add comments

model.py

@@ -10,7 +10,7 @@ import json
 
 class Model(ap.Model):
     def setup(self):
-        # self para
+        # self parameter
         self.sample = self.p.sample
         self.int_stop_ts = 0
         self.int_n_iter = int(self.p.n_iter)
@@ -27,11 +27,11 @@ class Model(ap.Model):
         self.remove_t = int(self.p.remove_t)
         self.int_netw_prf_n = int(self.p.netw_prf_n)
 
-        # init graph bom
+        # initialize graph bom
         G_bom = nx.adjacency_graph(json.loads(self.p.g_bom))
         self.product_network = ap.Network(self, G_bom)
 
-        # init graph firm
+        # initialize graph firm
         Firm = pd.read_csv("Firm_amended.csv")
         Firm['Code'] = Firm['Code'].astype('string')
         Firm.fillna(0, inplace=True)
@@ -49,7 +49,7 @@ class Model(ap.Model):
             firm_labels_dict[code] = Firm_attr.loc[code].to_dict()
         nx.set_node_attributes(G_Firm, firm_labels_dict)
 
-        # init graph firm prod
+        # initialize graph firm prod
         Firm_Prod = pd.read_csv("Firm_amended.csv")
         Firm_Prod.fillna(0, inplace=True)
         firm_prod = pd.DataFrame({'bool': Firm_Prod.loc[:, '1':].stack()})
@@ -122,11 +122,12 @@ class Model(ap.Model):
         # nx.to_pandas_adjacency(G_Firm).to_csv('adj_g_firm.csv')
         # nx.to_pandas_adjacency(G_FirmProd).to_csv('adj_g_firm_prod.csv')
 
-        # unconnected node
+        # connect unconnected nodes
         for node in nx.nodes(G_Firm):
             if G_Firm.degree(node) == 0:
                 for product_code in G_Firm.nodes[node]['Product_Code']:
-                    # unconnect node does not have possible suppliers
+                    # unconnected node does not have possible suppliers,
+                    # therefore find possible customer instead
                     # current node in graph firm prod
                     current_node = \
                         [n for n, v in G_FirmProd.nodes(data=True)
@@ -135,10 +136,10 @@ class Model(ap.Model):
 
                     lst_succ_product_code = list(
                         G_bom.successors(product_code))
-                    # different from for different types of product,
+                    # different from: for different types of product,
                     # finding a common supplier (the logic above),
-                    # for different types of product,
-                    # finding a custormer for each product
+                    # instead: for different types of product,
+                    # finding a customer for each product
                     for succ_product_code in lst_succ_product_code:
                         # for each product successor (finished product)
                         # the firm sells to,
@@ -187,14 +188,14 @@ class Model(ap.Model):
         # nx.draw(G_FirmProd)
         # plt.show()
 
-        # init product
+        # initialize product
         for ag_node, attr in self.product_network.graph.nodes(data=True):
             product = ProductAgent(self, code=ag_node.label, name=attr['Name'])
             self.product_network.add_agents([product], [ag_node])
         self.a_lst_total_products = ap.AgentList(self,
                                                  self.product_network.agents)
 
-        # init firm
+        # initialize firm
         for ag_node, attr in self.firm_network.graph.nodes(data=True):
             firm_agent = FirmAgent(
                 self,
@@ -210,7 +211,7 @@ class Model(ap.Model):
             self.firm_network.add_agents([firm_agent], [ag_node])
         self.a_lst_total_firms = ap.AgentList(self, self.firm_network.agents)
 
-        # init dct_lst_init_disrupt_firm_prod (from string to agent)
+        # initialize dct_lst_init_disrupt_firm_prod (from string to agent)
         t_dct = {}
         for firm_code, lst_product in \
                 self.dct_lst_init_disrupt_firm_prod.items():
@@ -368,7 +369,7 @@ class Model(ap.Model):
                         firm.dct_prod_up_prod_stat[
                             prod]['p_stat'].append(('R', self.t))
 
-        # stop simulation if any firm still in disrupted except inital removal
+        # stop simulation if any firm still in disrupted except initial removal
         if self.t > 0:
             for firm in self.a_lst_total_firms:
                 for prod in firm.dct_prod_up_prod_stat.keys():
@@ -443,8 +444,6 @@ class Model(ap.Model):
 
             # reset dct_request_prod_from_firm
             self.a_lst_total_firms.clean_before_trial()
-            # do not use:
-            # self.a_lst_total_firms.dct_request_prod_from_firm = {} why?
 
     def end(self):
         # print('/' * 20, 'output', '/' * 20)