def test_correct_example_update_works(self):
# test two networks with different thresholds
ntwk = DiscreteTimeSquareLattice(
shape=(5, 8),
activation_strength=2,
inactivation_strength=-2,
threshold=1.5,
steepness=1000,
weight_type='nearest_neighbor_diagonal',
)
ntwk.vs_matrix = np.array([
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
])
correct_next_vs_matrix = np.array([
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 2, 2, 2, 0, 0, 0, 0],
[0, 2, 1,-2, 0, 0, 0, 0],
[0, 2, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
])
ntwk.step()
np.testing.assert_array_equal(ntwk.vs_matrix, correct_next_vs_matrix)
# second network to test
ntwk = DiscreteTimeSquareLattice(
shape=(5, 8),
activation_strength=2,
inactivation_strength=-2,
threshold=2.5,
steepness=1000,
weight_type='nearest_neighbor_diagonal',
)
ntwk.vs_matrix = np.array([
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
])
correct_next_vs_matrix = np.array([
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 1,-2, 0, 0, 0, 0],
[0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
])
ntwk.step()
np.testing.assert_array_equal(ntwk.vs_matrix, correct_next_vs_matrix)
def test_make_weight_matrix_makes_correct_weight_matrices(self):
# we'll try out a 4 x 5 lattice for the nearest neighbor setting
# [x x x x x]
# [x x x x x]
# [x x x x x]
# [x x x x x]
# to vectorize the lattice we read left to right, top to bottom
correct_matrix = np.array([
# 00 01 02 03 04 10 11 12 13 14 20 21 22 23 24 30 31 32 33 34
[0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,], # 00
[1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,], # 01
[0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,], # 02
[0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,], # 03
[0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,], # 04
[1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0,], # 10
[1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0,], # 11
[0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0,], # 12
[0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0,], # 13
[0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0,], # 14
[0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0,], # 20
[0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0,], # 21
[0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0,], # 22
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1,], # 23
[0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1,], # 24
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0,], # 30
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0,], # 31
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0,], # 32
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1,], # 33
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0,], # 34
], dtype=float)
shape = (4, 5)
weight_type = 'nearest_neighbor_diagonal'
np.testing.assert_array_equal(DiscreteTimeSquareLattice.make_weight_matrix(shape, weight_type), correct_matrix)