#!/usr/bin/env python3"""Matplotlib Style Configurator Interactive utility to configure matplotlib style preferences and generatecustom style sheets. Creates a preview of the style and optionally savesit as a .mplstyle file. Usage:    python style_configurator.py [--preset PRESET] [--output FILE] [--preview] Presets:    publication, presentation, web, dark, minimal""" import numpy as npimport matplotlib.pyplot as pltfrom matplotlib.gridspec import GridSpecimport argparseimport os  # Predefined style presetsSTYLE_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()