-
Notifications
You must be signed in to change notification settings - Fork 41
/
primitives.jl
790 lines (657 loc) · 30.6 KB
/
primitives.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
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
# These functions do most of the work in the package.
# They are all type-stable recursive methods for performance and extensibility.
"""
dimsmatch([f], dim, query) => Bool
dimsmatch([f], dims::Tuple, query::Tuple) => Bool
Compare 2 dimensions or `Tuple` of `Dimension` are of the same base type,
or are at least rotations/transformations of the same type.
`f` is `<:` by default, but can be `>:` to match abstract types to concrete types.
"""
function dimsmatch end
@inline dimsmatch(dims, query)::Bool = dimsmatch(<:, dims, query)
@inline function dimsmatch(f::Function, dims::Tuple, query::Tuple)::Bool
length(dims) == length(query) || return false
all(map((d, l) -> dimsmatch(f, d, l), dims, query))
end
@inline dimsmatch(f::Function, dim, query)::Bool = dimsmatch(f, typeof(dim), typeof(query))
@inline dimsmatch(f::Function, dim::Type, query)::Bool = dimsmatch(f, dim, typeof(query))
@inline dimsmatch(f::Function, dim, query::Type)::Bool = dimsmatch(f, typeof(dim), query)
@inline dimsmatch(f::Function, dim::Nothing, query::Type)::Bool = false
@inline dimsmatch(f::Function, dim::Type, ::Nothing)::Bool = false
@inline dimsmatch(f::Function, dim, query::Nothing)::Bool = false
@inline dimsmatch(f::Function, dim::Nothing, query)::Bool = false
@inline dimsmatch(f::Function, dim::Nothing, query::Nothing) = false
@inline dimsmatch(f::Function, dim::Type{Val{D}}, match::Type{Val{M}}) where {D,M} =
dimsmatch(f, D, M)
@inline dimsmatch(f::Function, dim::Type{D}, match::Type{Val{M}}) where {D,M} =
dimsmatch(f, D, M)
@inline dimsmatch(f::Function, dim::Type{Val{D}}, match::Type{M}) where {D,M} =
dimsmatch(f, D, M)
@inline function dimsmatch(f::Function, dim::Type{D}, match::Type{M})::Bool where {D,M}
# Match based on type and inheritance
f(basetypeof(unwrap(D)), basetypeof(unwrap(M))) ||
# Or match based on name so that Dim{:X} matches X
isconcretetype(D) && isconcretetype(M) && name(D) === name(M)
end
"""
name2dim(s::Symbol) => Dimension
name2dim(dims...) => Tuple{Dimension,Vararg}
name2dim(dims::Tuple) => Tuple{Dimension,Vararg}
Convert a symbol to a dimension object. `:X`, `:Y`, `:Ti` etc will be converted
to `X()`, `Y()`, `Ti()`, as with any other dims generated with the [`@dim`](@ref) macro.
All other `Symbol`s `S` will generate `Dim{S}()` dimensions.
"""
function name2dim end
@inline name2dim(t::Tuple) = map(name2dim, t)
@inline name2dim(s::Symbol) = name2dim(Val{s}())
# Allow other things to pass through
@inline name2dim(d::Val{<:Dimension}) = d
@inline name2dim(d) = d
# name2dim is defined for concrete instances in dimensions.jl
@deprecate key2dim name2dim
@deprecate dim2key name
"""
sortdims([f], tosort, order) => Tuple
Sort dimensions `tosort` by `order`. Dimensions in `order` but
missing from `tosort` are replaced with `nothing`.
`tosort` and `order` can be `Tuple`s or `Vector`s or Dimension
or dimension type. Abstract supertypes like [`TimeDim`](@ref)
can be used in `order`.
`f` is `<:` by default, but can be `>:` to sort abstract types by concrete types.
"""
function sortdims end
@inline sortdims(a1, a2) = _dim_query(_sortdims, MaybeFirst(), a1, a2)
@inline sortdims(f::Function, a1, a2) = _dim_query(_sortdims, f, MaybeFirst(), a1, a2)
# Defined before the @generated function for world age
_asfunc(::Type{typeof(<:)}) = <:
_asfunc(::Type{typeof(>:)}) = >:
@inline function _sortdims(f, tosort, order::Tuple{<:Integer,Vararg})
map(order) do i
if i in 1:length(tosort)
tosort[i]
else
nothing
end
end
end
@inline _sortdims(f, tosort, order) = _sortdims_gen(f, tosort, order)
@generated _sortdims_gen(f, tosort::Tuple, order::Tuple) = begin
expr = Expr(:tuple)
allreadyfound = Int[]
for (i, ord) in enumerate(order.parameters)
# Make sure we don't find the same dim twice
found = 0
while true
found = findnext((tosort.parameters...,), found + 1) do s
dimsmatch(_asfunc(f), s, ord)
end
if found == nothing
push!(expr.args, :(nothing))
break
elseif !(found in allreadyfound)
push!(expr.args, :(tosort[$found]))
push!(allreadyfound, found)
break
end
end
end
return expr
end
"""
dims(x, query) => Tuple{Vararg{Dimension}}
dims(x, query...) => Tuple{Vararg{Dimension}}
Get the dimension(s) matching the type(s) of the query dimension.
