code: def test_fewer_points_than_dimensions_gh17436():
      # When the number of points is fewer than the number of dimensions, the
      # the covariance matrix would be singular, and the exception tested in
      # test_singular_data_covariance_gh10205 would occur. However, sometimes
      # this occurs when the user passes in the transpose of what `gaussian_kde`
      # expects. This can result in a huge covariance matrix, so bail early.
      rng = np.random.default_rng(2046127537594925772)
      rvs = rng.multivariate_normal(np.zeros(3), np.eye(3), size=5)
      message = (
          "Number of dimensions is greater than number of samples..."
      )
      with pytest.raises(ValueError, match=message):
          stats.gaussian_kde(rvs)
  
imports: from scipy import stats, linalg, integrate
  import numpy
  from numpy.testing import assert_almost_equal, assert_, assert_equal, assert_array_almost_equal, assert_array_almost_equal_nulp, assert_allclose
  import pytest
  from pytest import raises
label_desc: Use image node_id 23 for calling a global function with example usage: test_fewer_points_than_dimensions_gh17436() without return types