rose.utils package

Submodules

rose.utils.Hmax module

class rose.utils.Hmax.HrsmMax(signal: ndarray, dx: float, convert_m2mm: bool = True)

Bases: object

Computes the H rms and H max according to description of Level Accoustics report

Parameters:

  • signal – signal to be processed

  • dx – sampling frequency

  • convert_m2mm – (optional: default True) converts the signal from m to mm

Returns:

object

effective_values(n: int = 4, tau: int = 2, order: int = 3)

:param n:(optional, default = 4) number of time constants :param tau: (optional, default = 2) time constant :param order: (optional, default = 3) Butterworth filter order

power_spectral_density()

Computes power spectral density following Welch’s overlapped segment averaging estimator

rms_effective()

Computes RMS square root of power spectral density

rose.utils.Kalman_Filter module

class rose.utils.Kalman_Filter.KalmanFilter(initial_conditions, control_variable, process_variance, delta_t, independent=False)

Bases: object

Kalman filter: Two dimensional (e.g. displacement, velocity)

Parameters:

  • initial_conditions –

  • control_variable –

  • process_variance –

  • delta_t –

  • independent –

error_covariance_measures(sigma_xx, sigma_yy)
initial_cov_matrix(sigma_xx, sigma_yy)
initialise_control_matrices(timesteps: ndarray)

Initialise control matrices when timestep size is varying :param timesteps: :return:

kalman_gain()
new_observation(y)
predict_process_cov_matrix()
predicted_state()
state_matrix()
update_control_matrices(timestep)
update_control_matrices_by_index(t_idx)
update_process_covariance_matrix()

rose.utils.random_field module

rose.utils.random_field.create_rf(mean: float, coefficient_variation: float, len_scale: float, angles: float, nodes: ndarray, seed: int = 14, log_normal: bool = False) → ndarray

Create a 1D random field with a given mean and coefficient of variation.

Parameters

mean (float): mean of the random field coefficient_variation (float): coefficient of variation of the random field len_scale (float): length scale of the random field angles (float): angle of the random field nodes (np.ndarray): nodes of the random field seed (int): seed for the random field log_normal (bool): if True, the random field will be log-normal

Returns

np.ndarray: 1D random field

rose.utils.wolf_utils module

Module contents