProject['FeatureSelections/Scales'].value == scales).all()
assert (testProject['FeatureSelections/FeatureIds'].value ==
featureIds).all()
assert (testProject['FeatureSelections/SelectionMatrix'].value ==
selectionMatrix).all()
# Deserialize into a fresh operator
operatorToLoad = OpFeatureSelection(graph=graph)
deserializer = FeatureSelectionSerializer(operatorToLoad,
'FeatureSelections')
deserializer.deserializeFromHdf5(testProject, testProjectName)
assert (operatorToLoad.Scales.value == scales).all()
assert (operatorToLoad.FeatureIds.value == featureIds).all()
assert (
operatorToLoad.SelectionMatrix.value == selectionMatrix).all()
os.remove(testProjectName)
def test(self):
# Define the files we'll be making
testProjectName = 'test_project.ilp'
# Clean up: Remove the test data files we created last time (just in case)
for f in [testProjectName]:
try:
os.remove(f)
except:
pass
# Create an empty project
with h5py.File(testProjectName, 'w') as testProject:
testProject.create_dataset("ilastikVersion", data=b"1.0.0")
# Create an operator to work with and give it some input
graph = Graph()
operatorToSave = OpFeatureSelection(graph=graph)
scales = operatorToSave.Scales.value
featureIds = operatorToSave.FeatureIds.value
# All False (no features selected)
selectionMatrix = operatorToSave.MinimalFeatures
# Change a few to True
selectionMatrix[0,0] = True
selectionMatrix[1,1] = True
selectionMatrix[2,2] = True
selectionMatrix[3,3] = True
selectionMatrix[4,4] = True
selectionMatrix[5,5] = True
operatorToSave.SelectionMatrix.setValue(selectionMatrix)
# Serialize!
serializer = FeatureSelectionSerializer(operatorToSave, 'FeatureSelections')
serializer.serializeToHdf5(testProject, testProjectName)
with h5py.File(testProjectName, 'r') as testProject:
file_feature_ids = numpy.asarray(list(map(lambda s: s.decode('utf-8'), testProject['FeatureSelections/FeatureIds'].value)))
assert (testProject['FeatureSelections/Scales'].value == scales).all()
assert (file_feature_ids == featureIds).all()
assert (testProject['FeatureSelections/SelectionMatrix'].value == selectionMatrix).all()
# Deserialize into a fresh operator
operatorToLoad = OpFeatureSelection(graph=graph)
deserializer = FeatureSelectionSerializer(operatorToLoad, 'FeatureSelections')
deserializer.deserializeFromHdf5(testProject, testProjectName)
assert operatorToLoad.FeatureIds.value == getFeatureIdOrder(), \
"Feature IDs were deserialized to a strange order!"
assert isinstance(operatorToLoad.Scales.value, list)
assert isinstance(operatorToLoad.FeatureIds.value, list)
assert (operatorToLoad.Scales.value == scales)
assert (operatorToLoad.FeatureIds.value == featureIds)
assert (operatorToLoad.SelectionMatrix.value == selectionMatrix).all()
os.remove(testProjectName)
def test(self):
# Define the files we'll be making
testProjectName = 'test_project.ilp'
# Clean up: Remove the test data files we created last time (just in case)
for f in [testProjectName]:
try:
os.remove(f)
except:
pass
# Create an empty project
with h5py.File(testProjectName) as testProject:
testProject.create_dataset("ilastikVersion", data=0.6)
# Create an operator to work with and give it some input
graph = Graph()
operatorToSave = OpFeatureSelection(graph=graph, filter_implementation='Original')
# Configure scales
scales = [0.1, 0.2, 0.3, 0.4, 0.5]
operatorToSave.Scales.setValue(scales)
# Configure feature types
featureIds = [ 'GaussianSmoothing',
'LaplacianOfGaussian' ]
operatorToSave.FeatureIds.setValue(featureIds)
# All False (no features selected)
selectionMatrix = numpy.zeros((2, 5), dtype=bool)
# Change a few to True
selectionMatrix[0,0] = True
selectionMatrix[1,0] = True
selectionMatrix[0,2] = True
selectionMatrix[1,4] = True
operatorToSave.SelectionMatrix.setValue(selectionMatrix)
