tools Package

Elastix Module

class WORC.tools.Elastix.Elastix

Bases: object

__dict__ = mappingproxy({'__module__': 'WORC.tools.Elastix', '__init__': <function Elastix.__init__>, 'getparametermap': <function Elastix.getparametermap>, 'create_network': <function Elastix.create_network>, 'addchangeorder': <function Elastix.addchangeorder>, 'create_bbox': <function Elastix.create_bbox>, 'execute': <function Elastix.execute>, '__dict__': <attribute '__dict__' of 'Elastix' objects>, '__weakref__': <attribute '__weakref__' of 'Elastix' objects>, '__doc__': None, '__annotations__': {}})

__init__()

__module__ = 'WORC.tools.Elastix'

__weakref__

list of weak references to the object (if defined)

addchangeorder()

create_bbox(seg, pad=[2, 25, 25])

Create a bounding box around an input segmentation with a certain padding

create_network(nettype)

execute()

getparametermap(model='affine', size=(512, 512, 128))

Evaluate Module

class WORC.tools.Evaluate.Evaluate(label_type, modus='binary_classification', scores='percentages', ensemble_method='top_N', ensemble_size=100, parent=None, features=None, fastr_plugin='LinearExecution', name='Example')

Bases: object

Build a network that evaluates the performance of an estimator.

__dict__ = mappingproxy({'__module__': 'WORC.tools.Evaluate', '__doc__': 'Build a network that evaluates the performance of an estimator.', '__init__': <function Evaluate.__init__>, 'create_network': <function Evaluate.create_network>, 'create_links_Standalone': <function Evaluate.create_links_Standalone>, 'create_links_Addon': <function Evaluate.create_links_Addon>, 'set': <function Evaluate.set>, 'execute': <function Evaluate.execute>, '__dict__': <attribute '__dict__' of 'Evaluate' objects>, '__weakref__': <attribute '__weakref__' of 'Evaluate' objects>, '__annotations__': {}})

__init__(label_type, modus='binary_classification', scores='percentages', ensemble_method='top_N', ensemble_size=100, parent=None, features=None, fastr_plugin='LinearExecution', name='Example')

Initialize object.

Parameters

network: fastr network, default None

If you input a network, the evaluate network is added to the existing network.

__module__ = 'WORC.tools.Evaluate'

__weakref__

list of weak references to the object (if defined)

create_links_Addon()

Create links in network between nodes when adding Evaluate to WORC.

create_links_Standalone()

Create links in network between nodes when using standalone.

create_network()

Add evaluate components to network.

execute()

Execute the network through the fastr.network.execute command.

set(estimator=None, pinfo=None, images=None, segmentations=None, config=None, features=None, sink_data={})

Set the sources and sinks based on the provided attributes.

Inference Module

class WORC.tools.Inference.Inference(fastr_plugin='LinearExecution', name='Example')

Bases: object

Build a network that can use an existing model for inference.

__dict__ = mappingproxy({'__module__': 'WORC.tools.Inference', '__doc__': 'Build a network that can use an existing model for inference.', '__init__': <function Inference.__init__>, 'create_network': <function Inference.create_network>, '__dict__': <attribute '__dict__' of 'Inference' objects>, '__weakref__': <attribute '__weakref__' of 'Inference' objects>, '__annotations__': {}})

__init__(fastr_plugin='LinearExecution', name='Example')

Initialize object.

Parameters

network: fastr network, default None

If you input a network, the evaluate network is added to the existing network.

__module__ = 'WORC.tools.Inference'

__weakref__

list of weak references to the object (if defined)

create_network()

Add evaluate components to network.

Slicer Module

class WORC.tools.Slicer.Slicer(images=None, segmentations=None, network=None, fastr_plugin='ProcessPoolExecution', name='Example')

Bases: object

__dict__ = mappingproxy({'__module__': 'WORC.tools.Slicer', '__init__': <function Slicer.__init__>, 'create_network': <function Slicer.create_network>, 'set': <function Slicer.set>, 'execute': <function Slicer.execute>, '__dict__': <attribute '__dict__' of 'Slicer' objects>, '__weakref__': <attribute '__weakref__' of 'Slicer' objects>, '__doc__': None, '__annotations__': {}})

__init__(images=None, segmentations=None, network=None, fastr_plugin='ProcessPoolExecution', name='Example')

Build a network that evaluates the performance of an estimator.

Parameters

network: fastr network, default None

If you input a network, the evaluate network is added to the existing network.

__module__ = 'WORC.tools.Slicer'

__weakref__

list of weak references to the object (if defined)

create_network()

Add evaluate components to network.

execute()

Execute the network through the fastr.network.execute command.

set(images=None, segmentations=None, sink_data={})

Set the sources and sinks based on the provided attributes.

Transformix Module

class WORC.tools.Transformix.Transformix

Bases: object

__dict__ = mappingproxy({'__module__': 'WORC.tools.Transformix', '__init__': <function Transformix.__init__>, 'create_network': <function Transformix.create_network>, 'execute': <function Transformix.execute>, '__dict__': <attribute '__dict__' of 'Transformix' objects>, '__weakref__': <attribute '__weakref__' of 'Transformix' objects>, '__doc__': None, '__annotations__': {}})

__init__()

__module__ = 'WORC.tools.Transformix'

__weakref__

list of weak references to the object (if defined)

create_network()

execute()

createfixedsplits Module

WORC.tools.createfixedsplits.createfixedsplits(label_file=None, label_type=None, patient_IDs=None, stratify=True, test_size=0.2, N_iterations=1, modus='singlelabel', output=None)

Create fixed splits for a random-split cross-validation.

label_filefilepath

CSV file containing the labels of the patients.

label_type: list of strings

labels to extracted from the label file, e.g. [‘label1’]

patient_IDs: list of strings

names of patients to take into account. If None, take all

stratify: Boolean

If True, splits are stratified. In this case, you need to provide label data.

test_size: float

Percentage of patients in test set per iteration.

N_iterations: integer

Number of cross-validation iterations

modus: str

singlelabel or regression. Multilabel not implemented yet.

output: filepath

csv filename to save output to.

df: pandas Dataframe

Fixed splits created.

WORC.tools.createfixedsplits.test()

fingerprinting Module

class WORC.tools.fingerprinting.Fingerprinter

Bases: object

Fingerprinting object for WORC configuration.

__dict__ = mappingproxy({'__module__': 'WORC.tools.fingerprinting', '__doc__': 'Fingerprinting object for WORC configuration.', '__init__': <function Fingerprinter.__init__>, 'execute': <function Fingerprinter.execute>, '__dict__': <attribute '__dict__' of 'Fingerprinter' objects>, '__weakref__': <attribute '__weakref__' of 'Fingerprinter' objects>, '__annotations__': {}})

__init__()

Initialize object.

__module__ = 'WORC.tools.fingerprinting'

__weakref__

list of weak references to the object (if defined)

execute()

Determine fingerprint of dataset.

Parameters

worcobject: WORC object

WORC object to fingerprint