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Fix argmax, findmax, findXwithfirst, and expand testing #99

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14 changes: 9 additions & 5 deletions src/chainedvector.jl
Original file line number Diff line number Diff line change
Expand Up @@ -809,7 +809,10 @@ function Base.findmax(f::F, x::ChainedVector) where {F}
cleanup!(x) # get rid of any empty arrays
i = 1
y = f(x.arrays[1][1])
return findXwithfirst(!isless, f, x, y, i)
# x > y iff y < x for a well ordered set
# nb. isgreater = !isless is not correct. That is `>=`
isgreater(x, y) = isless(y, x)
return findXwithfirst(isgreater, f, x, y, i)
end

function Base.findmin(f::F, x::ChainedVector) where {F}
Expand All @@ -825,8 +828,9 @@ function findXwithfirst(comp, f, x, y, i)
for A in x.arrays
for y′ in A
y′′ = f(y′)
y = ifelse(comp(y′′, y), y′′, y)
i = ifelse(comp(y′′, y), i′, i)
c = comp(y′′, y) # store this before y changes
y = ifelse(c, y′′, y)
i = ifelse(c, i′, i)
i′ += 1
end
end
Expand All @@ -835,8 +839,8 @@ end

Base.findmax(x::ChainedVector) = findmax(identity, x)
Base.findmin(x::ChainedVector) = findmin(identity, x)
Base.argmax(x::ChainedVector) = findmax(identity, x)[1]
Base.argmin(x::ChainedVector) = findmin(identity, x)[1]
Base.argmax(x::ChainedVector) = findmax(identity, x)[2]
Base.argmin(x::ChainedVector) = findmin(identity, x)[2]
Base.argmax(f::F, x::ChainedVector) where {F} = x[findmax(f, x)[2]]
Base.argmin(f::F, x::ChainedVector) where {F} = x[findmin(f, x)[2]]

Expand Down
170 changes: 170 additions & 0 deletions test/chainedvector.jl
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
@testset "ChainedVector" begin

# identity checks
x = ChainedVector([[1,2,3], [4,5,6], [7,8,9,10]])
@test x == 1:10
@test length(x) == 10
Expand Down Expand Up @@ -55,6 +56,7 @@
insert!(x, 1, 2)
@test x[1] == 2


x = ChainedVector([[1,2,3], [4,5,6], [7,8,9,10]])
y = ChainedVector([[11,12,13], [14,15,16], [17,18,19,20]])

Expand Down Expand Up @@ -284,6 +286,17 @@
@test all(==(2), x)
@test length(x) == 5

# https://github.com/JuliaData/SentinelArrays.jl/issues/97
x = ChainedVector([[18, 70, 92, 15, 65], [25, 14, 95, 54, 57]])
@test findmax(x) == (95, 8)
@test findmin(x) == (14, 7)
@test argmax(x) == 8
@test argmin(x) == 7
@test findmax(inv, x) == (inv(14), 7)
@test findmin(inv, x) == (inv(95), 8)
@test argmax(inv, x) == 14
@test argmin(inv, x) == 95

x = ChainedVector(Vector{Float64}[])
@test !any(x -> iseven(x), x)
@test !any(map(x -> iseven(x), x))
Expand Down Expand Up @@ -423,6 +436,163 @@
@test (rand(10,10) * v) isa ChainedVector
end

@testset "ChainedVectors on Generated Vectors" begin
#=
# Use to generate text below
function test_vector_generator(;
lengths = rand(0:5, 5),
possible_values = 1:100,
)
values = rand(possible_values, sum(lengths))
remaining_values = copy(values)
arrays = map(lengths) do length
result = remaining_values[1:length]
remaining_values = @view remaining_values[length+1:end]
return result
end
return ChainedVector(arrays) => values
end
function Base.show(io::IO, cv::ChainedVector)
print(io, "ChainedVector(")
show(io, cv.arrays)
print(io, ")")
end
for i in 1:10
test_vector_generator() |>
repr |>
x->replace(x, "=>" => "=>\n ") |>
x->println(x,",")
end
=#

# Pairs of test vectors
# Some were inspired by https://github.com/JuliaData/SentinelArrays.jl/issues/97
int_vectors = [
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Instead of a hard-coded set of test vectors, could a few 1000 be generated when the test runs? That might catch a few more edge cases.

