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c679d56 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | """
Module for visualizations.
"""
import matplotlib.pyplot as plt
import numpy as np
def plot_error_distribution(all_scores, all_labels, save_path="docs/error_dist.png"):
"""
Function that plots the error distribution between normal and anomaly scores using label masking.
"""
# Mask the labels
normal_scores = all_scores[all_labels == 0]
anomaly_scores = all_scores[all_labels == 1]
# Plot the graph
plt.figure(figsize=(10, 5))
plt.hist(normal_scores, bins=50, alpha=0.6, label="Normal", density=True)
plt.hist(anomaly_scores, bins=50, alpha=0.6, label="Anomaly", density=True)
plt.xlabel("Reconstruction error")
plt.ylabel("Density")
plt.title("Per-frame reconstruction error: normal vs anomaly")
plt.legend()
plt.savefig(save_path, dpi=120, bbox_inches="tight")
print(f"saved: {save_path}") |