docstr: Tests whether interpolation results are correct.
docstr_tok: ["Tests","whether","interpolation","results","are","correct","."]
code: def test_interpolate_preset(self, points, weights, indices, _, out):
      """Tests whether interpolation results are correct."""
      weights = tf.convert_to_tensor(value=weights)
  
      result_unnormalized = weighted.interpolate(
          points=points,
          weights=weights,
          indices=indices,
          normalize=False,
      )
      result_normalized = weighted.interpolate(
          points=points,
          weights=2.0 * weights,
          indices=indices,
          normalize=True,
      )
      estimated_unnormalized = self.evaluate(result_unnormalized)
      estimated_normalized = self.evaluate(result_normalized)
  
      self.assertAllClose(estimated_unnormalized, out)
      self.assertAllClose(estimated_normalized, out)
  
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.math.interpolation import weighted
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 4 for calling the WeightedTest obj's underlying member method code with example usage: obj.test_interpolate_preset(points, weights, indices, _, out) without return types