code: def test_logistic_lipschitz(rng, scaling, n_samples=4, n_features=2):
      X = rng.standard_normal((n_samples, n_features)) * scaling
      y = rng.standard_normal(n_samples)
      n_features = X.shape[1]
  
      L = logistic_loss_lipschitz_constant(X)
      _check_lipschitz_continuous(
          lambda w: logistic_loss(X, y, w), n_features + 1, L
      )
  
file_path: nilearn/nilearn/decoding/tests/test_fista.py
imports: import numpy
  import pytest
  from nilearn.decoding._objective_functions import logistic_loss, logistic_loss_lipschitz_constant, spectral_norm_squared, squared_loss, squared_loss_grad
  from nilearn.decoding._proximal_operators import prox_l1
  from nilearn.decoding.fista import _check_lipschitz_continuous, mfista
label_desc: Use image node_id 1 for calling a global function with example usage: test_logistic_lipschitz(rng, scaling, n_samples, n_features) without return types