def create_pipeline_conmat_to_graph_density(
main_path, pipeline_name="graph_den_pipe", con_den=1.0, multi=False,
mod=True, plot=False, optim_seq="WS trfr 100", compute_ndi=False):
"""
Description:
Pipeline from connectivity matrices to graph analysis
Threshold is density based
Inputs (inputnode):
* conmat_file
* coords_file
* labels_file
"""
# TODO plot=True is kept for sake of clarity but is now unused
pipeline = pe.Workflow(name=pipeline_name + "_den_" +
str(con_den).replace(".", "_"))
pipeline.base_dir = main_path
inputnode = pe.Node(niu.IdentityInterface(
fields=['conmat_file', 'coords_file', 'labels_file']),
name='inputnode')
if multi:
# density-based graphs
# net_list
compute_net_List = pe.MapNode(interface=ComputeNetList(
), name='compute_net_List', iterfield=["Z_cor_mat_file"])
compute_net_List.inputs.density = con_den
pipeline.connect(inputnode, 'conmat_file',
compute_net_List, 'Z_cor_mat_file')
# radatools
# prepare net_list for radatools processing
prep_rada = pe.MapNode(interface=PrepRada(),
name='prep_rada', iterfield=["net_List_file"])
prep_rada.inputs.network_type = "U"
pipeline.connect(compute_net_List, 'net_List_file',
prep_rada, 'net_List_file')
if mod:
# compute community with radatools
community_rada = pe.MapNode(interface=CommRada(
), name='community_rada', iterfield=["Pajek_net_file"])
community_rada.inputs.optim_seq = optim_seq
pipeline.connect(prep_rada, 'Pajek_net_file',
community_rada, 'Pajek_net_file')
# node roles
node_roles = pe.MapNode(
interface=ComputeNodeRoles(role_type="4roles"),
name='node_roles',
iterfield=['Pajek_net_file', 'rada_lol_file'])
pipeline.connect(prep_rada, 'Pajek_net_file',
node_roles, 'Pajek_net_file')
pipeline.connect(community_rada, 'rada_lol_file',
node_roles, 'rada_lol_file')
node_roles.inputs.compute_ndi = compute_ndi
# compute network properties with rada
net_prop = pe.MapNode(interface=NetPropRada(
optim_seq="A"), name='net_prop', iterfield=["Pajek_net_file"])
pipeline.connect(prep_rada, 'Pajek_net_file',
net_prop, 'Pajek_net_file')
else:
# density-based graphs
# net_list
compute_net_List = pe.Node(
interface=ComputeNetList(), name='compute_net_List')
compute_net_List.inputs.density = con_den
pipeline.connect(inputnode, 'conmat_file',
compute_net_List, 'Z_cor_mat_file')
# radatools
# prepare net_list for radatools processing
prep_rada = pe.Node(interface=PrepRada(), name='prep_rada')
prep_rada.inputs.network_type = "U"
pipeline.connect(compute_net_List, 'net_List_file',
prep_rada, 'net_List_file')
if mod:
# compute community with radatools
community_rada = pe.Node(
interface=CommRada(), name='community_rada')
community_rada.inputs.optim_seq = optim_seq
pipeline.connect(prep_rada, 'Pajek_net_file',
community_rada, 'Pajek_net_file')
# node roles
node_roles = pe.Node(interface=ComputeNodeRoles(
role_type="4roles"), name='node_roles')
pipeline.connect(prep_rada, 'Pajek_net_file',
node_roles, 'Pajek_net_file')
pipeline.connect(community_rada, 'rada_lol_file',
node_roles, 'rada_lol_file')
node_roles.inputs.compute_ndi = compute_ndi
# compute network properties with rada
net_prop = pe.Node(interface=NetPropRada(
optim_seq="A"), name='net_prop')
pipeline.connect(prep_rada, 'Pajek_net_file',
net_prop, 'Pajek_net_file')
return pipeline