无报错

.idea/encodings.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Encoding">
+    <file url="file://$PROJECT_DIR$/input_data/input_firm_data/Firm_amended.csv" charset="UTF-8" />
+  </component>
+</project>

controller_db.py

@@ -39,7 +39,8 @@ class ControllerDB:
         self.lst_saved_s_id = []
 
         self.experiment_data = []
-        self.batch_size = 999  # 根据需求设置每批次的大小
+        self.batch_size = 2000
+        # 根据需求设置每批次的大小
 
     def init_tables(self):
         self.fill_experiment_table()

main.py

@@ -44,7 +44,7 @@ if __name__ == '__main__':
     # 输入参数
     parser = argparse.ArgumentParser(description='setting')
     parser.add_argument('--exp', type=str, default='without_exp')
-    parser.add_argument('--job', type=int, default='4')
+    parser.add_argument('--job', type=int, default='1')
     parser.add_argument('--reset_sample', type=int, default='0')
     parser.add_argument('--reset_db', type=bool, default=False)
 

my_model.py

@@ -91,7 +91,8 @@ class MyModel(Model):
 
         firm = pd.read_csv("input_data/input_firm_data/Firm_amended.csv")
 
-        firm['Code'] = firm['Code'].astype('string')
+        firm['Code'] = firm['Code'].astype(str)
+
         firm.fillna(0, inplace=True)
 
         firm_attr = firm.loc[:, ["Code", "Type_Region", "Revenue_Log", "原材料", "设备数量", "库存商品"]]
@@ -136,6 +137,15 @@ class MyModel(Model):
         # Add edges to G_Firm according to G_bom
         for node in nx.nodes(self.G_Firm):
             lst_pred_product_code = []
+            product_code = self.G_Firm.nodes[node].get('Product_Code')
+            # 打印值和类型
+            #print(f"节点 {node} 的 'Product_Code': {product_code}, 类型: {type(product_code)}")
+
+            # 如果 'Product_Code' 是 float 类型或单个值，将其转换为列表
+            if isinstance(product_code, float):
+                #print(f"警告: 节点 {node} 的 'Product_Code' 为浮点数，已转换为列表")
+                product_code = [product_code]  # 将浮点数包装为列表
+
             for product_code in self.G_Firm.nodes[node]['Product_Code']:
                 lst_pred_product_code += list(self.G_bom.predecessors(product_code))
             lst_pred_product_code = list(set(lst_pred_product_code))
@@ -152,13 +162,30 @@ class MyModel(Model):
                     n_pred_firm = len(lst_pred_firm)
 
                 if self.is_prf_size:
-                    lst_pred_firm_size = [self.G_Firm.nodes[pred_firm]['Revenue_Log'] for pred_firm in
-                                          lst_pred_firm]
-                    lst_prob = [size / sum(lst_pred_firm_size) for size in lst_pred_firm_size]
+                    # 获取 firm 的 size 列表
+                    lst_pred_firm_size = [self.G_Firm.nodes[pred_firm]['Revenue_Log'] for pred_firm in lst_pred_firm]
+                    # 检查 lst_pred_firm_size 是否为空或总和为 0
+                    if len(lst_pred_firm_size) == 0 or sum(lst_pred_firm_size) == 0:
+                        #print("警告: lst_pred_firm_size 为空或总和为 0，无法生成概率分布")
+                        lst_choose_firm = []  # 返回空结果，或根据需要处理
+                    else:
+                        # 计算总和
+                        sum_pred_firm_size = sum(lst_pred_firm_size)
+                        # 归一化生成 lst_prob
+                        lst_prob = [size / sum_pred_firm_size for size in lst_pred_firm_size]
+                        # 使用 np.isclose() 确保概率总和接近 1
+                        if not np.isclose(sum(lst_prob), 1.0):
+                            #print(f"警告: 概率总和为 {sum(lst_prob)}，现在进行修正")
+                            lst_prob = [prob / sum(lst_prob) for prob in lst_prob]
+                        # 确保没有负值或 0
+                        lst_prob = [max(0, prob) for prob in lst_prob]
+                        # 根据修正后的概率选择 firm
                         lst_choose_firm = self.nprandom.choice(lst_pred_firm, n_pred_firm, replace=False, p=lst_prob)
                 else:
+                    # 直接进行随机选择
                     lst_choose_firm = self.nprandom.choice(lst_pred_firm, n_pred_firm, replace=False)
 
+
                 # Add edges from predecessor firms to current node (firm)
                 lst_add_edge = [(pred_firm, node, {'Product': pred_product_code}) for pred_firm in lst_choose_firm]
                 self.G_Firm.add_edges_from(lst_add_edge)