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Refactor tests to test types and transform functionality separately #84

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merged 13 commits into from
Jun 28, 2021
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Merged

Refactor tests to test types and transform functionality separately #84

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af2f139
Test on ColumnTable and DataFrames
Apr 20, 2021
17bdcf5
Delete NamedTuple tests
Apr 20, 2021
b0f0340
Remove DataFrames tests
Apr 20, 2021
a20c32c
Add vector tests
Apr 20, 2021
88f7e88
Remove vector tests
Apr 20, 2021
af9205c
Add matrix tests
Jun 18, 2021
4d4bd63
Remove matrix tests
Jun 18, 2021
e78f19f
Add KeyedArray and AxisArray tests
Jun 18, 2021
2866889
Remove KeyedArray and AxisArray tests
Jun 18, 2021
dcf8579
Add cube tests
Jun 18, 2021
e292e95
Add KeyedArray tests with dims
Jun 18, 2021
6e1c812
Simplify tests by defining data at top
Jun 18, 2021
00376b7
Add broken apply! tests
Jun 28, 2021
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300 changes: 14 additions & 286 deletions test/linear_combination.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -4,102 +4,23 @@
@test lc isa Transform
@test cardinality(lc) == ManyToOne()

@testset "Vector" begin

@testset "all inds" begin
x = [1, 2]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(x, lc) == fill(-1)
@test lc(x) == fill(-1)
end

@testset "dims behaviour" begin
x = [1, 2]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(x, lc; dims=1) == fill(-1)
@test_throws BoundsError FeatureTransforms.apply(x, lc; dims=2)
end

@testset "dimension mismatch" begin
x = [1, 2, 3]
lc = LinearCombination([1, -1])
@test_throws DimensionMismatch FeatureTransforms.apply(x, lc)
end

@testset "specified inds" begin
x = [1, 2, 3]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(x, lc; inds=[2, 3]) == fill(-1)
@test lc(x; inds=[2, 3]) == fill(-1)
end

@testset "output is different type" begin
x = [1, 2]
lc = LinearCombination([.1, -.1])
@test FeatureTransforms.apply(x, lc) == fill(-.1)
@test lc(x) == fill(-.1)
end

@testset "apply_append" begin
x = [1, 2]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply_append(x, lc; append_dim=1) == [1, 2, -1]
end
@testset "default reduces over columns" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1, 1])
@test FeatureTransforms.apply(M, lc) == [2, 4]
@test lc(M) == [2, 4]
end

@testset "Matrix" begin

@testset "default reduces over columns" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1, 1])
@test FeatureTransforms.apply(M, lc) == [2, 4]
@test lc(M) == [2, 4]
end

@testset "dims" begin
@testset "dims = :" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1, 1])
@test_deprecated FeatureTransforms.apply(M, lc; dims=:)
end

@testset "dims = 1" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1, 1])
@test FeatureTransforms.apply(M, lc; dims=1) == [2, 4]
@test lc(M; dims=1) == [2, 4]
end

@testset "dims = 2" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(M, lc; dims=2) == [0, 0, -2]
end
end

@testset "dimension mismatch" begin
M = [1 1 1; 2 2 2]
lc = LinearCombination([1, -1, 1]) # there are only 2 rows
@test_throws DimensionMismatch FeatureTransforms.apply(M, lc)
end

@testset "specified inds" begin
M = [1 1; 5 2; 2 4]
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(M, lc; inds=[2, 3]) == [3, -2]
@test lc(M; inds=[2, 3]) == [3, -2]
end

@testset "apply_append" begin
M = [1 1 1; 2 2 2; 3 3 3]
lc = LinearCombination([1, 1, 1])

expected1 = [1 1 1; 2 2 2; 3 3 3; 6 6 6]
@test FeatureTransforms.apply_append(M, lc; dims=1, append_dim=1) == expected1
@testset "dims = :" begin
M = [1 1; 2 2; 3 5]
lc = LinearCombination([1, -1, 1])
@test_deprecated FeatureTransforms.apply(M, lc; dims=:)
end

expected2 = [1 1 1 3; 2 2 2 6; 3 3 3 9]
@test FeatureTransforms.apply_append(M, lc; dims=2, append_dim=2) == expected2
end
@testset "dimension mismatch" begin
M = [1 1 1; 2 2 2]
lc = LinearCombination([1, -1, 1]) # there are only 2 rows
@test_throws DimensionMismatch FeatureTransforms.apply(M, lc)
end

@testset "N-dim Array" begin
Expand All @@ -108,197 +29,4 @@
@test FeatureTransforms.apply(A, lc) == [2 11 20; 5 14 23; 8 17 26]
@test lc(A) == [2 11 20; 5 14 23; 8 17 26]
end

@testset "AxisArray" begin
A = AxisArray([1 2; 4 5], foo=["a", "b"], bar=["x", "y"])
lc = LinearCombination([1, -1])

@testset "all inds" begin
@test FeatureTransforms.apply(A, lc) == [-3, -3]
@test lc(A) == [-3, -3]
end

@testset "dims" begin
@testset "dims = :" begin
@test_deprecated FeatureTransforms.apply(A, lc; dims=:)
end

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

@testset "dims = 2" begin
@test FeatureTransforms.apply(A, lc; dims=2) == [-1, -1]
@test lc(A; dims=2) == [-1, -1]
end
end

@testset "dimension mismatch" begin
A = AxisArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
@test_throws DimensionMismatch FeatureTransforms.apply(A, lc; dims=2)
end

@testset "specified inds" begin
A = AxisArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
@test FeatureTransforms.apply(A, lc; inds=[1, 2]) == [-3, -3, -2]
@test lc(A; inds=[1, 2]) == [-3, -3, -2]
end

