Improve handling of NEST synaptic delay parameter

doc/nestml_language/synapses_in_nestml.rst

@@ -502,10 +502,13 @@ The synapse is allowed to contain an ``update`` block. Statements in the ``updat
 Dendritic delay
 ~~~~~~~~~~~~~~~
 
-In NEST, all synapses are expected to specify a nonzero dendritic delay, that is, the delay between arrival of a spike at the dendritic spine and the time at which its effects are felt at the soma (or conversely, the delay between a somatic action potential and the arrival at the dendritic spine due to dendritic backpropagation). To indicate that a given parameter is specifying this NEST-specific delay value, use an annotation:
+In NEST, all synapses are expected to specify a nonzero dendritic delay, that is, the delay between arrival of a spike at the dendritic spine and the time at which its effects are felt at the soma (or conversely, the delay between a somatic action potential and the arrival at the dendritic spine due to dendritic backpropagation). As delays and weights are hard-wired into the NEST C++ base classes for the NESTML synapse classes, special annotations must be made in the NESTML model to indicate which state variables or parameters correspond to weight and delay. To indicate the correspondence, use an annotation:
 
 .. code:: nestml
 
+   state:
+       w ms = 1 ms     @nest::weight
+
    parameters:
        dend_delay ms = 1 ms     @nest::delay
 

models/neurons/wb_cond_multisyn.nestml

@@ -29,7 +29,6 @@ wb_cond_multisyn
 neuron wb_cond_multisyn:
     state:
         r integer = 0 # number of steps in the current refractory phase
-
         V_m mV = -65. mV # Membrane potential
         Inact_h real = alpha_h_init / ( alpha_h_init + beta_h_init )    # Inactivation variable h for Na
         Act_n real = alpha_n_init / (alpha_n_init + beta_n_init)  # Activation variable n for K

models/synapses/neuromodulated_stdp.nestml

@@ -25,14 +25,14 @@ References
 """
 synapse neuromodulated_stdp:
     state:
-        w real = 1.
+        w real = 1.    @nest::weight    # Synaptic weight
         n real = 0.   # Neuromodulator concentration
         c real = 0.   # Eligibility trace
         pre_tr real = 0.
         post_tr real = 0.
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         tau_tr_pre ms = 20 ms   # STDP time constant for weight changes caused by pre-before-post spike pairings.
         tau_tr_post ms = 20 ms    # STDP time constant for weight changes caused by post-before-pre spike pairings.
         tau_c ms = 1000 ms    # Time constant of eligibility trace

models/synapses/noisy_synapse.nestml

@@ -9,8 +9,8 @@ Each presynaptic spike is passed to the postsynaptic partner with a weight sampl
 """
 synapse noisy_synapse:
     parameters:
-        w real = 1   # Synaptic weight
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        w real = 1.    @nest::weight    # Synaptic weight
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         A_noise real = .4
 
     input:

models/synapses/stdp_nn_pre_centered.nestml

@@ -52,12 +52,12 @@ References
 """
 synapse stdp_nn_pre_centered:
     state:
-        w real = 1   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
         pre_trace real = 0.
         post_trace real = 0.
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         lambda real = .01
         tau_tr_pre ms = 20 ms
         tau_tr_post ms = 20 ms

models/synapses/stdp_nn_restr_symm.nestml

@@ -44,13 +44,13 @@ References
 """
 synapse stdp_nn_restr_symm:
     state:
-        w real = 1.   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
         pre_trace real = 0.
         post_trace real = 0.
         pre_handled boolean = True
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         lambda real = .01
         tau_tr_pre ms = 20 ms
         tau_tr_post ms = 20 ms

models/synapses/stdp_nn_symm.nestml

@@ -49,12 +49,12 @@ References
 """
 synapse stdp_nn_symm:
     state:
-        w real = 1.   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
         pre_trace real = 0.
         post_trace real = 0.
