def test_none_passed_into_get_graph(self):
fac = DefaultNetworkXFactory()
try:
fac.get_graph(None)
self.fail('Expected NDExError')
except NDExError as ne:
self.assertEqual('input network is None', str(ne))
def test_two_node_one_edge_network(self):
net = NiceCXNetwork()
net.create_node('first')
net.create_node('second')
net.create_edge(edge_source=0, edge_target=1)
net.set_name('bob')
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(2, len(g))
self.assertEqual(1, g.number_of_edges())
self.assertTrue(0 in g)
if float(networkx.__version__) >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
self.assertEqual('first', nodelist[0][1]['name'])
self.assertEqual('second', nodelist[1][1]['name'])
self.assertEqual(0, edgelist[0][0])
self.assertEqual(1, edgelist[0][1])
self.assertEqual(None, edgelist[0][2]['interaction'])
def test_glypican_network_legacymode_true(self):
net = ndex2.create_nice_cx_from_file(TestDefaultNetworkXFactory.GLYPICAN_FILE)
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.Graph))
self.assertEqual('Glypican 2 network', g.graph['name'])
self.assertEqual('', g.graph['reference'])
self.assertEqual('Mirko von Elstermann', g.graph['author'])
self.assertEqual('Jorge Filmus', g.graph['reviewers'])
self.assertEqual('glypican_2pathway', g.graph['labels'])
self.assertEqual('APR-2018', g.graph['version'])
self.assertEqual('human', g.graph['organism'])
self.assertEqual('<i>Glypican 2 network</i> was derived from '
'the latest BioPAX3 version of the Pathway '
'Interaction Database (PID) curated by NCI/Nature. '
'The BioPAX was first converted to Extended Binary '
'SIF (EBS) by the PAXTools v5 utility. It was then '
'processed to remove redundant edges, to add a '
'\'directed flow\' layout, and to add a graphic '
'style using Cytoscape Visual Properties. This '
'network can be found in searches using its original '
'PID accession id, present in the \'labels\' '
'property.', g.graph['description'])
self.assertEqual(2, len(g))
self.assertEqual(1, g.number_of_edges())
self.assertTrue(0 in g)
self.assertTrue(1 in g)
if float(networkx.__version__) >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
self.assertEqual('MDK', nodelist[0][1]['name'])
self.assertEqual('Protein', nodelist[0][1]['type'])
aliaslist = nodelist[0][1]['alias']
self.assertEqual(2, len(aliaslist))
self.assertTrue('uniprot knowledgebase:Q2LEK4' in aliaslist)
self.assertTrue('uniprot knowledgebase:Q9UCC7' in aliaslist)
self.assertEqual('GPC2', nodelist[1][1]['name'])
self.assertEqual('Protein', nodelist[1][1]['type'])
aliaslist = nodelist[1][1]['alias']
self.assertEqual(1, len(aliaslist))
self.assertTrue('uniprot knowledgebase:Q8N158' in aliaslist)
self.assertEqual(0, edgelist[0][0])
self.assertEqual(1, edgelist[0][1])
self.assertEqual('in-complex-with', edgelist[0][2]['interaction'])
self.assertEqual('false', edgelist[0][2]['directed'])
# check coordinates
self.assertTrue((g.pos[0][0] + 398.3) < 1.0)
self.assertTrue((g.pos[0][1] - 70.71) < 1.0)
self.assertTrue((g.pos[1][0] + 353.49) < 1.0)
self.assertTrue((g.pos[1][1] - 70.71) < 1.0)
def test_glypican_network_legacyfalse_and_multigraph_passed_in(self):
net = ndex2.create_nice_cx_from_file(
TestDefaultNetworkXFactory.GLYPICAN_FILE)
fac = DefaultNetworkXFactory()
g = fac.get_graph(net, networkx_graph=networkx.MultiGraph())
self.assertEqual('Glypican 2 network', g.graph['name'])
self.assertEqual('', g.graph['reference'])
self.assertEqual('Mirko von Elstermann', g.graph['author'])
self.assertEqual('Jorge Filmus', g.graph['reviewers'])
self.assertEqual('glypican_2pathway', g.graph['labels'])
self.assertEqual('APR-2018', g.graph['version'])
self.assertEqual('human', g.graph['organism'])
self.assertEqual(
'<i>Glypican 2 network</i> was derived from '
'the latest BioPAX3 version of the Pathway '
'Interaction Database (PID) curated by NCI/Nature. '
