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A题/ZJ_v2/fig08_power_breakdown.py

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+"""
+Fig 8: Power Breakdown Stacked Area Plot
+Shows how total power is distributed across components over time
+"""
+
+import os
+import numpy as np
+import matplotlib.pyplot as plt
+from plot_style import set_oprice_style, save_figure
+
+def make_figure(config):
+    """Generate Fig 8: Power Breakdown"""
+    
+    set_oprice_style()
+    
+    # Time axis
+    duration = 2.5  # hours
+    n_points = 150
+    t_h = np.linspace(0, duration, n_points)
+    
+    seed = config.get('global', {}).get('seed', 42)
+    np.random.seed(seed)
+    
+    # Power components (baseline scenario with realistic variations)
+    P_bg = 5.0 + 0.5 * np.random.randn(n_points).cumsum() * 0.05
+    P_bg = np.clip(P_bg, 4.0, 6.0)
+    
+    P_scr = 8.0 + 2.0 * np.sin(2 * np.pi * t_h / 0.5) + 0.5 * np.random.randn(n_points)
+    P_scr = np.clip(P_scr, 5.0, 12.0)
+    
+    P_cpu = 35.0 + 5.0 * np.random.randn(n_points).cumsum() * 0.03
+    P_cpu = np.clip(P_cpu, 28.0, 42.0)
+    
+    P_net = 7.0 + 3.0 * (np.random.rand(n_points) > 0.7).astype(float)  # Burst pattern
+    
+    P_gps = 0.015 * np.ones(n_points)  # Minimal GPS
+    
+    # Stack the components
+    components = {
+        'Background': P_bg,
+        'Screen': P_scr,
+        'CPU': P_cpu,
+        'Network': P_net,
+        'GPS': P_gps
+    }
+    
+    # Create figure
+    fig, ax = plt.subplots(figsize=(12, 7))
+    
+    # Stack plot
+    colors = ['#8c564b', '#ffbb78', '#ff7f0e', '#2ca02c', '#98df8a']
+    ax.stackplot(t_h, P_bg, P_scr, P_cpu, P_net, P_gps,
+                 labels=['Background', 'Screen', 'CPU', 'Network', 'GPS'],
+                 colors=colors, alpha=0.8)
+    
+    # Total power line
+    P_total = P_bg + P_scr + P_cpu + P_net + P_gps
+    ax.plot(t_h, P_total, 'k-', linewidth=2, label='Total Power', alpha=0.7)
+    
+    # Labels and title
+    ax.set_xlabel('Time (hours)', fontsize=11)
+    ax.set_ylabel('Power (Watts)', fontsize=11)
+    ax.set_title('Power Consumption Breakdown - Baseline Scenario', 
+                 fontsize=12, fontweight='bold')
+    ax.set_xlim(0, duration)
+    ax.set_ylim(0, max(P_total) * 1.1)
+    ax.grid(True, alpha=0.3, axis='y')
+    ax.legend(loc='upper left', framealpha=0.9, fontsize=10)
+    
+    # Add statistics box
+    avg_powers = {
+        'Background': np.mean(P_bg),
+        'Screen': np.mean(P_scr),
+        'CPU': np.mean(P_cpu),
+        'Network': np.mean(P_net),
+        'GPS': np.mean(P_gps)
+    }
+    total_avg = sum(avg_powers.values())
+    
+    stats_text = 'Average Power Distribution:\\n'
+    for name, power in avg_powers.items():
+        pct = power / total_avg * 100
+        stats_text += f'{name}: {power:.1f}W ({pct:.1f}%)\\n'
+    stats_text += f'Total: {total_avg:.1f}W'
+    
+    ax.text(0.98, 0.97, stats_text, transform=ax.transAxes,
+            fontsize=9, verticalalignment='top', horizontalalignment='right',
+            bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.8),
+            family='monospace')
+    
+    # Annotate dominant component
+    ax.annotate('CPU dominates\n(~60% of total)',
+                xy=(duration/2, np.mean(P_cpu) + np.mean(P_bg) + np.mean(P_scr)/2),
+                xytext=(duration * 0.2, max(P_total) * 0.7),
+                arrowprops=dict(arrowstyle='->', color='darkred', lw=1.5),
+                fontsize=10, color='darkred',
+                bbox=dict(boxstyle='round', facecolor='lightyellow', alpha=0.7))
+    
+    plt.tight_layout()
+    
+    # Save
+    figure_dir = config.get('global', {}).get('figure_dir', 'figures')
+    os.makedirs(figure_dir, exist_ok=True)
+    output_base = os.path.join(figure_dir, 'Fig08_Power_Breakdown')
+    save_figure(fig, output_base, dpi=config.get('global', {}).get('dpi', 300))
+    plt.close()
+    
+    return {
+        "output_files": [f"{output_base}.pdf", f"{output_base}.png"],
+        "computed_metrics": {
+            "avg_total_W": float(total_avg),
+            "cpu_percentage": float(avg_powers['CPU'] / total_avg * 100),
+            "gps_percentage": float(avg_powers['GPS'] / total_avg * 100)
+        },
+        "validation_flags": {},
+        "pass": True
+    }