Merge pull request #820 from UWB-Biocomputing/SainiSTDPDevelopment

jasleenksaini · web-flow · commit 004f58ccb6e1 · 2025-03-19T13:53:22.000-07:00
[ISSUE-734] Add full graph for STDP simulations
diff --git a/Simulator/Connections/Neuro/ConnStatic.cpp b/Simulator/Connections/Neuro/ConnStatic.cpp
@@ -1,16 +1,16 @@
 /**
- * @file ConnStatic.cpp
- *
- * @ingroup Simulator/Connections
- * 
- * @brief The model of the small world network
- */
-
+* @file ConnStatic.cpp
+*
+* @ingroup Simulator/Connections/Neuro
+* 
+* @brief This class manages the Connections of the Neuro STDP network
+*/
 
 #include "ConnStatic.h"
 #include "AllEdges.h"
 #include "AllNeuroEdges.h"
 #include "AllVertices.h"
+#include "GraphManager.h"
 #include "OperationManager.h"
 #include "ParameterManager.h"
 #include "ParseParamError.h"
@@ -22,129 +22,70 @@
 
 #include <algorithm>
 
+/// @brief Default constructor for ConnStatic
 ConnStatic::ConnStatic()
 {
-   threshConnsRadius_ = 0;
-   connsPerVertex_ = 0;
-   rewiringProbability_ = 0;
-   radiiSize_ = 0;
 }
 
-///  Setup the internal structure of the class (allocate memories and initialize them).
-///  Initialize the small world network characterized by parameters:
-///  number of maximum connections per vertex, connection radius threshold, and
-///  small-world rewiring probability.
+/// @brief Set up the connections in the network
 void ConnStatic::setup()
 {
-   // we can obtain the Layout, which holds the vertices, from the Model
+   int added = 0;
+   LOG4CPLUS_INFO(fileLogger_, "Initializing connections");
+
+   // Obtain Vertices and Layout from the Model
    Layout &layout = Simulator::getInstance().getModel().getLayout();
    AllVertices &vertices = layout.getVertices();
-
-   Simulator &simulator = Simulator::getInstance();
-   int numVertices = simulator.getTotalVertices();
-   vector<DistDestVertex> distDestVertices[numVertices];
-   BGSIZE maxTotalEdges = simulator.getMaxEdgesPerVertex() * simulator.getTotalVertices();
-   WCurrentEpoch_.resize(maxTotalEdges);
-   sourceVertexIndexCurrentEpoch_.resize(maxTotalEdges);
-   destVertexIndexCurrentEpoch_.resize(maxTotalEdges);
+   // All Edges object for Connections
    AllNeuroEdges &neuroEdges = dynamic_cast<AllNeuroEdges &>(*edges_);
 
-   radiiSize_ = numVertices;
-   int added = 0;
 
-   LOG4CPLUS_INFO(fileLogger_, "Initializing connections");
+   // Iterator to traverse edges
+   GraphManager<NeuralVertexProperties>::EdgeIterator ei, ei_end;
+   GraphManager<NeuralVertexProperties> &gm = GraphManager<NeuralVertexProperties>::getInstance();
 
