-
-
Notifications
You must be signed in to change notification settings - Fork 5.5k
/
broadcast.jl
527 lines (462 loc) · 19.3 KB
/
broadcast.jl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
# This file is a part of Julia. License is MIT: https://julialang.org/license
module TestBroadcastInternals
using Base.Broadcast: broadcast_indices, check_broadcast_indices,
check_broadcast_shape, newindex, _bcs
using Base: OneTo
using Test
@test @inferred(_bcs((3,5), (3,5))) == (3,5)
@test @inferred(_bcs((3,1), (3,5))) == (3,5)
@test @inferred(_bcs((3,), (3,5))) == (3,5)
@test @inferred(_bcs((3,5), (3,))) == (3,5)
@test_throws DimensionMismatch _bcs((3,5), (4,5))
@test_throws DimensionMismatch _bcs((3,5), (3,4))
@test @inferred(_bcs((-1:1, 2:5), (-1:1, 2:5))) == (-1:1, 2:5)
@test @inferred(_bcs((-1:1, 2:5), (1, 2:5))) == (-1:1, 2:5)
@test @inferred(_bcs((-1:1, 1), (1, 2:5))) == (-1:1, 2:5)
@test @inferred(_bcs((-1:1,), (-1:1, 2:5))) == (-1:1, 2:5)
@test_throws DimensionMismatch _bcs((-1:1, 2:6), (-1:1, 2:5))
@test_throws DimensionMismatch _bcs((-1:1, 2:5), (2, 2:5))
@test @inferred(broadcast_indices(zeros(3,4), zeros(3,4))) == (OneTo(3),OneTo(4))
@test @inferred(broadcast_indices(zeros(3,4), zeros(3))) == (OneTo(3),OneTo(4))
@test @inferred(broadcast_indices(zeros(3), zeros(3,4))) == (OneTo(3),OneTo(4))
@test @inferred(broadcast_indices(zeros(3), zeros(1,4), zeros(1))) == (OneTo(3),OneTo(4))
check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,5))
check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,1))
check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3))
check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,5), zeros(3))
check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,5), 1)
check_broadcast_indices((OneTo(3),OneTo(5)), 5, 2)
@test_throws DimensionMismatch check_broadcast_indices((OneTo(3),OneTo(5)), zeros(2,5))
@test_throws DimensionMismatch check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,4))
@test_throws DimensionMismatch check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,4,2))
@test_throws DimensionMismatch check_broadcast_indices((OneTo(3),OneTo(5)), zeros(3,5), zeros(2))
check_broadcast_indices((-1:1, 6:9), 1)
check_broadcast_shape((-1:1, 6:9), (-1:1, 6:9))
check_broadcast_shape((-1:1, 6:9), (-1:1, 1))
check_broadcast_shape((-1:1, 6:9), (1, 6:9))
@test_throws DimensionMismatch check_broadcast_shape((-1:1, 6:9), (-1, 6:9))
@test_throws DimensionMismatch check_broadcast_shape((-1:1, 6:9), (-1:1, 6))
ci(x) = CartesianIndex(x)
@test @inferred(newindex(ci((2,2)), (true, true), (-1,-1))) == ci((2,2))
@test @inferred(newindex(ci((2,2)), (true, false), (-1,-1))) == ci((2,-1))
@test @inferred(newindex(ci((2,2)), (false, true), (-1,-1))) == ci((-1,2))
@test @inferred(newindex(ci((2,2)), (false, false), (-1,-1))) == ci((-1,-1))
@test @inferred(newindex(ci((2,2)), (true,), (-1,-1))) == ci((2,))
@test @inferred(newindex(ci((2,2)), (true,), (-1,))) == ci((2,))
@test @inferred(newindex(ci((2,2)), (false,), (-1,))) == ci((-1,))
@test @inferred(newindex(ci((2,2)), (), ())) == ci(())
end
function as_sub(x::AbstractVector)
y = similar(x, eltype(x), tuple(([size(x)...]*2)...))
y = view(y, 2:2:length(y))
y[:] = x[:]
y
end
function as_sub(x::AbstractMatrix)
y = similar(x, eltype(x), tuple(([size(x)...]*2)...))
y = view(y, 2:2:size(y,1), 2:2:size(y,2))
for j=1:size(x,2)
for i=1:size(x,1)
y[i,j] = x[i,j]
end
end
y
end
function as_sub(x::AbstractArray{T,3}) where T
y = similar(x, eltype(x), tuple(([size(x)...]*2)...))
