rtol -> atol
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14
EC.jl
14
EC.jl
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@ -94,8 +94,8 @@ resample(n::Int) = rand(1:n, n) |> unique |> sort
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If a list is provided for ref_eval, they are used as reference values for picking the closest eigenvalues at each point.
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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.
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If precalculated_exact_E is provided, ref_eval is ignored.
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If pseudo_inv_rtol > 0, the GEVP is avoided using Moore-Penrose psuedoinverse, using this value as the relative tolerance for dropping redundant vectors."
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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)
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If pseudo_inv_tol > 0, the GEVP is avoided using Moore-Penrose psuedoinverse, using this value as the relative tolerance for dropping redundant vectors."
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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)
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@assert EC.trained "EC model must be trained using train() before extrapolation"
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for c in c_vals
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@ -122,13 +122,13 @@ function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo
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verbose && println("Extrapolating for c = $c")
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evals = get_extrapolated_evals(EC.H0_EC, EC.H1_EC, EC.N_EC, c, pseudo_inv_rtol)
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evals = get_extrapolated_evals(EC.H0_EC, EC.H1_EC, EC.N_EC, c, pseudo_inv_tol)
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push!(EC.extrapolated_E, nearest(evals, current_E))
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if EC.ensemble_size > 0
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E_ensemble = zeros(ComplexF64, EC.ensemble_size)
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for i in 1:EC.ensemble_size
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evals = get_extrapolated_evals(EC.H0_EC_ensemble[i], EC.H1_EC_ensemble[i], EC.N_EC_ensemble[i], c, pseudo_inv_rtol)
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evals = get_extrapolated_evals(EC.H0_EC_ensemble[i], EC.H1_EC_ensemble[i], EC.N_EC_ensemble[i], c, pseudo_inv_tol)
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E_ensemble[i] = nearest(evals, current_E)
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end
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re_CI = std(real.(E_ensemble))
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@ -139,10 +139,10 @@ function extrapolate!(EC::affine_EC, c_vals; ref_eval=EC.training_E[end], pseudo
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end
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"Solve the GEVP with or without Moore-Penrose psuedoinverse"
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function get_extrapolated_evals(H0_EC, H1_EC, N_EC, c, pseudo_inv_rtol)
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function get_extrapolated_evals(H0_EC, H1_EC, N_EC, c, pseudo_inv_tol)
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H_EC = H0_EC + c .* H1_EC
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if pseudo_inv_rtol > 0
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inv_N_EC = pinv(N_EC; rtol=pseudo_inv_rtol)
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if pseudo_inv_tol > 0
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inv_N_EC = pinv(N_EC; atol=pseudo_inv_tol)
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H_EC = inv_N_EC * H_EC
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return eigvals(H_EC)
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else
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