code: def _make_data(n_feats, n_targets, n_samples, tmin, tmax):
      rng = np.random.RandomState(0)
      X = rng.randn(n_samples, n_feats)
      w = rng.randn(int((tmax - tmin) + 1) * n_feats, n_targets)
      # Delay inputs
      X_del = np.concatenate(
          _delay_time_series(X, tmin, tmax, 1.0).transpose(2, 0, 1),
          axis=1,
      )
      y = np.dot(X_del, w)
      return X, y
  
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy import einsum
  from numpy.fft import irfft, rfft
  from numpy.testing import assert_allclose, assert_array_equal, assert_equal
  from mne.decoding import ReceptiveField, TimeDelayingRidge
  from mne.decoding.receptive_field import _SCORERS, _delay_time_series, _delays_to_slice, _times_to_delays
  from mne.decoding.time_delaying_ridge import _compute_corrs, _compute_reg_neighbors
label_desc: Use image node_id 8 for calling a global function with example usage: _make_data(n_feats, n_targets, n_samples, tmin, tmax) and returns: X,  y