def create_TemporalGraph():
"""create a graph"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_0, dict_1, dict_2 = {}, {}, {}
for i in range(2):
g1.add_vertex()
for i in range(5):
g2.add_vertex()
for i in range(13):
g3.add_vertex()
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0, 1)
for i in range(4):
g2.add_edge(i, i + 1)
g2.add_edge(1, 3)
for i in range(12):
g3.add_edge(i, i + 1)
g3.add_edge(0, 3)
g3.add_edge(2, 6)
g3.add_edge(3, 6)
g3.add_edge(4, 6)
g3.add_edge(8, 10)
g3.add_edge(10, 12)
# -- Creating lineage: TEMPORAL edges
L12 = {0: [0, 1, 2], 1: [3, 4]}
L23 = {0: [0, 1], 1: [2], 2: [3, 4, 5, 6], 3: [7, 8], 4: [9, 10, 11, 12]}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_TemporalGraph_GraphProperty( set_as_ids = True ):
"""create a TemporalGraph with extra 'graph_property' to test relabbeling of keys and labels as ids"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_1, dict_2, dict_3 ={}, {}, {}
for i in range(2):
g1.add_vertex()
dict_1[i]="t1_vid_"+str(i)
g1.add_graph_property('time-point_vid',dict_1)
for i in range(5):
g2.add_vertex()
dict_2[i]="t2_vid_"+str(i)
g2.add_graph_property('time-point_vid',dict_2)
for i in range(13):
g3.add_vertex()
dict_3[i]="t3_vid_"+str(i)
g3.add_graph_property('time-point_vid',dict_3)
# -- Setting keys to vid type: will be relabelled when creating the TPG
if set_as_ids:
g1.set_graph_property_key_to_vid_type('time-point_vid')
g2.set_graph_property_key_to_vid_type('time-point_vid')
g3.set_graph_property_key_to_vid_type('time-point_vid')
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0,1)
for i in range(4):
g2.add_edge(i, i+1)
g2.add_edge(1,3)
for i in range(12):
g3.add_edge(i, i+1)
g3.add_edge(0,3)
g3.add_edge(2,6)
g3.add_edge(3,6)
g3.add_edge(4,6)
g3.add_edge(8,10)
g3.add_edge(10,12)
# -- Creating lineage: TEMPORAL edges
L12={
0 : [0, 1, 2],
1 : [3, 4]
}
L23={
0 : [0, 1],
1 : [2],
2 : [3, 4, 5, 6],
3 : [7, 8],
4 : [9, 10, 11, 12]
}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_TemporalGraph_partial_lineage():
"""
Create a TemporalPropertyGraph with partial lineage.
Simulate partial lost of lineage du to daughter cells being out of the acquisition frame.
Here the is no daughters for TPG_vertex_id #6 (cell_id #4 in g2).
"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_0, dict_1, dict_2 ={}, {}, {}
for i in range(2):
g1.add_vertex()
for i in range(5):
g2.add_vertex()
for i in range(13):
g3.add_vertex()
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0,1)
for i in range(4):
g2.add_edge(i, i+1)
g2.add_edge(1,3)
for i in range(12):
g3.add_edge(i, i+1)
g3.add_edge(0,3)
g3.add_edge(2,6)
g3.add_edge(3,6)
g3.add_edge(4,6)
g3.add_edge(8,10)
g3.add_edge(10,12)
# -- Creating lineage: TEMPORAL edges
L12={
0 : [0, 1, 2],
1 : [3, 4]
}
L23={
0 : [0, 1],
1 : [2],
2 : [3, 4, 5, 6],
3 : [7, 8],
}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_TemporalGraph_GraphProperty(set_as_ids=True):
"""create a TemporalGraph with extra 'graph_property' to test relabbeling of keys and labels as ids"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_1, dict_2, dict_3 = {}, {}, {}
for i in range(2):
g1.add_vertex()
dict_1[i] = "t1_vid_" + str(i)
g1.add_graph_property('time-point_vid', dict_1)
for i in range(5):
g2.add_vertex()
dict_2[i] = "t2_vid_" + str(i)
g2.add_graph_property('time-point_vid', dict_2)
for i in range(13):
g3.add_vertex()
dict_3[i] = "t3_vid_" + str(i)
g3.add_graph_property('time-point_vid', dict_3)
# -- Setting keys to vid type: will be relabelled when creating the TPG
if set_as_ids:
g1.set_graph_property_key_to_vid_type('time-point_vid')
g2.set_graph_property_key_to_vid_type('time-point_vid')
g3.set_graph_property_key_to_vid_type('time-point_vid')
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0, 1)
for i in range(4):
g2.add_edge(i, i + 1)
g2.add_edge(1, 3)
for i in range(12):
g3.add_edge(i, i + 1)
g3.add_edge(0, 3)
g3.add_edge(2, 6)
g3.add_edge(3, 6)
g3.add_edge(4, 6)
g3.add_edge(8, 10)
g3.add_edge(10, 12)
# -- Creating lineage: TEMPORAL edges
L12 = {0: [0, 1, 2], 1: [3, 4]}
L23 = {0: [0, 1], 1: [2], 2: [3, 4, 5, 6], 3: [7, 8], 4: [9, 10, 11, 12]}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_TemporalGraph_partial_lineage():
"""
Create a TemporalPropertyGraph with partial lineage.
