Add Scipy filters to xarray

[kujaku11]

Add ability to access filter methods directly from an xarray.DataArray or xarray.Dataset, this has been done in a package called xr-scipy, which doesn't seem to be supported much recently. So here we are going to update some of the filter methods and incorporate them within MTH5.

• Add decimation
• Add detrend
• Add zero mean
• Add lowpass
• Add highpass
• Add bandpass
• Add windowing?
• Update tests
• Update documentation

[codecov-commenter]

Codecov Report

Patch coverage: 63.87% and project coverage change: +0.04 🎉

Comparison is base (4281535) 58.71% compared to head (dbeca1b) 58.76%.

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Additional details and impacted files

@@            Coverage Diff             @@
##           master     #139      +/-   ##
==========================================
+ Coverage   58.71%   58.76%   +0.04%     
==========================================
  Files         118      120       +2     
  Lines       12292    12500     +208     
==========================================
+ Hits         7217     7345     +128     
- Misses       5075     5155      +80     

Impacted Files	Coverage Δ
mth5/io/collection.py	30.15% <0.00%> (-0.49%)	⬇️
mth5/io/phoenix/readers/header.py	33.60% <0.00%> (-0.10%)	⬇️
tests/io/lemi/test_lemi_collection.py	44.89% <0.00%> (-0.94%)	⬇️
tests/version_1/test_make_mth5_geomag.py	22.41% <0.00%> (ø)
tests/version_2/test_make_mth5_geomag.py	22.22% <0.00%> (ø)
mth5/io/usgs_ascii/header.py	34.21% <12.50%> (-0.46%)	⬇️
tests/io/zen/test_z3d.py	42.51% <28.57%> (ø)
mth5/timeseries/scipy_filters.py	54.92% <54.92%> (ø)
mth5/timeseries/channel_ts.py	82.06% <60.00%> (-0.63%)	⬇️
mth5/timeseries/run_ts.py	73.69% <60.00%> (-0.60%)	⬇️
... and 14 more

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