signal_flow_graph.py

                        if key == element:
                            temp_value += int(value)
                mat_content[row, column] += temp_value
            elif "in" in lista[0] and "out" in lista[-1]:
                row = len(delay_element_used) + int(lista[-1].replace("out", ""))
                column = len(delay_element_used) + int(lista[0].replace("in", ""))
                temp_value = 1
                for element in lista:
                    if "cmul" in element:
                        temp_value *= self.find_by_id(element).value
                    for key, value in addition_with_constant.items():
                        if key == element:
                            temp_value += int(value)
                mat_content[row, column] += temp_value
            elif lista[0][0] == 't' and lista[-1][0] == 't':
                row = int(lista[-1].replace("t", ""))
                column = int(lista[0].replace("t", ""))
                temp_value = 1
                for element in lista:
                    if "cmul" in element:
                        temp_value *= self.find_by_id(element).value
                    for key, value in addition_with_constant.items():
                        if key == element:
                            temp_value += int(value)
                mat_content[row, column] += temp_value
            elif lista[0][0] == 't' and "out" in lista[-1]:
                row = len(delay_element_used) + int(lista[-1].replace("out", ""))
                column = int(lista[0].replace("t", ""))
                temp_value = 1
                for element in lista:
                    if "cmul" in element:
                        temp_value *= self.find_by_id(element).value
                    for key, value in addition_with_constant.items():
                        if key == element:
                            temp_value += int(value)
                mat_content[row, column] += temp_value
        return matrix_answer, mat_content, matrix_in

    def find_all_paths(self, graph: dict, start: str, end: str, path=[]) -> list:
        """
        Returns all paths in graph from node start to node end

        Parameters
        ----------
        graph : dictionary
            The dictionary that are to be searched for loops.
        start : key in dictionary graph
            The "node" in the dictionary that are set as the start point.
        end : key in dictionary graph
            The "node" in the dictionary that are set as the end point.

        Returns
        -------
        The state-space representation of the SFG.
        """
        path = path + [start]
        if start == end:
            return [path]
        if start not in graph:
            return []
        paths = []
        for node in graph[start]:
            if node not in path:
                newpaths = self.find_all_paths(graph, node, end, path)
                for newpath in newpaths:
                    paths.append(newpath)
        return paths

    def edit(self) -> dict[str, "SFG"]:
        """Edit SFG in GUI."""
        from b_asic.GUI.main_window import start_editor

        return start_editor(self)

    def unfold(self, factor: int) -> "SFG":
        """
        Unfold the SFG *factor* times. Return a new SFG without modifying the original.

        Inputs and outputs are ordered with early inputs first. That is for an SFG
        with n inputs, the first n inputs are the inputs at time t, the next n
        inputs are the inputs at time t+1, the next n at t+2 and so on.

        Parameters
        ----------
        factor : int
            Number of times to unfold.
        """

        if factor == 0:
            raise ValueError("Unfolding 0 times removes the SFG")

        sfg = self()  # copy the sfg

        inputs = sfg.input_operations
        outputs = sfg.output_operations

        # Remove all delay elements in the SFG and replace each one
        # with one input operation and one output operation
        for delay in sfg.find_by_type_name(Delay.type_name()):
            i = Input(name="input_" + delay.graph_id)
            o = Output(
                src0=delay.input(0).signals[0].source, name="output_" + delay.graph_id
            )

            inputs.append(i)
            outputs.append(o)

            # move all outgoing signals from the delay to the new input operation
            while len(delay.output(0).signals) > 0:
                signal = delay.output(0).signals[0]
                destination = signal.destination
                destination.remove_signal(signal)
                signal.remove_source()
                destination.connect(i.output(0))

            delay.input(0).signals[0].remove_source()
            delay.input(0).clear()

        new_sfg = SFG(inputs, outputs)  # The new sfg without the delays

        sfgs = [new_sfg() for _ in range(factor)]  # Copy the SFG factor times

        # Add suffixes to all graphIDs and names in order to keep them separated
        for i in range(factor):
            for operation in sfgs[i].operations:
                suffix = f'_{i}'
                operation.graph_id = operation.graph_id + suffix
                if operation.name[:7] not in ['', 'input_t', 'output_']:
                    operation.name = operation.name + suffix

        input_name_to_idx = {}  # save the input port indices for future reference
        new_inputs = []
        # For each copy of the SFG, create new input operations for every "original"
        # input operation and connect them to begin creating the unfolded SFG
        for i in range(factor):
            for port, operation in zip(sfgs[i].inputs, sfgs[i].input_operations):
                if not operation.name.startswith("input_t"):
                    i = Input()
                    new_inputs.append(i)
                    port.connect(i)
                else:
                    # If the input was created earlier when removing the delays
                    # then just save the index
                    input_name_to_idx[operation.name] = port.index

        # Connect the original outputs in the same way as the inputs
        # Also connect the copies of the SFG together according to a formula
        # from the TSTE87 course material, and save the number of delays for
        # each interconnection
        new_outputs = []
        delay_placements = {}
        for i in range(factor):
            for port, operation in zip(sfgs[i].outputs, sfgs[i].output_operations):
                if not operation.name.startswith("output_t"):
                    new_outputs.append(Output(port))
                else:
                    index = operation.name[8:]  # Remove the "output_t" prefix
                    j = (i + 1) % factor
                    number_of_delays_between = (i + 1) // factor
                    input_port = sfgs[j].input(input_name_to_idx["input_t" + index])
                    input_port.connect(port)
                    delay_placements[port] = [i, number_of_delays_between]
            sfgs[i].graph_id = (
                f'sfg{i}'  # deterministically set the graphID of the sfgs
            )

        sfg = SFG(new_inputs, new_outputs)  # create a new SFG to remove floating nodes

        # Insert the interconnect delays according to what is saved in delay_placements
        for port, val in delay_placements.items():
            i, no_of_delays = val
            for _ in range(no_of_delays):
                sfg = sfg.insert_operation_after(f'sfg{i}.{port.index}', Delay())

        # Flatten all the copies of the original SFG
        for i in range(factor):
            sfg.find_by_id(f'sfg{i}').connect_external_signals_to_components()
            sfg = sfg()

        return sfg

    @property
    def is_linear(self) -> bool:
        return all(op.is_linear for op in self.split())

    @property
    def is_constant(self) -> bool:
        return all(output.is_constant for output in self._output_operations)

    def get_used_type_names(self) -> list[TypeName]:
        """Get a list of all TypeNames used in the SFG."""
        ret = list({op.type_name() for op in self.operations})
        ret.sort()
        return ret

    def get_used_graph_ids(self) -> set[GraphID]:
        """Get a list of all GraphID:s used in the SFG."""
        ret = set({op.graph_id for op in self.operations})
        sorted(ret)
        return ret