def check(method, directed):
SP1, pred = shortest_path(directed_G,
directed=directed,
overwrite=False,
return_predecessors=True)
SP2 = construct_dist_matrix(directed_G, pred, directed=directed)
assert_array_almost_equal(SP1, SP2)
def check(method, directed):
SP1, pred = shortest_path(directed_G,
directed=directed,
overwrite=False,
return_predecessors=True)
SP2 = construct_dist_matrix(directed_G, pred, directed=directed)
assert_array_almost_equal(SP1, SP2)
def test_construct_shortest_path():
SP_res = {True: directed_SP,
False: undirected_SP}
for method in methods:
for directed in (True, False):
SP1, pred = shortest_path(directed_G,
directed=directed,
overwrite=False,
return_predecessors=True)
SP2 = construct_dist_matrix(directed_G, pred, directed=directed)
yield (assert_array_almost_equal, SP1, SP2)
def test_construct_shortest_path():
SP_res = {True: directed_SP,
False: undirected_SP}
for method in methods:
for directed in (True, False):
SP1, pred = shortest_path(directed_G,
directed=directed,
overwrite=False,
return_predecessors=True)
SP2 = construct_dist_matrix(directed_G, pred, directed=directed)
yield (assert_array_almost_equal, SP1, SP2)
def geoDistDistribution(self, which='array', printd=False):
'''
Computation of the geodesic distances.
Input:
- which (string): if 'array', then the distances are returned as an array,
otherwise, if 'mean', the average distance is returned
- printd (bool): if set to true, then the average distance is printed
Output:
- distances (numpy.array): array of the numerical distances between nodes
- dmean (numpy.float64): mean distance
'''
import scipy.sparse.csgraph as csg
A = self.computeAdjMatrix('pruned')
Asparse = csg.csgraph_from_dense(A)
Dmatrix, predecessors = csg.shortest_path(Asparse,
return_predecessors=True,
method='D')
Dmatrix = csg.construct_dist_matrix(A, predecessors, directed=False)
distances = Dmatrix[Dmatrix != np.inf]
# self.introduce()
# print('Connected components = {}'.format(csg.connected_components(Asparse)))
# print('Done with distances')
if which == 'array':
return distances
elif which == 'mean':
dmean = distances.mean()
# if printd: print('<d> = {:.4f}'.format(dmean))
return dmean
