Colors

The colors module provides one color vocabulary for Matplotlib plots, geographic layers, and LaTeX output. GerryTools accepts ordinary Matplotlib colors and adds named palettes, deterministic district colors, xcolor-style mixtures, and palette preview helpers.

Most plotting methods accept any of these forms directly:

• a Matplotlib name such as "steelblue";

• a LaTeX Colors name such as "denim";

• a GerryTools name such as "ensemble:forest";

• a hex string such as "#0064bd"; or

• an RGB or RGBA tuple.

That means a named color can move from TeX to Python without maintaining a separate set of hex values. The LaTeX module of GerryTools also maintains the reverse compatibility through this color module so it remains simple to copy-paste output from GerryTools into active TeX documents.

Resolve a named color

from gerrytools.colors import get_named_color

get_named_color("cc:denim")

The cc: names form a compact color-corrected set. The ensemble: names provide stable colors for the supported ensemble methods, while the unprefixed registry also includes the Districtr, LaTeX, and Matplotlib named colors.

Some names occur in more than one source. which_color_source() reports which definition wins, and get_all_supported_colors_dict() returns the complete resolved mapping.

from gerrytools.colors import which_color_source

which_color_source("salmon")

convert_color_to_hexa_or_none() normalizes any supported input to an eight-digit hex value. It also understands xcolor-style mixtures. For example, "cc:denim!70!white" mixes 70 percent denim with 30 percent white.

Create a district palette

from gerrytools.colors import districtr

district_colors = districtr(8)

districtr(n) returns exactly n colors in a stable order, making district assignments visually consistent across related maps. For a plan whose labels are not consecutive integers, build an explicit label-to-color mapping rather than using the labels as list positions.

district_labels = ["A", "B", "C", "D"]
district_color = dict(zip(district_labels, districtr(len(district_labels))))

Sequential and diverging palettes

Use a sequential palette when magnitude increases in one direction. greens(), purples(), and flare() return a requested number of ordered colors. Use redbluecmap() or greenpurplecmap() when values diverge around a meaningful midpoint.

from gerrytools.colors import greenpurplecmap, purples

population_colors = purples(5)
deviation_colors = greenpurplecmap(7)

Preview palettes

from gerrytools.colors import compare_palettes, greenpurplecmap, redbluecmap

compare_palettes(
    {
        "red-blue": redbluecmap(7),
        "green-purple": greenpurplecmap(7),
    }
)

preview_palette() displays one sequence. compare_palettes() aligns several sequences in rows, which is useful when choosing a palette or checking that related figures use compatible colors. Both functions return their Matplotlib figure and axes, so the preview can be embedded or saved like any other figure.

The colors API lists the named-color dictionaries, sequential palettes, resolution helpers, and preview options.