generate 1.3.0 palette, render new color space figures

.gitignore

@@ -19,3 +19,6 @@ docs/_build/
 
 data/
 archive/
+
+notebooks/color_spaces_manyview.ipynb
+notebooks/oklch_srgb_spherical.ipynb

notebooks/gamut_3d_plotly.py

@@ -10,6 +10,7 @@ import math
 import plotly.io as io
 import os
 import json
+import numpy as np
 
 sys.path.insert(0, os.getcwd())
 
@@ -1016,6 +1017,440 @@ def main():
         return 0
     return 1
 
+def plot_sphere_in_oklch(
+    fig,
+    center,
+    radius,
+    gmap,
+    filters=(),
+    resolution=24,
+    opacity=0.4,
+    edges=False,
+    faces=False,
+    ecolor=None,
+    fcolor=None,
+    equal_metric=False    # <- new flag, see below
+):
+    space = 'oklch'
+    target = Color.CS_MAP[space]
+    flags = {
+        'is_cyl': target.is_polar(),
+        'is_labish': isinstance(target, Labish),
+        'is_lchish': isinstance(target, LChish),
+        'is_hslish': isinstance(target, HSLish),
+        'is_hwbish': isinstance(target, HWBish),
+        'is_hsvish': isinstance(target, HSVish)
+    }
+
+    # Center in OKLab (Euclidean space behind OKLCH)
+    c_center = Color(center).convert('oklab', in_place=True).normalize(nans=False)
+    L0, a0, b0 = c_center[0], c_center[1], c_center[2]
+
+    # Parametric sphere in (L, a, b)
+    thetas = np.linspace(0.0, np.pi, resolution)
+    phis = np.linspace(0.0, 2.0 * np.pi, 2 * resolution, endpoint=False)
+    TT, PP = np.meshgrid(thetas, phis)
+    TT_flat = TT.ravel()
+    PP_flat = PP.ravel()
+
+    L_vals = L0 + radius * np.cos(TT_flat)
+    a_vals = a0 + radius * np.sin(TT_flat) * np.cos(PP_flat)
+    b_vals = b0 + radius * np.sin(TT_flat) * np.sin(PP_flat)
+
+    x = []
+    y = []
+    z = []
+    cmap = []
+    inside_mask = []
+
+    for Lv, av, bv in zip(L_vals, a_vals, b_vals):
+        c = Color('oklab', [Lv, av, bv]).convert(space, in_place=True).normalize(nans=False)
+
+        # Basic L sanity; out-of-range L is definitely not useful
+        if not (0.0 <= c[0] <= 1.0):
+            inside_mask.append(False)
+            x.append(0.0); y.append(0.0); z.append(0.0)
+            cmap.append('#000000')
+            continue
+
+        store_coords(c, x, y, z, flags)
+
+        s = c.convert('srgb')
+        in_gamut = s.in_gamut()
+        inside_mask.append(in_gamut)
+
+        if in_gamut:
+            if not s.in_gamut():
+                s.fit(**gmap)
+            else:
+                s.clip()
+            if filters:
+                s.filter(filters[0], **filters[1], in_place=True, out_space=s.space()).clip()
+            cmap.append(s.to_string(hex=True, alpha=False))
+        else:
+            cmap.append('#000000')
+
+    inside_mask = np.asarray(inside_mask, dtype=bool)
+
+    # Triangulate parameter space (theta, phi)
+    uv = np.column_stack([TT_flat, PP_flat])
+    tri = Delaunay(uv)
+    simplices = tri.simplices
+
+    # Keep only triangles whose vertices are all in gamut
+    keep = inside_mask[simplices].all(axis=1)
+    simplices = simplices[keep]
+    if simplices.size == 0:
+        return
+
+    # Compact vertices to those actually used in kept simplices
+    used = np.unique(simplices.ravel())
+    idx_map = {old: i for i, old in enumerate(used)}
+    simplices_comp = np.vectorize(idx_map.__getitem__)(simplices)
+
+    x2 = [x[i] for i in used]
