update to alessandro's branch

src/juobs_linalg.jl

@@ -120,7 +120,6 @@ function uwgevp_tot(mat_list::Vector{Matrix}, tnot::Int64; iter::Int64 = 30, eve
     n = length(mat_list)
     evals = Array{Array{uwreal}}(undef, 0 )
     if !evec
-        println(tnot)
         c_inv = invert(mat_list[tnot])
         for i =1:n
             aux_evals = uwgevp(mat_list[i], c_inv, iter = iter)
@@ -136,18 +135,26 @@ function uwgevp_tot(mat_list::Vector{Matrix}, tnot::Int64; iter::Int64 = 30, eve
             ptilda = norm_evec(aux_evec, mat_list[i])
             m = uwdot(mat_list[i], ptilda)
             push!(evecs, m)
-            println( "\n t is ", i+3, " tnot is ", i)            
-            #if  2*tnot < i && i<n-5
-            #    tnot+=5
-            #end
         end
         return evals, evecs
     end
 end
+
+function uwgevp_tot(mat_list::Vector{Matrix}; iter::Int64=30, delta_t::Int64=3)
+    n = length(mat_list) - delta_t
+    evecs = Array{Matrix}(undef, 0)
+    for i = 2:n
+        c_inv = invert(mat_list[i])
+        usless, temp_evec = uwgevp(mat_list[i+delta_t], c_inv, evec=true, iter=iter)
+        push!(evecs, uwdot(mat_list[i], norm_evec(temp_evec, mat_list[i])))
+    end
+    return evecs
+end
+
 """
 uwgevp(c_t:: Matrix{uwreal}, c_tnot_inv::Matrix{uwreal}; iter = 30, evec = false)
 
-Given two matrices of uwreal C(t) and C(t0), this method solves the generalized eigenvalue problem
+Given two matrices of uwreal C(t) and C(t0)^-1, this method solves the generalized eigenvalue problem
 C(t)V = C(t_0)D V, where V is the eigenvector matrix and D is the diagonal matrix of eigenvalues.
 
 If evec = true also the eigenvectors are returned as columns of the orthogonal matrix u.