code: def test_tf_mxne_vs_mxne():
      """Test equivalence of TF-MxNE (with alpha_time=0) and MxNE."""
      alpha_space = 60.0
      alpha_time = 0.0
  
      M, G, active_set = _generate_tf_data()
  
      X_hat_tf, active_set_hat_tf, E = tf_mixed_norm_solver(
          M,
          G,
          alpha_space,
          alpha_time,
          maxit=200,
          tol=1e-8,
          verbose=True,
          debias=False,
          n_orient=1,
          tstep=4,
          wsize=32,
      )
  
      # Also run L21 and check that we get the same
      X_hat_l21, _, _ = mixed_norm_solver(
          M,
          G,
          alpha_space,
          maxit=200,
          tol=1e-8,
          verbose=False,
          n_orient=1,
          active_set_size=None,
          debias=False,
      )
  
      assert_allclose(X_hat_tf, X_hat_l21, rtol=1e-1)
  
file_path: mne-python/mne/inverse_sparse/tests/test_mxne_optim.py
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less
  from mne.inverse_sparse.mxne_optim import _Phi, _PhiT, dgap_l21l1, iterative_mixed_norm_solver, iterative_tf_mixed_norm_solver, mixed_norm_solver, norm_epsilon, norm_epsilon_inf, tf_mixed_norm_solver
  from mne.time_frequency._stft import stft_norm2
  from mne.utils import _record_warnings, catch_logging
label_desc: Use image node_id 7 for calling a global function with example usage: test_tf_mxne_vs_mxne() without return types