From 24b253bd0101617432fc465cef9f2648d82f93d4 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E5=BD=AD=E6=A3=AE?= <pengsen@fecr.com.cn>
Date: Tue, 25 Jan 2022 14:22:05 +0800
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---
 Rating/scripts/financial_score.py | 43 +++++++++++++++++--------------
 1 file changed, 23 insertions(+), 20 deletions(-)

diff --git a/Rating/scripts/financial_score.py b/Rating/scripts/financial_score.py
index e434ab9..6fd01b1 100644
--- a/Rating/scripts/financial_score.py
+++ b/Rating/scripts/financial_score.py
@@ -25,27 +25,30 @@ def financial_score(param1, param2):
 
     # main
     for key, value in param2.items():
-        refer = list(map(float, refers[key]))
-        weight = weights[key]
-        if value is None:
-            score = 0
-        elif value > refer[0]:
-            score = weight
-        elif value > refer[1]:
-            standard_score = round(weight * 1, 2)
-            score = linear_correlation_type(value, standard_score, refer[0], refer[1])
-        elif value > refer[2]:
-            standard_score = round(weight * 0.8, 2)
-            score = linear_correlation_type(value, standard_score, refer[1], refer[2])
-        elif value > refer[3]:
-            standard_score = round(weight * 0.5, 2)
-            score = linear_correlation_type(value, standard_score, refer[2], refer[3])
-        elif value > refer[4]:
-            standard_score = round(weight * 0.25, 2)
-            score = linear_correlation_type(value, standard_score, refer[3], refer[4])
+        if key == '已获利息倍数' and value is None:
+            scores[key] = 5
         else:
-            score = 0
-        scores[key] = round(score, 2)
+            refer = list(map(float, refers[key]))
+            weight = weights[key]
+            if value is None:
+                score = 0
+            elif value > refer[0]:
+                score = weight
+            elif value > refer[1]:
+                standard_score = round(weight * 1, 2)
+                score = linear_correlation_type(value, standard_score, refer[0], refer[1])
+            elif value > refer[2]:
+                standard_score = round(weight * 0.8, 2)
+                score = linear_correlation_type(value, standard_score, refer[1], refer[2])
+            elif value > refer[3]:
+                standard_score = round(weight * 0.5, 2)
+                score = linear_correlation_type(value, standard_score, refer[2], refer[3])
+            elif value > refer[4]:
+                standard_score = round(weight * 0.25, 2)
+                score = linear_correlation_type(value, standard_score, refer[3], refer[4])
+            else:
+                score = 0
+            scores[key] = round(score, 2)
 
     result = dict()