+    y2 = [y[i] for i in used]
+    z2 = [z[i] for i in used]
+    cmap2 = [cmap[i] for i in used]
+
+    class _Tri:
+        def __init__(self, simplices):
+            self.simplices = simplices
+
+    tri2 = _Tri(simplices_comp)
+
+    create3d(
+        fig,
+        x2,
+        y2,
+        z2,
+        tri2,
+        cmap2,
+        edges=edges,
+        faces=faces,
+        ecolor=ecolor,
+        fcolor=fcolor,
+        opacity=opacity,
+        filters=filters
+    )
+
+    if equal_metric:
+        set_equal_metric_aspect(fig)
+
+def plot_sphere_in_oklch2(
+    fig,
+    center,              # Color spec, interpreted via Color()
+    radius,              # OKLab radius
+    gmap,
+    filters=(),
+    resolution=24,
+    opacity=0.2,
+    edges=False,
+    faces=False,
+    ecolor=None,
+    fcolor=None,
+    outside_color='#000000'
+):
+    space = 'oklch'
+    target = Color.CS_MAP[space]
+    flags = {
+        'is_cyl': target.is_polar(),
+        'is_labish': isinstance(target, Labish),
+        'is_lchish': isinstance(target, LChish),
+        'is_hslish': isinstance(target, HSLish),
+        'is_hwbish': isinstance(target, HWBish),
+        'is_hsvish': isinstance(target, HSVish)
+    }
+
+    # Center in OKLab (Euclidean)
+    c_center = Color(center).convert('oklab', in_place=True).normalize(nans=False)
+    L0, a0, b0 = c_center[0], c_center[1], c_center[2]
+
+    # Parametric sphere in (L, a, b)
+    thetas = np.linspace(0.0, np.pi, resolution)
+    phis = np.linspace(0.0, 2.0 * np.pi, 2 * resolution, endpoint=False)
+    TT, PP = np.meshgrid(thetas, phis)
+    TT_flat = TT.ravel()
+    PP_flat = PP.ravel()
+
+    L_vals = L0 + radius * np.cos(TT_flat)
+    a_vals = a0 + radius * np.sin(TT_flat) * np.cos(PP_flat)
+    b_vals = b0 + radius * np.sin(TT_flat) * np.sin(PP_flat)
+
+    x, y, z, cmap = [], [], [], []
+
+    for Lv, av, bv in zip(L_vals, a_vals, b_vals):
+        # Build OKLab color, convert to OKLCH for consistency with the space
+        c = Color('oklab', [Lv, av, bv]).convert(space, in_place=True).normalize(nans=False)
+
+        # Map to plotted coordinates (LCh → Lab embedding)
+        store_coords(c, x, y, z, flags)
+
+        # Decide vertex color based on sRGB gamut
+        s = c.convert('srgb')
+        if s.in_gamut():
+            if not s.in_gamut():
+                s.fit(**gmap)
+            else:
+                s.clip()
+            if filters:
+                s.filter(filters[0], **filters[1], in_place=True, out_space=s.space()).clip()
+            cmap.append(s.to_string(hex=True, alpha=False))
+        else:
+            cmap.append(outside_color)
+
+    # Triangulate parameter space (theta, phi).
+    # NOTE: we DO NOT filter simplices here: full sphere is drawn,
+    # just colored differently inside vs outside.
+    uv = np.column_stack([TT_flat, PP_flat])
+    tri = Delaunay(uv)
+
+    create3d(
+        fig,
+        x,
+        y,
+        z,
+        tri,
+        cmap,
+        edges=edges,
+        faces=faces,
+        ecolor=ecolor,
+        fcolor=fcolor,
+        opacity=opacity,
+        filters=filters
+    )
+
+def plot_sphere_in_oklch3(
+    fig,
+    center,
+    radius,
+    gmap,
+    filters=(),
+    resolution=24,
+    opacity=0.4,
+    edges=False,
+    faces=False,
+    ecolor=None,
+    fcolor=None,
