def test_density_generator_invalid_height(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
seed = 1
with self.assertRaises(IndexError):
height += 2 #invald
simulate_predator_prey.density_generator(landscape, seed, width,
height)
def test_count_land_only(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
number_of_land_only = simulate_predator_prey.count_land_only(landscape)
self.assertEqual(
200,
number_of_land_only,
msg="Land-only squares number returned was unexpected")
def test_average_of_density(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
seed = 1
generated_density = simulate_predator_prey.density_generator(
landscape, seed, width, height)
number_of_land_only = simulate_predator_prey.count_land_only(landscape)
average = simulate_predator_prey.average_of_density(
generated_density, number_of_land_only)
#self.assertEqual(2.4268595788671457, average, msg = "Average returned was unexpected")
self.assertAlmostEqual(2.4268595788671457,
average,
delta=0.00000001,
msg="Average returned was unexpected")
def test_num_of_land_neighbours(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
land_neighbours = simulate_predator_prey.num_of_land_neighbours(
height_halo, width_halo, height, width, landscape)
expected_land_neighbours = np.zeros((22, 12), int)
expected_land_neighbours[1] = expected_land_neighbours[20] = [
0, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 0
]
for i in range(2, 20):
expected_land_neighbours[i] = [0, 3, 4, 4, 4, 4, 4, 4, 4, 4, 3, 0]
self.assertTrue(
(expected_land_neighbours == land_neighbours).all(),
msg="Number of land neighbours returned was unexpected")
def test_ppm_color_matrix_invalid_width(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
hare_densities = simulate_predator_prey.density_generator(
landscape, 1, width, height)
puma_densities = simulate_predator_prey.density_generator(
landscape, 1, width, height)
hare_cols = np.zeros((height, width), int)
puma_cols = np.zeros((height, width), int)
width += 2
with self.assertRaises(IndexError):
simulate_predator_prey.ppm_color_matrix(hare_densities,
puma_densities, landscape,
width, height, hare_cols,
puma_cols)
def test_landscape_generator(self):
width, height, width_halo, height_halo, landscape = simulate_predator_prey.landscape_generator(
"map.dat")
expected_landscape = np.zeros((22, 12), int)
for i in range(1, 21):
expected_landscape[i] = [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]
self.assertEqual(10, width, msg="Width returned was unexpected")
self.assertEqual(20, height, msg="Height returned was unexpected")
self.assertEqual(12,
width_halo,
msg="Width_halo returned was unexpected")
self.assertEqual(22,
height_halo,
msg="Height_halo returned was unexpected")
self.assertTrue((expected_landscape == landscape).all(),
msg="Landscape returned was unexpected")
def test_landscape_generator_nonExisting_file(self):
with self.assertRaises(FileNotFoundError):
simulate_predator_prey.landscape_generator("1234")