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         lambda real = .01
         tau_tr_pre ms = 20 ms
         tau_tr_post ms = 20 ms

models/synapses/stdp_triplet_naive.nestml

@@ -21,10 +21,10 @@ References
 """
 synapse stdp_triplet:
     state:
-        w nS = 1 nS   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
 
         tau_plus ms = 16.8 ms  # time constant for tr_r1
         tau_x ms = 101 ms  # time constant for tr_r2
@@ -61,14 +61,14 @@ synapse stdp_triplet:
 
     onReceive(post_spikes):
         # potentiate synapse
-        #w_ nS = Wmax * ( w / Wmax + tr_r1 * ( A2_plus + A3_plus * tr_o2 ) )
-        w_ nS = w + tr_r1 * ( A2_plus + A3_plus * tr_o2 )
+        #w_ real = Wmax * ( w / Wmax + tr_r1 * ( A2_plus + A3_plus * tr_o2 ) )
+        w_ real = w + tr_r1 * ( A2_plus + A3_plus * tr_o2 )
         w = min(Wmax, w_)
 
     onReceive(pre_spikes):
         # depress synapse
-        #w_ nS = Wmax * ( w / Wmax - tr_o1 * ( A2_minus + A3_minus * tr_r2 ) )
-        w_ nS = w - tr_o1 * ( A2_minus + A3_minus * tr_r2 )
+        #w_ real = Wmax * ( w / Wmax - tr_o1 * ( A2_minus + A3_minus * tr_r2 ) )
+        w_ real = w - tr_o1 * ( A2_minus + A3_minus * tr_r2 )
         w = max(Wmin, w_)
 
         # deliver spike to postsynaptic partner

models/synapses/third_factor_stdp_synapse.nestml

@@ -38,10 +38,10 @@ References
 """
 synapse third_factor_stdp:
     state:
-        w real = 1.   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
         lambda real = .01
         tau_tr_pre ms = 20 ms
         tau_tr_post ms = 20 ms

models/synapses/triplet_stdp_synapse.nestml

@@ -18,15 +18,15 @@ References
 """
 synapse stdp_triplet_nn:
     state:
-        w nS = 1 nS   # Synaptic weight
+        w real = 1.    @nest::weight    # Synaptic weight
 
         tr_r1 real = 0.
         tr_r2 real = 0.
         tr_o1 real = 0.
         tr_o2 real = 0.
 
     parameters:
-        d ms = 1 ms  @nest::delay   # Synaptic transmission delay
+        d ms = 1 ms    @nest::delay    # Synaptic transmission delay
 
         tau_plus ms = 16.8 ms  # time constant for tr_r1
         tau_x ms = 101 ms  # time constant for tr_r2

pynestml/cocos/co_co_all_variables_defined.py

@@ -60,6 +60,10 @@ def check_co_co(cls, node: ASTNeuron, after_ast_rewrite: bool = False):
             for var in vars:
                 symbol = var.get_scope().resolve_to_symbol(var.get_complete_name(), SymbolKind.VARIABLE)
 
+                if var.alternate_scope:
+                    # external reference resolved in a different scope
+                    continue
+
                 # test if the symbol has been defined at least
                 if symbol is None:
                     if after_ast_rewrite:   # after ODE-toolbox transformations, convolutions are replaced by state variables, so cannot perform this check properly

pynestml/cocos/co_co_nest_delay_decorator_specified.py → pynestml/cocos/co_co_nest_decorators_specified.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-# co_co_nest_delay_decorator_specified.py
+# co_co_nest_decorators_specified.py
 #
 # This file is part of NEST.
 #
@@ -25,9 +25,9 @@
 from pynestml.utils.messages import Messages
 
 
-class CoCoNESTDelayDecoratorSpecified(CoCo):
+class CoCoNESTDecoratorsSpecified(CoCo):
     """
-    This CoCo ensures that there is precisely one parameter decorated as "@nest::delay".
+    This CoCo ensures that there is precisely one variable decorated as "@nest::delay" and one as "@nest::weight".
     """
 
     @classmethod
@@ -36,14 +36,23 @@ def check_co_co(cls, node: ASTNeuronOrSynapse):
         Checks if the coco applies for the node.
         :param node:
         """
-        decorator_found = False
-        for variable in node.get_parameter_symbols() + node.get_internal_symbols():
+        delay_decorator_found = False
+        weight_decorator_found = False
+        for variable in node.get_state_symbols() + node.get_parameter_symbols() + node.get_internal_symbols():
             if variable.get_namespace_decorator("nest") == "delay":
-                decorator_found = True
-                break
+                delay_decorator_found = True
 
-        if not decorator_found:
+            if variable.get_namespace_decorator("nest") == "weight":
+                weight_decorator_found = True
+
+        if not delay_decorator_found:
             code, message = Messages.get_nest_delay_decorator_not_found()
             Logger.log_message(node=node, error_position=None,
                                code=code, message=message,
                                log_level=LoggingLevel.ERROR)
+
+        if not weight_decorator_found:
+            code, message = Messages.get_nest_weight_decorator_not_found()
+            Logger.log_message(node=node, error_position=None,
+                               code=code, message=message,
+                               log_level=LoggingLevel.ERROR)

pynestml/cocos/co_co_no_kernels_except_in_convolve.py

@@ -22,8 +22,8 @@
 from pynestml.cocos.co_co import CoCo
 from pynestml.meta_model.ast_function_call import ASTFunctionCall
 from pynestml.meta_model.ast_node import ASTNode
-from pynestml.meta_model.ast_external_variable import ASTExternalVariable
 from pynestml.meta_model.ast_kernel import ASTKernel
+from pynestml.meta_model.ast_variable import ASTVariable
 from pynestml.symbols.symbol import SymbolKind
 from pynestml.utils.logger import Logger, LoggingLevel
 from pynestml.utils.messages import Messages
@@ -84,7 +84,7 @@ def visit_variable(self, node: ASTNode):
             symbol = node.get_scope().resolve_to_symbol(kernelName, SymbolKind.VARIABLE)
             # if it is not a kernel just continue
             if symbol is None:
-                if not isinstance(node, ASTExternalVariable):
+                if not (isinstance(node, ASTVariable) and node.get_alternate_name()):
                     code, message = Messages.get_no_variable_found(kernelName)
                     Logger.log_message(node=self.__neuron_node, code=code, message=message, log_level=LoggingLevel.ERROR)
                 continue

pynestml/codegeneration/nest_builder.py

@@ -131,6 +131,7 @@ def build(self) -> None:
             n_cpu = len(os.sched_getaffinity(0))  # only available on Linux
         except AttributeError:
             n_cpu = os.cpu_count()
+        n_cpu = 8
 
         nest_config_path = f"-Dwith-nest={os.path.join(nest_path, 'bin', 'nest-config')}"
         cmake_cmd = ['cmake', nest_config_path, install_prefix, '.']

