def test_noise_errors():
with pytest.raises(ValueError):
tcod.noise.Noise(0)
with pytest.raises(ValueError):
tcod.noise.Noise(1, implementation=-1)
noise = tcod.noise.Noise(2)
with pytest.raises(ValueError):
noise.sample_mgrid(np.mgrid[:2, :2, :2])
with pytest.raises(ValueError):
noise.sample_ogrid(np.ogrid[:2, :2, :2])
def test_noise_class(implementation):
noise = tcod.noise.Noise(2, tcod.NOISE_SIMPLEX, implementation)
# cover attributes
assert noise.dimensions == 2
noise.algorithm = noise.algorithm
noise.implementation = noise.implementation
noise.octaves = noise.octaves
noise.hurst
noise.lacunarity
noise.get_point(0, 0)
noise.sample_mgrid(np.mgrid[:2, :3])
noise.sample_ogrid(np.ogrid[:2, :3])
def generate(self):
noise = tcod.noise.Noise(dimensions=2,
algorithm=tcod.NOISE_SIMPLEX,
implementation=tcod.noise.TURBULENCE,
hurst=0.9,
lacunarity=2.0,
octaves=4,
seed=None)
ogrid = [
np.arange(100, dtype=np.int32),
np.arange(200, dtype=np.int32)
]
samples = noise.sample_ogrid(ogrid)
samples = samples * 10
newmap = []
objects = []
y = 0
for row in samples:
x = 0
newrow = []
for col in row:
t = classes.Floor(x, y)
if int(col) == 2:
tree = farm.Tree(x, y)
tree.state = farm.Plant.PlantStates.RIPE
tree.init()
objects.append(tree)
elif int(col) == 9:
t = classes.Grass(x, y)
newrow.append(t)
x += 1
y += 1
newmap.append(newrow)
return (newmap, objects)
def create_noise():
noise = tcod.noise.Noise(
dimensions=2,
algorithm=tcod.NOISE_PERLIN,
implementation=tcod.noise.SIMPLE,
hurst=0.5,
lacunarity=2.0,
octaves=4,
seed=None,
)
ogrid = [np.arange(64, dtype=np.float32), np.arange(64, dtype=np.float32)]
print(ogrid)
ogrid[0] *= 0.25
ogrid[1] *= 0.25
samples = noise.sample_ogrid(ogrid)
print(samples)
return samples
def test_noise_copy():
rand = tcod.random.Random(tcod.random.MERSENNE_TWISTER, 42)
noise = tcod.noise.Noise(2, seed=rand)
noise2 = pickle.loads(pickle.dumps(noise))
assert (noise.sample_ogrid(np.ogrid[:3, :1]) == noise2.sample_ogrid(
np.ogrid[:3, :1])).all()
def test_noise_pickle(implementation):
rand = tcod.random.Random(tcod.random.MERSENNE_TWISTER, 42)
noise = tcod.noise.Noise(2, implementation, seed=rand)
noise2 = copy.copy(noise)
assert (noise.sample_ogrid(np.ogrid[:3, :1]) == noise2.sample_ogrid(
np.ogrid[:3, :1])).all()
def test_noise_samples():
noise = tcod.noise.Noise(2, tcod.NOISE_SIMPLEX, tcod.noise.SIMPLE)
np.testing.assert_equal(
noise.sample_mgrid(np.mgrid[:32, :24]),
noise.sample_ogrid(np.ogrid[:32, :24]),
)