Simulate partial lost of lineage du to daughter cells being out of the acquisition frame.
Here the is no daughters for TPG_vertex_id #6 (cell_id #4 in g2).
"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_0, dict_1, dict_2 = {}, {}, {}
for i in range(2):
g1.add_vertex()
for i in range(5):
g2.add_vertex()
for i in range(13):
g3.add_vertex()
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0, 1)
for i in range(4):
g2.add_edge(i, i + 1)
g2.add_edge(1, 3)
for i in range(12):
g3.add_edge(i, i + 1)
g3.add_edge(0, 3)
g3.add_edge(2, 6)
g3.add_edge(3, 6)
g3.add_edge(4, 6)
g3.add_edge(8, 10)
g3.add_edge(10, 12)
# -- Creating lineage: TEMPORAL edges
L12 = {0: [0, 1, 2], 1: [3, 4]}
L23 = {
0: [0, 1],
1: [2],
2: [3, 4, 5, 6],
3: [7, 8],
}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_TemporalGraph():
"""create a graph"""
g = TemporalPropertyGraph()
g1 = PropertyGraph()
g2 = PropertyGraph()
g3 = PropertyGraph()
# -- Adding vertices to 'PropertyGraph'
dict_0, dict_1, dict_2 ={}, {}, {}
for i in range(2):
g1.add_vertex()
for i in range(5):
g2.add_vertex()
for i in range(13):
g3.add_vertex()
# -- Adding STRUCTURAL edges to 'PropertyGraph'
g1.add_edge(0,1)
for i in range(4):
g2.add_edge(i, i+1)
g2.add_edge(1,3)
for i in range(12):
g3.add_edge(i, i+1)
g3.add_edge(0,3)
g3.add_edge(2,6)
g3.add_edge(3,6)
g3.add_edge(4,6)
g3.add_edge(8,10)
g3.add_edge(10,12)
# -- Creating lineage: TEMPORAL edges
L12={
0 : [0, 1, 2],
1 : [3, 4]
}
L23={
0 : [0, 1],
1 : [2],
2 : [3, 4, 5, 6],
3 : [7, 8],
4 : [9, 10, 11, 12]
}
# -- Extending TemporalPropertyGraph with structural graph ('PropertyGraph') and linking them with lineage information.
g.extend([g1, g2, g3], [L12, L23])
return g
def create_random_TPG():
import random
g = TemporalPropertyGraph()
# -- First, we create 'PropertyGraph':
p1, p2 = PropertyGraph(), PropertyGraph()
vids = range(1,10)
edges = []
for i in vids:
l = range((i+1),10)
random.shuffle(l)
for j in l[:3]:
edges.append((i,j))
mapping = dict((vid,[vid]) for vid in vids)
for v in vids:
p1.add_vertex(v)
p2.add_vertex(v)
for s,t in edges:
p1.add_edge(s,t)
p2.add_edge(s,t)
# -- Then we can create the 'TemporalPropertyGraph':
g.extend([p1,p2],[mapping])
return g
def create_random_TPG():
import random
g = TemporalPropertyGraph()
# -- First, we create 'PropertyGraph':
p1, p2 = PropertyGraph(), PropertyGraph()
vids = range(1, 10)
edges = []
for i in vids:
l = range((i + 1), 10)
random.shuffle(l)
for j in l[:3]:
edges.append((i, j))
mapping = dict((vid, [vid]) for vid in vids)
for v in vids:
p1.add_vertex(v)
p2.add_vertex(v)
for s, t in edges:
p1.add_edge(s, t)
p2.add_edge(s, t)
# -- Then we can create the 'TemporalPropertyGraph':
g.extend([p1, p2], [mapping])
return g
def test_import_TPG_from_networkx():
""" Create a random graph and import it to networkx """
g = create_random_TPG()
nxg = g.to_networkx()
gg = TemporalPropertyGraph().from_networkx(nxg)
