Using Presets

Palettize includes hundreds of colormap presets via the cmap library, plus custom built-in presets.

Listing Presets

See all available presets:

palettize list presets

Or in Python:

from palettize import list_available_presets

presets = list_available_presets()
print(f"Found {len(presets)} presets")
print(presets[:10])  # First 10

Using Presets

CLI

# Preview a preset
palettize show viridis

# Export a preset
palettize create viridis --format gdal --output viridis.txt --domain 0,255

Python

from palettize import create_colormap

# From preset
cmap = create_colormap(preset="viridis")

# Get colors
print(cmap.get_color(0))    # Start color
print(cmap.get_color(0.5))  # Middle
print(cmap.get_color(1))    # End color

Preset Categories

Scientific/Perceptually Uniform

These colormaps are designed for accurate data representation:

Preset	Type	Use Case
viridis	Sequential	General purpose, colorblind-safe
magma	Sequential	Dark backgrounds
inferno	Sequential	High contrast
plasma	Sequential	Good for heatmaps
cividis	Sequential	Colorblind-optimized

palettize show viridis
palettize show magma
palettize show inferno

Diverging

For data with a meaningful center point:

Preset	Use Case
RdBu	Red-Blue, good for temperature
RdYlBu	Red-Yellow-Blue
BrBG	Brown-Green, good for terrain
PiYG	Pink-Green
PRGn	Purple-Green

palettize show RdBu
palettize show BrBG

Sequential

For data with a natural ordering:

Preset	Character
Blues	Light to dark blue
Greens	Light to dark green
Reds	Light to dark red
YlOrRd	Yellow-Orange-Red
YlGnBu	Yellow-Green-Blue

palettize show Blues
palettize show YlOrRd

Categorical/Qualitative

For discrete categories (use carefully with continuous data):

Preset	Colors
Set1	Bold, distinct
Set2	Muted, distinct
Paired	Paired colors
tab10	Tableau 10

palettize show Set1
palettize show tab10

Custom Built-in Presets

Palettize includes some custom presets prefixed with custom/:

palettize show custom/grayscale
palettize show custom/simple_rgb

Modifying Presets

Cut (Sub-segment)

Use only part of a preset:

# Skip the dark ends of viridis
palettize show viridis --cut "0.1,0.9"

# Use only the first half
palettize show viridis --cut "0,0.5"

Change Interpolation Space

Override the interpolation:

# Use sRGB instead of default oklch
palettize show viridis --space srgb

Rename

Give a custom name:

palettize create viridis --format gdal --output elev.txt \
  --name "Elevation" --domain 0,4000

Loading Preset Data

Get raw preset data programmatically:

from palettize import load_preset_data

# Returns list of color stops
data = load_preset_data("viridis")
print(data[:3])  # First 3 stops

Finding the Right Preset

By Use Case

Visualization	Recommended Presets
Elevation/terrain	terrain, BrBG, YlGnBu
Temperature	RdBu, coolwarm, RdYlBu
Heatmaps	viridis, magma, inferno
Ocean depth	Blues, deep, ocean
Vegetation/NDVI	Greens, YlGn, BuGn
Population density	YlOrRd, Reds, OrRd
Categorical data	Set1, tab10, Paired

By Characteristic

Need	Presets
Colorblind-safe	viridis, cividis, magma
Print-friendly	viridis, gray, bone
Perceptually uniform	viridis, magma, inferno, plasma
High contrast	inferno, hot, jet
Dark background	magma, inferno
Light background	viridis, plasma

The cmap Library

Most presets come from the cmap library, which aggregates colormaps from:

• Matplotlib
• Bokeh
• Plotly
• Seaborn
• Scientific journals
• And more

Browse the full catalog in their documentation to discover more options.

Creating Custom Presets

If you frequently use the same colors, create them directly:

# Define custom colors
palettize show --colors "navy,white,darkred" --name "MyDiverging"

# Or in Python
from palettize import create_colormap

my_cmap = create_colormap(
    colors=["#001f3f", "#ffffff", "#85144b"],
    name="NavyWhiteMaroon"
)

For reusable custom presets, consider creating a custom exporter plugin or simply save your preferred color lists.