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changeset 508:27e64b3d3efa

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Restructure tests for InflatedTensorMapping
author Jonatan Werpers <jonatan@werpers.com>
date Mon, 23 Nov 2020 21:15:04 +0100
parents fbbb3733650c
children fe86ac896377 afdfb027e439
files test/testLazyTensors.jl
diffstat 1 files changed, 55 insertions(+), 48 deletions(-) [+]
line wrap: on
line diff
--- a/test/testLazyTensors.jl	Fri Nov 06 21:37:10 2020 +0100
+++ b/test/testLazyTensors.jl	Mon Nov 23 21:15:04 2020 +0100
@@ -340,61 +340,69 @@
     B = LazyLinearMap(B̃,(1,2),(3,))
     C = LazyLinearMap(C̃,(1,),(2,3))
 
-    @test InflatedTensorMapping(I(3,2), A, I(4)) isa TensorMapping{Float64, 4, 4}
-    @test InflatedTensorMapping(I(3,2), B, I(4)) isa TensorMapping{Float64, 5, 4}
-    @test InflatedTensorMapping(I(3), C, I(2,3)) isa TensorMapping{Float64, 4, 5}
-    @test InflatedTensorMapping(C, I(2,3)) isa TensorMapping{Float64, 3, 4}
-    @test InflatedTensorMapping(I(3), C) isa TensorMapping{Float64, 2, 3}
-    @test InflatedTensorMapping(I(3), I(2,3)) isa TensorMapping{Float64, 3, 3}
-
-    @test range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
-    @test domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
-
-    @test range_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,4,2,4)
-    @test domain_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,3,4)
-
-    @test range_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,4,2,3)
-    @test domain_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,2,3,2,3)
-
-    @inferred range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
-    @inferred domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
+    @testset "Constructors" begin
+        @test InflatedTensorMapping(I(3,2), A, I(4)) isa TensorMapping{Float64, 4, 4}
+        @test InflatedTensorMapping(I(3,2), B, I(4)) isa TensorMapping{Float64, 5, 4}
+        @test InflatedTensorMapping(I(3), C, I(2,3)) isa TensorMapping{Float64, 4, 5}
+        @test InflatedTensorMapping(C, I(2,3)) isa TensorMapping{Float64, 3, 4}
+        @test InflatedTensorMapping(I(3), C) isa TensorMapping{Float64, 2, 3}
+        @test InflatedTensorMapping(I(3), I(2,3)) isa TensorMapping{Float64, 3, 3}
+    end
 
-    # Test InflatedTensorMapping mapping w. before and after
-    tm = InflatedTensorMapping(I(3,2), A, I(4))
-    v = rand(domain_size(tm)...)
-    @tullio IAIv[a,b,c,d] := Ã[c,i]*v[a,b,i,d]
-    @test tm*v ≈ IAIv rtol=1e-14
-    @inferred LazyTensors.split_index(tm,1,1,1,1)
+    @testset "Range and domain size" begin
+        @test range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
+        @test domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
 
-    # Test InflatedTensorMapping mapping w. before
-    tm = InflatedTensorMapping(I(3,2), A)
-    v = rand(domain_size(tm)...)
-    @tullio IAIv[a,b,c] := Ã[c,i]*v[a,b,i]
-    @test tm*v ≈ IAIv rtol=1e-14
-    @inferred LazyTensors.split_index(tm,1,1,1)
+        @test range_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,4,2,4)
+        @test domain_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,3,4)
 
-    # Test InflatedTensorMapping mapping w. after
-    tm = InflatedTensorMapping(A,I(4))
-    v = rand(domain_size(tm)...)
-    @tullio IAIv[c,d] := Ã[c,i]*v[i,d]
-    @test tm*v ≈ IAIv rtol=1e-14
-    @inferred LazyTensors.split_index(tm,1,1)
+        @test range_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,4,2,3)
+        @test domain_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,2,3,2,3)
 
-    struct ScalingOperator{T,D} <: TensorMapping{T,D,D}
-        λ::T
-        size::NTuple{D,Int}
+        @inferred range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
+        @inferred domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
     end
 
-    LazyTensors.apply(m::ScalingOperator{T,D}, v, I::Vararg{Index,D}) where {T,D} = m.λ*v[I]
-    LazyTensors.range_size(m::ScalingOperator) = m.size
-    LazyTensors.domain_size(m::ScalingOperator) = m.size
+    @testset "Application" begin
+        # Test InflatedTensorMapping mapping w. before and after
+        tm = InflatedTensorMapping(I(3,2), A, I(4))
+        v = rand(domain_size(tm)...)
+        @tullio IAIv[a,b,c,d] := Ã[c,i]*v[a,b,i,d]
+        @test tm*v ≈ IAIv rtol=1e-14
+        @inferred LazyTensors.split_index(tm,1,1,1,1)
+
+        # Test InflatedTensorMapping mapping w. before
+        tm = InflatedTensorMapping(I(3,2), A)
+        v = rand(domain_size(tm)...)
+        @tullio IAIv[a,b,c] := Ã[c,i]*v[a,b,i]
+        @test tm*v ≈ IAIv rtol=1e-14
+        @inferred LazyTensors.split_index(tm,1,1,1)
 
-    tm = InflatedTensorMapping(I(2,3),ScalingOperator(2.0, (3,2)),I(3,4))
-    v = rand(domain_size(tm)...)
+        # Test InflatedTensorMapping mapping w. after
+        tm = InflatedTensorMapping(A,I(4))
+        v = rand(domain_size(tm)...)
+        @tullio IAIv[c,d] := Ã[c,i]*v[i,d]
+        @test tm*v ≈ IAIv rtol=1e-14
+        @inferred LazyTensors.split_index(tm,1,1)
+
+        @testset "Inference of application" begin
+            struct ScalingOperator{T,D} <: TensorMapping{T,D,D}
+                λ::T
+                size::NTuple{D,Int}
+            end
 
-    @inferred LazyTensors.split_index(tm,1,2,3,2,2,4)
-    @inferred apply(tm,v,Index{Unknown}.((1,2,3,2,2,4))...)
-    @inferred (tm*v)[1,2,3,2,2,4]
+            LazyTensors.apply(m::ScalingOperator{T,D}, v, I::Vararg{Index,D}) where {T,D} = m.λ*v[I]
+            LazyTensors.range_size(m::ScalingOperator) = m.size
+            LazyTensors.domain_size(m::ScalingOperator) = m.size
+
+            tm = InflatedTensorMapping(I(2,3),ScalingOperator(2.0, (3,2)),I(3,4))
+            v = rand(domain_size(tm)...)
+
+            @inferred LazyTensors.split_index(tm,1,2,3,2,2,4)
+            @inferred apply(tm,v,Index{Unknown}.((1,2,3,2,2,4))...)
+            @inferred (tm*v)[1,2,3,2,2,4]
+        end
+    end
 
     @testset "InflatedTensorMapping of InflatedTensorMapping" begin
         A = ScalingOperator(2.0,(2,3))
@@ -405,7 +413,6 @@
 
         @test InflatedTensorMapping(I(2), I(2), I(2)) isa InflatedTensorMapping # The constructor should always return its type.
     end
-
 end
 
 @testset "slice_tuple" begin