mplstyles-seaborn 0.2.5

Matplotlib style sheets based on seaborn-v0_8-dark theme with combinable palettes and contexts

mplstyles-seaborn

Matplotlib style sheets based on seaborn v0.8 themes with combinable palettes and contexts.

Overview

While matplotlib includes built-in seaborn v0.8 style sheets, they offer only a limited set of predefined combinations. This package extends matplotlib's seaborn styling without requiring seaborn as a dependency, providing all 120 possible combinations of seaborn's styles, color palettes, and contexts.

Features

• Zero seaborn dependency: Use seaborn-style plots with pure matplotlib
• Complete coverage: All 120 combinations of seaborn v0.8 styles, palettes, and contexts
• Easy integration: Styles automatically registered with matplotlib on import
• Multiple usage methods: Convenience functions or direct matplotlib integration
• Type hints: Full type annotation support

Example Galleries

For comprehensive visual examples, see our 📸 Example Galleries:

• Basic Usage Gallery - Fundamental usage patterns and plot types
• Style Comparison Gallery - All 120 style combinations visualized
• Comprehensive Demo Gallery - Advanced plot types and publication-ready figures

Installation

Install from PyPI:

pip install mplstyles-seaborn

Or with uv:

uv add mplstyles-seaborn

Development Installation

For development, install directly from GitHub:

pip install git+https://github.com/monodera/mplstyles-seaborn.git

Or with uv:

uv add git+https://github.com/monodera/mplstyles-seaborn.git

Quick Start

import matplotlib.pyplot as plt
import mplstyles_seaborn
import numpy as np

# Generate sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Method 1: Use convenience function
mplstyles_seaborn.use_style('whitegrid', 'colorblind', 'talk')

plt.figure(figsize=(10, 6))
plt.plot(x, y, label='sin(x)')
plt.title('Example Plot')
plt.legend()
plt.show()

Available Options

Styles (5 options)

• darkgrid - Dark grid background
• whitegrid - White grid background
• dark - Dark background, no grid
• white - White background, no grid
• ticks - White background with ticks

Palettes (6 options)

• dark - Deep, saturated colors
• colorblind - Colorblind-friendly palette
• muted - Muted, subdued colors
• bright - Bright, vibrant colors
• pastel - Light, pastel colors
• deep - Dark, deep colors

Contexts (4 options)

• paper - Smallest elements, for papers/publications
• notebook - Default size, for notebooks
• talk - Larger elements, for presentations
• poster - Largest elements, for posters

Usage Methods

1. Convenience Function

import mplstyles_seaborn

# Use all three parameters
mplstyles_seaborn.use_style('whitegrid', 'colorblind', 'talk')

# Use defaults for some parameters (defaults: darkgrid, dark, notebook)
mplstyles_seaborn.use_style(palette='colorblind', context='talk')

2. Direct Matplotlib

import matplotlib.pyplot as plt

# Styles are automatically registered on import
plt.style.use('seaborn-v0_8-whitegrid-colorblind-talk')

3. List Available Styles

import mplstyles_seaborn

# See all 120 available style combinations
styles = mplstyles_seaborn.list_available_styles()
print(f"Available styles: {len(styles)}")

# Print first few styles
for style in styles[:5]:
    print(style)

Run the examples with:

# Basic usage examples
uv run python examples/basic_usage.py

# Generate all 120 style combination comparisons  
uv run python examples/style_comparison.py

# Comprehensive demonstration with 7 different plot types
uv run python examples/comprehensive_demo.py

Basic Line Plot

import matplotlib.pyplot as plt
import numpy as np
import mplstyles_seaborn

# Apply style
mplstyles_seaborn.use_style('whitegrid', 'colorblind', 'talk')

# Create plot
x = np.linspace(0, 10, 100)
fig, ax = plt.subplots(figsize=(10, 6))

ax.plot(x, np.sin(x), label='sin(x)', linewidth=2)
ax.plot(x, np.cos(x), label='cos(x)', linewidth=2)
ax.plot(x, np.sin(x + np.pi/4), label='sin(x + pi/4)', linewidth=2)

ax.set_title('Trigonometric Functions')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.legend()

plt.tight_layout()
plt.show()

