initial commit

codes/notebooks/lognormal_visual.py

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+import numpy as np
+import matplotlib.pyplot as plt
+
+mu = 3.5
+sigmas = [0.1, 0.3]
+size = 100000
+rng = np.random.default_rng(42)
+
+fig, axes = plt.subplots(1, 2, figsize=(16, 6))
+
+for sigma in sigmas:
+    samples = rng.lognormal(mean=mu, sigma=sigma, size=size)
+    
+    # lognormal → normal 변환
+    log_samples = np.log(samples)
+    
+    # Lognormal 플롯
+    axes[0].hist(samples, bins=200, density=True, alpha=0.5, label=f"sigma={sigma}")
+    axes[0].set_xlim(0, 200)
+    axes[0].set_title("Lognormal Distribution")
+    axes[0].set_xlabel("Weight")
+    axes[0].set_ylabel("Density")
+    axes[0].legend()
+    
+    # Normal 플롯
+    axes[1].hist(log_samples, bins=200, density=True, alpha=0.5, label=f"sigma={sigma}")
+    axes[1].set_title("log(samples) → Normal Distribution")
+    axes[1].set_xlabel("log(Weight)")
+    axes[1].set_ylabel("Density")
+    axes[1].legend()
+
+plt.suptitle("Lognormal vs Normal (μ fixed)")
+plt.tight_layout()
+plt.show()