condense external variables

.vscode/launch.json

@@ -12,9 +12,9 @@
             "console": "integratedTerminal",
             "justMyCode": true,
             "args": [
-                "--exp", "with_exp",
+                "--exp", "test",
                 "--reset_db", "True",
-                "--job", "24"
+                "--job", "1"
             ]
         }
     ]

controller_db.py

@@ -23,7 +23,13 @@ class ControllerDB:
     def __init__(self, prefix, reset_flag=0):
         with open('conf_experiment.yaml') as yaml_file:
             dct_conf_experiment = yaml.full_load(yaml_file)
+
+        assert prefix in ['test', 'without_exp', 'with_exp'], \
+            "db name not in test, without_exp, with_exp"
+
         self.is_test = prefix == 'test'
+        self.is_with_exp = \
+            False if prefix == 'test' or prefix == 'without_exp' else True
         self.db_name_prefix = prefix
         dct_para_in_test = dct_conf_experiment[
             'test'] if self.is_test else dct_conf_experiment['not_test']
@@ -46,18 +52,8 @@ class ControllerDB:
         Firm.fillna(0, inplace=True)
 
         # fill dct_lst_init_remove_firm_prod
-        assert self.db_name_prefix in ['test', 'without_exp', 'with_exp'], \
-            "db name not in test, without_exp, with_exp"
-
         list_dct = []
-        if self.db_name_prefix in ['test', 'without_exp']:
+        if self.is_with_exp:
-            for _, row in Firm.iterrows():
-                code = row['Code']
-                row = row['1':]
-                for product_code in row.index[row == 1].to_list():
-                    dct = {code: [product_code]}
-                    list_dct.append(dct)
-        elif self.db_name_prefix in ['with_exp']:
             str_sql = "select e_id, count, max_max_ts, " \
                 "dct_lst_init_remove_firm_prod from " \
                 "iiabmdb.without_exp_experiment as a " \
@@ -76,13 +72,20 @@ class ControllerDB:
                 lambda x: pickle.loads(x))
             list_dct = result.loc[result['count'] >= 12,
                                   'dct_lst_init_remove_firm_prod'].to_list()
+        else:
+            for _, row in Firm.iterrows():
+                code = row['Code']
+                row = row['1':]
+                for product_code in row.index[row == 1].to_list():
+                    dct = {code: [product_code]}
+                    list_dct.append(dct)
         # list_dct = [{'140': ['1.4.5.1']}]
         # list_dct = [{'133': ['1.4.4.1']}]
         # list_dct = [{'2': ['1.1.3']}]
         # list_dct = [{'135': ['1.3.2.1']}]
         # list_dct = [{'79': ['2.1.3.4']}]
         # list_dct = [{'99': ['1.3.3']}]
-        # list_dct = [{'41': ['1.4.5']}]
+        list_dct = [{'41': ['1.4.5']}]
 
         # fill g_bom
         BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
@@ -98,9 +101,13 @@ class ControllerDB:
         g_product_js = json.dumps(nx.adjacency_data(g_bom))
 
         # insert exp
-        df_xv = pd.read_csv("xv_with_exp.csv", index_col=None)
+        df_xv = pd.read_csv(
+            f"xv_{'with_exp' if self.is_with_exp else 'without_exp'}.csv",
+            index_col=None)
         # read the OA table
-        df_oa = pd.read_csv("oa_with_exp.csv", index_col=None)
+        df_oa = pd.read_csv(
+            f"oa_{'with_exp' if self.is_with_exp else 'without_exp'}.csv",
+            index_col=None)
         df_oa = df_oa.iloc[:, 0:df_xv.shape[1]]
         for idx_scenario, row in df_oa.iterrows():
             dct_exp_para = {}
@@ -119,13 +126,10 @@ class ControllerDB:
 