+    draw_boundary=True,
+    boundary_color='black',
+    boundary_width=3
+):
+    space = 'oklch'
+    target = Color.CS_MAP[space]
+    flags = {
+        'is_cyl': target.is_polar(),
+        'is_labish': isinstance(target, Labish),
+        'is_lchish': isinstance(target, LChish),
+        'is_hslish': isinstance(target, HSLish),
+        'is_hwbish': isinstance(target, HWBish),
+        'is_hsvish': isinstance(target, HSVish)
+    }
+
+    # 1) Center in OKLab (Euclidean)
+    c_center = Color(center).convert('oklab', in_place=True).normalize(nans=False)
+    L0, a0, b0 = c_center[0], c_center[1], c_center[2]
+
+    # 2) Parametric sphere in (L, a, b)
+    thetas = np.linspace(0.0, np.pi, resolution)
+    phis = np.linspace(0.0, 2.0 * np.pi, 2 * resolution, endpoint=False)
+    TT, PP = np.meshgrid(thetas, phis)
+    TT_flat = TT.ravel()
+    PP_flat = PP.ravel()
+
+    L_vals = L0 + radius * np.cos(TT_flat)
+    a_vals = a0 + radius * np.sin(TT_flat) * np.cos(PP_flat)
+    b_vals = b0 + radius * np.sin(TT_flat) * np.sin(PP_flat)
+
+    x = []
+    y = []
+    z = []
+    cmap = []
+    inside_mask = []
+
+    for Lv, av, bv in zip(L_vals, a_vals, b_vals):
+        # OKLab -> OKLCH (for consistency with space)
+        c = Color('oklab', [Lv, av, bv]).convert(space, in_place=True).normalize(nans=False)
+
+        # Optionally reject totally crazy L, but not strictly required
+        if not (0.0 <= c[0] <= 1.0):
+            inside_mask.append(False)
+            x.append(0.0); y.append(0.0); z.append(0.0)
+            cmap.append('#000000')
+            continue
+
+        # Map to 3D coords used in gamut plotting
+        store_coords(c, x, y, z, flags)
+
+        # sRGB for display + in-gamut test
+        s = c.convert('srgb')
+        in_gamut = s.in_gamut()
+        inside_mask.append(in_gamut)
+
+        if in_gamut:
+            if not s.in_gamut():
+                s.fit(**gmap)
+            else:
+                s.clip()
+            if filters:
+                s.filter(filters[0], **filters[1], in_place=True, out_space=s.space()).clip()
+            cmap.append(s.to_string(hex=True, alpha=False))
+        else:
+            # color won't be used for clipped mesh, but keep list aligned
+            cmap.append('#000000')
+
+    inside_mask = np.asarray(inside_mask, dtype=bool)
+
+    # 3) Triangulate parameter space
+    uv = np.column_stack([TT_flat, PP_flat])
+    tri_all = Delaunay(uv)
+    simplices_all = tri_all.simplices
+
+    # ----- 3a) Build clipped mesh: only triangles fully inside gamut -----
+    keep = inside_mask[simplices_all].all(axis=1)
+    simplices = simplices_all[keep]
+    if simplices.size == 0:
+        # sphere completely out of gamut; nothing to draw
+        return
+
+    used = np.unique(simplices.ravel())
+    idx_map = {old: i for i, old in enumerate(used)}
+    simplices_comp = np.vectorize(idx_map.__getitem__)(simplices)
+
+    x2 = [x[i] for i in used]
+    y2 = [y[i] for i in used]
+    z2 = [z[i] for i in used]
+    cmap2 = [cmap[i] for i in used]
+
+    class _Tri:
+        def __init__(self, simplices):
+            self.simplices = simplices
+
+    tri2 = _Tri(simplices_comp)
+
+    # Clipped sphere surface
+    create3d(
+        fig,
+        x2,
+        y2,
+        z2,
+        tri2,
+        cmap2,
+        edges=edges,