Lookup can be an Int or an Dimension, or a tuple containing
any combination of either.
## Arguments
- `x`: any object with a `dims` method, or a `Tuple` of `Dimension`.
- `query`: Tuple or a single `Dimension` or `Dimension` `Type`.
## Example
```jldoctest
julia> using DimensionalData
julia> A = DimArray(ones(2, 3, 2), (X, Y, Z))
╭───────────────────────────╮
│ 2×3×2 DimArray{Float64,3} │
├───────────────────── dims ┤
↓ X, → Y, ↗ Z
└───────────────────────────┘
[:, :, 1]
1.0 1.0 1.0
1.0 1.0 1.0
julia> dims(A, (X, Y))
↓ X, → Y
```
"""
function dims end
@inline dims(a1, args...) = _dim_query(_dims, MaybeFirst(), a1, args...)
@inline dims(::Tuple{}, ::Tuple{}) = ()
@inline _dims(f, dims, query) = _remove_nothing(_sortdims(f, dims, query))
@inline _dims(f, dims, query...) = _remove_nothing(_sortdims(f, dims, query))
"""
commondims([f], x, query) => Tuple{Vararg{Dimension}}
This is basically `dims(x, query)` where the order of the original is kept,
unlike [`dims`](@ref) where the query tuple determines the order
Also unlike `dims`,`commondims` always returns a `Tuple`, no matter the input.
No errors are thrown if dims are absent from either `x` or `query`.
`f` is `<:` by default, but can be `>:` to sort abstract types by concrete types.
```jldoctest
julia> using DimensionalData, .Dimensions
julia> A = DimArray(ones(10, 10, 10), (X, Y, Z));
julia> commondims(A, X)
↓ X
julia> commondims(A, (X, Z))
↓ X, → Z
julia> commondims(A, Ti)
()
```
"""
function commondims end
@inline commondims(a1, args...) = _dim_query(_commondims, AlwaysTuple(), a1, args...)
_commondims(f, ds, query) = _dims(f, ds, _dims(_flip_subtype(f), query, ds))
"""
dimnum(x, query::Tuple) => NTuple{Int}
dimnum(x, query) => Int
Get the number(s) of `Dimension`(s) as ordered in the dimensions of an object.
## Arguments
- `x`: any object with a `dims` method, a `Tuple` of `Dimension` or a single `Dimension`.
- `query`: Tuple, Array or single `Dimension` or dimension `Type`.
The return type will be a Tuple of `Int` or a single `Int`,
depending on whether `query` is a `Tuple` or single `Dimension`.
## Example
```jldoctest
julia> using DimensionalData
julia> A = DimArray(ones(10, 10, 10), (X, Y, Z));
julia> dimnum(A, (Z, X, Y))
(3, 1, 2)
julia> dimnum(A, Y)
2
```
"""
function dimnum end
@inline function dimnum(x, q1, query...)
all(hasdim(x, q1, query...)) || _extradimserror(otherdims(x, (q1, query...)))
_dim_query(_dimnum, MaybeFirst(), x, q1, query...)
end
@inline dimnum(x, query::Function) =
_dim_query(_dimnum, MaybeFirst(), x, query)
@inline _dimnum(f::Function, ds::Tuple, query::Tuple{Vararg{Int}}) = query
@inline function _dimnum(f::Function, ds::Tuple, query::Tuple)
numbered = map(ds, ntuple(identity, length(ds))) do d, i
rebuild(d, i)
end
map(val, _dims(f, numbered, query))
end
"""
hasdim([f], x, query::Tuple) => NTuple{Bool}
hasdim([f], x, query...) => NTuple{Bool}
hasdim([f], x, query) => Bool
Check if an object `x` has dimensions that match or inherit from the `query` dimensions.
## Arguments
- `x`: any object with a `dims` method, a `Tuple` of `Dimension` or a single `Dimension`.
- `query`: Tuple or single `Dimension` or dimension `Type`.
- `f`: `<:` by default, but can be `>:` to match abstract types to concrete types.
Check if an object or tuple contains an `Dimension`, or a tuple of dimensions.
