julia> M = {cor(rand(4,4)) for i=1:2}
2-element Array{Any,1}:
4x4 Array{Float64,2}:
1.0 -0.227554 0.507924 -0.800516
-0.227554 1.0 0.220113 0.75924
0.507924 0.220113 1.0 -0.272765
-0.800516 0.75924 -0.272765 1.0
4x4 Array{Float64,2}:
1.0 -0.65399 -0.619397 -0.132602
-0.65399 1.0 -0.188752 0.818691
-0.619397 -0.188752 1.0 -0.680177
-0.132602 0.818691 -0.680177 1.0
julia> P=pmap(eig,M)
2-element Array{Any,1}:
([-2.08888e-16,0.340329,1.3362,2.32347],
4x4 Array{Float64,2}:
0.445323 0.628389 -0.283962 -0.571121
-0.485061 0.445037 -0.623672 0.421533
0.08456 -0.637878 -0.711606 -0.282095
0.747832 -0.0134082 -0.15497 0.645409)
([1.77636e-15,0.0237017,1.77733,2.19897],
4x4 Array{Float64,2}:
0.670874 -0.0224424 0.702664 -0.235982
0.513147 0.521253 -0.261832 0.629618
0.534381 -0.427716 -0.640692 -0.347864
0.0323244 -0.73814 0.164988 0.653364)
julia> P[1]
([-2.08888e-16,0.340329,1.3362,2.32347],
4x4 Array{Float64,2}:
0.445323 0.628389 -0.283962 -0.571121
-0.485061 0.445037 -0.623672 0.421533
0.08456 -0.637878 -0.711606 -0.282095
0.747832 -0.0134082 -0.15497 0.645409)
julia> P[2]
([1.77636e-15,0.0237017,1.77733,2.19897],
4x4 Array{Float64,2}:
0.670874 -0.0224424 0.702664 -0.235982
0.513147 0.521253 -0.261832 0.629618
0.534381 -0.427716 -0.640692 -0.347864
0.0323244 -0.73814 0.164988 0.653364)
How can you separate results, eigenvalues and eigenvectors?
The first and subsequent lines array P [1] and P [2]
