def assemble_cx(stmts_with_counts):
for channel, (stmts, ev_counts,
source_counts) in stmts_with_counts.items():
cxa = CxAssembler(stmts, network_name='%s INDRA interactome' % channel)
cxa.make_model()
add_semantic_hub_layout(cxa.cx, channel)
model_id = cxa.upload_model()
def upload_ndex_network(kinase, stmts):
network_set_id = '9d9d4f66-e3da-11eb-b666-0ac135e8bacf'
name = '%s INDRA network' % kinase
cxa = CxAssembler(stmts, name)
cxa.make_model()
add_semantic_hub_layout(cxa.cx, kinase)
network_id = cxa.upload_model(private=False)
# Style setting already done as part of upload
# ndex_client.set_style(network_id)
ndex_client.add_to_network_set(network_id, network_set_id)
return network_id
def test_hub_layout():
stmts = [st_phos, st_dephos, st_act]
cxa = CxAssembler(stmts)
cxa.make_model()
graph = hub_layout.cx_to_networkx(cxa.cx)
erk = hub_layout.get_node_by_name(graph, 'MAPK1')
hub_layout.add_semantic_hub_layout(cxa.cx, 'MAPK1')
assert cxa.cx['cartesianLayout']
for node in cxa.cx['cartesianLayout']:
if node['node'] == erk:
assert node['x'] == 0.0
assert node['y'] == 0.0
else:
assert node['x'] != 0
assert node['y'] != 0
node_classes = hub_layout.classify_nodes(graph, erk)
assert node_classes[hub_layout.get_node_by_name(graph, 'DUSP4')] == \
(1, 'modification', 'other')
assert node_classes[hub_layout.get_node_by_name(graph, 'MAP2K1')] in \
{(1, 'activity', 'protein'), (1, 'modification', 'protein')}
import sys
import pickle
from indra.databases import ndex_client
from indra.assemblers.cx import CxAssembler
from indra.assemblers.cx.hub_layout import add_semantic_hub_layout
if __name__ == '__main__':
kinase = sys.argv[1]
with open('dark_kinase_statements_assembled.pkl', 'rb') as fh:
stmts = pickle.load(fh)
cxa = CxAssembler(stmts[kinase])
cxa.make_model()
add_semantic_hub_layout(cxa.cx, kinase)
model_id = cxa.upload_model()
ndex_client.set_style(model_id)