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frostburn/quaternion_density_cloud.py

Created September 9, 2018 13:37
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Visualizing a quaternion density cloud
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quaternion_density_cloud.py
import numpy as np
import quaternion
import scipy.misc
import multiprocessing
t = 0
def project_cloud(seed):
np.random.seed(seed)
cloud = np.random.randn(1000000, 4) * 0.2
cloud[:, 0] = 0
cloud = quaternion.as_quat_array(cloud)
c = np.quaternion(0, 1, 0.5, -t) * 0.05
d = np.quaternion(0, 0.2 + 2 * t, -3, 1) * 0.05
results = []
z = cloud
for i in range(16):
r = (1 + z) ** 8
z = r*(z + d)/r + c
results.append(z)
width = 640
height = 360
center_x = 0
center_y = 0
transform = np.quaternion(1, 3, 2, 1)
transform /= abs(transform)
transform **= 4.7979 * t
transform *= 1.2
imgs = []
for z in results:
z -= np.quaternion(0, center_y, center_x, 0)
z *= transform
z = quaternion.as_float_array(z)
img = np.histogram2d(z[:, 1], z[:, 2], range=[(-height/width, height/width), (-1, 1)], bins=[height, width])[0]
imgs.append(img)
return imgs
num_frames = 256
for n in range(num_frames):
t = n / num_frames
p = multiprocessing.Pool(14) # New pool to sync global t
imgss = p.map(project_cloud, range(14 * 4))
p.close()
r = 0
g = 0
b = 0
for imgs in imgss:
r += imgs[-6]
g += imgs[-3]
b += imgs[-1]
weight = (r.mean() + g.mean() + b.mean()) * 9
r /= weight
g /= weight
b /= weight
img = np.array([r, g, b])
filename = 'imgs/density_{0:05d}.png'.format(n)
print('Saving', filename)
scipy.misc.toimage(img, cmin=0, cmax=1).save(filename)
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