-   for (int srcVertex = 0; srcVertex < numVertices; srcVertex++) {
-      distDestVertices[srcVertex].clear();
-
-      // pick the connections shorter than threshConnsRadius
-      for (int destVertex = 0; destVertex < numVertices; destVertex++) {
-         if (srcVertex != destVertex) {
-            BGFLOAT dist = layout.dist_(srcVertex, destVertex);
-            if (dist <= threshConnsRadius_) {
-               DistDestVertex distDestVertex {dist, destVertex};
-               distDestVertices[srcVertex].push_back(distDestVertex);
-            }
-         }
-      }
-
-      // sort ascendant
-      sort(distDestVertices[srcVertex].begin(), distDestVertices[srcVertex].end());
-      // pick the shortest connsPerVertex_ connections
-      for (BGSIZE i = 0; i < distDestVertices[srcVertex].size() && (int)i < connsPerVertex_; i++) {
-         int destVertex = distDestVertices[srcVertex][i].destVertex;
-         edgeType type = layout.edgType(srcVertex, destVertex);
-
-         LOG4CPLUS_DEBUG(fileLogger_,
-                         "Source: " << srcVertex << " Dest: " << destVertex
-                                    << " Dist: " << distDestVertices[srcVertex][i].dist);
-
-         BGSIZE iEdg = edges_->addEdge(type, srcVertex, destVertex, simulator.getDeltaT());
-         added++;
-
-         // set edge weight
-         // TODO: we need another synaptic weight distibution mode (normal distribution)
-         if (neuroEdges.edgSign(type) > 0) {
-            neuroEdges.W_[iEdg] = initRNG.inRange(excWeight_[0], excWeight_[1]);
-         } else {
-            neuroEdges.W_[iEdg] = initRNG.inRange(inhWeight_[0], inhWeight_[1]);
-         }
-      }
-   }
-
-   string weight_str = "";
-   for (int i = 0; i < maxTotalEdges; i++) {
-      WCurrentEpoch_[i] = neuroEdges.W_[i];
-      sourceVertexIndexCurrentEpoch_[i] = neuroEdges.sourceVertexIndex_[i];
-      destVertexIndexCurrentEpoch_[i] = neuroEdges.destVertexIndex_[i];
+   // Initialize GraphManager and iterate through edges
+   for (boost::tie(ei, ei_end) = gm.edges(); ei != ei_end; ++ei) {
+      int srcVertex = gm.source(*ei);
+      int destVertex = gm.target(*ei);
+      double weight = gm.weight(*ei);
+      edgeType type = layout.edgType(srcVertex, destVertex);
+      BGFLOAT dist = layout.dist_(srcVertex, destVertex);
 
-      if (WCurrentEpoch_[i] != 0) {
-         // LOG4CPLUS_DEBUG(edgeLogger_,i << WCurrentEpoch_[i]);
-         weight_str += to_string(WCurrentEpoch_[i]) + " ";
-      }
-   }
-   // LOG4CPLUS_DEBUG(edgeLogger_, "Weights are " << weight_str);
+      // Debug
+      // cout <<  "Source: " << srcVertex << " Dest: " << destVertex << " Dist: " << dist << " Weight: " << weight << endl;
 
-   int nRewiring = added * rewiringProbability_;
+      // Log edge data
+      LOG4CPLUS_DEBUG(edgeLogger_, "Source: " << srcVertex << ", Dest: " << destVertex
+                                              << ", Dist: " << dist << ", Weight: " << weight);
 
-   LOG4CPLUS_DEBUG(fileLogger_, "Rewiring connections: " << nRewiring);
+      // Add edge and store weight
+      BGSIZE iEdg
+         = edges_->addEdge(type, srcVertex, destVertex, Simulator::getInstance().getDeltaT());
+      neuroEdges.W_[iEdg] = weight;
+      added++;
+   }
 
+   // Log the total number of connections added
    LOG4CPLUS_DEBUG(fileLogger_, "Added connections: " << added);
+}
 
-   // Register variable weight if need
-   // Recorder &recorder = Simulator::getInstance().getModel().getRecorder();
-   // recorder.registerVariable("weight", WCurrentEpoch_, Recorder::UpdatedType::DYNAMIC);
+/// @brief Register graph properties to NeuralVertexProperties
+void ConnStatic::registerGraphProperties()
+{
+   Connections::registerGraphProperties();
+   GraphManager<NeuralVertexProperties> &gm = GraphManager<NeuralVertexProperties>::getInstance();
+   gm.registerProperty("source", &NeuralEdgeProperties::source);
+   gm.registerProperty("target", &NeuralEdgeProperties::target);
+   gm.registerProperty("weight", &NeuralEdgeProperties::weight);
 }
 
