code: def testNonPositiveDf(self):
      with self.assertRaisesOpError("Argument `df` must be positive."):
          self.evaluate(
              mvst.MultivariateStudentTLinearOperator(
                  loc=self._input([0.0]),
                  df=self._input(0.0),
                  scale=tf.linalg.LinearOperatorDiag(
                      self._input([1.0]), is_non_singular=True
                  ),
                  validate_args=True,
              ).sample(seed=test_util.test_seed())
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import multivariate_student_t
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 3 for calling the MultivariateStudentTTestFloat32StaticShape obj's underlying member method code with example usage: obj.testNonPositiveDf() without return types