diff --git a/lib/DataDrivenDMD/test/linear_autonomous.jl b/lib/DataDrivenDMD/test/linear_autonomous.jl
index 8bfc0c71..fe470d8f 100644
--- a/lib/DataDrivenDMD/test/linear_autonomous.jl
+++ b/lib/DataDrivenDMD/test/linear_autonomous.jl
@@ -108,8 +108,8 @@ end
     sol_ = solve(prob, Tsit5(), saveat = 0.01)
 
     # True Rank is 3
-    X = Q * sol_[:, :] + 1.0e-3 * randn(rng, 20, 1001)
-    DX = Q * sol_(sol_.t, Val{1})[:, :] + 1.0e-3 * randn(rng, 20, 1001)
+    X = Q * Array(sol_) + 1.0e-3 * randn(rng, 20, 1001)
+    DX = Q * Array(sol_(sol_.t, Val{1})) + 1.0e-3 * randn(rng, 20, 1001)
     ddprob = ContinuousDataDrivenProblem(X, sol_.t, DX = DX)
 
     for alg in [TOTALDMD(3, DMDPINV()); TOTALDMD(0.01, DMDSVD(3))]
diff --git a/lib/DataDrivenSparse/test/cartpole.jl b/lib/DataDrivenSparse/test/cartpole.jl
index 92b33e7a..ff8ef0c6 100644
--- a/lib/DataDrivenSparse/test/cartpole.jl
+++ b/lib/DataDrivenSparse/test/cartpole.jl
@@ -21,7 +21,7 @@ cart_pole_prob = ODEProblem(cart_pole, u0, tspan)
 solution = solve(cart_pole_prob, Tsit5(), saveat = dt)
 
 # Create the differential data
-X = solution[:, :]
+X = Array(solution)
 DX = similar(X)
 for (i, xi) in enumerate(eachcol(X))
     DX[:, i] = cart_pole(xi, [], solution.t[i])
diff --git a/lib/DataDrivenSparse/test/pendulum.jl b/lib/DataDrivenSparse/test/pendulum.jl
index 86f99125..c4ae4040 100644
--- a/lib/DataDrivenSparse/test/pendulum.jl
+++ b/lib/DataDrivenSparse/test/pendulum.jl
@@ -44,7 +44,7 @@ sol = solve(prob, Tsit5(), saveat = dt)
 end
 
 @testset "Noise" begin
-    X = sol[:, :]
+    X = Array(sol)
     t = sol.t
 
     rng = StableRNG(21)