code: def test_integrated_value(self):
      dtype = np.float64
      interval_times = tf.constant(
          [0.25, 0.5, 1.0, 2.0, 3.0], dtype=dtype
      )
      interval_values = tf.constant(
          [0.05, 0.051, 0.052, 0.053, 0.055], dtype=dtype
      )
      # Checks that the integral is correct by computing it using a Riemann sum.
      test_times = tf.constant(
          np.linspace(1.0, 1.1, num=51), dtype=dtype
      )
      dt = np.array(0.002, dtype=dtype)
      values, integrated = self.evaluate(
          monotone_convex.interpolate(
              test_times, interval_values, interval_times
          )
      )
      actual = integrated[-1]
      expected = np.sum(dt * (values[1:] + values[:-1]) / 2)
      self.assertAlmostEqual(actual, expected)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow.python.framework import test_util
  from tf_quant_finance.rates.hagan_west import monotone_convex
label_desc: Use image node_id 5 for calling the MonotoneConvexTest obj's underlying member method code with example usage: obj.test_integrated_value() without return types