fix light mode negation, improve oklch dist calc efficiency

.gitignore

@@ -19,3 +19,7 @@ docs/_build/
 
 data/
 archive/
+
+notebooks/color_spaces_manyview.ipynb
+notebooks/oklch_srgb_spherical.ipynb
+notebooks/v1.4.0/

README.md

@@ -142,6 +142,8 @@ dark `tundra` variant with the soft harshness level.
   each of which is generated using the [Firefox `manifest.json`
   template](templates/apps/firefox/templates/none-dark.manifest.json).
 
+  Static [light][4] and [dark][5] are additionally available.
+
   ![Firefox theme previews](images/firefox/themes.png)
 
 # Switching themes
@@ -204,3 +206,5 @@ biome/harshness/mode. This can be done for any app config file.
 [1]: https://github.com/isa/TextMate-Themes/blob/master/monoindustrial.tmTheme
 [2]: https://addons.mozilla.org/en-US/firefox/collections/18495484/monobiome/
 [3]: https://github.com/ologio/symconf
+[4]: https://addons.mozilla.org/en-US/firefox/collections/18495484/monobiome-light/
+[5]: https://addons.mozilla.org/en-US/firefox/collections/18495484/monobiome-dark/

examples/class.py

@@ -0,0 +1,68 @@
+class WLBPosteriorEstimator(PosteriorEstimatorTrainer):
+    """
+    Weighted likelihood bootstrap (WLB) estimator.
+
+    Trains models to approximate draws from the *weight posterior* (under
+    Jeffrey's prior).
+    """
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        assert not self.use_non_atomic_loss
+
+    def get_dataloaders(
+        self,
+        starting_round: int = 0,
+        training_batch_size: int = 200,
+        validation_fraction: float = 0.1,
+        resume_training: bool = False,
+        dataloader_kwargs: dict | None = None,
+    ) -> tuple[data.DataLoader, data.DataLoader]:
+        """
+        Add logic for generating session-specific WLB weights.
+
+        This is probably the easiest place to stick some fixed weights on a
+        point-wise basis for a given training run, and we load them later where
+        we need them in the ``train()`` loop.
+        """
+        theta, x, prior_masks = self.get_simulations(starting_round)
+
+        # generate session specific WLB weights to attach point-wise
+        N = theta.shape[0]
+        wlb_z = Exponential(1.0).sample((N,))
+        wlb_w = (wlb_z / wlb_z.sum()) * N
+
+        dataset = data.TensorDataset(theta, x, prior_masks, wlb_w)
+
+        num_examples = theta.size(0)
+        num_training_examples = int((1 - validation_fraction) * num_examples)
+        num_validation_examples = num_examples - num_training_examples
+
+        if not resume_training:
+            permuted_indices = torch.randperm(num_examples)
+            self.train_indices, self.val_indices = (
+                permuted_indices[:num_training_examples],
+                permuted_indices[num_training_examples:],
+            )
+
+        train_loader_kwargs = {
+            "batch_size": min(training_batch_size, num_training_examples),
+            "drop_last": True,
+            "sampler": SubsetRandomSampler(self.train_indices.tolist()),
+        }
+        val_loader_kwargs = {
+            "batch_size": min(training_batch_size, num_validation_examples),
+            "shuffle": False,
+            "drop_last": True,
+            "sampler": SubsetRandomSampler(self.val_indices.tolist()),
+        }
+        if dataloader_kwargs is not None:
+            train_loader_kwargs = dict(train_loader_kwargs, **dataloader_kwargs)
+            val_loader_kwargs = dict(val_loader_kwargs, **dataloader_kwargs)
+
+        train_loader = data.DataLoader(dataset, **train_loader_kwargs)
+        val_loader = data.DataLoader(dataset, **val_loader_kwargs)
+
+        return train_loader, val_loader
+

monobiome/__init__.py

@@ -0,0 +1,3 @@
+from importlib.metadata import version
+
+__version__ = version("monobiome")

monobiome/__main__.py

@@ -0,0 +1,19 @@
+from monobiome.cli import create_parser, configure_logging
+
+
+def main() -> None:
+    parser = create_parser()
+    args = parser.parse_args()
+
+    # skim off log level to handle higher-level option
+    if hasattr(args, "log_level") and args.log_level is not None:
+        configure_logging(args.log_level)
+
+    if "func" in args:
+        args.func(args)
+    else:
+        parser.print_help()
+
+
+if __name__ == "__main__":
+    main()

monobiome/cli/__init__.py

@@ -0,0 +1,32 @@
+import logging
+import argparse
+
+from monobiome.cli import scheme, palette
+
+logger: logging.Logger = logging.getLogger(__name__)
+
+def configure_logging(log_level: int) -> None:
+    """
+    Configure logger's logging level.
+    """
+
+    logger.setLevel(log_level)
+
+def create_parser() -> argparse.ArgumentParser:
+    parser = argparse.ArgumentParser(
+        description="Accent modeling CLI",
+    )
+    parser.add_argument(
+        "--log-level",
+        type=int,
+        metavar="int",
+        choices=[10, 20, 30, 40, 50],
+        help="Log level: 10=DEBUG, 20=INFO, 30=WARNING, 40=ERROR, 50=CRITICAL",
+    )
+
+    subparsers = parser.add_subparsers(help="subcommand help")
+
+    palette.register_parser(subparsers)
+    scheme.register_parser(subparsers)
+
+    return parser

monobiome/cli/palette.py

@@ -0,0 +1,51 @@
+import argparse
+from pathlib import Path
+
+from monobiome.util import _SubparserType
+from monobiome.palette import generate_palette
+
+
+def register_parser(subparsers: _SubparserType) -> None:
+    parser = subparsers.add_parser(
+        "palette",
+        help="generate primary palette"
+    )
+
+    parser.add_argument(
+        "-n",
+        "--notation",
+        type=str,
+        default="hex",
+        choices=["hex", "oklch"],
+        help="Color notation to export (either hex or oklch)",
+    )
+    parser.add_argument(
+        "-f",
+        "--format",
+        type=str,
+        default="toml",
+        choices=["json", "toml"],
+        help="Format of palette file (either JSON or TOML)",
+    )
+    parser.add_argument(
+        "-o",
+        "--output",
+        type=str,
+        help="Output file to write palette content",
+    )
+
+    parser.set_defaults(func=handle_palette)
+
+
+def handle_palette(args: argparse.Namespace) -> None:
+    notation = args.notation
+    file_format = args.format
+    output = args.output
+
+    palette_text = generate_palette(notation, file_format)
+
+    if output is None:
+        print(palette_text)
+    else:
+        with Path(output).open("w") as f:
+            f.write(palette_text)

