allow inline expressions as postsynaptic third-factor

Author: C.A.P. Linssen

doc/running/running_nest.rst

@@ -276,7 +276,7 @@ Additionally, if the synapse requires it, specify the ``"post_ports"`` entry to
                                                            "post_ports": ["post_spikes",
                                                                           ["I_post_dend", "I_dend"]]}]})
 
-This specifies that the neuron ``iaf_psc_exp_dend`` has to be generated paired with the synapse ``third_factor_stdp``, and that the input ports ``post_spikes`` and ``I_post_dend`` in the synapse are to be connected to the postsynaptic partner. For the ``I_post_dend`` input port, the corresponding variable in the (postsynaptic) neuron is called ``I_dend``.
+This specifies that the neuron ``iaf_psc_exp_dend`` has to be generated paired with the synapse ``third_factor_stdp``, and that the input ports ``post_spikes`` and ``I_post_dend`` in the synapse are to be connected to the postsynaptic partner. For the ``I_post_dend`` input port, the corresponding variable in the (postsynaptic) neuron is called ``I_dend``. Note that inline expressions in the postsynaptic neuron can also be used, referred to by name analogous to a state variable.
 
 To prevent the NESTML code generator from moving specific variables from synapse into postsynaptic neuron, the code generation option ``strictly_synaptic_vars`` may be used (see https://nestml.readthedocs.io/en/latest/pynestml.transformers.html#pynestml.transformers.synapse_post_neuron_transformer.SynapsePostNeuronTransformer).
 

pynestml/codegeneration/nest_code_generator.py

@@ -583,7 +583,14 @@ def _get_synapse_model_namespace(self, synapse: ASTModel) -> Dict:
                 namespace["state_vars_that_need_continuous_buffering_transformed"] = [xfrm.get_neuron_var_name_from_syn_port_name(port_name, removesuffix(synapse.paired_neuron.unpaired_name, FrontendConfiguration.suffix), removesuffix(synapse.paired_neuron.paired_synapse.get_name().split("__with_")[0], FrontendConfiguration.suffix)) for port_name in synapse.paired_neuron.state_vars_that_need_continuous_buffering]
                 namespace["state_vars_that_need_continuous_buffering_transformed_iv"] = {}
                 for var_name, var_name_transformed in zip(namespace["state_vars_that_need_continuous_buffering"], namespace["state_vars_that_need_continuous_buffering_transformed"]):
-                    namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = self._nest_printer.print(synapse.paired_neuron.get_initial_value(var_name_transformed))
+                    if synapse.paired_neuron.get_initial_value(var_name_transformed) is None:
+                        if var_name_transformed in [sym.name for sym in synapse.paired_neuron.get_inline_expression_symbols()]:
+                            # the postsynaptic variable is actually an inline expression: initial value is 0
+                            namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = "0"
+                        else:
+                            raise Exception("State variable \"" + str(var_name_transformed) + "\" was not found in the neuron model \"" + synapse.paired_neuron.name + "\"")
+                    else:
+                        namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = self._nest_printer.print(synapse.paired_neuron.get_initial_value(var_name_transformed))
 
             namespace["continuous_post_ports"] = []
             if "neuron_synapse_pairs" in FrontendConfiguration.get_codegen_opts().keys():
@@ -705,8 +712,13 @@ def _get_neuron_model_namespace(self, neuron: ASTModel) -> Dict:
                 namespace["state_vars_that_need_continuous_buffering_transformed_iv"] = {}
                 for var_name, var_name_transformed in zip(namespace["state_vars_that_need_continuous_buffering"], namespace["state_vars_that_need_continuous_buffering_transformed"]):
                     if neuron.get_initial_value(var_name_transformed) is None:
-                        raise Exception("State variable \"" + str(var_name_transformed) + "\" was not found in the neuron model \"" + neuron.name + "\"")
-                    namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = self._nest_printer.print(neuron.get_initial_value(var_name_transformed))
+                        if var_name_transformed in [sym.name for sym in neuron.get_inline_expression_symbols()]:
+                            # the postsynaptic variable is actually an inline expression: initial value is 0
+                            namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = "0"
+                        else:
+                            raise Exception("State variable \"" + str(var_name_transformed) + "\" was not found in the neuron model \"" + neuron.name + "\"")
+                    else:
+                        namespace["state_vars_that_need_continuous_buffering_transformed_iv"][var_name] = self._nest_printer.print(neuron.get_initial_value(var_name_transformed))
             else:
                 namespace["state_vars_that_need_continuous_buffering"] = []
             if "extra_on_emit_spike_stmts_from_synapse" in dir(neuron):

pynestml/codegeneration/resources_nest/point_neuron/common/NeuronHeader.jinja2

@@ -879,7 +879,7 @@ private:
   // -------------------------------------------------------------------------
   //   Getters/setters for inline expressions
   // -------------------------------------------------------------------------
-
+public: // XXX REMOVE -- use friend class instead?
 {%  filter indent(2, True) -%}
 {%- for equations_block in neuron.get_equations_blocks() %}
 {%-     for inline_expr in equations_block.get_inline_expressions() %}
@@ -890,6 +890,7 @@ private:
 {%     endfor %}
 {%- endfor %}
 {%- endfilter %}
+private: // XXX REMOVE
 
   // -------------------------------------------------------------------------
   //   Getters/setters for input buffers

tests/nest_tests/traub_cond_multisyn_test.py

@@ -86,11 +86,12 @@ def test_traub_cond_multisyn(self):
         else:
             nest.SetStatus(multimeter[1], {"record_from": record_from,
                                            "interval": dt})
-        # {"AMPA": 1, "NMDA": 2, "GABA_A": 3, "GABA_B": 4}
-        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": 1})  # AMPA
-        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": 2})  # NMDA
-        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": 3})  # GABAA
-        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": 4})  # GABAB
+
+        receptor_types = nest.GetStatus(neuron2, "receptor_types")[0]
+        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": receptor_types["AMPA"]})  # AMPA
+        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": receptor_types["NMDA"]})  # NMDA
+        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": receptor_types["GABAA"]})  # GABAA
+        nest.Connect(neuron1, neuron2, syn_spec={"receptor_type": receptor_types["GABAB"]})  # GABAB
 
         if NESTTools.detect_nest_version().startswith("v2"):
             nest.Connect([multimeter[0]], neuron1, "one_to_one")