code: def test_1nn(get_mats, get_labels):
      """Test KNearestNeighbor with K=1"""
      n_matrices, n_channels, n_classes = 9, 3, 3
      covmats = get_mats(n_matrices, n_channels, "spd")
      labels = get_labels(n_matrices, n_classes)
  
      knn = KNearestNeighbor(1, metric="riemann")
      knn.fit(covmats, labels)
      preds = knn.predict(covmats)
      assert_array_equal(labels, preds)
  
imports: import pickle
  import numpy
  from numpy.testing import assert_array_equal
  import pytest
  from pytest import approx
  from scipy.stats import mode
  from sklearn.dummy import DummyClassifier
  from conftest import get_distances, get_means, get_metrics
  from pyriemann.estimation import Covariances
  from pyriemann.utils.kernel import kernel
  from pyriemann.utils.mean import mean_covariance
  from pyriemann.classification import _mode_2d, MDM, FgMDM, KNearestNeighbor, TSclassifier, SVC, MeanField, class_distinctiveness
label_desc: Use image node_id 18 for calling a global function with example usage: test_1nn(get_mats, get_labels) without return types