merged with master

.mention-bot

@@ -0,0 +1,3 @@
+{
+  "userBlacklist": ["otizonaizit", "tammoippen"] // users in this list will never be mentioned by mention-bot
+}

extras/userdoc/md/documentation/connection-management.md

@@ -192,11 +192,11 @@ Example:
     syn_dict ={"model": "static_synapse", "weight":2.5, "delay":0.5, 'receptor_type': 1}
     Connect(A, B, syn_spec=syn_dict)
 
-**Array** parameters can be used in conjunction with the rules 'one\_to\_one'
-and 'all\_to\_all'. The arrays can be specified as numpy arrays or lists. As
-for the scalar parameters, all parameters but the receptor types must be
-specified as arrays of floats. For 'one\_to\_one' the array must have the same
-length as the population vector.
+**Array** parameters can be used in conjunction with the rules 'one\_to\_one',
+'all\_to\_all', 'fixed\_indegree' and 'fixed\_outdegree'. The arrays can be
+specified as numpy arrays or lists. As for the scalar parameters, all
+parameters but the receptor types must be specified as arrays of floats.
+For 'one\_to\_one' the array must have the same length as the population vector.
 
 Example:
 
@@ -216,6 +216,34 @@ Example:
     syn_dict = {'weight': [[1.2, -3.5, 2.5],[0.4, -0.2, 0.7]]}
     Connect(A, B, syn_spec=syn_dict)
 
+For 'fixed\_indegree' the array has to be a two-dimensional NumPy array
+with shape (len(post), indegree), where indegree is the number of
+incoming connections per target neuron, therefore the rows describe the
+target and the columns the connections converging to the target neuron,
+regardless of the identity of the source neurons.
+
+Example:
+
+    A = Create("iaf_neuron", 5)
+    B = Create("iaf_neuron", 3)
+    conn_dict = {'rule': 'fixed_indegree', 'indegree': 2}
+    syn_dict = {'weight': [[1.2, -3.5],[0.4, -0.2],[0.6, 2.2]]}
+    Connect(A, B, conn_spec=conn_dict, syn_spec=syn_dict)
+
+For 'fixed\_outdegree' the array has to be a two-dimensional NumPy array
+with shape (len(pre), outdegree), where outdegree is the number of
+outgoing connections per source neuron, therefore the rows describe the
+source and the columns the connections starting from the source neuron
+regardless of the identity of the target neuron.
+
+Example:
+
+    A = Create("iaf_neuron", 2)
+    B = Create("iaf_neuron", 5)
+    conn_dict = {'rule': 'fixed_outdegree', 'outdegree': 3}
+    syn_dict = {'weight': [[1.2, -3.5, 0.4], [-0.2, 0.6, 2.2]]}
+    Connect(A, B, conn_spec=conn_dict, syn_spec=syn_dict)
+
 **Distributed** parameters are initialized with yet another dictionary
 specifying the 'distribution' and the distribution-specific parameters, whose
 specification is optional.

lib/sli/helpinit.sli

@@ -1191,7 +1191,7 @@ SeeAlso: SetOptions, help, helpindex
 /:helpdesk_complete_command
 {
   /helpdesk /command GetOption
-  statusdict/hostos :: 6 Take (darwin) eq
+  (^darwin) statusdict/hostos :: regex_find
   {
     % OSX, must use open -a <cmd> <url>
     (open -a ) exch join

models/CMakeLists.txt

@@ -24,6 +24,8 @@ set( models_sources
     aeif_cond_alpha_multisynapse.h aeif_cond_alpha_multisynapse.cpp
     aeif_cond_beta_multisynapse.h aeif_cond_beta_multisynapse.cpp
     aeif_cond_exp.h aeif_cond_exp.cpp
+    aeif_psc_alpha.h aeif_psc_alpha.cpp
+    aeif_psc_exp.h aeif_psc_exp.cpp
     amat2_psc_exp.h amat2_psc_exp.cpp
     binary_neuron.h binary_neuron_impl.h
     cont_delay_connection.h cont_delay_connection_impl.h
@@ -94,6 +96,7 @@ set( models_sources
     tsodyks_connection_hom.h tsodyks_connection_hom.cpp
     volume_transmitter.h volume_transmitter.cpp
     vogels_sprekeler_connection.h
+    weight_recorder.h weight_recorder.cpp
     spike_dilutor.h spike_dilutor.cpp
     )
 

models/aeif_cond_alpha.cpp

@@ -180,7 +180,7 @@ nest::aeif_cond_alpha_dynamics_DT0( double,
  * ---------------------------------------------------------------- */
 
 nest::aeif_cond_alpha::Parameters_::Parameters_()
-  : V_peak_( 0.0 )    // mV, should not be larger that V_th+10
+  : V_peak_( 0.0 )    // mV
   , V_reset_( -60.0 ) // mV
   , t_ref_( 0.0 )     // ms
   , g_L( 30.0 )       // nS
@@ -303,6 +303,11 @@ nest::aeif_cond_alpha::Parameters_::set( const DictionaryDatum& d )
     }
   }
 
+  if ( V_peak_ < V_th )
+  {
+    throw BadProperty( "V_peak >= V_th required." );
+  }
+
   if ( C_m <= 0 )
   {
     throw BadProperty( "Capacitance must be strictly positive." );

models/aeif_cond_alpha_multisynapse.cpp

@@ -69,7 +69,7 @@ RecordablesMap< aeif_cond_alpha_multisynapse >::create()
  * ---------------------------------------------------------------- */
 
 aeif_cond_alpha_multisynapse::Parameters_::Parameters_()
-  : V_peak_( 0.0 )    // mV, should not be larger that V_th+10
+  : V_peak_( 0.0 )    // mV
   , V_reset_( -60.0 ) // mV
   , t_ref_( 0.0 )     // ms
   , g_L( 30.0 )       // nS
@@ -234,9 +234,14 @@ aeif_cond_alpha_multisynapse::Parameters_::set( const DictionaryDatum& d )
     HMIN = tmp;
   }
 
-  if ( V_peak_ <= V_th )
+  if ( V_peak_ < V_th )
   {
-    throw BadProperty( "V_peak must be larger than threshold." );
+    throw BadProperty( "V_peak >= V_th required." );
+  }
+
+  if ( V_reset_ >= V_peak_ )
+  {
+    throw BadProperty( "Ensure that: V_reset < V_peak ." );
   }
 
   if ( Delta_T < 0. )