#!/usr/bin/env python
# Copyright 2011-2014 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.
import fastr
IS_TEST = True
FAILS = True # Indicate that this network is supposed to have failing jobs
[docs]def create_network():
network = fastr.Network('failing_network')
# create sources
source_1 = network.create_source(fastr.typelist['Int'],
id_='source_1')
source_2 = network.create_source(fastr.typelist['Int'],
id_='source_2')
source_3 = network.create_source(fastr.typelist['Int'],
id_='source_3')
# Create sinks
sink_1 = network.create_sink(fastr.typelist['Int'], id_='sink_1')
sink_2 = network.create_sink(fastr.typelist['Int'], id_='sink_2')
sink_3 = network.create_sink(fastr.typelist['Int'], id_='sink_3')
sink_4 = network.create_sink(fastr.typelist['Int'], id_='sink_4')
sink_5 = network.create_sink(fastr.typelist['Int'], id_='sink_5')
# create nodes
step_1 = network.create_node('Fail', id_='step_1')
step_2 = network.create_node('Fail', id_='step_2')
step_3 = network.create_node('Fail', id_='step_3')
range_node = network.create_node('Range', id_='range')
sum_node = network.create_node('Sum', id_='sum')
# create links
step_1.inputs['in_1'] = source_1.output
step_1.inputs['in_2'] = source_2.output
step_1.inputs['fail_2'] = [False, True, False, True]
step_2.inputs['in_1'] = source_3.output
step_2.inputs['in_2'] = source_1.output
step_2.inputs['fail_1'] = [False, False, True, True]
step_3.inputs['in_1'] = step_1.outputs['out_2']
step_3.inputs['in_2'] = step_2.outputs['out_1']
range_node.inputs['value'] = step_3.outputs['out_1']
sum_node.inputs['values'] = range_node.outputs['result']
sink_1.input = step_1.outputs['out_1']
sink_2.input = step_2.outputs['out_2']
sink_3.input = step_3.outputs['out_1']
sink_4.input = range_node.outputs['result']
sink_5.input = sum_node.outputs['result']
# Check/Draw/execute network
return network
[docs]def source_data(network):
fastr.log.info('Creating source data for {}'.format(network.id))
return {
'source_1': {'sample_1': 'vfslist://example_data/add_ints/values'},
'source_2': {'sample_1': 'vfslist://example_data/add_ints/values'},
'source_3': {'sample_1': 'vfslist://example_data/add_ints/values'},
}
[docs]def sink_data(network):
fastr.log.info('Creating sink data for {}'.format(network.id))
return {
'sink_1': 'vfs://tmp/results/{}/sink_1_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id),
'sink_2': 'vfs://tmp/results/{}/sink_2_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id),
'sink_3': 'vfs://tmp/results/{}/sink_3_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id),
'sink_4': 'vfs://tmp/results/{}/sink_4_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id),
'sink_5': 'vfs://tmp/results/{}/sink_5_{{sample_id}}_{{cardinality}}{{ext}}'.format(network.id),
}
[docs]def main():
network = create_network()
network.draw_network(name=network.id, draw_dimension=True)
network.execute(source_data(network), sink_data(network))
if __name__ == '__main__':
main()