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more small tests #139

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more small tests #139

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2 changes: 2 additions & 0 deletions test/combine.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,8 @@ ABdata[3:6,3:6,:,2] = Bdata
A1 = AxisArray(A1data, Axis{:X}(1:2), Axis{:Y}(1:2))
A2 = AxisArray(reshape(A2data, size(A2data)..., 1), Axis{:X}(1:2), Axis{:Y}(1:2), Axis{:Z}([:foo]))

@test_throws ArgumentError collapse(Val{1}, A1, AxisArray(A1data, Axis{:L}(1:4), Axis{:M}(1:5)))

@test @inferred(collapse(Val{2}, A1, A2)) == AxisArray(cat(3, A1data, A2data), Axis{:X}(1:2), Axis{:Y}(1:2), Axis{:collapsed}(AxisArrays.CategoricalVector([(1,), (2, :foo)])))
@test @inferred(collapse(Val{2}, A1)) == AxisArray(reshape(A1, 2, 2, 1), Axis{:X}(1:2), Axis{:Y}(1:2), Axis{:collapsed}(AxisArrays.CategoricalVector([(1,)])))
@test @inferred(collapse(Val{2}, A1)) == AxisArray(reshape(A1.data, size(A1)..., 1), axes(A1)..., Axis{:collapsed}(AxisArrays.CategoricalVector([(1,)])))
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6 changes: 5 additions & 1 deletion test/indexing.jl
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Expand Up @@ -59,7 +59,11 @@ odd_inds = collect(1:2:length(A))
@test axes(A[vec(trues(A))]) == axes(A[all_inds])
@test @inferred(A[vec(isodd.(A))]) == A[1:2:length(A)] == A[odd_inds]
@test axes(A[vec(isodd.(A))]) == axes(A[odd_inds])

# setindex! for logical indices
AA = copy(A)
AA[vec(isodd.(A))] = 0.
@test AA[odd_inds] == zeros(odd_inds)
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I think this method of zeros is deprecated

@test AA[2:2:length(AA)] == A[2:2:length(AA)]
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What are you testing here? Did you mean to do:

AA[odd_inds] == A[2:2:length(AA)]

or something like that?

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No, I'm checking that the even indexed items weren't modified.

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Oh wow, sorry, I totally misread the second line!

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No worries haha I absolutely cannot throw stones in this regard!


B = AxisArray(reshape(1:15, 5,3), .1:.1:0.5, [:a, :b, :c])

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1 change: 1 addition & 0 deletions test/sortedvector.jl
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Expand Up @@ -11,6 +11,7 @@ A = AxisArray(reshape(1:16, 8, 2), v, [:a, :b])
# test StepRange indexing
@test v[1:2:8] == [1.0; 10.0; 12.0; 14.0]

@test AxisArrays.checkaxis(v) == nothing
# Test SortedVector with a hierarchical index (indexed using Tuples)
srand(1234)
data = reshape(1.:40., 20, 2)
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