code: def test_bad_input(self):
      msg = "Mask shape \(2L?, 3L?\) != data shape \(5L?, 5L?\)"
      data = arange(25).reshape(5, 5)
      bad_mask = array([[0, 1, 1], [0, 0, 1]], dtype=bool)
  
      with self.assertRaisesRegexp(ValueError, msg):
          AdjustedArray(data, bad_mask, {}, missing_value=-1)
  
imports: from collections import namedtuple
  from itertools import chain, product
  from textwrap import dedent
  from unittest import TestCase
  from nose_parameterized import parameterized
  from numpy import arange, array, asarray, dtype, full, where
  from six.moves import zip_longest
  from toolz import curry
  from catalyst.errors import WindowLengthNotPositive, WindowLengthTooLong
  from catalyst.lib.adjustment import Datetime64Overwrite, Datetime641DArrayOverwrite, Float64Multiply, Float64Overwrite, Float641DArrayOverwrite, Int64Overwrite, ObjectOverwrite
  from catalyst.lib.adjusted_array import AdjustedArray, NOMASK
  from catalyst.lib.labelarray import LabelArray
  from catalyst.testing import check_arrays, parameter_space
  from catalyst.utils.compat import unicode
  from catalyst.utils.numpy_utils import coerce_to_dtype, datetime64ns_dtype, default_missing_value_for_dtype, float64_dtype, int64_dtype, object_dtype
label_desc: Use image node_id 8 for calling the AdjustedArrayTestCase obj's underlying member method code with example usage: obj.test_bad_input() without return types