jld -> jld2

Author: mohamed82008

test/REQUIRE

@@ -1 +1 @@
-JLD
+FileIO

test/onetoall.jld

@@ -1,14 +1,14 @@
 using Compat, Compat.Test, Compat.LinearAlgebra
 using Compat.SparseArrays, Compat.DelimitedFiles, Compat.Random
-using IterativeSolvers, JLD, AlgebraicMultigrid
+using IterativeSolvers, FileIO, AlgebraicMultigrid
 import AlgebraicMultigrid: V, coarse_solver, Pinv, Classical
 
 include("sa_tests.jl")
 
 @testset "AlgebraicMultigrid Tests" begin
 
-graph = load("test.jld")["G"]
-ref_S = load("ref_S_test.jld")["G"]
+graph = load("test.jld2")["G"]
+ref_S = load("ref_S_test.jld2")["G"]
 ref_split = readdlm("ref_split_test.txt")
 
 @testset "Strength of connection" begin
@@ -37,7 +37,7 @@ srand(0)
 S = sprand(10,10,0.1); S = S + S'
 @test split_nodes(RS(), S) ==  [0, 1, 1, 0, 0, 0, 0, 0, 1, 1]
 
-a = load("thing.jld")["G"]
+a = load("thing.jld2")["G"]
 S, T = AlgebraicMultigrid.strength_of_connection(Classical(0.25), a)
 @test split_nodes(RS(), S) == [0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0,
 0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0,
@@ -60,7 +60,7 @@ P, R = AlgebraicMultigrid.direct_interpolation(A, copy(A), splitting)
               0.0  1.0  0.0
               0.0  0.5  0.5
               0.0  0.0  1.0 ]
-A = load("thing.jld")["G"]
+A = load("thing.jld2")["G"]
 ml = ruge_stuben(A)
 @test size(ml.levels[2].A, 1) == 19
 end
@@ -85,7 +85,7 @@ end
 @test size(ml.final_A, 1) == 7
 @test nnz(ml.final_A) == 19
 
-A = load("randlap.jld")["G"]
+A = load("randlap.jld2")["G"]
 ml = ruge_stuben(A)
 @test length(ml) == 3
 s = [100, 17]
@@ -127,7 +127,7 @@ x = solve(ml, A * ones(1000))
 @test sum(abs2, x - ones(1000)) < 1e-8
 
 
-A = load("randlap.jld")["G"]
+A = load("randlap.jld2")["G"]
 
 ml = ruge_stuben(A, presmoother = fsmoother,
                     postsmoother = fsmoother)
@@ -141,7 +141,7 @@ x = solve(ml, A * ones(100))
 end
 
 @testset "Preconditioning" begin
-A = load("thing.jld")["G"]
+A = load("thing.jld2")["G"]
 n = size(A, 1)
 smoother = GaussSeidel(ForwardSweep())
 ml = ruge_stuben(A, presmoother = smoother,

test/onetoall.jld2

@@ -309,13 +309,13 @@ function test_jacobi_prolongator()
     A = poisson(100)
     T = poisson(100)
     x = smooth_prolongator(JacobiProlongation(4/3), A, T, 1, 1)
-    ref = load("ref_R.jld")["G"]
+    ref = load("ref_R.jld2")["G"]
     @test sum(abs2, x - ref) < 1e-6
 end
 
 # Issue #24
 function nodes_not_agg()
-    A = load("onetoall.jld")["G"]
+    A = load("onetoall.jld2")["G"]
     ml = smoothed_aggregation(A)
     @test size(ml.levels[2].A) == (11,11)
     @test size(ml.final_A) == (2,2)