def test_compute_ricci_curvature():
Gd = nx.DiGraph()
Gd.add_edges_from([(1, 2), (2, 3), (3, 4), (2, 4), (4, 2)])
orc_directed = FormanRicci(Gd)
orc_directed.compute_ricci_curvature()
frc = nx.get_edge_attributes(orc_directed.G, "formanCurvature")
assert frc == {(1, 2): -2, (2, 3): 0, (2, 4): 0, (3, 4): 1, (4, 2): 0}
def test_compute_ricci_curvature():
G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (3, 4), (2, 4)])
G.add_node(5)
frc = FormanRicci(G, method="1d")
frc.compute_ricci_curvature()
frc_edges = list(nx.get_edge_attributes(frc.G, "formanCurvature").values())
frc_nodes = list(nx.get_node_attributes(frc.G, "formanCurvature").values())
frc_edges_ans = [0.0, -1.0, -1.0, 0.0]
frc_nodes_ans = [0.0, -0.6666666666666666, -0.5, -0.5, 0]
npt.assert_array_almost_equal(frc_edges, frc_edges_ans)
npt.assert_array_almost_equal(frc_nodes, frc_nodes_ans)
frc_a = FormanRicci(G, method="augmented")
frc_a.compute_ricci_curvature()
frc_a_edges = list(
nx.get_edge_attributes(frc_a.G, "formanCurvature").values())
frc_a_nodes = list(
nx.get_node_attributes(frc_a.G, "formanCurvature").values())
frc_a_edges_ans = [0.0, 2.0, 2.0, 3.0]
frc_a_nodes_ans = [0.0, 1.3333333333333333, 2.5, 2.5, 0]
npt.assert_array_almost_equal(frc_a_edges, frc_a_edges_ans)
npt.assert_array_almost_equal(frc_a_nodes, frc_a_nodes_ans)
def main():
# import an example NetworkX karate club graph
G = nx.karate_club_graph()
# compute the Ollivier-Ricci curvature of the given graph G
orc = OllivierRicci(G, alpha=0.5, verbose="INFO")
orc.compute_ricci_curvature()
print(
"Karate Club Graph: The Ollivier-Ricci curvature of edge (0,1) is %f" %
orc.G[0][1]["ricciCurvature"])
# compute the Forman-Ricci curvature of the given graph G
frc = FormanRicci(G)
frc.compute_ricci_curvature()
print("Karate Club Graph: The Forman-Ricci curvature of edge (0,1) is %f" %
frc.G[0][1]["formanCurvature"])
# -----------------------------------
# Compute Ricci flow metric - Optimal Transportation Distance
G = nx.karate_club_graph()
orc_OTD = OllivierRicci(G, alpha=0.5, method="OTD", verbose="INFO")
orc_OTD.compute_ricci_flow(iterations=10)
np.save(path1+"lig_IDM_graphs/"+pdbid+"_ollivier_15_C_ligand.npy", orc_temp)
np.save(path1+"lig_IDM_graphs/"+pdbid+"_forman_15_C_ligand.npy", frc_temp)
"""
for i in range(len(all_comb)):
print("Processing: {:20}".format(comb_d[i]))
for pdbid in train_list_2013["arr_0"]:
print("Processing v2013: {:4}".format(pdbid))
orc_temp = []
frc_temp = []
for c in np.linspace(0, 15, 150):
G = gen_lignet(all_comb[i], pdbid, c, path2)
if G.number_of_edges() > 0:
orc = OllivierRicci(G, alpha=0.5)
orc.compute_ricci_curvature()
frc = FormanRicci(G)
frc.compute_ricci_curvature()
orc_temp.append(orc.G)
frc_temp.append(frc.G)
else:
orc_temp.append(G)
frc_temp.append(G)
nx.write_gpickle([orc_temp, frc_temp], path2 + "lig_IDM_graphs/" +
pdbid + "_15_" + comb_d[i] + "_ligand.gpickle")
for pdbid in test_list_2013["arr_0"]:
print("Processing v2013: ", pdbid)
orc_temp = []
frc_temp = []
for c in np.linspace(0, 15, 150):
import networkx as nx
from GraphRicciCurvature.OllivierRicci import OllivierRicci
from GraphRicciCurvature.FormanRicci import FormanRicci
