A matrix-based representation of a network or graph where rows and columns represent nodes and cell color indicates the presence or weight of edges between them. This visualization complements node-link diagrams by excelling at revealing clusters, structural patterns, and density in large or dense networks where node-link layouts become cluttered. Reordering nodes by cluster, degree, or community membership exposes block-diagonal structure and makes group boundaries immediately visible.
""" anyplot.ai
heatmap-adjacency: Network Adjacency Matrix Heatmap
Library: bokeh 3.9.0 | Python 3.13.13
Quality: 87/100 | Created: 2026-05-08
"""
# ruff: noqa: E402
import sys
# Prevent this script's directory from shadowing the installed bokeh package
_script_dir = sys.path[0] if sys.path else ""
if _script_dir and "implementations/python" in _script_dir:
sys.path = sys.path[1:]
import math
import os
import time
from pathlib import Path
import numpy as np
from bokeh.io import output_file, save
from bokeh.models import BasicTicker, ColorBar, ColumnDataSource, LinearColorMapper
from bokeh.palettes import Viridis256
from bokeh.plotting import figure
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
# Theme tokens
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"
NAN_COLOR = "#E8E5DE" if THEME == "light" else "#252520"
# Data — 24 researchers across 4 departments, ordered by department
np.random.seed(42)
dept_codes = ["Phy", "Chem", "Bio", "Math"]
n_per_dept = 6
node_names = [f"{code}{i:02d}" for code in dept_codes for i in range(1, n_per_dept + 1)]
node_community = [idx for idx in range(len(dept_codes)) for _ in range(n_per_dept)]
n = len(node_names)
# Weighted symmetric adjacency matrix
adj = np.zeros((n, n))
for i in range(n):
for j in range(i + 1, n):
same_dept = node_community[i] == node_community[j]
if same_dept and np.random.rand() < 0.80:
w = np.random.uniform(0.5, 1.0)
adj[i, j] = w
adj[j, i] = w
elif not same_dept and np.random.rand() < 0.08:
w = np.random.uniform(0.1, 0.4)
adj[i, j] = w
adj[j, i] = w
# NaN encodes absent edges (no self-loops shown)
adj_nan = adj.astype(float)
adj_nan[adj == 0] = np.nan
# Flatten to row-per-cell format for ColumnDataSource
xs, ys, weights = [], [], []
for i in range(n):
for j in range(n):
xs.append(node_names[j]) # column = target node
ys.append(node_names[i]) # row = source node
weights.append(adj_nan[i, j])
source = ColumnDataSource({"x": xs, "y": ys, "weight": weights})
# Continuous color mapper — viridis for edge weights
mapper = LinearColorMapper(palette=Viridis256, low=0.1, high=1.0, nan_color=NAN_COLOR)
# Figure (square canvas for symmetric matrix)
p = figure(
width=3600,
height=3600,
x_range=node_names,
y_range=list(reversed(node_names)),
toolbar_location=None,
title="Researcher Collaboration · heatmap-adjacency · bokeh · anyplot.ai",
)
# Heatmap rectangles
p.rect(
x="x", y="y", width=1, height=1, source=source, fill_color={"field": "weight", "transform": mapper}, line_color=None
)
# Colorbar
colorbar = ColorBar(
color_mapper=mapper,
ticker=BasicTicker(desired_num_ticks=6),
label_standoff=20,
border_line_color=None,
location=(0, 0),
title="Connection Strength",
title_text_font_size="20pt",
title_text_color=INK,
major_label_text_font_size="18pt",
major_label_text_color=INK_SOFT,
background_fill_color=ELEVATED_BG,
width=60,
)
p.add_layout(colorbar, "right")
# Typography
p.title.text_font_size = "28pt"
p.title.text_color = INK
p.title.text_font_style = "normal"
p.xaxis.axis_label = "Researcher (Target)"
p.yaxis.axis_label = "Researcher (Source)"
p.xaxis.axis_label_text_font_size = "22pt"
p.yaxis.axis_label_text_font_size = "22pt"
p.xaxis.axis_label_text_color = INK
p.yaxis.axis_label_text_color = INK
p.xaxis.major_label_text_font_size = "15pt"
p.yaxis.major_label_text_font_size = "15pt"
p.xaxis.major_label_text_color = INK_SOFT
p.yaxis.major_label_text_color = INK_SOFT
p.xaxis.major_label_orientation = math.pi / 3
# Theme-adaptive chrome
p.background_fill_color = PAGE_BG
p.border_fill_color = PAGE_BG
p.outline_line_color = INK_SOFT
p.xaxis.axis_line_color = INK_SOFT
p.yaxis.axis_line_color = INK_SOFT
p.xaxis.major_tick_line_color = INK_SOFT
p.yaxis.major_tick_line_color = INK_SOFT
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
# Save HTML
output_file(f"plot-{THEME}.html")
save(p)
# Screenshot with headless Chrome via Selenium
W, H = 3600, 3600
opts = Options()
for arg in (
"--headless=new",
"--no-sandbox",
"--disable-dev-shm-usage",
"--disable-gpu",
f"--window-size={W},{H}",
"--hide-scrollbars",
):
opts.add_argument(arg)
driver = webdriver.Chrome(options=opts)
driver.set_window_size(W, H)
driver.get(f"file://{Path(f'plot-{THEME}.html').resolve()}")
time.sleep(3)
driver.save_screenshot(f"plot-{THEME}.png")
driver.quit()
Part of Network Adjacency Matrix Heatmap on anyplot.ai.