Network Latency Heatmap

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(111)
payload_size = np.random.lognormal(5, 1.5, 7000)
latency = 10 + 0.001 * payload_size + np.random.exponential(20, 7000)

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#0f172a')
ax.set_facecolor('#0f172a')

colors = ['#0f172a', '#1e3a5f', '#2563eb', '#3b82f6', '#60a5fa', '#93c5fd', '#bfdbfe', '#dbeafe']
cmap = LinearSegmentedColormap.from_list('blue_glow', colors, N=256)

hb = ax.hexbin(payload_size/1000, latency, gridsize=30, cmap=cmap, mincnt=1, edgecolors='none')

cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.8)
cbar.ax.set_facecolor('#0f172a')
cbar.outline.set_edgecolor('#1e3a5f')
cbar.ax.tick_params(colors='#60a5fa', labelsize=9)
cbar.set_label('Request Count', color='#60a5fa', fontsize=10)

ax.set_xlabel('Payload Size (KB)', color='#60a5fa', fontsize=11)
ax.set_ylabel('Latency (ms)', color='#60a5fa', fontsize=11)
ax.tick_params(colors='#60a5fa', labelsize=10)
for spine in ax.spines.values():
    spine.set_visible(False)

plt.tight_layout()