y = view(y, 2:2:size(y,1), 2:2:size(y,2), 2:2:size(y,3))
for k=1:size(x,3)
for j=1:size(x,2)
for i=1:size(x,1)
y[i,j,k] = x[i,j,k]
end
end
end
y
end
bittest(f::Function, a...) = (@test f.(a...) == BitArray(broadcast(f, a...)))
n1 = 21
n2 = 32
n3 = 17
rb = 1:5
for arr in (identity, as_sub)
@test broadcast(+, arr(eye(2)), arr([1, 4])) == [2 1; 4 5]
@test broadcast(+, arr(eye(2)), arr([1 4])) == [2 4; 1 5]
@test broadcast(+, arr([1 0]), arr([1, 4])) == [2 1; 5 4]
@test broadcast(+, arr([1, 0]), arr([1 4])) == [2 5; 1 4]
@test broadcast(+, arr([1, 0]), arr([1, 4])) == [2, 4]
@test broadcast(+, arr([1, 0]), 2) == [3, 2]
@test @inferred(broadcast(+, arr(eye(2)), arr([1, 4]))) == arr([2 1; 4 5])
@test arr(eye(2)) .+ arr([1 4]) == arr([2 4; 1 5])
@test arr([1 0]) .+ arr([1, 4]) == arr([2 1; 5 4])
@test arr([1, 0]) .+ arr([1 4]) == arr([2 5; 1 4])
@test arr([1, 0]) .+ arr([1, 4]) == arr([2, 4])
@test arr([1]) .+ arr([]) == arr([])
A = arr(eye(2)); @test broadcast!(+, A, A, arr([1, 4])) == arr([2 1; 4 5])
A = arr(eye(2)); @test broadcast!(+, A, A, arr([1 4])) == arr([2 4; 1 5])
A = arr([1 0]); @test_throws DimensionMismatch broadcast!(+, A, A, arr([1, 4]))
A = arr([1 0]); @test broadcast!(+, A, A, arr([1 4])) == arr([2 4])
A = arr([1 0]); @test broadcast!(+, A, A, 2) == arr([3 2])
@test arr([ 1 2]) .* arr([3, 4]) == [ 3 6; 4 8]
@test arr([24.0 12.0]) ./ arr([2.0, 3.0]) == [12 6; 8 4]
@test arr([1 2]) ./ arr([3, 4]) == [1/3 2/3; 1/4 2/4]
@test arr([1 2]) .\ arr([3, 4]) == [3 1.5; 4 2]
@test arr([3 4]) .^ arr([1, 2]) == [3 4; 9 16]
@test arr(BitArray([true false])) .* arr(BitArray([true, true])) == [true false; true false]
@test arr(BitArray([true false])) .^ arr(BitArray([false, true])) == [true true; true false]
@test arr(BitArray([true false])) .^ arr([0, 3]) == [true true; true false]
M = arr([11 12; 21 22])
@test broadcast_getindex(M, eye(Int, 2).+1,arr([1, 2])) == [21 11; 12 22]
@test_throws BoundsError broadcast_getindex(M, eye(Int, 2).+1,arr([1, -1]))
@test_throws BoundsError broadcast_getindex(M, eye(Int, 2).+1,arr([1, 2]), [2])
@test broadcast_getindex(M, eye(Int, 2).+1,arr([2, 1]), [1]) == [22 12; 11 21]
A = arr(zeros(2,2))
broadcast_setindex!(A, arr([21 11; 12 22]), eye(Int, 2).+1,arr([1, 2]))
@test A == M
broadcast_setindex!(A, 5, [1,2], [2 2])
@test A == [11 5; 21 5]
broadcast_setindex!(A, 7, [1,2], [1 2])
@test A == fill(7, 2, 2)
A = arr(zeros(3,3))
broadcast_setindex!(A, 10:12, 1:3, 1:3)
@test A == diagm(10:12)
@test_throws BoundsError broadcast_setindex!(A, 7, [1,-1], [1 2])
for f in ((==), (<) , (!=), (<=))
bittest(f, arr(eye(2)), arr([1, 4]))
bittest(f, arr(eye(2)), arr([1 4]))
bittest(f, arr([0, 1]), arr([1 4]))
bittest(f, arr([0 1]), arr([1, 4]))
bittest(f, arr([1, 0]), arr([1, 4]))
bittest(f, arr(rand(rb, n1, n2, n3)), arr(rand(rb, n1, n2, n3)))
bittest(f, arr(rand(rb, 1, n2, n3)), arr(rand(rb, n1, 1, n3)))
