示例#1
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    def setup_model_generation_helpers(self, neuron: ASTNeuron):
        """
        Returns a namespace for Jinja2 neuron model documentation template.

        :param neuron: a single neuron instance
        :type neuron: ASTNeuron
        :return: a map from name to functionality.
        :rtype: dict
        """
        converter = LatexReferenceConverter()
        latex_expression_printer = LatexExpressionPrinter(converter)

        namespace = dict()

        namespace['now'] = datetime.datetime.utcnow()
        namespace['neuron'] = neuron
        namespace['neuronName'] = str(neuron.get_name())
        namespace['printer'] = NestPrinter(latex_expression_printer)
        namespace['assignments'] = NestAssignmentsHelper()
        namespace['names'] = NestNamesConverter()
        namespace['declarations'] = NestDeclarationsHelper()
        namespace['utils'] = ASTUtils()
        namespace['odeTransformer'] = OdeTransformer()

        import textwrap
        pre_comments_bak = neuron.pre_comments
        neuron.pre_comments = []
        namespace['neuron_source_code'] = textwrap.indent(
            neuron.__str__(), "   ")
        neuron.pre_comments = pre_comments_bak

        return namespace
示例#2
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    def setup_index_generation_helpers(self, neurons: List[ASTNeuron]):
        """
        Returns a namespace for Jinja2 neuron model index page template.

        :param neurons: a list of neuron instances
        :type neurons: List[ASTNeuron]
        :return: a map from name to functionality.
        :rtype: dict
        """
        converter = LatexReferenceConverter()
        latex_expression_printer = LatexExpressionPrinter(converter)

        namespace = dict()

        namespace['now'] = datetime.datetime.utcnow()
        namespace['neurons'] = neurons
        namespace['neuronNames'] = [
            str(neuron.get_name()) for neuron in neurons
        ]
        namespace['printer'] = NestPrinter(latex_expression_printer)
        namespace['assignments'] = NestAssignmentsHelper()
        namespace['names'] = NestNamesConverter()
        namespace['declarations'] = NestDeclarationsHelper()
        namespace['utils'] = ASTUtils()
        namespace['odeTransformer'] = OdeTransformer()

        return namespace
示例#3
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def setup_generation_helpers(neuron):
    """
    Returns a standard namespace with often required functionality.
    :param neuron: a single neuron instance
    :type neuron: ASTNeuron
    :return: a map from name to functionality.
    :rtype: dict
    """
    gsl_converter = GSLReferenceConverter()
    gsl_printer = LegacyExpressionPrinter(gsl_converter)
    # helper classes and objects
    converter = NESTReferenceConverter(False)
    legacy_pretty_printer = LegacyExpressionPrinter(converter)

    namespace = dict()

    namespace['neuronName'] = neuron.get_name()
    namespace['neuron'] = neuron
    namespace['moduleName'] = FrontendConfiguration.get_module_name()
    namespace['printer'] = NestPrinter(legacy_pretty_printer)
    namespace['assignments'] = NestAssignmentsHelper()
    namespace['names'] = NestNamesConverter()
    namespace['declarations'] = NestDeclarationsHelper()
    namespace['utils'] = ASTUtils()
    namespace['idemPrinter'] = LegacyExpressionPrinter()
    namespace['outputEvent'] = namespace['printer'].print_output_event(neuron.get_body())
    namespace['is_spike_input'] = ASTUtils.is_spike_input(neuron.get_body())
    namespace['is_current_input'] = ASTUtils.is_current_input(neuron.get_body())
    namespace['odeTransformer'] = OdeTransformer()
    namespace['printerGSL'] = gsl_printer
    namespace['now'] = datetime.datetime.utcnow()

    define_solver_type(neuron, namespace)
    return namespace
示例#4
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    def setup_generation_helpers(self, neuron):
        """
        Returns a standard namespace with often required functionality.
        :param neuron: a single neuron instance
        :type neuron: ASTNeuron
        :return: a map from name to functionality.
        :rtype: dict
        """
        gsl_converter = GSLReferenceConverter()
        gsl_printer = LegacyExpressionPrinter(gsl_converter)
        # helper classes and objects
        converter = NESTReferenceConverter(False)
        legacy_pretty_printer = LegacyExpressionPrinter(converter)

        namespace = dict()

        namespace['neuronName'] = neuron.get_name()
        namespace['neuron'] = neuron
        namespace['moduleName'] = FrontendConfiguration.get_module_name()
        namespace['printer'] = NestPrinter(legacy_pretty_printer)
        namespace['assignments'] = NestAssignmentsHelper()
        namespace['names'] = NestNamesConverter()
        namespace['declarations'] = NestDeclarationsHelper()
        namespace['utils'] = ASTUtils()
        namespace['idemPrinter'] = LegacyExpressionPrinter()
        namespace['outputEvent'] = namespace['printer'].print_output_event(neuron.get_body())
        namespace['is_spike_input'] = ASTUtils.is_spike_input(neuron.get_body())
        namespace['is_current_input'] = ASTUtils.is_current_input(neuron.get_body())
        namespace['odeTransformer'] = OdeTransformer()
        namespace['printerGSL'] = gsl_printer
        namespace['now'] = datetime.datetime.utcnow()
        namespace['tracing'] = FrontendConfiguration.is_dev

        namespace['PredefinedUnits'] = pynestml.symbols.predefined_units.PredefinedUnits
        namespace['UnitTypeSymbol'] = pynestml.symbols.unit_type_symbol.UnitTypeSymbol

