Image Array¶
This demo presents the image array scene in 2D and shows how the animation state evolves over time with lib-anim. The script defines a canva, adds the corresponding items, and updates them frame by frame to produce the final motion.
Full Code¶
1'''
22D image array demo
3'''
4
5import numpy as np
6import anim
7
8# ═══ 2D Animation canva ═══════════════════════════════════════════════════
9
10class Canva(anim.plane.canva):
11
12 # ────────────────────────────────────────────────────────────────────────
13 def __init__(self, window):
14
15 # Number of channels (1 or 3)
16 self.nchannel = 1
17
18 # Number of pixels in the image
19 self.npix = 500
20
21 super().__init__(window, pixelperunit=self.npix)
22
23 self.item.img = anim.plane.image(
24 position = [0.5, 0.5],
25 dimension = [1, 1],
26 array = self.ripple(0),
27 # colormap = anim.colormap('gnuplot', range=[-1, 1])
28 )
29
30 # ────────────────────────────────────────────────────────────────────────
31 def ripple(self, t):
32
33 # Base field
34 x = np.linspace(-1, 1, self.npix)
35 X, Y = np.meshgrid(x, x)
36 base_field = (20 * X**2) + (20 * Y**2)
37
38 match self.nchannel:
39
40 case 1:
41 ''' Single channel '''
42
43 return np.sin(base_field - t/2/np.pi)
44
45 case 3:
46 ''' RGB channels '''
47
48 R = np.sin(base_field - t/2/np.pi)
49 G = np.sin(base_field - t/2/np.pi+np.pi/2)
50 B = np.sin(base_field - t/2/np.pi+np.pi)
51
52 return np.concatenate((R[:,:,None], G[:,:,None], B[:,:,None]), axis=2)
53
54 # ────────────────────────────────────────────────────────────────────────
55 def update(self, t):
56
57 self.item.img.array = self.ripple(t.step)
58
59 # Confirm update
60 super().update(t)
61
62# ═══ Main ═════════════════════════════════════════════════════════════════
63
64W = anim.window('Image animation')
65
66# Add animation
67W.add(Canva)
68
69# Allow backward animation
70W.allow_backward = True
71W.allow_negative_time = True
72
73W.show()