Neural Network Layer Activations

import matplotlib.pyplot as plt
import numpy as np

# Network layers and activation strengths
layers = ['Conv1', 'Pool1', 'Conv2', 'Pool2', 'Conv3', 'FC1', 'FC2', 'Output']
np.random.seed(42)
activations = [0.85, 0.72, 0.91, 0.68, 0.95, 0.88, 0.75, 0.98]

# Angles
angles = np.linspace(0, 2 * np.pi, len(layers), endpoint=False).tolist()
activations_plot = activations + [activations[0]]
angles += angles[:1]

# Dark theme
fig, ax = plt.subplots(figsize=(10, 10), subplot_kw=dict(polar=True), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Neon glow effect
for lw, alpha in [(14, 0.06), (10, 0.12), (6, 0.25)]:
    ax.plot(angles, activations_plot, color='#F527B0', linewidth=lw, alpha=alpha)
ax.plot(angles, activations_plot, color='#F527B0', linewidth=2.5)
ax.fill(angles, activations_plot, color='#F527B0', alpha=0.15)

# Scatter with glow
for angle, val in zip(angles[:-1], activations):
    ax.scatter(angle, val, color='#F527B0', s=150, alpha=0.3, zorder=4)
    ax.scatter(angle, val, color='#F527B0', s=80, edgecolors='white', linewidth=1, zorder=5)

# Styling
ax.set_ylim(0, 1.1)
ax.set_xticks(angles[:-1])
ax.set_xticklabels(layers, fontsize=11, color='white', fontweight='500')
ax.set_yticks([0.25, 0.5, 0.75, 1.0])
ax.set_yticklabels(['0.25', '0.50', '0.75', '1.00'], fontsize=9, color='#888888')

ax.spines['polar'].set_color('#555555')
ax.grid(color='#555555', linewidth=0.8, alpha=0.7)
ax.tick_params(colors='#888888')

ax.set_title('Neural Network Activation Pattern', fontsize=16, color='white', fontweight='bold', pad=25)

plt.tight_layout()
plt.show()