Merge branch 'main' into GradedUnitRangeDual

NDTensors/Project.toml

@@ -1,7 +1,7 @@
 name = "NDTensors"
 uuid = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 authors = ["Matthew Fishman <[email protected]>"]
-version = "0.3.49"
+version = "0.3.52"
 
 [deps]
 Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"

NDTensors/src/abstractarray/set_types.jl

@@ -1,4 +1,5 @@
-using .TypeParameterAccessors: TypeParameterAccessors, set_ndims
+using .TypeParameterAccessors: TypeParameterAccessors
+
 """
 # Do we still want to define things like this?
 TODO: Use `Accessors.jl` notation:
@@ -14,13 +15,3 @@ TODO: Use `Accessors.jl` notation:
 function TypeParameterAccessors.set_ndims(numbertype::Type{<:Number}, ndims)
   return numbertype
 end
-
-"""
-`set_indstype` should be overloaded for
-types with structured dimensions,
-like `OffsetArrays` or named indices
-(such as ITensors).
-"""
-function set_indstype(arraytype::Type{<:AbstractArray}, dims::Tuple)
-  return set_ndims(arraytype, length(dims))
-end

NDTensors/src/abstractarray/similar.jl

@@ -1,4 +1,5 @@
-using .TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype
+using Base: DimOrInd, Dims, OneTo
+using .TypeParameterAccessors: IsWrappedArray, unwrap_array_type, set_eltype, similartype
 
 ## Custom `NDTensors.similar` implementation.
 ## More extensive than `Base.similar`.
@@ -96,58 +97,3 @@ end
 # Use the `size` to determine the dimensions
 # NDTensors.similar
 similar(array::AbstractArray) = NDTensors.similar(typeof(array), size(array))
-
-## similartype
-
-function similartype(arraytype::Type{<:AbstractArray}, eltype::Type, dims::Tuple)
-  return similartype(similartype(arraytype, eltype), dims)
-end
-
-@traitfn function similartype(
-  arraytype::Type{ArrayT}, eltype::Type
-) where {ArrayT; !IsWrappedArray{ArrayT}}
-  return set_eltype(arraytype, eltype)
-end
-
-@traitfn function similartype(
-  arraytype::Type{ArrayT}, dims::Tuple
-) where {ArrayT; !IsWrappedArray{ArrayT}}
-  return set_indstype(arraytype, dims)
-end
-
-function similartype(arraytype::Type{<:AbstractArray}, dims::DimOrInd...)
-  return similartype(arraytype, dims)
-end
-
-function similartype(arraytype::Type{<:AbstractArray})
-  return similartype(arraytype, eltype(arraytype))
-end
-
-## Wrapped arrays
-@traitfn function similartype(
-  arraytype::Type{ArrayT}, eltype::Type
-) where {ArrayT; IsWrappedArray{ArrayT}}
-  return similartype(unwrap_array_type(arraytype), eltype)
-end
-
-@traitfn function similartype(
-  arraytype::Type{ArrayT}, dims::Tuple
-) where {ArrayT; IsWrappedArray{ArrayT}}
-  return similartype(unwrap_array_type(arraytype), dims)
-end
-
-# This is for uniform `Diag` storage which uses
-# a Number as the data type.
-# TODO: Delete this when we change to using a
-# `FillArray` instead. This is a stand-in
-# to make things work with the current design.
-function similartype(numbertype::Type{<:Number})
-  return numbertype
-end
-
-# Instances
-function similartype(array::AbstractArray, eltype::Type, dims...)
-  return similartype(typeof(array), eltype, dims...)
-end
-similartype(array::AbstractArray, eltype::Type) = similartype(typeof(array), eltype)
-similartype(array::AbstractArray, dims...) = similartype(typeof(array), dims...)

NDTensors/src/blocksparse/blockdims.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: TypeParameterAccessors
+
 """
     BlockDim
 
@@ -18,7 +20,9 @@ const BlockDims{N} = NTuple{N,BlockDim}
 
 Base.ndims(ds::Type{<:BlockDims{N}}) where {N} = N
 
-similartype(::Type{<:BlockDims}, ::Type{Val{N}}) where {N} = BlockDims{N}
+function TypeParameterAccessors.similartype(::Type{<:BlockDims}, ::Type{Val{N}}) where {N}
+  return BlockDims{N}
+end
 
 Base.copy(ds::BlockDims) = ds
 

NDTensors/src/blocksparse/blocksparsetensor.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: similartype
+
 #
 # BlockSparseTensor (Tensor using BlockSparse storage)
 #

NDTensors/src/blocksparse/diagblocksparse.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: similartype
+
 export DiagBlockSparse, DiagBlockSparseTensor
 
 # DiagBlockSparse can have either Vector storage, in which case

NDTensors/src/blocksparse/similar.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: similartype
+
 # NDTensors.similar
 function similar(storagetype::Type{<:BlockSparse}, blockoffsets::BlockOffsets, dims::Tuple)
   data = similar(datatype(storagetype), nnz(blockoffsets, dims))

