ActivityDrivenModel: Use the copula

Use the copula to generate correlated activities and reluctances.

Co-authored-by: Amrita Goswami <[email protected]>

src/models/ActivityDrivenModel.cpp

@@ -69,6 +69,8 @@ void ActivityDrivenModel::get_agents_from_power_law()
     power_law_distribution<> dist_activity( eps, gamma );
     truncated_normal_distribution<> dist_reluctance( reluctance_mean, reluctance_sigma, reluctance_eps );
 
+    bivariate_gaussian_copula copula( covariance_factor, dist_activity, dist_reluctance );
+
     auto mean_activity = dist_activity.mean();
 
     // Initial conditions for the opinions, initialize to [-1,1]
@@ -77,18 +79,16 @@ void ActivityDrivenModel::get_agents_from_power_law()
     {
         network.agents[i].data.opinion = dis_opinion( gen ); // Draw the opinion value
 
-        if( !mean_activities )
-        { // Draw from a power law distribution (1-gamma)/(1-eps^(1-gamma)) * a^(-gamma)
-            network.agents[i].data.activity = dist_activity( gen );
-        }
-        else
-        {
-            network.agents[i].data.activity = mean_activity;
-        }
+        auto res                        = copula( gen );
+        network.agents[i].data.activity = res[0];
 
         if( use_reluctances )
         {
-            network.agents[i].data.reluctance = dist_reluctance( gen );
+            network.agents[i].data.reluctance = res[1];
+        }
+        if( mean_activities )
+        {
+            network.agents[i].data.activity = mean_activity;
         }
     }