def test_dist2prox_prox2dist(): """ Test Utils: Prox2Dist & Dist2Prox """ assert np.isclose(dist2prox(prox2dist(P)) , P).all()
from distanceclosure.dijkstra import Dijkstra
from distanceclosure.utils import prox2dist
import numpy as np
import networkx as nx
#
# Test
#
# Numpy
P = np.array([
[1.,.9,.1,0.],
[.9,1.,.8,0.],
[.1,.8,1.,.6],
[0.,0.,.6,1.],
], dtype=float)
D = prox2dist(P)
#
# Edgelist
#
edgelist_luis = {
('s','b'):.9,
('s','c'):.1,
('b','c'):.8,
('c','d'):.6,
}
edgelist_james = {
('s','a'):8,
('s','c'):6,
('s','d'):5,
('a','d'):2,
('a','e'):1,
def test_dist2prox(): """ Test Utils: Dist2Prox """ assert np.isclose(prox2dist(P), D_true).all()
}
"""
edgelist = {
('s','b'):.9,
('s','c'):.1,
('b','c'):.8,
('c','d'):.6,
}
"""
matrix = np.array([
[1.,.9,.1,0.],
[.9,1.,.8,0.],
[.1,.8,1.,.6],
[0.,0.,.6,1.],
], dtype=float)
matrix = prox2dist(matrix)
sparse = csr_matrix(matrix)
source = 2
# NX
#G = nx.from_edgelist(edgelist)
G = nx.from_numpy_matrix(matrix)
#nx.set_edge_attributes(G, 'weight', edgelist)
nx_lenghts = nx.single_source_dijkstra_path_length(G, source=source, weight='weight')
nx_paths = nx.single_source_dijkstra_path(G, source=source, weight='weight')
d = Dijkstra(verbose=True)
#d.from_edgelist(edgelist, directed=False)
#d.from_numpy_matrix(matrix, directed=False)
d.from_sparse_matrix(sparse, directed=False)
