propagation: Fix valgrind error in JakesPropagationLossModel

src/propagation/examples/main-propagation-loss.cc

@@ -53,7 +53,7 @@ static double dround (double number, double precision)
 }
 
 static Gnuplot
-TestDeterministic (Ptr<PropagationLossModel> model)
+TestDeterministic (Ptr<PropagationLossModel> model, double targetDistance, double step)
 {
   Ptr<ConstantPositionMobilityModel> a = CreateObject<ConstantPositionMobilityModel> ();
   Ptr<ConstantPositionMobilityModel> b = CreateObject<ConstantPositionMobilityModel> ();
@@ -73,7 +73,7 @@ TestDeterministic (Ptr<PropagationLossModel> model)
   {
     a->SetPosition (Vector (0.0, 0.0, 0.0));
 
-    for (double distance = 0.0; distance < 2500.0; distance += 10.0)
+    for (double distance = 0.0; distance < targetDistance; distance += step)
       {
         b->SetPosition (Vector (distance, 0.0, 0.0));
 
@@ -99,7 +99,7 @@ TestDeterministic (Ptr<PropagationLossModel> model)
 }
 
 static Gnuplot
-TestProbabilistic (Ptr<PropagationLossModel> model, unsigned int samples = 100000)
+TestProbabilistic (Ptr<PropagationLossModel> model, double targetDistance, double step, unsigned int samples)
 {
   Ptr<ConstantPositionMobilityModel> a = CreateObject<ConstantPositionMobilityModel> ();
   Ptr<ConstantPositionMobilityModel> b = CreateObject<ConstantPositionMobilityModel> ();
@@ -131,7 +131,7 @@ TestProbabilistic (Ptr<PropagationLossModel> model, unsigned int samples = 10000
   {
     a->SetPosition (Vector (0.0, 0.0, 0.0));
 
-    for (double distance = 100.0; distance < 2500.0; distance += 100.0)
+    for (double distance = 100.0; distance < targetDistance; distance += step)
       {
         b->SetPosition (Vector (distance, 0.0, 0.0));
 
@@ -169,9 +169,9 @@ TestProbabilistic (Ptr<PropagationLossModel> model, unsigned int samples = 10000
 
 static Gnuplot
 TestDeterministicByTime (Ptr<PropagationLossModel> model,
-                         Time timeStep = Seconds (0.001),
-                         Time timeTotal = Seconds (1.0),
-                         double distance = 100.0)
+                         Time timeStep,
+                         Time timeTotal,
+                         double distance)
 {
   Ptr<ConstantPositionMobilityModel> a = CreateObject<ConstantPositionMobilityModel> ();
   Ptr<ConstantPositionMobilityModel> b = CreateObject<ConstantPositionMobilityModel> ();
@@ -219,15 +219,32 @@ TestDeterministicByTime (Ptr<PropagationLossModel> model,
 
 int main (int argc, char *argv[])
 {
+  bool test = false;
   CommandLine cmd (__FILE__);
+  cmd.AddValue ("test", "Run as a test, sample the models only once", test);
   cmd.Parse (argc, argv);
 
+  double testDeterministicDistance = 2500.0;
+  double testProbabilisticDistance = 2500.0;
+  unsigned int testProbabilisticSamples = 100000;
+  Time testJakesTimeOneMsRes = Seconds (1.0);
+  Time testJakesTimeZeroDotOneMsRes = Seconds (0.1);
+
+  if (test)
+    {
+      testDeterministicDistance = 10;
+      testProbabilisticDistance = 200;
+      testProbabilisticSamples = 1;
+      testJakesTimeOneMsRes = Seconds (0.001);
+      testJakesTimeZeroDotOneMsRes = Seconds (0.0001);
+    }
+
   GnuplotCollection gnuplots ("main-propagation-loss.pdf");
 
   {
     Ptr<FriisPropagationLossModel> friis = CreateObject<FriisPropagationLossModel> ();
 
-    Gnuplot plot = TestDeterministic (friis);
+    Gnuplot plot = TestDeterministic (friis, testDeterministicDistance, 10.0);
     plot.SetTitle ("ns3::FriisPropagationLossModel (Default Parameters)");
     gnuplots.AddPlot (plot);
   }
@@ -236,7 +253,7 @@ int main (int argc, char *argv[])
     Ptr<LogDistancePropagationLossModel> log = CreateObject<LogDistancePropagationLossModel> ();
     log->SetAttribute ("Exponent", DoubleValue (2.5));
 
