ActivityDrivenModel: Unit test includes reluctance

We modified the unit test with one bot and one agent to now include the reluctance (of the agent). Co-authored-by: Moritz Sallermann <[email protected]>
seldon-code · Mar 16, 2024 · 01f3af7 · 01f3af7
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diff --git a/test/res/1bot_1agent_activity_prob.toml b/test/res/1bot_1agent_activity_prob.toml
@@ -22,6 +22,12 @@ K = 2.0                 # Social interaction strength
 mean_activities = false # Use the mean value of the powerlaw distribution for the activities of all agents
 mean_weights = false    # Use the meanfield approximation of the network edges
 
+reluctances = true 			# Assigns a "reluctance" (m_i) to each agent. By default; false and every agent has a reluctance of 1
+reluctance_mean   = 1.5 	# Mean of distribution before drawing from a truncated normal distribution (default set to 1.0)
+reluctance_sigma  = 2.5 	# Width of normal distribution (before truncating)
+reluctance_eps    = 0.01 	# Minimum such that the normal distribution is truncated at this value
+covariance_factor = 0.25 	# Determines whether activities and reluctances will be correlated. If set to 0.0 (default) then they will not be correlated.
+
 n_bots = 1 # The number of bots to be used; if not specified defaults to 0 (which means bots are deactivated)
 # Bots are agents with fixed opinions and different parameters, the parameters are specified in the following lists
 # If n_bots is smaller than the length of any of the lists, the first n_bots entries are used. If n_bots is greater the code will throw an exception.

diff --git a/test/test_activity.cpp b/test/test_activity.cpp
@@ -85,7 +85,9 @@ TEST_CASE( "Test the probabilistic activity driven model for two agents", "[acti
     }
 }
 
-TEST_CASE( "Test the probabilistic activity driven model with one bot and one agent", "[activity1Bot1Agent]" )
+TEST_CASE(
+    "Test the probabilistic activity driven model with one bot and one (reluctant) agent",
+    "[activity1Bot1AgentReluctance]" )
 {
     using namespace Seldon;
     using namespace Catch::Matchers;
@@ -122,16 +124,20 @@ TEST_CASE( "Test the probabilistic activity driven model with one bot and one ag
     auto time_elapsed   = iterations * dt;
 
     // Final agent and bot opinions after the simulation run
-    auto x_t     = agent.data.opinion;
-    auto x_t_bot = bot.data.opinion;
+    auto x_t        = agent.data.opinion;
+    auto x_t_bot    = bot.data.opinion;
+    auto reluctance = agent.data.reluctance;
+
+    fmt::print( "Agent reluctance is = {}\n", reluctance );
 
     // The bot opinion should not change during the simulation
     REQUIRE_THAT( x_t_bot, WithinAbs( x_bot, 1e-16 ) );
 
     // Test that the agent opinion matches the analytical solution for an agent with a bot
     // Analytical solution is:
     // x_t = [x(0) - Ktanh(alpha*x_bot)]e^(-t) + Ktanh(alpha*x_bot)
-    auto x_t_analytical = ( x_0 - K * tanh( alpha * x_bot ) ) * exp( -time_elapsed ) + K * tanh( alpha * x_bot );
+    auto x_t_analytical = ( x_0 - K / reluctance * tanh( alpha * x_bot ) ) * exp( -time_elapsed )
+                          + K / reluctance * tanh( alpha * x_bot );
 
     REQUIRE_THAT( x_t, WithinAbs( x_t_analytical, 1e-5 ) );
 }