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Hey,
The following behaviors are really annoying:
julia> t = TaylorScalar{Float64, 3}((Inf, 1.0, 0.0))
TaylorScalar{Float64, 3}((Inf, 1.0, 0.0))
julia> t+1
TaylorScalar{Float64, 3}((Inf, 1.0, 0.0)) ##### OK
julia> t*1
TaylorScalar{Float64, 3}((Inf, NaN, NaN)) ##### Should be Inf, 1.0, 0.0
julia> t*2
TaylorScalar{Float64, 3}((Inf, NaN, NaN)) ##### Should be Inf, 2.0, 0.0
julia>
The last one even looks like a correctness issue...
but also :
julia> t2 = TaylorScalar{Float64, 3}((0.0, 1.0, 0.0))
TaylorScalar{Float64, 3}((0.0, 1.0, 0.0))
julia> t2^1
TaylorScalar{Float64, 3}((0.0, NaN, NaN)) ##### Should be 0.0, 1.0, 0.0
julia> t2^2
TaylorScalar{Float64, 3}((0.0, NaN, NaN)) ##### Should not be NaNs...
julia>
Using TaylorSeries.jl dos not produce these NaNs, and this makes my test cases fail... Do you think this is something that would be fixable in the current state of TaylorDiff ?
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