max_iter = 20
zoom = -0.7
width, height = 7 * scale, 12 * scale
depth = u_samples
du = 1.0 / u_samples
c = np.quaternion(0.45, -0.3, 0.2, 0.5)
def source(q):
val = mandel(q, q, max_iter)
core = (val <= 0)
illumination = exp(-0.39 * val)
illumination = array(
[0.8 * illumination, 0.5 * illumination, illumination * 0.99]) * 40
illumination[:, core] = 0
absorption = array([2.5 * core, 1.5 * core, core]) * 40
return illumination, absorption
def generate_subpixel_image(offset_x, offset_y):
slices = generate_mesh_slices(width, height, depth, 0, 0, 0, 0, zoom,
theta, phi, gamma, beta, offset_x,
offset_y)
image = illuminate_and_absorb(slices, source,
array([0.35, 0.3, 0.4]) * 0.25, du)
return image
image = threaded_anti_alias(generate_subpixel_image, width, height,
anti_aliasing)
imsave("/tmp/transdimensional_doorknob.png", make_picture_frame(image))
absorption = 2.5*exp(-0.3*val)
absorption[core] = 4
green += 40*core * dz
green *= exp(-dz * absorption)
absorption = 2*exp(-0.35*val)
absorption[core] = 2.5
blue += 30*core * dz
blue *= exp(-dz * absorption)
lock.acquire()
result += array([red, green, blue])*0.1
lock.release()
ts = []
offsets_x = np.arange(anti_aliasing) / anti_aliasing * dx
offsets_y = np.arange(anti_aliasing) / anti_aliasing * dy
for i in offsets_x:
for j in offsets_y:
ts.append(Thread(target=accumulate_subpixels, args=(i, j)))
ts[-1].start()
for t in ts:
t.join()
result /= anti_aliasing**2
image = result
imsave("/tmp/out.png", make_picture_frame(image))
