Subgraph Netlist Decorator

class hal_py.SubgraphNetlistDecorator
__init__(self: hal_py.SubgraphNetlistDecorator, netlist: hal_py.Netlist) → None

Construct new SubgraphNetlistDecorator object.

Parameters:netlist (hal_py.Netlist) – The netlist to operate on.
copy_subgraph_netlist(*args, **kwargs)

Overloaded function.

  1. copy_subgraph_netlist(self: hal_py.SubgraphNetlistDecorator, subgraph_gates: List[hal_py.Gate]) -> hal_py.Netlist

    Get a deep copy of a netlist subgraph including all of its gates and nets, but excluding modules and groupings.

    param list[hal_py.Gate] subgraph_gates:
     The gates making up the subgraph that shall be copied from the netlist.
    returns:The copied subgraph netlist on success, None otherwise.
    rtype:hal_py.Netlist or None

  2. copy_subgraph_netlist(self: hal_py.SubgraphNetlistDecorator, subgraph_module: hal_py.Module) -> hal_py.Netlist

    Get a deep copy of a netlist subgraph including all of its gates and nets, but excluding modules and groupings.

    param hal_py.Module subgraph_module:
     The module making up the subgraph that shall be copied from the netlist.
    returns:The copied subgraph netlist on success, None otherwise.
    rtype:hal_py.Netlist or None
get_subgraph_function(*args, **kwargs)

Overloaded function.

  1. get_subgraph_function(self: hal_py.SubgraphNetlistDecorator, subgraph_gates: List[hal_py.Gate], subgraph_output: hal_py.Net, cache: Dict[Tuple[int, hal_py.GatePin], hal_py.BooleanFunction]) -> Optional[hal_py.BooleanFunction]

    Get the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. The variables of the resulting Boolean function are created from the subgraph input nets using ‘BooleanFunctionNetDecorator.get_boolean_variable’. Utilizes a cache for speedup on consecutive calls.

    param list[hal_py.Gate] subgraph_gates:
     The gates making up the subgraph to consider.
    param hal_py.Net subgraph_output:
     The subgraph oputput net for which to generate the Boolean function.
    param dict[tuple(int,hal_py.GatePin),hal_py.BooleanFunction] cache:
     Cache to speed up computations. The cache is filled by this function.
    returns:The combined Boolean function of the subgraph on success, None otherwise.
    rtype:hal_py.BooleanFunction or None

  2. get_subgraph_function(self: hal_py.SubgraphNetlistDecorator, subgraph_gates: List[hal_py.Gate], subgraph_output: hal_py.Net) -> Optional[hal_py.BooleanFunction]

    Get the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. The variables of the resulting Boolean function are created from the subgraph input nets using ‘BooleanFunctionNetDecorator.get_boolean_variable’.

    param list[hal_py.Gate] subgraph_gates:
     The gates making up the subgraph to consider.
    param hal_py.Net subgraph_output:
     The subgraph oputput net for which to generate the Boolean function.
    returns:The combined Boolean function of the subgraph on success, None otherwise.
    rtype:hal_py.BooleanFunction or None

  3. get_subgraph_function(self: hal_py.SubgraphNetlistDecorator, subgraph_module: hal_py.Module, subgraph_output: hal_py.Net, cache: Dict[Tuple[int, hal_py.GatePin], hal_py.BooleanFunction]) -> Optional[hal_py.BooleanFunction]

    Get the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. The variables of the resulting Boolean function are created from the subgraph input nets using ‘BooleanFunctionNetDecorator.get_boolean_variable’. Utilizes a cache for speedup on consecutive calls.

    param hal_py.Module subgraph_module:
     The module making up the subgraph to consider.
    param hal_py.Net subgraph_output:
     The subgraph oputput net for which to generate the Boolean function.
    param dict[tuple(int,hal_py.GatePin),hal_py.BooleanFunction] cache:
     Cache to speed up computations. The cache is filled by this function.
    returns:The combined Boolean function of the subgraph on success, None otherwise.
    rtype:hal_py.BooleanFunction or None

  4. get_subgraph_function(self: hal_py.SubgraphNetlistDecorator, subgraph_module: hal_py.Module, subgraph_output: hal_py.Net) -> Optional[hal_py.BooleanFunction]

    Get the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. The variables of the resulting Boolean function are created from the subgraph input nets using ‘BooleanFunctionNetDecorator.get_boolean_variable’.

    :param hal_py.Module subgraph_module:The module making up the subgraph to consider. :param hal_py.Net subgraph_output: The subgraph oputput net for which to generate the Boolean function. :returns: The combined Boolean function of the subgraph on success, None otherwise. :rtype: hal_py.BooleanFunction or None

get_subgraph_function_inputs(*args, **kwargs)

Overloaded function.

  1. get_subgraph_function_inputs(self: hal_py.SubgraphNetlistDecorator, subgraph_gates: List[hal_py.Gate], subgraph_output: hal_py.Net) -> Optional[Set[hal_py.Net]]

    Get the inputs of the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. This does not actually build the boolean function but only determines the inputs the subgraph function would have, which is a lot faster.

    param list[hal_py.Gate] subgraph_gates:
     The subgraph_gates making up the subgraph to consider.
    param hal_py.Net subgraph_output:
     The subgraph oputput net from which to start the back propagation from.
    returns:The input nets that would be the input for the subgraph function
    rtype:set(hal_py.Net) or None

  2. get_subgraph_function_inputs(self: hal_py.SubgraphNetlistDecorator, subgraph_module: hal_py.Module, subgraph_output: hal_py.Net) -> Optional[Set[hal_py.Net]]

    Get the inputs of the combined Boolean function of a subgraph of combinational gates starting at the source of the provided subgraph output net. This does not actually build the boolean function but only determines the inputs the subgraph function would have, which is a lot faster.

    :param hal_py.Module subgraph_module:The module making up the subgraph to consider. :param hal_py.Net subgraph_output: The subgraph oputput net from which to start the back propagation from. :returns: The input nets that would be the input for the subgraph function :rtype: set(hal_py.Net) or None