+        faces=faces,
+        ecolor=ecolor,
+        fcolor=fcolor,
+        opacity=opacity,
+        filters=filters
+    )
+
+    # ----- 3b) Boundary curve: edges where inside/outside differ -----
+    if draw_boundary:
+        boundary_edges = set()
+
+        for vs in simplices_all:
+            m = inside_mask[vs]
+            # If all in or all out, no boundary here
+            if np.all(m) or (not np.any(m)):
+                continue
+
+            # For each triangle edge, if it connects inside<->outside, add it
+            edge_pairs = ((vs[0], vs[1]), (vs[1], vs[2]), (vs[2], vs[0]))
+            for a, b in edge_pairs:
+                if inside_mask[a] != inside_mask[b]:
+                    # use sorted so (a,b) and (b,a) are treated the same
+                    boundary_edges.add(tuple(sorted((a, b))))
+
+        if boundary_edges:
+            xe, ye, ze = [], [], []
+            for a, b in boundary_edges:
+                xe.extend([x[a], x[b], None])
+                ye.extend([y[a], y[b], None])
+                ze.extend([z[a], z[b], None])
+
+            fig.add_trace(
+                go.Scatter3d(
+                    x=xe,
+                    y=ye,
+                    z=ze,
+                    mode='lines',
+                    line={'color': boundary_color, 'width': boundary_width},
+                    showlegend=False,
+                    name=''
+                )
+            )
+
+
+def set_equal_metric_aspect(fig):
+    xs = []
+    ys = []
+    zs = []
+
+    for tr in fig.data:
+        # Just be defensive in case some traces don't have full 3D coords
+        tx = getattr(tr, 'x', None)
+        ty = getattr(tr, 'y', None)
+        tz = getattr(tr, 'z', None)
+        if tx is None or ty is None or tz is None:
+            continue
+        xs.extend([v for v in tx if v is not None])
+        ys.extend([v for v in ty if v is not None])
+        zs.extend([v for v in tz if v is not None])
+
+    if not xs or not ys or not zs:
+        return
+
+    xmin, xmax = min(xs), max(xs)
+    ymin, ymax = min(ys), max(ys)
+    zmin, zmax = min(zs), max(zs)
+
+    dx = xmax - xmin or 1.0
+    dy = ymax - ymin or 1.0
+    dz = zmax - zmin or 1.0
+
+    m = max(dx, dy, dz)
+
+    fig.update_layout(
+        scene=dict(
+            aspectmode='manual',
+            aspectratio=dict(
+                x=dx / m,
+                y=dy / m,
+                z=dz / m
+            )
+        )
+    )
+
+def freeze_scene_axes(fig):
+    xs, ys, zs = [], [], []
+
+    for tr in fig.data:
+        tx = getattr(tr, 'x', None)
+        ty = getattr(tr, 'y', None)
+        tz = getattr(tr, 'z', None)
+        if tx is None or ty is None or tz is None:
+            continue
+        xs.extend([v for v in tx if v is not None])
+        ys.extend([v for v in ty if v is not None])
+        zs.extend([v for v in tz if v is not None])
+
+    if not xs or not ys or not zs:
+        return
+
+    xmin, xmax = min(xs), max(xs)
+    ymin, ymax = min(ys), max(ys)
+    zmin, zmax = min(zs), max(zs)
+
+    fig.update_layout(
+        scene=dict(
+            xaxis=dict(range=[xmin, xmax], autorange=False),
+            yaxis=dict(range=[ymin, ymax], autorange=False),
+            zaxis=dict(range=[zmin, zmax], autorange=False),
+        )
+    )
+
+
+
         
