experiment design

conf_experiment.yaml

@@ -6,9 +6,7 @@ meta_seed: 0
 test:  # only for test scenarios
   n_sample: 1
   n_iter: 20
-  n_max_trial: 10
 
 not_test:  # normal scenarios
   n_sample: 50
   n_iter: 20
-  n_max_trial: 10

controller_db.py

@@ -72,20 +72,34 @@ class ControllerDB:
         g_product_js = json.dumps(nx.adjacency_data(g_bom))
 
         # insert exp
-        for idx_exp, dct in enumerate(list_dct):
-            self.add_experiment_1(idx_exp, self.dct_parameter['n_max_trial'],
-                                  dct, g_product_js)  # same g_bom for all exp
-            print(f'Inserted experiment for exp {idx_exp}!')
+        df_xv = pd.read_csv("xv.csv", index_col=None)
+        # read the OA table
+        df_oa = pd.read_fwf("oa.csv", index_col=None)
+        for idx_scenario, row in df_oa.iterrows():
+            dct_exp_para = {}
+            for idx_col, para_level in enumerate(row):
+                dct_exp_para[df_xv.columns[idx_col]] = \
+                    df_xv.iloc[para_level, idx_col]
+            # different initial removal
+            for idx_init_removal, dct_init_removal in enumerate(list_dct):
+                self.add_experiment_1(idx_scenario,
+                                      idx_init_removal,
+                                      dct_init_removal,
+                                      g_product_js,
+                                      **dct_exp_para)
+                print(f"Inserted experiment for scenario {idx_scenario}, "
+                      f"init_removal {idx_init_removal}!")
 
-    def add_experiment_1(self, idx_exp, n_max_trial,
-                         dct_lst_init_remove_firm_prod, g_bom):
+    def add_experiment_1(self, idx_scenario, idx_init_removal,
+                         dct_lst_init_remove_firm_prod, g_bom, n_max_trial):
         e = Experiment(
-            idx_exp=idx_exp,
+            idx_scenario=idx_scenario,
+            idx_init_removal=idx_init_removal,
             n_sample=int(self.dct_parameter['n_sample']),
             n_iter=int(self.dct_parameter['n_iter']),
-            n_max_trial=n_max_trial,
             dct_lst_init_remove_firm_prod=dct_lst_init_remove_firm_prod,
-            g_bom=g_bom)
+            g_bom=g_bom,
+            n_max_trial=n_max_trial)
         db_session.add(e)
         db_session.commit()
 

firm.py

@@ -157,6 +157,7 @@ class FirmAgent(ap.Agent):
         lst_firm_size = [
             firm.revenue_log for firm in self.model.a_lst_total_firms
             if product in firm.a_lst_product
+            and product not in firm.a_lst_product_removed
         ]
         prod_accept = self.revenue_log / sum(lst_firm_size)
         if self.model.nprandom.choice([True, False],

model.py

@@ -220,6 +220,10 @@ class Model(ap.Model):
                         lost_percent = n_up_product_removed / len(
                             product.a_predecessors())
                         lst_size = self.a_lst_total_firms.revenue_log
+                        lst_size = [firm.revenue_log for firm in self.a_lst_total_firms
+                                    if product in firm.a_lst_product
+                                    and product not in firm.a_lst_product_removed
+                                    ]
                         std_size = (firm.revenue_log - min(lst_size) +
                                     1) / (max(lst_size) - min(lst_size) + 1)
                         prod_remove = 1 - std_size * (1 - lost_percent)

oa.csv

@@ -0,0 +1,3 @@
+X1
+0
+1

orm.py

@@ -43,16 +43,17 @@ class Experiment(Base):
     __tablename__ = f"{db_name_prefix}_experiment"
     id = Column(Integer, primary_key=True, autoincrement=True)
 
-    idx_exp = Column(Integer, nullable=False)
+    idx_scenario = Column(Integer, nullable=False)
+    idx_init_removal = Column(Integer, nullable=False)
 
     # fixed parameters
     n_sample = Column(Integer, nullable=False)
     n_iter = Column(Integer, nullable=False)
 
     # variables
-    n_max_trial = Column(Integer, nullable=False)
     dct_lst_init_remove_firm_prod = Column(PickleType, nullable=False)
     g_bom = Column(Text(4294000000), nullable=False)
+    n_max_trial = Column(Integer, nullable=False)
 
     sample = relationship(
         'Sample', back_populates='experiment', lazy='dynamic')

xv.csv

@@ -0,0 +1,3 @@
+n_max_trial
+5
+10