tytel: hmm, wonder what 1D worley noise would be like

worley.py

from math import sqrt
from tqdm import tqdm
from random import random
import matplotlib
from matplotlib import pyplot as plt

point_count = 20

zoop = [0]*2048
points = [0]*point_count

def closest_point(x):
    """Find the closest point to a given position."""
    best = 0
    best_dist = 4000000000
    x2 = x * x

    for y, z in enumerate(points):
        score = abs((z * z) - x2)
        if score < best_dist:
            best_dist = score
            best = y
    return points[best]

def lerp(a, b, t):
    return ((1.0 - t) * a) + (t * b)

print("Placing 1D Worley points")
for i in tqdm(range(0, point_count)):
    points[i] = round(random() * 2048)

print("Sorting")
points = sorted(points)

print("Closest point check")
for i in tqdm(range(0, 2048)):
    point = closest_point(i)
    zoop[i] = point

print("Distance testing")
for i in tqdm(range(0, 2048)):
    dist = abs((zoop[i] * zoop[i]) - (i * i))
    zoop[i] = sqrt(dist)

fig, ax = plt.subplots()
ax.plot(zoop)
fig.savefig('worley.svg')

worley.svg

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