-    Gnuplot plot = TestDeterministic (log);
+    Gnuplot plot = TestDeterministic (log, testDeterministicDistance, 10.0);
     plot.SetTitle ("ns3::LogDistancePropagationLossModel (Exponent = 2.5)");
     gnuplots.AddPlot (plot);
   }
@@ -246,7 +263,7 @@ int main (int argc, char *argv[])
     Ptr<ExponentialRandomVariable> expVar = CreateObjectWithAttributes<ExponentialRandomVariable> ("Mean", DoubleValue (50.0));
     random->SetAttribute ("Variable", PointerValue (expVar));
 
-    Gnuplot plot = TestDeterministic (random);
+    Gnuplot plot = TestDeterministic (random, testDeterministicDistance, 10.0);
     plot.SetTitle ("ns3::RandomPropagationLossModel with Exponential Distribution");
     gnuplots.AddPlot (plot);
   }
@@ -257,9 +274,13 @@ int main (int argc, char *argv[])
     // doppler frequency shift for 5.15 GHz at 100 km/h
     Config::SetDefault ("ns3::JakesProcess::DopplerFrequencyHz", DoubleValue (477.9));
 
-    Gnuplot plot = TestDeterministicByTime (jakes, Seconds (0.001), Seconds (1.0));
+    Gnuplot plot = TestDeterministicByTime (jakes, Seconds (0.001), testJakesTimeOneMsRes, 100.0);
     plot.SetTitle ("ns3::JakesPropagationLossModel (with 477.9 Hz shift and 1 millisec resolution)");
     gnuplots.AddPlot (plot);
+    // Usually objects are aggregated either to a Node or a Channel, and this aggregation ensures
+    // a proper call to Dispose.
+    // Here we must call it manually, since the PropagationLossModel is not aggregated to anything.
+    jakes->Dispose ();
   }
 
   {
@@ -268,15 +289,19 @@ int main (int argc, char *argv[])
     // doppler frequency shift for 5.15 GHz at 100 km/h
     Config::SetDefault ("ns3::JakesProcess::DopplerFrequencyHz", DoubleValue (477.9));
 
-    Gnuplot plot = TestDeterministicByTime (jakes, Seconds (0.0001), Seconds (0.1));
+    Gnuplot plot = TestDeterministicByTime (jakes, Seconds (0.0001), testJakesTimeZeroDotOneMsRes, 100.0);
     plot.SetTitle ("ns3::JakesPropagationLossModel (with 477.9 Hz shift and 0.1 millisec resolution)");
     gnuplots.AddPlot (plot);
-  }
+    // Usually objects are aggregated either to a Node or a Channel, and this aggregation ensures
+    // a proper call to Dispose.
+    // Here we must call it manually, since the PropagationLossModel is not aggregated to anything.
+    jakes->Dispose ();
+   }
 
   {
     Ptr<ThreeLogDistancePropagationLossModel> log3 = CreateObject<ThreeLogDistancePropagationLossModel> ();
 
-    Gnuplot plot = TestDeterministic (log3);
+    Gnuplot plot = TestDeterministic (log3, testDeterministicDistance, 10.0);
     plot.SetTitle ("ns3::ThreeLogDistancePropagationLossModel (Defaults)");
     gnuplots.AddPlot (plot);
   }
@@ -288,7 +313,7 @@ int main (int argc, char *argv[])
     log3->SetAttribute ("Exponent1", DoubleValue (3.0));
     log3->SetAttribute ("Exponent2", DoubleValue (10.0));
 
-    Gnuplot plot = TestDeterministic (log3);
+    Gnuplot plot = TestDeterministic (log3, testDeterministicDistance, 10.0);
     plot.SetTitle ("ns3::ThreeLogDistancePropagationLossModel (Exponents 1.0, 3.0 and 10.0)");
     gnuplots.AddPlot (plot);
   }
@@ -296,7 +321,7 @@ int main (int argc, char *argv[])
   {
     Ptr<NakagamiPropagationLossModel> nak = CreateObject<NakagamiPropagationLossModel> ();
 
-    Gnuplot plot = TestProbabilistic (nak);
+    Gnuplot plot = TestProbabilistic (nak, testProbabilisticDistance, 100.0, testProbabilisticSamples);
     plot.SetTitle ("ns3::NakagamiPropagationLossModel (Default Parameters)");
     gnuplots.AddPlot (plot);
   }
@@ -307,7 +332,7 @@ int main (int argc, char *argv[])
     Ptr<NakagamiPropagationLossModel> nak = CreateObject<NakagamiPropagationLossModel> ();
     log3->SetNext (nak);
 
