Deffuant: Implemented the update rule in the vector model

Also hacked in the generation of the initial agents by hardcoding the dimensionality <--- TODO Co-authored-by: Amrita Goswami <[email protected]>
seldon-code · Mar 21, 2024 · 42a1837 · 42a1837
1 parent c19efbc
commit 42a1837
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Showing 3 changed files with 44 additions and 12 deletions.
diff --git a/include/agents/discrete_vector_agent.hpp b/include/agents/discrete_vector_agent.hpp
@@ -42,9 +42,8 @@ inline DiscreteVectorAgent agent_from_string<DiscreteVectorAgent>( const std::st
 {
     DiscreteVectorAgent res{};
 
-    auto callback = [&]( int idx_list [[maybe_unused]], const auto & substring ) {
-        res.data.opinion.push_back( std::stoi( substring ) );
-    };
+    auto callback = [&]( int idx_list [[maybe_unused]], const auto & substring )
+    { res.data.opinion.push_back( std::stoi( substring ) ); };
 
     parse_comma_separated_list( str, callback );
     return res;

diff --git a/src/models/DeffuantModelVector.cpp b/src/models/DeffuantModelVector.cpp
@@ -1,7 +1,9 @@
+#include "agent.hpp"
 #include "agents/discrete_vector_agent.hpp"
 #include "models/DeffuantModel.hpp"
-#include <cmath>
+#include "util/math.hpp"
 #include <cstddef>
+#include <random>
 #include <vector>
 
 namespace Seldon
@@ -10,23 +12,53 @@ namespace Seldon
 template<>
 void DeffuantModelAbstract<DiscreteVectorAgent>::initialize_agents()
 {
+    std::uniform_int_distribution<int> dist( 0, 1 );
+    int dim = 5;
+
     for( size_t i = 0; i < network.agents.size(); i++ )
     {
-        // network.agents[i].data.opinion = double( i ) / double( network.agents.size() );
+        auto & opinion = network.agents[i].data.opinion;
+        opinion.resize( dim );
+        for( auto & o : opinion )
+        {
+            o = dist( gen );
+        }
     }
 }
 
 template<>
 void DeffuantModelAbstract<DiscreteVectorAgent>::update_rule( AgentT & agent1, AgentT & agent2 )
 {
+    size_t dim      = agent1.data.opinion.size();
+    auto & opinion1 = agent1.data.opinion;
+    auto & opinion2 = agent2.data.opinion;
+
+    auto distance = hamming_distance( std::span( opinion1 ), std::span( opinion2 ) );
+
+    std::uniform_int_distribution<> dist_pair( 0, 1 );
+    std::uniform_real_distribution<> dist_convince( 0, 1 );
+
     // Update rule
-    // auto opinion_diff = agent1.data.opinion - agent2.data.opinion;
     // Only if less than homophily_threshold
-    // if( std::abs( opinion_diff ) < homophily_threshold )
-    // {
-        // agent1.data.opinion -= mu * opinion_diff;
-    //     agent2.data.opinion += mu * opinion_diff;
-    // }
+    if( distance < homophily_threshold )
+    {
+        for( size_t idx_opinion = 0; idx_opinion < dim; idx_opinion++ )
+        {
+            if( opinion1[idx_opinion] != opinion2[idx_opinion] )
+            {
+                // randomly select one of the
+                auto idx_selected = dist_pair( gen );
+                if( idx_selected == 0 && mu < dist_convince( gen ) )
+                {
+                    opinion1[idx_opinion] = opinion2[idx_opinion];
+                }
+                else
+                {
+                    opinion2[idx_opinion] = opinion1[idx_opinion];
+                }
+            }
+        }
+    }
 }
 
 template class DeffuantModelAbstract<DiscreteVectorAgent>;

diff --git a/test/test_util.cpp b/test/test_util.cpp
@@ -16,7 +16,8 @@ TEST_CASE( "Test parse_comma_separated_list", "[util_parse_list]" )
     std::vector<double> dbl_vec_expected = { -2.0, 13.0 };
     std::vector<int> int_vec_expected    = { 12, 10 };
 
-    auto callback = [&]( int idx_list, std::string & substr ) {
+    auto callback = [&]( int idx_list, std::string & substr )
+    {
         if( idx_list == 0 || idx_list == 3 )
         {
             int_vec.push_back( std::stoi( substr ) );