     def add_experiment_1(self, idx_scenario, idx_init_removal,
                          dct_lst_init_remove_firm_prod, g_bom,
-                         n_max_trial, crit_supplier,
+                         n_max_trial, prf_size, prf_conn,
-                         firm_req_prf_size, firm_req_prf_conn,
-                         firm_acc_prf_size, firm_acc_prf_conn,
-                         netw_sply_prf_n, netw_sply_prf_size,
-                         netw_cust_prf_n, netw_cust_prf_size,
                          cap_limit_prob_type, cap_limit_level,
-                         diff_new_conn, diff_remove, proactive_ratio):
+                         diff_new_conn, crit_supplier, diff_remove,
+                         proactive_ratio, netw_prf_n):
         e = Experiment(
             idx_scenario=idx_scenario,
             idx_init_removal=idx_init_removal,
@@ -134,20 +138,15 @@ class ControllerDB:
             dct_lst_init_remove_firm_prod=dct_lst_init_remove_firm_prod,
             g_bom=g_bom,
             n_max_trial=n_max_trial,
-            crit_supplier=crit_supplier,
+            prf_size=prf_size,
-            firm_req_prf_size=firm_req_prf_size,
+            prf_conn=prf_conn,
-            firm_req_prf_conn=firm_req_prf_conn,
-            firm_acc_prf_size=firm_acc_prf_size,
-            firm_acc_prf_conn=firm_acc_prf_conn,
-            netw_sply_prf_n=netw_sply_prf_n,
-            netw_sply_prf_size=netw_sply_prf_size,
-            netw_cust_prf_n=netw_cust_prf_n,
-            netw_cust_prf_size=netw_cust_prf_size,
             cap_limit_prob_type=cap_limit_prob_type,
             cap_limit_level=cap_limit_level,
             diff_new_conn=diff_new_conn,
+            crit_supplier=crit_supplier,
             diff_remove=diff_remove,
-            proactive_ratio=proactive_ratio
+            proactive_ratio=proactive_ratio,
+            netw_prf_n=netw_prf_n
         )
         db_session.add(e)
         db_session.commit()

firm.py

@@ -23,12 +23,10 @@ class FirmAgent(ap.Agent):
         self.dct_request_prod_from_firm = {}
 
         # para
-        self.flt_crit_supplier = float(self.p.crit_supplier)
+        self.is_prf_size = self.model.is_prf_size
-        self.is_firm_req_prf_size = bool(self.p.firm_req_prf_size)
+        self.is_prf_conn = bool(self.p.prf_conn)
-        self.is_firm_req_prf_conn = bool(self.p.firm_req_prf_conn)
-        self.is_firm_acc_prf_size = bool(self.p.firm_acc_prf_size)
-        self.is_firm_acc_prf_conn = bool(self.p.firm_acc_prf_conn)
         self.flt_diff_new_conn = float(self.p.diff_new_conn)
+        self.flt_crit_supplier = float(self.p.crit_supplier)
 
