Filled Contour Plot — lets-plot

A filled contour plot displays colored regions between level curves of a 2D scalar field, creating a smooth gradient visualization of continuous data. Unlike basic contour plots that show only isolines, filled contours use color bands to represent value ranges, making it easier to perceive gradual changes and identify regions of similar magnitude. This visualization is particularly effective for showing how a quantity varies continuously across a 2D surface.

Filled Contour Plot rendered with lets-plot

Python source (lets-plot)

""" anyplot.ai
contour-filled: Filled Contour Plot
Library: letsplot 4.9.0 | Python 3.13.13
Quality: 89/100 | Updated: 2026-05-11
"""

import os

import numpy as np
import pandas as pd
from lets_plot import (
    LetsPlot,
    aes,
    element_rect,
    element_text,
    geom_contour,
    geom_contourf,
    ggplot,
    ggsize,
    labs,
    scale_fill_viridis,
    theme,
    theme_minimal,
)
from lets_plot.export import ggsave


LetsPlot.setup_html()

# 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"

# Data - Topographic elevation map
np.random.seed(42)
n_points = 60

# Coordinates in km (realistic geographic scale)
x = np.linspace(0, 50, n_points)
y = np.linspace(0, 50, n_points)
X, Y = np.meshgrid(x, y)

# Elevation model in meters - multiple peaks simulating mountain ranges
# Main peak (2500m) at position (15, 20)
peak1 = 2500 * np.exp(-((X - 15) ** 2 + (Y - 20) ** 2) / 50)
# Secondary peak (1800m) at position (35, 35)
peak2 = 1800 * np.exp(-((X - 35) ** 2 + (Y - 35) ** 2) / 40)
# Valley depression (800m baseline with deeper valley)
valley = 800 - 600 * np.exp(-((X - 25) ** 2 + (Y - 10) ** 2) / 60)
# Ridge formation along diagonal
ridge = 400 * np.exp(-((X - Y) ** 2) / 100)

Z = peak1 + peak2 + valley + ridge
Z = np.maximum(Z, 100)  # Floor at 100m elevation

# Convert to long-form DataFrame for lets-plot
df = pd.DataFrame({"longitude_km": X.flatten(), "latitude_km": Y.flatten(), "elevation_m": Z.flatten()})

# Create filled contour plot with smooth color bands
plot = (
    ggplot(df, aes(x="longitude_km", y="latitude_km", z="elevation_m"))
    + geom_contourf(aes(fill="..level.."), bins=15)
    + geom_contour(color="white", size=0.4, alpha=0.5, bins=15)
    + scale_fill_viridis(name="Elevation (m)", option="plasma")
    + labs(x="Longitude (km)", y="Latitude (km)", title="contour-filled · letsplot · anyplot.ai")
    + theme_minimal()
    + theme(
        plot_background=element_rect(fill=PAGE_BG, color=PAGE_BG),
        panel_background=element_rect(fill=PAGE_BG),
        axis_title=element_text(size=20, color=INK),
        axis_text=element_text(size=16, color=INK_SOFT),
        plot_title=element_text(size=24, color=INK),
        legend_text=element_text(size=14, color=INK_SOFT),
        legend_title=element_text(size=16, color=INK),
        legend_background=element_rect(fill=ELEVATED_BG, color=INK_SOFT),
    )
    + ggsize(1600, 900)
)

# Save PNG (scale=3 gives 4800x2700)
ggsave(plot, f"plot-{THEME}.png", path=".", scale=3)

# Save HTML for interactivity
ggsave(plot, f"plot-{THEME}.html", path=".")

Part of Filled Contour Plot on anyplot.ai.

Filled Contour Plot — lets-plot

Python source (lets-plot)

Other implementations