Also, I think it would be clearer to only test Int here, to avoid NaN and floating point rounding.

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I think that is part of @Seelengrab 's Supposition.jl is supposed to do. I'm just trying to get this pull request through before I start messing with adding test dependencies, but we seem to be stuck here.

ChainedVector([[100, 20], [10, 30, 70, 40], [50], Int[], [60, 90, 80]]) =>
[100, 20, 10, 30, 70, 40, 50, 60, 90, 80],
ChainedVector([[2,1,3], [4,5,6], [7,8,10,9]]) =>
[2, 1, 3, 4, 5, 6, 7, 8, 10, 9],
ChainedVector([[18, 70, 92, 15, 65], [25, 14, 95, 54, 57]]) =>
[18, 70, 92, 15, 65, 25, 14, 95, 54, 57],
ChainedVector([[2, 34], [61, 8, 71], [65, 81, 51], [48, 93, 48, 94], [59, 15, 16, 56, 83]]) =>
[2, 34, 61, 8, 71, 65, 81, 51, 48, 93, 48, 94, 59, 15, 16, 56, 83],
ChainedVector([[23, 97, 70, 70], [4, 4], [61, 17], [95, 84, 91]]) =>
[23, 97, 70, 70, 4, 4, 61, 17, 95, 84, 91],
ChainedVector([[61, 23, 67, 61], [27, 19, 100], [26, 95], [2, 27, 63], [51, 52, 25]]) =>
[61, 23, 67, 61, 27, 19, 100, 26, 95, 2, 27, 63, 51, 52, 25],
ChainedVector([[25, 6, 94], [50], [63, 1, 76], [96, 6]]) =>
[25, 6, 94, 50, 63, 1, 76, 96, 6],
ChainedVector([[98, 5, 94], [82, 60], [58, 46, 13, 62, 48]]) =>
[98, 5, 94, 82, 60, 58, 46, 13, 62, 48],
ChainedVector([[28, 26], [21, 18, 64, 15], [11, 81, 17, 90], [29], [16, 67, 34, 84]]) =>
[28, 26, 21, 18, 64, 15, 11, 81, 17, 90, 29, 16, 67, 34, 84],
ChainedVector([[95, 15, 49, 31, 63], [79, 88], [76], [87, 52], [86, 50, 68, 61]]) =>
[95, 15, 49, 31, 63, 79, 88, 76, 87, 52, 86, 50, 68, 61],
ChainedVector([[71], [96, 84], [88, 3], [76, 47]]) =>
[71, 96, 84, 88, 3, 76, 47],
ChainedVector([[7, 21, 31], [45], [53, 53]]) =>
[7, 21, 31, 45, 53, 53],
ChainedVector([[24, 28, 75, 42], [7, 38, 59, 10], [21, 30, 14], [8, 39], [13, 68, 42]]) =>
[24, 28, 75, 42, 7, 38, 59, 10, 21, 30, 14, 8, 39, 13, 68, 42],
]
floating_point_vectors = [
ChainedVector([[2.1, -4.6, -2.5], [-5.0, 6.4, 2.0, -0.5], [-6.1, -7.6, -3.2, -4.7, 4.3], [-1.7, 6.4, -8.9, -7.4], [-7.7, -1.4, 3.1, 4.5]]) =>
[2.1, -4.6, -2.5, -5.0, 6.4, 2.0, -0.5, -6.1, -7.6, -3.2, -4.7, 4.3, -1.7, 6.4, -8.9, -7.4, -7.7, -1.4, 3.1, 4.5],
ChainedVector([[-8.5, -1.2, -3.8, 7.5], [8.2, 7.5, -5.3], [-2.7, 0.6, -6.2, 6.1, 1.4]]) =>
[-8.5, -1.2, -3.8, 7.5, 8.2, 7.5, -5.3, -2.7, 0.6, -6.2, 6.1, 1.4],
ChainedVector([[-7.2], [8.1, 2.3, 7.5], [-8.4, -5.7]]) =>
[-7.2, 8.1, 2.3, 7.5, -8.4, -5.7],
ChainedVector([[-3.7, 7.8, -5.0], [0.1], [5.0, -4.1], [-1.6, -0.9, 8.7, -7.8]]) =>
[-3.7, 7.8, -5.0, 0.1, 5.0, -4.1, -1.6, -0.9, 8.7, -7.8],
ChainedVector([[8.6, -2.0], [8.0, 3.4, 3.3], [1.0], [5.4, -2.6, -4.7, 4.4, 4.4], [7.9]]) =>
[8.6, -2.0, 8.0, 3.4, 3.3, 1.0, 5.4, -2.6, -4.7, 4.4, 4.4, 7.9],
ChainedVector([[7.6, 5.9], [7.9, -8.8, -1.5, -0.4, 6.0], [-5.1, -0.4, 4.4, 7.3]]) =>
[7.6, 5.9, 7.9, -8.8, -1.5, -0.4, 6.0, -5.1, -0.4, 4.4, 7.3],