-    Gnuplot plot = TestProbabilistic (log3);
+    Gnuplot plot = TestProbabilistic (log3, testProbabilisticDistance, 100.0, testProbabilisticSamples);
     plot.SetTitle ("ns3::ThreeLogDistancePropagationLossModel and ns3::NakagamiPropagationLossModel (Default Parameters)");
     gnuplots.AddPlot (plot);
   }

src/propagation/model/jakes-process.cc

@@ -68,7 +68,7 @@ void
 JakesProcess::SetPropagationLossModel (Ptr<const PropagationLossModel> propagationModel)
 {
   Ptr<const JakesPropagationLossModel> jakes = propagationModel->GetObject<JakesPropagationLossModel> ();
-  NS_ASSERT_MSG (jakes != 0, "Jakes Process can work only with JakesPropagationLossModel!");
+  NS_ASSERT_MSG (jakes != nullptr, "Jakes Process can work only with JakesPropagationLossModel!");
   m_jakes = jakes;
 
   NS_ASSERT (m_nOscillators != 0);
@@ -127,7 +127,8 @@ JakesProcess::~JakesProcess()
 void
 JakesProcess::DoDispose ()
 {
-  m_jakes = 0;
+  m_uniformVariable = nullptr;
+  m_jakes = nullptr;
 }
 
 std::complex<double>

src/propagation/model/jakes-process.h

@@ -62,7 +62,6 @@ public:
   static TypeId GetTypeId (void);
   JakesProcess ();
   virtual ~JakesProcess();
-  virtual void DoDispose ();
 
   /**
    * Get the channel complex gain
@@ -80,6 +79,10 @@ public:
    * \param model the propagation model using this class
    */
   void SetPropagationLossModel (Ptr<const PropagationLossModel> model);
+
+protected:
+  virtual void DoDispose ();
+
 private:
   /**
    * This class Represents a single oscillator
@@ -119,7 +122,7 @@ private:
   void SetDopplerFrequencyHz (double dopplerFrequencyHz);
 
   /**
-   *
+   * Builds the object Oscillators
    */
   void ConstructOscillators ();
 private:

src/propagation/model/jakes-propagation-loss-model.cc

@@ -51,13 +51,20 @@ JakesPropagationLossModel::GetTypeId ()
   return tid;
 }
 
+void
+JakesPropagationLossModel::DoDispose ()
+{
+  m_uniformVariable = nullptr;
+  m_propagationCache.Cleanup ();
+}
+
 double
 JakesPropagationLossModel::DoCalcRxPower (double txPowerDbm,
                                           Ptr<MobilityModel> a,
                                           Ptr<MobilityModel> b) const
 {
   Ptr<JakesProcess> pathData = m_propagationCache.GetPathData (a, b, 0 /**Spectrum model uid is not used in PropagationLossModel*/);
-  if (pathData == 0)
+  if (!pathData)
     {
       pathData = CreateObject<JakesProcess> ();
       pathData->SetPropagationLossModel (this);

src/propagation/model/jakes-propagation-loss-model.h

@@ -48,6 +48,9 @@ public:
   JakesPropagationLossModel (const JakesPropagationLossModel &) = delete;
   JakesPropagationLossModel & operator = (const JakesPropagationLossModel &) = delete;
 
+protected:
+  virtual void DoDispose () override;
+
 private:
   friend class JakesProcess;
 

src/propagation/model/propagation-cache.h

@@ -69,6 +69,19 @@ public:
     NS_ASSERT (m_pathCache.find (key) == m_pathCache.end ());
     m_pathCache.insert (std::make_pair (key, data));
   };
+
+  /**
+   * Clean the cache
+   */
+  void Cleanup ()
+  {
+    for (auto i : m_pathCache)
+      {
+        i.second->Dispose ();
+      }
+    m_pathCache.clear ();
+  }
+
 private:
   /// Each path is identified by
   struct PropagationPathIdentifier

src/propagation/test/examples-to-run.py

@@ -8,7 +8,7 @@
 #
 # See test.py for more information.
 cpp_examples = [
-    ("main-propagation-loss", "True", "False"),
+    ("main-propagation-loss --test", "True", "True"),
 ]
 
 # A list of Python examples to run in order to ensure that they remain