Customization

Themes

GlyphX ships seven built-in themes. Pass the name as a string:

from glyphx import Figure

Figure(theme="dark")
Figure(theme="colorblind")   # Okabe-Ito palette — safe for all types
Figure(theme="warm")
Figure(theme="ocean")
Figure(theme="pastel")
Figure(theme="monochrome")
Figure(theme="default")      # clean white (default)

Built-in Themes

Name	Background	Color Palette
default	White	Tableau-style
dark	Charcoal (#1e1e1e)	Muted blues and ambers
colorblind	White	Okabe-Ito — safe for deuteranopia, protanopia, tritanopia
pastel	Off-white (#f9f9f9)	Soft muted tones
warm	Cream (#fff8f0)	Earthy reds and greens, Georgia serif font
ocean	Light blue (#f0f8ff)	Deep blues and teals
monochrome	White	Greys only — print-safe

Note

The colorblind theme uses the Okabe-Ito palette, the scientific standard for colorblind-accessible data visualization. Earlier versions used grayscale incorrectly — this was fixed in v1.5.0.

Custom Themes

Pass a dict with any subset of theme keys:

my_theme = {
    "colors":      ["#ff6b6b", "#4ecdc4", "#45b7d1", "#96ceb4"],
    "background":  "#1a1a2e",
    "text_color":  "#eeeeee",
    "axis_color":  "#555",
    "grid_color":  "#333",
    "font":        "Roboto, sans-serif",
}

Figure(theme=my_theme)

Colors and Line Styles

Pass color and linestyle directly to any series:

from glyphx.series import LineSeries

LineSeries(x, y, color="#16a34a", linestyle="solid",    width=2.5)
LineSeries(x, y, color="#2563eb", linestyle="dashed",   width=2.5)
LineSeries(x, y, color="#dc2626", linestyle="dotted",   width=2.5)
LineSeries(x, y, color="#d97706", linestyle="longdash", width=2.5)

Available linestyle values: "solid", "dashed", "dotted", "longdash"

Colormaps

Nine perceptually-uniform colormaps are built in:

Name	Type	Best for
viridis	Sequential	Default continuous encoding
plasma	Sequential	High-contrast continuous data
inferno	Sequential	Print-safe on dark backgrounds
magma	Sequential	Heatmaps and density plots
cividis	Sequential	Deuteranopia-safe alternative to viridis
coolwarm	Diverging	Correlation matrices, positive/negative
rdbu	Diverging	Two-sided data centered at zero
spectral	Multi-hue	Categorical ranges (use sparingly)
greys	Sequential	Monochrome / print output

from glyphx.colormaps import apply_colormap, colormap_colors, list_colormaps
from glyphx.series import ScatterSeries

# Single value → hex color
color = apply_colormap(0.75, "plasma")

# N evenly-spaced colors
colors = colormap_colors("viridis", 6)

# Color-encode scatter points by a third variable
ScatterSeries(x, y, c=z_values, cmap="plasma", size=8)

Annotations

Add text callouts in data-space coordinates:

fig.annotate(
    "Record High",
    x=11, y=2.9,
    arrow=True,
    color="#dc2626",
    font_size=12,
)

Statistical Significance Brackets

fig = (
    Figure()
    .add(BarSeries(["Control","Drug A","Drug B"], means, yerr=errors))
    .add_stat_annotation("Control", "Drug A", p_value=0.0003)
    .add_stat_annotation("Control", "Drug B", p_value=0.031, y_offset=30)
)

Grid Layouts

Subplot grid on a single Figure:

fig = Figure(rows=2, cols=2, width=1000, height=700)
fig.add_axes(0, 0).add_series(LineSeries([1,2,3], [4,5,6]))
fig.add_axes(0, 1).add_series(BarSeries(["A","B","C"], [5,3,7]))
fig.add_axes(1, 0).add_series(ScatterSeries([1,2,3], [4,5,6]))
fig.add_axes(1, 1).add_series(HistogramSeries(data, bins=15))
fig.show()

Multiple Figures on one HTML page:

from glyphx.layout import grid

html = grid([f1, f2, f3], rows=1, cols=3)
open("dashboard.html", "w").write(html)

Tight Layout

fig = (
    Figure()
    .add(BarSeries(long_category_names, values))
    .tight_layout()
)