code: def test_nonuniform_scale_samples_truncnorm():
      """
      Test the rescaling of samples for truncated normal distribution
      """
      problem = {
          "num_vars": 1,
          "dists": ["truncnorm"],
          "bounds": [[0, 3.14, 2, 1]],
          "names": ["x1"],
      }
      actual = latin.sample(problem, 10, seed=42)
      expected = np.array(
          [
              [2.68693037],
              [1.34115848],
              [0.39811064],
              [2.09477163],
              [2.49999031],
              [3.028063],
              [1.5564238],
              [1.11686499],
              [1.68414443],
              [1.9022482],
          ]
      )
      np.testing.assert_allclose(actual, expected)
  
imports: from pytest import raises
  from numpy.testing import assert_equal, assert_allclose
  import numpy
  from scipy import stats
  import pytest
  from SALib.util import read_param_file, _scale_samples, _unscale_samples, compute_groups_matrix
  from SALib.sample import latin
label_desc: Use image node_id 15 for calling a global function with example usage: test_nonuniform_scale_samples_truncnorm() without return types