docs: known-issues 3건 추가 + devlog 2026-03-12 세션 기록

test_setup.py

@@ -1,55 +1,6 @@
-"""등급역전 분석 + AAA EDF 진단"""
-import sqlite3
-import numpy as np
-from scipy.stats import norm
-
-conn = sqlite3.connect("data/edf.db")
-
-# 1) 등급별 EDF 상세 확인 — 역전 여부
-print("=== 등급별 EDF 상세 (역전 확인) ===")
-rows = conn.execute("""
-    SELECT dd_rating, COUNT(*), AVG(DD), MIN(DD), MAX(DD), AVG(EDF), MIN(EDF), MAX(EDF)
-    FROM merton_results 
-    GROUP BY dd_rating
-    ORDER BY AVG(DD) DESC
-""").fetchall()
-
-rating_order = ["AAA","AA+","AA","AA-","A+","A","A-","BBB+","BBB","BBB-",
-                "BB+","BB","BB-","B+","B","B-","CCC+","CCC","CCC-"]
-
-prev_edf = -1
-print(f"{'등급':>5} | {'N':>5} | {'DD평균':>8} | {'DD최소':>8} | {'EDF평균':>12} | {'역전':>4}")
-print("-" * 65)
-for rating in rating_order:
-    match = [r for r in rows if r[0] == rating]
-    if match:
-        r = match[0]
-        edf = r[5]
-        inversion = " !!!" if edf < prev_edf and prev_edf >= 0 else ""
-        print(f"  {r[0]:5s} | {r[1]:5d} | {r[2]:8.2f} | {r[3]:8.2f} | {edf:12.8f} | {inversion}")
-        prev_edf = edf
-
-# 2) AAA 개별 확인
-print("\n=== AAA 종목 상세 ===")
-aaa = conn.execute("""
-    SELECT mr.ticker, c.name, mr.DD, mr.EDF, mr.E, mr.D, mr.sigma_V
-    FROM merton_results mr JOIN companies c ON mr.ticker = c.ticker
-    WHERE mr.dd_rating = 'AAA'
-    ORDER BY mr.DD DESC
-    LIMIT 15
-""").fetchall()
-for r in aaa:
-    # 수동 EDF 계산
-    manual_edf = norm.cdf(-r[2])
-    print(f"  {r[0]} {r[1][:15]:15s} | DD={r[2]:8.2f} | EDF={r[3]:.2e} | manual_N(-DD)={manual_edf:.2e} | E={r[4]:.2e} D={r[5]:.2e}")
-
-# 3) AA- EDF 역전 확인 (AA-가 A+보다 높은 문제)
-print("\n=== AA- vs A+ 비교 ===")
-for grade in ["AA-", "A+", "A", "A-"]:
-    data = conn.execute(f"""
-        SELECT AVG(DD), AVG(EDF), MIN(EDF), MAX(EDF), COUNT(*)
-        FROM merton_results WHERE dd_rating = '{grade}'
-    """).fetchone()
-    print(f"  {grade:5s}: DD평균={data[0]:.2f}, EDF평균={data[1]:.6f}, EDF범위=[{data[2]:.6f}, {data[3]:.6f}], N={data[4]}")
-
-conn.close()
+"""Verify Excel file"""
+import openpyxl
+wb = openpyxl.load_workbook("outputs/EDF_Report_20260312.xlsx")
+for s in wb.sheetnames:
+    ws = wb[s]
+    print(f"  {s}: {ws.max_row} rows x {ws.max_column} cols")