sdynpy.signal_processing.sdynpy_srs.WindowedRandomResults

Module: sdynpy.signal_processing.sdynpy_srs
Source: GitHub

Signature¶

class sdynpy.signal_processing.sdynpy_srs.WindowedRandomResults(time: numpy.ndarray, sample_rate: float, gravity: float, window: numpy.ndarray, ref_srs: numpy.ndarray, srs_frequency: numpy.ndarray, srs_matrix: numpy.ndarray, xc_matrix: numpy.ndarray, rr_matrix: numpy.ndarray, metrics: List[sdynpy.signal_processing.sdynpy_srs.WindowedRandomMetrics], metadata: Dict[str, Any]) -> None

Collection of generated windowed-random realizations and associated results.

Parameters¶

time : ndarray Time vector with shape (n_samples,).
sample_rate : float Sampling rate in samples per second.
gravity : float Acceleration-of-gravity conversion factor used when integrating acceleration to obtain velocity and displacement.
window : ndarray Applied time-domain window with shape (n_samples,).
ref_srs : ndarray Reference SRS breakpoint array with shape (n_breakpoints, 2). The first column contains frequency and the second contains spectral amplitude.
srs_frequency : ndarray Frequency vector corresponding to srs_matrix, with shape (n_freq,).
srs_matrix : ndarray Computed SRS values for each realization, with shape (n_freq, n_realizations).
xc_matrix : ndarray Compensated windowed acceleration histories, with shape (n_samples, n_realizations).
rr_matrix : ndarray Stationary random acceleration histories prior to windowing, with shape (n_samples, n_realizations).
metrics : list of WindowedRandomMetrics Metrics for each realization.
metadata : dict Dictionary of generation settings and other bookkeeping information.

Notes¶

Each column of xc_matrix, rr_matrix, and srs_matrix corresponds to one realization.

Attributes¶

Name	Summary
`metrics_array`	Return the realization metrics as a dense numeric array.

`metrics_array`¶

Return the realization metrics as a dense numeric array.

Returns¶

ndarray
Array with shape (n_realizations, 6) containing columns:
1. LANL RMS dB error
2. energy
3. REA
4. peak acceleration
5. peak velocity
6. peak displacement

Methods¶

Name	Summary
`__init__`	Initialize self. See help(type(self)) for accurate signature.

`init`¶

def sdynpy.signal_processing.sdynpy_srs.WindowedRandomResults.__init__(self, time: numpy.ndarray, sample_rate: float, gravity: float, window: numpy.ndarray, ref_srs: numpy.ndarray, srs_frequency: numpy.ndarray, srs_matrix: numpy.ndarray, xc_matrix: numpy.ndarray, rr_matrix: numpy.ndarray, metrics: List[sdynpy.signal_processing.sdynpy_srs.WindowedRandomMetrics], metadata: Dict[str, Any]) -> None

Initialize self. See help(type(self)) for accurate signature.