sdynpy.MultipleCoherenceArray

• Defined as: sdynpy.core.sdynpy_data.MultipleCoherenceArray

• Module: sdynpy.core.sdynpy_data

• Source: GitHub

• Parent: sdynpy.NDDataArray

• Parent: sdynpy.SdynpyArray

• Parent: numpy.ndarray

Signature¶

class sdynpy.MultipleCoherenceArray(shape, nelements, buffer=None, offset=0, strides=None, order=None)

Data array used to store coherence data

Attributes¶

function_type¶

Returns the function type of the data array

Methods¶

from_time_data¶

• Source: GitHub

def sdynpy.MultipleCoherenceArray.from_time_data(response_data: sdynpy.core.sdynpy_data.TimeHistoryArray, samples_per_average: int = None, overlap: float = 0.0, window=array([1.]), reference_data: sdynpy.core.sdynpy_data.TimeHistoryArray = None)

Computes coherence from reference and response time histories

Parameters¶

• response_data : TimeHistoryArray Time data to be used as responses

• samples_per_average : int, optional Number of samples used to split up the signals into averages. The default is None, meaning the data is treated as a single measurement frame.

• overlap : float, optional The overlap as a fraction of the frame (e.g. 0.5 specifies 50% overlap). The default is 0.0, meaning no overlap is used.

• window : np.ndarray or str, optional A 1D ndarray with length samples_per_average that specifies the coefficients of the window. A Hann window is applied if not specified. If a string is specified, then the window will be obtained from scipy.

• reference_data : TimeHistoryArray Time data to be used as reference. If not specified, the response data will be used as references, resulting in a square coherence matrix.

Returns¶

• PowerSpectralDensityArray

• A PSD array computed from the specified reference and

• response signals.

Raises¶

• ValueError

• Raised if reference and response functions do not have consistent

• abscissa