debug the run_id

env.py

@@ -21,21 +21,22 @@ class Env(ap.Model):
     n_firm: int
     e_revenue: float
 
-    a_lst_worker: ap.AgentList[WorkerAgent]
-    a_lst_firm: ap.AgentList[FirmAgent]
+    a_lst_worker: ap.AgentList
+    a_lst_firm: ap.AgentList
 
     """
         Worker: Mean(s), Gini(s)
-        Firm: Mean((pi_{j,t})), Gini(pi_{j,t})
+        Firm: Mean((pi_{j,t})), Gini(pi_{j,t}), Mean(s_a_yield)
         Env: Percent(IsHired)
     """
     out_w_avg_salary: float
     out_w_gini_salary: float
     out_f_avg_profit: float
+    out_f_avg_yield: float
     out_f_gini_profit: float
     out_w_percent_hired: float
 
-    def __init__(self, dct_all):
+    def __init__(self, dct_all, _run_id=None):
         super().__init__()
 
         # 工作人员、企业数量、搜寻企业数量赋值
@@ -89,10 +90,12 @@ class Env(ap.Model):
         # self.picture_out()
         self.update()
 
-        if self.t == 200:
+        if self.t >= 200:
             self.running = False
+            self.stop()
         else:
             self.t += 1
+            # print(f"running the {self.t} step")
 
     def update(self):
         lst_salary = []
@@ -106,19 +109,23 @@ class Env(ap.Model):
         self.out_w_gini_salary = self.gini(lst_salary)
 
         lst_profit = []
+        lst_yield = []
         # n_w_firm = 0
         for f in self.a_lst_firm:
             lst_profit.append(f.s_profit)
+            lst_yield.append(f.s_a_yield)
             # if f.s_profit > 0:
             #     n_w_firm += 1
         n_firms = len(lst_profit)
         self.out_f_avg_profit = sum(lst_profit) / n_firms
+        self.out_f_avg_yield = sum(lst_yield) / n_firms
         self.out_f_gini_profit = self.gini(lst_profit)
         self.out_w_percent_hired = n_hired / n_workers
 
         self.record('out_w_avg_salary')
         self.record('out_w_gini_salary')
         self.record('out_f_avg_profit')
+        self.record('out_f_avg_yield')
         self.record('out_f_gini_profit')
         self.record('out_w_percent_hired')
 

experiment.py

@@ -24,7 +24,8 @@ model_para = {
     "n_firm": 100
 }
 
-lst_op_key = ['out_w_avg_salary', 'out_w_gini_salary', 'out_f_avg_profit', 'out_f_gini_profit', 'out_w_percent_hired']
+lst_op_key = ['out_w_avg_salary', 'out_w_gini_salary', 'out_f_avg_profit', 'out_f_avg_yield',
+              'out_f_gini_profit', 'out_w_percent_hired']
 lst_2d_op_avg = []
 lst_2d_xv = []
 for idx_row in range(idx_start-1, n_row, 1):
@@ -48,8 +49,8 @@ for idx_row in range(idx_start-1, n_row, 1):
                 break
 
         lst_2d_op.append([the_model.out_w_avg_salary, the_model.out_w_gini_salary,
-                          the_model.out_f_avg_profit, the_model.out_f_gini_profit,
-                          the_model.out_w_percent_hired])
+                          the_model.out_f_avg_profit, the_model.out_f_avg_yield,
+                          the_model.out_f_gini_profit, the_model.out_w_percent_hired])
 
     arr_op = np.array(lst_2d_op)
     lst_2d_op_avg.append(arr_op.mean(axis=0).tolist())

firm.py

@@ -40,6 +40,7 @@ class FirmAgent(ap.Agent):
         self.initial_f_salary = randint(8000, 10000)
         self.s_profit = 0
         self.s_value = 0
+        self.s_a_yield = 0
 
     def apply(self, the_worker):
         self.l_applied_workers.append(the_worker)