implement consistent quantization of srgb8 for palette figure

monobiome/palette.py

@@ -5,6 +5,10 @@ from importlib.metadata import version
 
 from coloraide import Color
 
+from monobiome.util import (
+    hex_from_rgb8,
+    srgb8_from_color,
+)
 from monobiome.constants import (
     h_map,
     L_points,
@@ -24,8 +28,8 @@ def compute_hlc_map(notation: str) -> dict[str, Any]:
             oklch = Color('oklch', [_l/100, _c, _h])
 
             if notation == "hex":
-                srgb = oklch.convert('srgb')
+                rgb8 = srgb8_from_color(oklch)
-                c_str = srgb.to_string(hex=True)
+                c_str = hex_from_rgb8(rgb8)
             elif notation == "oklch":
                 ol, oc, oh = oklch.convert('oklch').coords()
                 c_str = f"oklch({ol*100:.1f}% {oc:.4f} {oh:.1f})"

monobiome/plotting.py

@@ -5,6 +5,7 @@ import matplotlib.pyplot as plt
 from coloraide import Color
 from matplotlib.collections import LineCollection
 
+from monobiome.util import srgb8_from_color
 from monobiome.palette import compute_hlc_map
 from monobiome.constants import (
     h_map,
@@ -87,7 +88,9 @@ def plot_hue_chroma_star() -> tuple[plt.Figure, plt.Axes]:
 
         _h = h_map[h_str]
         h_colors = [
-            Color('oklch', [_l/100, _c, _h]).convert("srgb")
+            Color(
+                'oklch', [_l/100, _c, _h]
+            ).convert("srgb").fit(method="oklch-chroma")
             for _l, _c in zip(L_points, Lpoints_Cstar, strict=True)
         ]
         
@@ -124,7 +127,7 @@ def palette_image(
 
     h = row_count * cell_size
     w = max_cols * cell_size
-    img = np.ones((h, w, 3), float)
+    img = np.ones((h, w, 3), int)
 
     lightness_keys_per_row = []
 
@@ -133,8 +136,7 @@ def palette_image(
         lkeys = sorted(shades.keys())
         lightness_keys_per_row.append(lkeys)
         for c, k in enumerate(lkeys):
-            col = Color(shades[k]).convert("srgb").fit(method="clip")
+            rgb = srgb8_from_color(shades[k])
-            rgb = [col["r"], col["g"], col["b"]]
             r0, r1 = r * cell_size, (r + 1) * cell_size
             c0, c1 = c * cell_size, (c + 1) * cell_size
             img[r0:r1, c0:c1, :] = rgb
@@ -156,7 +158,7 @@ def show_palette(
     if show_labels:
         fig, ax = plt.subplots(figsize=(fig_w, fig_h), dpi=dpi)
 
-        ax.imshow(img, interpolation="none", origin="upper")
+        ax.imshow(img, interpolation="nearest", origin="upper")
         ax.set_xticks([])
 
         ytick_pos = [(i + 0.5) * cell_size for i in range(len(names))]

monobiome/util.py

@@ -2,6 +2,7 @@ import math
 from types import GenericAlias
 from argparse import ArgumentParser, _SubParsersAction
 
+import numpy as np
 from coloraide import Color
 
 _SubParsersAction.__class_getitem__ = classmethod(GenericAlias)
@@ -33,3 +34,13 @@ def oklch_distance(xc: Color, yc: Color) -> float:
     dz = l1 - l2
     
     return (dx**2 + dy**2 + dz**2)**0.5
+
+def srgb8_from_color(c: str | Color) -> np.ndarray:
+    c = Color(c).convert("srgb").fit(method="oklch-chroma")
+    rgb = np.array([c["r"], c["g"], c["b"]], dtype=float)
+    rgb8 = np.clip(np.round(rgb * 255), 0, 255).astype(np.uint8)
+
+    return rgb8
+
+def hex_from_rgb8(rgb8: np.ndarray) -> str:
+    return f"#{int(rgb8[0]):02x}{int(rgb8[1]):02x}{int(rgb8[2]):02x}"

scripts/prepare.sh

@@ -11,3 +11,6 @@ uv run monobiome palette -n oklch -f toml -o colors/oklch-palette.toml
 
 # generate provided app config
 "$script_dir/generate.sh"
+
+# generate release plots
+uv run "$script_dir/plots.py"