Source code for WORC.resources.fastr_tests.segmentix_test

#!/usr/bin/env python

# Copyright 2017-2018 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

IS_TEST = True


[docs]def create_network(): # Import the faster environment and set it up import fastr # Create a new network network = fastr.Network(id_='Segmentix_test') # Create a source node in the network source_segmentation = network.create_source('ITKImageFile', id_='segmentation_in') source_mask = network.create_source('ITKImageFile', id_='mask') source_parameters = network.create_source('ParameterFile', id_='parameters') # Create a new node in the network using toollist node_segmentix = network.create_node('Segmentix', id_="segmentix") # Create a link between the source output and an input of the addint node node_segmentix.inputs['segmentation_in'] = source_segmentation.output node_segmentix.inputs['mask'] = source_mask.output node_segmentix.inputs['parameters'] = source_parameters.output # Create a sink to save the data sink_segmentation = network.create_sink('ITKImageFile', id_='segmentation_out') # Link the addint node to the sink sink_segmentation.input = node_segmentix.outputs['segmentation_out'] return network
[docs]def source_data(network): return {'segmentation_in': 'vfs://worc_example_data/CLM/seg_liver.nii.gz', 'mask': 'vfs://worc_example_data/CLM/seg_tumor.nii.gz', 'parameters': 'vfs://worc_example_data/CLM/parameters.ini'}
[docs]def sink_data(network): return {'segmentation_out': 'vfs://tmp/results/{}/segmentix_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id)}
[docs]def main(): network = create_network() # Execute # network.draw_network() network.execute(source_data(network), sink_data(network), execution_plugin="ProcessPoolExecution")
if __name__ == '__main__': main()