bittest(f, arr(rand(rb, 1, n2, 1)), arr(rand(rb, n1, 1, n3)))
bittest(f, arr(bitrand(n1, n2, n3)), arr(bitrand(n1, n2, n3)))
end
end
r1 = 1:1
r2 = 1:5
ratio = [1,1/2,1/3,1/4,1/5]
@test r1.*r2 == [1:5;]
@test r1./r2 == ratio
m = [1:2;]'
@test m.*r2 == [1:5 2:2:10]
@test m./r2 ≈ [ratio 2ratio]
@test m./[r2;] ≈ [ratio 2ratio]
@test @inferred(broadcast(+,[0,1.2],reshape([0,-2],1,1,2))) == reshape([0 -2; 1.2 -0.8],2,1,2)
rt = Base.return_types(broadcast, Tuple{typeof(+), Array{Float64, 3}, Array{Int, 1}})
@test length(rt) == 1 && rt[1] == Array{Float64, 3}
rt = Base.return_types(broadcast!, Tuple{Function, Array{Float64, 3}, Array{Float64, 3}, Array{Int, 1}})
@test length(rt) == 1 && rt[1] == Array{Float64, 3}
# f.(args...) syntax (#15032)
let x = [1,3.2,4.7], y = [3.5, pi, 1e-4], α = 0.2342
@test sin.(x) == broadcast(sin, x)
@test sin.(α) == broadcast(sin, α)
@test sin.(3.2) == broadcast(sin, 3.2) == sin(3.2)
@test factorial.(3) == broadcast(factorial, 3)
@test atan2.(x, y) == broadcast(atan2, x, y)
@test atan2.(x, y') == broadcast(atan2, x, y')
@test atan2.(x, α) == broadcast(atan2, x, α)
@test atan2.(α, y') == broadcast(atan2, α, y')
end
# issue 14725
let a = Number[2, 2.0, 4//2, 2+0im] / 2
@test eltype(a) == Number
end
let a = Real[2, 2.0, 4//2] / 2
@test eltype(a) == Real
end
let a = Real[2, 2.0, 4//2] / 2.0
@test eltype(a) == Float64
end
# issue 16164
let a = broadcast(Float32, [3, 4, 5])
@test eltype(a) == Float32
end
# broadcasting scalars:
@test sin.(1) === broadcast(sin, 1) === sin(1)
@test (()->1234).() === broadcast(()->1234) === 1234
# issue #4883
@test isa(broadcast(tuple, [1 2 3], ["a", "b", "c"]), Matrix{Tuple{Int,String}})
@test isa(broadcast((x,y)->(x==1 ? 1.0 : x, y), [1 2 3], ["a", "b", "c"]), Matrix{Tuple{Real,String}})
let a = length.(["foo", "bar"])
@test isa(a, Vector{Int})
@test a == [3, 3]
end
let a = sin.([1, 2])
@test isa(a, Vector{Float64})
@test a ≈ [0.8414709848078965, 0.9092974268256817]
end
# PR #17300: loop fusion
@test (x->x+1).((x->x+2).((x->x+3).(1:10))) == collect(7:16)
let A = [sqrt(i)+j for i = 1:3, j=1:4]
@test atan2.(log.(A), sum(A,1)) == broadcast(atan2, broadcast(log, A), sum(A, 1))
end
let x = sin.(1:10)
@test atan2.((x->x+1).(x), (x->x+2).(x)) == broadcast(atan2, x.+1, x.+2)
@test sin.(atan2.([x.+1,x.+2]...)) == sin.(atan2.(x.+1 ,x.+2)) == @. sin(atan2(x+1,x+2))
@test sin.(atan2.(x, 3.7)) == broadcast(x -> sin(atan2(x,3.7)), x)
@test atan2.(x, 3.7) == broadcast(x -> atan2(x,3.7), x) == broadcast(atan2, x, 3.7)
end
# Use side effects to check for loop fusion.
let g = Int[]
f17300(x) = begin; push!(g, x); x+2; end
f17300.(f17300.(f17300.(1:3)))
@test g == [1,3,5, 2,4,6, 3,5,7]
empty!(g)
@. f17300(f17300(f17300(1:3)))
@test g == [1,3,5, 2,4,6, 3,5,7]
end
# fusion with splatted args:
let x = sin.(1:10), a = [x]
@test cos.(x) == cos.(a...)
