diagnostik_schwellenwert.png

# ===========================================================================
# MODULE 16 · Diagnostic thresholds (Healthy vs. Diseased)
# ===========================================================================
print("[16] Diagnostik & Schwellenwert ...")

x = np.linspace(0, 10, 300)
healthy = stats.norm.pdf(x, 3.5, 1.0)
diseased = stats.norm.pdf(x, 6.0, 1.2)

fig, ax = plt.subplots(figsize=(8, 4.5))

ax.plot(x, healthy, color=PRIMARY, linewidth=2, label="Gesund (negativ)")
ax.fill_between(x, healthy, alpha=0.10, color=PRIMARY)

ax.plot(x, diseased, color=EVENT, linewidth=2, label="Krank (positiv)")
ax.fill_between(x, diseased, alpha=0.10, color=EVENT)

# Cut-off at 4.8
cutoff = 4.8
ax.axvline(cutoff, color="#16181C", linestyle="-", linewidth=1.5)
ax.text(cutoff + 0.1, 0.35, "Schwellenwert\n(Cut-off)", color="#16181C", fontsize=10, fontweight="semibold")

# Fill errors: False Positives (Healthy above cutoff)
fp_x = x[x >= cutoff]
ax.fill_between(fp_x, stats.norm.pdf(fp_x, 3.5, 1.0), color=PRIMARY, alpha=0.4, label="Falsch-Positiv (FP)")

# Fill errors: False Negatives (Diseased below cutoff)
fn_x = x[x < cutoff]
ax.fill_between(fn_x, stats.norm.pdf(fn_x, 6.0, 1.2), color=EVENT, alpha=0.4, label="Falsch-Negativ (FN)")

ax.set_xlabel("Biomarker-Konzentration (z.B. Laktat, CRP)")
ax.set_ylabel("Wahrscheinlichkeitsdichte")
ax.set_title("Diagnostischer Schwellenwert & Klassifikationsfehler")
ax.legend(loc="upper right")
ax.grid(True, linestyle=":", alpha=0.6)

(ASSETS / "16-diagnostik-schwellen" / "assets").mkdir(parents=True, exist_ok=True)
save(fig, ASSETS / "16-diagnostik-schwellen" / "assets" / "diagnostik_schwellenwert.png")