@testset "apply_append" begin
A = AxisArray([1 2; 4 5], foo=["a", "b"], bar=["x", "y"])

expected1 = [1 2; 4 5; -3 -3]
@test FeatureTransforms.apply_append(A, lc; dims=1, append_dim=1) == expected1

expected2 = [1 2 -1; 4 5 -1]
@test FeatureTransforms.apply_append(A, lc; dims=2, append_dim=2) == expected2
end
end

@testset "AxisKey" begin
A = KeyedArray([1 2; 4 5], foo=["a", "b"], bar=["x", "y"])
lc = LinearCombination([1, -1])

@testset "all inds" begin
@test FeatureTransforms.apply(A, lc) == [-3, -3]
@test lc(A) == [-3, -3]
end

@testset "dims" begin
@testset "dims = :" begin
@test_deprecated FeatureTransforms.apply(A, lc; dims=:)
end

@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

@testset "dimension mismatch" begin
A = KeyedArray([1 2 3; 4 5 6], foo=["a", "b"], bar=["x", "y", "z"])
@test_throws DimensionMismatch FeatureTransforms.apply(A, lc; dims=2)
end

@testset "specified inds" begin
A = KeyedArray([1 2 3; 4 5 5], foo=["a", "b"], bar=["x", "y", "z"])
@test FeatureTransforms.apply(A, lc; inds=[1, 2]) == [-3, -3, -2]
@test lc(A; inds=[1, 2]) == [-3, -3, -2]
end

@testset "apply_append" begin
A = KeyedArray([1 2; 4 5], foo=["a", "b"], bar=["x", "y"])

expected1 = [1 2; 4 5; -3 -3]
@test FeatureTransforms.apply_append(A, lc; dims=:foo, append_dim=:foo) == expected1

expected2 = [1 2 -1; 4 5 -1]
@test FeatureTransforms.apply_append(A, lc; dims=:bar, append_dim=:bar) == expected2
end
end

@testset "NamedTuple" begin
@testset "all cols" begin
nt = (a = [1, 2, 3], b = [4, 5, 6])
lc = LinearCombination([1, -1])
expected = (Column1 = [-3, -3, -3],)
@test FeatureTransforms.apply(nt, lc) == expected
@test lc(nt) == expected
end

@testset "custom header" begin
nt = (a = [1, 2, 3], b = [4, 5, 6])
lc = LinearCombination([1, -1])
expected = (x = [-3, -3, -3],)
@test FeatureTransforms.apply(nt, lc; header=[:x]) == expected
@test lc(nt; header=[:x]) == expected
end

@testset "dimension mismatch" begin
nt = (a = [1, 2, 3], b = [4, 5, 6], c = [1, 1, 1])
lc = LinearCombination([1, -1])
@test_throws DimensionMismatch FeatureTransforms.apply(nt, lc)
end

@testset "specified cols" begin
nt = (a = [1, 2, 3], b = [4, 5, 6], c = [1, 1, 1])
lc = LinearCombination([1, -1])
expected = (Column1 = [-3, -3, -3],)
@test FeatureTransforms.apply(nt, lc; cols=[:a, :b]) == expected
@test lc(nt; cols=[:a, :b]) == expected
end

@testset "single col" begin
nt = (a = [1, 2, 3], b = [4, 5, 6])
lc_single = LinearCombination([-1])
expected = (Column1 = [-1, -2, -3],)
@test FeatureTransforms.apply(nt, lc_single; cols=:a) == expected
@test FeatureTransforms.apply(nt, lc_single; cols=[:a]) == expected
@test lc_single(nt; cols=:a) == expected
end

@testset "apply_append" begin
nt = (a = [1, 2, 3], b = [4, 5, 6])
lc = LinearCombination([1, -1])
expected = (a = [1, 2, 3], b = [4, 5, 6], Column1 = [-3, -3, -3])
@test FeatureTransforms.apply_append(nt, lc) == expected
end
end

@testset "DataFrame" begin

@testset "all cols" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6])
lc = LinearCombination([1, -1])
@test FeatureTransforms.apply(df, lc) == DataFrame(:Column1 => [-3, -3, -3])
@test lc(df) == DataFrame(:Column1 => [-3, -3, -3])
end

@testset "custom header" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6])
lc = LinearCombination([1, -1])
expected = DataFrame(:x => [-3, -3, -3])
@test FeatureTransforms.apply(df, lc; header=[:x]) == expected
@test lc(df; header=[:x]) == expected
end

@testset "dimension mismatch" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6], :c => [1, 1, 1])
lc = LinearCombination([1, -1])
@test_throws DimensionMismatch FeatureTransforms.apply(df, lc)
end

@testset "specified cols" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6], :c => [1, 1, 1])
lc = LinearCombination([1, -1])
expected = DataFrame(:Column1 => [3, 4, 5])

@test FeatureTransforms.apply(df, lc; cols=[:b, :c]) == expected
@test lc(df; cols=[:b, :c]) == expected
end

@testset "single col" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6])
lc_single = LinearCombination([-1])
expected = DataFrame(:Column1 => [-1, -2, -3])
@test FeatureTransforms.apply(df, lc_single; cols=:a) == expected
@test FeatureTransforms.apply(df, lc_single; cols=[:a]) == expected
@test lc_single(df; cols=:a) == expected
end

@testset "apply_append" begin
df = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6])
lc = LinearCombination([1, -1])
expected = DataFrame(:a => [1, 2, 3], :b => [4, 5, 6], :Column1 => [-3, -3, -3])
@test FeatureTransforms.apply_append(df, lc) == expected
end
end
end
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