Merge pull request #833 from apdavison/nest-3.10

apdavison · web-flow · commit 2f4aee83d938 · 2026-05-06T11:40:33.000+02:00
Add support for NEST 3.10
diff --git a/.github/workflows/full-test.yml b/.github/workflows/full-test.yml
@@ -33,7 +33,7 @@ jobs:
     - name: Install Linux system dependencies
       if: startsWith(matrix.os, 'ubuntu')
       run: |
-        sudo apt-get install libltdl-dev libgsl0-dev python3-all-dev openmpi-bin libopenmpi-dev
+        sudo apt-get install libltdl-dev libgsl0-dev python3-all-dev openmpi-bin libopenmpi-dev libboost-dev
     - name: Install basic Python dependencies
       run: |
         python -m pip install --upgrade pip
@@ -50,15 +50,19 @@ jobs:
       if: startsWith(matrix.os, 'ubuntu')
       run: |
         python -m pip install "cython<3.1.0"
-        wget https://github.com/nest/nest-simulator/archive/refs/tags/v3.9.tar.gz -O nest-simulator-3.9.tar.gz
-        tar xzf nest-simulator-3.9.tar.gz
-        cmake -DCMAKE_INSTALL_PREFIX=$HOME/.local -Dwith-mpi=ON ./nest-simulator-3.9
+        wget https://github.com/nest/nest-simulator/archive/refs/tags/v3.10_rc2.tar.gz -O nest-simulator-3.10.tar.gz
+        tar xzf nest-simulator-3.10.tar.gz
+        cmake -DCMAKE_INSTALL_PREFIX=$HOME/.local -Dwith-mpi=ON ./nest-simulator-3.10_rc2
         make
         make install
     - name: Install Arbor
       if: startsWith(matrix.os, 'ubuntu')
       run: |
         python -m pip install arbor==0.9.0 libNeuroML morphio
+    - name: Install NESTML
+      if: startsWith(matrix.os, 'ubuntu')
+      run: |
+        python -m pip install https://github.com/nest/nestml/archive/refs/tags/v8.3.0-rc2.tar.gz
     - name: Install PyNN itself
       run: |
         python -m pip install -e ".[test,nestml]"
diff --git a/examples/nestml/stdp_synapse.nestml b/examples/nestml/stdp_synapse.nestml
@@ -63,7 +63,6 @@ model stdp_synapse:
         post_trace real = 0.
 
     parameters:
-        d ms = 1 ms    # Synaptic transmission delay
         lambda real =  0.01         # (dimensionless) learning rate for causal updates
         alpha real = 1              # relative learning rate for acausal firing
         tau_tr_pre ms = 20 ms       # time constant of presynaptic trace
@@ -83,7 +82,7 @@ model stdp_synapse:
         post_spikes <- spike
 
     output:
-        spike(weight real, delay ms)
+        spike
 
     onReceive(post_spikes):
         post_trace += 1
@@ -102,7 +101,7 @@ model stdp_synapse:
         w = max(Wmin, w_)
 
         # deliver spike to postsynaptic partner
-        emit_spike(w, d)
+        emit_spike(w)
 
     update:
         integrate_odes()
diff --git a/examples/nestml/tsodyks_synapse.nestml b/examples/nestml/tsodyks_synapse.nestml
@@ -1,7 +1,6 @@
 model tsodyks_synapse_nestml:
     parameters:
         w real = 1          # Synaptic weight
-        d ms = 1 ms         # Dendritic delay (required by PyNESTML; NEST applies transmission delay at connection level)
         tau_psc ms = 3 ms   # Time constant of postsynaptic current
         tau_fac ms = 0 ms   # Time constant for facilitation (0 = no facilitation)
         tau_rec ms = 800 ms # Time constant for recovery from depression
@@ -10,20 +9,20 @@ model tsodyks_synapse_nestml:
     state:
         x real = 1          # Fraction of synaptic resources available
         y real = 0          # Fraction of resources in use
-        u real = 0.5        # Running value of utilisation
+        u real = U          # Running value of utilisation
         t_last_update ms = 0 ms
 
     input:
         pre_spikes <- spike
 
     output:
-        spike(weight real, delay ms)
+        spike
 
     onReceive(pre_spikes):
         dt ms = t - t_last_update
         t_last_update = t
 
-        Puu real = tau_fac == 0 ms ? 0 : exp(-dt / tau_fac)
+        Puu real = tau_fac == 0 ? 0 : exp(-dt / tau_fac)
         Pyy real = exp(-dt / tau_psc)
         Pzz real = exp(-dt / tau_rec)
         Pxy real = ((Pzz - 1) * tau_rec - (Pyy - 1) * tau_psc) / (tau_psc - tau_rec)
@@ -39,4 +38,4 @@ model tsodyks_synapse_nestml:
         x -= delta_y_tsp
         y += delta_y_tsp
 