Scatter Plot

import matplotlib.pyplot as plt
import numpy as np
import mplstyles_seaborn

# Apply dark theme with muted palette
mplstyles_seaborn.use_style('dark', 'muted', 'notebook')

# Generate data
np.random.seed(42)
x = np.random.randn(200)
y = np.random.randn(200)

# Create scatter plot
fig, ax = plt.subplots(figsize=(8, 6))
ax.scatter(x, y, alpha=0.7, s=60)
ax.set_title('Random Scatter Plot')
ax.set_xlabel('X values')
ax.set_ylabel('Y values')

plt.tight_layout()
plt.show()

Font Configuration

The package includes optimized font settings:

1. Source Sans 3 (if available)
2. Arial (fallback)
3. DejaVu Sans (further fallback)
4. System fonts

Font family is automatically set to sans-serif for consistent appearance.

API Reference

Functions

use_style(style='darkgrid', palette='dark', context='notebook')

Apply a seaborn-v0.8 style with specified parameters.

Parameters:

• style (str): Style type - 'darkgrid', 'whitegrid', 'dark', 'white', 'ticks'
• palette (str): Color palette - 'dark', 'colorblind', 'muted', 'bright', 'pastel', 'deep'
• context (str): Context scaling - 'paper', 'notebook', 'talk', 'poster'

list_available_styles()

Returns a sorted list of all 120 available style names.

Returns:

• list[str]: List of style names

register_styles()

Register all styles with matplotlib (called automatically on import).

Constants

• STYLES: List of available style types
• PALETTES: List of available color palettes
• CONTEXTS: List of available contexts

Development

Requirements

• Python >=3.11
• matplotlib >=3.5
• seaborn >=0.11 (for development/generation only)

Setup

git clone https://github.com/monodera/mplstyles-seaborn.git
cd mplstyles-seaborn
uv sync

Testing

This project includes comprehensive tests covering:

• Unit tests for all API functions
• Integration tests with matplotlib
• Validation tests for all 120 style files
• Error handling and edge cases
• Performance benchmarks

Running Tests

# Install test dependencies
uv sync --extra test

# Run all tests
uv run pytest

# Run tests with coverage
uv run pytest --cov=src/mplstyles_seaborn --cov-report=term-missing

# Run specific test categories
uv run pytest tests/test_api.py          # API function tests
uv run pytest tests/test_integration.py # Matplotlib integration tests
uv run pytest tests/test_styles.py      # Style file validation tests
uv run pytest tests/test_errors.py      # Error handling tests

# Run performance tests (marked as slow)
uv run pytest tests/test_performance.py -m "not slow"  # Fast performance tests
uv run pytest tests/test_performance.py                # All performance tests

# Run with verbose output
uv run pytest -v

Manual Testing

# Test package import and basic functionality
uv run python -c "import mplstyles_seaborn; print(len(mplstyles_seaborn.list_available_styles()))"

# Test specific style application
uv run python -c "import matplotlib.pyplot as plt; plt.style.use('seaborn-v0_8-whitegrid-colorblind-talk')"

# Run example scripts
uv run python examples/basic_usage.py
uv run python examples/style_comparison.py
uv run python examples/comprehensive_demo.py

Regenerating Styles

# Generate and fix all 120 style files in one command (recommended)
uv run python scripts/build_styles.py

# Alternative: Generate only (for development/testing)
uv run python scripts/build_styles.py --generate-only

# Alternative: Fix existing files only
uv run python scripts/build_styles.py --fix-only

License

This project is licensed under the MIT License.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Development Support

This project was primarily developed using Claude Code, Anthropic's AI-powered coding assistant.

Related Projects

• seaborn - Statistical data visualization library
• matplotlib - Python plotting library