     def remove_edge_to_cus_remove_cus_up_prod(self, remove_product):
         lst_out_edge = list(
@@ -80,7 +78,7 @@ class FirmAgent(ap.Agent):
                     continue
                 # select based on connection
                 lst_firm_connect = []
-                if self.is_firm_req_prf_conn:
+                if self.is_prf_conn:
                     for firm in \
                             self.dct_cand_alt_supply_up_prod_removed[product]:
                         out_edges = self.model.firm_network.graph.out_edges(
@@ -98,7 +96,7 @@ class FirmAgent(ap.Agent):
                             lst_firm_connect.append(firm)
                 if len(lst_firm_connect) == 0:
                     # select based on size or not
-                    if self.is_firm_req_prf_size:
+                    if self.is_prf_size:
                         lst_size = \
                             [size for size in
                              self.dct_cand_alt_supply_up_prod_removed[
@@ -113,7 +111,7 @@ class FirmAgent(ap.Agent):
                             self.dct_cand_alt_supply_up_prod_removed[product])
                 elif len(lst_firm_connect) > 0:
                     # select based on size of connected firm or not
-                    if self.is_firm_req_prf_size:
+                    if self.is_prf_size:
                         lst_firm_size = \
                             [firm.revenue_log for firm in lst_firm_connect]
                         lst_prob = \
@@ -161,7 +159,7 @@ class FirmAgent(ap.Agent):
                 elif len(lst_firm) > 1:
                     # handling based on connection
                     lst_firm_connect = []
-                    if self.is_firm_acc_prf_conn:
+                    if self.is_prf_conn:
                         for firm in lst_firm:
                             out_edges = \
                                 self.model.firm_network.graph.out_edges(
@@ -182,7 +180,7 @@ class FirmAgent(ap.Agent):
                                 lst_firm_connect.append(firm)
                     if len(lst_firm_connect) == 0:
                         # handling based on size or not
-                        if self.is_firm_acc_prf_size:
+                        if self.is_prf_size:
                             lst_firm_size = \
                                 [firm.revenue_log for firm in lst_firm]
                             lst_prob = \
@@ -197,7 +195,7 @@ class FirmAgent(ap.Agent):
                         self.accept_request(select_customer, product)
                     elif len(lst_firm_connect) > 0:
                         # handling based on size of connected firm or not
-                        if self.is_firm_acc_prf_size:
+                        if self.is_prf_size:
                             lst_firm_size = \
                                 [firm.revenue_log for firm in lst_firm_connect]
                             lst_prob = \

model.py

@@ -19,14 +19,12 @@ class Model(ap.Model):
         self.dct_lst_remove_firm_prod = self.p.dct_lst_init_remove_firm_prod
 
         self.int_n_max_trial = int(self.p.n_max_trial)
-        self.int_netw_sply_prf_n = int(self.p.netw_sply_prf_n)
+        self.is_prf_size = bool(self.p.prf_size)
-        self.is_netw_sply_prf_size = bool(self.p.netw_sply_prf_size)
-        self.int_netw_cust_prf_n = int(self.p.netw_cust_prf_n)
-        self.is_netw_cust_prf_size = bool(self.p.netw_cust_prf_size)
         self.str_cap_limit_prob_type = str(self.p.cap_limit_prob_type)
         self.flt_cap_limit_level = float(self.p.cap_limit_level)
         self.flt_diff_remove = float(self.p.diff_remove)
         self.proactive_ratio = float(self.p.proactive_ratio)
+        self.int_netw_prf_n = int(self.p.netw_prf_n)
 
         # init graph bom
         G_bom = nx.adjacency_graph(json.loads(self.p.g_bom))
@@ -81,11 +79,11 @@ class Model(ap.Model):
                 lst_pred_firm = \
                     Firm['Code'][Firm[pred_product_code] == 1].to_list()
                 # select multiple supplier (multi-sourcing)
-                n_pred_firm = self.int_netw_sply_prf_n
+                n_pred_firm = self.int_netw_prf_n
                 if n_pred_firm > len(lst_pred_firm):
                     n_pred_firm = len(lst_pred_firm)
                 # based on size or not
-                if self.is_netw_sply_prf_size:
+                if self.is_prf_size:
                     lst_pred_firm_size = \
                         [G_Firm.nodes[pred_firm]['Revenue_Log']
                             for pred_firm in lst_pred_firm]
@@ -147,11 +145,11 @@ class Model(ap.Model):
                         lst_succ_firm = Firm['Code'][
                             Firm[succ_product_code] == 1].to_list()
                         # select multiple customer (multi-selling)
-                        n_succ_firm = self.int_netw_cust_prf_n
+                        n_succ_firm = self.int_netw_prf_n
                         if n_succ_firm > len(lst_succ_firm):
                             n_succ_firm = len(lst_succ_firm)
                         # based on size or not
-                        if self.is_netw_cust_prf_size:
+                        if self.is_prf_size:
                             lst_succ_firm_size = \
                                 [G_Firm.nodes[succ_firm]['Revenue_Log']
                                     for succ_firm in lst_succ_firm]

