def test_linear_threshold_with_step(self):
G = networkx.DiGraph()
G.add_edge(1, 2, influence=.5)
G.add_edge(2, 1, influence=.5)
G.add_edge(1, 3, influence=.2)
G.add_edge(3, 1, influence=.2)
G.add_edge(2, 3, influence=.3)
G.add_edge(2, 4, influence=.5)
G.add_edge(3, 4, influence=.1)
G.add_edge(3, 5, influence=.2)
G.add_edge(4, 5, influence=.2)
G.add_edge(5, 6, influence=.6)
G.add_edge(6, 5, influence=.6)
G.add_edge(6, 4, influence=.3)
G.add_edge(6, 2, influence=.4)
G.node[2]['threshold'] = .4
G.node[3]['threshold'] = .4
G.node[4]['threshold'] = .55
G.node[5]['threshold'] = .5
G.node[6]['threshold'] = .3
layers = linear_threshold(G, [1], 1)
assert_equal(len(layers[0]), 1)
assert (1 in layers[0])
assert_equal(len(layers[1]), 1)
assert (2 in layers[1])
layers = linear_threshold(G, [1], 2)
assert_equal(len(layers[0]), 1)
assert (1 in layers[0])
assert_equal(len(layers[1]), 1)
assert (2 in layers[1])
assert_equal(len(layers[2]), 1)
assert (3 in layers[2])
def test_linear_threshold_with_step(self):
G = networkx.DiGraph()
G.add_edge(1,2,influence=.5)
G.add_edge(2,1,influence=.5)
G.add_edge(1,3,influence=.2)
G.add_edge(3,1,influence=.2)
G.add_edge(2,3,influence=.3)
G.add_edge(2,4,influence=.5)
G.add_edge(3,4,influence=.1)
G.add_edge(3,5,influence=.2)
G.add_edge(4,5,influence=.2)
G.add_edge(5,6,influence=.6)
G.add_edge(6,5,influence=.6)
G.add_edge(6,4,influence=.3)
G.add_edge(6,2,influence=.4)
G.node[2]['threshold'] = .4
G.node[3]['threshold'] = .4
G.node[4]['threshold'] = .55
G.node[5]['threshold'] = .5
G.node[6]['threshold'] = .3
layers = linear_threshold(G, [1], 1)
assert_equal(len(layers[0]), 1)
assert(1 in layers[0])
assert_equal(len(layers[1]), 1)
assert(2 in layers[1])
layers = linear_threshold(G, [1], 2)
assert_equal(len(layers[0]), 1)
assert(1 in layers[0])
assert_equal(len(layers[1]), 1)
assert(2 in layers[1])
assert_equal(len(layers[2]), 1)
assert(3 in layers[2])
def test_linear_threshold(self):
G = networkx.DiGraph()
G.add_edge(1, 2, influence=.5)
G.add_edge(2, 1, influence=.5)
G.add_edge(1, 3, influence=.2)
G.add_edge(3, 1, influence=.2)
G.add_edge(2, 3, influence=.3)
G.add_edge(2, 4, influence=.5)
G.add_edge(3, 4, influence=.1)
G.add_edge(3, 5, influence=.2)
G.add_edge(4, 5, influence=.2)
G.add_edge(5, 6, influence=.6)
G.add_edge(6, 5, influence=.6)
G.add_edge(6, 4, influence=.3)
G.add_edge(6, 2, influence=.4)
G.node[2]['threshold'] = .4
G.node[3]['threshold'] = .4
G.node[4]['threshold'] = .55
G.node[5]['threshold'] = .5
G.node[6]['threshold'] = .3
layers = linear_threshold(G, [1])
print layers
assert_equal(len(layers[0]), 1)
assert (1 in layers[0])
assert_equal(len(layers[1]), 1)
assert (2 in layers[1])
assert_equal(len(layers[2]), 1)
assert (3 in layers[2])
assert_equal(len(layers[3]), 1)
assert (4 in layers[3])
assert_equal(len(reduce(lambda x, y: x + y, layers)), 4)
def test_linear_threshold(self):
G = networkx.DiGraph()
G.add_edge(1,2,influence=.5)
G.add_edge(2,1,influence=.5)
G.add_edge(1,3,influence=.2)
G.add_edge(3,1,influence=.2)
G.add_edge(2,3,influence=.3)
G.add_edge(2,4,influence=.5)
G.add_edge(3,4,influence=.1)
G.add_edge(3,5,influence=.2)
G.add_edge(4,5,influence=.2)
G.add_edge(5,6,influence=.6)
G.add_edge(6,5,influence=.6)
G.add_edge(6,4,influence=.3)
G.add_edge(6,2,influence=.4)
G.node[2]['threshold'] = .4
G.node[3]['threshold'] = .4
G.node[4]['threshold'] = .55
G.node[5]['threshold'] = .5
G.node[6]['threshold'] = .3
layers = linear_threshold(G, [1])
print layers
assert_equal(len(layers[0]), 1)
assert(1 in layers[0])
assert_equal(len(layers[1]), 1)
assert(2 in layers[1])
assert_equal(len(layers[2]), 1)
assert(3 in layers[2])
assert_equal(len(layers[3]), 1)
assert(4 in layers[3])
assert_equal(len(reduce(lambda x,y: x+y, layers)), 4)
def test_linear_threshold_graph_without_attribute(self):
G = networkx.Graph()
G.add_edges_from([(1,2), (1,3), (2,3), (3,4), (3,5), (4,5), (4,6), (5,6)])
layers = linear_threshold(G, [1])
assert_equal(len(layers[0]), 1)
assert(1 in layers[0])
assert_equal(len(layers[1]), 1)
assert(2 in layers[1])
assert_equal(len(layers[2]), 1)
assert(3 in layers[2])
layers = linear_threshold(G, [1,4])
assert_equal(len(reduce(lambda x,y: x+y, layers)), 6)
layers = linear_threshold(G, [1,2])
assert_equal(len(layers[0]), 2)
assert(1 in layers[0])
assert(2 in layers[0])
assert_equal(len(layers[1]), 1)
assert(3 in layers[1])
def test_linear_threshold_graph_without_attribute(self):
G = networkx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (3, 5), (4, 5),
(4, 6), (5, 6)])
layers = linear_threshold(G, [1])
assert_equal(len(layers[0]), 1)
assert (1 in layers[0])
assert_equal(len(layers[1]), 1)
assert (2 in layers[1])
assert_equal(len(layers[2]), 1)
assert (3 in layers[2])
layers = linear_threshold(G, [1, 4])
assert_equal(len(reduce(lambda x, y: x + y, layers)), 6)
layers = linear_threshold(G, [1, 2])
assert_equal(len(layers[0]), 2)
assert (1 in layers[0])
assert (2 in layers[0])
assert_equal(len(layers[1]), 1)
assert (3 in layers[1])
