docstr: Test for distribution of face indices with area weighted sampler.
docstr_tok: ["Test","for","distribution","of","face","indices","with","area","weighted","sampler","."]
code: def test_face_distribution(self):
      """Test for distribution of face indices with area weighted sampler."""
      vertices, faces = mesh_test_utils.create_square_triangle_mesh()
      num_samples = 1000
      (
          _,
          sample_faces,
      ) = sampler.area_weighted_random_sample_triangle_mesh(
          vertices, faces, num_samples
      )
  
      # All points should be approx poisson distributed among the 4 faces.
      self.assertEqual(sample_faces.shape[0], num_samples)
      num_faces = faces.shape[0]
      expected = np.array(
          [num_samples / num_faces] * num_faces, dtype=np.intp
      )
      self.compare_poisson_equivalence(
          expected, tf.math.bincount(sample_faces)
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  import tensorflow
  from tensorflow_graphics.geometry.representation.mesh import sampler
  from tensorflow_graphics.geometry.representation.mesh.tests import mesh_test_utils
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 18 for calling the MeshSamplerTest obj's underlying member method code with example usage: obj.test_face_distribution() without return types