code: def test_gaussian_random_projector_dot_product():
      dataset = datasets.TrumpApproval()
      projector = preprocessing.GaussianRandomProjector(n_components=3)
  
      for x, y in dataset:
          y = projector.transform_one(x)
          y_arr = np.array(list(y.values()))
          x_arr = np.array(list(x.values()))
          P = np.array(
              [
                  [projector._projection_matrix[i, j] for j in x]
                  for i in range(projector.n_components)
              ]
          )
          np.testing.assert_allclose(x_arr @ P.T, y_arr)
  
imports: from __future__ import annotations
  import numpy
  from river import datasets, preprocessing
label_desc: Use image node_id 1 for calling a global function with example usage: test_gaussian_random_projector_dot_product() without return types