ExperimentalIRF Class

class openirf.ExperimentalIRF(t_vec=array([], dtype=float64), y_vec=array([], shape=(0, 0, 0), dtype=float64), f_vec=array([], shape=(0, 0, 0), dtype=float64))

OpenIRF Experimental IRF Class

Stores time series (t_vec,y_vec_,f_vec) for IRF calculation.

Shape of time series arrays

• 3D: Multiple dofs, multiple measurements (dof,number_of_measurements,points)

• 2D: Single dof, multiple measurements (number_of_measurements,points)

• 1D: Single dof, one measurement (points)

Constraints

• t_vec must matched stored t_vec (if already stored)

• All data must share the same t_vec

• Data cannot be added without a specified or already stored t_vec

Attributes

param t_vec:

Time vector of time series y_vec and f_vec.

type t_vec:

ndarray

param y_vec:

Time series of system responses.

type y_vec:

ndarray

param f_vec:

Time series of applied forces.

type f_vec:

ndarray

add_time_series(y_vec, f_vec, t_vec=None)

Add Time Series

This method allows to add time series to the class istance.

Shape of time series arrays

• 3D: Multiple dofs, multiple measurements (dof,number_of_measurements,points)

• 2D: Single dof, multiple measurements (number_of_measurements,points)

• 1D: Single dof, one measurement (points)

Constraints

• t_vec must matched stored t_vec (if already stored)

• All data must share the same t_vec

• Data cannot be added without a specified or already stored t_vec

Parameters

param t_vec:

Time vector of time series y_vec and f_vec.

type t_vec:

ndarray

param y_vec:

Time series of system responses.

type y_vec:

ndarray

param f_vec:

Time series of applied forces.

type f_vec:

ndarray, optional

f_vec = array([], shape=(0, 0, 0), dtype=float64)

t_vec = array([], dtype=float64)

y_vec = array([], shape=(0, 0, 0), dtype=float64)