## Example
```jldoctest
julia> using DimensionalData
julia> A = DimArray(ones(10, 10, 10), (X, Y, Z));
julia> hasdim(A, X)
true
julia> hasdim(A, (Z, X, Y))
(true, true, true)
julia> hasdim(A, Ti)
false
```
"""
function hasdim end
@inline hasdim(x, a1, args...) =
_dim_query(_hasdim, MaybeFirst(), x, a1, args...)
@inline _hasdim(f, dims, query) =
map(d -> !(d isa Nothing), _sortdims(f, _commondims(f, dims, query), query))
@inline _hasdim(f, dims, query::Tuple{Vararg{Int}}) =
map(l -> l in eachindex(dims), query)
"""
otherdims(x, query) => Tuple{Vararg{Dimension,N}}
Get the dimensions of an object _not_ in `query`.
## Arguments
- `x`: any object with a `dims` method, a `Tuple` of `Dimension`.
- `query`: Tuple or single `Dimension` or dimension `Type`.
- `f`: `<:` by default, but can be `>:` to match abstract types to concrete types.
A tuple holding the unmatched dimensions is always returned.
## Example
```jldoctest
julia> using DimensionalData, DimensionalData.Dimensions
julia> A = DimArray(ones(10, 10, 10), (X, Y, Z));
julia> otherdims(A, X)
↓ Y, → Z
julia> otherdims(A, (Y, Z))
↓ X
```
"""
function otherdims end
@inline otherdims(x, query...) =
_dim_query(_otherdims, AlwaysTuple(), x, query...)
@inline _otherdims(f, ds) = ds
@inline function _otherdims(f, ds, query)
sorted = sortdims(f, dims(ds, query), ds)
_otherdims_from_nothing(f, ds, sorted)
end
# Work with a sorted query where the missing dims are `nothing`
@inline _otherdims_from_nothing(f, ds::Tuple, query::Tuple) =
(_dimifnothing(f, first(ds), first(query))..., _otherdims_from_nothing(f, tail(ds), tail(query))...)
@inline _otherdims_from_nothing(f, ::Tuple{}, ::Tuple{}) = ()
@inline _dimifnothing(f, dim, query) = ()
@inline _dimifnothing(f, dim, query::Nothing) = (dim,)
"""
setdims(X, newdims) => AbstractArray
setdims(::Tuple, newdims) => Tuple{Vararg{Dimension,N}}
Replaces the first dim matching `<: basetypeof(newdim)` with newdim,
and returns a new object or tuple with the dimension updated.
## Arguments
- `x`: any object with a `dims` method, a `Tuple` of `Dimension` or a single `Dimension`.
- `newdim`: Tuple or single `Dimension`, `Type` or `Symbol`.
# Example
```jldoctest
using DimensionalData, DimensionalData.Dimensions, DimensionalData.Lookups
A = ones(X(10), Y(10:10:100))
B = setdims(A, Y(Categorical('a':'j'; order=ForwardOrdered())))
lookup(B, Y)
# output
Categorical{Char} ForwardOrdered
wrapping: 'a':1:'j'
```
"""
function setdims end
@inline setdims(x, d1, d2, ds...) = setdims(x, (d1, d2, ds...))
@inline setdims(x) = x
@inline setdims(x, newdims::Dimension) = rebuild(x; dims=setdims(dims(x), name2dim(newdims)))
@inline setdims(x, newdims::Tuple) = rebuild(x; dims=setdims(dims(x), name2dim(newdims)))
@inline setdims(dims::Tuple, newdim::Dimension) = setdims(dims, (newdim,))
@inline setdims(dims::Tuple, newdims::Tuple) = swapdims(dims, sortdims(newdims, dims))
@inline setdims(dims::Tuple, newdims::Tuple{}) = dims
"""
swapdims(x::T, newdims) => T
swapdims(dims::Tuple, newdims) => Tuple{Vararg{Dimension}}
Swap dimensions for the passed in dimensions, in the
order passed.
Passing in the `Dimension` types rewraps the dimension index,
keeping the index values and metadata, while constructed `Dimension`
objects replace the original dimension. `nothing` leaves the original
dimension as-is.
## Arguments
- `x`: any object with a `dims` method or a `Tuple` of `Dimension`.
- `newdim`: Tuple of `Dimension` or dimension `Type`.
# Example
```jldoctest
using DimensionalData
A = ones(X(2), Y(4), Z(2))
Dimensions.swapdims(A, (Dim{:a}, Dim{:b}, Dim{:c}))
# output
╭───────────────────────────╮
│ 2×4×2 DimArray{Float64,3} │
├───────────────────── dims ┤
↓ a, → b, ↗ c
└───────────────────────────┘
[:, :, 1]
1.0 1.0 1.0 1.0
1.0 1.0 1.0 1.0
```
"""
function swapdims end
@inline swapdims(x, d1, d2, ds...) = swapdims(x, (d1, d2, ds...))