monobiome/cli/scheme.py

@@ -0,0 +1,155 @@
+import argparse
+from pathlib import Path
+
+from monobiome.util import _SubparserType
+from monobiome.scheme import generate_scheme
+from monobiome.constants import monotone_h_map
+
+
+def register_parser(subparsers: _SubparserType) -> None:
+    parser = subparsers.add_parser(
+        "scheme",
+        help="create scheme variants"
+    )
+
+    parser.add_argument(
+        "mode",
+        type=str,
+        choices=["dark", "light"],
+        help="Scheme mode (light or dark)"
+    )
+    parser.add_argument(
+        "biome",
+        type=str,
+        choices=list(monotone_h_map.keys()),
+        help="Biome setting for scheme."
+    )
+    parser.add_argument(
+        "-m",
+        "--metric",
+        type=str,
+        default="oklch",
+        choices=["wcag", "oklch", "lightness"],
+        help="Metric to use for measuring swatch distances."
+    )
+
+    # e.g., wcag=4.5; oklch=0.40; lightness=40
+    parser.add_argument(
+        "-d",
+        "--distance",
+        type=float,
+        default=0.40,
+        help="Distance threshold for specified metric",
+    )
+    parser.add_argument(
+        "-o",
+        "--output",
+        type=str,
+        help="Output file to write scheme content",
+    )
+
+    # these params remain rooted in lightness; no need to accommodate metric
+    # given these are monotone adjustments. You *could* consider rooting these
+    # in metric units, but along monotones, distance=lightness and WCAG isn't a
+    # particularly good measure of perceptual distinction, so we'd prefer the
+    # former.
+    parser.add_argument(
+        "-l",
+        "--l-base",
+        type=int,
+        default=20,
+        help="Minimum lightness level (default: 20)",
+    )
+    parser.add_argument(
+        "--l-step",
+        type=int,
+        default=5,
+        help="Lightness step size (default: 5)",
+    )
+
+    # gaps
+    parser.add_argument(
+        "--fg-gap",
+        type=int,
+        default=50,
+        help="Foreground lightness gap (default: 50)",
+    )
+    parser.add_argument(
+        "--grey-gap",
+        type=int,
+        default=30,
+        help="Grey lightness gap (default: 30)",
+    )
+    parser.add_argument(
+        "--term-fg-gap",
+        type=int,
+        default=65,
+        help="Terminal foreground lightness gap (default: 60)",
+    )
+
+    parser.set_defaults(func=handle_scheme)
+
+
+def handle_scheme(args: argparse.Namespace) -> None:
+    output = args.output
+
+    mode = args.mode
+    biome =  args.biome
+    metric = args.metric
+    distance = args.distance
+    l_base = args.l_base
+    l_step = args.l_step
+    fg_gap = args.fg_gap
+    grey_gap = args.grey_gap
+    term_fg_gap = args.term_fg_gap
+
+    full_color_map = {
+        "red": "red",
+        "orange": "orange",
+        "yellow": "yellow",
+        "green": "green",
+        "cyan": "cyan",
+        "blue": "blue",
+        "violet": "violet",
+        "magenta": "orange",
+    }
+    term_color_map = {
+        "red": "red",
+        "yellow": "yellow",
+        "green": "green",
+        "cyan": "blue",
+        "blue": "blue",
+        "magenta": "orange",
+    }
+    vim_color_map = {
+        "red": "red",
+        "orange": "orange",
+        "yellow": "yellow",
+        "green": "green",
+        "cyan": "green",
+        "blue": "blue",
+        "violet": "blue",
+        "magenta": "red",
+    }
+    # vim_color_map = full_color_map
+
+    scheme_text = generate_scheme(
+        mode,
+        biome,
+        metric,
+        distance,
+        l_base,
+        l_step,
+        fg_gap,
+        grey_gap,
+        term_fg_gap,
+        full_color_map,
+        term_color_map,
+        vim_color_map,
+    )
+
+    if output is None:
+        print(scheme_text)
+    else:
+        with Path(output).open("w") as f:
+            f.write(scheme_text)

monobiome/constants.py

@@ -0,0 +1,123 @@
+import tomllib
+from importlib.resources import files
+
+import numpy as np
+
+from monobiome.curve import (
+    l_maxC_h,
+    bezier_y_at_x,
+)
+
+parameters_file = files("monobiome.data") / "parameters.toml"
+parameters = tomllib.load(parameters_file.open("rb"))
+
+L_min: int = parameters.get("L_min", 10)
+L_max: int = parameters.get("L_max", 98)
+L_step: int = parameters.get("L_step", 5)
+
+L_points: list[int] = list(range(L_min, L_max+1))
+
+# L-space just affects accuracy of chroma max
+L_space = np.arange(0, 100 + L_step, L_step)
+
+monotone_C_map = parameters.get("monotone_C_map", {})
+h_weights = parameters.get("h_weights", {})
+h_L_offsets = parameters.get("h_L_offsets", {})
+h_C_offsets = parameters.get("h_C_offsets", {})
+monotone_h_map = parameters.get("monotone_h_map", {})
+accent_h_map = parameters.get("accent_h_map", {})
+h_map = {**monotone_h_map, **accent_h_map}
+
+"""
+Compute chroma maxima at provided lightness levels across hues.
+
+A map with max chroma values for each hue across lightness space
+
+{
+   "red": [ Cmax@L=10, Cmax@L=11, Cmax@L=12, ... ],
+   "orange": [ Cmax@L=10, Cmax@L=11, Cmax@L=12, ... ],
+   ...
+}
+"""
+Lspace_Cmax_Hmap = {
+    h_str: [l_maxC_h(_L, _h) for _L in L_space]
+    for h_str, _h in h_map.items()
+}
+
+
+"""
+Set QBR curves, *unbounded* chroma curves for all hues
+
+1. Raw bezier chroma values for each hue across the lightness space
+
+   Lpoints_Cqbr_Hmap = {
+      "red": [ Bezier@L=10, Bezier@L=11, Bezier@L=12, ... ],
+      ...
+   }
+
+2. Three bezier control points for each hue's chroma curve
+
+   QBR_ctrl_Hmap = {
+      "red": np.array([
+          [ x1, y1 ],
+          [ x2, y2 ],
+          [ x3, y3 ]
+       ]),
+      ...
+   }
+"""
+Lpoints_Cqbr_Hmap = {}
+QBR_ctrl_Hmap = {}
+
+for h_str, _h in monotone_h_map.items():
+    Lpoints_Cqbr_Hmap[h_str] = np.array(
+        [monotone_C_map[h_str]]*len(L_points)
+    )
+    
+for h_str, _h in accent_h_map.items():
+    Lspace_Cmax = Lspace_Cmax_Hmap[h_str]
+    
+    # get L value of max chroma; will be a bezier control
+    L_Cmax_idx = np.argmax(Lspace_Cmax)
+    L_Cmax = L_space[L_Cmax_idx]
+
+    # offset control point by any preset x-shift
+    L_Cmax += h_L_offsets[h_str]
+
+    # and get max C at the L offset
+    Cmax = l_maxC_h(L_Cmax, _h)
+
+    # set 3 control points; shift by any global linear offest
+    C_offset = h_C_offsets.get(h_str, 0)
+    
+    p_0 = np.array([0, 0])
+    p_Cmax = np.array([L_Cmax, Cmax + C_offset])
+    p_100 = np.array([100, 0])
+    
+    B_L_points = bezier_y_at_x(
+        p_0, p_Cmax, p_100,
+        h_weights.get(h_str, 1),
+        L_points
+    )
+    Lpoints_Cqbr_Hmap[h_str] = B_L_points
+    QBR_ctrl_Hmap[h_str] = np.vstack([p_0, p_Cmax, p_100])
+
+
+"""
+Bezier chroma values, but bounded to attainable gamut colors (bezier fit
+can produce invalid chroma values)
+
+h_L_points_Cstar = {
+   "red": [ bounded-bezier@L=10, bounded-bezier@L=11, ... ],
+   ...
+}
+"""
+Lpoints_Cstar_Hmap = {}
+
+for h_str, L_points_C in Lpoints_Cqbr_Hmap.items():
+    _h = h_map[h_str]
+
+    Lpoints_Cstar_Hmap[h_str] = [
+        max(0, min(_C, l_maxC_h(_L, _h)))
+        for _L, _C in zip(L_points, L_points_C, strict=True)
+    ]