ChainedVector([[3.2, -3.2, 1.2, -1.2, -2.1], [0.5], [6.2], [2.9], [-8.1, 5.8, 4.8, -3.4, -3.1]]) =>
[3.2, -3.2, 1.2, -1.2, -2.1, 0.5, 6.2, 2.9, -8.1, 5.8, 4.8, -3.4, -3.1],
ChainedVector([[-8.0, -1.9, -5.1, -1.4, -8.3], [5.1, -3.7, 6.3, -4.8, -3.3], [-7.0], [-2.4, 4.0, -3.7], [-6.6, -6.9, 2.5, -1.3]]) =>
[-8.0, -1.9, -5.1, -1.4, -8.3, 5.1, -3.7, 6.3, -4.8, -3.3, -7.0, -2.4, 4.0, -3.7, -6.6, -6.9, 2.5, -1.3],
ChainedVector([[-7.5], [-1.5, -5.8, 8.4], [-8.4, -1.9, 2.3, -0.8, -8.5], [0.2, 0.5, -7.4, 2.1, -3.9]]) =>
[-7.5, -1.5, -5.8, 8.4, -8.4, -1.9, 2.3, -0.8, -8.5, 0.2, 0.5, -7.4, 2.1, -3.9],
ChainedVector([[3.9, -8.9], [-0.3, 0.0, 7.3], [-2.9, 8.6, 5.8, 0.5], [0.0, -4.5, 3.3, 0.4, -3.2]]) =>
[3.9, -8.9, -0.3, 0.0, 7.3, -2.9, 8.6, 5.8, 0.5, 0.0, -4.5, 3.3, 0.4, -3.2],
]
rational_vectors = [
ChainedVector(Vector{Rational{Int64}}[[1, 1//2, 1//2, 4//5], [7//10], [1, 1//5, 7//10, 3//10, 1], [3//5], [1]]) =>
Rational{Int64}[1, 1//2, 1//2, 4//5, 7//10, 1, 1//5, 7//10, 3//10, 1, 3//5, 1],
ChainedVector(Vector{Rational{Int64}}[[1//5], [1, 4//5, 1//5], [3//5, 7//10, 3//5], [9//10, 1//5, 7//10, 1//2], [1//2, 7//10, 9//10, 3//5, 7//10]]) =>
Rational{Int64}[1//5, 1, 4//5, 1//5, 3//5, 7//10, 3//5, 9//10, 1//5, 7//10, 1//2, 1//2, 7//10, 9//10, 3//5, 7//10],
ChainedVector(Vector{Rational{Int64}}[[7//10, 1, 1//5, 1//2, 2//5], [1//5, 4//5, 1//2, 1//5], [3//10, 3//10, 1//2], [3//10, 1//10, 4//5, 3//5], [2//5, 7//10, 1, 3//10, 3//10]]) =>
Rational{Int64}[7//10, 1, 1//5, 1//2, 2//5, 1//5, 4//5, 1//2, 1//5, 3//10, 3//10, 1//2, 3//10, 1//10, 4//5, 3//5, 2//5, 7//10, 1, 3//10, 3//10],
ChainedVector(Vector{Rational{Int64}}[[1//10, 4//5], [1//2], [1//10], [4//5, 1, 3//5, 9//10, 9//10]]) =>
Rational{Int64}[1//10, 4//5, 1//2, 1//10, 4//5, 1, 3//5, 9//10, 9//10],
ChainedVector(Vector{Rational{Int64}}[[3//10, 1, 9//10, 3//5], [1, 1], [1, 4//5, 3//5, 9//10]]) =>
Rational{Int64}[3//10, 1, 9//10, 3//5, 1, 1, 1, 4//5, 3//5, 9//10],
ChainedVector(Vector{Rational{Int64}}[[3//10, 7//10], [4//5], [4//5, 1, 1//10, 9//10], [1, 1, 4//5]]) =>
Rational{Int64}[3//10, 7//10, 4//5, 4//5, 1, 1//10, 9//10, 1, 1, 4//5],
ChainedVector(Vector{Rational{Int64}}[[2//5], [3//5, 9//10, 7//10, 9//10], [1//2, 1, 1//10, 1//5], [1//5, 4//5, 7//10, 2//5]]) =>
Rational{Int64}[2//5, 3//5, 9//10, 7//10, 9//10, 1//2, 1, 1//10, 1//5, 1//5, 4//5, 7//10, 2//5],
ChainedVector(Vector{Rational{Int64}}[[7//10], [3//5, 1//5, 2//5, 3//5, 4//5], [4//5], [7//10, 3//5, 7//10, 7//10, 1//10]]) =>
Rational{Int64}[7//10, 3//5, 1//5, 2//5, 3//5, 4//5, 4//5, 7//10, 3//5, 7//10, 7//10, 1//10],
ChainedVector(Vector{Rational{Int64}}[[1//2, 1, 1//2, 9//10, 2//5], [9//10, 1//2, 3//5], [4//5, 7//10], [3//10, 2//5], [9//10, 1]]) =>
Rational{Int64}[1//2, 1, 1//2, 9//10, 2//5, 9//10, 1//2, 3//5, 4//5, 7//10, 3//10, 2//5, 9//10, 1],
ChainedVector(Vector{Rational{Int64}}[[9//10, 3//10, 1//10, 2//5], [4//5], [9//10, 2//5]]) =>
Rational{Int64}[9//10, 3//10, 1//10, 2//5, 4//5, 9//10, 2//5],

