watex.methods.em.EMAP.ama#

EMAP.ama(smooth=True, drop_outliers=True, return_phi=False)[source]#

Use an adaptive-moving-average filter to estimate average apparent resistivities at a single static-correction-reference frequency..

The AMA filter estimates static-corrected apparent resistivities at a single reference frequency by calculating a profile of average impedances along the length of the line. Sounding curves are then shifted so that they intersect the averaged profile.

Parameters:

  • smooth (bool, default=True,) – Smooth the tensor data along the frequencies.

  • drop_outliers (bool, default=True) – Suppress outliers in the data when smoothing data along the frequencies axis. Note that drop_outliers does not take effect if smooth is False.

  • return_phi (bool, default=False,) – return corrected phase. Mostly the phase does not need to correct since it is not affected by the static shift effect. However, it can be as smooth phase curve when smooth=True

  • versionadded: (..) – 0.2.1: Polish the tensor data along the frequency axis remove noises and deal with the static shift effect when interferences noises are strong enough.

Returns:

  • rc (np.ndarray, shape (N, M)) – EMAP apparent resistivity static shift corrected or static correction factor or impedance tensor.

  • rc, phi_c (Tuple of shape (N, N)) – EMAP apparent resistivity and phase corrected.

Example

>>> import watex as wx
>>> import matplotlib.pyplot as plt
>>> edi_data = wx.fetch_data ('edis', as_frame =True, key ='edi')
>>> p = wx.methods.EMAP (out='z').fit(edi_data.edi)
>>> z_corrected = p.ama () # output z in complex dtype
>>> plt.plot (np.arange (len(p.ediObjs_)) , np.abs(
    [ ediobj.Z.z[:, 0, 1][7]  for ediobj in p.ediObjs_]) , '-ok',
    np.arange(len(p.ediObjs_)), np.abs( z_corrected[7,: ]) , 'or-')

References

[2]

Torres-Verdin and Bostick, 1992, Principles of spatial surface electric field filtering in magnetotellurics: electromagnetic array profiling (EMAP), Geophysics, v57, p603-622.https://doi.org/10.1190/1.2400625

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