NDTensors/src/diag/similar.jl

@@ -1,11 +1,13 @@
+using NDTensors.TypeParameterAccessors: TypeParameterAccessors
+
 # NDTensors.similar
 function similar(storagetype::Type{<:Diag}, dims::Dims)
   return setdata(storagetype, similar(datatype(storagetype), mindim(dims)))
 end
 
 # TODO: Redesign UniformDiag to make it handled better
 # by generic code.
-function similartype(storagetype::Type{<:UniformDiag}, eltype::Type)
+function TypeParameterAccessors.similartype(storagetype::Type{<:UniformDiag}, eltype::Type)
   # This will also set the `datatype`.
   return set_eltype(storagetype, eltype)
 end

NDTensors/src/dims.jl

@@ -1,4 +1,5 @@
 using .DiagonalArrays: DiagonalArrays
+using .TypeParameterAccessors: TypeParameterAccessors
 
 export dense, dims, dim, mindim, diaglength
 
@@ -52,7 +53,7 @@ dim_to_stride(ds, k::Int) = dim_to_strides(ds)[k]
 # code (it helps to construct a Tuple(::NTuple{N,Int}) where the
 # only known thing for dispatch is a concrete type such
 # as Dims{4})
-similartype(::Type{<:Dims}, ::Type{Val{N}}) where {N} = Dims{N}
+TypeParameterAccessors.similartype(::Type{<:Dims}, ::Type{Val{N}}) where {N} = Dims{N}
 
 # This is to help with ITensor compatibility
 dim(i::Int) = i

NDTensors/src/empty/empty.jl

@@ -1,22 +1,25 @@
+using .TypeParameterAccessors: TypeParameterAccessors, set_eltype, similartype
 
 #
 # Represents a tensor order that could be set to any order.
 #
 
 struct EmptyOrder end
 
-function similartype(StoreT::Type{<:TensorStorage{EmptyNumber}}, ElT::Type)
+function TypeParameterAccessors.similartype(
+  StoreT::Type{<:TensorStorage{EmptyNumber}}, ElT::Type
+)
   return set_eltype(StoreT, ElT)
 end
 
-function similartype(
+function TypeParameterAccessors.similartype(
   StoreT::Type{<:TensorStorage{EmptyNumber}}, DataT::Type{<:AbstractArray}
 )
   return set_datatype(StoreT, DataT)
 end
 
 ## TODO fix this similartype to use set eltype for BlockSparse
-function similartype(
+function TypeParameterAccessors.similartype(
   ::Type{StoreT}, ::Type{ElT}
 ) where {StoreT<:BlockSparse{EmptyNumber},ElT}
   return BlockSparse{ElT,similartype(datatype(StoreT), ElT),ndims(StoreT)}

NDTensors/src/lib/TypeParameterAccessors/src/TypeParameterAccessors.jl

@@ -13,6 +13,7 @@ include("set_parameters.jl")
 include("specify_parameters.jl")
 include("default_parameters.jl")
 include("base/abstractarray.jl")
+include("base/similartype.jl")
 include("base/array.jl")
 include("base/linearalgebra.jl")
 include("base/stridedviews.jl")

NDTensors/src/lib/TypeParameterAccessors/src/base/similartype.jl

@@ -0,0 +1,62 @@
+"""
+`set_indstype` should be overloaded for
+types with structured dimensions,
+like `OffsetArrays` or named indices
+(such as ITensors).
+"""
+function set_indstype(arraytype::Type{<:AbstractArray}, dims::Tuple)
+  return set_ndims(arraytype, length(dims))
+end
+
+function similartype(arraytype::Type{<:AbstractArray}, eltype::Type, dims::Tuple)
+  return similartype(similartype(arraytype, eltype), dims)
+end
+
+@traitfn function similartype(
+  arraytype::Type{ArrayT}, eltype::Type
+) where {ArrayT; !IsWrappedArray{ArrayT}}
+  return set_eltype(arraytype, eltype)
+end
+
+@traitfn function similartype(
+  arraytype::Type{ArrayT}, dims::Tuple
+) where {ArrayT; !IsWrappedArray{ArrayT}}
+  return set_indstype(arraytype, dims)
+end
+
+function similartype(arraytype::Type{<:AbstractArray}, dims::Base.DimOrInd...)
+  return similartype(arraytype, dims)
+end
+
+function similartype(arraytype::Type{<:AbstractArray})
+  return similartype(arraytype, eltype(arraytype))
+end
+
+## Wrapped arrays
+@traitfn function similartype(
+  arraytype::Type{ArrayT}, eltype::Type
+) where {ArrayT; IsWrappedArray{ArrayT}}
+  return similartype(unwrap_array_type(arraytype), eltype)
+end
+
+@traitfn function similartype(
+  arraytype::Type{ArrayT}, dims::Tuple
+) where {ArrayT; IsWrappedArray{ArrayT}}
+  return similartype(unwrap_array_type(arraytype), dims)
+end
+
+# This is for uniform `Diag` storage which uses
+# a Number as the data type.
+# TODO: Delete this when we change to using a
+# `FillArray` instead. This is a stand-in
+# to make things work with the current design.
+function similartype(numbertype::Type{<:Number})
+  return numbertype
+end
+
+# Instances
+function similartype(array::AbstractArray, eltype::Type, dims...)
+  return similartype(typeof(array), eltype, dims...)
+end
+similartype(array::AbstractArray, eltype::Type) = similartype(typeof(array), eltype)
+similartype(array::AbstractArray, dims...) = similartype(typeof(array), dims...)

