class_docstr: Test for 1-D usage of tfp.math.interp_regular_1d_grid.
class_docstr_tok: ["Test","for","1-D","usage","of","tfp.math.interp_regular_1d_grid","."]
code: def test_vector_valued_interpolation_with_1_batch_dim_scalar_minmax(
      self,
  ):
      # implied_x_ref.shape = [3, 200], with all 3 batch members having the same
      # min and max (hence, "scalar minmax").
      implied_x_ref = np.array([np.linspace(1.0, 3.0, 200)] * 3)
      y_ref = np.stack(  # Shape [3, 200, 2]
          [np.exp(implied_x_ref), np.exp(2 * implied_x_ref)], axis=-1
      )
  
      x = 1 + 2 * self.rng.rand(3, 5)
      # Interpolate along axis 1, the axis with 200 elements.
      y = interpolation.batch_interp_regular_1d_grid(
          x, x_ref_min=1.0, x_ref_max=3.0, y_ref=y_ref, axis=1
      )
      self.assertAllEqual((3, 5, 2), y.shape)
      y_ = self.evaluate(y)
      expected_y = np.stack([np.exp(x), np.exp(2 * x)], axis=-1)
      self.assertAllClose(y_, expected_y, rtol=1e-3, atol=1e-3)
  
imports: import numpy
  from scipy import interpolate
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math import interpolation
label_desc: Use image node_id 11 for calling the BatchInterpRegular1DGridTest obj's underlying member method code with example usage: obj.test_vector_valued_interpolation_with_1_batch_dim_scalar_minmax() without return types