oa_with_exp.csv

@@ -1,37 +1,37 @@
 X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16,X17,X18,X19,X20,X21,X22,X23
-1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1
+0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
-2,1,1,1,2,1,1,2,2,2,2,2,1,2,1,1,1,1,1,2,2,2,2
+1,0,0,0,1,0,0,1,1,1,1,1,0,1,0,0,0,0,0,1,1,1,1
-3,1,1,1,3,1,1,3,3,3,3,3,1,3,1,1,1,1,1,3,3,3,3
+2,0,0,0,2,0,0,2,2,2,2,2,0,2,0,0,0,0,0,2,2,2,2
-1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2,2,3,3,3,3
+0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,2,2,2,2
-2,1,1,1,2,1,1,2,2,3,3,3,2,3,2,2,2,2,2,1,1,1,1
+1,0,0,0,1,0,0,1,1,2,2,2,1,2,1,1,1,1,1,0,0,0,0
-3,1,1,1,3,1,1,3,3,1,1,1,2,1,2,2,2,2,2,2,2,2,2
+2,0,0,0,2,0,0,2,2,0,0,0,1,0,1,1,1,1,1,1,1,1,1
-1,1,1,2,1,2,2,2,3,1,2,3,1,3,1,1,2,2,2,1,2,2,3
+0,0,0,1,0,1,1,1,2,0,1,2,0,2,0,0,1,1,1,0,1,1,2
-2,1,1,2,2,2,2,3,1,2,3,1,1,1,1,1,2,2,2,2,3,3,1
+1,0,0,1,1,1,1,2,0,1,2,0,0,0,0,0,1,1,1,1,2,2,0
-3,1,1,2,3,2,2,1,2,3,1,2,1,2,1,1,2,2,2,3,1,1,2
+2,0,0,1,2,1,1,0,1,2,0,1,0,1,0,0,1,1,1,2,0,0,1
-1,1,2,1,1,2,2,3,2,1,3,2,1,3,2,2,1,1,2,2,1,3,2
+0,0,1,0,0,1,1,2,1,0,2,1,0,2,1,1,0,0,1,1,0,2,1
-2,1,2,1,2,2,2,1,3,2,1,3,1,1,2,2,1,1,2,3,2,1,3
+1,0,1,0,1,1,1,0,2,1,0,2,0,0,1,1,0,0,1,2,1,0,2
-3,1,2,1,3,2,2,2,1,3,2,1,1,2,2,2,1,1,2,1,3,2,1
+2,0,1,0,2,1,1,1,0,2,1,0,0,1,1,1,0,0,1,0,2,1,0
-1,1,2,2,2,1,2,3,1,3,2,1,2,3,1,2,1,2,1,3,2,1,2
+0,0,1,1,1,0,1,2,0,2,1,0,1,2,0,1,0,1,0,2,1,0,1
-2,1,2,2,3,1,2,1,2,1,3,2,2,1,1,2,1,2,1,1,3,2,3
+1,0,1,1,2,0,1,0,1,0,2,1,1,0,0,1,0,1,0,0,2,1,2
-3,1,2,2,1,1,2,2,3,2,1,3,2,2,1,2,1,2,1,2,1,3,1
+2,0,1,1,0,0,1,1,2,1,0,2,1,1,0,1,0,1,0,1,0,2,0
-1,1,2,2,2,2,1,3,2,1,1,3,2,2,2,1,2,1,1,3,3,2,1
+0,0,1,1,1,1,0,2,1,0,0,2,1,1,1,0,1,0,0,2,2,1,0
-2,1,2,2,3,2,1,1,3,2,2,1,2,3,2,1,2,1,1,1,1,3,2
+1,0,1,1,2,1,0,0,2,1,1,0,1,2,1,0,1,0,0,0,0,2,1