@test atan2.(x,x) == atan2.(a..., a...) == atan2.([x, x]...)
@test atan2.(x, cos.(x)) == atan2.(a..., cos.(x)) == broadcast(atan2, x, cos.(a...)) == broadcast(atan2, a..., cos.(a...))
@test ((args...)->cos(args[1])).(x) == cos.(x) == ((y,args...)->cos(y)).(x)
end
@test atan2.(3,4) == atan2(3,4) == (() -> atan2(3,4)).()
# fusion with keyword args:
let x = [1:4;]
f17300kw(x; y=0) = x + y
@test f17300kw.(x) == x
@test f17300kw.(x, y=1) == f17300kw.(x; y=1) == f17300kw.(x; [(:y,1)]...) == x .+ 1
@test f17300kw.(sin.(x), y=1) == f17300kw.(sin.(x); y=1) == sin.(x) .+ 1
@test sin.(f17300kw.(x, y=1)) == sin.(f17300kw.(x; y=1)) == sin.(x .+ 1)
end
# issue #23236
let X = [[true,false],[false,true]]
@test [.!x for x in X] == [[false,true],[true,false]]
end
# splice escaping of @.
let x = [4, -9, 1, -16]
@test [2, 3, 4, 5] == @.(1 + sqrt($sort(abs(x))))
end
# interaction of @. with let
@test [1,4,9] == @. let x = [1,2,3]; x^2; end
# interaction of @. with for loops
let x = [1,2,3], y = x
@. for i = 1:3
y = y^2 # should convert to y .= y.^2
end
@test x == [1,256,6561]
end
# interaction of @. with function definitions
let x = [1,2,3]
@. f(x) = x^2
@test f(x) == [1,4,9]
end
# PR #17510: Fused in-place assignment
let x = [1:4;], y = x
y .= 2:5
@test y === x == [2:5;]
y .= factorial.(x)
@test y === x == [2,6,24,120]
y .= 7
@test y === x == [7,7,7,7]
y .= factorial.(3)
@test y === x == [6,6,6,6]
f17510() = 9
y .= f17510.()
@test y === x == [9,9,9,9]
y .-= 1
@test y === x == [8,8,8,8]
@. y -= 1:4 # @. should convert to .-=
@test y === x == [7,6,5,4]
x[1:2] .= 1
@test y === x == [1,1,5,4]
@. x[1:2] .+= [2,3] # use .+= to make sure @. works with dotted assignment
@test y === x == [3,4,5,4]
@. x[:] .= 0 # use .= to make sure @. works with dotted assignment
@test y === x == [0,0,0,0]
@. x[2:end] = 1:3 # @. should convert to .=
@test y === x == [0,1,2,3]
end
let a = [[4, 5], [6, 7]]
a[1] .= 3
@test a == [[3, 3], [6, 7]]
end
let d = Dict(:foo => [1,3,7], (3,4) => [5,9])
d[:foo] .+= 2
@test d[:foo] == [3,5,9]
d[3,4] .-= 1
@test d[3,4] == [4,8]
end
let identity = error, x = [1,2,3]
x .= 1 # make sure it goes to broadcast!(Base.identity, ...), not identity
@test x == [1,1,1]
end
# make sure scalars are inlined, which causes f.(x,scalar) to lower to a "thunk"
import Base.Meta: isexpr
@test isexpr(expand(Main, :(f.(x,y))), :call)
@test isexpr(expand(Main, :(f.(x,1))), :thunk)
@test isexpr(expand(Main, :(f.(x,1.0))), :thunk)
@test isexpr(expand(Main, :(f.(x,$π))), :thunk)
@test isexpr(expand(Main, :(f.(x,"hello"))), :thunk)
@test isexpr(expand(Main, :(f.(x,$("hello")))), :thunk)
# PR #17623: Fused binary operators
@test [true] .* [true] == [true]
@test [1,2,3] .|> (x->x+1) == [2,3,4]
let g = Int[], ⊕ = (a,b) -> let c=a+2b; push!(g, c); c; end
@test [1,2,3] .⊕ [10,11,12] .⊕ [100,200,300] == [221,424,627]
@test g == [21,221,24,424,27,627] # test for loop fusion
end
# Fused unary operators
@test .√[3,4,5] == sqrt.([3,4,5])
@test .![true, true, false] == [false, false, true]
@test .-[1,2,3] == -[1,2,3] == .+[-1,-2,-3] == [-1,-2,-3]
