def simplex2D_subjective():
print("Displaying 2D simplex output")
N = 100
pmap = [[combined(simplex2D, x / N, y / N) for x in range(N)]
for y in range(N)]
plt.subplot(221)
plt.title("6 octaves")
plt.imshow(pmap, cmap='plasma', interpolation='nearest')
plt.subplot(222)
plt.title("1 octave")
pmap = [[
combined(simplex2D, 6 * x / N, 6 * y / N, octaves=1) for x in range(N)
] for y in range(N)]
plt.imshow(pmap, cmap='plasma', interpolation='nearest')
plt.subplot(223)
plt.title("4 octaves, marbled")
mpmap = [[
sin(1.6 * 2 * pi *
combined(simplex2D, 6 * x / N, 6 * y / N, octaves=4))
for x in range(N)
] for y in range(N)]
plt.imshow(mpmap, cmap='plasma', interpolation='nearest')
plt.subplot(224)
plt.title("15 octaves, crinkled")
cpmap = [[
combined(simplex2D, 10 * x / N, 10 * y / N, octaves=15)
for x in range(N)
] for y in range(N)]
plt.imshow(cpmap, cmap='plasma', interpolation='nearest')
plt.show()
def white2D_functional():
print("Testing correlation for 2D white noise")
N = 100
x1 = randrange(-1000, 1000, 1)
y1 = randrange(-1000, 1000, 1)
x2 = x1 + randrange(-1000, 1000, 1)
y2 = y1 + randrange(-1000, 1000, 1)
values1 = [[combined(white, x / N, y / N) for x in range(x1, x1 + N)] for y in range(y1, y1 + N)]
values2 = [[combined(white, x / N, y / N) for x in range(x2, x2 + N)] for y in range(y2, y2 + N)]
rho = spearmanr(values1, values2, axis=None)
assert abs(rho[0]) < 0.5
print("rho = %s" % rho[0])
print("\tNot signifying correlation found")
def white4D_performance():
print("Testing time to fill a 10x10x10x10 array with default parameters")
base = time()
N = 10
pmap = [[[[combined(white, x / N, y / N, z / N, w / N) for x in range(N)] for y in range(N)] for z in range(N)] for w in range(N)]
elapsed = time() - base
print("\tElapsed %s seconds" % elapsed)
assert elapsed < 1.5
def white2D_performance2():
print("Testing time to fill a 70x70 array with 15 octaves")
base = time()
N = 70
pmap = [[combined(white, x / N, y / N, octaves=50) for x in range(N)] for y in range(N)]
elapsed = time() - base
print("\tElapsed %s seconds" % elapsed)
assert elapsed < 1.8
def white2D_performance():
print("Testing time to fill a 200x200 array with default parameters")
base = time()
N = 200
pmap = [[combined(white, x / N, y / N) for x in range(N)] for y in range(N)]
elapsed = time() - base
print("\tElapsed %s seconds" % elapsed)
assert elapsed < 0.5
def white4D_functional():
print("Testing correlation for 4D white noise")
N = 20
x1 = randrange(-1000, 1000, 1)
y1 = randrange(-1000, 1000, 1)
z1 = randrange(-1000, 1000, 1)
w1 = randrange(-1000, 1000, 1)
x2 = x1 + randrange(-1000, 1000, 1)
y2 = y1 + randrange(-1000, 1000, 1)
z2 = z1 + randrange(-1000, 1000, 1)
w2 = w1 + randrange(-1000, 1000, 1)
values1 = [[[[combined(white, x / N, y / N) for x in range(x1, x1 + N)] for y in range(y1, y1 + N)] for z in range(z1, z1 + N)] for w in range(w1, w1 + N)]
values2 = [[[[combined(white, x / N, y / N) for x in range(x2, x2 + N)] for y in range(y2, y2 + N)] for z in range(z2, z2 + N)] for w in range(w2, w2 + N)]
rho = spearmanr(values1, values2, axis=None)
assert abs(rho[0]) < 0.5
print("rho = %s" % rho[0])
print("\tNot signifying correlation found")
def opensimplex3D_performance():
print("Testing time to fill a 30x30x30 array with default parameters")
base = time()
N = 30
pmap = [[[combined(opensimplex3D, x / N, y / N, z / N) for x in range(N)]
for y in range(N)] for z in range(N)]
elapsed = time() - base
print("\tElapsed %s seconds" % elapsed)
assert elapsed < 2.5
