Colormap presets#

Purpose and concepts#

cmap is an immutable named colormap; palette returns a color list for loops or plot_style. Presets use Matplotlib 3.11.2 native LUTs without a runtime Matplotlib dependency.

Minimal complete example#

Run this file directly with laymesh validate or laymesh render; it contains its own canvas and required definitions.

1# Preset discovery, sampling, colors and immutable reversal.2page=canvas(size=(100mm,60mm),background="#ffffff")3cm=cmap("viridis")4names=cmap_names(category="sequential")5colors=cm.colors(8)6reverse=cm.reversed()7accent=cm.sample(0.5)8cycle=palette("tab10",8)9for i,color in enumerate(colors) {10 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))11 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))12 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))13}

# Preset discovery, sampling, colors and immutable reversal.
page=canvas(size=(100mm,60mm),background="#ffffff")
cm=cmap("viridis")
names=cmap_names(category="sequential")
colors=cm.colors(8)
reverse=cm.reversed()
accent=cm.sample(0.5)
cycle=palette("tab10",8)
for i,color in enumerate(colors) {
 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))
 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))
 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))
}

1# Preset discovery, sampling, colors and immutable reversal.2page=canvas(size=(100mm,60mm),background="#ffffff")3cm=cmap("viridis")4names=cmap_names(category="sequential")5colors=cm.colors(8)6reverse=cm.reversed()7accent=cm.sample(0.5)8cycle=palette("tab10",8)9for i,color in enumerate(colors) {10 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))11 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))12 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))13}

# Preset discovery, sampling, colors and immutable reversal.
page=canvas(size=(100mm,60mm),background="#ffffff")
cm=cmap("viridis")
names=cmap_names(category="sequential")
colors=cm.colors(8)
reverse=cm.reversed()
accent=cm.sample(0.5)
cycle=palette("tab10",8)
for i,color in enumerate(colors) {
 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))
 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))
 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))
}

Dependencies

examples/manual/cmaps.lay

Parameters and default behavior#

Unitless geometry uses the canvas unit; unitless type and stroke sizes use pt. Explicit call parameters override inherited/theme defaults. The linked interface reference lists accepted types, choices and defaults per parameter.

Composition#

Iterate over cmap_names() to explore every preset. Categorical colors retain native order, sequential maps sample evenly and cyclic maps omit the repeated endpoint. Shared color_scale keeps layers and colorbars consistent.

1# Preset discovery, sampling, colors and immutable reversal.2page=canvas(size=(100mm,60mm),background="#ffffff")3cm=cmap("viridis")4names=cmap_names(category="sequential")5colors=cm.colors(8)6reverse=cm.reversed()7accent=cm.sample(0.5)8cycle=palette("tab10",8)9for i,color in enumerate(colors) {10 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))11 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))12 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))13}

# Preset discovery, sampling, colors and immutable reversal.
page=canvas(size=(100mm,60mm),background="#ffffff")
cm=cmap("viridis")
names=cmap_names(category="sequential")
colors=cm.colors(8)
reverse=cm.reversed()
accent=cm.sample(0.5)
cycle=palette("tab10",8)
for i,color in enumerate(colors) {
 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))
 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))
 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))
}

1# Preset discovery, sampling, colors and immutable reversal.2page=canvas(size=(100mm,60mm),background="#ffffff")3cm=cmap("viridis")4names=cmap_names(category="sequential")5colors=cm.colors(8)6reverse=cm.reversed()7accent=cm.sample(0.5)8cycle=palette("tab10",8)9for i,color in enumerate(colors) {10 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))11 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))12 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))13}

# Preset discovery, sampling, colors and immutable reversal.
page=canvas(size=(100mm,60mm),background="#ffffff")
cm=cmap("viridis")
names=cmap_names(category="sequential")
colors=cm.colors(8)
reverse=cm.reversed()
accent=cm.sample(0.5)
cycle=palette("tab10",8)
for i,color in enumerate(colors) {
 page.add(rect(size=(10mm,12mm),fill=color),offset=(10mm+i*10mm,8mm))
 page.add(rect(size=(10mm,12mm),fill=reverse.sample(i/7)),offset=(10mm+i*10mm,24mm))
 page.add(rect(size=(10mm,8mm),fill=cycle[i]),offset=(10mm+i*10mm,40mm))
}

Dependencies

examples/manual/cmaps.lay

Common errors and limits#

Names are case-sensitive and support native aliases and _r; rdbu aliases RdBu. n is an integer from 0 to 10,000; t must be finite and is clamped outside the domain. Existing names now use Matplotlib colors, changing some previous output.

