Add sqrtN solve for sherman-morrison and white noise kernels

[vhaasteren]

Let N be the white noise kernel (marginalizingNmat, ShermanMorrison, ndarray_alt, ...). The solve(x) method would calculate N^{-1}x. Assume that LL^T=N with L a Cholesky factor. Then the new sqrtsolve(x) would return L^{-1}x

This PR implements that

[codecov]

Codecov Report

❌ Patch coverage is 65.51724% with 20 lines in your changes missing coverage. Please review.
✅ Project coverage is 71.47%. Comparing base (e04d9d4) to head (9264b2c).
⚠️ Report is 27 commits behind head on dev.

Files with missing lines	Patch %	Lines
enterprise/signals/gp_signals.py	15.38%	11 Missing ⚠️
enterprise/signals/signal_base.py	80.00%	9 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##              dev     #419      +/-   ##
==========================================
- Coverage   72.53%   71.47%   -1.07%     
==========================================
  Files          13       13              
  Lines        3401     3306      -95     
==========================================
- Hits         2467     2363     -104     
- Misses        934      943       +9     

Files with missing lines	Coverage Δ
enterprise/signals/signal_base.py	89.73% <80.00%> (-1.78%)	⬇️
enterprise/signals/gp_signals.py	65.59% <15.38%> (-5.55%)	⬇️

... and 4 files with indirect coverage changes

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[vhaasteren]

Hi @AaronDJohnson, any chance you can give this a quick review? My p-value paper is entering production

[AaronDJohnson]

Sorry for the delay! This looks good.