Closed FriesischScott closed 2 years ago
Merging #62 (ee0dd9b) into master (97fc031) will increase coverage by
0.59%
. The diff coverage is100.00%
.
@@ Coverage Diff @@
## master #62 +/- ##
==========================================
+ Coverage 98.39% 98.98% +0.59%
==========================================
Files 16 18 +2
Lines 373 590 +217
==========================================
+ Hits 367 584 +217
Misses 6 6
Impacted Files | Coverage Δ | |
---|---|---|
src/models/pce/pcebases.jl | 100.00% <100.00%> (ø) |
|
src/models/pce/polynomialchaosexpansion.jl | 100.00% <100.00%> (ø) |
|
src/sensitivity/sobolindices.jl | 100.00% <100.00%> (ø) |
|
src/simulations/subset.jl | 100.00% <0.00%> (ø) |
|
src/reliability/probabilityoffailure.jl | 100.00% <0.00%> (ø) |
|
src/models/externalmodel.jl | 98.07% <0.00%> (+1.30%) |
:arrow_up: |
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I need to find a few more examples to check hermite polynomials and also hybrid bases.
Looks great to me, a very nice contribution and implementation. Only (minor) suggestion is that evaluate! could allow for raw samples as well as a DF. But we would have to change this for the evaluate functions
Looks great to me, a very nice contribution and implementation. Only (minor) suggestion is that evaluate! could allow for raw samples as well as a DF. But we would have to change this for the evaluate functions
Maybe create an issue for it so we can discuss this generally?
Can compute PCE using least squares minimization or full quadrature rules using legendre basis functions.
The code should be fully extendible to other basis function, e.g. hermite by overloading a few methods in
pcebases.jl
.Unfortunately
SparseGrids.jl
doesn't seem to support mixing nodes/weights for different families of polynomials. Having sparse quadrature rules will be very important going forward.I'll add hermite polynomials before merging this.