text: import warnings
  import functools
  import sys
  import numpy as np
  import types
  import numbers
  
  from ..util import img_as_float
  from ._warnings import all_warnings, warn
  
  __all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
             'safe_as_int', 'assert_nD', 'warn']
  
  
  class skimage_deprecation(Warning):
      """Create our own deprecation class, since Python >= 2.7
      silences deprecations by default.
  
      """
      pass
  
  
  class deprecated(object):
      """Decorator to mark deprecated functions with warning.
  
      Adapted from <http://wiki.python.org/moin/PythonDecoratorLibrary>.
  
      Parameters
      ----------
      alt_func : str
          If given, tell user what function to use instead.
      behavior : {'warn', 'raise'}
          Behavior during call to deprecated function: 'warn' = warn user that
          function is deprecated; 'raise' = raise error.
      removed_version : str
          The package version in which the deprecated function will be removed.
      """
  
      def __init__(self, alt_func=None, behavior='warn', removed_version=None):
          self.alt_func = alt_func
          self.behavior = behavior
          self.removed_version = removed_version
  
      def __call__(self, func):
  
          alt_msg = ''
          if self.alt_func is not None:
              alt_msg = ' Use ``%s`` instead.' % self.alt_func
          rmv_msg = ''
          if self.removed_version is not None:
              rmv_msg = (' and will be removed in version %s' %
                         self.removed_version)
  
          msg = ('Function ``%s`` is deprecated' % func.__name__ +
                 rmv_msg + '.' + alt_msg)
  
          @functools.wraps(func)
          def wrapped(*args, **kwargs):
              if self.behavior == 'warn':
                  func_code = func.__code__
                  warnings.simplefilter('always', skimage_deprecation)
                  warnings.warn_explicit(msg,
                                         category=skimage_deprecation,
                                         filename=func_code.co_filename,
                                         lineno=func_code.co_firstlineno + 1)
              elif self.behavior == 'raise':
                  raise skimage_deprecation(msg)
              return func(*args, **kwargs)
  
          # modify doc string to display deprecation warning
          doc = '**Deprecated function**.' + alt_msg
          if wrapped.__doc__ is None:
              wrapped.__doc__ = doc
          else:
              wrapped.__doc__ = doc + '\n\n    ' + wrapped.__doc__
  
          return wrapped
  
  
  def get_bound_method_class(m):
      """Return the class for a bound method.
  
      """
      return m.im_class if sys.version < '3' else m.__self__.__class__
  
  
  def safe_as_int(val, atol=1e-3):
      """
      Attempt to safely cast values to integer format.
  
      Parameters
      ----------
      val : scalar or iterable of scalars
          Number or container of numbers which are intended to be interpreted as
          integers, e.g., for indexing purposes, but which may not carry integer
          type.
      atol : float
          Absolute tolerance away from nearest integer to consider values in
          ``val`` functionally integers.
  
      Returns
      -------
      val_int : NumPy scalar or ndarray of dtype `np.int64`
          Returns the input value(s) coerced to dtype `np.int64` assuming all
          were within ``atol`` of the nearest integer.
  
      Notes
      -----
      This operation calculates ``val`` modulo 1, which returns the mantissa of
      all values. Then all mantissas greater than 0.5 are subtracted from one.
      Finally, the absolute tolerance from zero is calculated. If it is less
      than ``atol`` for all value(s) in ``val``, they are rounded and returned
      in an integer array. Or, if ``val`` was a scalar, a NumPy scalar type is
      returned.
  
      If any value(s) are outside the specified tolerance, an informative error
      is raised.
  
      Examples
      --------
      >>> safe_as_int(7.0)
      7
  
      >>> safe_as_int([9, 4, 2.9999999999])
      array([9, 4, 3])
  
      >>> safe_as_int(53.1)
      Traceback (most recent call last):
          ...
      ValueError: Integer argument required but received 53.1, check inputs.
  
      >>> safe_as_int(53.01, atol=0.01)
      53
  
      """
      mod = np.asarray(val) % 1                # Extract mantissa
  
      # Check for and subtract any mod values > 0.5 from 1
      if mod.ndim == 0:                        # Scalar input, cannot be indexed
          if mod > 0.5:
              mod = 1 - mod
      else:                                    # Iterable input, now ndarray
          mod[mod > 0.5] = 1 - mod[mod > 0.5]  # Test on each side of nearest int
  
      try:
          np.testing.assert_allclose(mod, 0, atol=atol)
      except AssertionError:
          raise ValueError("Integer argument required but received "
                           "{0}, check inputs.".format(val))
  
      return np.round(val).astype(np.int64)
  
  
  def assert_nD(array, ndim, arg_name='image'):
      """
      Verify an array meets the desired ndims and array isn't empty.
  
      Parameters
      ----------
      array : array-like
          Input array to be validated
      ndim : int or iterable of ints
          Allowable ndim or ndims for the array.
      arg_name : str, optional
          The name of the array in the original function.
  
      """
      array = np.asanyarray(array)
      msg_incorrect_dim = "The parameter `%s` must be a %s-dimensional array"
      msg_empty_array = "The parameter `%s` cannot be an empty array"
      if isinstance(ndim, int):
          ndim = [ndim]
      if array.size == 0:
          raise ValueError(msg_empty_array % (arg_name))
      if not array.ndim in ndim:
          raise ValueError(msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim])))
  
  
  def copy_func(f, name=None):
      """Create a copy of a function.
  
      Parameters
      ----------
      f : function
          Function to copy.
      name : str, optional
          Name of new function.
  
      """
      return types.FunctionType(f.__code__, f.__globals__, name or f.__name__,
                                f.__defaults__, f.__closure__)
  
  
  def check_random_state(seed):
      """Turn seed into a `np.random.RandomState` instance.
  
      Parameters
      ----------
      seed : None, int or np.random.RandomState
             If `seed` is None, return the RandomState singleton used by `np.random`.
             If `seed` is an int, return a new RandomState instance seeded with `seed`.
             If `seed` is already a RandomState instance, return it.
  
      Raises
      ------
      ValueError
          If `seed` is of the wrong type.
  
      """
      # Function originally from scikit-learn's module sklearn.utils.validation
      if seed is None or seed is np.random:
          return np.random.mtrand._rand
      if isinstance(seed, (numbers.Integral, np.integer)):
          return np.random.RandomState(seed)
      if isinstance(seed, np.random.RandomState):
          return seed
      raise ValueError('%r cannot be used to seed a numpy.random.RandomState'
                       ' instance' % seed)
  
  
  def convert_to_float(image, preserve_range):
      """Convert input image to double image with the appropriate range.
  
      Parameters
      ----------
      image : ndarray
          Input image.
      preserve_range : bool
          Determines if the range of the image should be kept or transformed
          using img_as_float. Also see
          https://scikit-image.org/docs/dev/user_guide/data_types.html
  
      Returns
      -------
      image : ndarray
          Transformed version of the input.
      """
      if preserve_range:
          image = image.astype(np.double)
      else:
          image = img_as_float(image)
      return image
  