@inline swapdims(x) = x
@inline swapdims(x, newdims::Tuple) =
rebuild(x; dims=format(swapdims(dims(x), newdims), x))
@inline swapdims(dims::DimTuple, newdims::Tuple) =
map((d, nd) -> _swapdims(d, nd), dims, newdims)
@inline _swapdims(dim::Dimension, newdim::DimType) = basetypeof(newdim)(val(dim))
@inline _swapdims(dim::Dimension, newdim::Dimension) = newdim
@inline _swapdims(dim::Dimension, newdim::Nothing) = dim
"""
slicedims(x, I) => Tuple{Tuple,Tuple}
slicedims(f, x, I) => Tuple{Tuple,Tuple}
Slice the dimensions to match the axis values of the new array.
All methods return a tuple containing two tuples: the new dimensions,
and the reference dimensions. The ref dimensions are no longer used in
the new struct but are useful to give context to plots.
Called at the array level the returned tuple will also include the
previous reference dims attached to the array.
# Arguments
- `f`: a function `getindex`, `view` or `dotview`. This will be used for slicing
`getindex` is the default if `f` is not included.
- `x`: An `AbstractDimArray`, `Tuple` of `Dimension`, or `Dimension`
- `I`: A tuple of `Integer`, `Colon` or `AbstractArray`
"""
function slicedims end
@propagate_inbounds slicedims(args...) = slicedims(getindex, args...)
@propagate_inbounds slicedims(f::Function, x, i1, i2, I...) = slicedims(f, x, (i1, i2, I...))
@propagate_inbounds slicedims(f::Function, x, I::CartesianIndex) = slicedims(f, x, Tuple(I))
@propagate_inbounds slicedims(f::Function, x, I::Tuple) = _slicedims(f, dims(x), refdims(x), I)
@propagate_inbounds slicedims(f::Function, dims::Tuple, I::Tuple) = _slicedims(f, dims, I)
@propagate_inbounds slicedims(f::Function, dims::Tuple, refdims::Tuple, i1, I...) = slicedims(f, dims, refdims, (i1, I...))
@propagate_inbounds slicedims(f::Function, dims::Tuple, refdims::Tuple, I) = _slicedims(f, dims, refdims, I)
@propagate_inbounds slicedims(f::Function, dims::Tuple, refdims::Tuple, I::CartesianIndex) =
slicedims(f, dims, refdims, Tuple(I))
@propagate_inbounds function _slicedims(f, dims::Tuple, refdims::Tuple, I::Tuple)
# Unaligned may need grouped slicing
newdims, newrefdims = if any(map(d -> lookup(d) isa Unaligned, dims))
# Separate out unaligned dims
udims = _unalligned_dims(dims)
odims = otherdims(dims, udims)
oI = map(d -> I[dimnum(dims, d)], odims)
uI = map(d -> I[dimnum(dims, d)], udims)
d, rd = _slicedims(f, odims, oI)
udims, urefdims = sliceunalligneddims(f, uI, udims...)
# Recombine dims and refdims
Dimensions.dims((d..., udims...), dims), (rd..., urefdims...)
else
_slicedims(f, dims, I)
end
return newdims, (refdims..., newrefdims...)
end
@propagate_inbounds _slicedims(f, dims::Tuple, refdims::Tuple, I::Tuple{}) = dims, refdims
@propagate_inbounds _slicedims(f, dims::DimTuple, I::Tuple{}) = dims, ()
@propagate_inbounds function _slicedims(f, dims::DimTuple, I::Tuple{<:CartesianIndex})
return _slicedims(f, dims, Tuple(I[1]))
end
@propagate_inbounds _slicedims(f, dims::DimTuple, I::Tuple) = begin
d = _slicedims(f, first(dims), first(I))
ds = _slicedims(f, tail(dims), tail(I))
(d[1]..., ds[1]...), (d[2]..., ds[2]...)
end
# Return an AnonDim where e.g. a trailing Colon was passed
@propagate_inbounds function _slicedims(f, dims::Tuple{}, I::Tuple{Base.Slice,Vararg})
d = (AnonDim(_unwrapinds(first(I))),), ()
ds = _slicedims(f, (), tail(I))
(d[1]..., ds[1]...), (d[2]..., ds[2]...)
end
# Drop trailing Integers
@propagate_inbounds _slicedims(f, dims::Tuple{}, I::Tuple{Integer,Vararg}) = _slicedims(f, (), tail(I))
@propagate_inbounds _slicedims(f, dims::Tuple{}, I::Tuple{CartesianIndices{0,Tuple{}},Vararg}) = _slicedims(f, (), tail(I))
@propagate_inbounds _slicedims(f, dims::Tuple{}, I::Tuple{}) = (), ()
@propagate_inbounds _slicedims(f, d::Dimension, i::Colon) = (d,), ()
@propagate_inbounds _slicedims(f::F, d::Dimension, i::Integer) where F = (), (f(d, i:i),)
@propagate_inbounds _slicedims(f::F, d::Dimension, i) where F = (f(d, i),), ()
_unwrapinds(s::Base.Slice) = s.indices
_unwrapinds(x) = x # Not sure this can ever be hit? But just in case
_unalligned_dims(dims::Tuple) = _unalligned_dims(dims...)
