commit 7e23db09ca066d41c7e1227d5444c2d5f3482151 (HEAD -> main, origin/main, origin/HEAD)

Author: xloem <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.uint16)

+    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):