#!/usr/bin/env python3
"""
Matplotlib Style Configurator
Interactive utility to configure matplotlib style preferences and generate
custom style sheets. Creates a preview of the style and optionally saves
it as a .mplstyle file.
Usage:
python style_configurator.py [--preset PRESET] [--output FILE] [--preview]
Presets:
publication, presentation, web, dark, minimal
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
import argparse
import os
# Predefined style presets
STYLE_PRESETS = {
'publication': {
'figure.figsize': (8, 6),
'figure.dpi': 100,
'savefig.dpi': 300,
'savefig.bbox': 'tight',
'font.family': 'sans-serif',
'font.sans-serif': ['Arial', 'Helvetica'],
'font.size': 11,
'axes.labelsize': 12,
'axes.titlesize': 14,
'axes.linewidth': 1.5,
'axes.grid': False,
'axes.spines.top': False,
'axes.spines.right': False,
'lines.linewidth': 2,
'lines.markersize': 8,
'xtick.labelsize': 10,
'ytick.labelsize': 10,
'xtick.direction': 'in',
'ytick.direction': 'in',
'xtick.major.size': 6,
'ytick.major.size': 6,
'xtick.major.width': 1.5,
'ytick.major.width': 1.5,
'legend.fontsize': 10,
'legend.frameon': True,
'legend.framealpha': 1.0,
'legend.edgecolor': 'black',
},
'presentation': {
'figure.figsize': (12, 8),
'figure.dpi': 100,
'savefig.dpi': 150,
'font.size': 16,
'axes.labelsize': 20,
'axes.titlesize': 24,
'axes.linewidth': 2,
'lines.linewidth': 3,
'lines.markersize': 12,
'xtick.labelsize': 16,
'ytick.labelsize': 16,
'legend.fontsize': 16,
'axes.grid': True,
'grid.alpha': 0.3,
},
'web': {
'figure.figsize': (10, 6),
'figure.dpi': 96,
'savefig.dpi': 150,
'font.size': 11,
'axes.labelsize': 12,
'axes.titlesize': 14,
'lines.linewidth': 2,
'axes.grid': True,
'grid.alpha': 0.2,
'grid.linestyle': '--',
},
'dark': {
'figure.facecolor': '#1e1e1e',
'figure.edgecolor': '#1e1e1e',
'axes.facecolor': '#1e1e1e',
'axes.edgecolor': 'white',
'axes.labelcolor': 'white',
'text.color': 'white',
'xtick.color': 'white',
'ytick.color': 'white',
'grid.color': 'gray',
'grid.alpha': 0.3,
'axes.grid': True,
'legend.facecolor': '#1e1e1e',
'legend.edgecolor': 'white',
'savefig.facecolor': '#1e1e1e',
},
'minimal': {
'figure.figsize': (10, 6),
'axes.spines.top': False,
'axes.spines.right': False,
'axes.spines.left': False,
'axes.spines.bottom': False,
'axes.grid': False,
'xtick.bottom': True,
'ytick.left': True,
'axes.axisbelow': True,
'lines.linewidth': 2.5,
'font.size': 12,
}
}
def generate_preview_data():
"""Generate sample data for style preview."""
np.random.seed(42)
x = np.linspace(0, 10, 100)
y1 = np.sin(x) + 0.1 * np.random.randn(100)
y2 = np.cos(x) + 0.1 * np.random.randn(100)
scatter_x = np.random.randn(100)
scatter_y = 2 * scatter_x + np.random.randn(100)
categories = ['A', 'B', 'C', 'D', 'E']
bar_values = [25, 40, 30, 55, 45]
return {
'x': x, 'y1': y1, 'y2': y2,
'scatter_x': scatter_x, 'scatter_y': scatter_y,
'categories': categories, 'bar_values': bar_values
}
def create_style_preview(style_dict=None):
"""Create a preview figure demonstrating the style."""
