add attributes to spiking input ports

models/neurons/terub_gpe_neuron.nestml

@@ -78,8 +78,8 @@ model terub_gpe_neuron:
         inline g_k_Ca real = 15.0 #Report:15,  Terman Rubin 2002: 20.0
         inline g_k1 real = 30.0
 
-        inline I_exc_mod real = -convolve(g_exc, exc_spikes) * V_m
-        inline I_inh_mod real = convolve(g_inh, inh_spikes) * (V_m - E_gg)
+        inline I_exc_mod real = -convolve(g_exc, exc_spikes.weight) * V_m
+        inline I_inh_mod real = convolve(g_inh, inh_spikes.weight) * (V_m - E_gg)
 
         inline tau_n real = g_tau_n_0 + g_tau_n_1 / (1. + exp(-(V_m-g_theta_n_tau)/g_sigma_n_tau))
         inline tau_h real = g_tau_h_0 + g_tau_h_1 / (1. + exp(-(V_m-g_theta_h_tau)/g_sigma_h_tau))

pynestml/codegeneration/printers/python_variable_printer.py

@@ -56,9 +56,9 @@ def _print_python_name(cls, variable_name: str) -> str:
         """
         differential_order = variable_name.count("\"")
         if differential_order > 0:
-            return variable_name.replace("\"", "").replace("$", "__DOLLAR") + "__" + "d" * differential_order
+            return variable_name.replace(".", "__DOT__").replace("\"", "").replace("$", "__DOLLAR") + "__" + "d" * differential_order
 
-        return variable_name.replace("$", "__DOLLAR")
+        return variable_name.replace(".", "__DOT__").replace("$", "__DOLLAR")
 
     def print_variable(self, variable: ASTVariable) -> str:
         """

pynestml/codegeneration/resources_python_standalone/point_neuron/@NEURON_NAME@.py.jinja2

@@ -103,7 +103,11 @@ class Neuron_{{neuronName}}(Neuron):
     {{ port.get_symbol_name() }}: List[float] = []
     spike_received_{{ port.get_symbol_name() }}: List[bool] = []
 {%-     else %}
-    {{ port.get_symbol_name() }}: float = 0.
+{%         set ast_input_port = utils.get_input_port_by_name(astnode.get_input_blocks(), port.name) %}
+{%-        for attribute in ast_input_port.get_parameters() %}
+    {{ port.get_symbol_name() }}__DOT__{{ attribute.name }}: float = 0.
+{%-        endfor %}
+    {{ port.get_symbol_name() }}: float = 0.    # buffer for the port name by itself (train of unweighted delta pulses)
     spike_received_{{ port.get_symbol_name() }}: bool = False
 {%-     endif %}
 {%- endfor %}
@@ -337,9 +341,17 @@ class Neuron_{{neuronName}}(Neuron):
 
   def handle(self, t_spike: float, w: float, port_name: str) -> None:
 {%-     for port in neuron.get_spike_input_ports() %}
-    if port_name == "{{port.name}}":
-      self.B_.{{port.get_symbol_name()}} += abs(w)
-      self.B_.spike_received_{{port.get_symbol_name()}} = True
+    if port_name == "{{ port.name }}":
+      self.B_.{{ port.get_symbol_name() }} += 1.    # unweighted spike port
+{%         set ast_input_port = utils.get_input_port_by_name(astnode.get_input_blocks(), port.name) %}
+{%-        for attribute in ast_input_port.get_parameters() %}
+{%             if attribute.name == "weight" %}
+      self.B_.{{ port.get_symbol_name() }}__DOT__{{ attribute.name }} += abs(w)    # unweighted spike port
+{%             else %}
+{{                 raise('The Python-standalone code generator only supports \'weight\' spike input port attribute for now') }}
+{%             endif %}
+{%          endfor %}
+      self.B_.spike_received_{{ port.get_symbol_name() }} = True
       return
 {%-     endfor %}
     raise Exception("Received a spike on unknown input port \"" + port_name + "\" at t = " + "{0:E}".format(t_spike))

pynestml/codegeneration/resources_python_standalone/point_neuron/directives_py/ApplySpikesFromBuffers.jinja2

@@ -1,6 +1,6 @@
 {%- if tracing %}# generated by {{self._TemplateReference__context.name}}{% endif %}
 {%- for spike_updates_for_port in spike_updates.values() %}
-{%- for ast in spike_updates_for_port -%}
-{%- include "directives_py/Assignment.jinja2" %}
-{%- endfor %}
+{%-     for ast in spike_updates_for_port -%}
+{%-         include "directives_py/Assignment.jinja2" %}
+{%-     endfor %}
 {%- endfor %}

pynestml/codegeneration/resources_python_standalone/point_neuron/test_python_standalone_module.py.jinja2

@@ -43,8 +43,8 @@ class TestSimulator:
         sg_inh = simulator.add_neuron(SpikeGenerator(interval=50.))
 {% for neuron in neurons %}
         neuron = simulator.add_neuron(Neuron_{{neuron.get_name()}}(timestep=simulator.timestep))
-        simulator.connect(sg_exc, neuron, "exc_spikes",w=1000.)
-        simulator.connect(sg_inh, neuron, "inh_spikes",w=4000.)
+        simulator.connect(sg_exc, neuron, "spike_in_port",w=1000.)
+        simulator.connect(sg_inh, neuron, "spike_in_port",w=-4000.)
 {% endfor %}
 
         simulator.run(t_stop)