NDTensors/src/lib/TypeParameterAccessors/test/runtests.jl

@@ -5,5 +5,6 @@ using Test: @testset
   include("test_defaults.jl")
   include("test_custom_types.jl")
   include("test_wrappers.jl")
+  include("test_similartype.jl")
 end
 end

NDTensors/src/lib/TypeParameterAccessors/test/test_similartype.jl

@@ -0,0 +1,15 @@
+@eval module $(gensym())
+using Test: @test, @test_broken, @testset
+using LinearAlgebra: Adjoint
+using NDTensors.TypeParameterAccessors: similartype
+@testset "TypeParameterAccessors similartype" begin
+  @test similartype(Array, Float64, (2, 2)) == Matrix{Float64}
+  # TODO: Is this a good definition? Probably it should be left unspecified.
+  @test similartype(Array) == Array{Any}
+  @test similartype(Array, Float64) == Array{Float64}
+  @test similartype(Array, (2, 2)) == Matrix
+  @test similartype(Adjoint{Float32,Matrix{Float32}}, Float64, (2, 2, 2)) ==
+    Array{Float64,3}
+  @test similartype(Adjoint{Float32,Matrix{Float32}}, Float64) == Matrix{Float64}
+end
+end

NDTensors/src/tensor/set_types.jl

@@ -17,7 +17,7 @@ end
 
 # TODO: Modify the `storagetype` according to `inds`, such as the dimensions?
 # TODO: Make a version that accepts `indstype::Type`?
-function set_indstype(tensortype::Type{<:Tensor}, inds::Tuple)
+function TypeParameterAccessors.set_indstype(tensortype::Type{<:Tensor}, inds::Tuple)
   return Tensor{eltype(tensortype),length(inds),storagetype(tensortype),typeof(inds)}
 end
 

NDTensors/src/tensor/similar.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: TypeParameterAccessors, set_indstype, similartype
+
 # NDTensors.similar
 similar(tensor::Tensor) = setstorage(tensor, similar(storage(tensor)))
 
@@ -56,11 +58,11 @@ function Base.similar(tensor::Tensor, eltype::Type, dims::Dims)
   return NDTensors.similar(tensor, eltype, dims)
 end
 
-function similartype(tensortype::Type{<:Tensor}, eltype::Type)
+function TypeParameterAccessors.similartype(tensortype::Type{<:Tensor}, eltype::Type)
   return set_storagetype(tensortype, similartype(storagetype(tensortype), eltype))
 end
 
-function similartype(tensortype::Type{<:Tensor}, dims::Tuple)
+function TypeParameterAccessors.similartype(tensortype::Type{<:Tensor}, dims::Tuple)
   tensortype_new_inds = set_indstype(tensortype, dims)
   # Need to pass `dims` in case that information is needed to make a storage type,
   # for example `BlockSparse` needs the number of dimensions.

NDTensors/src/tensorstorage/similar.jl

@@ -1,3 +1,5 @@
+using .TypeParameterAccessors: TypeParameterAccessors, set_ndims, similartype
+
 # NDTensors.similar
 similar(storage::TensorStorage) = setdata(storage, NDTensors.similar(data(storage)))
 
@@ -61,14 +63,16 @@ Base.similar(storage::TensorStorage, eltype::Type) = NDTensors.similar(storage,
 ## Base.similar(storage::TensorStorage, dims::Dims...) = NDTensors.similar(storage, dims...)
 ## Base.similar(storage::TensorStorage, dims::DimOrInd...) = NDTensors.similar(storage, dims...)
 
-function similartype(storagetype::Type{<:TensorStorage}, eltype::Type)
+function TypeParameterAccessors.similartype(
+  storagetype::Type{<:TensorStorage}, eltype::Type
+)
   # TODO: Don't convert to an `AbstractVector` with `set_ndims(datatype, 1)`, once we support
   # more general data types.
   # return set_datatype(storagetype, NDTensors.similartype(datatype(storagetype), eltype))
   return set_datatype(storagetype, set_ndims(similartype(datatype(storagetype), eltype), 1))
 end
 
-function similartype(storagetype::Type{<:TensorStorage}, dims::Tuple)
+function TypeParameterAccessors.similartype(storagetype::Type{<:TensorStorage}, dims::Tuple)
   # TODO: In the future, set the dimensions of the data type based on `dims`, once
   # more general data types beyond `AbstractVector` are supported.
   # `similartype` unwraps any wrapped data.

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensors"
 uuid = "9136182c-28ba-11e9-034c-db9fb085ebd5"
 authors = ["Matthew Fishman <[email protected]>", "Miles Stoudenmire <[email protected]>"]
-version = "0.7.1"
+version = "0.7.3"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"