code: def test_mean_weight_zero(kind, mean, get_mats):
      """Setting one weight to almost 0 it's almost like not passing the mat"""
      n_matrices, n_channels = 5, 3
      mats = get_mats(n_matrices, n_channels, kind)
      w = 2.3 * np.ones(n_matrices)
      C = mean(mats[1:], sample_weight=w[1:])
      w[0] = 1e-12
      Cw = mean(mats, sample_weight=w)
      assert C == approx(Cw, rel=1e-6, abs=1e-8)
  
imports: import numpy
  from scipy.stats import gmean
  import pytest
  from pytest import approx
  from pyriemann.utils.geodesic import geodesic_riemann
  from pyriemann.utils.mean import mean_covariance, mean_ale, mean_alm, mean_euclid, mean_harmonic, mean_identity, mean_kullback_sym, mean_logdet, mean_logeuclid, mean_power, mean_riemann, mean_wasserstein, maskedmean_riemann, nanmean_riemann
label_desc: Use image node_id 3 for calling a global function with example usage: test_mean_weight_zero(kind, mean, get_mats) without return types