-/// Load member variables from configuration file.
-/// Registered to OperationManager as Operations::op::loadParameters
+/// @brief Loads parameters related to connections
 void ConnStatic::loadParameters()
 {
-   ParameterManager::getInstance().getBGFloatByXpath("//threshConnsRadius/text()",
-                                                     threshConnsRadius_);
-   ParameterManager::getInstance().getIntByXpath("//connsPerNeuron/text()", connsPerVertex_);
-   ParameterManager::getInstance().getBGFloatByXpath("//rewiringProbability/text()",
-                                                     rewiringProbability_);
-   //ParameterManager::getInstance().getBGFloatByXpath("//excWeight/min/text()", excWeight_[0]);
-   //ParameterManager::getInstance().getBGFloatByXpath("//excWeight/max/text()", excWeight_[1]);
-   //ParameterManager::getInstance().getBGFloatByXpath("//inhWeight/min/text()", inhWeight_[0]);
-   //ParameterManager::getInstance().getBGFloatByXpath("//inhWeight/max/text()", inhWeight_[1]);
 }
 
-///  Prints out all parameters to logging file.
-///  Registered to OperationManager as Operation::printParameters
+/// @brief Prints the parameters of the connection
 void ConnStatic::printParameters() const
 {
-   LOG4CPLUS_DEBUG(fileLogger_, "CONNECTIONS PARAMETERS"
-                                   << endl
-                                   << "\tConnections Type: ConnStatic" << endl
-                                   << "\tConnection radius threshold: " << threshConnsRadius_
-                                   << endl
-                                   << "\tConnections per neuron: " << connsPerVertex_ << endl
-                                   << "\tRewiring probability: " << rewiringProbability_ << endl
-                                   << "\tExhitatory min weight: " << excWeight_[0] << endl
-                                   << "\tExhitatory max weight: " << excWeight_[1] << endl
-                                   << "\tInhibitory min weight: " << inhWeight_[0] << endl
-                                   << "\tInhibitory max weight: " << inhWeight_[1] << endl
-                                   << endl);
 }
diff --git a/Simulator/Connections/Neuro/ConnStatic.h b/Simulator/Connections/Neuro/ConnStatic.h
@@ -17,10 +17,6 @@
  * every neighbor of \f$v\f$ is connected to every other neighbor of \f$v\f$).
  * Let \f$C_v\f$ denote the fracion of these allowable edges that actually exist.
  * Define \f$C\f$ as the average of \f$C_v\f$ overall \f$v\f$ (Watts et al. 1998).
- *
- * We first create a regular network characterized by two parameters: the number of maximum 
- * connections per neuron and connection radius threshold, then rewire it according 
- * to the small-world rewiring probability.
  */
 
 #pragma once
@@ -48,6 +44,9 @@ class ConnStatic : public Connections {
       return new ConnStatic();
    }
 
+   /// Register vertex properties with the GraphManager
+   virtual void registerGraphProperties() override;
+
    ///  Setup the internal structure of the class (allocate memories and initialize them).
    ///  Initialize the small world network characterized by parameters:
    ///  number of maximum connections per vertex, connection radius threshold, and
@@ -62,12 +61,6 @@ class ConnStatic : public Connections {
    ///  Registered to OperationManager as Operation::printParameters
    virtual void printParameters() const override;
 
-   ///  Get connection radius threshold
-   BGFLOAT getConnsRadiusThresh() const
-   {
-      return threshConnsRadius_;
-   }
-
    /// Get array of vertex weights
    const vector<BGFLOAT> &getWCurrentEpoch() const
    {
@@ -102,24 +95,6 @@ class ConnStatic : public Connections {
    RecordableVector<BGFLOAT> WCurrentEpoch_;
    // vector<BGFLOAT> WCurrentEpoch_;
 