-3,1,2,2,1,2,1,2,1,3,3,2,2,1,2,1,2,1,1,2,2,1,3
+2,0,1,1,0,1,0,1,0,2,2,1,1,0,1,0,1,0,0,1,1,0,2
-1,2,1,2,2,2,1,1,3,3,3,1,1,2,2,2,1,2,1,2,1,2,3
+0,1,0,1,1,1,0,0,2,2,2,0,0,1,1,1,0,1,0,1,0,1,2
-2,2,1,2,3,2,1,2,1,1,1,2,1,3,2,2,1,2,1,3,2,3,1
+1,1,0,1,2,1,0,1,0,0,0,1,0,2,1,1,0,1,0,2,1,2,0
-3,2,1,2,1,2,1,3,2,2,2,3,1,1,2,2,1,2,1,1,3,1,2
+2,1,0,1,0,1,0,2,1,1,1,2,0,0,1,1,0,1,0,0,2,0,1
-1,2,1,2,2,1,2,2,3,3,1,2,2,1,2,1,1,1,2,1,3,3,2
+0,1,0,1,1,0,1,1,2,2,0,1,1,0,1,0,0,0,1,0,2,2,1
-2,2,1,2,3,1,2,3,1,1,2,3,2,2,2,1,1,1,2,2,1,1,3
+1,1,0,1,2,0,1,2,0,0,1,2,1,1,1,0,0,0,1,1,0,0,2
-3,2,1,2,1,1,2,1,2,2,3,1,2,3,2,1,1,1,2,3,2,2,1
+2,1,0,1,0,0,1,0,1,1,2,0,1,2,1,0,0,0,1,2,1,1,0
-1,2,1,1,3,2,2,2,1,2,3,3,2,1,1,2,2,1,1,3,1,2,2
+0,1,0,0,2,1,1,1,0,1,2,2,1,0,0,1,1,0,0,2,0,1,1
-2,2,1,1,1,2,2,3,2,3,1,1,2,2,1,2,2,1,1,1,2,3,3
+1,1,0,0,0,1,1,2,1,2,0,0,1,1,0,1,1,0,0,0,1,2,2
-3,2,1,1,2,2,2,1,3,1,2,2,2,3,1,2,2,1,1,2,3,1,1
+2,1,0,0,1,1,1,0,2,0,1,1,1,2,0,1,1,0,0,1,2,0,0
-1,2,2,2,3,1,1,2,2,2,1,1,1,3,1,2,2,1,2,2,3,1,3
+0,1,1,1,2,0,0,1,1,1,0,0,0,2,0,1,1,0,1,1,2,0,2
-2,2,2,2,1,1,1,3,3,3,2,2,1,1,1,2,2,1,2,3,1,2,1
+1,1,1,1,0,0,0,2,2,2,1,1,0,0,0,1,1,0,1,2,0,1,0
-3,2,2,2,2,1,1,1,1,1,3,3,1,2,1,2,2,1,2,1,2,3,2
+2,1,1,1,1,0,0,0,0,0,2,2,0,1,0,1,1,0,1,0,1,2,1
-1,2,2,1,3,2,1,3,3,2,3,2,2,2,1,1,1,2,2,1,2,1,1
+0,1,1,0,2,1,0,2,2,1,2,1,1,1,0,0,0,1,1,0,1,0,0
-2,2,2,1,1,2,1,1,1,3,1,3,2,3,1,1,1,2,2,2,3,2,2
+1,1,1,0,0,1,0,0,0,2,0,2,1,2,0,0,0,1,1,1,2,1,1
-3,2,2,1,2,2,1,2,2,1,2,1,2,1,1,1,1,2,2,3,1,3,3
+2,1,1,0,1,1,0,1,1,0,1,0,1,0,0,0,0,1,1,2,0,2,2
-1,2,2,1,3,1,2,1,2,3,2,3,1,1,2,1,2,2,1,2,2,3,1
+0,1,1,0,2,0,1,0,1,2,1,2,0,0,1,0,1,1,0,1,1,2,0
-2,2,2,1,1,1,2,2,3,1,3,1,1,2,2,1,2,2,1,3,3,1,2
+1,1,1,0,0,0,1,1,2,0,2,0,0,1,1,0,1,1,0,2,2,0,1
-3,2,2,1,2,1,2,3,1,2,1,2,1,3,2,1,2,2,1,1,1,2,3
+2,1,1,0,1,0,1,2,0,1,0,1,0,2,1,0,1,1,0,0,0,1,2