_unalligned_dims(dim::Dimension{<:Unaligned}, args...) = (dim, _unalligned_dims(args...)...)
_unalligned_dims(dim::Dimension, args...) = _unalligned_dims(args...)
_unalligned_dims() = ()
# Default
function sliceunalligneddims(f, uI, udims...)
udims, ()
end
"""
reducedims(x, dimstoreduce) => Tuple{Vararg{Dimension}}
Replace the specified dimensions with an index of length 1.
This is usually to match a new array size where an axis has been
reduced with a method like `mean` or `reduce` to a length of 1,
but the number of dimensions has not changed.
`Lookup` traits are also updated to correspond to the change in
cell step, sampling type and order.
"""
function reducedims end
@inline reducedims(x, dimstoreduce) = _reducedims(x, name2dim(dimstoreduce))
@inline _reducedims(x, dimstoreduce) = _reducedims(x, (dimstoreduce,))
@inline _reducedims(x, dimstoreduce::Tuple) = _reducedims(dims(x), dimstoreduce)
@inline _reducedims(dims::DimTuple, dimstoreduce::Tuple) =
map(_reducedims, dims, sortdims(dimstoreduce, dims))
# Map numbers to corresponding dims. Not always type-stable
@inline _reducedims(dims::DimTuple, dimstoreduce::Tuple{Vararg{Int}}) =
map(_reducedims, dims, sortdims(map(i -> dims[i], dimstoreduce), dims))
# Reduce matching dims but ignore nothing vals - they are the dims not being reduced
@inline _reducedims(dim::Dimension, ::Nothing) = dim
@inline _reducedims(dim::Dimension, ::DimOrDimType) = rebuild(dim, reducelookup(lookup(dim)))
const DimTupleOrEmpty = Union{DimTuple,Tuple{}}
struct _Throw end
"""
comparedims(A::AbstractDimArray...; kw...)
comparedims(A::Tuple...; kw...)
comparedims(A::Dimension...; kw...)
comparedims(::Type{Bool}, args...; kw...)
Check that dimensions or tuples of dimensions passed as each
argument are the same, and return the first valid dimension.
If `AbstractDimArray`s are passed as arguments their dimensions are compared.
Empty tuples and `nothing` dimension values are ignored,
returning the `Dimension` value if it exists.
Passing `Bool` as the first argument means `true`/`false` will be returned,
rather than throwing an error.
# Keywords
These are all `Bool` flags:
- `type`: compare dimension type, `true` by default.
- `valtype`: compare wrapped value type, `false` by default.
- `val`: compare wrapped values, `false` by default.
- `order`: compare order, `false` by default.
- `length`: compare lengths, `true` by default.
- `ignore_length_one`: ignore length `1` in comparisons, and return whichever
dimension is not length 1, if any. This is useful in e.g. broadcasting comparisons.
`false` by default.
- `warn`: a `String` or `nothing`. Used only for `Bool` methods,
to give a warning for `false` values and include `warn` in the warning text.
"""
function comparedims end
@inline comparedims(args...; kw...) = _comparedims(_Throw, args...; kw...)
@inline comparedims(T::Type, args...; kw...) = _comparedims(T, args...; kw...)
@inline _comparedims(T::Type, d1::Dimension, ds::Dimension...; kw...) =
map(d -> _comparedims(T, d1, d; kw...), (d1, ds...))
@inline _comparedims(T::Type, A::Tuple; kw...) = _comparedims(T, map(dims, A)...; kw...)
@inline _comparedims(T::Type, A...; kw...) = _comparedims(T, map(dims, A)...; kw...)
@inline _comparedims(T::Type, dims::Vararg{Tuple{Vararg{Dimension}}}; kw...) =
map(d -> _comparedims(T, first(dims), d; kw...), dims)
@inline _comparedims(T::Type{_Throw}; kw...) = ()
@inline _comparedims(T::Type{_Throw}, a::DimTuple, b::DimTuple; kw...) =
(_comparedims(T, first(a), first(b); kw...), _comparedims(T, tail(a), tail(b); kw...)...)
@inline _comparedims(::Type{_Throw}, a::DimTupleOrEmpty, ::Nothing; kw...) = a
@inline _comparedims(::Type{_Throw}, ::Nothing, b::DimTupleOrEmpty; kw...) = b
@inline _comparedims(::Type{_Throw}, a::DimTuple, b::Tuple{}; kw...) = a
@inline _comparedims(::Type{_Throw}, a::Tuple{}, b::DimTuple; kw...) = b
@inline _comparedims(::Type{_Throw}, a::Tuple{}, b::Tuple{}; kw...) = ()
@inline _comparedims(::Type{_Throw}, ::Nothing, ::Nothing; kw...) = nothing
@inline _comparedims(::Type{_Throw}, a::AnonDim, b::AnonDim; kw...) = nothing
@inline _comparedims(::Type{_Throw}, a::Dimension, b::AnonDim; kw...) = a
@inline _comparedims(::Type{_Throw}, a::AnonDim, b::Dimension; kw...) = b
@inline function _comparedims(::Type{_Throw}, a::Dimension, b::Dimension;
type=true, valtype=false, val=false, length=true, order=false, ignore_length_one=false,
)
type && basetypeof(a) != basetypeof(b) && _dimsmismatcherror(a, b)
valtype && typeof(parent(a)) != typeof(parent(b)) && _valtypeerror(a, b)
val && parent(lookup(a)) != parent(lookup(b)) && _valerror(a, b)
if order
(isnolookup(a) || isnolookup(b) || LU.order(a) == LU.order(b)) || _ordererror(a, b)
end
if ignore_length_one && (Base.length(a) == 1 || Base.length(b) == 1)
return Base.length(b) == 1 ? a : b
end
length && Base.length(a) != Base.length(b) && _dimsizeerror(a, b)
return a
end
@inline _comparedims(T::Type; kw...) = true
@inline _comparedims(T::Type{Bool}, d1::Dimension, ds::Dimension...; kw...) =
all(map(d -> _comparedims(T, d1, d; kw...), ds))
@inline _comparedims(T::Type{Bool}, dims::Vararg{Tuple{Vararg{Dimension}}}; kw...) =
all(map(d -> _comparedims(T, first(dims), d; kw...), dims))
@inline _comparedims(T::Type{Bool}, a::DimTuple, b::DimTuple; kw...) =
all((_comparedims(T, first(a), first(b); kw...), _comparedims(T, tail(a), tail(b); kw...)...))
@inline _comparedims(T::Type{Bool}, a::DimTupleOrEmpty, ::Nothing; kw...) = true
@inline _comparedims(T::Type{Bool}, ::Nothing, b::DimTupleOrEmpty; kw...) = true
@inline _comparedims(T::Type{Bool}, ::Nothing, ::Nothing; kw...) = true
@inline _comparedims(T::Type{Bool}, a::DimTuple, b::Tuple{}; kw...) = true
@inline _comparedims(T::Type{Bool}, a::Tuple{}, b::DimTuple; kw...) = true
@inline _comparedims(T::Type{Bool}, a::Tuple{}, b::Tuple{}; kw...) = true
@inline _comparedims(T::Type{Bool}, a::AnonDim, b::AnonDim; kw...) = true
@inline _comparedims(T::Type{Bool}, a::Dimension, b::AnonDim; kw...) = true
@inline _comparedims(T::Type{Bool}, a::AnonDim, b::Dimension; kw...) = true
@inline function _comparedims(::Type{Bool}, a::Dimension, b::Dimension;
type=true, valtype=false, val=false, length=true, order=false, ignore_length_one=false,
warn::Union{Nothing,String}=nothing,
)
if type && basetypeof(a) != basetypeof(b)
isnothing(warn) || _dimsmismatchwarn(a, b, warn)
return false
end
if valtype && typeof(parent(a)) != typeof(parent(b))
isnothing(warn) || _valtypewarn(a, b, warn)
return false
end
if val && parent(lookup(a)) != parent(lookup(b))
isnothing(warn) || _valwarn(a, b, warn)
return false
end
if order && !(isnolookup(a) || isnolookup(b) || LU.order(a) == LU.order(b))
isnothing(warn) || _orderwarn(a, b, warn)
return false
end
if ignore_length_one && (Base.length(a) == 1 || Base.length(b) == 1)
return true
end
if length && Base.length(a) != Base.length(b)
isnothing(warn) || _dimsizewarn(a, b, warn)
return false
end
return true
end
"""
combinedims(xs; check=true)
Combine the dimensions of each object in `xs`, in the order they are found.
