N = 20 # Number of iterations

tol = Tolerance(1e-3)
tols = 10 .^ range(0, stop=-3, length=N)

trace = SolverTrace(N, CurrentStep(N),
                    ColumnSeparator(),
                    Performance(100), # Could be number of points processed each iteration
                    ColumnSeparator(),
                    tol)
print_header(trace)
for i = 1:N
    # Do work
    # ...
    # Set which tolerance was achieved in this iteration:
    tol.current = tols[i]

    SolverTraces.next!(trace)
end

Performance Tolerance [ 1/20] │ 970.904 kHz │ 1.00×10⁰ (10⁻³) [ 2/20] │ 436.679 kHz │ 6.95×10⁻¹ (10⁻³) [ 4/20] │ 672.164 kHz │ 3.36×10⁻¹ (10⁻³) [ 6/20] │ 892.722 kHz │ 1.62×10⁻¹ (10⁻³) [ 8/20] │ 1.074 MHz │ 7.85×10⁻² (10⁻³) [10/20] │ 1.168 MHz │ 3.79×10⁻² (10⁻³) [12/20] │ 1.207 MHz │ 1.83×10⁻² (10⁻³) [14/20] │ 1.303 MHz │ 8.86×10⁻³ (10⁻³) [16/20] │ 1.431 MHz │ 4.28×10⁻³ (10⁻³) [18/20] │ 1.561 MHz │ 2.07×10⁻³ (10⁻³) [20/20] │ 1.685 MHz │ 1.00×10⁻³ (10⁻³)

f(x) = (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2
x0 = [0.0, 0.0]

max_iter = 100
tol = 1e-8

value = ScalarColumn(Inf, "Value")
tolerance = Tolerance(tol, "|∇|")

trace = SolverTrace(max_iter,
                    CurrentStep(max_iter), ColumnSeparator(), value, tolerance,
                    print_interval=1)
trace_callback = opt_state -> begin
    tolerance.current = opt_state.g_norm
    value.n = opt_state.value
    SolverTraces.next!(trace)
    false
end
options = Optim.Options(iterations=max_iter, g_tol=tol,
                        callback=trace_callback)
print_header(trace)
optimize(f, x0, options)