oa_without_exp.csv

@@ -1,2 +1,2 @@
-X1,X2,X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15
+X1,X2,X3,X4,X5,X6,X7,X8,X9,X10
-0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
+0,0,0,0,0,0,0,0,0,0

orm.py

@@ -55,20 +55,15 @@ class Experiment(Base):
     g_bom = Column(Text(4294000000), nullable=False)
 
     n_max_trial = Column(Integer, nullable=False)
-    firm_req_prf_size = Column(Boolean, nullable=False)
+    prf_size = Column(Boolean, nullable=False)
-    firm_req_prf_conn = Column(Boolean, nullable=False)
+    prf_conn = Column(Boolean, nullable=False)
     cap_limit_prob_type = Column(String(16), nullable=False)
     cap_limit_level = Column(DECIMAL(8, 4), nullable=False)
-    firm_acc_prf_size = Column(Boolean, nullable=False)
-    firm_acc_prf_conn = Column(Boolean, nullable=False)
     diff_new_conn = Column(DECIMAL(8, 4), nullable=False)
     crit_supplier = Column(DECIMAL(8, 4), nullable=False)
     diff_remove = Column(DECIMAL(8, 4), nullable=False)
     proactive_ratio = Column(DECIMAL(8, 4), nullable=False)
-    netw_sply_prf_n = Column(Integer, nullable=False)
+    netw_prf_n = Column(Integer, nullable=False)
-    netw_sply_prf_size = Column(Boolean, nullable=False)
-    netw_cust_prf_n = Column(Integer, nullable=False)
-    netw_cust_prf_size = Column(Boolean, nullable=False)
 
     sample = relationship(
         'Sample', back_populates='experiment', lazy='dynamic')

xv_with_exp.csv

@@ -1,4 +1,4 @@
-n_max_trial,firm_req_prf_size,firm_req_prf_conn,cap_limit_prob_type,cap_limit_level,firm_acc_prf_size,firm_acc_prf_conn,diff_new_conn,crit_supplier,diff_remove,proactive_ratio,netw_sply_prf_n,netw_sply_prf_size,netw_cust_prf_n,netw_cust_prf_size
+n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,diff_remove,proactive_ratio,netw_prf_n
-15,TRUE,TRUE,uniform,5,TRUE,TRUE,0.3,2,0.5,0.3,3,TRUE,3,TRUE
+15,TRUE,TRUE,uniform,5,0.3,2,0.5,0.3,3
-10,FALSE,FALSE,normal,10,FALSE,FALSE,0.5,1,1,0.5,2,FALSE,2,FALSE
+10,FALSE,FALSE,normal,10,0.5,1,1,0.5,2
-5,,,,15,,,0.7,0.5,2,0.7,1,,1,
+5,,,,15,0.7,0.5,2,0.7,1

xv_without_exp.csv

@@ -1,2 +1,2 @@
-n_max_trial,firm_req_prf_size,firm_req_prf_conn,cap_limit_prob_type,cap_limit_level,firm_acc_prf_size,firm_acc_prf_conn,diff_new_conn,crit_supplier,diff_remove,proactive_ratio,netw_sply_prf_n,netw_sply_prf_size,netw_cust_prf_n,netw_cust_prf_size
+n_max_trial,prf_size,prf_conn,cap_limit_prob_type,cap_limit_level,diff_new_conn,crit_supplier,diff_remove,proactive_ratio,netw_prf_n
-10,TRUE,TRUE,uniform,10,TRUE,TRUE,0.5,1,1,0,2,TRUE,2,TRUE
+10,TRUE,TRUE,uniform,10,0.5,1,1,0,2