'The BioPAX was first converted to Extended Binary '
'SIF (EBS) by the PAXTools v5 utility. It was then '
'processed to remove redundant edges, to add a '
'\'directed flow\' layout, and to add a graphic '
'style using Cytoscape Visual Properties. This '
'network can be found in searches using its original '
'PID accession id, present in the \'labels\' '
'property.', g.graph['description'])
self.assertEqual(2, len(g))
self.assertEqual(1, g.number_of_edges())
self.assertTrue(0 in g)
self.assertTrue(1 in g)
if float(networkx.__version__) >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
self.assertEqual('MDK', nodelist[0][1]['name'])
self.assertEqual('Protein', nodelist[0][1]['type'])
aliaslist = nodelist[0][1]['alias']
self.assertEqual(2, len(aliaslist))
self.assertTrue('uniprot knowledgebase:Q2LEK4' in aliaslist)
self.assertTrue('uniprot knowledgebase:Q9UCC7' in aliaslist)
self.assertEqual('GPC2', nodelist[1][1]['name'])
self.assertEqual('Protein', nodelist[1][1]['type'])
aliaslist = nodelist[1][1]['alias']
self.assertEqual(1, len(aliaslist))
self.assertTrue('uniprot knowledgebase:Q8N158' in aliaslist)
self.assertEqual(0, edgelist[0][0])
self.assertEqual(1, edgelist[0][1])
self.assertEqual('in-complex-with', edgelist[0][2]['interaction'])
self.assertEqual('false', edgelist[0][2]['directed'])
# check coordinates
self.assertTrue((g.pos[0][0] + 398.3) < 1.0)
self.assertTrue((g.pos[0][1] - 70.71) < 1.0)
self.assertTrue((g.pos[1][0] + 353.49) < 1.0)
self.assertTrue((g.pos[1][1] - 70.71) < 1.0)
def test_none_passed_into_get_graph(self):
fac = DefaultNetworkXFactory()
try:
fac.get_graph(None)
self.fail('Expected NDExError')
except NDExError as ne:
self.assertEqual('input network is None', str(ne))
def test_two_node_one_edge_network(self):
net = NiceCXNetwork()
net.create_node('first')
net.create_node('second')
net.create_edge(edge_source=0, edge_target=1)
net.set_name('bob')
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(2, len(g))
self.assertEqual(1, g.number_of_edges())
self.assertTrue(0 in g)
if NETWORKX_MAJOR_VERSION >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
self.assertEqual('first', nodelist[0][1]['name'])
self.assertEqual('second', nodelist[1][1]['name'])
self.assertEqual(0, edgelist[0][0])
self.assertEqual(1, edgelist[0][1])
self.assertEqual(None, edgelist[0][2]['interaction'])
def test_darktheme_network_legacytrue(self):
net = ndex2\
.create_nice_cx_from_file(TestDefaultNetworkXFactory
.DARKTHEME_FILE)
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertEqual('Dark theme final version', g.graph['name'])
self.assertTrue('Perfetto L.,' in g.graph['reference'])
self.assertEqual('Theodora Pavlidou', g.graph['author'])
self.assertEqual('SIGNOR-EGF', g.graph['labels'])
self.assertEqual('18-Jan-2019', g.graph['version'])
self.assertEqual('Human, 9606, H**o sapiens', g.graph['organism'])
self.assertEqual('SIGNOR-EGF', g.graph['labels'])
self.assertTrue('epidermal growth factor' in g.graph['description'])
self.assertEqual(34, len(g))
self.assertEqual(50, g.number_of_edges())
self.assertTrue(1655 in g)
self.assertTrue(1622 in g)
if NETWORKX_MAJOR_VERSION >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
stat_three_index = -1
for i in range(0, len(nodelist)):
if nodelist[i][1]['name'] == 'STAT3':
stat_three_index = i
break
self.assertEqual('STAT3', nodelist[stat_three_index][1]['name'])
self.assertEqual('protein', nodelist[stat_three_index][1]['type'])
self.assertTrue('represents' not in nodelist[stat_three_index][1])
sixteenfiftyfiveedge = -1
for i in range(len(edgelist)):
if edgelist[i][0] == 1655 and edgelist[i][1] == 1654:
sixteenfiftyfiveedge = i
break
self.assertTrue((1655 == edgelist[sixteenfiftyfiveedge][0] and
1654 == edgelist[sixteenfiftyfiveedge][1]) or
(1654 == edgelist[sixteenfiftyfiveedge][0] and