 if __name__ == "__main__":
     sys.exit(main())

pyproject.toml

@@ -6,6 +6,7 @@ readme = "README.md"
 requires-python = ">=3.12"
 dependencies = [
     "coloraide>=5.1",
+    "imageio[ffmpeg]>=2.37.2",
     "ipython>=9.6.0",
     "kaleido>=1.1.0",
     "matplotlib>=3.10.7",

templates/groups/monobiome-oklch.json

@@ -546,76 +546,76 @@
     "98": "oklch(98.0% 0.0094 262.0)"
   },
   "red": {
-    "10": "oklch(10.0% 0.0391 29.0)",
+    "10": "oklch(10.0% 0.0406 29.0)",
-    "11": "oklch(11.0% 0.0429 29.0)",
+    "11": "oklch(11.0% 0.0446 29.0)",
-    "12": "oklch(12.0% 0.0468 29.0)",
+    "12": "oklch(12.0% 0.0486 29.0)",
-    "13": "oklch(13.0% 0.0506 29.0)",
+    "13": "oklch(13.0% 0.0526 29.0)",
-    "14": "oklch(14.0% 0.0545 29.0)",
+    "14": "oklch(14.0% 0.0566 29.0)",
-    "15": "oklch(15.0% 0.0583 29.0)",
+    "15": "oklch(15.0% 0.0606 29.0)",
-    "16": "oklch(16.0% 0.0621 29.0)",
+    "16": "oklch(16.0% 0.0645 29.0)",
-    "17": "oklch(17.0% 0.0659 29.0)",
+    "17": "oklch(17.0% 0.0685 29.0)",
-    "18": "oklch(18.0% 0.0697 29.0)",
+    "18": "oklch(18.0% 0.0724 29.0)",
-    "19": "oklch(19.0% 0.0735 29.0)",
+    "19": "oklch(19.0% 0.0763 29.0)",
-    "20": "oklch(20.0% 0.0773 29.0)",
+    "20": "oklch(20.0% 0.0802 29.0)",
-    "21": "oklch(21.0% 0.0810 29.0)",
+    "21": "oklch(21.0% 0.0841 29.0)",
-    "22": "oklch(22.0% 0.0847 29.0)",
+    "22": "oklch(22.0% 0.0879 29.0)",
-    "23": "oklch(23.0% 0.0885 29.0)",
+    "23": "oklch(23.0% 0.0918 29.0)",
-    "24": "oklch(24.0% 0.0922 29.0)",
+    "24": "oklch(24.0% 0.0956 29.0)",
-    "25": "oklch(25.0% 0.0958 29.0)",
+    "25": "oklch(25.0% 0.0994 29.0)",
-    "26": "oklch(26.0% 0.0995 29.0)",
+    "26": "oklch(26.0% 0.1031 29.0)",
-    "27": "oklch(27.0% 0.1031 29.0)",
+    "27": "oklch(27.0% 0.1068 29.0)",
-    "28": "oklch(28.0% 0.1067 29.0)",
+    "28": "oklch(28.0% 0.1106 29.0)",
-    "29": "oklch(29.0% 0.1103 29.0)",
+    "29": "oklch(29.0% 0.1142 29.0)",
-    "30": "oklch(30.0% 0.1139 29.0)",
+    "30": "oklch(30.0% 0.1179 29.0)",
-    "31": "oklch(31.0% 0.1174 29.0)",
+    "31": "oklch(31.0% 0.1215 29.0)",
-    "32": "oklch(32.0% 0.1209 29.0)",
+    "32": "oklch(32.0% 0.1250 29.0)",
-    "33": "oklch(33.0% 0.1244 29.0)",
+    "33": "oklch(33.0% 0.1286 29.0)",
-    "34": "oklch(34.0% 0.1278 29.0)",
+    "34": "oklch(34.0% 0.1320 29.0)",
-    "35": "oklch(35.0% 0.1312 29.0)",
+    "35": "oklch(35.0% 0.1355 29.0)",
-    "36": "oklch(36.0% 0.1346 29.0)",
+    "36": "oklch(36.0% 0.1389 29.0)",
-    "37": "oklch(37.0% 0.1378 29.0)",
+    "37": "oklch(37.0% 0.1422 29.0)",
-    "38": "oklch(38.0% 0.1411 29.0)",
+    "38": "oklch(38.0% 0.1454 29.0)",
-    "39": "oklch(39.0% 0.1443 29.0)",
+    "39": "oklch(39.0% 0.1486 29.0)",
-    "40": "oklch(40.0% 0.1474 29.0)",
+    "40": "oklch(40.0% 0.1517 29.0)",
-    "41": "oklch(41.0% 0.1505 29.0)",
+    "41": "oklch(41.0% 0.1548 29.0)",
-    "42": "oklch(42.0% 0.1535 29.0)",
+    "42": "oklch(42.0% 0.1577 29.0)",