monobiome/curve.py

@@ -0,0 +1,77 @@
+from functools import cache
+
+import numpy as np
+from coloraide import Color
+
+
+def quad_bezier_rational(
+    P0: float,
+    P1: float,
+    P2: float,
+    w: float,
+    t: np.array,
+) -> np.array:
+    """
+    Compute the point values of a quadratic rational Bezier curve.
+
+    Uses `P0`, `P1`, and `P2` as the three control points of the curve. `w`
+    controls the weight toward the middle control point ("sharpness" of the
+    curve"), and `t` is the number of sample points used along the curve.
+    """
+
+    t = np.asarray(t)[:, None]
+    num = (1-t)**2*P0 + 2*w*(1-t)*t*P1 + t**2*P2
+    den = (1-t)**2 + 2*w*(1-t)*t + t**2
+    
+    return num / den
+    
+def bezier_y_at_x(
+    P0: float,
+    P1: float,
+    P2: float,
+    w: float,
+    x: float,
+    n: int = 400,
+) -> np.array:
+    """
+    For the provided QBR parameters, provide the curve value at the given
+    input.
+    """
+
+    t = np.linspace(0, 1, n)
+    B = quad_bezier_rational(P0, P1, P2, w, t)
+    x_vals, y_vals = B[:, 0], B[:, 1]
+    
+    return np.interp(x, x_vals, y_vals)
+
+@cache
+def l_maxC_h(
+    _l: float,
+    _h: float,
+    space: str = 'srgb',
+    eps: float = 1e-6,
+    tol: float = 1e-9
+) -> float:
+    """
+    Binary search for max attainable OKLCH chroma at fixed lightness and hue.
+
+    Parameters:
+        _l: lightness
+        _h: hue
+
+    Returns:
+        Max in-gamut chroma at provided lightness and hue
+    """
+
+    def chroma_in_gamut(_c: float) -> bool:
+        color = Color('oklch', [_l/100, _c, _h])
+        return color.convert(space).in_gamut(tolerance=tol)
+
+    lo, hi = 0.0, 0.1
+    while chroma_in_gamut(hi):
+        hi *= 2
+    while hi - lo > eps:
+        m = (lo + hi) / 2
+        lo, hi = (m, hi) if chroma_in_gamut(m) else (lo, m)
+
+    return lo

monobiome/palette.py

@@ -0,0 +1,54 @@
+import json
+from functools import cache
+from importlib.metadata import version
+
+from coloraide import Color
+
+from monobiome.constants import (
+    h_map,
+    L_points,
+    Lpoints_Cstar_Hmap,
+)
+
+
+@cache
+def compute_hlc_map(notation: str) -> dict[str, dict[int, str]]:
+    hlc_map = {}
+
+    for h_str, Lpoints_Cstar in Lpoints_Cstar_Hmap.items():
+        _h = h_map[h_str]
+        hlc_map[h_str] = {}
+        
+        for _l, _c in zip(L_points, Lpoints_Cstar, strict=True):
+            oklch = Color('oklch', [_l/100, _c, _h])
+
+            if notation == "hex":
+                srgb = oklch.convert('srgb')
+                c_str = srgb.to_string(hex=True)
+            elif notation == "oklch":
+                ol, oc, oh = oklch.convert('oklch').coords()
+                c_str = f"oklch({ol*100:.1f}% {oc:.4f} {oh:.1f})"
+            
+            hlc_map[h_str][_l] = c_str
+
+    return hlc_map
+
+def generate_palette(
+    notation: str,
+    file_format: str,
+) -> str:
+    mb_version = version("monobiome")
+    hlc_map = compute_hlc_map(notation)
+            
+    if file_format == "json":
+        hlc_map["version"] = mb_version
+        return json.dumps(hlc_map, indent=4)
+    else:
+        toml_lines = [f"version = {mb_version}", ""]
+        for _h, _lc_map in hlc_map.items():
+            toml_lines.append(f"[{_h}]")
+            for _l, _c in _lc_map.items():
+                toml_lines.append(f'l{_l} = "{_c}"')
+            toml_lines.append("")
+
+        return "\n".join(toml_lines)