1655 == edgelist[sixteenfiftyfiveedge][1]))
self.assertEqual('form complex',
edgelist[sixteenfiftyfiveedge][2]['interaction'])
self.assertEqual('true', edgelist[sixteenfiftyfiveedge][2]['directed'])
self.assertEqual('"pubmed:15284024"',
edgelist[sixteenfiftyfiveedge][2]['citation'])
# check coordinates
self.assertTrue((g.pos[1655][0] + 90.96) < 1.0)
self.assertTrue((g.pos[1655][1] - 145.72) < 1.0)
def test_one_node_network(self):
net = NiceCXNetwork()
node_one = net.create_node('first')
net.set_node_attribute(node_one,
'booleanattrib',
'false',
type='boolean')
net.set_node_attribute(node_one, 'integerattrib', '1', type='integer')
net.set_node_attribute(node_one, 'doubleattrib', '2.0', type='double')
net.set_node_attribute(node_one, 'longattrib', '3', type='long')
net.set_node_attribute(node_one,
'stringattrib',
'false',
type='string')
net.set_node_attribute(node_one,
'list_of_booleanattrib', ['True'],
type='list_of_boolean')
net.set_node_attribute(node_one,
'list_of_doubleattrib', ['4.0'],
type='list_of_double')
net.set_node_attribute(node_one,
'list_of_integerattrib', ['5'],
type='list_of_integer')
net.set_node_attribute(node_one,
'list_of_longattrib', ['6'],
type='list_of_long')
net.set_node_attribute(node_one,
'list_of_stringattrib', ['false'],
type='list_of_string')
net.set_name('bob')
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(1, len(g))
self.assertEqual(0, g.number_of_edges())
self.assertTrue(0 in g)
if NETWORKX_MAJOR_VERSION >= 2:
nodelist = list(g.nodes(data=True))
else:
nodelist = g.nodes(data=True)
self.assertEqual('false', nodelist[0][1]['booleanattrib'])
self.assertEqual('1', nodelist[0][1]['integerattrib'])
self.assertEqual('2.0', nodelist[0][1]['doubleattrib'])
self.assertEqual('3', nodelist[0][1]['longattrib'])
self.assertEqual('false', nodelist[0][1]['stringattrib'])
self.assertEqual(['True'], nodelist[0][1]['list_of_booleanattrib'])
self.assertEqual(['4.0'], nodelist[0][1]['list_of_doubleattrib'])
self.assertEqual(['5'], nodelist[0][1]['list_of_integerattrib'])
self.assertEqual(['6'], nodelist[0][1]['list_of_longattrib'])
self.assertEqual(['false'], nodelist[0][1]['list_of_stringattrib'])
def test_darktheme_network_legacytrue(self):
net = ndex2.create_nice_cx_from_file(TestDefaultNetworkXFactory.DARKTHEME_FILE)
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertEqual('Dark theme final version', g.graph['name'])
self.assertTrue('Perfetto L.,' in g.graph['reference'])
self.assertEqual('Theodora Pavlidou', g.graph['author'])
self.assertEqual('SIGNOR-EGF', g.graph['labels'])
self.assertEqual('18-Jan-2019', g.graph['version'])
self.assertEqual('Human, 9606, H**o sapiens', g.graph['organism'])
self.assertEqual('SIGNOR-EGF', g.graph['labels'])
self.assertTrue('epidermal growth factor' in g.graph['description'])
self.assertEqual(34, len(g))
self.assertEqual(50, g.number_of_edges())
self.assertTrue(1655 in g)
self.assertTrue(1622 in g)
if float(networkx.__version__) >= 2:
nodelist = list(g.nodes(data=True))
edgelist = list(g.edges(data=True))
else:
nodelist = g.nodes(data=True)
edgelist = g.edges(data=True)
stat_three_index = -1
for i in range(0, len(nodelist)):
if nodelist[i][1]['name'] == 'STAT3':
stat_three_index = i
break
self.assertEqual('STAT3', nodelist[stat_three_index][1]['name'])
self.assertEqual('protein', nodelist[stat_three_index][1]['type'])
self.assertTrue('represents' not in nodelist[stat_three_index][1])
sixteenfiftyfiveedge = -1
for i in range(len(edgelist)):
if edgelist[i][0] == 1655 and edgelist[i][1] == 1654:
sixteenfiftyfiveedge = i
break
self.assertTrue((1655 == edgelist[sixteenfiftyfiveedge][0] and
1654 == edgelist[sixteenfiftyfiveedge][1]) or
(1654 == edgelist[sixteenfiftyfiveedge][0] and
1655 == edgelist[sixteenfiftyfiveedge][1]))
self.assertEqual('form complex', edgelist[sixteenfiftyfiveedge][2]['interaction'])
self.assertEqual('true', edgelist[sixteenfiftyfiveedge][2]['directed'])
self.assertEqual('"pubmed:15284024"', edgelist[sixteenfiftyfiveedge][2]['citation'])
# check coordinates
self.assertTrue((g.pos[1655][0] + 90.96) < 1.0)
self.assertTrue((g.pos[1655][1] - 145.72) < 1.0)
def apply_layout_to_network(network):
"""
applies layout to network
:param network:
:return:
"""
fac = DefaultNetworkXFactory()
netx = fac.get_graph(network, None)
num_nodes = len(network.get_nodes())
netx.pos = nx.drawing.spring_layout(netx, scale=num_nodes,
k=1.8, iterations=50)
network.set_opaque_aspect("cartesianLayout", cartesian(netx))
def test_empty_network_passed_in_with_various_legacy_modes(self):
net = NiceCXNetwork()
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.Graph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=False)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=None)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
try:
DefaultNetworkXFactory(legacymode='blah')
self.fail('Expected NDExError')
except NDExError as ne:
self.assertEqual('blah not a valid value for '
'legacymode parameter', str(ne))
def test_one_node_no_edge_network(self):
net = NiceCXNetwork()
net.create_node('first')
net.set_name('bob')
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(1, len(g))
self.assertEqual(0, g.number_of_edges())
self.assertTrue(0 in g)
nodelist = g.nodes(data=True)
if NETWORKX_MAJOR_VERSION >= 2:
self.assertEqual('first', nodelist[0]['name'])
else:
self.assertEqual('first', nodelist[0][1]['name'])
def test_one_node_no_edge_network(self):
net = NiceCXNetwork()
net.create_node('first')
net.set_name('bob')
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(1, len(g))
self.assertEqual(0, g.number_of_edges())
self.assertTrue(0 in g)
nodelist = g.nodes(data=True)
if float(networkx.__version__) >= 2:
self.assertEqual('first', nodelist[0]['name'])
else:
self.assertEqual('first', nodelist[0][1]['name'])
def test_one_node_no_edge_network_legacytrue(self):
net = NiceCXNetwork()
net.create_node('first')
net.set_name('bob')
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertEqual('bob', g.graph['name'])
self.assertEqual(1, len(g))
self.assertEqual(0, g.number_of_edges())
self.assertTrue(0 in g)
if float(networkx.__version__) >= 2:
nodelist = list(g.nodes(data=True))
else:
nodelist = g.nodes(data=True)
self.assertEqual('first', nodelist[0][1]['name'])
def apply_layout_to_network(network, theargs, target_node_degree):
"""
applies layout to network
:param network:
:return:
"""
fac = DefaultNetworkXFactory()
netx = fac.get_graph(network, None)
num_nodes = len(network.get_nodes())
# sys.stderr.write(str(list(netx.nodes(data=True))) + '\n')
# sys.stderr.write(str(list(netx.edges(data=True))) + '\n')
posdict, fixedlist = get_pos_values(target_node_degree)
netx.pos = nx.drawing.spring_layout(netx, scale=theargs.scale,
k=theargs.k, iterations=theargs.iterations,
weight=theargs.weight,
seed=theargs.seed,
pos=posdict, fixed=fixedlist)
network.set_opaque_aspect("cartesianLayout", cartesian(netx))
class NiceCXNetworkXConvertor(object):
"""
"""
def __init__(self):
"""
Constructor
"""
self._netxfac = DefaultNetworkXFactory()
def get_networkx(self, network):
"""
:param network:
:type network: :py:class:`~ndex2.nice_cx_network.NiceCXNetwork`
:return:
"""
return self._netxfac.get_graph(network)
def __init__(self):
"""
Constructor
"""
self._netxfac = DefaultNetworkXFactory()
def run_diffusion(self,
cxnetwork,
time_param=0.1,
normalize_laplacian=False,
input_col_name=constants.DEFAULT_INPUT,
output_prefix=constants.DEFAULT_OUTPUT_PREFIX,
correct_rank=False,
via_service=False,
service_read_timeout=360):
"""
Runs diffusion annotating the 'cxnetwork' passed in with
new node attributes 'outputprefix'_heat and 'output_prefix'_rank
added to 'cxnetwork' in place.
