Stream Graph
CPU Thread Activity Stream
Stream visualization of CPU thread utilization across multiple cores with cyberpunk aesthetic.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
COLORS = {
'background': '#0a0a0f',
'text': '#ffffff',
'grid': '#333333',
}
np.random.seed(808)
seconds = np.arange(0, 60)
# CPU threads (8 cores)
core_colors = ['#F5276C', '#F54927', '#F5B027', '#27D3F5', '#27F5B0', '#6CF527', '#4927F5', '#F527B0']
cores = []
for i in range(8):
phase = i * np.pi / 4
usage = 20 + 30 * np.sin(seconds * np.pi / 15 + phase) + 20 * np.random.random(60)
cores.append(np.clip(usage, 5, 100))
fig, ax = plt.subplots(figsize=(14, 6), facecolor=COLORS['background'])
ax.set_facecolor(COLORS['background'])
ax.stackplot(seconds, *cores, colors=core_colors, alpha=0.85, baseline='sym',
labels=[f'Core {i}' for i in range(8)])
ax.axhline(0, color=COLORS['grid'], linewidth=0.5, alpha=0.5)
ax.set_xlim(0, 59)
ax.set_title('CPU Core Utilization (Real-time)', color=COLORS['text'], fontsize=14, fontweight='bold', pad=15)
ax.set_xlabel('Time (seconds)', color=COLORS['text'], fontsize=11)
ax.set_ylabel('Utilization (%)', color=COLORS['text'], fontsize=11)
ax.legend(loc='upper center', bbox_to_anchor=(0.5, -0.12), frameon=False, labelcolor=COLORS['text'], fontsize=9, ncol=5)
for spine in ax.spines.values():
spine.set_visible(False)
ax.tick_params(colors=COLORS['text'], labelsize=9)
plt.tight_layout()
plt.subplots_adjust(bottom=0.18)
plt.show()
Library
Matplotlib
Category
Time Series
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