pynestml/codegeneration/nest_code_generator.py

@@ -26,7 +26,7 @@
 import odetoolbox
 import pynestml
 
-from pynestml.cocos.co_co_nest_delay_decorator_specified import CoCoNESTDelayDecoratorSpecified
+from pynestml.cocos.co_co_nest_decorators_specified import CoCoNESTDecoratorsSpecified
 from pynestml.codegeneration.code_generator import CodeGenerator
 from pynestml.codegeneration.nest_assignments_helper import NestAssignmentsHelper
 from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils
@@ -212,7 +212,7 @@ def set_options(self, options: Mapping[str, Any]) -> Mapping[str, Any]:
 
     def run_nest_target_specific_cocos(self, neurons: Sequence[ASTNeuron], synapses: Sequence[ASTSynapse]):
         for synapse in synapses:
-            CoCoNESTDelayDecoratorSpecified.check_co_co(synapse)
+            CoCoNESTDecoratorsSpecified.check_co_co(synapse)
             if Logger.has_errors(synapse):
                 raise Exception("Error(s) occurred during code generation")
 
@@ -400,6 +400,8 @@ def analyse_synapse(self, synapse: ASTSynapse) -> Dict[str, ASTAssignment]:
             ASTUtils.add_timestep_symbol(synapse)
 
         ASTUtils.update_blocktype_for_common_parameters(synapse)
+        ASTUtils.set_nest_namespace_decorator_alternate_name(synapse, {"delay": "get_delay()",
+                                                                       "weight": "get_weight()"})
 
         return spike_updates
 

pynestml/codegeneration/printers/nest_variable_printer.py

@@ -27,7 +27,6 @@
 from pynestml.codegeneration.printers.cpp_variable_printer import CppVariablePrinter
 from pynestml.codegeneration.printers.expression_printer import ExpressionPrinter
 from pynestml.codegeneration.nest_unit_converter import NESTUnitConverter
-from pynestml.meta_model.ast_external_variable import ASTExternalVariable
 from pynestml.meta_model.ast_variable import ASTVariable
 from pynestml.symbols.predefined_units import PredefinedUnits
 from pynestml.symbols.predefined_variables import PredefinedVariables
@@ -56,13 +55,8 @@ def print_variable(self, variable: ASTVariable) -> str:
         """
         assert isinstance(variable, ASTVariable)
 
-        if isinstance(variable, ASTExternalVariable):
-            _name = str(variable)
-            if variable.get_alternate_name():
-                # the disadvantage of this approach is that the time the value is to be obtained is not explicitly specified, so we will actually get the value at the end of the min_delay timestep
-                return "((post_neuron_t*)(__target))->get_" + variable.get_alternate_name() + "()"
-
-            return "((post_neuron_t*)(__target))->get_" + _name + "(_tr_t)"
+        if variable.get_alternate_name():
+            return variable.get_alternate_name()
 
         if variable.get_name() == PredefinedVariables.E_CONSTANT:
             return "numerics::e"

pynestml/codegeneration/printers/python_variable_printer.py

@@ -25,7 +25,6 @@
 from pynestml.codegeneration.printers.expression_printer import ExpressionPrinter
 from pynestml.codegeneration.printers.variable_printer import VariablePrinter
 from pynestml.codegeneration.python_code_generator_utils import PythonCodeGeneratorUtils
-from pynestml.meta_model.ast_external_variable import ASTExternalVariable
 from pynestml.meta_model.ast_variable import ASTVariable
 from pynestml.symbols.predefined_units import PredefinedUnits
 from pynestml.symbols.predefined_variables import PredefinedVariables
@@ -68,8 +67,8 @@ def print_variable(self, variable: ASTVariable) -> str:
         """
         assert isinstance(variable, ASTVariable)
 
-        if isinstance(variable, ASTExternalVariable):
-            raise Exception("Python-standalone target does not support synapses")
+        if variable.get_alternate_name():
+            raise Exception("Python-standalone target does not support alternate names for variables")
 
         if variable.get_name() == PredefinedVariables.E_CONSTANT:
             return "math.e"