Application Memory Usage Distribution

import matplotlib.pyplot as plt
import numpy as np
from scipy import stats

np.random.seed(61)

# Memory usage (MB) - mix of light and heavy apps
light_apps = np.random.exponential(50, 400)
medium_apps = np.random.normal(200, 80, 400)
heavy_apps = np.random.normal(500, 150, 200)
memory = np.concatenate([light_apps, medium_apps, heavy_apps])
memory = memory[memory > 0]

kde = stats.gaussian_kde(memory)
x = np.linspace(0, 1000, 500)
y = kde(x)

fig, ax = plt.subplots(figsize=(12, 6), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Gradient by memory usage
for i in range(len(x)-1):
    if x[i] < 100:
        color = '#27F5B0'  # Light - mint
    elif x[i] < 300:
        color = '#27D3F5'  # Medium - cyan
    elif x[i] < 500:
        color = '#F5B027'  # Heavy - amber
    else:
        color = '#F5276C'  # Very heavy - coral
    ax.fill_between(x[i:i+2], y[i:i+2], alpha=0.6, color=color)

ax.plot(x, y, color='#27F5B0', linewidth=3)
ax.plot(x, y, color='#27F5B0', linewidth=8, alpha=0.2)

# Percentiles
p50 = np.percentile(memory, 50)
p90 = np.percentile(memory, 90)
ax.axvline(p50, color='#27D3F5', linestyle='--', linewidth=2, label=f'P50: {p50:.0f}MB')
ax.axvline(p90, color='#F5B027', linestyle='--', linewidth=2, label=f'P90: {p90:.0f}MB')

ax.set_xlabel('Memory Usage (MB)', fontsize=12, color='white', fontweight='500')
ax.set_ylabel('Density', fontsize=12, color='white', fontweight='500')
ax.set_title('Application Memory Consumption Distribution', fontsize=16, color='white', fontweight='bold', pad=15)

ax.tick_params(colors='white', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#334155')
ax.legend(loc='upper right', facecolor='#1e293b', edgecolor='#334155', labelcolor='white')
ax.grid(True, alpha=0.1, color='white')
ax.set_xlim(0, 1000)

plt.tight_layout()
plt.show()