Use StableRNGs.jl to make tests more consistent (#80)

* Use StableRNGs to make tests more consistent

* Bump to v0.4.2

Project.toml

@@ -1,7 +1,7 @@
 name = "ITensorTDVP"
 uuid = "25707e16-a4db-4a07-99d9-4d67b7af0342"
 authors = ["Matthew Fishman <[email protected]> and contributors"]
-version = "0.4.1"
+version = "0.4.2"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"

test/test_contract.jl

@@ -2,6 +2,7 @@
 using ITensors: ITensors, dag, delta, denseblocks
 using ITensors: MPO, OpSum, apply, contract, inner, randomMPS, siteinds, truncate!
 using ITensorTDVP: ITensorTDVP
+using StableRNGs: StableRNG
 using Test: @test, @test_throws, @testset
 @testset "Contract MPO (eltype=$elt, conserve_qns=$conserve_qns)" for elt in (
     Float32, Float64, Complex{Float32}, Complex{Float64}
@@ -10,7 +11,8 @@ using Test: @test, @test_throws, @testset
 
   N = 20
   s = siteinds("S=1/2", N; conserve_qns)
-  psi = randomMPS(elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=8)
+  rng = StableRNG(1234)
+  psi = randomMPS(rng, elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=8)
   os = OpSum()
   for j in 1:(N - 1)
     os += 0.5, "S+", j, "S-", j + 1

test/test_dmrg.jl

@@ -1,6 +1,7 @@
 @eval module $(gensym())
 using ITensors: ITensors, MPO, OpSum, inner, randomMPS, siteinds
 using ITensorTDVP: ITensorTDVP
+using StableRNGs: StableRNG
 using Test: @test, @test_throws, @testset
 @testset "DMRG (eltype=$elt, nsite=$nsite, conserve_qns=$conserve_qns)" for elt in (
     Float32, Float64, Complex{Float32}, Complex{Float64}
@@ -18,7 +19,8 @@ using Test: @test, @test_throws, @testset
     os += "Sz", j, "Sz", j + 1
   end
   H = MPO(elt, os, s)
-  psi = randomMPS(elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=20)
+  rng = StableRNG(1234)
+  psi = randomMPS(rng, elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=20)
   nsweeps = 10
   maxdim = [10, 20, 40, 100]
   @test_throws ErrorException ITensorTDVP.dmrg(H, psi; maxdim, cutoff, nsite)

test/test_dmrg_x.jl

@@ -2,6 +2,7 @@
 using ITensors: ITensors, MPO, MPS, OpSum, ProjMPO, inner, siteinds
 using ITensorTDVP: dmrg_x
 using Random: Random
+using StableRNGs: StableRNG
 using Test: @test, @test_throws, @testset
 @testset "DMRG-X (eltype=$elt, conserve_qns=$conserve_qns)" for elt in (
     Float32, Float64, Complex{Float32}, Complex{Float64}
@@ -27,9 +28,10 @@ using Test: @test, @test_throws, @testset
   Random.seed!(12)
   W = 12
   # Random fields h ∈ [-W, W]
-  h = W * (2 * rand(real(elt), n) .- 1)
+  rng = StableRNG(1234)
+  h = W * (2 * rand(rng, real(elt), n) .- 1)
   H = MPO(elt, heisenberg(n; h), s)
-  initstate = rand(["↑", "↓"], n)
+  initstate = rand(rng, ["↑", "↓"], n)
   ψ = MPS(elt, s, initstate)
   @test_throws ErrorException dmrg_x(H, ψ; nsite=2, maxdim=20, cutoff=1e-10)
   dmrg_x_kwargs = (; nsweeps=20, normalize=true, maxdim=20, cutoff=1e-10, outputlevel=0)