monobiome/plotting.py

@@ -0,0 +1,176 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+from monobiome.constants import (
+    h_map,
+    L_space,
+    L_points,
+    accent_h_map,
+    monotone_h_map,
+    Lspace_Cmax_Hmap,
+    Lpoints_Cstar_Hmap,
+)
+
+
+def plot_hue_chroma_bounds() -> None:
+    name_h_map = {}
+    ax_h_map = {}
+    fig, axes = plt.subplots(
+        len(monotone_h_map),
+        1,
+        sharex=True,
+        sharey=True,
+        figsize=(4, 10)
+    )
+
+    for i, h_str in enumerate(Lpoints_Cstar_Hmap):
+        _h = h_map[h_str]
+
+        l_space_Cmax = Lspace_Cmax_Hmap[h_str]
+        l_points_Cstar = Lpoints_Cstar_Hmap[h_str]
+        
+        if _h not in ax_h_map:
+            ax_h_map[_h] = axes[i]
+        ax = ax_h_map[_h]
+        
+        if _h not in name_h_map:
+            name_h_map[_h] = []
+        name_h_map[_h].append(h_str)
+
+        # plot Cmax and Cstar
+        ax.plot(L_space, l_space_Cmax, c="g", alpha=0.3, label="Cmax")
+        
+        cstar_label = f"{'accent' if h_str in accent_h_map else 'monotone'} C*"
+        ax.plot(L_points, l_points_Cstar, alpha=0.7, label=cstar_label)
+        
+        ax.title.set_text(f"Hue [${_h}$] - {'|'.join(name_h_map[_h])}")
+        
+    axes[-1].set_xlabel("Lightness (%)")
+    axes[-1].set_xticks([L_points[0], L_points[-1]])
+
+    fig.tight_layout()
+    fig.subplots_adjust(top=0.9)
+
+    handles, labels = axes[-1].get_legend_handles_labels()
+    unique = dict(zip(labels, handles))
+    fig.legend(unique.values(), unique.keys(), loc='lower center', bbox_to_anchor=(0.5, -0.06), ncol=3)
+
+    plt.suptitle("$C^*$ curves for hue groups")
+    plt.show()
+
+
+def plot_hue_chroma_star() -> None:
+    fig, ax = plt.subplots(1, 1, figsize=(8, 6))
+
+    # uncomment to preview 5 core term colors
+    colors = accent_h_map.keys()
+    #colors = set(["red", "orange", "yellow", "green", "blue"])
+
+    for h_str in Lpoints_Cstar_Hmap:
+        if h_str not in accent_h_map or h_str not in colors:
+            continue
+        ax.fill_between(
+            L_points,
+            Lpoints_Cstar_Hmap[h_str],
+            alpha=0.2,
+            color='grey',
+            label=h_str
+        )
+
+        x, y = L_points, Lpoints_Cstar_Hmap[h_str]
+        n = int(0.45*len(x))
+        ax.text(x[n], y[n]-0.01, h_str, rotation=10, va='center', ha='left')
+        
+    ax.set_xlabel("Lightness (%)")
+    ax.set_xticks([L_points[0], 45, 50, 55, 60, 65, 70, L_points[-1]])
+    plt.suptitle("$C^*$ curves (v1.4.0)")
+    fig.show()
+
+
+def palette_image(palette, cell_size=40, keys=None):
+    if keys is None:
+        names = list(palette.keys())
+    else:
+        names = keys
+        
+    row_count = len(names)
+    col_counts = [len(palette[n]) for n in names]
+    max_cols = max(col_counts)
+
+    h = row_count * cell_size
+    w = max_cols * cell_size
+    img = np.ones((h, w, 3), float)
+
+    lightness_keys_per_row = []
+
+    for r, name in enumerate(names):
+        shades = palette[name]
+        keys = sorted(shades.keys())
+        lightness_keys_per_row.append(keys)
+        for c, k in enumerate(keys):
+            col = Color(shades[k]).convert("srgb").fit(method="clip")
+            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
+
+    return img, names, lightness_keys_per_row, cell_size, max_cols
+
+
+def show_palette(palette, cell_size=40, keys=None):
+    img, names, keys, cell_size, max_cols = palette_image(palette, cell_size, keys=keys)
+
+    fig_w = img.shape[1] / 100
+    fig_h = img.shape[0] / 100
+    fig, ax = plt.subplots(figsize=(fig_w, fig_h))
+
+    ax.imshow(img, interpolation="none", origin="upper")
+    ax.set_xticks([])
+
+    ytick_pos = [(i + 0.5) * cell_size for i in range(len(names))]
+    ax.set_yticks(ytick_pos)
+    ax.set_yticklabels(names)
+
+    ax.set_ylim(img.shape[0], 0)   # ensures rows render correctly without half-cells
+
+    plt.show()
+
+
+if __name__ == "__main__":
+    from monobiome.constants import OKLCH_hL_dict
+
+    keys = [
+        "alpine",
+        "badlands",
+        "chaparral",
+        "savanna",
+        "grassland",
+        "reef",
+        "tundra",
+        "heathland",
+        "moorland",
+        "orange",
+        "yellow",
+        "green",
+        "cyan",
+        "blue",
+        "violet",
+        "magenta",
+        "red",
+    ]
+    term_keys = [
+        "alpine",
+        "badlands",
+        "chaparral",
+        "savanna",
+        "grassland",
+        "tundra",
+        "red",
+        "orange",
+        "yellow",
+        "green",
+        "blue",
+    ]
+
+    show_palette(OKLCH_hL_dict, cell_size=25, keys=keys)
+    # show_palette(OKLCH_hL_dict, cell_size=1, keys=term_keys)

