code: def test_array_args_basic():
      """Tests passing explicit arrays instead of column labels for prot_attr,
      target, and sample_weight.
      """
      # single array
      pa_array = basic(prot_attr=pd.Index([1, 0, 1], name="ZZ"))
      assert pa_array.X.columns.equals(pd.Index(["X1", "X2", "Z"]))
      assert pa_array.X.index.names == ["ZZ"]
      # mixed array and label
      tar_array_mixed = basic(target=[np.array([4, 8, 12]), "y"])
      assert tar_array_mixed.y.shape == (3, 2)
      assert tar_array_mixed.X.shape == (3, 3)
      assert tar_array_mixed.y.index.equals(tar_array_mixed.X.index)
      # sample weight
      sw_array = basic(sample_weight=[0.5, 0.4, 2.1])
      assert sw_array.sample_weight.index.equals(sw_array.X.index)
  
imports: from functools import partial
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  from pandas.api.types import is_numeric_dtype
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.compose import make_column_transformer
  from sklearn.preprocessing import OneHotEncoder, minmax_scale
  from aif360.datasets import AdultDataset, GermanDataset, CompasDataset, LawSchoolGPADataset, MEPSDataset19, MEPSDataset20, MEPSDataset21
  from aif360.sklearn.datasets import standardize_dataset, NumericConversionWarning, fetch_adult, fetch_bank, fetch_german, fetch_compas, fetch_lawschool_gpa, fetch_meps
label_desc: Use image node_id 4 for calling a global function with example usage: test_array_args_basic() without return types