Individual functions#

cmap#

Get an immutable named Matplotlib 3.11.2 colormap for sampling, palette lists and reversal.

Returns: cmap

Minimal complete source · Composition source · All parameters

cmap_names#

List canonical colormap names, optionally filtered by category and including reversed names; aliases are omitted.

Returns: list

Minimal complete source · Composition source · All parameters

palette#

Create a palette: categorical colors cycle in native order, sequential colors sample evenly, and cyclic maps omit the repeated endpoint.

Returns: list

Minimal complete source · Composition source · All parameters

cmap-sample#

Sample a finite normalized position, clamping values outside zero to one.

Returns: color

Required inputs: t.

Minimal complete source · Composition source · All parameters

cmap-colors#

Return a palette with native size by default; categorical colors cycle, sequential maps sample evenly and cyclic maps omit the repeated endpoint.

Returns: list

Minimal complete source · Composition source · All parameters

cmap-reversed#

Return a reversed colormap using Matplotlib native reversed lookup tables.

Returns: cmap

Minimal complete source · Composition source · All parameters

Detailed behavior and further examples#

Names are case-sensitive. Native Matplotlib aliases and _r names are accepted; rdbu aliases RdBu. cmap_names() lists 87 canonical presets; reversed=true lists 174 canonical names. All registered upstream aliases remain usable.

cmap("viridis") returns an immutable handle; .sample(t) clamps finite positions to 0–1, .colors(n) returns typed colors, and .reversed() creates an independent reversed handle. palette("tab10") is a shortcut for cmap("tab10").colors().

Sequential and diverging palettes use evenly spaced positions, with one sample at the midpoint. Cyclic palettes sample [0, 1) to avoid a repeated endpoint. Qualitative palettes select original colors in order and wrap when n exceeds their size. Omitted/null n uses the native LUT size; n=0 is empty, and integers outside 0–10,000 are rejected.

1cm = cmap("coolwarm")2scale = color_scale(norm="centered", vmin=-2, vmax=2, center=0, cmap=cm)3style = plot_style(colors=palette("tab10"))

cm = cmap("coolwarm")
scale = color_scale(norm="centered", vmin=-2, vmax=2, center=0, cmap=cm)
style = plot_style(colors=palette("tab10"))

The same color_scale can be shared by heatmap, contourf, numeric scatter and colorbar. Custom color lists retain RGB/alpha interpolation. Explicit layer colors override the style cycle.

Dictionary series · Shared scale · Full catalogue

Preset catalogue#

Category	Presets
`sequential`	`magma`, `inferno`, `plasma`, `viridis`, `cividis`, `Blues`, `BuGn`, `BuPu`, `GnBu`, `Greens`, `Greys`, `OrRd`, `Oranges`, `PuBu`, `PuBuGn`, `PuRd`, `Purples`, `RdPu`, `Reds`, `Wistia`, `YlGn`, `YlGnBu`, `YlOrBr`, `YlOrRd`, `afmhot`, `autumn`, `bone`, `cool`, `copper`, `gist_heat`, `gray`, `hot`, `pink`, `spring`, `summer`, `winter`
`diverging`	`berlin`, `managua`, `vanimo`, `BrBG`, `PRGn`, `PiYG`, `PuOr`, `RdBu`, `RdGy`, `RdYlBu`, `RdYlGn`, `Spectral`, `bwr`, `coolwarm`, `seismic`
`cyclic`	`twilight`, `twilight_shifted`, `hsv`
`qualitative`	`Accent`, `okabe_ito`, `Dark2`, `Paired`, `Pastel1`, `Pastel2`, `Set1`, `Set2`, `Set3`, `tab10`, `tab20`, `tab20b`, `tab20c`
`misc`	`turbo`, `CMRmap`, `binary`, `brg`, `cubehelix`, `flag`, `gist_earth`, `gist_gray`, `gist_ncar`, `gist_rainbow`, `gist_stern`, `gist_yarg`, `gnuplot`, `gnuplot2`, `jet`, `nipy_spectral`, `ocean`, `prism`, `rainbow`, `terrain`

Compatibility and reproduction#

Colors now follow Matplotlib 3.11.2, including native reversed LUTs and 8-bit RGB quantization. Older cividis/RdBu output can change. Data and source hashes are committed; ordinary native/WASM builds do not require Python or Matplotlib. To regenerate or verify, install the optional release/cmap-requirements.txt and run python scripts/build-cmaps.py or append --check. Source attribution and the Matplotlib license are included in release notices.