install instructions and formatting

README.md

@@ -22,7 +22,7 @@ micromamba create -f environment.yml
 micromamba activate seldonenv
 ```
 
-### Compilation
+### Compilation and Installation
 
 We use `meson` to compile and build Seldon. 
 
@@ -31,6 +31,13 @@ meson setup build
 meson compile -C build
 ```
 
+To install `seldon` to your `conda` environment, run the following:
+
+```bash
+meson setup build --prefix $CONDA_PREFIX
+meson install -C build
+```
+
 ### Quick Start 
 
 Run the executable, and provide the input configuration TOML file (as the first
@@ -41,6 +48,12 @@ cd build
 ./seldon /path/to/config -o /path/to/output/dir
 ``` 
 
+If you've installed it, you can simply run `seldon` anywhere.
+
+```bash
+seldon /path/to/config -o /path/to/output/dir
+```
+
 #### Output files
 The file `network.txt` contains information about the network. 
 First column is the index of the agent, then the next column is the number of incoming agent connections *including* the agent itself. Subsequent columns are the neighbouring incoming agent indices and weights. In addition, every iteration produces a *double* opinion value for each agent. These are outputted to files named opinions_i.txt.

src/models/ActivityDrivenModel.cpp

@@ -52,7 +52,8 @@ void Seldon::ActivityAgentModel::update_network_probabilistic()
         {
             // Implement the weight for the probability of agent `idx_agent` contacting agent `j`
             // Not normalised since this is taken care of by the reservoir sampling
-            auto weight_callback = [idx_agent, this]( size_t j ) {
+            auto weight_callback = [idx_agent, this]( size_t j )
+            {
                 if( idx_agent == j ) // The agent does not contact itself
                     return 0.0;
                 return std::pow(
@@ -111,7 +112,8 @@ void Seldon::ActivityAgentModel::update_network_mean()
         contact_prob_list[idx_agent] = weights; // set to zero
     }
 
-    auto probability_helper = []( double omega, size_t m ) {
+    auto probability_helper = []( double omega, size_t m )
+    {
         double p = 0;
         for( size_t i = 1; i <= m; i++ )
             p += ( std::pow( -omega, i + 1 ) + omega ) / ( omega + 1 );
@@ -122,7 +124,8 @@ void Seldon::ActivityAgentModel::update_network_mean()
     {
         // Implement the weight for the probability of agent `idx_agent` contacting agent `j`
         // Not normalised since this is taken care of by the reservoir sampling
-        auto weight_callback = [idx_agent, this]( size_t j ) {
+        auto weight_callback = [idx_agent, this]( size_t j )
+        {
             if( idx_agent == j ) // The agent does not contact itself
                 return 0.0;
             return std::pow(