-    "43": "oklch(43.0% 0.1564 29.0)",
+    "43": "oklch(43.0% 0.1606 29.0)",
-    "44": "oklch(44.0% 0.1592 29.0)",
+    "44": "oklch(44.0% 0.1634 29.0)",
-    "45": "oklch(45.0% 0.1619 29.0)",
+    "45": "oklch(45.0% 0.1660 29.0)",
-    "46": "oklch(46.0% 0.1645 29.0)",
+    "46": "oklch(46.0% 0.1685 29.0)",
-    "47": "oklch(47.0% 0.1670 29.0)",
+    "47": "oklch(47.0% 0.1709 29.0)",
-    "48": "oklch(48.0% 0.1694 29.0)",
+    "48": "oklch(48.0% 0.1732 29.0)",
-    "49": "oklch(49.0% 0.1716 29.0)",
+    "49": "oklch(49.0% 0.1752 29.0)",
-    "50": "oklch(50.0% 0.1737 29.0)",
+    "50": "oklch(50.0% 0.1772 29.0)",
-    "51": "oklch(51.0% 0.1756 29.0)",
+    "51": "oklch(51.0% 0.1789 29.0)",
-    "52": "oklch(52.0% 0.1774 29.0)",
+    "52": "oklch(52.0% 0.1804 29.0)",
-    "53": "oklch(53.0% 0.1789 29.0)",
+    "53": "oklch(53.0% 0.1817 29.0)",
-    "54": "oklch(54.0% 0.1802 29.0)",
+    "54": "oklch(54.0% 0.1828 29.0)",
-    "55": "oklch(55.0% 0.1813 29.0)",
+    "55": "oklch(55.0% 0.1836 29.0)",
-    "56": "oklch(56.0% 0.1821 29.0)",
+    "56": "oklch(56.0% 0.1842 29.0)",
-    "57": "oklch(57.0% 0.1827 29.0)",
+    "57": "oklch(57.0% 0.1845 29.0)",
-    "58": "oklch(58.0% 0.1829 29.0)",
+    "58": "oklch(58.0% 0.1845 29.0)",
-    "59": "oklch(59.0% 0.1829 29.0)",
+    "59": "oklch(59.0% 0.1842 29.0)",
-    "60": "oklch(60.0% 0.1825 29.0)",
+    "60": "oklch(60.0% 0.1836 29.0)",
-    "61": "oklch(61.0% 0.1819 29.0)",
+    "61": "oklch(61.0% 0.1826 29.0)",
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+    "65": "oklch(65.0% 0.1426 262.0)",
-    "66": "oklch(66.0% 0.1394 262.0)",
+    "66": "oklch(66.0% 0.1415 262.0)",
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+    "67": "oklch(67.0% 0.1401 262.0)",
-    "68": "oklch(68.0% 0.1365 262.0)",
+    "68": "oklch(68.0% 0.1384 262.0)",
-    "69": "oklch(69.0% 0.1346 262.0)",
+    "69": "oklch(69.0% 0.1364 262.0)",
-    "70": "oklch(70.0% 0.1324 262.0)",
+    "70": "oklch(70.0% 0.1342 262.0)",
-    "71": "oklch(71.0% 0.1300 262.0)",
+    "71": "oklch(71.0% 0.1317 262.0)",
-    "72": "oklch(72.0% 0.1273 262.0)",
+    "72": "oklch(72.0% 0.1289 262.0)",
-    "73": "oklch(73.0% 0.1244 262.0)",
+    "73": "oklch(73.0% 0.1259 262.0)",
-    "74": "oklch(74.0% 0.1212 262.0)",
+    "74": "oklch(74.0% 0.1226 262.0)",
-    "75": "oklch(75.0% 0.1179 262.0)",
+    "75": "oklch(75.0% 0.1192 262.0)",
-    "76": "oklch(76.0% 0.1144 262.0)",
+    "76": "oklch(76.0% 0.1155 262.0)",
-    "77": "oklch(77.0% 0.1107 262.0)",
+    "77": "oklch(77.0% 0.1117 262.0)",
-    "78": "oklch(78.0% 0.1068 262.0)",
+    "78": "oklch(78.0% 0.1077 262.0)",
-    "79": "oklch(79.0% 0.1028 262.0)",
+    "79": "oklch(79.0% 0.1036 262.0)",
-    "80": "oklch(80.0% 0.0986 262.0)",
+    "80": "oklch(80.0% 0.0994 262.0)",
-    "81": "oklch(81.0% 0.0943 262.0)",
+    "81": "oklch(81.0% 0.0950 262.0)",
     "82": "oklch(82.0% 0.0898 262.0)",
     "83": "oklch(83.0% 0.0845 262.0)",
     "84": "oklch(84.0% 0.0792 262.0)",

