docstr: Tests sample for scale specification.
docstr_tok: ["Tests","sample","for","scale","specification","."]
code: def test_mean_and_scale_sobol(self):
      """Tests sample for scale specification."""
      mean = np.array([[1.0, 0.1], [0.1, 1.0], [2.0, 0.3], [0.0, 0.0]])
      scale = np.array([[0.4, -0.1], [0.22, 1.38]])
      covariance = np.matmul(scale, scale.transpose())
      sample_shape = [2, 3, 5000]
      sample = self.evaluate(
          tff_rnd.mv_normal_sample(
              sample_shape,
              mean=mean,
              scale_matrix=scale,
              random_type=tff_rnd.RandomType.SOBOL,
          )
      )
  
      np.testing.assert_array_equal(sample.shape, sample_shape + [4, 2])
      np.testing.assert_array_almost_equal(
          np.mean(sample, axis=(0, 1, 2)), mean, decimal=1
      )
      for i in range(4):
          np.testing.assert_array_almost_equal(
              np.cov(sample[0, 1, :, i, :], rowvar=False),
              covariance,
              decimal=1,
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  import tf_quant_finance
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 8 for calling the RandomTest obj's underlying member method code with example usage: obj.test_mean_and_scale_sobol() without return types