fixed conversion TCI2 -> TCI1

Author: rittermarc

src/abstracttensortrain.jl

@@ -191,11 +191,11 @@ function _addtttensor(
 end
 
 @doc raw"""
-function add(
-    lhs::AbstractTensorTrain{V}, rhs::AbstractTensorTrain{V};
-    factorlhs=one(V), factorrhs=one(V),
-    tolerance::Float64=0.0, maxbonddim::Int=typemax(Int)
-) where {V}
+    function add(
+        lhs::AbstractTensorTrain{V}, rhs::AbstractTensorTrain{V};
+        factorlhs=one(V), factorrhs=one(V),
+        tolerance::Float64=0.0, maxbonddim::Int=typemax(Int)
+    ) where {V}
 
 Addition of two tensor trains. If `C = add(A, B)`, then `C(v) ≈ A(v) + B(v)` at each index set `v`. Note that this function increases the bond dimension, i.e. ``\chi_{\text{result}} = \chi_1 + \chi_2`` if the original tensor trains had bond dimensions ``\chi_1`` and ``\chi_2``.
 

src/conversion.jl

@@ -26,7 +26,7 @@ function TensorCI1{ValueType}(
     kwargs...
 ) where {ValueType}
     L = length(tci2)
-    tci1 = TensorCI1{ValueType}(length.(tci2.localset))
+    tci1 = TensorCI1{ValueType}(tci2.localdims)
     tci1.Iset = IndexSet.(tci2.Iset)
     tci1.Jset = IndexSet.(tci2.Jset)
     tci1.PiIset = getPiIset.(Ref(tci1), 1:L)
@@ -51,22 +51,21 @@ function TensorCI1{ValueType}(
     end
     tci1.P[end] = ones(ValueType, 1, 1)
 
-    tci1.pivoterrors = max.(tci2.bonderrorsforward, tci2.bonderrorsbackward)
+    tci1.pivoterrors = tci2.bonderrors
     tci1.maxsamplevalue = tci2.maxsamplevalue
     return tci1
 end
 
 function TensorCI2{ValueType}(tci1::TensorCI1{ValueType}) where {ValueType}
-    tci2 = TensorCI2{ValueType}(vcat(sitedims(tci1)...)::Vector{Int})
+    tci2 = TensorCI2{ValueType}(vcat(collect.(sitedims(tci1))...)::Vector{Int})
     tci2.Iset = [i.fromint for i in tci1.Iset]
     tci2.Jset = [j.fromint for j in tci1.Jset]
-    tci2.localset = tci1.localset
+    tci2.localdims = tci1.localdims
     L = length(tci1)
     tci2.sitetensors[1:L-1] = TtimesPinv.(tci1, 1:L-1)
     tci2.sitetensors[end] = tci1.T[end]
     tci2.pivoterrors = Float64[]
-    tci2.bonderrorsforward = tci1.pivoterrors
-    tci2.bonderrorsbackward = tci1.pivoterrors
+    tci2.bonderrors = tci1.pivoterrors
     tci2.maxsamplevalue = tci1.maxsamplevalue
     return tci2
 end

src/tensorci1.jl

@@ -159,11 +159,11 @@ function linkdim(tci::TensorCI1{V}, i::Int) where {V}
 end
 
 function sitedims(tci::TensorCI1{V}) where {V}
-    return [size(T)[2:end-1] for T in tci.T]
+    return [collect(size(T)[2:end-1]) for T in tci.T]
 end
 
 function sitedim(tci::TensorCI1{V}, i::Int) where {V}
-    return size(tci.T[i])[2:end-1]
+    return collect(size(tci.T[i])[2:end-1])
 end
 
 """

test/runtests.jl

@@ -16,5 +16,6 @@ include("test_batcheval.jl")
 include("test_tensorci1.jl")
 include("test_tensorci2.jl")
 include("test_tensortrain.jl")
+include("test_conversion.jl")
 include("test_contraction.jl")
-include("test_integration.jl")
+include("test_integration.jl")

test/test_conversion.jl

@@ -1,7 +1,7 @@
 using Test
 import TensorCrossInterpolation: TensorCI1, TensorCI2, sitedims, linkdims, rank,
-    addglobalpivot!, crossinterpolate1, optimize!, MatrixACA, rrlu,
-    nrows, ncols, evaluate, left, right
+    addglobalpivot!, crossinterpolate1, crossinterpolate2, optimize!, MatrixACA, rrlu,
+    nrows, ncols, evaluate, left, right, pivoterror, tensortrain
 
 @testset "Conversion between rrLU and ACA" begin
     A = [
@@ -31,7 +31,7 @@ end
     @test rank(tci2) == 0
     @test all(isempty.(tci2.Iset))
     @test all(isempty.(tci2.Jset))
-    @test all(isempty.(tci2.T))
+    @test all(isempty.(tci2.sitetensors))
 
     globalpivot = [2, 2, 3, 1]
     tci1 = TensorCI1{ComplexF64}(rand, fill(d, n), globalpivot)