-        emit_spike(delta_y_tsp * w, d)
+        emit_spike(delta_y_tsp * w)
diff --git a/pyNN/nest/cells.py b/pyNN/nest/cells.py
@@ -39,7 +39,7 @@ def get_defaults(model_name):
     for name, value in defaults.items():
         if name in variables:
             default_initial_values[name] = value
-        elif name not in ignore:
+        elif name not in ignore and not name.startswith('__'):
             if isinstance(value, valid_types):
                 default_params[name] = conversion.make_pynn_compatible(value)
             else:
@@ -53,10 +53,7 @@ def get_receptor_types(model_name):
 
 
 def get_recordables(model_name):
-    try:
-        return [name for name in nest.GetDefaults(model_name, "recordables")]
-    except nest.NESTError:
-        return []
+    return list(nest.GetDefaults(model_name).get("recordables", []))
 
 
 def native_cell_type(model_name):
diff --git a/pyNN/nest/extensions/CMakeLists.txt b/pyNN/nest/extensions/CMakeLists.txt
@@ -192,14 +192,23 @@ add_custom_target( dist
     )
 
 
+# On macOS, loadable modules need -undefined dynamic_lookup so that NEST
+# kernel symbols (provided by nestkernel_api.so at Python import time) are
+# resolved at dlopen time rather than requiring a libnest.so at link time.
+if ( APPLE )
+  set( MACOS_LINK_FLAGS "-undefined dynamic_lookup" )
+else ()
+  set( MACOS_LINK_FLAGS "" )
+endif ()
+
 # Create a module for loading at runtime
 # with the `Install` command.
 add_library( ${MODULE_NAME}_module MODULE ${MODULE_SOURCES} )
 target_link_libraries(${MODULE_NAME}_module ${USER_LINK_LIBRARIES})
 set_target_properties( ${MODULE_NAME}_module
     PROPERTIES
     COMPILE_FLAGS "${NEST_CXXFLAGS} -DLTX_MODULE"
-    LINK_FLAGS "${NEST_LIBS}"
+    LINK_FLAGS "${NEST_LIBS} ${MACOS_LINK_FLAGS}"
     PREFIX ""
     OUTPUT_NAME ${MODULE_NAME} )
 install( TARGETS ${MODULE_NAME}_module
diff --git a/pyNN/nest/extensions/simple_stochastic_synapse.h b/pyNN/nest/extensions/simple_stochastic_synapse.h
@@ -9,6 +9,7 @@
 
 // Includes from nestkernel:
 #include "connection.h"
+#include "dictionary.h"
 #include "kernel_manager.h"
 
 
@@ -156,15 +157,15 @@ class simple_stochastic_synapse : public nest::Connection< targetidentifierT >
   // data member holding the weight.
 
   //! Store connection status information in dictionary
-  void get_status( DictionaryDatum& d ) const;
+  void get_status( Dictionary& d ) const;
 
   /**
    * Set connection status.
    *
    * @param d Dictionary with new parameter values
    * @param cm ConnectorModel is passed along to validate new delay values
    */
-  void set_status( const DictionaryDatum& d, nest::ConnectorModel& cm );
+  void set_status( const Dictionary& d, nest::ConnectorModel& cm );
 
   //! Allows efficient initialization on construction
   void
@@ -203,23 +204,23 @@ simple_stochastic_synapse< targetidentifierT >::send( nest::Event& e,
 template < typename targetidentifierT >
 void
 simple_stochastic_synapse< targetidentifierT >::get_status(
-  DictionaryDatum& d ) const
+  Dictionary& d ) const
 {
   ConnectionBase::get_status( d );
-  def< double >( d, nest::names::weight, weight_ );
-  def< double >( d, nest::names::p, p_ );
-  def< long >( d, nest::names::size_of, sizeof( *this ) );
+  d[ nest::names::weight ] = weight_;
+  d[ nest::names::p ] = p_;
+  d[ nest::names::size_of ] = static_cast< long >( sizeof( *this ) );
 }
 
 template < typename targetidentifierT >
 void
 simple_stochastic_synapse< targetidentifierT >::set_status(
-  const DictionaryDatum& d,
+  const Dictionary& d,
   nest::ConnectorModel& cm )
 {
   ConnectionBase::set_status( d, cm );
-  updateValue< double >( d, nest::names::weight, weight_ );
-  updateValue< double >( d, nest::names::p, p_ );
+  d.update_value( nest::names::weight, weight_ );
+  d.update_value( nest::names::p, p_ );
 }
 