# PR 16988
@test Base.promote_op(+, Bool) === Int
@test isa(broadcast(+, [true]), Array{Int,1})
# issue #17304
let foo = [[1,2,3],[4,5,6],[7,8,9]]
@test max.(foo...) == broadcast(max, foo...) == [7,8,9]
end
# Issue 17314
@test broadcast(x->log(log(log(x))), [1000]) == [log(log(log(1000)))]
let f17314 = x -> x < 0 ? false : x
@test eltype(broadcast(f17314, 1:3)) === Int
@test eltype(broadcast(f17314, -1:1)) === Integer
@test eltype(broadcast(f17314, Int[])) == Union{Bool,Int}
end
let io = IOBuffer()
broadcast(x->print(io,x), 1:5) # broadcast with side effects
@test take!(io) == [0x31,0x32,0x33,0x34,0x35]
end
# Issue 18176
let f18176(a, b, c) = a + b + c
@test f18176.(1.0:2, 3, 4) == f18176.(3.0, 1.0:2, 4.0) == broadcast(f18176, 3, 4, 1.0:2)
end
# Issue #17984
let A17984 = []
@test isa(abs.(A17984), Array{Any,1})
end
# Issue #16966
@test parse.(Int, "1") == 1
@test parse.(Int, ["1", "2"]) == [1, 2]
@test trunc.((Int,), [1.2, 3.4]) == [1, 3]
@test abs.((1, -2)) == (1, 2)
@test broadcast(+, 1.0, (0, -2.0)) == (1.0,-1.0)
@test broadcast(+, 1.0, (0, -2.0), [1]) == [2.0, 0.0]
@test broadcast(*, ["Hello"], ", ", ["World"], "!") == ["Hello, World!"]
let s = "foo"
@test s .* ["bar", "baz"] == ["foobar", "foobaz"] == "foo" .* ["bar", "baz"]
end
# Ensure that even strange constructors that break `T(x)::T` work with broadcast
struct StrangeType18623 end
StrangeType18623(x) = x
StrangeType18623(x,y) = (x,y)
@test @inferred(broadcast(StrangeType18623, 1:3)) == [1,2,3]
@test @inferred(broadcast(StrangeType18623, 1:3, 4:6)) == [(1,4),(2,5),(3,6)]
@test typeof(Int.(Number[1, 2, 3])) === typeof((x->Int(x)).(Number[1, 2, 3]))
@test @inferred(broadcast(CartesianIndex, 1:2)) == [CartesianIndex(1), CartesianIndex(2)]
@test @inferred(broadcast(CartesianIndex, 1:2, 3:4)) == [CartesianIndex(1,3), CartesianIndex(2,4)]
# Issue 18622
@test @inferred(broadcast(muladd, [1.0], [2.0], [3.0])) == [5.0]
@test @inferred(broadcast(tuple, 1:3, 4:6, 7:9)) == [(1,4,7), (2,5,8), (3,6,9)]
# 19419
@test @inferred(broadcast(round, Int, [1])) == [1]
# https://discourse.julialang.org/t/towards-broadcast-over-combinations-of-sparse-matrices-and-scalars/910
let
f(A, n) = broadcast(x -> +(x, n), A)
@test @inferred(f([1.0], 1)) == [2.0]
g() = (a = 1; Base.Broadcast._broadcast_eltype(x -> x + a, 1.0))
@test @inferred(g()) === Float64
end
# Ref as 0-dimensional array for broadcast
@test (-).(C_NULL, C_NULL)::UInt == 0
@test (+).(1, Ref(2)) == fill(3)
@test (+).(Ref(1), Ref(2)) == fill(3)
@test (+).([[0,2], [1,3]], Ref{Vector{Int}}([1,-1])) == [[1,1], [2,2]]
# Check that broadcast!(f, A) populates A via independent calls to f (#12277, #19722),
# and similarly for broadcast!(f, A, numbers...) (#19799).
@test let z = 1; A = broadcast!(() -> z += 1, zeros(2)); A[1] != A[2]; end
@test let z = 1; A = broadcast!(x -> z += x, zeros(2), 1); A[1] != A[2]; end
# broadcasting for custom AbstractArray
struct Array19745{T,N} <: AbstractArray{T,N}
data::Array{T,N}
end
Base.getindex(A::Array19745, i::Integer...) = A.data[i...]
