model+firm

firm.py

@@ -1,6 +1,15 @@
 import agentpy as ap
 
 
-class Firm(ap.Agent):
+class FirmAgent(ap.Agent):
-    def setup(self):
+    def setup(self, code, name, type_region, revenue_log):
         self.firm_network = self.model.firm_network
+
+        self.code = code
+        self.name = name
+        self.type_region = type_region
+        self.revenue_log = revenue_log
+
+        self.is_disrupted = False
+    
+    

model.py

@@ -2,16 +2,25 @@ import agentpy as ap
 import pandas as pd
 import numpy as np
 import networkx as nx
+from firm import FirmAgent
 
 sample = 0
-sample = 0
+seed = 0
-dct_sample_para = {'sample': sample, 'seed': sample}
+n_iter = 3
+list_init_remove_firm_code = [0, 2]
+dct_sample_para = {
+    'sample': sample,
+    'seed': seed,
+    'n_iter': n_iter,
+    'list_init_remove_firm_code': list_init_remove_firm_code
+}
 
 
 class Model(ap.Model):
     def setup(self):
         self.sample = self.p.sample
         self.nprandom = np.random.default_rng(self.p.seed)
+        self.int_n_iter = int(self.p.n_iter)
 
         # init graph bom
         BomNodes = pd.read_csv('BomNodes.csv', index_col=0)
@@ -79,6 +88,43 @@ class Model(ap.Model):
                 # print('-'*20)
 
         self.firm_network = ap.Network(self, G_Firm)
+        # print([node.label for node in self.firm_network.nodes])
+        # print([list(self.firm_network.graph.predecessors(node)) for node in self.firm_network.nodes])
+        # print([self.firm_network.graph.nodes[node.label]['Name'] for node in self.firm_network.nodes])
+        # print([v for v in self.firm_network.graph.nodes(data=True)])
+
+        # init firm
+        for ag_node, attr in self.firm_network.graph.nodes(data=True):
+            firm_agent = FirmAgent(self,
+                                   code=attr['Code'],
+                                   name=attr['Name'],
+                                   type_region=attr['Type_Region'],
+                                   revenue_log=attr['Revenue_Log'])
+            self.firm_network.add_agents([firm_agent], [ag_node])
+        a_list_total_firms = ap.AgentList(self, self.firm_network.agents)
+        # set the initial firm that is removed
+        list_b_is_removed = list(
+            map(lambda x: x in self.p.list_init_remove_firm_code,
+                self.firm_network.agents.code))
+        self.a_list_firms_removed = a_list_total_firms.select(
+            list_b_is_removed)
+        self.a_list_firms_removed.is_removed = True
+
+    def update(self):
+        # Update list of unhappy people
+        # self.agents.update_happiness()
+        # self.unhappy = self.agents.select(self.agents.happy == False)
+
+        # Stop simulation if reached terminal number of iteration
+        if self.t == self.int_n_iter:
+            self.stop()
+
+    def step(self):
+        # Move unhappy people to new location
+        self.unhappy.find_new_home()
+
+    def end(self):
+        pass
 
     def draw_network(self):
         import matplotlib.pyplot as plt
@@ -102,4 +148,4 @@ class Model(ap.Model):
 
 model = Model(dct_sample_para)
 model.setup()
-model.draw_network()
+# model.draw_network()