:param cxnetwork: network to run diffusion on
:type cxnetwork: :py:class:`~ndex2.nice_cx_network.NiceCXNetwork`
:param time_param: stop time passed to :py:func:`scipy.sparse.linalg.expm_multiply`
:type time_param: int
:param normalize_laplacian: If `True`, will create a normalized
laplacian matrix for diffusion.
:type normalize_laplacian: bool
:param input_col_name: Name of node attribute that contains
diffusion heat inputs which should
be double values between `0.0` and
`1.0` where `1.0` is maximum heat
(seed) and 0.0 is minimum.
:type input_col_name: str
:param output_prefix: Prefix name for diffusion output attached
to each node. Each
node will get <PREFIX>_rank and
<PREFIX>_heat.
:type output_prefix: str
:param correct_rank: If True, multiple nodes that have same heat
will have same rank. NOTE: This only works
with local invocation of diffusion at the moment
and will raise a
:py:class:`~networkheatdiffusion.base.HeatDiffusionError`
if set to True and invoked with `via_service` set to `True`
:type correct_rank: bool
:param via_service: if `True` run diffusion via remote service
:param service_read_timeout: Seconds to wait for a response
from service. Only used when 'via_service' is
set to `True`
:type service_read_timeout: int
:raises HeatDiffusionError: If network has no nodes and/or edges or
there is an error
:return: network passed in with diffusion columns added
:rtype: :py:class:`~ndex2.nice_cx_network.NiceCXNetwork`
"""
if via_service is not None and via_service is True:
if correct_rank is True:
raise HeatDiffusionError(
'correct_rank flag only works with local invocation'
'of diffusion')
return self._run_diffusion_via_service(
cxnetwork,
time_param=time_param,
normalize_laplacian=normalize_laplacian,
input_col_name=input_col_name,
output_prefix=output_prefix,
service_read_timeout=service_read_timeout)
if cxnetwork is None:
raise HeatDiffusionError('No network found')
if len(cxnetwork.get_nodes()) == 0:
raise HeatDiffusionError('No nodes found in network')
if len(cxnetwork.get_edges()) == 0:
raise HeatDiffusionError('No edges found in network')
netx_fac = DefaultNetworkXFactory()
netx_graph = netx_fac.get_graph(cxnetwork,
networkx_graph=networkx.MultiGraph())
matrix = self._create_sparse_matrix(netx_graph, normalize_laplacian)
heat_array = self._find_heat(netx_graph, input_col_name)
diffused_heat_array = self._diffuse(matrix, heat_array, time_param)
node_heat, node_rank = self._add_heat(netx_graph,
diffused_heat_array,
correct_rank=correct_rank)
return self._add_diffusion_dict_to_network(cxnetwork, node_heat,
node_rank)
def test_empty_network_passed_in_with_various_legacy_modes(self):
net = NiceCXNetwork()
fac = DefaultNetworkXFactory()
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=True)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.Graph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=False)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
fac = DefaultNetworkXFactory(legacymode=None)
g = fac.get_graph(net)
self.assertTrue(isinstance(g, networkx.MultiGraph))
self.assertEqual(0, len(g))
self.assertEqual(0, g.number_of_edges())
try:
DefaultNetworkXFactory(legacymode='blah')
self.fail('Expected NDExError')
except NDExError as ne:
self.assertEqual('blah not a valid value for '
'legacymode parameter', str(ne))
