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hungarian
I'm observing a weird behavior with the hungarian function (tested only on Julia 1.8). If weights are integers the algorithm works fine
julia> weights_int = [1 missing; missing missing] 2×2 Matrix{Union{Missing, Int64}}: 1 missing missing missing julia> hungarian(weights_int) ([1, 0], 1)
If the weight matrix has float values instead the algorithm hangs
julia> weights_float = [1.0 missing; missing missing] 2×2 Matrix{Union{Missing, Float64}}: 1.0 missing missing missing julia> hungarian(weights_float)
Is this expected behavior? Can it be fixed? How?
The text was updated successfully, but these errors were encountered:
MWE:
weights_int = [1.0 Inf; Inf Inf] Hungarian.munkres(weights_int)
looks like the implementation for forbidden edges hits a corner case.
cc @dourouc05
Sorry, something went wrong.
Inf
prevfloat(Inf)
Merge pull request #20 from Gnimuc/infinite-loop
97ad440
Fix #18 by explicitly converting `Inf` to `prevfloat(Inf)`
Successfully merging a pull request may close this issue.
I'm observing a weird behavior with the
hungarian
function (tested only on Julia 1.8). If weights are integers the algorithm works fineIf the weight matrix has float values instead the algorithm hangs
Is this expected behavior? Can it be fixed? How?
The text was updated successfully, but these errors were encountered: