code: def test_from_arrays_index_datetimelike_mixed():
      idx1 = date_range(
          "2015-01-01 10:00", freq="D", periods=3, tz="US/Eastern"
      )
      idx2 = date_range("2015-01-01 10:00", freq="h", periods=3)
      idx3 = pd.timedelta_range("1 days", freq="D", periods=3)
      idx4 = pd.period_range("2011-01-01", freq="D", periods=3)
  
      result = MultiIndex.from_arrays([idx1, idx2, idx3, idx4])
      tm.assert_index_equal(result.get_level_values(0), idx1)
      tm.assert_index_equal(result.get_level_values(1), idx2)
      tm.assert_index_equal(result.get_level_values(2), idx3)
      tm.assert_index_equal(result.get_level_values(3), idx4)
  
      result2 = MultiIndex.from_arrays(
          [Series(idx1), Series(idx2), Series(idx3), Series(idx4)]
      )
      tm.assert_index_equal(result2.get_level_values(0), idx1)
      tm.assert_index_equal(result2.get_level_values(1), idx2)
      tm.assert_index_equal(result2.get_level_values(2), idx3)
      tm.assert_index_equal(result2.get_level_values(3), idx4)
  
      tm.assert_index_equal(result, result2)
  
imports: from datetime import date, datetime
  import itertools
  import numpy
  import pytest
  from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
  import pandas
  from pandas import Index, MultiIndex, Series, Timestamp, date_range
  import pandas._testing
label_desc: Use image node_id 11 for calling a global function with example usage: test_from_arrays_index_datetimelike_mixed() without return types