-   /// radii size （2020/2/13 add radiiSize for use in serialization/deserialization)
-   int radiiSize_;
-
-   /// number of maximum connections per vertex
-   int connsPerVertex_;
-
-   /// Connection radius threshold
-   BGFLOAT threshConnsRadius_;
-
-   /// Small-world rewiring probability
-   BGFLOAT rewiringProbability_;
-
-   /// Min/max values of excitatory neuron's synapse weight
-   BGFLOAT excWeight_[2];
-
-   /// Min/max values of inhibitory neuron's synapse weight
-   BGFLOAT inhWeight_[2];
-
    struct DistDestVertex {
       BGFLOAT dist;     ///< distance to the destination vertex
       int destVertex;   ///< index of the destination vertex
@@ -139,10 +114,5 @@ template <class Archive> void ConnStatic::serialize(Archive &archive)
    archive(cereal::base_class<Connections>(this),
            cereal::make_nvp("sourceVertexIndexCurrentEpoch", sourceVertexIndexCurrentEpoch_),
            cereal::make_nvp("destVertexIndexCurrentEpoch", destVertexIndexCurrentEpoch_),
-           cereal::make_nvp("WCurrentEpoch", WCurrentEpoch_),
-           cereal::make_nvp("radiiSize", radiiSize_),
-           cereal::make_nvp("connsPerVertex", connsPerVertex_),
-           cereal::make_nvp("threshConnsRadius", threshConnsRadius_),
-           cereal::make_nvp("rewiringProbability", rewiringProbability_),
-           cereal::make_nvp("excWeight", excWeight_), cereal::make_nvp("inhWeight", inhWeight_));
+           cereal::make_nvp("WCurrentEpoch", WCurrentEpoch_));
 }
diff --git a/Simulator/Core/Core.cpp b/Simulator/Core/Core.cpp
@@ -146,21 +146,25 @@ int Core::runSimulation(string executableName, string cmdLineArguments)
    }
 
    // Ask all objects to register their Graph properties
+   LOG4CPLUS_TRACE(consoleLogger, "Registering Graph Properties");
    OperationManager::getInstance().executeOperation(Operations::registerGraphProperties);
 
    // Retrieve class attribute from the 'LayoutParams' in the config file
    // This value indicate the simulation type (Neural or NG911) for graph manager configuration
    // Log fatal error if no simulation type is found and terminate
+   // Retrieve class attribute from the 'LayoutParams' in the config file
+   // This value indicates the simulation type (Neural or NG911) for graph manager configuration
+
    string configData;
    ParameterManager::getInstance().getStringByXpath("//LayoutParams/@class", configData);
-
-   if (configData.find("Neur")) {
+   if (configData == "LayoutNeuro") {
       GraphManager<NeuralVertexProperties>::getInstance().readGraph();
-   }
-   if (configData.find("91")) {
+      LOG4CPLUS_TRACE(consoleLogger, "Reading Neural Vertex Properties");
+   } else if (configData.find("Layout911") != std::string::npos) {
       GraphManager<NG911VertexProperties>::getInstance().readGraph();
+      LOG4CPLUS_TRACE(consoleLogger, "Reading NG911 Vertex Properties");
    } else {
-      LOG4CPLUS_FATAL(consoleLogger, "ERROR: Unknown simulation type'");
+      LOG4CPLUS_FATAL(consoleLogger, "ERROR: Unknown simulation type");
       return -1;
    }
 
diff --git a/Simulator/Utils/Global.h b/Simulator/Utils/Global.h
@@ -286,11 +286,14 @@ struct NeuralVertexProperties : public VertexProperties {
    bool active;
 };
 
-/// @brief  The structure to hold the edge properties
-struct EdgeProperties {
-   // TODO: Edge Properties
+/// @brief The structure to hold the edge properties
+struct NeuralEdgeProperties {
+   int source;
+   int target;
+   double weight;
 };
 