        rng_visitor = ASTRandomNumberGeneratorVisitor()
        neuron.accept(rng_visitor)
        namespace['norm_rng'] = rng_visitor._norm_rng_is_used

        self.define_solver_type(neuron, namespace)
        return namespace
示例#5
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    def setup_generation_helpers(self, neuron: ASTNeuron) -> Dict:
        """
        Returns a standard namespace with often required functionality.
        :param neuron: a single neuron instance
        :type neuron: ASTNeuron
        :return: a map from name to functionality.
        :rtype: dict
        """
        gsl_converter = GSLReferenceConverter()
        gsl_printer = UnitlessExpressionPrinter(gsl_converter)
        # helper classes and objects
        converter = NESTReferenceConverter(False)
        unitless_pretty_printer = UnitlessExpressionPrinter(converter)

        namespace = dict()

        namespace['neuronName'] = neuron.get_name()
        namespace['neuron'] = neuron
        namespace['moduleName'] = FrontendConfiguration.get_module_name()
        namespace['printer'] = NestPrinter(unitless_pretty_printer)
        namespace['assignments'] = NestAssignmentsHelper()
        namespace['names'] = NestNamesConverter()
        namespace['declarations'] = NestDeclarationsHelper()
        namespace['utils'] = ASTUtils()
        namespace['idemPrinter'] = UnitlessExpressionPrinter()
        namespace['outputEvent'] = namespace['printer'].print_output_event(
            neuron.get_body())
        namespace['is_spike_input'] = ASTUtils.is_spike_input(
            neuron.get_body())
        namespace['is_current_input'] = ASTUtils.is_current_input(
            neuron.get_body())
        namespace['odeTransformer'] = OdeTransformer()
        namespace['printerGSL'] = gsl_printer
        namespace['now'] = datetime.datetime.utcnow()
        namespace['tracing'] = FrontendConfiguration.is_dev

        namespace[
            'PredefinedUnits'] = pynestml.symbols.predefined_units.PredefinedUnits
        namespace[
            'UnitTypeSymbol'] = pynestml.symbols.unit_type_symbol.UnitTypeSymbol

        namespace['initial_values'] = {}
        namespace['uses_analytic_solver'] = neuron.get_name() in self.analytic_solver.keys() \
            and self.analytic_solver[neuron.get_name()] is not None
        if namespace['uses_analytic_solver']:
            namespace['analytic_state_variables'] = self.analytic_solver[
                neuron.get_name()]["state_variables"]
            namespace['analytic_variable_symbols'] = {
                sym:
                neuron.get_equations_block().get_scope().resolve_to_symbol(
                    sym, SymbolKind.VARIABLE)
                for sym in namespace['analytic_state_variables']
            }
            namespace['update_expressions'] = {}
            for sym, expr in self.analytic_solver[
                    neuron.get_name()]["initial_values"].items():
                namespace['initial_values'][sym] = expr
            for sym in namespace['analytic_state_variables']:
                expr_str = self.analytic_solver[
                    neuron.get_name()]["update_expressions"][sym]
                expr_ast = ModelParser.parse_expression(expr_str)
                # pretend that update expressions are in "equations" block, which should always be present, as differential equations must have been defined to get here
                expr_ast.update_scope(
                    neuron.get_equations_blocks().get_scope())
                expr_ast.accept(ASTSymbolTableVisitor())
                namespace['update_expressions'][sym] = expr_ast

            namespace['propagators'] = self.analytic_solver[
                neuron.get_name()]["propagators"]

        namespace['uses_numeric_solver'] = neuron.get_name() in self.analytic_solver.keys() \
            and self.numeric_solver[neuron.get_name()] is not None
        if namespace['uses_numeric_solver']:
            namespace['numeric_state_variables'] = self.numeric_solver[
                neuron.get_name()]["state_variables"]
            namespace['numeric_variable_symbols'] = {
                sym:
                neuron.get_equations_block().get_scope().resolve_to_symbol(
                    sym, SymbolKind.VARIABLE)
                for sym in namespace['numeric_state_variables']
            }
            assert not any([
                sym is None
                for sym in namespace['numeric_variable_symbols'].values()
            ])
            namespace['numeric_update_expressions'] = {}
            for sym, expr in self.numeric_solver[
                    neuron.get_name()]["initial_values"].items():
                namespace['initial_values'][sym] = expr
            for sym in namespace['numeric_state_variables']:
                expr_str = self.numeric_solver[
                    neuron.get_name()]["update_expressions"][sym]
                expr_ast = ModelParser.parse_expression(expr_str)
                # pretend that update expressions are in "equations" block, which should always be present, as differential equations must have been defined to get here
                expr_ast.update_scope(
                    neuron.get_equations_blocks().get_scope())
                expr_ast.accept(ASTSymbolTableVisitor())
                namespace['numeric_update_expressions'][sym] = expr_ast

            namespace['useGSL'] = namespace['uses_numeric_solver']
            namespace['names'] = GSLNamesConverter()
            converter = NESTReferenceConverter(True)
            unitless_pretty_printer = UnitlessExpressionPrinter(converter)
            namespace['printer'] = NestPrinter(unitless_pretty_printer)

        namespace["spike_updates"] = neuron.spike_updates

        rng_visitor = ASTRandomNumberGeneratorVisitor()
        neuron.accept(rng_visitor)
        namespace['norm_rng'] = rng_visitor._norm_rng_is_used

        return namespace