diff --git a/EC.jl b/EC.jl
index 4dbdfc0..de38c14 100644
--- a/EC.jl
+++ b/EC.jl
@@ -94,8 +94,8 @@ resample(n::Int) = rand(1:n, n) |> unique |> sort
 If a list is provided for ref_eval, they are used as reference values for picking the closest eigenvalues at each point.
 If a single number is provided for ref_eval, it is used as a reference for the first point, and the previous eigenvalue is used as the reference for each successive point.
 If precalculated_exact_E is provided, ref_eval is ignored.
-If pseudo_inv_rtol > 0, the GEVP is avoided using Moore-Penrose psuedoinverse, using this value as the relative tolerance for dropping redundant vectors."
-function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo_inv_rtol=1e-6, verbose=true, tol=1e-5, precalculated_exact_E=nothing)
+If pseudo_inv_tol > 0, the GEVP is avoided using Moore-Penrose psuedoinverse, using this value as the relative tolerance for dropping redundant vectors."
+function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo_inv_tol=1e-6, verbose=true, tol=1e-5, precalculated_exact_E=nothing)
     @assert EC.trained "EC model must be trained using train() before extrapolation"
 
     for c in c_vals
@@ -122,13 +122,13 @@ function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo
 
         verbose && println("Extrapolating for c = $c")
 
-        evals = get_extrapolated_evals(EC.H0_EC, EC.H1_EC, EC.N_EC, c, pseudo_inv_rtol)
+        evals = get_extrapolated_evals(EC.H0_EC, EC.H1_EC, EC.N_EC, c, pseudo_inv_tol)
         push!(EC.extrapolated_E, nearest(evals, current_E))
 
         if EC.ensemble_size > 0
             E_ensemble = zeros(ComplexF64, EC.ensemble_size)
             for i in 1:EC.ensemble_size
-                evals = get_extrapolated_evals(EC.H0_EC_ensemble[i], EC.H1_EC_ensemble[i], EC.N_EC_ensemble[i], c, pseudo_inv_rtol)
+                evals = get_extrapolated_evals(EC.H0_EC_ensemble[i], EC.H1_EC_ensemble[i], EC.N_EC_ensemble[i], c, pseudo_inv_tol)
                 E_ensemble[i] = nearest(evals, current_E)
             end
             re_CI = std(real.(E_ensemble))
@@ -139,10 +139,10 @@ function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo
 end
 
 "Solve the GEVP with or without Moore-Penrose psuedoinverse"
-function get_extrapolated_evals(H0_EC, H1_EC, N_EC, c, pseudo_inv_rtol)
+function get_extrapolated_evals(H0_EC, H1_EC, N_EC, c, pseudo_inv_tol)
     H_EC = H0_EC + c .* H1_EC
-    if pseudo_inv_rtol > 0
-        inv_N_EC = pinv(N_EC; rtol=pseudo_inv_rtol)
+    if pseudo_inv_tol > 0
+        inv_N_EC = pinv(N_EC; atol=pseudo_inv_tol)
         H_EC = inv_N_EC * H_EC
         return eigvals(H_EC)
     else