 } // namespace
diff --git a/pyNN/nest/extensions/stochastic_stp_synapse.h b/pyNN/nest/extensions/stochastic_stp_synapse.h
@@ -11,6 +11,7 @@
 
 // Includes from nestkernel:
 #include "connection.h"
+#include "dictionary.h"
 
 /* BeginUserDocs: synapse, short-term plasticity
 
@@ -93,13 +94,13 @@ class stochastic_stp_synapse : public nest::Connection< targetidentifierT >
   /**
    * Get all properties of this connection and put them into a dictionary.
    */
-  void get_status( DictionaryDatum& d ) const;
+  void get_status( Dictionary& d ) const;
 
   /**
    * Set default properties of this connection from the values given in
    * dictionary.
    */
-  void set_status( const DictionaryDatum& d, nest::ConnectorModel& cm );
+  void set_status( const Dictionary& d, nest::ConnectorModel& cm );
 
   /**
    * Send an event to the receiver of this connection.
diff --git a/pyNN/nest/extensions/stochastic_stp_synapse_impl.h b/pyNN/nest/extensions/stochastic_stp_synapse_impl.h
@@ -16,8 +16,8 @@
 #include "connector_model.h"
 #include "nest_names.h"
 
-// Includes from sli:
-#include "dictutils.h"
+// Includes from nestkernel:
+#include "dictionary.h"
 
 namespace pynn
 {
@@ -55,30 +55,29 @@ stochastic_stp_synapse< targetidentifierT >::stochastic_stp_synapse(
 template < typename targetidentifierT >
 void
 stochastic_stp_synapse< targetidentifierT >::get_status(
-  DictionaryDatum& d ) const
+  Dictionary& d ) const
 {
   ConnectionBase::get_status( d );
-  def< double >( d, nest::names::weight, weight_ );
-  def< double >( d, nest::names::dU, U_ );
-  def< double >( d, nest::names::u, u_ );
-  def< double >( d, nest::names::tau_rec, tau_rec_ );
-  def< double >( d, nest::names::tau_fac, tau_fac_ );
+  d[ nest::names::weight ] = weight_;
+  d[ nest::names::dU ] = U_;
+  d[ nest::names::u ] = u_;
+  d[ nest::names::tau_rec ] = tau_rec_;
+  d[ nest::names::tau_fac ] = tau_fac_;
 }
 
 
 template < typename targetidentifierT >
 void
 stochastic_stp_synapse< targetidentifierT >::set_status(
-  const DictionaryDatum& d,
+  const Dictionary& d,
   nest::ConnectorModel& cm )
 {
   ConnectionBase::set_status( d, cm );
-  updateValue< double >( d, nest::names::weight, weight_ );
-
-  updateValue< double >( d, nest::names::dU, U_ );
-  updateValue< double >( d, nest::names::u, u_ );
-  updateValue< double >( d, nest::names::tau_rec, tau_rec_ );
-  updateValue< double >( d, nest::names::tau_fac, tau_fac_ );
+  d.update_value( nest::names::weight, weight_ );
+  d.update_value( nest::names::dU, U_ );
+  d.update_value( nest::names::u, u_ );
+  d.update_value( nest::names::tau_rec, tau_rec_ );
+  d.update_value( nest::names::tau_fac, tau_fac_ );
 }
 
 } // of namespace pynn
diff --git a/pyNN/nest/nestml.py b/pyNN/nest/nestml.py
@@ -109,7 +109,7 @@ def nestml_synapse_type(
         nestml_description,
         postsynaptic_neuron_nestml_description=None,
         weight_variable="w",
-        delay_variable="d"
+        delay_variable=None
 ):
     """
     Register a NESTML synapse description and return a synapse type class.
@@ -270,6 +270,24 @@ def _compile_and_resolve():
             codegen_opts=codegen_opts,
         )
         nest.Install(module_name)
+    except nest.NESTErrors.DynamicModuleManagementError as e:
+        missing_delay = [
+            entry["name"] for entry in _pending
+            if entry["type"] == "synapse" and entry["delay_variable"] is None
+        ]
+        hint = ""
+        if missing_delay:
+            hint = (
+                f"Synapse model(s) {missing_delay} have no delay_variable set. "
+                "If your NESTML model uses an explicit delay variable, "
+                "pass delay_variable='<name>' to nestml_synapse_type() "
+                "to match the delay parameter in your model."
+            )
+        raise RuntimeError(
+            f"Failed to install NESTML module '{module_name}'. "
+            "NESTML model compilation failed silently. "
+            f"{hint}"
+        ) from e
     finally:
         for tmpdir in tmpdirs:
             shutil.rmtree(tmpdir, ignore_errors=True)
diff --git a/pyNN/nest/populations.py b/pyNN/nest/populations.py
@@ -282,7 +282,7 @@ def _set_initial_value_array(self, variable, value):
                 simulator.state.set_status(self.node_collection[self._mask_local],
                                            variable, local_values)
         except nest.NESTError as e:
-            if "Unused dictionary items" in e.args[0]:
+            if "Unused dictionary items" in e.args[0] or "Unaccessed" in e.args[0]:
                 logger.warning("NEST does not allow setting an initial value for %s" % variable)
                 # should perhaps check whether value-to-be-set is the same as current value,
                 # and raise an Exception if not, rather than just emit a warning.
diff --git a/pyNN/nest/projections.py b/pyNN/nest/projections.py
@@ -268,8 +268,10 @@ def _convergent_connect(self, presynaptic_indices, postsynaptic_index,
                     weights = np.array([weights])
                 if delays is not None and not np.isscalar(delays):
                     delays = np.array([delays])
-                if weights is not None or delays is not None:
-                    syn_dict.update({'weight': weights, 'delay': delays})
+                if weights is not None:
+                    syn_dict['weight'] = weights
+                if delays is not None:
+                    syn_dict['delay'] = delays
 
