A ternary plot displays three-component compositional data on an equilateral triangle where each vertex represents 100% of one component. Points inside the triangle show compositions that sum to a constant total (usually 100%), with position indicating relative proportions. This visualization is essential for data where three variables are interdependent and constrained to sum to a fixed value.
""" anyplot.ai
ternary-basic: Basic Ternary Plot
Library: plotly 6.7.0 | Python 3.13.13
Quality: 92/100 | Updated: 2026-05-06
"""
import os
import numpy as np
import plotly.graph_objects as go
# Theme tokens (see prompts/default-style-guide.md "Theme-adaptive Chrome")
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
GRID = "rgba(26,26,23,0.10)" if THEME == "light" else "rgba(240,239,232,0.10)"
# Okabe-Ito palette (first series is always #009E73)
IMPRINT = [
"#009E73", # bluish green (brand — primary)
"#C475FD", # vermillion (secondary)
"#4467A3", # blue (tertiary)
"#BD8233", # reddish purple (quaternary)
]
# Data: Soil composition samples with meaningful clustering by soil type
np.random.seed(42)
# Generate clustered data representing distinct soil types
sandy_soils = np.array(
[
[75, 15, 10],
[70, 20, 10],
[80, 12, 8],
[76, 14, 10],
[78, 16, 6],
[72, 18, 10],
[77, 15, 8],
[74, 19, 7],
[81, 13, 6],
[75, 17, 8],
]
)
silty_soils = np.array(
[
[35, 55, 10],
[30, 60, 10],
[32, 58, 10],
[28, 62, 10],
[38, 52, 10],
[33, 57, 10],
[31, 59, 10],
[36, 54, 10],
[29, 61, 10],
[34, 56, 10],
]
)
clayey_soils = np.array(
[
[20, 20, 60],
[15, 25, 60],
[18, 22, 60],
[22, 18, 60],
[16, 24, 60],
[19, 21, 60],
[21, 19, 60],
[17, 23, 60],
[20, 22, 58],
[18, 24, 58],
]
)
loam_soils = np.array(
[
[40, 40, 20],
[42, 38, 20],
[38, 42, 20],
[41, 39, 20],
[43, 37, 20],
[39, 41, 20],
[40, 38, 22],
[42, 40, 18],
[41, 41, 18],
[39, 39, 22],
]
)
# Combine all soil types
compositions = np.vstack([sandy_soils, silty_soils, clayey_soils, loam_soils])
sand = compositions[:, 0]
silt = compositions[:, 1]
clay = compositions[:, 2]
# Soil type labels for color encoding (fourth variable)
soil_types = (
["Sandy"] * len(sandy_soils)
+ ["Silty"] * len(silty_soils)
+ ["Clayey"] * len(clayey_soils)
+ ["Loam"] * len(loam_soils)
)
soil_type_indices = np.array(
[0] * len(sandy_soils) + [1] * len(silty_soils) + [2] * len(clayey_soils) + [3] * len(loam_soils)
)
# Create ternary plot with color-encoded soil type
fig = go.Figure()
# Add traces for each soil type
for soil_idx, (name, color) in enumerate(zip(["Sandy", "Silty", "Clayey", "Loam"], IMPRINT, strict=True)):
mask = soil_type_indices == soil_idx
fig.add_trace(
go.Scatterternary(
a=sand[mask],
b=silt[mask],
c=clay[mask],
mode="markers",
name=name,
marker={"size": 14, "color": color, "opacity": 0.75, "line": {"width": 1, "color": "white"}},
hovertemplate=(
"<b>%{customdata}</b><br>Sand: %{a:.1f}%<br>Silt: %{b:.1f}%<br>Clay: %{c:.1f}%<extra></extra>"
),
customdata=soil_types,
)
)
# Layout and styling with theme-adaptive colors
fig.update_layout(
title={
"text": "ternary-basic · plotly · pyplots.ai",
"font": {"size": 28, "color": INK},
"x": 0.5,
"xanchor": "center",
},
ternary={
"sum": 100,
"aaxis": {
"title": {"text": "Sand (%)", "font": {"size": 22, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 18, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"baxis": {
"title": {"text": "Silt (%)", "font": {"size": 22, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 18, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"caxis": {
"title": {"text": "Clay (%)", "font": {"size": 22, "color": INK}},
"tickmode": "linear",
"tick0": 0,
"dtick": 20,
"tickfont": {"size": 18, "color": INK_SOFT},
"linewidth": 2,
"linecolor": INK_SOFT,
"gridwidth": 1,
"gridcolor": GRID,
},
"bgcolor": PAGE_BG,
},
paper_bgcolor=PAGE_BG,
plot_bgcolor=PAGE_BG,
margin={"l": 100, "r": 100, "t": 150, "b": 100},
legend={
"x": 0.98,
"y": 0.02,
"xanchor": "right",
"yanchor": "bottom",
"bgcolor": PAGE_BG,
"bordercolor": INK_SOFT,
"borderwidth": 1,
"font": {"color": INK_SOFT, "size": 16},
},
)
# Save outputs
fig.write_image(f"plot-{THEME}.png", width=1600, height=900, scale=3)
fig.write_html(f"plot-{THEME}.html", include_plotlyjs="cdn")
Part of Basic Ternary Plot on anyplot.ai.