def peak_index(curve):
"""Find index to the peak of the provided curve."""
curve = curve.reshape((1, curve.size))
pot_peak_indices, _ = Hvsr.find_peaks(curve)
pot_peak_indices = pot_peak_indices[0]
pot_peak_amp = curve[0, pot_peak_indices]
pot_peak_index = np.argwhere(pot_peak_amp == np.max(pot_peak_amp))[0][0]
return pot_peak_indices[pot_peak_index]
def mc_peak_frq(self, distribution='log-normal'):
"""Frequency of the peak of the mean H/V curve.
Parameters
----------
distribution : {'normal', 'log-normal'}, optional
Refer to :meth:`mean_curve <Hvsr.mean_curve>` for details.
Returns
-------
float
Frequency associated with the peak of the mean H/V curve.
"""
mc = self.mean_curve(distribution)
return float(self.frq[np.where(mc == np.max(mc[Hvsr.find_peaks(mc)[0]]))])
def mc_peak_amp(self, distribution='log-normal'):
"""Amplitude of the peak of the mean H/V curve.
Parameters
----------
distribution : {'normal', 'log-normal'}, optional
Refer to :meth:`mean_curve <Hvsr.mean_curve>` for details.
Returns
-------
float
Amplitude associated with the peak of the mean H/V curve.
"""
mc = self.mean_curve(distribution)
return np.max(mc[Hvsr.find_peaks(mc)[0]])
def mc_peak_frq(self, distribution='lognormal'):
"""Frequency of the peak of the mean HVSR curve.
Parameters
----------
distribution : {'normal', 'lognormal'}, optional
Refer to :meth:`mean_curve <Hvsr.mean_curve>` for details.
Returns
-------
float
Frequency associated with the peak of the mean HVSR curve.
"""
mc = self.mean_curve(distribution)
mc = mc.reshape((1, mc.size))
i_low, i_high = self.hvsrs[0].i_low, self.hvsrs[0].i_high
return self.frq[i_low + int(np.where(mc[0, i_low:i_high] == np.max(mc[0, Hvsr.find_peaks(mc[:, i_low:i_high], starting_index=i_low)[0]]))[0])]
def mc_peak_amp(self, distribution='lognormal'):
"""Amplitude of the peak of the mean HVSR curve.
Parameters
----------
distribution : {'normal', 'lognormal'}, optional
Refer to :meth:`mean_curve <Hvsr.mean_curve>` for details.
Returns
-------
float
Amplitude associated with the peak of the mean HVSR curve.
"""
mc = self.mean_curve(distribution)
mc = mc.reshape((1, mc.size))
i_low, i_high = self.hvsrs[0].i_low, self.hvsrs[0].i_high
return np.max(mc[0, Hvsr.find_peaks(mc[:, i_low:i_high], starting_index=i_low)[0]])
def peak_index(curve):
"""Find index to the peak of the provided curve."""
pot_peak_indices, _ = Hvsr.find_peaks(curve)
pot_peak_amp = curve[pot_peak_indices]
pot_peak_index = np.argwhere(pot_peak_amp == np.max(pot_peak_amp))[0][0]
return pot_peak_indices[pot_peak_index]