monobiome/scheme.py

@@ -0,0 +1,254 @@
+from functools import cache
+from collections.abc import Callable
+
+from coloraide import Color
+
+from monobiome.util import oklch_distance
+from monobiome.palette import compute_hlc_map
+from monobiome.constants import (
+    accent_h_map,
+    monotone_h_map,
+)
+
+
+@cache
+def compute_dma_map(
+    dT: float,
+    metric: Callable | None = None
+) -> dict[str, dict]:
+    """
+    For threshold `dT`, compute the nearest accent shades that exceed that
+    threshold for every monotone shade.
+
+    Returns: map of minimum constraint satisfying accent colors for monotone
+        spectra
+
+        {
+            "alpine": {
+                "oklch( ... )": {
+                    "red": *nearest oklch >= dT from M base*,
+                    ...
+                },
+                ...
+            },
+            ...
+        }
+    """
+
+    if metric is None:
+        metric = oklch_distance
+    
+    oklch_hlc_map = compute_hlc_map("oklch")
+    oklch_color_map = {
+        c_name: [Color(c_str) for c_str in c_str_dict.values()]
+        for c_name, c_str_dict in oklch_hlc_map.items()
+    }
+    
+    dT_mL_acol_map = {}
+    for m_name in monotone_h_map:
+        mL_acol_map = {}
+        m_colors = oklch_color_map[m_name]
+        
+        for m_color in m_colors:
+            acol_min_map = {}
+            
+            for a_name in accent_h_map:
+                a_colors = oklch_color_map[a_name]
+                oklch_dists = filter(
+                    lambda d: (d[1] - dT) >= 0,
+                    [
+                        (ac, metric(m_color, ac))
+                        for ac in a_colors
+                    ]
+                )
+                oklch_dists = list(oklch_dists)
+                if oklch_dists:
+                    min_a_color = min(oklch_dists, key=lambda t: t[1])[0]
+                    acol_min_map[a_name] = min_a_color
+    
+            # make sure the current monotone level has *all* accents; o/w
+            # ignore
+            if len(acol_min_map) < len(accent_h_map):
+                continue
+
+            mL = m_color.coords()[0]
+            mL_acol_map[int(mL*100)] = acol_min_map
+        dT_mL_acol_map[m_name] = mL_acol_map
+
+    return dT_mL_acol_map
+
+def generate_scheme_groups(
+    mode: str,
+    biome: str,
+    metric: str,
+    distance: float,
+    l_base: int,
+    l_step: int,
+    fg_gap: int,
+    grey_gap: int,
+    term_fg_gap: int,
+    accent_color_map: dict[str, str],
+) -> tuple[dict[str, str], ...]:
+    """
+    Parameters:
+        mode: one of ["dark", "light"]
+        biome: biome setting
+        metric: one of ["wcag", "oklch", "lightness"]
+    """
+
+    metric_map = {
+        "wcag": lambda mc,ac: ac.contrast(mc, method='wcag21'),
+        "oklch": oklch_distance,
+        "lightness": lambda mc,ac: abs(mc.coords()[0]-ac.coords()[0])*100,
+    }
+    
+    metric_func = metric_map[metric]
+    dT_mL_acol_map = compute_dma_map(distance, metric=metric_func)
+    Lma_map = {
+        m_name: mL_acol_dict[l_base]
+        for m_name, mL_acol_dict in dT_mL_acol_map.items()
+        if l_base in mL_acol_dict
+    }
+    
+    # the `mL_acol_dict` only includes lightnesses where all accent colors were
+    # within threshold. Coverage here will be partial if, at the `mL`, there is
+    # some monotone base that doesn't have all accents within threshold. This
+    # can happen at the edge, e.g., alpine@L15 has all accents w/in the
+    # distance, but the red accent was too far under tundra@L15, so there's no
+    # entry. This particular case is fairly rare; it's more likely that *all*
+    # monotones are undefined. Either way, both such cases lead to partial
+    # scheme coverage.
+    if len(Lma_map) < len(monotone_h_map):
+        print(f"Warning: partial scheme coverage for {l_base=}@{distance=}")
+    if biome not in Lma_map:
+        print(f"Biome {biome} unable to meet {metric} constraints")
+    accent_colors = Lma_map.get(biome, {})
+    
+    meta_pairs = [
+        ("mode", mode),
+        ("biome", biome),
+        ("metric", metric),
+        ("distance", distance),
+        ("l_base", l_base),
+        ("l_step", l_step),
+        ("fg_gap", fg_gap),
+        ("grey_gap", grey_gap),
+        ("term_fg_gap", term_fg_gap),
+    ]
+
+    # note how selection_bg steps up by `l_step`, selection_fg steps down by
+    # `l_step` (from their respective bases)
+    term_pairs = [
+        ("background", f"f{{{{{biome}.l{l_base}}}}}"),
+        ("selection_bg", f"f{{{{{biome}.l{l_base+l_step}}}}}"),
+        ("selection_fg", f"f{{{{{biome}.l{l_base+term_fg_gap-l_step}}}}}"),
+        ("foreground", f"f{{{{{biome}.l{l_base+term_fg_gap}}}}}"),
+        ("cursor", f"f{{{{{biome}.l{l_base+term_fg_gap-l_step}}}}}"),
+        ("cursor_text", f"f{{{{{biome}.l{l_base+l_step}}}}}"),
+    ]
+
+    monotone_pairs = []
+    monotone_pairs += [
+        (f"bg{i}", f"f{{{{{biome}.l{l_base+i*l_step}}}}}")
+        for i in range(4)
+    ]
+    monotone_pairs += [
+        (f"fg{3-i}", f"f{{{{{biome}.l{fg_gap+l_base+i*l_step}}}}}")
+        for i in range(4)
+    ]
+ 
+    accent_pairs = [
+        ("black", f"f{{{{{biome}.l{l_base}}}}}"),
+        ("grey", f"f{{{{{biome}.l{l_base+grey_gap}}}}}"),
+        ("white", f"f{{{{{biome}.l{l_base+term_fg_gap-2*l_step}}}}}"),
+    ]
+    for color_name, mb_accent in accent_color_map.items():
+        aL = int(100*accent_colors[mb_accent].coords()[0])
+        accent_pairs.append(
+            (
+                color_name,
+                f"f{{{{{mb_accent}.l{aL}}}}}"
+            )
+        )
+    
+    return meta_pairs, term_pairs, monotone_pairs, accent_pairs
+
+def generate_scheme(
+    mode: str,
+    biome: str,
+    metric: str,
+    distance: float,
+    l_base: int,
+    l_step: int,
+    fg_gap: int,
+    grey_gap: int,
+    term_fg_gap: int,
+    full_color_map: dict[str, str],
+    term_color_map: dict[str, str],
+    vim_color_map: dict[str, str],
+) -> str:
+    l_sys = l_base
+    l_app = l_base + l_step
+
+    term_bright_offset = 10
+
+    # negate gaps if mode is light
+    if mode == "light":
+        l_step *= -1
+        fg_gap *= -1
+        grey_gap *= -1
+        term_fg_gap *= -1
+        term_bright_offset *= -1
+
+    meta, _, mt, ac = generate_scheme_groups(
+        mode, biome, metric, distance,
+        l_sys, l_step,
+        fg_gap, grey_gap, term_fg_gap,
+        full_color_map
+    )
+
+    _, term, _, term_norm_ac = generate_scheme_groups(
+        mode, biome, metric, distance,
+        l_app, l_step,
+        fg_gap, grey_gap, term_fg_gap,
+        term_color_map
+    )
+    _, _, _, term_bright_ac = generate_scheme_groups(
+        mode, biome, metric, distance,
+        l_app + term_bright_offset, l_step,
+        fg_gap, grey_gap, term_fg_gap,
+        term_color_map
+    )
+
+    _, _, vim_mt, vim_ac = generate_scheme_groups(
+        mode, biome, metric, distance,
+        l_app, l_step,
+        fg_gap, grey_gap, term_fg_gap,
+        vim_color_map
+    )
+
+    def pair_strings(pair_list: list[tuple[str, str]]) -> list[str]:
+        return [
+            f"{lhs:<12} = \"{rhs}\""
+            for lhs, rhs in pair_list
+        ]
+
+    scheme_pairs = []
+    scheme_pairs += pair_strings(meta)
+    scheme_pairs += pair_strings(mt)
+    scheme_pairs += pair_strings(ac)
+
+    scheme_pairs += ["", "[term]"]
+    scheme_pairs += pair_strings(term)
+
+    scheme_pairs += ["", "[term.normal]"]
+    scheme_pairs += pair_strings(term_norm_ac)
+
+    scheme_pairs += ["", "[term.bright]"]
+    scheme_pairs += pair_strings(term_bright_ac)
+
+    scheme_pairs += ["", "[vim]"]
+    scheme_pairs += pair_strings(vim_mt)
+    scheme_pairs += pair_strings(vim_ac)
+
+    return "\n".join(scheme_pairs)

