lmfit.minimize with method='lbfgsb' doesn't obey setting max_nfev > 15000

[rowlesmr]

Description

When minimising a residual using lmfit.minimize with method='lbfgsb', setting max_nfev to a value greater than the default value of maxiter (15000) of scipy.optimize.fmin_l_bfgs_b results in the minimisation still terminating at nfev=15000. Setting the keyword argument maxiter=50000 gives RuntimeWarning: ignoring 'maxiter' argument to 'Minimizer()'. Use 'max_nfev' instead..

What am I doing wrong?

A Minimal, Complete, and Verifiable example

import lmfit
import numpy as np


def G(a, b, x) -> float:
    return a * np.exp(-b * x * x)


def residual(params, x, data):
    a_s = [params['a1'], params['a2'], params['a3'], params['a4'], params['a5']]
    b_s = [params['b1'], params['b2'], params['b3'], params['b4'], params['b5']]
    c = params['c']

    model = c * np.ones(x.size)
    for a, b in zip(a_s, b_s):
        model += G(a, b, x)

    return data - model


X = np.asarray([0.00, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10, 0.11, 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, 0.19, 0.20, 0.22, 0.24, 0.25, 0.26, 0.28, 0.30, 0.32, 0.34, 0.35, 0.36, 0.38, 0.40, 0.42, 0.44, 0.45, 0.46, 0.48, 0.50, 0.55, 0.60, 0.65, 0.70, 0.80, 0.90, 1.00, 1.10, 1.20, 1.30, 1.40, 1.50, 1.60, 1.70, 1.80, 1.90, 2.00, 2.50, 3.00, 3.50, 4.00, 5.00, 6.00])
Y = np.asarray([57.000, 56.926, 56.708, 56.360, 55.900, 55.351, 54.736, 54.076, 53.388, 52.687, 51.982, 51.278, 50.580, 49.888, 49.202, 48.523, 47.849, 47.182, 46.519, 45.862, 45.212, 43.932, 42.686, 42.078, 41.481, 40.321, 39.212, 38.153, 37.145, 36.659, 36.185, 35.270, 34.397, 33.562, 32.760, 32.370, 31.988, 31.243, 30.523, 28.817, 27.231, 25.759, 24.401, 22.031, 20.106, 18.561, 17.300, 16.227, 15.265, 14.362, 13.489, 12.636, 11.807, 11.009, 10.253, 9.550, 6.917, 5.550, 4.820, 4.270, 3.240, 2.410])

params = lmfit.Parameters()

params.add('a1', value=11.4)
params.add('a2', value=21.66)
params.add('a3', value=14.82)
params.add('a4', value=6.84)
params.add('a5', value=1.71)

params.add('b1', value=0.2379567949423352)
params.add('b2', value=1.5687819528065554)
params.add('b3', value=16.957819441754367)
params.add('b4', value=37.086721911270914)
params.add('b5', value=149.49345053809822)

params.add('c', value=3.213258144928004)

out = lmfit.minimize(residual, params, args=(X, Y), method='lbfgsb', max_nfev=50000)
# out.nfev=15012 out.success=False out.message='STOP: TOTAL NO. of f AND g EVALUATIONS EXCEEDS LIMIT'
print(f"Doesn't follow max_nfev > maxiter default:\n{out.nfev=} {out.success=} {out.message=}")

out = lmfit.minimize(residual, params, args=(X, Y), method='lbfgsb', max_nfev=5)
# out.nfev=6 out.success=False out.message='Fit aborted: number of function evaluations > 5'
print(f"\nDoes follow max_nfev < maxiter default:\n{out.nfev=} {out.success=} {out.message=}")

out = lmfit.minimize(residual, params, args=(X, Y), method='lbfgsb', maxiter=50000)
# out.nfev=15012 out.success=False out.message='STOP: TOTAL NO. of f AND g EVALUATIONS EXCEEDS LIMIT'
print(f"\nRuntimeWarning because I used maxiter:\n{out.nfev=} {out.success=} {out.message=}")

Error message:

C:\Users\184277j\AppData\Local\Programs\Python\Python39\lib\site-packages\lmfit\minimizer.py:497: RuntimeWarning: ignoring `maxiter` argument to `Minimizer()`. Use `max_nfev` instead.
  warnings.warn(maxeval_warning.format(maxnfev_alias, 'Minimizer'),

Version information

Python: 3.9.4 (tags/v3.9.4:1f2e308, Apr 6 2021, 13:40:21) [MSC v.1928 64 bit (AMD64)]

lmfit: 1.2.0, scipy: 1.6.3, numpy: 1.21.4,asteval: 0.9.29, uncertainties: 3.1.7

[newville]

For completeness, this was addressed in #866.