if style_dict:
plt.rcParams.update(style_dict)
data = generate_preview_data()
fig = plt.figure(figsize=(14, 10))
gs = GridSpec(2, 2, figure=fig, hspace=0.3, wspace=0.3)
# Line plot
ax1 = fig.add_subplot(gs[0, 0])
ax1.plot(data['x'], data['y1'], label='sin(x)', marker='o', markevery=10)
ax1.plot(data['x'], data['y2'], label='cos(x)', linestyle='--')
ax1.set_xlabel('X axis')
ax1.set_ylabel('Y axis')
ax1.set_title('Line Plot')
ax1.legend()
ax1.grid(True, alpha=0.3)
# Scatter plot
ax2 = fig.add_subplot(gs[0, 1])
colors = np.sqrt(data['scatter_x']**2 + data['scatter_y']**2)
scatter = ax2.scatter(data['scatter_x'], data['scatter_y'],
c=colors, cmap='viridis', alpha=0.6, s=50)
ax2.set_xlabel('X axis')
ax2.set_ylabel('Y axis')
ax2.set_title('Scatter Plot')
cbar = plt.colorbar(scatter, ax=ax2)
cbar.set_label('Distance')
ax2.grid(True, alpha=0.3)
# Bar chart
ax3 = fig.add_subplot(gs[1, 0])
bars = ax3.bar(data['categories'], data['bar_values'],
edgecolor='black', linewidth=1)
# Color bars with gradient
colors = plt.cm.viridis(np.linspace(0.2, 0.8, len(bars)))
for bar, color in zip(bars, colors):
bar.set_facecolor(color)
ax3.set_xlabel('Categories')
ax3.set_ylabel('Values')
ax3.set_title('Bar Chart')
ax3.grid(True, axis='y', alpha=0.3)
# Multiple line plot with fills
ax4 = fig.add_subplot(gs[1, 1])
ax4.plot(data['x'], data['y1'], label='Signal 1', linewidth=2)
ax4.fill_between(data['x'], data['y1'] - 0.2, data['y1'] + 0.2,
alpha=0.3, label='±1 std')
ax4.plot(data['x'], data['y2'], label='Signal 2', linewidth=2)
ax4.fill_between(data['x'], data['y2'] - 0.2, data['y2'] + 0.2,
alpha=0.3)
ax4.set_xlabel('X axis')
ax4.set_ylabel('Y axis')
ax4.set_title('Time Series with Uncertainty')
ax4.legend()
ax4.grid(True, alpha=0.3)
fig.suptitle('Style Preview', fontsize=16, fontweight='bold')
return fig
def save_style_file(style_dict, filename):
"""Save style dictionary as .mplstyle file."""
with open(filename, 'w') as f:
f.write("# Custom matplotlib style\n")
f.write("# Generated by style_configurator.py\n\n")
# Group settings by category
categories = {
'Figure': ['figure.'],
'Font': ['font.'],
'Axes': ['axes.'],
'Lines': ['lines.'],
'Markers': ['markers.'],
'Ticks': ['tick.', 'xtick.', 'ytick.'],
'Grid': ['grid.'],
'Legend': ['legend.'],
'Savefig': ['savefig.'],
'Text': ['text.'],
}
for category, prefixes in categories.items():
category_items = {k: v for k, v in style_dict.items()
if any(k.startswith(p) for p in prefixes)}
if category_items:
f.write(f"# {category}\n")
for key, value in sorted(category_items.items()):
# Format value appropriately
if isinstance(value, (list, tuple)):
value_str = ', '.join(str(v) for v in value)
elif isinstance(value, bool):
value_str = str(value)
else:
value_str = str(value)
f.write(f"{key}: {value_str}\n")
f.write("\n")
print(f"Style saved to {filename}")
def print_style_info(style_dict):
"""Print information about the style."""
print("\n" + "="*60)
print("STYLE CONFIGURATION")
print("="*60)
categories = {
'Figure Settings': ['figure.'],
'Font Settings': ['font.'],
'Axes Settings': ['axes.'],
'Line Settings': ['lines.'],
'Grid Settings': ['grid.'],
'Legend Settings': ['legend.'],
}
for category, prefixes in categories.items():
category_items = {k: v for k, v in style_dict.items()
if any(k.startswith(p) for p in prefixes)}
if category_items:
print(f"\n{category}:")
for key, value in sorted(category_items.items()):
print(f" {key}: {value}")
print("\n" + "="*60 + "\n")
def list_available_presets():
"""Print available style presets."""