monobiome/util.py

@@ -0,0 +1,35 @@
+import math
+from types import GenericAlias
+from argparse import ArgumentParser, _SubParsersAction
+
+from coloraide import Color
+
+_SubParsersAction.__class_getitem__ = classmethod(GenericAlias)
+_SubparserType = _SubParsersAction[ArgumentParser]
+
+def oklch_distance(xc: Color, yc: Color) -> float:
+    """
+    Compute the distance between two colors in OKLCH space.
+
+    Note: `xc` and `yc` are presumed to be OKLCH colors already, such that
+    `.coords()` yields an `(l, c, h)` triple directly rather than first
+    requiring conversion. When we can make this assumption, we save roughly an
+    order of magnitude in runtime.
+
+    1. `xc.distance(yc, space="oklch")`: 500k evals takes ~2s
+    2. This method: 500k evals takes ~0.2s
+    """
+
+    l1, c1, h1 = xc.coords()
+    l2, c2, h2 = yc.coords()
+
+    rad1 = h1 / 180 * math.pi
+    rad2 = h2 / 180 * math.pi
+    x1, y1 = c1 * math.cos(rad1), c1 * math.sin(rad1)
+    x2, y2 = c2 * math.cos(rad2), c2 * math.sin(rad2)
+    
+    dx = x1 - x2
+    dy = y1 - y2
+    dz = l1 - l2
+    
+    return (dx**2 + dy**2 + dz**2)**0.5

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

@@ -1,11 +1,16 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"
+
 [project]
 name = "monobiome"
-version = "1.2.0"
-description = "Add your description here"
+version = "1.4.0"
+description = "Monobiome color palette"
 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",
@@ -20,3 +25,39 @@ dependencies = [
 dev = [
     "ipykernel>=7.0.1",
 ]
+
+[project.scripts]
+monobiome = "monobiome.__main__:main"
+
+[project.urls]
+Homepage = "https://doc.olog.io/monobiome"
+Documentation = "https://doc.olog.io/monobiome"
+Repository = "https://git.olog.io/olog/monobiome"
+Issues = "https://git.olog.io/olog/monobiome/issues"
+
+[tool.setuptools.packages.find]
+include = ["monobiome*"]
+
+[tool.setuptools.package-data]
+"monobiome" = ["data/*.toml"]
+
+[tool.ruff]
+line-length = 79
+
+[tool.ruff.lint]
+select = ["ANN", "E", "F", "UP", "B", "SIM", "I", "C4", "PERF"]
+
+[tool.ruff.lint.isort]
+length-sort = true
+order-by-type = false
+force-sort-within-sections = false
+
+[tool.ruff.lint.per-file-ignores]
+"tests/**" = ["S101"]
+"**/__init__.py" = ["F401"]
+
+[tool.ruff.format]
+quote-style = "double"
+indent-style = "space"
+docstring-code-format = true
+

scripts/generate.sh

@@ -1,3 +1,7 @@
+#!/usr/bin/env bash
+# note: this script is not portable; to be run in the monobiome scripts/
+# directory (notice the `rm` invocations)
+
 rm -rf app-config/*
 symconf -c templates/ generate -o app-config
 

scripts/render.sh

@@ -0,0 +1,40 @@
+#!/usr/bin/env bash
+# usage: render.sh width height [extra kitty args...]
+#   useful for reproducible screenshots of terminal/vim setups 
+
+set -euo pipefail
+w=${1:?width}; h=${2:?height}
+out=${3:?file};
+#out="kitty-$(date +%Y%m%d-%H%M%S).png"
+shift 3 || true
+
+# spawn a kitty window w/ a mark
+title="kitty-$(date +%s%N)"
+sock="$XDG_RUNTIME_DIR/kitty-$title.sock"
+kitty -o allow_remote_control=yes --listen-on "unix:$sock" --title "$title" "$@" &
+
+# create a targeted rule for the marked window and resize
+sleep 2
+swaymsg "for_window [title=\"$title\"] mark --add $title, floating enable, resize set width ${w} px height ${h} px, move position center" >/dev/null
+
+# get the spawned window geometry
+sleep 2
+geom=$(swaymsg -t get_tree | jq -r --arg t "$title" '.. | select(.name? == $t) | .rect | "\(.x),\(.y) \(.width)x\(.height)"')
+wgeom=$(swaymsg -t get_tree | jq -r --arg t "$title" '.. | select(.name? == $t) | .window_rect | "\(.x),\(.y) \(.width)x\(.height)"')
+
+read gx gy _ < <(awk -F'[ ,x]' '{print $1,$2}' <<<"$geom")
+read wx wy ww wh < <(awk -F'[ ,x]' '{print $1,$2,$3,$4}' <<<"$wgeom")
+inner_geom="$((gx+wx)),$((gy+wy)) ${ww}x${wh}"
+
+echo "+ title=$title"
+echo "+ geom=$geom"
+echo "+ out=$out"
+
+# take a screenshot
+mkdir -p "$(dirname "$out")"
+grim -g "$inner_geom" "$out"
+echo "saved: $out"
+
+# close the kitty window
+kitty @ --to "unix:$sock" close-window
+

scripts/screens.sh

@@ -0,0 +1,33 @@
+#!/usr/bin/env bash
+# usage: screens.sh prefix
+
+set -euo pipefail
+prefix=${1:-}
+
+script_dir="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+render_script="$script_dir/render.sh"
+
+#biomes=(alpine)
+#modes=(light dark)
+biomes=(alpine)
+modes=(dark)
+
+for biome in "${biomes[@]}"; do
+    for mode in "${modes[@]}"; do
+        echo "Applying $biome-$mode theme"
+        symconf config \
+            -a kitty,nvim \
+            -m "$mode" \
+            -s "default-$biome-monobiome" \
+            -T font=Berkeley
+        sleep 2
+
+        echo "Taking screenshot..."
+        "$render_script" 800 600 "images/render/$prefix-$biome-$mode.png" nvim \
+            +':highlight Cursor blend=100' \
+            +':set guicursor=n:block-Cursor' \
+            +':silent! setlocal nonumber nocursorline signcolumn=no foldcolumn=no' \
+            +':lua vim.diagnostic.config({virtual_text=false,signs=false,underline=false})' \
+            examples/class.py
+    done
+done

templates/apps/firefox/templates/none-dark.auto-manifest.json

@@ -1,6 +1,6 @@
 {
   "manifest_version": 2,
-  "version": "1.2.0",
+  "version": "f{{theme.version}}",
   "name": "monobiome-f{{theme.biome}}",
   "theme": {
     "colors": {

templates/apps/firefox/templates/none-dark.dark-manifest.json

@@ -1,6 +1,6 @@
 {
   "manifest_version": 2,
-  "version": "1.2.0",
+  "version": "f{{theme.version}}",
   "name": "monobiome-f{{theme.biome}}-dark",
   "theme": {
     "colors": {

templates/apps/firefox/templates/none-dark.light-manifest.json

@@ -1,6 +1,6 @@
 {
   "manifest_version": 2,
-  "version": "1.2.0",
+  "version": "f{{theme.version}}",
   "name": "monobiome-f{{theme.biome}}-light",
   "theme": {
     "colors": {

