watex.methods.em.MT.remove_ss_emap#
- MT.remove_ss_emap(fltr='ama', out=False, smooth=True, drop_outliers=True, rotate=0.0, update_z=True)[source]#
Filter Z to remove the static schift using the EMAP moving average filters.
Three available filters:
‘ama’: Adaptative moving average
‘tma’: Trimming moving-average
‘flma’: Fixed-length dipole moving average
Could export new Edi if the keyword argument export is set to
True- Parameters:
fltr (str , default='ama') –
Type of filter to apply. Default is Adaptative moving-average of Torres-verdin [1]. Can be [‘ama’|’tma’|’flma’]
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.
out (bool , default =False,) – Output new filtered EDI. Otherwise return Z collections objects of corrected Tensors.
smooth (bool, default=False,) – Smooth the tensor data along the frequencies.
versionadded (..)
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.versionadded – Polish the tensor data along the frequency axis remove noises and deal with the static shift effect when interferences noises are strong enough.
- Returns:
self
- Return type:
watex.methods.ZCfor methods chaining.
References
[1]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
See also
remove_static_shiftRemove static shift using the spatial filter median and write a new edifile.
Examples
>>> import watex >>> from watex.methods import ZC >>> edi_sample = watex.fetch_data ('edis', samples =17 , return_data =True ) >>> zo = ZC ().fit(edi_sample) >>> zo.ediObjs_[0].Z.z[:, 0, 1][:7] array([10002.46 +9747.34j , 11679.44 +8714.329j, 15896.45 +3186.737j, 21763.01 -4539.405j, 28209.36 -8494.808j, 19538.68 -2400.844j, 8908.448+5251.157j]) >>> zc = zo.remove_ss_emap() >>> zc[0].z[:, 0, 1] [:7] array([12120.08320804+6939.9874753j , 13030.91462606+6522.58481295j, 15432.0206124 +4970.42806287j, 21899.60942244+3826.47476912j, 29109.17100085+4537.17072741j, 19252.07839732+4108.71578943j, 9473.20464326+4146.50327315j])