def test_get_population():
ga = DiffusionGA('just_for_test')
arr = numpy.empty(4)
for i in range(4):
arr[i] = i
ga._fitness_arr = numpy.empty(2)
ga._fitness_arr[0] = arr[0]
ga._fitness_arr[1] = arr[1]
ga._chrom_arr = numpy.empty(2)
ga._chrom_arr[0] = arr[2]
ga._chrom_arr[1] = arr[3]
assert (ga.population[0] == arr[2:]).all()
assert (ga.population[1] == arr[:2]).all()
def test_get_neighbour(fit_list, row, column):
ga = RealGA(fitness_test_sin_func)
dga = DiffusionGA(ga)
dga._chrom_arr = numpy.array(list(range(9))).reshape((3, 3))
dga._fitness_arr = numpy.array(fit_list).reshape(3, 3)
shape = dga._chrom_arr.shape
selected_chromosome = dga._get_neighbour(row, column)
indices = numpy.where(dga._chrom_arr == selected_chromosome)
coords = (indices[0][0], indices[1][0])
valid_indices = [((row - 1) % shape[0], column),
((row + 1) % shape[0], column),
(row, (column - 1) % shape[1]),
(row, (column + 1) % shape[1])]
assert coords in valid_indices