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clean up plotting method signatures

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This commit is contained in:
smgr
2026-01-16 16:34:00 -08:00
parent 99ed1c9557
commit a5256aaa62
3 changed files with 8 additions and 27 deletions
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images/release/1.5.1/palette.png
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29
monobiome/plotting.py
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@@ -72,12 +72,11 @@ def plot_hue_chroma_bounds() -> tuple[plt.Figure, plt.Axes]:
return fig, axes return fig, axes
def plot_hue_chroma_star() -> tuple[plt.Figure, plt.Axes]: def plot_hue_chroma_star() -> tuple[plt.Figure, plt.Axes]:
fig, ax = plt.subplots(1, 1, figsize=(8, 6)) fig, ax = plt.subplots(1, 1, figsize=(8, 6))
# uncomment to preview 5 core term colors
colors = accent_h_map.keys() colors = accent_h_map.keys()
# uncomment to preview just the 5 core term colors
# colors = set(["red", "orange", "yellow", "green", "blue"]) # colors = set(["red", "orange", "yellow", "green", "blue"])
for h_str, _ in max_Cstar_Horder: for h_str, _ in max_Cstar_Horder:
@@ -92,30 +91,16 @@ def plot_hue_chroma_star() -> tuple[plt.Figure, plt.Axes]:
for _l, _c in zip(L_points, Lpoints_Cstar, strict=True) for _l, _c in zip(L_points, Lpoints_Cstar, strict=True)
] ]
# # ax.fill_between(
# ax.scatter(
# L_points,
# Lpoints_Cstar,
# alpha=0.7,
# c=h_colors,
# #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')
x = np.asarray(L_points) x = np.asarray(L_points)
y = np.asarray(Lpoints_Cstar) y = np.asarray(Lpoints_Cstar)
pts = np.column_stack([x, y]).reshape(-1, 1, 2) pts = np.column_stack([x, y]).reshape(-1, 1, 2)
segs = np.concatenate([pts[:-1], pts[1:]], axis=1) segs = np.concatenate([pts[:-1], pts[1:]], axis=1)
rgb = np.asarray(h_colors) rgb = np.asarray(h_colors)
seg_colors = (rgb[:-1] + rgb[1:]) / 2 seg_colors = (rgb[:-1] + rgb[1:]) / 2
lc = LineCollection(segs, colors=seg_colors, linewidth=3, lc = LineCollection(segs, colors=seg_colors, linewidth=3,
capstyle="round", joinstyle="round", capstyle="round", joinstyle="round",
label=h_str) label=h_str)
ax.add_collection(lc) ax.add_collection(lc)
ax.autoscale_view() ax.autoscale_view()
@@ -126,12 +111,11 @@ def plot_hue_chroma_star() -> tuple[plt.Figure, plt.Axes]:
return fig, ax return fig, ax
def palette_image( def palette_image(
palette: dict[str, dict[int, str]], palette: dict[str, dict[int, str]],
cell_size: int = 40, cell_size: int = 40,
keys: list[str] | None = None keys: list[str] | None = None
) -> tuple[np.ndarray, list[str], list[list[int]], int, int]: ) -> tuple[np.ndarray, list[str], list[list[int]]]:
names = list(palette.keys()) if keys is None else keys names = list(palette.keys()) if keys is None else keys
row_count = len(names) row_count = len(names)
@@ -155,8 +139,7 @@ def palette_image(
c0, c1 = c * cell_size, (c + 1) * cell_size c0, c1 = c * cell_size, (c + 1) * cell_size
img[r0:r1, c0:c1, :] = rgb img[r0:r1, c0:c1, :] = rgb
return img, names, lightness_keys_per_row, cell_size, max_cols return img, names, lightness_keys_per_row
def show_palette( def show_palette(
palette: dict[str, dict[int, str]], palette: dict[str, dict[int, str]],
@@ -165,9 +148,7 @@ def show_palette(
show_labels: bool = True, show_labels: bool = True,
dpi: int = 100, dpi: int = 100,
) -> tuple[plt.Figure, plt.Axes]: ) -> tuple[plt.Figure, plt.Axes]:
img, names, keys, cell_size, max_cols = palette_image( img, names, _ = palette_image(palette, cell_size, keys=keys)
palette, cell_size, keys=keys
)
fig_w = img.shape[1] / 100 fig_w = img.shape[1] / 100
fig_h = img.shape[0] / 100 fig_h = img.shape[0] / 100

4
scripts/plots.py
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@@ -17,8 +17,8 @@ fig.savefig(Path(figure_dir, "chroma-curves.png"))
# "oklch" causes some slight hex drift when later using an eyedropper # "oklch" causes some slight hex drift when later using an eyedropper
hlc_map = compute_hlc_map("hex") # ("oklch") hlc_map = compute_hlc_map("hex") # ("oklch")
fig, ax = plotting.show_palette(hlc_map) fig, ax = plotting.show_palette(hlc_map, cell_size=25)
fig.savefig(Path(figure_dir, "palette.png")) fig.savefig(Path(figure_dir, "palette.png"), pad_inches=0)
fig, ax = plotting.show_palette(hlc_map, show_labels=False) fig, ax = plotting.show_palette(hlc_map, show_labels=False)
fig.savefig(Path(figure_dir, "palette-bare.png"), pad_inches=0) fig.savefig(Path(figure_dir, "palette-bare.png"), pad_inches=0)