templates/groups/palette/monobiome.toml

@@ -1,4 +1,4 @@
-version = "1.2.0"
+version = "1.3.0"
 
 [alpine]
 l10 = "#030303"

uv.lock

@@ -290,6 +290,39 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c7/93/0dd45cd283c32dea1545151d8c3637b4b8c53cdb3a625aeb2885b184d74d/fonttools-4.60.1-py3-none-any.whl", hash = "sha256:906306ac7afe2156fcf0042173d6ebbb05416af70f6b370967b47f8f00103bbb", size = 1143175, upload-time = "2025-09-29T21:13:24.134Z" },
 ]
 
+[[package]]
+name = "imageio"
+version = "2.37.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "pillow" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/a3/6f/606be632e37bf8d05b253e8626c2291d74c691ddc7bcdf7d6aaf33b32f6a/imageio-2.37.2.tar.gz", hash = "sha256:0212ef2727ac9caa5ca4b2c75ae89454312f440a756fcfc8ef1993e718f50f8a", size = 389600, upload-time = "2025-11-04T14:29:39.898Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/fb/fe/301e0936b79bcab4cacc7548bf2853fc28dced0a578bab1f7ef53c9aa75b/imageio-2.37.2-py3-none-any.whl", hash = "sha256:ad9adfb20335d718c03de457358ed69f141021a333c40a53e57273d8a5bd0b9b", size = 317646, upload-time = "2025-11-04T14:29:37.948Z" },
+]
+
+[package.optional-dependencies]
+ffmpeg = [
+    { name = "imageio-ffmpeg" },
+    { name = "psutil" },
+]
+
+[[package]]
+name = "imageio-ffmpeg"
+version = "0.6.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/44/bd/c3343c721f2a1b0c9fc71c1aebf1966a3b7f08c2eea8ed5437a2865611d6/imageio_ffmpeg-0.6.0.tar.gz", hash = "sha256:e2556bed8e005564a9f925bb7afa4002d82770d6b08825078b7697ab88ba1755", size = 25210, upload-time = "2025-01-16T21:34:32.747Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/da/58/87ef68ac83f4c7690961bce288fd8e382bc5f1513860fc7f90a9c1c1c6bf/imageio_ffmpeg-0.6.0-py3-none-macosx_10_9_intel.macosx_10_9_x86_64.whl", hash = "sha256:9d2baaf867088508d4a3458e61eeb30e945c4ad8016025545f66c4b5aaef0a61", size = 24932969, upload-time = "2025-01-16T21:34:20.464Z" },
+    { url = "https://files.pythonhosted.org/packages/40/5c/f3d8a657d362cc93b81aab8feda487317da5b5d31c0e1fdfd5e986e55d17/imageio_ffmpeg-0.6.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:b1ae3173414b5fc5f538a726c4e48ea97edc0d2cdc11f103afee655c463fa742", size = 21113891, upload-time = "2025-01-16T21:34:00.277Z" },
+    { url = "https://files.pythonhosted.org/packages/33/e7/1925bfbc563c39c1d2e82501d8372734a5c725e53ac3b31b4c2d081e895b/imageio_ffmpeg-0.6.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:1d47bebd83d2c5fc770720d211855f208af8a596c82d17730aa51e815cdee6dc", size = 25632706, upload-time = "2025-01-16T21:33:53.475Z" },
+    { url = "https://files.pythonhosted.org/packages/a0/2d/43c8522a2038e9d0e7dbdf3a61195ecc31ca576fb1527a528c877e87d973/imageio_ffmpeg-0.6.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:c7e46fcec401dd990405049d2e2f475e2b397779df2519b544b8aab515195282", size = 29498237, upload-time = "2025-01-16T21:34:13.726Z" },
+    { url = "https://files.pythonhosted.org/packages/a0/13/59da54728351883c3c1d9fca1710ab8eee82c7beba585df8f25ca925f08f/imageio_ffmpeg-0.6.0-py3-none-win32.whl", hash = "sha256:196faa79366b4a82f95c0f4053191d2013f4714a715780f0ad2a68ff37483cc2", size = 19652251, upload-time = "2025-01-16T21:34:06.812Z" },
+    { url = "https://files.pythonhosted.org/packages/2c/c6/fa760e12a2483469e2bf5058c5faff664acf66cadb4df2ad6205b016a73d/imageio_ffmpeg-0.6.0-py3-none-win_amd64.whl", hash = "sha256:02fa47c83703c37df6bfe4896aab339013f62bf02c5ebf2dce6da56af04ffc0a", size = 31246824, upload-time = "2025-01-16T21:34:28.6Z" },
+]
+
 [[package]]
 name = "iniconfig"
 version = "2.3.0"
@@ -589,10 +622,11 @@ wheels = [
 
 [[package]]
 name = "monobiome"
-version = "0.1.0"
+version = "1.2.0"
 source = { virtual = "." }
 dependencies = [
     { name = "coloraide" },
+    { name = "imageio", extra = ["ffmpeg"] },
     { name = "ipython" },
     { name = "kaleido" },
     { name = "matplotlib" },
@@ -611,6 +645,7 @@ dev = [
 [package.metadata]
 requires-dist = [
     { name = "coloraide", specifier = ">=5.1" },
+    { name = "imageio", extras = ["ffmpeg"], specifier = ">=2.37.2" },
     { name = "ipython", specifier = ">=9.6.0" },
     { name = "kaleido", specifier = ">=1.1.0" },
     { name = "matplotlib", specifier = ">=3.10.7" },