Fix type derivation of kernel buffers

pynestml/codegeneration/nest_code_generator.py

@@ -841,10 +841,8 @@ def get_spike_update_expressions(self, neuron: ASTNeuron, kernel_buffers, solver
 
             for kernel_var in kernel.get_variables():
                 for var_order in range(ASTUtils.get_kernel_var_order_from_ode_toolbox_result(kernel_var.get_name(), solver_dicts)):
-                    kernel_spike_buf_name = ASTUtils.construct_kernel_X_spike_buf_name(
-                        kernel_var.get_name(), spike_input_port, var_order)
-                    expr = ASTUtils.get_initial_value_from_ode_toolbox_result(
-                        kernel_spike_buf_name, solver_dicts)
+                    kernel_spike_buf_name = ASTUtils.construct_kernel_X_spike_buf_name(kernel_var.get_name(), spike_input_port, var_order)
+                    expr = ASTUtils.get_initial_value_from_ode_toolbox_result(kernel_spike_buf_name, solver_dicts)
                     assert expr is not None, "Initial value not found for kernel " + kernel_var
                     expr = str(expr)
                     if expr in ["0", "0.", "0.0"]:

pynestml/utils/ast_utils.py

@@ -28,6 +28,7 @@
 
 from pynestml.codegeneration.printers.ast_printer import ASTPrinter
 from pynestml.codegeneration.printers.cpp_variable_printer import CppVariablePrinter
+from pynestml.codegeneration.printers.nestml_printer import NESTMLPrinter
 from pynestml.generated.PyNestMLLexer import PyNestMLLexer
 from pynestml.meta_model.ast_assignment import ASTAssignment
 from pynestml.meta_model.ast_block import ASTBlock
@@ -984,7 +985,7 @@ def add_declarations_to_state_block(cls, neuron: ASTNeuron, variables: List, ini
         return neuron
 
     @classmethod
-    def add_declaration_to_state_block(cls, neuron: ASTNeuron, variable: str, initial_value: str) -> ASTNeuron:
+    def add_declaration_to_state_block(cls, neuron: ASTNeuron, variable: str, initial_value: str, type_str: str = "real") -> ASTNeuron:
         """
         Adds a single declaration to an arbitrary state block of the neuron. The declared variable is of type real.
         :param neuron: a neuron
@@ -997,7 +998,7 @@ def add_declaration_to_state_block(cls, neuron: ASTNeuron, variable: str, initia
 
         tmp = ModelParser.parse_expression(initial_value)
         vector_variable = ASTUtils.get_vectorized_variable(tmp, neuron.get_scope())
-        declaration_string = variable + ' real' + (
+        declaration_string = variable + " " + type_str + (
             '[' + vector_variable.get_vector_parameter() + ']'
             if vector_variable is not None and vector_variable.has_vector_parameter() else '') + ' = ' + initial_value
         ast_declaration = ModelParser.parse_declaration(declaration_string)
@@ -1604,12 +1605,13 @@ def update_initial_values_for_odes(cls, neuron: ASTNeuron, solver_dicts: List[di
 
     @classmethod
     def create_initial_values_for_kernels(cls, neuron: ASTNeuron, solver_dicts: List[dict], kernels: List[ASTKernel]) -> None:
-        """
+        r"""
         Add the variables used in kernels from the ode-toolbox result dictionary as ODEs in NESTML AST
         """
         for solver_dict in solver_dicts:
             if solver_dict is None:
                 continue
+
             for var_name in solver_dict["initial_values"].keys():
                 if cls.variable_in_kernels(var_name, kernels):
                     # original initial value expressions should have been removed to make place for ode-toolbox results
@@ -1622,9 +1624,19 @@ def create_initial_values_for_kernels(cls, neuron: ASTNeuron, solver_dicts: List
             for var_name, expr in solver_dict["initial_values"].items():
                 # overwrite is allowed because initial values might be repeated between numeric and analytic solver
                 if cls.variable_in_kernels(var_name, kernels):
-                    expr = "0"    # for kernels, "initial value" returned by ode-toolbox is actually the increment value; the actual initial value is assumed to be 0
+                    spike_in_port_name = var_name.split("__X__")[1]
+                    spike_in_port_name = spike_in_port_name.split("__d")[0]
+                    spike_in_port = ASTUtils.get_input_port_by_name(neuron.get_input_blocks(), spike_in_port_name)
+                    if spike_in_port:
+                        type_str = NESTMLPrinter().print_data_type(spike_in_port.data_type)
+                        differential_order: int = len(re.findall("__d", var_name))
+                        if differential_order:
+                            type_str += "*s**-" + str(differential_order)
+                    else:
+                        type_str = "real"
+                    expr = "0 " + type_str    # for kernels, "initial value" returned by ode-toolbox is actually the increment value; the actual initial value is assumed to be 0
                     if not cls.declaration_in_state_block(neuron, var_name):
-                        cls.add_declaration_to_state_block(neuron, var_name, expr)
+                        cls.add_declaration_to_state_block(neuron, var_name, expr, type_str)
 
     @classmethod
     def transform_ode_and_kernels_to_json(cls, neuron: ASTNeuron, parameters_blocks: Sequence[ASTBlockWithVariables],
@@ -1895,7 +1907,8 @@ def replace_var(_expr, replace_var_name: str, replace_with_var_name: str):
             for decl in equation_block.get_declarations():
                 if isinstance(decl, ASTInlineExpression) \
                    and isinstance(decl.get_expression(), ASTSimpleExpression) \
-                   and '__X__' in str(decl.get_expression()):
+                   and '__X__' in str(decl.get_expression()) \
+                   and decl.get_expression().get_variable():
                     replace_with_var_name = decl.get_expression().get_variable().get_name()
                     neuron.accept(ASTHigherOrderVisitor(lambda x: replace_var(
                         x, decl.get_variable_name(), replace_with_var_name)))

pynestml/utils/messages.py

@@ -1050,7 +1050,7 @@ def templated_arg_types_inconsistent(cls, function_name, failing_arg_idx, other_
         """
         message = 'In function \'' + function_name + '\': actual derived type of templated parameter ' + \
             str(failing_arg_idx + 1) + ' is \'' + failing_arg_type_str + '\', which is inconsistent with that of parameter(s) ' + \
-            ', '.join([str(_ + 1) for _ in other_args_idx]) + ', which have type \'' + other_type_str + '\''
+            ', '.join([str(_ + 1) for _ in other_args_idx]) + ', which has/have type \'' + other_type_str + '\''
         return MessageCode.TEMPLATED_ARG_TYPES_INCONSISTENT, message
 
     @classmethod