ApproxFun.jl
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Improve type-stability in newton
After this, the following is type-inferred
julia> x=Fun(Chebyshev(0..1))
Fun(Chebyshev(0..1),[0.5, 0.5])
julia> u1 = 0.5*one(x)
Fun(Chebyshev(0..1),[0.5])
julia> u2 = 0.5*one(x)
Fun(Chebyshev(0..1),[0.5])
julia> N_dep = (u1,u2) -> [
u1(0)*u1(0)*u1(0) - 0.125;
u2(0) - 1;
u1' - u1*u1;
u2' + u1*u1*u2;
]
#1 (generic function with 1 method)
julia> @inferred newton(N_dep, [u1,u2]);
Codecov Report
Base: 39.58% // Head: 39.50% // Decreases project coverage by -0.08%
:warning:
Coverage data is based on head (
8997503
) compared to base (81b94a7
). Patch coverage: 90.90% of modified lines in pull request are covered.
Additional details and impacted files
@@ Coverage Diff @@
## master #783 +/- ##
==========================================
- Coverage 39.58% 39.50% -0.09%
==========================================
Files 14 14
Lines 682 681 -1
==========================================
- Hits 270 269 -1
Misses 412 412
Impacted Files | Coverage Δ | |
---|---|---|
src/ApproxFun.jl | 50.00% <ø> (ø) |
|
src/Extras/autodifferentiation.jl | 62.06% <90.90%> (-0.44%) |
:arrow_down: |
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Closing at stale