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)",
-    "11": "oklch(11.0% 0.0429 29.0)",
-    "12": "oklch(12.0% 0.0468 29.0)",
-    "13": "oklch(13.0% 0.0506 29.0)",
-    "14": "oklch(14.0% 0.0545 29.0)",
-    "15": "oklch(15.0% 0.0583 29.0)",
-    "16": "oklch(16.0% 0.0621 29.0)",
-    "17": "oklch(17.0% 0.0659 29.0)",
-    "18": "oklch(18.0% 0.0697 29.0)",
-    "19": "oklch(19.0% 0.0735 29.0)",
-    "20": "oklch(20.0% 0.0773 29.0)",
-    "21": "oklch(21.0% 0.0810 29.0)",
-    "22": "oklch(22.0% 0.0847 29.0)",
-    "23": "oklch(23.0% 0.0885 29.0)",
-    "24": "oklch(24.0% 0.0922 29.0)",
-    "25": "oklch(25.0% 0.0958 29.0)",
-    "26": "oklch(26.0% 0.0995 29.0)",
-    "27": "oklch(27.0% 0.1031 29.0)",
-    "28": "oklch(28.0% 0.1067 29.0)",
-    "29": "oklch(29.0% 0.1103 29.0)",
-    "30": "oklch(30.0% 0.1139 29.0)",
-    "31": "oklch(31.0% 0.1174 29.0)",
-    "32": "oklch(32.0% 0.1209 29.0)",
-    "33": "oklch(33.0% 0.1244 29.0)",
-    "34": "oklch(34.0% 0.1278 29.0)",
-    "35": "oklch(35.0% 0.1312 29.0)",
-    "36": "oklch(36.0% 0.1346 29.0)",
-    "37": "oklch(37.0% 0.1378 29.0)",
-    "38": "oklch(38.0% 0.1411 29.0)",
-    "39": "oklch(39.0% 0.1443 29.0)",
-    "40": "oklch(40.0% 0.1474 29.0)",
-    "41": "oklch(41.0% 0.1505 29.0)",
-    "42": "oklch(42.0% 0.1535 29.0)",
-    "43": "oklch(43.0% 0.1564 29.0)",
-    "44": "oklch(44.0% 0.1592 29.0)",
-    "45": "oklch(45.0% 0.1619 29.0)",
-    "46": "oklch(46.0% 0.1645 29.0)",
-    "47": "oklch(47.0% 0.1670 29.0)",
-    "48": "oklch(48.0% 0.1694 29.0)",
-    "49": "oklch(49.0% 0.1716 29.0)",
-    "50": "oklch(50.0% 0.1737 29.0)",
-    "51": "oklch(51.0% 0.1756 29.0)",
-    "52": "oklch(52.0% 0.1774 29.0)",
-    "53": "oklch(53.0% 0.1789 29.0)",
-    "54": "oklch(54.0% 0.1802 29.0)",
-    "55": "oklch(55.0% 0.1813 29.0)",
-    "56": "oklch(56.0% 0.1821 29.0)",
-    "57": "oklch(57.0% 0.1827 29.0)",
-    "58": "oklch(58.0% 0.1829 29.0)",
-    "59": "oklch(59.0% 0.1829 29.0)",
-    "60": "oklch(60.0% 0.1825 29.0)",
-    "61": "oklch(61.0% 0.1819 29.0)",
-    "62": "oklch(62.0% 0.1809 29.0)",
-    "63": "oklch(63.0% 0.1795 29.0)",
-    "64": "oklch(64.0% 0.1778 29.0)",
+    "10": "oklch(10.0% 0.0406 29.0)",
+    "11": "oklch(11.0% 0.0446 29.0)",
+    "12": "oklch(12.0% 0.0486 29.0)",
+    "13": "oklch(13.0% 0.0526 29.0)",
+    "14": "oklch(14.0% 0.0566 29.0)",
+    "15": "oklch(15.0% 0.0606 29.0)",
+    "16": "oklch(16.0% 0.0645 29.0)",
+    "17": "oklch(17.0% 0.0685 29.0)",
+    "18": "oklch(18.0% 0.0724 29.0)",
+    "19": "oklch(19.0% 0.0763 29.0)",
+    "20": "oklch(20.0% 0.0802 29.0)",
+    "21": "oklch(21.0% 0.0841 29.0)",
+    "22": "oklch(22.0% 0.0879 29.0)",
+    "23": "oklch(23.0% 0.0918 29.0)",
+    "24": "oklch(24.0% 0.0956 29.0)",
+    "25": "oklch(25.0% 0.0994 29.0)",
+    "26": "oklch(26.0% 0.1031 29.0)",
+    "27": "oklch(27.0% 0.1068 29.0)",
+    "28": "oklch(28.0% 0.1106 29.0)",
+    "29": "oklch(29.0% 0.1142 29.0)",
+    "30": "oklch(30.0% 0.1179 29.0)",
+    "31": "oklch(31.0% 0.1215 29.0)",
+    "32": "oklch(32.0% 0.1250 29.0)",
+    "33": "oklch(33.0% 0.1286 29.0)",
+    "34": "oklch(34.0% 0.1320 29.0)",
+    "35": "oklch(35.0% 0.1355 29.0)",
+    "36": "oklch(36.0% 0.1389 29.0)",
+    "37": "oklch(37.0% 0.1422 29.0)",
+    "38": "oklch(38.0% 0.1454 29.0)",
+    "39": "oklch(39.0% 0.1486 29.0)",
+    "40": "oklch(40.0% 0.1517 29.0)",
+    "41": "oklch(41.0% 0.1548 29.0)",
+    "42": "oklch(42.0% 0.1577 29.0)",
+    "43": "oklch(43.0% 0.1606 29.0)",
+    "44": "oklch(44.0% 0.1634 29.0)",
+    "45": "oklch(45.0% 0.1660 29.0)",
+    "46": "oklch(46.0% 0.1685 29.0)",
+    "47": "oklch(47.0% 0.1709 29.0)",
+    "48": "oklch(48.0% 0.1732 29.0)",
+    "49": "oklch(49.0% 0.1752 29.0)",
+    "50": "oklch(50.0% 0.1772 29.0)",
+    "51": "oklch(51.0% 0.1789 29.0)",
+    "52": "oklch(52.0% 0.1804 29.0)",
+    "53": "oklch(53.0% 0.1817 29.0)",
+    "54": "oklch(54.0% 0.1828 29.0)",
+    "55": "oklch(55.0% 0.1836 29.0)",
+    "56": "oklch(56.0% 0.1842 29.0)",
+    "57": "oklch(57.0% 0.1845 29.0)",
+    "58": "oklch(58.0% 0.1845 29.0)",
+    "59": "oklch(59.0% 0.1842 29.0)",
+    "60": "oklch(60.0% 0.1836 29.0)",
+    "61": "oklch(61.0% 0.1826 29.0)",
+    "62": "oklch(62.0% 0.1814 29.0)",
+    "63": "oklch(63.0% 0.1799 29.0)",
+    "64": "oklch(64.0% 0.1780 29.0)",
     "65": "oklch(65.0% 0.1758 29.0)",
-    "66": "oklch(66.0% 0.1735 29.0)",
-    "67": "oklch(67.0% 0.1709 29.0)",
-    "68": "oklch(68.0% 0.1680 29.0)",
-    "69": "oklch(69.0% 0.1648 29.0)",
-    "70": "oklch(70.0% 0.1613 29.0)",
-    "71": "oklch(71.0% 0.1576 29.0)",
-    "72": "oklch(72.0% 0.1537 29.0)",
-    "73": "oklch(73.0% 0.1496 29.0)",
-    "74": "oklch(74.0% 0.1453 29.0)",
-    "75": "oklch(75.0% 0.1408 29.0)",
-    "76": "oklch(76.0% 0.1361 29.0)",
-    "77": "oklch(77.0% 0.1313 29.0)",
-    "78": "oklch(78.0% 0.1264 29.0)",
-    "79": "oklch(79.0% 0.1213 29.0)",
+    "66": "oklch(66.0% 0.1734 29.0)",
+    "67": "oklch(67.0% 0.1706 29.0)",
+    "68": "oklch(68.0% 0.1676 29.0)",
+    "69": "oklch(69.0% 0.1643 29.0)",
+    "70": "oklch(70.0% 0.1608 29.0)",
+    "71": "oklch(71.0% 0.1571 29.0)",
+    "72": "oklch(72.0% 0.1531 29.0)",
+    "73": "oklch(73.0% 0.1490 29.0)",
+    "74": "oklch(74.0% 0.1447 29.0)",
+    "75": "oklch(75.0% 0.1402 29.0)",
+    "76": "oklch(76.0% 0.1355 29.0)",
+    "77": "oklch(77.0% 0.1308 29.0)",
+    "78": "oklch(78.0% 0.1259 29.0)",
+    "79": "oklch(79.0% 0.1208 29.0)",
     "80": "oklch(80.0% 0.1147 29.0)",
     "81": "oklch(81.0% 0.1079 29.0)",
     "82": "oklch(82.0% 0.1012 29.0)",
@@ -637,351 +637,351 @@
     "98": "oklch(98.0% 0.0097 29.0)"
   },
   "orange": {
-    "10": "oklch(10.0% 0.0213 62.5)",
-    "11": "oklch(11.0% 0.0234 62.5)",
+    "10": "oklch(10.0% 0.0214 62.5)",
+    "11": "oklch(11.0% 0.0235 62.5)",
     "12": "oklch(12.0% 0.0256 62.5)",
-    "13": "oklch(13.0% 0.0277 62.5)",
-    "14": "oklch(14.0% 0.0298 62.5)",
-    "15": "oklch(15.0% 0.0319 62.5)",
-    "16": "oklch(16.0% 0.0340 62.5)",
-    "17": "oklch(17.0% 0.0361 62.5)",
-    "18": "oklch(18.0% 0.0382 62.5)",
-    "19": "oklch(19.0% 0.0403 62.5)",
-    "20": "oklch(20.0% 0.0424 62.5)",
-    "21": "oklch(21.0% 0.0445 62.5)",
-    "22": "oklch(22.0% 0.0465 62.5)",
-    "23": "oklch(23.0% 0.0486 62.5)",
-    "24": "oklch(24.0% 0.0507 62.5)",
-    "25": "oklch(25.0% 0.0527 62.5)",
-    "26": "oklch(26.0% 0.0548 62.5)",
-    "27": "oklch(27.0% 0.0569 62.5)",
-    "28": "oklch(28.0% 0.0589 62.5)",
-    "29": "oklch(29.0% 0.0609 62.5)",
-    "30": "oklch(30.0% 0.0630 62.5)",
-    "31": "oklch(31.0% 0.0650 62.5)",
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templates/groups/palette/monobiome.toml

