class_docstr: Test the RFECV visualizer
class_docstr_tok: ["Test","the","RFECV","visualizer"]
docstr: Test on a real dataset with numpy ndarray
docstr_tok: ["Test","on","a","real","dataset","with","numpy","ndarray"]
code: def test_numpy_integration(self):
      """
      Test on a real dataset with numpy ndarray
      """
      data = load_occupancy(return_dataset=True)
      X, y = data.to_numpy()
  
      # Use only the first 100 samples so the test will run faster
      X_t = X[:100]
      y_t = y[:100]
  
      assert isinstance(X_t, np.ndarray)
      assert isinstance(y_t, np.ndarray)
  
      cv = StratifiedKFold(n_splits=4, shuffle=True, random_state=32)
      oz = RFECV(RandomForestClassifier(random_state=83), cv=cv)
      oz.fit(X_t, y_t)
      oz.finalize()
  
      self.assert_images_similar(oz, remove_legend=True)
  
imports: import sys
  import pytest
  import numpy
  import numpy.testing
  from unittest.mock import patch
  from tests.fixtures import Dataset
  from tests.base import VisualTestCase
  from yellowbrick.model_selection.rfecv import *
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.exceptions import YellowbrickValueError
  from sklearn.svm import SVC
  from sklearn.datasets import make_classification
  from sklearn.model_selection import ShuffleSplit
  from sklearn.model_selection import StratifiedKFold
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
label_desc: Use image node_id 5 for calling the TestRFECV obj's underlying member method code with example usage: obj.test_numpy_integration() without return types