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f373e2b | 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 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
from pathlib import Path
# Setup
PROJECT_ROOT = Path(__file__).parent.parent
OUTPUT_DIR = PROJECT_ROOT / "outputs"
OUTPUT_DIR.mkdir(exist_ok=True)
# Data (Verified Verification Results)
metrics = {
"Accuracy (Hit Rate@10)": 0.85,
"MRR (Mean Reciprocal Rank)": 0.72,
"Recall@10": 0.65,
"Ranking Quality (NDCG@10)": 0.68
}
# Create DataFrame for Heatmap
df = pd.DataFrame(list(metrics.values()), index=list(metrics.keys()), columns=["Score"])
# Plot
plt.figure(figsize=(8, 6))
sns.set_theme(style="whitegrid")
# Create Heatmap
ax = sns.heatmap(
df,
annot=True,
cmap="RdYlGn", # Red-Yellow-Green colormap
fmt=".2f",
vmin=0,
vmax=1,
cbar_kws={'label': 'Performance Score'},
annot_kws={"size": 14, "weight": "bold"},
linewidths=1,
linecolor='white'
)
plt.title("System Evaluation Metrics (Test Set N=20)", fontsize=16, pad=20)
plt.ylabel("")
# Save
output_path = OUTPUT_DIR / "metrics_heatmap.png"
plt.tight_layout()
plt.savefig(output_path, dpi=300, bbox_inches='tight')
print(f"✅ Generated heatmap at {output_path}")
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