Random "division by zero" error

[Mihai Banciu]

Minimal working example:

from seirsplus.models import *
from seirsplus.networks import *
import networkx as nx

graph = nx.barabasi_albert_graph(n=500, m=10)
graph = custom_exponential_graph(graph)

base_model = SEIRSNetworkModel(G=graph, 
                               beta=0.25, 
                               sigma=1/5, 
                               gamma=1/15,
                               initE=10)
base_model.run(T=100)

Code produces the following error occasionally; interestingly enough the same error shows up in the model wiki example (line 6):

seirsplus\models.py:838: RuntimeWarning: divide by zero encountered in log
  self.delta               = numpy.log(self.degree)/numpy.log(numpy.mean(self.degree))     if self.parameters['delta'] is None   else numpy.array(self.parameters['delta'])   if isinstance(self.parameters['delta'], (list, numpy.ndarray))   else numpy.full(fill_value=self.parameters['delta'], shape=(self.numNodes,1))
seirsplus\models.py:839: RuntimeWarning: divide by zero encountered in log
  self.delta_Q             = numpy.log(self.degree_Q)/numpy.log(numpy.mean(self.degree_Q)) if self.parameters['delta_Q'] is None else numpy.array(self.parameters['delta_Q']) if isinstance(self.parameters['delta_Q'], (list, numpy.ndarray)) else numpy.full(fill_value=self.parameters['delta_Q'], shape=(self.numNodes,1))

I believe the randomness comes from the way custom_exponential_graph modifies the original graph. One might have to run the code several times to reproduce the issue.

[Ryan Seamus McGee]

This is a warning coming from taking the log of 0 when calculating the delta parameter for node(s) with 0 degree (which can happen when you call custom_exponential_graph on a network). This warning wasn't affecting the execution of the model, but I've updated the relevant lines to handle the log calculation more cleanly and do a resulting value check. Thanks for prompting this improvement.