An arc diagram arranges nodes along a single horizontal line and draws connections between them as curved arcs above the line. This layout excels at revealing patterns in sequential or ordered data while minimizing visual clutter compared to force-directed layouts. Arc height typically indicates the distance between connected nodes, making it easy to spot long-range versus short-range connections.
""" anyplot.ai
arc-basic: Basic Arc Diagram
Library: letsplot 4.10.1 | Python 3.13.13
Quality: 87/100 | Updated: 2026-05-30
"""
import os
import numpy as np
import pandas as pd
from lets_plot import (
LetsPlot,
aes,
element_blank,
element_rect,
element_text,
geom_path,
geom_point,
geom_segment,
geom_text,
ggplot,
ggsize,
labs,
layer_tooltips,
scale_alpha_identity,
scale_color_identity,
scale_size_identity,
theme,
xlim,
ylim,
)
from lets_plot.export import ggsave
LetsPlot.setup_html()
# Theme tokens — Imprint palette, theme-adaptive chrome
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
# Imprint palette — 3 weight levels in canonical order, first = brand green
ARC_COLORS = {
1: "#009E73", # Weak — Imprint position 1 (brand green)
2: "#C475FD", # Moderate — Imprint position 2 (lavender)
3: "#4467A3", # Strong — Imprint position 3 (blue)
}
ARC_ALPHAS = {1: 0.70, 2: 0.82, 3: 0.95}
NODE_FILL = "#BD8233" # Imprint position 4 (ochre) — warm entity anchor
# Data: Character interactions in a story chapter
nodes = ["Alice", "Bob", "Carol", "David", "Eve", "Frank", "Grace", "Henry", "Iris", "Jack"]
n_nodes = len(nodes)
edges = [
(0, 1, 3), # Alice-Bob (strong)
(0, 3, 2), # Alice-David
(1, 2, 2), # Bob-Carol
(2, 4, 1), # Carol-Eve
(3, 5, 2), # David-Frank
(4, 6, 1), # Eve-Grace
(0, 7, 1), # Alice-Henry (long-range)
(1, 5, 2), # Bob-Frank
(2, 3, 3), # Carol-David (strong)
(5, 8, 1), # Frank-Iris
(6, 9, 2), # Grace-Jack
(0, 9, 1), # Alice-Jack (longest range)
(3, 7, 2), # David-Henry
(7, 8, 1), # Henry-Iris
(8, 9, 2), # Iris-Jack
]
x_positions = np.linspace(0, 1.3, n_nodes)
y_baseline = 0.06
connections = [0] * n_nodes
for s, t, w in edges:
connections[s] += w
connections[t] += w
weight_labels = {1: "Weak", 2: "Moderate", 3: "Strong"}
# Arc path data — increased floor size for weak arc visibility
arc_data = []
for edge_id, (start, end, weight) in enumerate(edges):
x_start = x_positions[start]
x_end = x_positions[end]
distance = abs(end - start)
height = 0.08 * distance
n_points = 50
t_vals = np.linspace(0, np.pi, n_points)
arc_x = x_start + (x_end - x_start) * (1 - np.cos(t_vals)) / 2
arc_y = y_baseline + height * np.sin(t_vals)
line_size = 1.8 + weight * 1.3 # raised floor: weak=3.1, moderate=4.4, strong=5.7
for i in range(n_points):
arc_data.append(
{
"x": arc_x[i],
"y": arc_y[i],
"edge_id": edge_id,
"size": line_size,
"color": ARC_COLORS[weight],
"alpha": ARC_ALPHAS[weight],
"connection": f"{nodes[start]} ↔ {nodes[end]}",
"strength": weight_labels[weight],
}
)
arc_df = pd.DataFrame(arc_data)
max_conn = max(connections)
node_sizes = [10 + 8 * (c / max_conn) for c in connections]
node_df = pd.DataFrame(
{"x": x_positions, "y": [y_baseline] * n_nodes, "name": nodes, "node_size": node_sizes, "connections": connections}
)
baseline_df = pd.DataFrame({"x": [x_positions[0]], "xend": [x_positions[-1]], "y": [y_baseline], "yend": [y_baseline]})
label_df = pd.DataFrame({"x": x_positions, "y": [y_baseline - 0.038] * n_nodes, "name": nodes})
# Legend — upper-left to balance canvas composition and utilize empty space
legend_x = 0.0
legend_y_start = 0.79
legend_spacing = 0.068
legend_line_len = 0.085
legend_lines = pd.DataFrame(
{
"x": [legend_x] * 3,
"xend": [legend_x + legend_line_len] * 3,
"y": [legend_y_start - i * legend_spacing for i in range(3)],
"yend": [legend_y_start - i * legend_spacing for i in range(3)],
"color": [ARC_COLORS[3], ARC_COLORS[2], ARC_COLORS[1]],
"size": [1.8 + 3 * 1.3, 1.8 + 2 * 1.3, 1.8 + 1 * 1.3],
"alpha": [ARC_ALPHAS[3], ARC_ALPHAS[2], ARC_ALPHAS[1]],
}
)
legend_text_df = pd.DataFrame(
{
"x": [legend_x + legend_line_len + 0.013] * 3,
"y": [legend_y_start - i * legend_spacing for i in range(3)],
"label": ["Strong (3)", "Moderate (2)", "Weak (1)"],
}
)
legend_title_df = pd.DataFrame({"x": [legend_x], "y": [legend_y_start + 0.075], "label": ["Connection Strength"]})
alice_df = node_df[node_df["name"] == "Alice"].copy()
arc_peak_x = float((x_positions[0] + x_positions[9]) / 2)
arc_peak_y = float(y_baseline + 0.08 * 9 + 0.04)
arc_label_df = pd.DataFrame({"x": [arc_peak_x], "y": [arc_peak_y], "label": ["longest range"]})
# Plot
plot = (
ggplot()
+ geom_segment(
data=baseline_df, mapping=aes(x="x", y="y", xend="xend", yend="yend"), color=INK_SOFT, size=0.6, alpha=0.4
)
+ geom_path(
data=arc_df,
mapping=aes(x="x", y="y", group="edge_id", size="size", color="color", alpha="alpha"),
tooltips=layer_tooltips().title("@connection").line("Strength|@strength"),
)
+ scale_size_identity()
+ scale_color_identity()
+ scale_alpha_identity()
+ geom_point(data=alice_df, mapping=aes(x="x", y="y"), size=22, color="#009E73", fill=PAGE_BG, stroke=2.5, shape=21)
+ geom_point(
data=node_df,
mapping=aes(x="x", y="y", size="node_size"),
color=INK,
fill=NODE_FILL,
stroke=1.5,
shape=21,
tooltips=layer_tooltips().title("@name").line("Total weight|@connections"),
)
+ geom_text(data=label_df, mapping=aes(x="x", y="y", label="name"), size=9, color=INK, fontface="bold", vjust=1)
+ geom_segment(
data=legend_lines,
mapping=aes(x="x", y="y", xend="xend", yend="yend", color="color", size="size", alpha="alpha"),
tooltips="none",
)
+ geom_text(data=legend_text_df, mapping=aes(x="x", y="y", label="label"), size=7, color=INK_SOFT, hjust=0)
+ geom_text(
data=legend_title_df, mapping=aes(x="x", y="y", label="label"), size=8, color=INK, fontface="bold", hjust=0
)
+ geom_text(data=arc_label_df, mapping=aes(x="x", y="y", label="label"), size=7, color=INK_SOFT, fontface="italic")
+ xlim(-0.05, 1.48)
+ ylim(-0.12, 0.92)
+ labs(
title="arc-basic · python · letsplot · anyplot.ai",
subtitle="Character interactions in a story chapter — node size reflects connection strength",
)
+ theme(
axis_title=element_blank(),
axis_text=element_blank(),
axis_ticks=element_blank(),
axis_line=element_blank(),
panel_grid=element_blank(),
panel_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
plot_title=element_text(size=16, face="bold", color=INK),
plot_subtitle=element_text(size=13, color=INK_SOFT),
legend_position="none",
)
+ ggsize(800, 450)
)
# Save — theme-suffixed filenames, scale=4 → 3200×1800 px
ggsave(plot, f"plot-{THEME}.png", path=".", scale=4)
ggsave(plot, f"plot-{THEME}.html", path=".")
Part of Basic Arc Diagram on anyplot.ai.