print("\nAvailable style presets:")
print("-" * 40)
descriptions = {
'publication': 'Optimized for academic publications',
'presentation': 'Large fonts for presentations',
'web': 'Optimized for web display',
'dark': 'Dark background theme',
'minimal': 'Minimal, clean style',
}
for preset, desc in descriptions.items():
print(f" {preset:15s} - {desc}")
print("-" * 40 + "\n")
def interactive_mode():
"""Run interactive mode to customize style settings."""
print("\n" + "="*60)
print("MATPLOTLIB STYLE CONFIGURATOR - Interactive Mode")
print("="*60)
list_available_presets()
preset = input("Choose a preset to start from (or 'custom' for default): ").strip().lower()
if preset in STYLE_PRESETS:
style_dict = STYLE_PRESETS[preset].copy()
print(f"\nStarting from '{preset}' preset")
else:
style_dict = {}
print("\nStarting from default matplotlib style")
print("\nCommon settings you might want to customize:")
print(" 1. Figure size")
print(" 2. Font sizes")
print(" 3. Line widths")
print(" 4. Grid settings")
print(" 5. Color scheme")
print(" 6. Done, show preview")
while True:
choice = input("\nSelect option (1-6): ").strip()
if choice == '1':
width = input(" Figure width (inches, default 10): ").strip() or '10'
height = input(" Figure height (inches, default 6): ").strip() or '6'
style_dict['figure.figsize'] = (float(width), float(height))
elif choice == '2':
base = input(" Base font size (default 12): ").strip() or '12'
style_dict['font.size'] = float(base)
style_dict['axes.labelsize'] = float(base) + 2
style_dict['axes.titlesize'] = float(base) + 4
elif choice == '3':
lw = input(" Line width (default 2): ").strip() or '2'
style_dict['lines.linewidth'] = float(lw)
elif choice == '4':
grid = input(" Enable grid? (y/n): ").strip().lower()
style_dict['axes.grid'] = grid == 'y'
if style_dict['axes.grid']:
alpha = input(" Grid transparency (0-1, default 0.3): ").strip() or '0.3'
style_dict['grid.alpha'] = float(alpha)
elif choice == '5':
print(" Theme options: 1=Light, 2=Dark")
theme = input(" Select theme (1-2): ").strip()
if theme == '2':
style_dict.update(STYLE_PRESETS['dark'])
elif choice == '6':
break
return style_dict
def main():
"""Main function."""
parser = argparse.ArgumentParser(
description='Matplotlib style configurator',
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
Examples:
# Show available presets
python style_configurator.py --list
# Preview a preset
python style_configurator.py --preset publication --preview
# Save a preset as .mplstyle file
python style_configurator.py --preset publication --output my_style.mplstyle
# Interactive mode
python style_configurator.py --interactive
"""
)
parser.add_argument('--preset', type=str, choices=list(STYLE_PRESETS.keys()),
help='Use a predefined style preset')
parser.add_argument('--output', type=str,
help='Save style to .mplstyle file')
parser.add_argument('--preview', action='store_true',
help='Show style preview')
parser.add_argument('--list', action='store_true',
help='List available presets')
parser.add_argument('--interactive', action='store_true',
help='Run in interactive mode')
args = parser.parse_args()
if args.list:
list_available_presets()
# Also show currently available matplotlib styles
print("\nBuilt-in matplotlib styles:")
print("-" * 40)
for style in sorted(plt.style.available):
print(f" {style}")
return
if args.interactive:
style_dict = interactive_mode()
elif args.preset:
style_dict = STYLE_PRESETS[args.preset].copy()
print(f"Using '{args.preset}' preset")
else:
print("No preset or interactive mode specified. Showing default preview.")
style_dict = {}
if style_dict:
print_style_info(style_dict)
if args.output:
save_style_file(style_dict, args.output)
if args.preview or args.interactive:
print("Creating style preview...")
fig = create_style_preview(style_dict if style_dict else None)
if args.output:
preview_filename = args.output.replace('.mplstyle', '_preview.png')
plt.savefig(preview_filename, dpi=150, bbox_inches='tight')
print(f"Preview saved to {preview_filename}")
plt.show()
if __name__ == "__main__":
main()