code: def test_rus_fit_resample_half():
      sampling_strategy = {0: 3, 1: 6}
      rus = RandomUnderSampler(
          sampling_strategy=sampling_strategy,
          random_state=RND_SEED,
          replacement=True,
      )
      X_resampled, y_resampled = rus.fit_resample(X, Y)
  
      X_gt = np.array(
          [
              [0.92923648, 0.76103773],
              [0.47104475, 0.44386323],
              [0.92923648, 0.76103773],
              [0.15490546, 0.3130677],
              [0.15490546, 0.3130677],
              [0.15490546, 0.3130677],
              [0.20792588, 1.49407907],
              [0.15490546, 0.3130677],
              [0.12372842, 0.6536186],
          ]
      )
      y_gt = np.array([0, 0, 0, 1, 1, 1, 1, 1, 1])
      assert_array_equal(X_resampled, X_gt)
      assert_array_equal(y_resampled, y_gt)
  
file_path: imbalanced-learn/imblearn/under_sampling/_prototype_selection/tests/test_random_under_sampler.py
imports: from collections import Counter
  from datetime import datetime
  import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.utils._testing import assert_array_equal
  from imblearn.under_sampling import RandomUnderSampler
label_desc: Use image node_id 2 for calling a global function with example usage: test_rus_fit_resample_half() without return types