🐛 stochastic models SI probability computation

GiulioRossetti · May 10, 2019 · f80b144 · f80b144
1 parent d031ee3
commit f80b144
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Showing 5 changed files with 15 additions and 10 deletions.
diff --git a/ndlib/models/epidemics/SEIRModel.py b/ndlib/models/epidemics/SEIRModel.py
@@ -67,8 +67,9 @@ def iteration(self, node_status=True):
                 neighbors = self.graph.predecessors(u)
 
             if u_status == 0:  # Susceptible
-                infected_neighbors = len([v for v in neighbors if self.status[v] == 2 or self.status[v] == 1])
-                if eventp < self.params['model']['beta'] * infected_neighbors:
+                triggered = 1 if len([v for v in neighbors if self.status[v] == 1]) > 0 else 0
+
+                if eventp < self.params['model']['beta'] * triggered:
                     actual_status[u] = 2  # Exposed
                     self.progress[u] = 0
 

diff --git a/ndlib/models/epidemics/SEISModel.py b/ndlib/models/epidemics/SEISModel.py
@@ -80,8 +80,9 @@ def iteration(self, node_status=True):
                 neighbors = self.graph.predecessors(u)
 
             if u_status == 0:  # Susceptible
-                infected_neighbors = len([v for v in neighbors if self.status[v] == 2 or self.status[v] == 1])
-                if eventp < self.params['model']['beta'] * infected_neighbors:
+                triggered = 1 if len([v for v in neighbors if self.status[v] == 1]) > 0 else 0
+
+                if eventp < self.params['model']['beta'] * triggered:
                     actual_status[u] = 2  # Exposed
                     self.progress[u] = 0
 

diff --git a/ndlib/models/epidemics/SIModel.py b/ndlib/models/epidemics/SIModel.py
@@ -68,8 +68,9 @@ def iteration(self, node_status=True):
                 neighbors = self.graph.predecessors(u)
 
             if u_status == 0:
-                infected_neighbors = len([v for v in neighbors if self.status[v] == 1])
-                if eventp < self.params['model']['beta'] * infected_neighbors:
+                triggered = 1 if len([v for v in neighbors if self.status[v] == 1]) > 0 else 0
+
+                if eventp < self.params['model']['beta'] * triggered:
                     actual_status[u] = 1
 
         delta, node_count, status_delta = self.status_delta(actual_status)

diff --git a/ndlib/models/epidemics/SIRModel.py b/ndlib/models/epidemics/SIRModel.py
@@ -76,8 +76,9 @@ def iteration(self, node_status=True):
                 neighbors = self.graph.predecessors(u)
 
             if u_status == 0:
-                infected_neighbors = len([v for v in neighbors if self.status[v] == 1])
-                if eventp < self.params['model']['beta'] * infected_neighbors:
+                triggered = 1 if len([v for v in neighbors if self.status[v] == 1]) > 0 else 0
+
+                if eventp < self.params['model']['beta'] * triggered:
                     actual_status[u] = 1
             elif u_status == 1:
                 if eventp < self.params['model']['gamma']:

diff --git a/ndlib/models/epidemics/SISModel.py b/ndlib/models/epidemics/SISModel.py
@@ -75,8 +75,9 @@ def iteration(self, node_status=True):
                 neighbors = self.graph.predecessors(u)
 
             if u_status == 0:
-                infected_neighbors = len([v for v in neighbors if self.status[v] == 1])
-                if eventp < self.params['model']['beta'] * infected_neighbors:
+                triggered = 1 if len([v for v in neighbors if self.status[v] == 1]) > 0 else 0
+
+                if eventp < self.params['model']['beta'] * triggered:
                     actual_status[u] = 1
             elif u_status == 1:
                 if eventp < self.params['model']['lambda']: