proactive strategy exp

SQL_check_num_dis_firm_in_ts.sql

@@ -0,0 +1,20 @@
+select * from 
+(select s_id, ts, count(id) as num_dis_firm from
+iiabmdb.with_exp_result
+where ts > 0
+group by s_id, ts) as a
+where a.num_dis_firm > 3;
+
+select * from 
+iiabmdb.with_exp_result
+where s_id = '54170';
+
+SELECT * FROM iiabmdb.with_exp_sample where id='54170';
+SELECT max(id) FROM iiabmdb.with_exp_sample;
+
+select * from 
+(select s_id, id_firm, id_product, ts, count(id) as num_dup from
+iiabmdb.with_exp_result
+where ts > 0
+group by s_id, id_firm, id_product, ts) as a
+where a.num_dup > 1;

controller_db.py

@@ -91,10 +91,10 @@ class ControllerDB:
         g_product_js = json.dumps(nx.adjacency_data(g_bom))
 
         # insert exp
-        df_xv = pd.read_csv("xv.csv", index_col=None)
+        df_xv = pd.read_csv("xv_without_exp.csv", index_col=None)
         # read the OA table
         df_oa = pd.read_csv("oa_without_exp.csv", index_col=None)
-        df_oa = df_oa.iloc[:, 0:9]
+        df_oa = df_oa.iloc[:, 0:10]
         for idx_scenario, row in df_oa.iterrows():
             dct_exp_para = {}
             for idx_col, para_level in enumerate(row):
@@ -115,7 +115,7 @@ class ControllerDB:
                          n_max_trial, crit_supplier, firm_pref_request,
                          firm_pref_accept, netw_pref_cust_n,
                          netw_pref_cust_size, cap_limit, diff_new_conn,
-                         diff_remove,):
+                         diff_remove, proactive_ratio):
         e = Experiment(
             idx_scenario=idx_scenario,
             idx_init_removal=idx_init_removal,
@@ -132,6 +132,7 @@ class ControllerDB:
             cap_limit=cap_limit,
             diff_new_conn=diff_new_conn,
             diff_remove=diff_remove,
+            proactive_ratio=proactive_ratio
         )
         db_session.add(e)
         db_session.commit()

model.py

@@ -25,6 +25,7 @@ class Model(ap.Model):
         self.flt_netw_pref_cust_size = float(self.p.netw_pref_cust_size)
         self.flt_cap_limit = int(self.p.cap_limit)
         self.flt_diff_remove = float(self.p.diff_remove)
+        self.proactive_ratio = float(self.p.proactive_ratio)
 
         # init graph bom
         G_bom = nx.adjacency_graph(json.loads(self.p.g_bom))
@@ -172,7 +173,6 @@ class Model(ap.Model):
                 firm.a_lst_product_removed.append(product)
 
         # proactive strategy
-        proactive_ratio = 1.0
         # get all the firm prod affected
         for firm, a_lst_product in self.dct_lst_remove_firm_prod.items():
             for product in a_lst_product:
@@ -198,7 +198,7 @@ class Model(ap.Model):
                     [lst_affected[i] for i in
                      self.nprandom.choice(range(len(lst_affected)),
                                           round(len(lst_affected) *
-                                                proactive_ratio))]
+                                                self.proactive_ratio))]
 
                 for firm_code, prod_code in lst_firm_proactive:
                     pro_firm_prod_code = \
@@ -266,11 +266,15 @@ class Model(ap.Model):
                                     'Product': di_supp_prod.code
                                 })
                             ])
+                            # print(f"proactive add {select_cand.code} to "
+                            #       f"{pro_firm.code} "
+                            #       f"for {di_supp_code} {di_supp_prod.code}")
                             # change capacity
                             select_cand.dct_prod_capacity[di_supp_prod] -= 1
+                            break
 
         # draw network
-        self.draw_network()
+        # self.draw_network()
 
     def update(self):
         self.a_lst_total_firms.clean_before_time_step()

oa_without_exp.csv

@@ -1,2 +1,2 @@
 X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13
-1,1,1,1,1,1,1,1,1,1,1,1,1
+0,0,0,0,0,0,0,0,0,0,0,0,0

orm.py

@@ -63,6 +63,7 @@ class Experiment(Base):
     cap_limit = Column(Integer, nullable=False)
     diff_new_conn = Column(DECIMAL(8, 4), nullable=False)
     diff_remove = Column(DECIMAL(8, 4), nullable=False)
+    proactive_ratio = Column(DECIMAL(8, 4), nullable=False)
 
     sample = relationship(
         'Sample', back_populates='experiment', lazy='dynamic')

xv_with_exp.csv

@@ -0,0 +1,4 @@
+n_max_trial,crit_supplier,firm_pref_request,firm_pref_accept,netw_pref_cust_n,netw_pref_cust_size,cap_limit,diff_new_conn,diff_remove,proactive_ratio
+15,2,2,2,0.5,2,4,0.5,0.5,0.4
+10,1,1,1,1,1,2,1,1,0.6
+5,0.5,0.5,0.5,2,0.5,1,2,2,0.8

xv_without_exp.csv

@@ -1,4 +1,2 @@
-n_max_trial,crit_supplier,firm_pref_request,firm_pref_accept,netw_pref_cust_n,netw_pref_cust_size,cap_limit,diff_new_conn,diff_remove
-15,2,2,2,0.5,2,4,0.5,0.5
-10,1,1,1,1,1,2,1,1
-5,0.5,0.5,0.5,2,0.5,1,2,2
+n_max_trial,crit_supplier,firm_pref_request,firm_pref_accept,netw_pref_cust_n,netw_pref_cust_size,cap_limit,diff_new_conn,diff_remove,proactive_ratio
+10,1,1,1,1,1,2,1,1,0