pyyeti.srs.srsmap

pyyeti.srs.srsmap(timeslice, tsoverlap, sig, sr, freq, Q, wep=0, **srsargs)

Make a shock response spectral map (‘waterfall’) over time and frequency.

Parameters:

• timeslice (scalar or string-integer) – If scalar, it is the length in seconds for each slice. If string, it contains the integer number of points for each slice. For example, if sr is 1000 samples/second, timeslice=0.75 is equivalent to timeslice="750".

• tsoverlap (scalar in [0, 1) or string-integer) – If scalar, is the fraction of each time-slice to overlap. If string, it contains the integer number of points to overlap. For example, if sr is 1000 samples/second, tsoverlap=0.5 and tsoverlap="500" each specify 50% overlap.

• sig (1d array_like) – Base acceleration signal; vector.

• sr (scalar) – The sample rate (samples/sec)

• freq (array_like) – Frequency vector in Hz. This defines the single DOF systems to use.

• Q (scalar) – Dynamic amplification factor \(Q = 1/(2\zeta)\) where \(\zeta\) is the fraction of critical damping.

• wep (scalar) – Argument for the pyyeti.dsp.windowends(); specifies the window-ends portion. Each time slice is passed through pyyeti.dsp.windowends() if wep > 0.

• **srsargs (miscellaneous options for srs()) – Allows the setting of ic, stype, peak, eqsine, etc options for srs(). See srs() for more information.

Returns:

• mp (2d ndarray) – The SRS map; columns span time, rows span frequency (so each column is an SRS curve). Time increases going across the columns and frequency increases going down the rows.

• t (1d ndarray) – Time vector of center times; corresponds to columns in map. Signal is assumed to start at time = 0.

• f (1d ndarray) – Frequency vector equal to the input freq; corresponds to rows in map.

Notes

This routine calls pyyeti.dsp.waterfall() for handling the timeslices and preparing the output. srs() and pyyeti.dsp.windowends() are passed to that function.

See also

srs(), pyyeti.dsp.waterfall(), pyyeti.dsp.windowends()

Examples

Generate a sine sweep signal @ 4 octaves/min; process in 2-second windows with 50% overlap; 2% windowends, compute equivalent sine.

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from pyyeti import srs
>>> from pyyeti import ytools
>>> from matplotlib import cm, colors
>>> sig, t, f = ytools.gensweep(10, 1, 50, 4)
>>> sr = 1/t[1]
>>> frq = np.arange(1., 50.1)
>>> Q = 20
>>> mp, t, f = srs.srsmap(2, .5, sig, sr, frq, Q, .02,
...                       eqsine=1)
>>> _ = plt.figure('Example', clear=True, layout='constrained')
>>> cs = plt.contour(t, f, mp, 40, cmap=cm.plasma)
>>> # This doesn't work in matplotlib 3.5.0:
>>> #   cbar = plt.colorbar()
>>> #   cbar.filled = True
>>> #   cbar.draw_all()
>>> # But this does:
>>> norm = colors.Normalize(
...            vmin=cs.cvalues.min(), vmax=cs.cvalues.max()
...        )
>>> sm = plt.cm.ScalarMappable(norm=norm, cmap=cs.cmap)
>>> cb = plt.colorbar(sm, ax=plt.gca())  # , ticks=cs.levels)
>>> #
>>> _ = plt.xlabel('Time (s)')
>>> _ = plt.ylabel('Frequency (Hz)')
>>> ttl = 'EQSINE Map of Sine-Sweep @ 4 oct/min, Q = 20'
>>> _ = plt.title(ttl)

Also show results on a 3D surface plot:

>>> fig = plt.figure("Example 2", clear=True,
...                  layout='constrained')
>>> ax = fig.add_subplot(projection="3d")
>>> x, y = np.meshgrid(t, f)
>>> surf = ax.plot_surface(x, y, mp, rstride=1, cstride=1,
...                        linewidth=0, cmap=cm.plasma)
>>> _ = fig.colorbar(surf, shrink=0.5, aspect=5)
>>> ax.view_init(azim=-123, elev=48)
>>> _ = ax.set_xlabel('Time (s)')
>>> _ = ax.set_ylabel('Frequency (Hz)')
>>> _ = ax.set_zlabel('Amplitude')
>>> _ = plt.title(ttl)