[ITensorsNamedDimsArraysExt] Convert symmetric tensors

Author: mtfishman

NDTensors/Project.toml

@@ -1,7 +1,7 @@
 name = "NDTensors"
 uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 authors = ["Matthew Fishman <[email protected]>"]
-version = "0.3.62"
+version = "0.3.63"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

NDTensors/src/lib/GradedAxes/src/gradedunitrangedual.jl

@@ -94,6 +94,21 @@ function blockedunitrange_getindices(
   return flip_blockvector(v)
 end
 
+# Fixes ambiguity error.
+# TODO: Write this in terms of `blockedunitrange_getindices(dual(a), indices)`.
+function blockedunitrange_getindices(
+  a::GradedUnitRangeDual, indices::AbstractBlockVector{<:Block{1}}
+)
+  blks = map(bs -> mortar(map(b -> a[b], bs)), blocks(indices))
+  # We pass `length.(blks)` to `mortar` in order
+  # to pass block labels to the axes of the output,
+  # if they exist. This makes it so that
+  # `only(axes(a[indices])) isa `GradedUnitRange`
+  # if `a isa `GradedUnitRange`, for example.
+  v = mortar(blks, labelled_length.(blks))
+  return flip_blockvector(v)
+end
+
 function flip_blockvector(v::BlockVector)
   block_axes = flip.(axes(v))
   flipped = mortar(vec.(blocks(v)), block_axes)

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensors"
 uuid = "9136182c-28ba-11e9-034c-db9fb085ebd5"
 authors = ["Matthew Fishman <[email protected]>", "Miles Stoudenmire <[email protected]>"]
-version = "0.7.4"
+version = "0.7.5"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"

src/lib/ITensorsNamedDimsArraysExt/src/to_nameddimsarray.jl

@@ -1,5 +1,5 @@
-using ..NDTensors: data, inds
 using ITensors: ITensor
+using ..NDTensors: data, inds
 
 # TODO: Delete this, it is a hack to decide
 # if an Index is blocked.
@@ -34,21 +34,35 @@ function to_nameddimsarray(x::DiagTensor)
   return named(DiagonalArray(data(x), size(x)), name.(inds(x)))
 end
 
-using ..NDTensors: BlockSparseTensor
+using ITensors: ITensors, dir, qn
+using ..NDTensors: BlockSparseTensor, array, blockdim, datatype, nblocks, nzblocks
 using ..NDTensors.BlockSparseArrays: BlockSparseArray
+using ..NDTensors.BlockSparseArrays.BlockArrays: BlockArrays, blockedrange
+using ..NDTensors.GradedAxes: dual, gradedrange
+using ..NDTensors.TypeParameterAccessors: set_ndims
 # TODO: Delete once `BlockSparse` is removed.
 function to_nameddimsarray(x::BlockSparseTensor)
-  blockinds = map(i -> [blockdim(i, b) for b in 1:nblocks(i)], inds(x))
+  blockinds = map(inds(x)) do i
+    r = gradedrange([qn(i, b) => blockdim(i, b) for b in 1:nblocks(i)])
+    if dir(i) == ITensors.In
+      return dual(r)
+    end
+    return r
+  end
   blocktype = set_ndims(datatype(x), ndims(x))
   # TODO: Make a simpler constructor:
   # BlockSparseArray(blocktype, blockinds)
-  arraystorage = BlockSparseArray{eltype(x),ndims(x),blocktype}(blockinds)
+  arraystorage = BlockSparseArray{eltype(x),ndims(x),blocktype}(undef, blockinds)
   for b in nzblocks(x)
-    arraystorage[BlockArrays.Block(Tuple(b)...)] = x[b]
+    arraystorage[BlockArrays.Block(Int.(Tuple(b))...)] = array(x[b])
   end
   return named(arraystorage, name.(inds(x)))
 end
 
+using ITensors: QN
+using ..NDTensors.GradedAxes: GradedAxes
+GradedAxes.fuse_labels(l1::QN, l2::QN) = l1 + l2
+
 ## TODO: Add this back, define `CombinerArrays` library in NDTensors!
 ## using ..NDTensors: CombinerTensor, CombinerArray, storage
 ## # TODO: Delete when we directly use `CombinerArray` as storage.