]
@testset for (x,y) in Iterators.flatten([int_vectors, floating_point_vectors, rational_vectors])
@test copy(x) == y
@test collect(x) == y
@test length(x) == length(y)
# should this be approx?
@test sum(x) ≈ sum(y)
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@test findmax(x) == findmax(y)
@test findmin(x) == findmin(y)
@test maximum(x) == maximum(y)
@test minimum(x) == minimum(y)
@test argmax(x) == argmax(y)
@test argmin(x) == argmin(y)
@test all(>(0),x) == all(>(0),y)
@test any(>(0),x) == any(>(0),y)
@test any(<(0),x) == any(<(0),y)
@test count(>(0),x) == count(>(0),y)
@test count(<(0),x) == count(<(0),y)
@test extrema(inv, x) == extrema(inv, y)
@static if VERSION ≥ v"1.6"
@test findmax(x->x+1, x) == findmax(x->x+1, y)
@test findmin(x->x-1, x) == findmin(x->x-1, y)
@test findfirst(isodd, x) == findfirst(isodd, y)
@test findfirst(iseven, x) == findfirst(iseven ,y)
@test findlast(isodd, x) == findlast(isodd, y)
@test findlast(iseven, x) == findlast(iseven ,y)
@test findall(iseven, x) == findall(iseven ,y)
@test findnext(isodd, x, 5) == findnext(isodd, y, 5)
@test findprev(isodd, x, 5) == findprev(isodd, y, 5)
end
@test let (val, idx) = findmax(x)
max_val = maximum(x)
val == max_val == x[idx]
end
@test let (val, idx) = findmin(x)
min_val = minimum(x)
val == min_val == x[idx]
end
@test x[argmax(x)] == maximum(x)
@test x[argmin(x)] == minimum(x)
@test let (val, idx) = findmax(inv, x)
max_val = maximum(inv, x)
val == max_val == inv(x[idx])
end
@test let (val, idx) = findmin(inv, x)
min_val = minimum(inv, x)
val == min_val == inv(x[idx])
end
@test inv(argmax(inv, x)) == maximum(inv, x)
@test inv(argmin(inv, x)) == minimum(inv, x)
end
end


@testset "iteration protocol on ChainedVector" begin
for len in 0:6
cv = ChainedVector([1:len])
Expand Down
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