# Serialize!
serializer = FeatureSelectionSerializer(operatorToSave, 'FeatureSelections')
serializer.serializeToHdf5(testProject, testProjectName)
assert (testProject['FeatureSelections/Scales'].value == scales).all()
assert (testProject['FeatureSelections/FeatureIds'].value == featureIds).all()
assert (testProject['FeatureSelections/SelectionMatrix'].value == selectionMatrix).all()
# Deserialize into a fresh operator
operatorToLoad = OpFeatureSelection(graph=graph, filter_implementation='Original')
deserializer = FeatureSelectionSerializer(operatorToLoad, 'FeatureSelections')
deserializer.deserializeFromHdf5(testProject, testProjectName)
assert isinstance(operatorToLoad.Scales.value, list)
assert isinstance(operatorToLoad.FeatureIds.value, list)
assert (operatorToLoad.Scales.value == scales)
assert (operatorToLoad.FeatureIds.value == featureIds)
assert (operatorToLoad.SelectionMatrix.value == selectionMatrix).all()
os.remove(testProjectName)
def test(self):
# Define the files we'll be making
testProjectName = "test_project.ilp"
# Clean up: Remove the test data files we created last time (just in case)
for f in [testProjectName]:
try:
os.remove(f)
except:
pass
# Create an empty project
with h5py.File(testProjectName, "w") as testProject:
testProject.create_dataset("ilastikVersion", data=b"1.0.0")
# Create an operator to work with and give it some input
graph = Graph()
operatorToSave = OpFeatureSelection(graph=graph)
scales = operatorToSave.Scales.value
featureIds = operatorToSave.FeatureIds.value
# All False (no features selected)
selectionMatrix = operatorToSave.MinimalFeatures
# Change a few to True
selectionMatrix[0, 0] = True
selectionMatrix[1, 1] = True
selectionMatrix[2, 2] = True
selectionMatrix[3, 3] = True
selectionMatrix[4, 4] = True
selectionMatrix[5, 5] = True
operatorToSave.SelectionMatrix.setValue(selectionMatrix)
# Serialize!
serializer = FeatureSelectionSerializer(operatorToSave,
"FeatureSelections")
serializer.serializeToHdf5(testProject, testProjectName)
with h5py.File(testProjectName, "r") as testProject:
file_feature_ids = numpy.asarray(
list(
map(lambda s: s.decode("utf-8"),
testProject["FeatureSelections/FeatureIds"].value)))
assert (
testProject["FeatureSelections/Scales"].value == scales).all()
assert (file_feature_ids == featureIds).all()
assert (testProject["FeatureSelections/SelectionMatrix"].value ==
selectionMatrix).all()
# Deserialize into a fresh operator
operatorToLoad = OpFeatureSelection(graph=graph)
deserializer = FeatureSelectionSerializer(operatorToLoad,
"FeatureSelections")
deserializer.deserializeFromHdf5(testProject, testProjectName)
assert (operatorToLoad.FeatureIds.value == getFeatureIdOrder()
), "Feature IDs were deserialized to a strange order!"
assert isinstance(operatorToLoad.Scales.value, list)
assert isinstance(operatorToLoad.FeatureIds.value, list)
assert operatorToLoad.Scales.value == scales
assert operatorToLoad.FeatureIds.value == featureIds
assert (
operatorToLoad.SelectionMatrix.value == selectionMatrix).all()
os.remove(testProjectName)
def test(self):
# Define the files we'll be making
testProjectName = 'test_project.ilp'
# Clean up: Remove the test data files we created last time (just in case)
for f in [testProjectName]:
try:
os.remove(f)
except:
pass
# Create an empty project
with h5py.File(testProjectName, 'w') as testProject:
testProject.create_dataset("ilastikVersion", data="1.0.0")
# Create an operator to work with and give it some input
graph = Graph()
operatorToSave = OpFeatureSelection(
graph=graph, filter_implementation='Original')
scales = operatorToSave.Scales.value
featureIds = operatorToSave.FeatureIds.value
# All False (no features selected)
selectionMatrix = operatorToSave.SelectionMatrix.value.copy()
# Change a few to True
selectionMatrix[0, 0] = True
selectionMatrix[1, 1] = True
selectionMatrix[2, 2] = True
selectionMatrix[3, 3] = True
selectionMatrix[4, 4] = True
selectionMatrix[5, 5] = True
operatorToSave.SelectionMatrix.setValue(selectionMatrix)
# Serialize!
serializer = FeatureSelectionSerializer(operatorToSave,
'FeatureSelections')
serializer.serializeToHdf5(testProject, testProjectName)
with h5py.File(testProjectName, 'r') as testProject:
assert (
testProject['FeatureSelections/Scales'].value == scales).all()
assert (testProject['FeatureSelections/FeatureIds'].value ==
featureIds).all()
assert (testProject['FeatureSelections/SelectionMatrix'].value ==
selectionMatrix).all()
# Deserialize into a fresh operator
operatorToLoad = OpFeatureSelection(
graph=graph, filter_implementation='Original')
deserializer = FeatureSelectionSerializer(operatorToLoad,
'FeatureSelections')
deserializer.deserializeFromHdf5(testProject, testProjectName)
assert operatorToLoad.FeatureIds.value == getFeatureIdOrder(), \
"Feature IDs were deserialized to a strange order!"
assert isinstance(operatorToLoad.Scales.value, list)
assert isinstance(operatorToLoad.FeatureIds.value, list)
assert (operatorToLoad.Scales.value == scales)
assert (operatorToLoad.FeatureIds.value == featureIds)
assert (
operatorToLoad.SelectionMatrix.value == selectionMatrix).all()
os.remove(testProjectName)
