code: def test_gls_warning(reset_randomstate):
      data = np.random.standard_normal((400, 200))
      data[:, 1:] = data[:, :1] + 0.01 * data[:, 1:]
      with pytest.warns(
          EstimationWarning, match="Many series are being down weighted"
      ):
          factors = PCA(data, ncomp=2, gls=True).factors
      assert factors.shape == (data.shape[0], 2)
  
imports: from statsmodels.compat.platform import PLATFORM_WIN32
  import warnings
  import numpy
  import pandas
  import pytest
  from numpy.testing import assert_allclose, assert_equal, assert_raises
  from statsmodels.multivariate.pca import PCA, pca
  from statsmodels.multivariate.tests.results.datamlw import data, princomp1, princomp2
  from statsmodels.tools.sm_exceptions import EstimationWarning
label_desc: Use image node_id 3 for calling a global function with example usage: test_gls_warning(reset_randomstate) without return types