"""
function combinedims end
function combinedims(xs::Vector; kw...)
if length(xs) > 0
reduce(xs; init=dims(first(xs))) do ds, A
_combinedims(ds, dims(A); kw...)
end
else
()
end
end
combinedims(; kw...) = ()
combinedims(x1, xs...; kw...) = combinedims(map(dims, (x1, xs...))...; kw...)
combinedims(dt1::DimTupleOrEmpty; kw...) = dt1
combinedims(dt1::DimTupleOrEmpty, dt2::DimTupleOrEmpty, dimtuples::DimTupleOrEmpty...; kw...) =
reduce((dt2, dimtuples...); init=dt1) do dims1, dims2
_combinedims(dims1, dims2; kw...)
end
# Cant use `map` here, tuples may not be the same length
_combinedims(a::DimTupleOrEmpty, b::DimTupleOrEmpty; check=true, kw...) = begin
if check # Check the matching dims are the same
common = commondims(a, b)
comparedims(dims(a, common), dims(b, common); kw...)
end
# Take them from a, and add any extras from b
(a..., otherdims(b, a)...)
end
"""
basedims(ds::Tuple)
basedims(d::Union{Dimension,Symbol,Type})
Returns `basetypeof(d)()` or a `Tuple` of called on a `Tuple`.
See [`basetypeof`](@ref)
"""
function basedims end
@inline basedims(x) = basedims(dims(x))
@inline basedims(ds::Tuple) = map(basedims, ds)
@inline basedims(d::Dimension) = basetypeof(d)()
@inline basedims(d::Symbol) = name2dim(d)
@inline basedims(T::Type{<:Dimension}) = basetypeof(T)()
@inline pairs2dims(pairs::Pair...) = map(p -> basetypeof(name2dim(first(p)))(last(p)), pairs)
@inline kw2dims(kw::Base.Iterators.Pairs) = kw2dims(values(kw))
# Convert `Symbol` keyword arguments to a `Tuple` of `Dimension`
@inline kw2dims(kw::NamedTuple{Keys}) where Keys = kw2dims(name2dim(Keys), values(kw))
@inline kw2dims(dims::Tuple, vals::Tuple) =
(rebuild(first(dims), first(vals)), kw2dims(tail(dims), tail(vals))...)
@inline kw2dims(::Tuple{}, ::Tuple{}) = ()
# Queries
# Most primitives use these for argument handling
abstract type QueryMode end
struct MaybeFirst <: QueryMode end
struct AlwaysTuple <: QueryMode end
(::AlwaysTuple)(xs::Tuple) = xs
(::MaybeFirst)(xs::Tuple) = first(xs)
(::MaybeFirst)(::Tuple{}) = nothing
# Call the function f with standardised args
# This looks like HELL, but it removes this complexity
# from every other method and makes sure they all behave the same way.
@inline _dim_query(f::Function, t::QueryMode, args...) =
_dim_query(f, <:, t::QueryMode, args...)
@inline _dim_query(f::Function, t::QueryMode, op::Union{typeof(<:),typeof(>:)}, args...) =
_dim_query(f, op, t::QueryMode, args...)
@inline _dim_query(f::Function, t::QueryMode, op::Union{typeof(<:),typeof(>:)}, a1, args::Tuple) =
_dim_query(f, op, t::QueryMode, a1, args...)
@inline _dim_query(f::Function, op::Function, t::QueryMode, a1, args...) =
_dim_query1(f, op, t, _wraparg(a1, args...)...)
@inline _dim_query(f::Function, op::Function, t::QueryMode, a1, args::Tuple) =
_dim_query1(f, op, t::QueryMode, _wraparg(a1)..., _wraparg(args...))
@inline _dim_query1(f, op::Function, t, x, l1, l2, ls...) = _dim_query1(f, op, t, x, (l1, l2, ls...))
@inline _dim_query1(f, op::Function, t, x) = _dim_query1(f, op, t, dims(x))
@inline _dim_query1(f, op::Function, t, x, query) = _dim_query1(f, op, t, dims(x), query)
@inline _dim_query1(f, op::Function, t, x::Nothing) = _dimsnotdefinederror()
@inline _dim_query1(f, op::Function, t, x::Nothing, query) = _dimsnotdefinederror()
@inline _dim_query1(f, op::Function, t, ds::Tuple, query::Colon) =
_dim_query1(f, op, t, ds, basedims(ds))
@inline function _dim_query1(f, op::Function, t, ds::Tuple, query::Function)
selection = foldl(ds; init=()) do acc, d
query(d) ? (acc..., d) : acc
end
_dim_query1(f, op, t, ds, selection)
end
@inline function _dim_query1(f, op::Function, t, d::Tuple, query)
ds = dims(query)
isnothing(ds) && _dims_are_not_dims()
_dim_query1(f, op, t, d, ds)
end
@inline _dim_query1(f, op::Function, t::QueryMode, d::Tuple, query::Union{Dimension,DimType,Val,Integer}) =
_dim_query1(f, op, t, d, (query,)) |> t
@inline _dim_query1(f, op::Function, ::QueryMode, d::Tuple, query::Tuple) = map(unwrap, f(op, d, query))
@inline _dim_query1(f, op::Function, ::QueryMode, d::Tuple) = map(unwrap, f(op, d))
# Utils
# Remove `nothing` from a `Tuple`
@inline _remove_nothing(xs::Tuple) = _remove_nothing(xs...)
