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Test on dimnames for KeyedArrays #62

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Mar 23, 2021
Merged

Test on dimnames for KeyedArrays #62

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2 changes: 2 additions & 0 deletions test/linear_combination.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -143,11 +143,13 @@

@testset "dims = 1" begin
@test FeatureTransforms.apply(A, lc; dims=1) == [-3, -3]
@test FeatureTransforms.apply(A, lc; dims=:foo) == [-3, -3]
@test lc(A; dims=1) == [-3, -3]
end

@testset "dims = 2" begin
@test FeatureTransforms.apply(A, lc; dims=2) == [-1, -1]
@test FeatureTransforms.apply(A, lc; dims=:bar) == [-1, -1]
@test lc(A; dims=2) == [-1, -1]
end
end
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2 changes: 1 addition & 1 deletion test/one_hot_encoding.jl
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Expand Up @@ -101,7 +101,7 @@
A = KeyedArray(M, foo=["a", "b"], bar=["x", "y"])
expected = [1 0 0 0 0; 0 0 0 1 0; 0 1 0 0 0; 0 0 0 0 1]

@testset "dims = $d" for d in (1, 2, Colon())
@testset "dims = $d" for d in (1, 2, Colon(), :foo, :bar)
transformed = FeatureTransforms.apply(A, ohe; dims=d)
# This transform doesn't preserve the type it operates on
@test transformed isa AbstractArray
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2 changes: 1 addition & 1 deletion test/periodic.jl
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Expand Up @@ -351,7 +351,7 @@
bar=["x", "y"]
)

@testset "dims = $d" for d in (Colon(), :foo, :bar)
@testset "dims = $d" for d in (Colon(), :foo, :bar, 1, 2)
transformed = FeatureTransforms.apply(A, p; dims=d)
@test transformed isa KeyedArray
@test transformed ≈ expected atol=1e-14
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2 changes: 1 addition & 1 deletion test/power.jl
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Expand Up @@ -74,7 +74,7 @@
A = KeyedArray([1 2 3; 4 5 6], foo=["a", "b"], bar=["x", "y", "z"])
expected = KeyedArray([1 8 27; 64 125 216], foo=["a", "b"], bar=["x", "y", "z"])

@testset "dims = $d" for d in (Colon(), :foo, :bar)
@testset "dims = $d" for d in (Colon(), :foo, :bar, 1, 2)
transformed = FeatureTransforms.apply(A, p; dims=d)
@test transformed isa KeyedArray
@test transformed == expected
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36 changes: 19 additions & 17 deletions test/scaling.jl
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Expand Up @@ -412,31 +412,33 @@
@test _A ≈ A_expected atol=1e-5
end

@testset "dims = :" begin
scaling = MeanStdScaling(A, dims=:)
@test FeatureTransforms.apply(A, scaling; dims=:) ≈ A_expected atol=1e-5
end

@testset "dims = 1" begin
scaling = MeanStdScaling(A; dims=1)
@test FeatureTransforms.apply(A, scaling; dims=1) ≈ A_expected atol=1e-5
end

@testset "dims = 2" begin
scaling = MeanStdScaling(A; dims=2)
@test FeatureTransforms.apply(A, scaling; dims=2) ≈ A_expected atol=1e-5
@testset "dims = $d" for d in (Colon(), 1, 2, :foo, :bar)
scaling = MeanStdScaling(A, dims=d)
@test FeatureTransforms.apply(A, scaling; dims=d) ≈ A_expected atol=1e-5
end

@testset "inds" begin
scaling = MeanStdScaling(A)
@test FeatureTransforms.apply(A, scaling; inds=[2, 3]) ≈ [-0.559017, -1.11803] atol=1e-5
@test FeatureTransforms.apply(A, scaling; dims=:, inds=[2, 3]) ≈ [-0.559017, -1.11803] atol=1e-5

scaling = MeanStdScaling(A; dims=1, inds=[2])
@test FeatureTransforms.apply(A, scaling; dims=1, inds=[2]) ≈ [-1.0 0.0 1.0] atol=1e-5
@testset "dims=$d" for d in (1, :foo)
scaling = MeanStdScaling(A; dims=d, inds=[2])
@test isapprox(
FeatureTransforms.apply(A, scaling; dims=d, inds=[2]),
[-1.0 0.0 1.0],
atol=1e-5
)
end

scaling = MeanStdScaling(A; dims=2, inds=[2])
@test FeatureTransforms.apply(A, scaling; dims=2, inds=[2]) ≈ [-0.70711 0.70711]' atol=1e-5
@testset "dims=$d" for d in (2, :bar)
scaling = MeanStdScaling(A; dims=2, inds=[2])
@test isapprox(
FeatureTransforms.apply(A, scaling; dims=2, inds=[2]),
[-0.70711 0.70711]',
atol=1e-5
)
end
end

@testset "Re-apply" begin
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4 changes: 3 additions & 1 deletion test/temporal.jl
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Expand Up @@ -114,7 +114,7 @@
@test FeatureTransforms.apply(A, hod) == expected
@test hod(A) == expected

@testset "dims = $d" for d in (Colon(), 1, 2)
@testset "dims = $d" for d in (Colon(), 1, 2, :foo, :bar)
transformed = FeatureTransforms.apply(A, hod; dims=d)
@test transformed isa KeyedArray
@test transformed == expected
Expand All @@ -125,6 +125,8 @@
@test FeatureTransforms.apply(A, hod; dims=:, inds=[2, 3]) == [2, 9]
@test FeatureTransforms.apply(A, hod; dims=1, inds=[2]) == [2 10 12]
@test FeatureTransforms.apply(A, hod; dims=2, inds=[2]) == reshape([9, 10], 2, 1)
@test FeatureTransforms.apply(A, hod; dims=:foo, inds=[2]) == [2 10 12]
@test FeatureTransforms.apply(A, hod; dims=:bar, inds=[2]) == reshape([9, 10], 2, 1)
end
end

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