Base.setindex!(A::Array19745, v::Any, i::Integer...) = setindex!(A.data, v, i...)
Base.size(A::Array19745) = size(A.data)
Base.Broadcast._containertype(::Type{T}) where {T<:Array19745} = Array19745
Base.Broadcast.promote_containertype(::Type{Array19745}, ::Type{Array19745}) = Array19745
Base.Broadcast.promote_containertype(::Type{Array19745}, ::Type{Array}) = Array19745
Base.Broadcast.promote_containertype(::Type{Array19745}, ct) = Array19745
Base.Broadcast.promote_containertype(::Type{Array}, ::Type{Array19745}) = Array19745
Base.Broadcast.promote_containertype(ct, ::Type{Array19745}) = Array19745
Base.Broadcast.broadcast_indices(::Type{Array19745}, A) = indices(A)
Base.Broadcast.broadcast_indices(::Type{Array19745}, A::Ref) = ()
getfield19745(x::Array19745) = x.data
getfield19745(x) = x
function Base.Broadcast.broadcast_c(f, ::Type{Array19745}, A, Bs...)
T = Base.Broadcast._broadcast_eltype(f, A, Bs...)
shape = Base.Broadcast.broadcast_indices(A, Bs...)
dest = Array19745(Array{T}(Base.index_lengths(shape...)))
return broadcast!(f, dest, A, Bs...)
end
@testset "broadcasting for custom AbstractArray" begin
a = randn(10)
aa = Array19745(a)
@test a .+ 1 == @inferred(aa .+ 1)
@test a .* a' == @inferred(aa .* aa')
@test isa(aa .+ 1, Array19745)
@test isa(aa .* aa', Array19745)
end
# broadcast should only "peel off" one container layer
@test get.([Nullable(1), Nullable(2)]) == [1, 2]
let io = IOBuffer()
broadcast(x -> print(io, x), [Nullable(1.0)])
@test String(take!(io)) == "Nullable{Float64}(1.0)"
end
# Test that broadcast's promotion mechanism handles closures accepting more than one argument.
# (See issue #19641 and referenced issues and pull requests.)
let f() = (a = 1; Base.Broadcast._broadcast_eltype((x, y) -> x + y + a, 1.0, 1.0))
@test @inferred(f()) == Float64
end
@testset "broadcast resulting in BitArray" begin
let f(x) = x ? true : "false"
ba = f.([true])
@test ba isa BitArray
@test ba == [true]
a = f.([false])
@test a isa Array{String}
@test a == ["false"]
@test f.([true, false]) == [true, "false"]
end
end
# Test that broadcast treats type arguments as scalars, i.e. containertype yields Any,
# even for subtypes of abstract array. (https://github.com/JuliaStats/DataArrays.jl/issues/229)
@testset "treat type arguments as scalars, DataArrays issue 229" begin
@test Base.Broadcast.containertype(AbstractArray) == Any
@test broadcast(==, [1], AbstractArray) == BitArray([false])
@test broadcast(==, 1, AbstractArray) == false
end
# Test that broadcasting identity where the input and output Array shapes do not match
# yields the correct result, not merely a partial copy. See pull request #19895 for discussion.
let N = 5
@test iszero(ones(N, N) .= zeros(N, N))
@test iszero(ones(N, N) .= zeros(N, 1))
@test iszero(ones(N, N) .= zeros(1, N))
@test iszero(ones(N, N) .= zeros(1, 1))
end
@testset "test broadcast for matrix of matrices" begin
A = fill(zeros(2,2), 4, 4)
A[1:3,1:3] .= [ones(2,2)]
@test all(A[1:3,1:3] .== [ones(2,2)])
end
# Test that broadcast does not confuse eltypes. See also
# https://github.com/JuliaLang/julia/issues/21325
@testset "eltype confusion (#21325)" begin
foo(x::Char, y::Int) = 0
foo(x::String, y::Int) = "hello"
@test broadcast(foo, "x", [1, 2, 3]) == ["hello", "hello", "hello"]
@test isequal(
[Set([1]), Set([2])] .∪ Set([3]),
[Set([1, 3]), Set([2, 3])])
@test isequal(@inferred(broadcast(foo, "world", Nullable(1))),
Nullable("hello"))
end
# Issue #21291
let t = (0, 1, 2)
o = 1
@test @inferred(broadcast(+, t, o)) == (1, 2, 3)
end