np.int removed from numpy causes error for hopfield_dynamics.pattern_tools.py

[mwatts15]

In executing the create_checkerboard function and a couple others, you'd get an error like the one below rather than having the expected pattern returned. This is due to removal of a previously deprecated attribute .int from numpy. Replacing it with builtin int as suggested resolves the issue.

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[1], line 11
      9 factory = pattern_tools.PatternFactory(pattern_size, pattern_size)
     10 # create a checkerboard pattern and add it to the pattern list
---> 11 checkerboard = factory.create_checkerboard()
     12 pattern_list = [checkerboard]
     14 # add random patterns to the list

File ~/work/neuronal-dynamics/bmnn/lib/python3.11/site-packages/neurodynex3/hopfield_network/pattern_tools.py:116, in PatternFactory.create_checkerboard(self)
    110 def create_checkerboard(self):
    111     """
    112     creates a checkerboard pattern of size (pattern_length x pattern_width)
    113     Returns:
    114         checkerboard pattern
    115     """
--> 116     pw = np.ones(self.pattern_length, np.int)
    117     # set every second value to -1
    118     pw[1::2] = -1

File ~/work/neuronal-dynamics/bmnn/lib/python3.11/site-packages/numpy/__init__.py:313, in __getattr__(attr)
    308     warnings.warn(
    309         f"In the future `np.{attr}` will be defined as the "
    310         "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
    312 if attr in __former_attrs__:
--> 313     raise AttributeError(__former_attrs__[attr])
    315 if attr == 'testing':
    316     import numpy.testing as testing

AttributeError: module 'numpy' has no attribute 'int'.
`np.int` was a deprecated alias for the builtin `int`. To avoid this error in existing code, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
    https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations