dot packing animation

# dot packing animation

import cv2
import numpy as np
from easing_functions import CubicEaseInOut

# force window to 100% scale (windows only)
import ctypes
ctypes.windll.user32.SetProcessDPIAware()


ints = lambda *args: tuple(map(int, args))
rounds = lambda *args: tuple(map(round, args))

class Dot:
    def __init__(self, xs, ys, size, ease=CubicEaseInOut()):
        self.xs = xs
        self.ys = ys
        self.size = size
        self.ease = ease

    def draw(self, img, t):
        i = int(t)
        f = t % 1

        max_i = min(len(self.xs), len(self.ys)) - 2
        if i > max_i:
            i = max_i
            f = 1.0

        f = self.ease(f)

        x = self.xs[i]*(1.0-f) + self.xs[i+1]*f
        y = self.ys[i]*(1.0-f) + self.ys[i+1]*f

        img = cv2.circle(img, rounds(x, y), self.size, 255, -1)


# set parameters here
count = 500
spacing = 10
img_x, img_y = 800, 800

x0, y0 = spacing*2, img_y-spacing*2
dx, dy = spacing, -spacing
x_count_start, x_count_end = 1, int(count/4)

# make dots
dots = []
for i in range(count):
    dot = Dot([], [], int(spacing*0.8/2))
    dots.append(dot)

# calculate and save values
for x_count in range(x_count_start, x_count_end+1):
    for i in range(count):
        ix = i % x_count
        iy = int(i / x_count)

        x = x0 + ix * dx
        y = y0 + iy * dy

        dots[i].xs.append(x)
        dots[i].ys.append(y)

# animate
t = 0.0
while True:
    img = np.zeros((img_y, img_x), dtype='uint8')
    for i in range(count):
        dots[i].draw(img, t)

    cv2.imshow('img', img)
    key = cv2.waitKey(10)

    if key == ord('r'):
        t = 0.0
    elif key == ord('x'):
        cv2.destroyAllWindows()
        break

    t += 0.01