test/test_linsolve.jl

@@ -1,8 +1,10 @@
 @eval module $(gensym())
-using ITensors: ITensors, MPO, OpSum, apply, randomMPS, siteinds
+using ITensors: scalartype
+using ITensors.ITensorMPS: MPO, OpSum, apply, randomMPS, siteinds
 using ITensorTDVP: ITensorTDVP, dmrg
 using KrylovKit: linsolve
 using LinearAlgebra: norm
+using StableRNGs: StableRNG
 using Test: @test, @test_throws, @testset
 using Random: Random
 @testset "linsolve (eltype=$elt, conserve_qns=$conserve_qns)" for elt in (
@@ -18,25 +20,26 @@ using Random: Random
     os += 0.5, "S-", j, "S+", j + 1
     os += "Sz", j, "Sz", j + 1
   end
-  H = ITensors.convert_leaf_eltype(elt, MPO(os, s))
+  H = MPO(elt, os, s)
   state = [isodd(n) ? "Up" : "Dn" for n in 1:N]
-  Random.seed!(1234)
-  x_c = randomMPS(elt, s, state; linkdims=2)
+  rng = StableRNG(1234)
+  x_c = randomMPS(rng, elt, s, state; linkdims=2)
   e, x_c = dmrg(H, x_c; nsweeps=10, cutoff=1e-6, maxdim=20, outputlevel=0)
-  @test ITensors.scalartype(x_c) == elt
+  @test scalartype(x_c) == elt
   # Compute `b = H * x_c`
   b = apply(H, x_c; cutoff=1e-8)
-  @test ITensors.scalartype(b) == elt
+  @test scalartype(b) == elt
   # Starting guess
-  x0 = x_c + elt(0.05) * randomMPS(elt, s, state; linkdims=2)
-  @test ITensors.scalartype(x0) == elt
+  rng = StableRNG(1234)
+  x0 = x_c + elt(0.05) * randomMPS(rng, elt, s, state; linkdims=2)
+  @test scalartype(x0) == elt
   nsweeps = 10
   cutoff = 1e-5
   maxdim = 20
   updater_kwargs = (; tol=1e-4, maxiter=20, krylovdim=30, ishermitian=true)
   @test_throws ErrorException linsolve(H, b, x0; cutoff, maxdim, updater_kwargs)
   x = linsolve(H, b, x0; nsweeps, cutoff, maxdim, updater_kwargs)
-  @test ITensors.scalartype(x) == elt
+  @test scalartype(x) == elt
   @test norm(x - x_c) < 1e-2
 end
 end

