Visualization

Visualization tools help you understand test function landscapes through surface plots, contour plots, and interactive visualizations.

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Installation

pip install surfaces[viz]

This installs:

• plotly: Interactive plots and 3D surfaces

• matplotlib: Static plots and publication-quality figures

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What You Get

Surface Plots

3D visualization of 2D test functions:

from surfaces.test_functions.algebraic import AckleyFunction
from surfaces.visualization import plot_surface

func = AckleyFunction()
fig = plot_surface(func)
fig.show()

Contour Plots

2D contour visualization:

from surfaces.test_functions.algebraic import RastriginFunction
from surfaces.visualization import plot_contour

func = RastriginFunction(n_dim=2)
fig = plot_contour(func)
fig.show()

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Interactive Features

Plotly-based visualizations are interactive:

• Rotate: Click and drag to rotate 3D surfaces

• Zoom: Scroll to zoom in/out

• Pan: Shift + drag to pan

• Hover: See exact values at any point

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Usage Examples

Basic Surface Plot

from surfaces.test_functions.algebraic import HimmelblausFunction
from surfaces.visualization import plot_surface

func = HimmelblausFunction()

# Create interactive 3D surface
fig = plot_surface(
    func,
    title="Himmelblau's Function",
    resolution=100
)
fig.show()

Save to File

from surfaces.visualization import plot_surface, plot_contour

# Save as HTML (interactive)
fig = plot_surface(func)
fig.write_html("surface.html")

# Save as PNG (static)
fig.write_image("surface.png")

Multiple Functions

from surfaces.test_functions.algebraic import (
    SphereFunction,
    RastriginFunction,
    AckleyFunction
)
from surfaces.visualization import plot_surface

functions = [
    SphereFunction(n_dim=2),
    RastriginFunction(n_dim=2),
    AckleyFunction()
]

for func in functions:
    fig = plot_surface(func, title=func.__class__.__name__)
    fig.write_html(f"{func.__class__.__name__.lower()}.html")

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Matplotlib Backend

For publication-quality static figures:

import matplotlib.pyplot as plt
from surfaces.test_functions.algebraic import BealeFunction
from surfaces.visualization import plot_contour_matplotlib

func = BealeFunction()

fig, ax = plot_contour_matplotlib(func)
plt.savefig("beale_contour.pdf", dpi=300)

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Visualization in Documentation

The Surfaces documentation includes a function_gallery with pre-generated visualizations of all 2D test functions.

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Dependencies Note

Plotly

Plotly is the primary visualization library. It provides:

• Interactive 3D surfaces

• WebGL rendering for performance

• HTML export for sharing

Matplotlib

Matplotlib is optional but useful for:

• Publication-quality figures

• PDF/EPS export

• Custom styling

Kaleido

For static image export (PNG, PDF), you may need kaleido:

pip install kaleido

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Next Steps

• Visualization - Visualization guide

• /examples/visualization - Visualization examples

• /api_reference/visualization - API reference