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

templates/groups/theme/default-alpine-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "alpine"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-alpine-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "alpine"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-badlands-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "badlands"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-badlands-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "badlands"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-chaparral-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "chaparral"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-chaparral-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "chaparral"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-grassland-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "grassland"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-grassland-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "grassland"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-savanna-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "savanna"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-savanna-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "savanna"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-tundra-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "tundra"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/default-tundra-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "tundra"
 contrast     = "default"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-alpine-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "alpine"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-alpine-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "alpine"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-badlands-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "badlands"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-badlands-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "badlands"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-chaparral-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "chaparral"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-chaparral-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "chaparral"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-grassland-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "grassland"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-grassland-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "grassland"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-savanna-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "savanna"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-savanna-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "savanna"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-tundra-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "tundra"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/hard-tundra-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "tundra"
 contrast     = "hard"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-alpine-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "alpine"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-alpine-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "alpine"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-badlands-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "badlands"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-badlands-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "badlands"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-chaparral-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "chaparral"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-chaparral-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "chaparral"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-grassland-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "grassland"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-grassland-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "grassland"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-savanna-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "savanna"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-savanna-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "savanna"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-tundra-monobiome-dark.toml

@@ -11,6 +11,7 @@
 mode         = "dark"
 biome        = "tundra"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

templates/groups/theme/soft-tundra-monobiome-light.toml

@@ -11,6 +11,7 @@
 mode         = "light"
 biome        = "tundra"
 contrast     = "soft"
+version      = "f{{version}}"
 # --------------------------------------------
 
 # - SYS --------------------------------------

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"
-source = { virtual = "." }
+version = "1.4.0"
+source = { editable = "." }
 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" },