y'know there must be code for this somewhere already. but this makes a
   quick analog image.

   commit 7e23db09ca066d41c7e1227d5444c2d5f3482151 (HEAD -> main,
   origin/main, origin/HEAD)
   Author: xloem <[1]0xloem@gmail.com>
   Date:   Sun Mar 27 23:13:15 2022 -0400
       implement quickly
   diff --git a/gen_encoder_wheel/__main__.py
   b/gen_encoder_wheel/__main__.py
   index f1bd4f6..608eb43 100644
   --- a/gen_encoder_wheel/__main__.py
   +++ b/gen_encoder_wheel/__main__.py
   @@ -3,6 +3,12 @@ from imageio import v3 as iio
    import numpy as np
    import click
   +# i used to have an idea for very precise position detection.
   +# i do not remember what that idea was.
   +
   +def angle2intensity(distance, angle):
   +    return angle / np.pi / 2
   +
    @click.command()
    @click.option('--size', default=4096, help='Height of wheel.')
    @click.option('--ratio', default=1.0, help='Aspect ratio of wheel.
   width = ratio * size')
   @@ -10,8 +16,13 @@ import click
    @click.option('--output', help='Output filename.')
    def generate(size, ratio, dpi, output):
        height = size * dpi
   -    width = height * ratio
   -    img =
   np.random.randint(0,0xffff,size=(int(width+.5),height,3),dtype=np.uint1
   6)
   +    fwidth = height * ratio
   +    width = int(fwidth+.5)
   +    x = np.tile(np.arange(width) / (fwidth - 1) * 2 - 1, (height, 1))
   +    y = np.tile((np.arange(height) / (height - 1) * 2 - 1)[:, None],
   width)
   +    dists = np.sqrt(x * x + y * y)
   +    angs = np.arctan2(x, y)
   +    img = (angle2intensity(dists, angs) * 0xffff +
   np.random.random((width, height))).astype(np.uint16)
        return write(output, img)
    def write(fn, ndimg):

References

   1. mailto:0xloem@gmail.com