Value |∇| [ 1/100] │ 9.507e-01 4.58×10⁻² (10⁻⁸) [ 2/100] │ 9.507e-01 2.02×10⁻² (10⁻⁸) [ 3/100] │ 9.507e-01 2.17×10⁻² (10⁻⁸) [ 4/100] │ 9.262e-01 5.24×10⁻² (10⁻⁸) [ 5/100] │ 8.292e-01 4.26×10⁻² (10⁻⁸) [ 6/100] │ 8.292e-01 4.27×10⁻² (10⁻⁸) [ 7/100] │ 8.139e-01 3.11×10⁻² (10⁻⁸) [ 8/100] │ 7.570e-01 3.22×10⁻² (10⁻⁸) [ 9/100] │ 7.383e-01 2.42×10⁻² (10⁻⁸) [ 10/100] │ 6.989e-01 2.43×10⁻² (10⁻⁸) [ 11/100] │ 6.800e-01 2.12×10⁻² (10⁻⁸) [ 12/100] │ 6.475e-01 1.81×10⁻² (10⁻⁸) [ 13/100] │ 6.377e-01 2.15×10⁻² (10⁻⁸) [ 14/100] │ 5.978e-01 1.65×10⁻² (10⁻⁸) [ 15/100] │ 5.978e-01 2.78×10⁻² (10⁻⁸) [ 16/100] │ 5.476e-01 2.43×10⁻² (10⁻⁸) [ 17/100] │ 5.449e-01 1.75×10⁻² (10⁻⁸) [ 18/100] │ 5.091e-01 1.47×10⁻² (10⁻⁸) [ 19/100] │ 5.091e-01 2.93×10⁻² (10⁻⁸) [ 20/100] │ 4.564e-01 2.39×10⁻² (10⁻⁸) [ 21/100] │ 4.564e-01 4.39×10⁻² (10⁻⁸) [ 22/100] │ 3.654e-01 3.91×10⁻² (10⁻⁸) [ 23/100] │ 3.654e-01 3.66×10⁻² (10⁻⁸) [ 24/100] │ 2.994e-01 2.79×10⁻² (10⁻⁸) [ 25/100] │ 2.994e-01 3.62×10⁻² (10⁻⁸) [ 26/100] │ 2.598e-01 2.98×10⁻² (10⁻⁸) [ 27/100] │ 2.266e-01 4.85×10⁻² (10⁻⁸) [ 28/100] │ 1.445e-01 3.58×10⁻² (10⁻⁸) [ 29/100] │ 1.445e-01 2.98×10⁻² (10⁻⁸) [ 30/100] │ 1.445e-01 2.45×10⁻² (10⁻⁸) [ 31/100] │ 9.866e-02 1.91×10⁻² (10⁻⁸) [ 32/100] │ 9.866e-02 2.64×10⁻² (10⁻⁸) [ 33/100] │ 6.483e-02 1.58×10⁻² (10⁻⁸) [ 34/100] │ 6.483e-02 1.84×10⁻² (10⁻⁸) [ 35/100] │ 5.485e-02 6.61×10⁻³ (10⁻⁸) [ 36/100] │ 4.880e-02 1.88×10⁻² (10⁻⁸) [ 37/100] │ 1.220e-02 1.49×10⁻² (10⁻⁸) [ 38/100] │ 1.220e-02 7.78×10⁻³ (10⁻⁸) [ 39/100] │ 1.220e-02 6.49×10⁻³ (10⁻⁸) [ 40/100] │ 5.976e-03 2.70×10⁻³ (10⁻⁸) [ 41/100] │ 5.976e-03 3.46×10⁻³ (10⁻⁸) [ 42/100] │ 2.624e-03 1.52×10⁻³ (10⁻⁸) [ 43/100] │ 2.624e-03 1.34×10⁻³ (10⁻⁸) [ 44/100] │ 2.624e-03 1.23×10⁻³ (10⁻⁸) [ 45/100] │ 3.583e-04 9.66×10⁻⁴ (10⁻⁸) [ 46/100] │ 3.583e-04 3.54×10⁻⁴ (10⁻⁸) [ 47/100] │ 4.827e-05 1.27×10⁻⁴ (10⁻⁸) [ 48/100] │ 4.827e-05 5.66×10⁻⁵ (10⁻⁸) [ 49/100] │ 4.827e-05 1.50×10⁻⁵ (10⁻⁸) [ 50/100] │ 3.590e-05 1.45×10⁻⁵ (10⁻⁸) [ 51/100] │ 1.332e-05 1.42×10⁻⁵ (10⁻⁸) [ 52/100] │ 1.565e-06 4.92×10⁻⁶ (10⁻⁸) [ 53/100] │ 1.565e-06 3.46×10⁻⁶ (10⁻⁸) [ 54/100] │ 1.565e-06 9.10×10⁻⁷ (10⁻⁸) [ 55/100] │ 1.565e-06 6.87×10⁻⁷ (10⁻⁸) [ 56/100] │ 4.966e-07 5.78×10⁻⁷ (10⁻⁸) [ 57/100] │ 2.273e-07 1.31×10⁻⁷ (10⁻⁸) [ 58/100] │ 2.120e-07 7.11×10⁻⁸ (10⁻⁸) [ 59/100] │ 6.942e-08 8.18×10⁻⁸ (10⁻⁸) [ 60/100] │ 1.876e-08 2.13×10⁻⁸ (10⁻⁸) [ 61/100] │ 1.876e-08 9.27×10⁻⁹ (10⁻⁸) * Status: success * Candidate solution Minimizer: [1.00e+00, 1.00e+00] Minimum: 3.525527e-09 * Found with Algorithm: Nelder-Mead Initial Point: [0.00e+00, 0.00e+00] * Convergence measures √(Σ(yᵢ-ȳ)²)/n ≤ 1.0e-08 * Work counters Seconds run: 0 (vs limit Inf) Iterations: 60 f(x) calls: 118

SolverTrace(num_steps, i, print_interval, io, progress, columns, callbacks)

SolverTrace(num_steps[, column=CurrentStep(num_steps), columns...;
                        io=stdout, num_printouts=10, progress_meter=true,
                        print_interval, kwargs...])

print_header(s)

next!(fun, s::SolverTrace; kwargs...)