Mutating functions now return the first argument before any additional data.

Author: Jack Dunham

src/solvers/applyexp.jl

@@ -29,7 +29,9 @@ end
 )
   prob = problem(region_iter)
 
-  iszero(abs(exponent_step)) && return local_state
+  if iszero(abs(exponent_step))
+    return region_iter, local_state
+  end
 
   solver_kwargs = region_kwargs(solver, region_iter)
 
@@ -54,7 +56,7 @@ end
 
   prob.current_exponent += exponent_step
 
-  return local_state
+  return region_iter, local_state
 end
 
 function default_sweep_callback(
@@ -91,7 +93,7 @@ function applyexp(
   ]
   sweep_iter = SweepIterator(init_prob, kws_array)
 
-  converged_prob = sweep_solve!(sweep_callback, sweep_iter)
+  converged_prob = problem(sweep_solve!(sweep_callback, sweep_iter))
 
   return state(converged_prob)
 end

src/solvers/eigsolve.jl

@@ -37,7 +37,7 @@ end
   if outputlevel >= 2
     @printf("  Region %s: energy = %.12f\n", current_region(region_iter), eigenvalue(prob))
   end
-  return local_state
+  return region_iter, local_state
 end
 
 function default_sweep_callback(
@@ -64,7 +64,7 @@ function eigsolve(operator, init_state; nsweeps, nsites=1, outputlevel=0, sweep_
     state=align_indices(init_state), operator=ProjTTN(align_indices(operator))
   )
   sweep_iter = SweepIterator(init_prob, nsweeps; nsites, outputlevel, sweep_kwargs...)
-  prob = sweep_solve!(sweep_iter)
+  prob = problem(sweep_solve!(sweep_iter))
   return eigenvalue(prob), state(prob)
 end
 

src/solvers/extract.jl

@@ -7,10 +7,10 @@ function extract!(region_iter::RegionIterator; subspace_algorithm="nothing")
 
   prob.state = psi
 
-  local_state = subspace_expand!(region_iter, local_state; subspace_algorithm)
+  _, local_state = subspace_expand!(region_iter, local_state; subspace_algorithm)
   shifted_operator = position(operator(prob), state(prob), region)
 
   prob.operator = shifted_operator
 
-  return local_state
+  return region_iter, local_state
 end

src/solvers/fitting.jl

@@ -41,7 +41,7 @@ function extract!(region_iter::RegionIterator{<:FittingProblem})
   prob.state = tn
   prob.gauge_region = region
 
-  return local_tensor
+  return region_iter, local_tensor
 end
 
 @define_default_kwargs function update!(
@@ -58,7 +58,7 @@ end
     @printf("  Region %s: squared overlap = %.12f\n", region, overlap(F))
   end
 
-  return local_tensor
+  return region_iter, local_tensor
 end
 
 function region_plan(F::FittingProblem; nsites, sweep_kwargs...)
@@ -90,7 +90,7 @@ function fit_tensornetwork(
   kwargs_array = [(; sweep_kwargs..., extra_sweep_kwargs..., sweep) for sweep in 1:nsweeps]
 
   sweep_iter = SweepIterator(init_prob, kwargs_array)
-  converged_prob = sweep_solve!(sweep_iter)
+  converged_prob = problem(sweep_solve!(sweep_iter))
 
   return rename_vertices(inv_vertex_map(overlap_network), ket(converged_prob))
 end
@@ -109,7 +109,11 @@ end
 #end
 
 function ITensors.apply(
-  A::ITensorNetwork, x::ITensorNetwork; maxdim=typemax(Int), cutoff=0.0, sweep_kwargs...
+  A::AbstractITensorNetwork,
+  x::AbstractITensorNetwork;
+  maxdim=typemax(Int),
+  cutoff=0.0,
+  sweep_kwargs...,
 )
   init_state = ITensorNetwork(v -> inds -> delta(inds), siteinds(x); link_space=maxdim)
   overlap_network = inner_network(x, A, init_state)

src/solvers/insert.jl

@@ -28,5 +28,5 @@ function insert!(region_iter, local_tensor; normalize=false, set_orthogonal_regi
 
   prob.state = psi
 
-  return prob
+  return region_iter
 end

src/solvers/iterators.jl

@@ -100,8 +100,10 @@ function increment!(region_iter::RegionIterator)
 end
 
 function compute!(iter::RegionIterator)
-  local_state = @with_defaults extract!(iter; region_kwargs(extract!, iter)...)
-  local_state = @with_defaults update!(iter, local_state; region_kwargs(update!, iter)...)
+  _, local_state = @with_defaults extract!(iter; region_kwargs(extract!, iter)...)
+  _, local_state = @with_defaults update!(
+    iter, local_state; region_kwargs(update!, iter)...
+  )
   @with_defaults insert!(iter, local_state; region_kwargs(insert!, iter)...)
 
   return iter

src/solvers/subspace/densitymatrix.jl

@@ -10,23 +10,23 @@ using Printf: @printf
   psi = copy(state(prob))
 
   prev_vertex_set = setdiff(pos(operator(prob)), region)
-  (length(prev_vertex_set) != 1) && return local_state
+  (length(prev_vertex_set) != 1) && return region_iter, local_state
   prev_vertex = only(prev_vertex_set)
   A = psi[prev_vertex]
 
   next_vertices = filter(v -> (hascommoninds(psi[v], A)), region)
-  isempty(next_vertices) && return local_state
+  isempty(next_vertices) && return region_iter, local_state
   next_vertex = only(next_vertices)
   C = psi[next_vertex]
 
   a = commonind(A, C)
-  isnothing(a) && return local_state
+  isnothing(a) && return region_iter, local_state
   basis_size = prod(dim.(uniqueinds(A, C)))
 
   expanded_maxdim = compute_expansion(
     dim(a), basis_size; region_kwargs(compute_expansion, region_iter)...
   )
-  expanded_maxdim <= 0 && return local_state
+  expanded_maxdim <= 0 && return region_iter, local_state
 
   envs = environments(operator(prob))
   H = operator(operator(prob))
@@ -50,7 +50,7 @@ using Printf: @printf
   end
   if norm(dag(U) * A) > 1E-10
     @printf("Warning: |U*A| = %.3E in subspace expansion\n", norm(dag(U) * A))
-    return local_state
+    return region_iter, local_state
   end
 
   Ax, ax = directsum(A => a, U => commonind(U, D))
@@ -61,5 +61,5 @@ using Printf: @printf
 
   prob.state = psi
 
-  return local_state
+  return region_iter, local_state
 end

src/solvers/subspace/subspace.jl

@@ -7,14 +7,14 @@ using NDTensors.BackendSelection: Backend, @Backend_str
   backend = Backend(subspace_algorithm)
 
   if backend isa Backend"nothing"
-    return local_state
+    return region_iter, local_state
   end
 
-  local_state = @with_defaults subspace_expand!(
+  _, local_state = @with_defaults subspace_expand!(
     backend, region_iter, local_state; region_kwargs(subspace_expand!, region_iter)...
   )
 
-  return local_state
+  return region_iter, local_state
 end
 
 function subspace_expand!(backend, region_iterator, local_state; kwargs...)