+
 /// @brief The structure to hold the Graph properties
 struct GraphProperties {
    // TODO: Graph Properties
diff --git a/Simulator/Utils/GraphManager.h b/Simulator/Utils/GraphManager.h
@@ -52,7 +52,7 @@ template <typename VertexProperties> class GraphManager {
 public:
    /// Using directive for graphml graph type (adjacency list)
    using Graph = boost::adjacency_list<boost::vecS, boost::vecS, boost::directedS, VertexProperties,
-                                       EdgeProperties, GraphProperties>;
+                                       NeuralEdgeProperties, GraphProperties>;
 
    using EdgeIterator = typename boost::graph_traits<Graph>::edge_iterator;
    using VertexIterator = typename boost::graph_traits<Graph>::vertex_iterator;
@@ -109,6 +109,11 @@ template <typename VertexProperties> class GraphManager {
    /// @return the target vertex index for the given Edge
    size_t target(const EdgeDescriptor &edge) const;
 
+   /// @brief Retrieves the weight of an edge
+   /// @param edge the EdgeDescriptor
+   /// @return the weight of the given edge
+   double weight(const EdgeDescriptor &edge) const;
+
    /// @brief Direct access to the VertexProperties of a vertex descriptor
    /// @param vertex   the vertex descriptor (index)
    /// @return the VertexProperties of the vertex descriptor
@@ -175,7 +180,6 @@ template <typename VertexProperties> bool GraphManager<VertexProperties>::readGr
 
    // If graphFilePath_ isn't already defined, get it from ParameterManager
    if (graphFilePath_ == "") {
-      // string file_name;
       string path = "//graphmlFile/text()";
       if (!ParameterManager::getInstance().getStringByXpath(path, graphFilePath_)) {
          cerr << "Could not find XML path: " << path << ".\n";
@@ -233,6 +237,16 @@ size_t GraphManager<VertexProperties>::target(
    return boost::target(edge, graph_);
 }
 
+/// @brief Retrieves the weight of an edge
+/// @param edge the EdgeDescriptor
+/// @return the weight of the given edge
+template <typename VertexProperties>
+double GraphManager<VertexProperties>::weight(
+   const typename GraphManager<VertexProperties>::EdgeDescriptor &edge) const
+{
+   return boost::get(&NeuralEdgeProperties::weight, graph_, edge);
+}
+
 /// @brief Directly access the VertexProperties of a vertex descriptor.
 /// @param vertex The vertex descriptor (index).
 /// @return The VertexProperties of the vertex.
diff --git a/configfiles/graphs/test-tiny.graphml b/configfiles/graphs/test-tiny.graphml
@@ -4,6 +4,7 @@
   <key id="active" for="node" attr.name="active" attr.type="boolean" />
   <key id="y" for="node" attr.name="y" attr.type="double" />
   <key id="x" for="node" attr.name="x" attr.type="double" />
+  <key id="weight" for="edge" attr.name="weight" attr.type="double" />
   <graph edgedefault="directed">
     <node id="0">
       <data key="x">0</data>
@@ -29,5 +30,17 @@
       <data key="active">0</data>
       <data key="type">EXC</data>
     </node>
+    <edge id="e1" source="0" target="1">
+      <data key="weight">5.0e-9</data>
+    </edge>
+    <edge id="e2" source="1" target="2">
+      <data key="weight">-3.2e-8</data>
+    </edge>
+    <edge id="e3" source="2" target="3">
+      <data key="weight">3.3e-8</data>
+    </edge>
+    <edge id="e4" source="3" target="0">
+      <data key="weight">6.4e-8</data>
+    </edge>
   </graph>
 </graphml>
diff --git a/configfiles/test-tiny-stdp.xml b/configfiles/test-tiny-stdp.xml
diff --git a/docs/Developer/GraphAndEventInputs.md b/docs/Developer/GraphAndEventInputs.md