                 if postsynaptic_cell.celltype.standard_receptor_type:
                     # For the standard TsodyksMarkramSynapse, copy "tau_psc" from the
@@ -463,7 +465,10 @@ def _get_attributes_as_list(self, names):
             else:
                 nest_names.append(name)
         values = nest.GetStatus(self.nest_connections, nest_names)
-        values = np.array(values)  # ought to preserve int type for source, target
+        if isinstance(values, dict):  # NEST 3.10_rc1
+            values = np.array([values[key] for key in nest_names]).T
+        else:
+            values = np.array(values)  # ought to preserve int type for source, target
         if 'weight' in names:
             # other attributes could also have scale factors - need to use translation mechanisms
             scale_factors = np.ones(len(names))
@@ -492,7 +497,20 @@ def _get_attributes_as_arrays(self, names, multiple_synapses='sum'):
             value_arr = np.nan * np.ones((self.pre.size, self.post.size))
             connection_attributes = nest.GetStatus(self.nest_connections,
                                                    ('source', 'target', attribute_name))
-            for conn in connection_attributes:
+            # GetStatus return format varies by NEST version:
+            #   dict {key: [values]}  — seen in some NEST 3.x builds
+            #   list of dicts         — NEST 3.10rc1
+            #   list of tuples        — older NEST
+            if isinstance(connection_attributes, dict):
+                conn_iter = zip(connection_attributes['source'],
+                                connection_attributes['target'],
+                                connection_attributes[attribute_name])
+            elif connection_attributes and isinstance(connection_attributes[0], dict):
+                conn_iter = ((c['source'], c['target'], c[attribute_name])
+                             for c in connection_attributes)
+            else:
+                conn_iter = connection_attributes
+            for conn in conn_iter:
                 # (offset is always 0,0 for connections created with connect())
                 src, tgt, value = conn
                 addr = self.pre.id_to_index(src), self.post.id_to_index(tgt)
diff --git a/pyNN/nest/simulator.py b/pyNN/nest/simulator.py
@@ -221,7 +221,11 @@ def _set_spike_precision(self, precision):
     spike_precision = property(fget=_get_spike_precision, fset=_set_spike_precision)
 
     def _set_verbosity(self, verbosity):
-        nest.set_verbosity('M_{}'.format(verbosity.upper()))
+        try:
+            nest.set_verbosity('M_{}'.format(verbosity.upper()))
+        except AttributeError:
+            vb_level = getattr(nest.VerbosityLevel, verbosity.upper())
+            nest.verbosity = vb_level
     verbosity = property(fset=_set_verbosity)
 
     def set_status(self, nodes, params, val=None):
@@ -308,8 +312,11 @@ def clear(self):
         self.current_sources = []
         self.recording_devices = []
         self.recorders = set()
-        # clear the sli stack, if this is not done --> memory leak cause the stack increases
-        nest.ll_api.sr('clear')
+        try:
+            # clear the sli stack, if this is not done --> memory leak cause the stack increases
+            nest.ll_api.sr('clear')
+        except AttributeError:  # NEST 3.10+
+            pass
         # reset the simulation kernel
         nest.ResetKernel()
         # but this reverts some of the PyNN settings, so we have to repeat them (see NEST #716)
diff --git a/test/system/test_nest.py b/test/system/test_nest.py
diff --git a/test/system/test_nest_nestml.py b/test/system/test_nest_nestml.py
