code: def test_large_features(self):
      # Generate a data set with large values, and run kmeans on it to
      # (regression for 1077).
      d = 300
      n = 100
  
      m1 = np.random.randn(d)
      m2 = np.random.randn(d)
      x = 10000 * np.random.randn(n, d) - 20000 * m1
      y = 10000 * np.random.randn(n, d) + 20000 * m2
  
      data = np.empty((x.shape[0] + y.shape[0], d), np.double)
      data[: x.shape[0]] = x
      data[x.shape[0] :] = y
  
      kmeans(data, 2)
  
imports: from __future__ import division, print_function, absolute_import
  import warnings
  import sys
  import numpy
  from numpy.testing import assert_array_equal, assert_array_almost_equal, assert_allclose, assert_equal, assert_
  from scipy._lib._numpy_compat import suppress_warnings
  import pytest
  from pytest import raises
  from scipy.cluster.vq import kmeans, kmeans2, py_vq, vq, whiten, ClusterError, _krandinit
  from scipy.cluster import _vq
  from scipy.sparse.sputils import matrix
label_desc: Use image node_id 1 for calling the TestKMean obj's underlying member method code with example usage: obj.test_large_features() without return types