code: def _test_inspect(self):
      data = arange(15, dtype=float).reshape(5, 3)
      adj_array = AdjustedArray(
          data,
          NOMASK,
          {4: [Float64Multiply(2, 3, 0, 0, 4.0)]},
          float("nan"),
      )
  
      expected = dedent(
          """\
              Adjusted Array (float64):
  
              Data:
              array([[  0.,   1.,   2.],
                     [  3.,   4.,   5.],
                     [  6.,   7.,   8.],
                     [  9.,  10.,  11.],
                     [ 12.,  13.,  14.]])
  
              Adjustments:
              {4: [Float64Multiply(first_row=2, last_row=3, first_col=0, \
  last_col=0, value=4.000000)]}
              """
      )
      got = adj_array.inspect()
      self.assertEqual(expected, got)
  
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 9 for calling the AdjustedArrayTestCase obj's underlying member method code with example usage: obj._test_inspect() without return types