@inline _remove_nothing(x, xs...) = (x, _remove_nothing(xs...)...)
@inline _remove_nothing(::Nothing, xs...) = _remove_nothing(xs...)
@inline _remove_nothing() = ()
# This looks ridiculous, but gives seven arguments with constant-propagation,
# which means type stability using Symbols/types instead of objects.
@inline _wraparg(d1, d2, d3, d4, d5, d6, d7, ds...) =
(_w(d1), _w(d2), _w(d3), _w(d4), _w(d5), _w(d6), _w(d7), _wraparg(ds...)...)
@inline _wraparg(d1, d2, d3, d4, d5, d6) = _w(d1), _w(d2), _w(d3), _w(d4), _w(d5), _w(d6)
@inline _wraparg(d1, d2, d3, d4, d5) = _w(d1), _w(d2), _w(d3), _w(d4), _w(d5)
@inline _wraparg(d1, d2, d3, d4) = _w(d1), _w(d2), _w(d3), _w(d4)
@inline _wraparg(d1, d2, d3) = _w(d1), _w(d2), _w(d3)
@inline _wraparg(d1, d2) = _w(d1), _w(d2)
@inline _wraparg(d1) = (_w(d1),)
@inline _wraparg() = ()
@inline _w(t::Tuple) = _wraparg(t...)
@inline _w(x) = x
@inline _w(s::Symbol) = name2dim(s)
@inline _w(::Type{T}) where T = Val{T}()
@inline _flip_subtype(::typeof(<:)) = >:
@inline _flip_subtype(::typeof(>:)) = <:
_astuple(t::Tuple) = t
_astuple(x) = (x,)
# Warnings and Error methods.
_dimsmismatchmsg(a, b) = "$(basetypeof(a)) and $(basetypeof(b)) dims on the same axis."
_valmsg(a, b) = "Lookup values for $(basetypeof(a)) of $(parent(a)) and $(parent(b)) do not match."
_dimsizemsg(a, b) = "Found both lengths $(length(a)) and $(length(b)) for $(basetypeof(a))."
_valtypemsg(a, b) = "Lookup for $(basetypeof(a)) of $(lookup(a)) and $(lookup(b)) do not match."
_extradimsmsg(extradims) = "$(map(basetypeof, extradims)) dims were not found in object."
_extradimsmsg(::Tuple{}) = "Some dims were not found in object."
_metadatamsg(a, b) = "Metadata $(metadata(a)) and $(metadata(b)) do not match."
_ordermsg(a, b) = "Lookups do not all have the same order: $(order(a)), $(order(b))."
_typemsg(a, b) = "Lookups do not all have the same type: $(order(a)), $(order(b))."
# Warning: @noinline to avoid allocations when it isn't used
@noinline _dimsmismatchwarn(a, b, msg="") = @warn string(_dimsmismatchmsg(a, b), msg)
@noinline _valwarn(a, b, msg="") = @warn string(_valmsg(a, b), msg)
@noinline _dimsizewarn(a, b, msg="") = @warn string(_dimsizemsg(a, b), msg)
@noinline _valtypewarn(a, b, msg="") = @warn string(_valtypemsg(a, b), msg)
@noinline _extradimswarn(dims, msg="") = @warn string(_extradimsmsg(dims), msg)
@noinline _orderwarn(a, b, msg="") = @warn string(_ordermsg(a, b), msg)
# Error
@noinline _dimsmismatcherror(a, b) = throw(DimensionMismatch(_dimsmismatchmsg(a, b)))
@noinline _dimsizeerror(a, b) = throw(DimensionMismatch(_dimsizemsg(a, b)))
@noinline _valtypeerror(a, b) = throw(DimensionMismatch(_valtypemsg(a, b)))
@noinline _valerror(a, b) = throw(DimensionMismatch(_valmsg(a, b)))
@noinline _ordererror(a, b) = throw(DimensionMismatch(_ordermsg(a, b)))
@noinline _metadataerror(a, b) = throw(DimensionMismatch(_metadatamsg(a, b)))
@noinline _extradimserror(args) = throw(ArgumentError(_extradimsmsg(args)))
@noinline _dimsnotdefinederror() = throw(ArgumentError("Object does not define a `dims` method"))
@noinline _dims_are_not_dims() = throw(ArgumentError("`dims` are not `Dimension`s"))