code: def test_comparison_methods_array(comparison_op, dtype):
      op_name = f"__{comparison_op.__name__}__"
  
      a = pd.array(["a", None, "c"], dtype=dtype)
      other = [None, None, "c"]
      result = getattr(a, op_name)(other)
      if dtype.storage == "pyarrow_numpy":
          if operator.ne == comparison_op:
              expected = np.array([True, True, False])
          else:
              expected = np.array([False, False, False])
              expected[-1] = getattr(other[-1], op_name)(a[-1])
          tm.assert_numpy_array_equal(result, expected)
  
          result = getattr(a, op_name)(pd.NA)
          if operator.ne == comparison_op:
              expected = np.array([True, True, True])
          else:
              expected = np.array([False, False, False])
          tm.assert_numpy_array_equal(result, expected)
  
      else:
          expected_dtype = (
              "boolean[pyarrow]"
              if dtype.storage == "pyarrow"
              else "boolean"
          )
          expected = np.full(len(a), fill_value=None, dtype="object")
          expected[-1] = getattr(other[-1], op_name)(a[-1])
          expected = pd.array(expected, dtype=expected_dtype)
          tm.assert_extension_array_equal(result, expected)
  
          result = getattr(a, op_name)(pd.NA)
          expected = pd.array([None, None, None], dtype=expected_dtype)
          tm.assert_extension_array_equal(result, expected)
  
imports: import operator
  import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under12p0
  from pandas.core.dtypes.common import is_dtype_equal
  import pandas
  import pandas._testing
  from pandas.core.arrays.string_arrow import ArrowStringArray, ArrowStringArrayNumpySemantics
label_desc: Use image node_id 19 for calling a global function with example usage: test_comparison_methods_array(comparison_op, dtype) without return types