test/test_tdvp.jl

@@ -20,6 +20,7 @@ using ITensorTDVP: ITensorTDVP, tdvp
 using KrylovKit: exponentiate
 using LinearAlgebra: norm
 using Observers: observer
+using StableRNGs: StableRNG
 using Test: @test, @test_throws, @testset
 const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
 @testset "Basic TDVP (eltype=$elt)" for elt in elts
@@ -33,7 +34,8 @@ const elts = (Float32, Float64, Complex{Float32}, Complex{Float64})
     os += "Sz", j, "Sz", j + 1
   end
   H = MPO(elt, os, s)
-  ψ0 = randomMPS(elt, s; linkdims=10)
+  rng = StableRNG(1234)
+  ψ0 = randomMPS(rng, elt, s; linkdims=10)
   time_step = elt(0.1) * im
   # Time evolve forward:
   ψ1 = tdvp(H, -time_step, ψ0; cutoff, nsite=1)
@@ -71,15 +73,16 @@ end
   H1 = MPO(elt, os1, s)
   H2 = MPO(elt, os2, s)
   Hs = [H1, H2]
-  ψ0 = randomMPS(elt, s; linkdims=10)
+  rng = StableRNG(1234)
+  ψ0 = randomMPS(rng, elt, s; linkdims=10)
   ψ1 = tdvp(Hs, -elt(0.1) * im, ψ0; cutoff, nsite=1)
   @test ITensors.scalartype(ψ1) === complex(elt)
   @test norm(ψ1) ≈ 1 rtol = √eps(real(elt))
   ## Should lose fidelity:
   #@test abs(inner(ψ0,ψ1)) < 0.9
   # Average energy should be conserved:
   @test real(sum(H -> inner(ψ1', H, ψ1), Hs)) ≈ sum(H -> inner(ψ0', H, ψ0), Hs) rtol =
-    2 * √eps(real(elt))
+    4 * √eps(real(elt))
   # Time evolve backwards:
   ψ2 = tdvp(Hs, elt(0.1) * im, ψ1; cutoff)
   @test ITensors.scalartype(ψ2) === complex(elt)
@@ -98,7 +101,8 @@ end
     os += "Sz", j, "Sz", j + 1
   end
   H = MPO(os, s)
-  ψ0 = randomMPS(s; linkdims=10)
+  rng = StableRNG(1234)
+  ψ0 = randomMPS(rng, s; linkdims=10)
   function updater(PH, state0; internal_kwargs, kwargs...)
     return exponentiate(PH, internal_kwargs.time_step, state0; kwargs...)
   end
@@ -252,7 +256,8 @@ end
     os += "Sz", j, "Sz", j + 1
   end
   H = MPO(os, s)
-  state = randomMPS(s; linkdims=2)
+  rng = StableRNG(1234)
+  state = randomMPS(rng, s; linkdims=2)
   state2 = deepcopy(state)
   trange = 0.0:tau:ttotal
   for (step, t) in enumerate(trange)

test/test_tdvp_time_dependent.jl

@@ -1,8 +1,9 @@
 @eval module $(gensym())
-using ITensors: ITensors, Index, QN, contract, randomITensor
+using ITensors: ITensors, Index, QN, contract, randomITensor, scalartype
 using ITensors.ITensorMPS: MPO, MPS, ProjMPO, ProjMPOSum, randomMPS, position!, siteinds
 using ITensorTDVP: ITensorTDVP, TimeDependentSum, tdvp
 using LinearAlgebra: norm
+using StableRNGs: StableRNG
 using Test: @test, @test_skip, @testset
 include(joinpath(pkgdir(ITensorTDVP), "examples", "03_models.jl"))
 include(joinpath(pkgdir(ITensorTDVP), "examples", "03_updaters.jl"))
@@ -17,7 +18,8 @@ include(joinpath(pkgdir(ITensorTDVP), "examples", "03_updaters.jl"))
     H = MPO(elt, s, "I")
     H⃗ = (H, H)
     region = 2:3
-    ψ = randomMPS(elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=2)
+    rng = StableRNG(1234)
+    ψ = randomMPS(rng, elt, s, j -> isodd(j) ? "↑" : "↓"; linkdims=2)
     H⃗ᵣ = ProjMPO.(H⃗)
     map(Hᵣ -> position!(Hᵣ, ψ, first(region)), H⃗ᵣ)
     ∑Hᵣ = ProjMPOSum(collect(H⃗))
@@ -87,10 +89,10 @@ include(joinpath(pkgdir(ITensorTDVP), "examples", "03_updaters.jl"))
       abstol=tol,
     )
 
-    @test ITensors.scalartype(ψ₀) == complex(elt)
-    @test ITensors.scalartype(ψₜ_ode) == complex(elt)
-    @test ITensors.scalartype(ψₜ_krylov) == complex(elt)
-    @test ITensors.scalartype(ψₜ_full) == complex(elt)
+    @test scalartype(ψ₀) == complex(elt)
+    @test scalartype(ψₜ_ode) == complex(elt)
+    @test scalartype(ψₜ_krylov) == complex(elt)
+    @test scalartype(ψₜ_full) == complex(elt)
     @test norm(ψ₀) ≈ 1
     @test norm(ψₜ_ode) ≈ 1
     @test norm(ψₜ_krylov) ≈ 1 rtol = √(eps(real(elt)))