add f_calls_limit parameter to minimise #49
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@@ Coverage Diff @@
## master #49 +/- ##
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+ Coverage 89.55% 90.14% +0.58%
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Files 4 4
Lines 67 71 +4
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+ Hits 60 64 +4
Misses 7 7
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src/optimise.jl
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| @@ -38,6 +39,7 @@ function minimise(f, X::T; structure = HeapedVector, tol=1e-3) where {T} | |||
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| # find candidate for upper bound of global minimum by just evaluating a point in the interval: | |||
| m = sup(f(Interval.(mid.(X)))) # evaluate at midpoint of current interval | |||
| f_calls += 3 | |||
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This is a single call to f so should just increment by 1?
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Great, thanks! Could you please add a couple of tests for this? |
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I've added a test and improved a bit the termination criteria so it's more accurate. |
| @@ -2,11 +2,11 @@ | |||
| numeric_type(::IntervalBox{N, T}) where {N, T} = T | |||
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| """ | |||
| minimise(f, X, structure = SortedVector, tol=1e-3) | |||
| minimise(f, X, structure = SortedVector, tol=1e-3, f_calls_limit=Inf) | |||
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Inf is a Float64. Presumably the number of calls should be an integer. So this should be replaced by some large integer like 10^20, or given a sentinel value like -1 (probably preferable).
| @@ -35,6 +35,11 @@ using IntervalOptimisation: numeric_type | |||
| @test length(minimisers) == 1 | |||
| @test minimisers[1] ⊆ -0.1..0.1 | |||
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| global n_calls = 0 | |||
| f = x -> begin global n_calls += 1; x^2 end | |||
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You should probably use a let block instead of the global variable.
| global n_calls = 0 | ||
| f = x -> begin global n_calls += 1; x^2 end | ||
| global_min, minimisers = minimise(f, -10..11, tol = 1e-10, f_calls_limit = 10) | ||
| @test n_calls == 10 #note : for other values we can overshoot, since we call 3 times per iteration |
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Maybe the minimise function should return the total number of calls.
This adds an option to limit the number of function evaluations the minimise method can do. I used the same name as in Optim.jl.
Using the following I counted that the function was getting called 3 times per iteration, which seems to hold across dimensions.
fix #44