Function start_log has a Cognitive Complexity of 7 (exceeds 5 allowed). Consider refactoring.

Open

    def start_log(self, opt, logdir):
        self.opt_map = opt.pmap.get_opt_map()
        print("create log at", logdir)
        self.writer = tf.summary.create_file_writer(
            logdir=logdir,

• Read up
  Read up

Avoid too many return statements within this function.

Open

            return (

Avoid too many return statements within this function.

Open

            return val * (10 ** (-3 * (len(big_units) - 1))), big_units[-1]

Avoid too many return statements within this function.

Open

            return tape.gradient(val, phi_variable)

Avoid too many return statements within this function.

Open

            return grad

Avoid too many return statements within this function.

Open

    return sign * (10 ** (tmp % 3)), prefix

Function slepian_fourier has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def slepian_fourier(t, params):
    """
    ----
    """
    t_final = tf.cast(params["t_final"].get_value(), tf.float64)

• Read up
  Read up

Function quick_setup has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def quick_setup(self, cfg, base_dir: str = None) -> None:
        """
        Load a quick setup cfg and create all necessary components.

        Parameters

• Read up
  Read up

Function get_potential_function has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def get_potential_function(self, phi_variable, deriv_order=1, phi_sig=0):
        phi = (
            (self.params["phi"].get_value() + phi_sig)
            / self.params["phi_0"].get_value()
            * 2

• Read up
  Read up

Function Hs_of_t has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def Hs_of_t(self, signal, interpolate_res=2):
        """
        Generate a list of Hamiltonians for each time step of interpolated signal for Runge-Kutta Methods.

        Args:

• Read up
  Read up

Function get_noise has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def get_noise(self, sig):
        noise_amp = self.params["noise_amp"].get_value().numpy()
        bfl_num = int(self.params["bfl_num"].get_value().numpy())
        noise = []
        bfls = 2 * np.random.randint(2, size=bfl_num) - 1

• Read up
  Read up

Function set_max_excitations has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def set_max_excitations(self, max_excitations) -> None:
        """
        Set the maximum number of excitations in the system used for propagation.
        """
        if max_excitations:

• Read up
  Read up

Function __initialize_parameters has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def __initialize_parameters(self) -> None:
        par_lens = {}
        pars = {}
        par_ids_model = []
        for comp in self.__components.values():

• Read up
  Read up

Function set_init_state has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def set_init_state(self, state):
        if self.lindbladian and state.shape[0] != state.shape[1]:
            if state.shape[0] == self.tot_dim:
                self.init_state = tf_utils.tf_state_to_dm(state)
            elif state.shape[0] == self.tot_dim**2:

• Read up
  Read up

Function ask_yn has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

def ask_yn() -> bool:
    """Ask for y/n user decision in the command line."""
    asking = True
    text = input("(y/n): ")
    if text == "y":

• Read up
  Read up

Function fromdict has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def fromdict(self, cfg: dict) -> None:
        """
        Load a file and parse it to create a Model object.

        Parameters

• Read up
  Read up

Function get_minimum_phi_var has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def get_minimum_phi_var(self, init_phi_variable: tf.float64 = 0, phi_sig=0):
        # TODO maybe improve to analytical funciton here
        # TODO do not reevaluate if not necessary
        phi_0 = self.params["phi_0"].get_value()
        initial_pot_eval = self.get_potential_function(0.0, 0)

• Read up
  Read up

Function update_Hamiltonians has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def update_Hamiltonians(self):
        """Recompute the matrix representations of the Hamiltonians."""
        control_hams = dict()
        hamiltonians = dict()
        for key, sub in self.subsystems.items():

• Read up
  Read up

Function get_Frame_Rotation has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def get_Frame_Rotation(self, t_final: np.float64, freqs: dict, framechanges: dict):
        """
        Compute the frame rotation needed to align Lab frame and rotating Eigenframes
        of the qubits.

• Read up
  Read up

Function get_potential_function has a Cognitive Complexity of 6 (exceeds 5 allowed). Consider refactoring.

Open

    def get_potential_function(
        self, phi_variable, deriv_order=1, phi_sig=0
    ) -> tf.float64:
        if phi_sig != 0:
            raise NotImplementedError()

• Read up
  Read up