code: def test_pyarrow_array_to_numpy_and_mask(np_dtype_to_arrays):
      """
      Test conversion from pyarrow array to numpy array.
  
      Modifies the pyarrow buffer to contain padding and offset, which are
      considered valid buffers by pyarrow.
  
      Also tests empty pyarrow arrays with non empty buffers.
      See https://github.com/pandas-dev/pandas/issues/40896
      """
      (
          np_dtype,
          pa_array,
          np_expected,
          mask_expected,
      ) = np_dtype_to_arrays
      data, mask = pyarrow_array_to_numpy_and_mask(pa_array, np_dtype)
      tm.assert_numpy_array_equal(data[:3], np_expected)
      tm.assert_numpy_array_equal(mask, mask_expected)
  
      mask_buffer = pa_array.buffers()[0]
      data_buffer = pa_array.buffers()[1]
      data_buffer_bytes = pa_array.buffers()[1].to_pybytes()
  
      # Add trailing padding to the buffer.
      data_buffer_trail = pa.py_buffer(data_buffer_bytes + b"\x00")
      pa_array_trail = pa.Array.from_buffers(
          type=pa_array.type,
          length=len(pa_array),
          buffers=[mask_buffer, data_buffer_trail],
          offset=pa_array.offset,
      )
      pa_array_trail.validate()
      data, mask = pyarrow_array_to_numpy_and_mask(
          pa_array_trail, np_dtype
      )
      tm.assert_numpy_array_equal(data[:3], np_expected)
      tm.assert_numpy_array_equal(mask, mask_expected)
  
      # Add offset to the buffer.
      offset = b"\x00" * (pa_array.type.bit_width // 8)
      data_buffer_offset = pa.py_buffer(offset + data_buffer_bytes)
      mask_buffer_offset = pa.py_buffer(b"\x0E")
      pa_array_offset = pa.Array.from_buffers(
          type=pa_array.type,
          length=len(pa_array),
          buffers=[mask_buffer_offset, data_buffer_offset],
          offset=pa_array.offset + 1,
      )
      pa_array_offset.validate()
      data, mask = pyarrow_array_to_numpy_and_mask(
          pa_array_offset, np_dtype
      )
      tm.assert_numpy_array_equal(data[:3], np_expected)
      tm.assert_numpy_array_equal(mask, mask_expected)
  
      # Empty array
      np_expected_empty = np.array([], dtype=np_dtype)
      mask_expected_empty = np.array([], dtype=np.bool_)
  
      pa_array_offset = pa.Array.from_buffers(
          type=pa_array.type,
          length=0,
          buffers=[mask_buffer, data_buffer],
          offset=pa_array.offset,
      )
      pa_array_offset.validate()
      data, mask = pyarrow_array_to_numpy_and_mask(
          pa_array_offset, np_dtype
      )
      tm.assert_numpy_array_equal(data[:3], np_expected_empty)
      tm.assert_numpy_array_equal(mask, mask_expected_empty)
  
file_path: pandas/pandas/tests/arrays/masked/test_arrow_compat.py
imports: import numpy
  import pytest
  import pandas
  import pandas._testing
  from pandas.core.arrays.arrow._arrow_utils import pyarrow_array_to_numpy_and_mask
label_desc: Use image node_id 9 for calling a global function with example usage: test_pyarrow_array_to_numpy_and_mask(np_dtype_to_arrays) without return types