Refactor and use Cholesky decomposition for correlated_values and correlated_values_norm
#271
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## master #271 +/- ##
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+ Coverage 96.50% 96.56% +0.05%
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Files 16 16
Lines 1919 1951 +32
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+ Hits 1852 1884 +32
Misses 67 67
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This PR is ready for review. |
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While this PR is ready for review, it's going to conflict badly with #262. Let's hold off on this one until after that one. |
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pre-commit run --all-fileswith no errorsClean up
correlated_valuesandcorrelated_values_norm. Make the code easier to follow. Also use the more efficient Cholesky decomposition in cases where the user-provided covariance matrix is positive-definite. If it is strictly positive semi-definite then use the eigenvalue decomposition that was previously used.Note, previously
correlated_values_norm(which accepts a normalized correlation matrix) did the numerical lifting andcorrelated_values(which accepts a covariance matrix) calledcorrelated_values_norm. This is reversed now. Nowcorrelated_valuesdoes the numerical work andcorrelated_values_normcallscorrelated_values.