# import an example NetworkX karate club graph
G = nx.karate_club_graph()
# compute the Ollivier-Ricci curvature of the given graph G
orc = OllivierRicci(G, alpha=0.5, verbose="INFO")
orc.compute_ricci_curvature()
print("Karate Club Graph: The Ollivier-Ricci curvature of edge (0,1) is %f" % orc.G[0][1]["ricciCurvature"])
# compute the Forman-Ricci curvature of the given graph G
frc = FormanRicci(G)
frc.compute_ricci_curvature()
print("Karate Club Graph: The Forman-Ricci curvature of edge (0,1) is %f" % frc.G[0][1]["formanCurvature"])
# -----------------------------------
# Construct a directed graph example
Gd = nx.DiGraph()
Gd.add_edges_from([(1, 2), (2, 3), (3, 4), (2, 4), (4, 2)])
# compute the Ollivier-Ricci curvature of the given directed graph Gd
orc_directed = OllivierRicci(Gd)
orc_directed.compute_ricci_curvature()
for n1, n2 in Gd.edges():
print("Directed Graph: The Ollivier-Ricci curvature of edge(%d,%d) id %f" %
(n1, n2, orc_directed.G[n1][n2]["ricciCurvature"]))
# compute the Forman-Ricci curvature of the given directed graph Gd
frc_directed = FormanRicci(Gd)
def create_test(threshold, cutoff, num_of_gaps):
test_list = np.load("ORC PLB IDM 2016/test_list.npz", allow_pickle=True)
for i in range(len(test_list["arr_0"])):
pdbid = test_list["arr_0"][i]
print("Processing: ", pdbid)
data = np.load("ORC PLB IDM 2016/Complexes/" + pdbid + "_complex_" +
str(cutoff) + ".npz",
allow_pickle=True)
pro_data, lig_data = data['PRO'], data['LIG']
pro_hvy_atom = ['C', 'N', 'O', 'S']
lig_hvy_atom = ['C', 'N', 'O', 'S', 'P', 'F', 'Cl', 'Br', 'I']
pro_coords, lig_coords = [], []
for p in pro_hvy_atom:
temp = []
for proatm in pro_data:
for j in range(len(proatm['typ'])):
pt = str(proatm['typ'][j]).replace(" ", "")
pt = pt.upper()
if pt == p:
temp.append(proatm['pos'][j])
pro_coords.append(temp)
for q in lig_hvy_atom:
temp = []
for ligatm in lig_data:
for j in range(len(ligatm['typ'])):
lt = str(ligatm['typ'][j]).replace(" ", "")
lt = lt.upper()
if lt == q:
temp.append(ligatm['pos'][j])
lig_coords.append(temp)
X_graphs = []
for i in range(0, len(pro_coords)):
for j in range(0, len(lig_coords)):
temp_feature = []
# generate graph with protein and ligand atom combination and specified cutoff distance
for l in np.linspace(0, threshold, num_of_gaps):
#l = 7.4
#print(pro_hvy_atom[i],"--",lig_hvy_atom[j], ": ", l, end="\r")
G = nx.Graph()
G = gen_graph(pro_coords[i], lig_coords[j],
pro_hvy_atom[i], lig_hvy_atom[j], l)
#vertices = np.zeros(G.number_of_nodes())
if G.number_of_edges() > 0:
frc = FormanRicci(G)
frc.compute_ricci_curvature()
temp_feature.append(frc.G)
else:
temp_feature.append(G)
"""
for v in orc.G.nodes():
try:
vertices[v] = orc.G.nodes[v]["ricciCurvature"]
except:
vertices[v] = 0
# Binning the vertex ORCs
index = np.linspace(-1, 1, num_of_bins)
bins = np.zeros(num_of_bins)
for v in range(len(vertices)):
for ind in range(len(index)-1):
if vertices[v] >= index[ind] and vertices[v] < index[ind+1]:
bins[ind] += 1
temp_feature.append(bins)
"""
X_graphs.append(temp_feature)
#feature_x.append(X_feature)
np.save(
"ORC PLB IDM 2016/forman_test_graphs/" + pdbid + "_" +
str(cutoff) + "_" + str(threshold) + ".npy", X_graphs)
