old_contents: from __future__ import print_function, division
  import numpy as np
  import sys
  if sys.version_info < (3,):
      scalarTypes = (float, int, long, np.float64, np.int64, np.int32)
  else:
      scalarTypes = (float, int, np.float64, np.int64, np.int32)
  
  
  def isScalar(f):
      if isinstance(f, scalarTypes):
          return True
      elif isinstance(f, np.ndarray) and f.size == 1 and type(f[0]) in scalarTypes:
          return True
      return False
  
  
  def asArray_N_x_Dim(pts, dim):
          if type(pts) == list:
              pts = np.array(pts)
          assert isinstance(pts, np.ndarray), "pts must be a numpy array"
  
          if dim > 1:
              pts = np.atleast_2d(pts)
          elif len(pts.shape) == 1:
              pts = pts[:, np.newaxis]
  
          assert pts.shape[1] == dim, "pts must be a column vector of shape (nPts, {0:d}) not ({1:d}, {2:d})".format(*((dim,)+pts.shape))
  
          return pts
  
  
  def requires(modules):
      """Decorator to wrap functions with soft dependencies.
  
      This function was inspired by the `requires` function of pysal,
      which is released under the 'BSD 3-Clause "New" or "Revised" License'.
  
      https://github.com/pysal/pysal/blob/master/pysal/lib/common.py
  
      Parameters
      ----------
      modules : dict
          Dictionary containing soft dependencies, e.g.,
          {'matplotlib': matplotlib}.
  
      Returns
      -------
      decorated_function : function
          Original function if all soft dependencies are met, otherwise
          it returns an empty function which prints why it is not running.
  
      """
  
      # Check the required modules, add missing ones in the list `missing`.
      missing = []
      for key, item in modules.items():
          if item is False:
              missing.append(key)
  
      def decorated_function(function):
          """Wrap function."""
          if not missing:
              return function
          else:
              def passer(*args, **kwargs):
                  print(('Missing dependencies: {d}.'.format(d=missing)))
                  print(('Not running `{}`.'.format(function.__name__)))
              return passer
  
      return decorated_function
  
new_contents: from __future__ import print_function, division
  import numpy as np
  import sys
  
  
  scalarTypes = (float, int, np.float_, np.float64, np.int64, np.int32, np.number)
  if sys.version_info < (3,):
      scalarTypes += (long, )
  
  def isScalar(f):
      if isinstance(f, scalarTypes):
          return True
      elif isinstance(f, np.ndarray) and f.size == 1 and type(f[0]) in scalarTypes:
          return True
      return False
  
  
  def asArray_N_x_Dim(pts, dim):
          if type(pts) == list:
              pts = np.array(pts)
          assert isinstance(pts, np.ndarray), "pts must be a numpy array"
  
          if dim > 1:
              pts = np.atleast_2d(pts)
          elif len(pts.shape) == 1:
              pts = pts[:, np.newaxis]
  
          assert pts.shape[1] == dim, "pts must be a column vector of shape (nPts, {0:d}) not ({1:d}, {2:d})".format(*((dim,)+pts.shape))
  
          return pts
  
  
  def requires(modules):
      """Decorator to wrap functions with soft dependencies.
  
      This function was inspired by the `requires` function of pysal,
      which is released under the 'BSD 3-Clause "New" or "Revised" License'.
  
      https://github.com/pysal/pysal/blob/master/pysal/lib/common.py
  
      Parameters
      ----------
      modules : dict
          Dictionary containing soft dependencies, e.g.,
          {'matplotlib': matplotlib}.
  
      Returns
      -------
      decorated_function : function
          Original function if all soft dependencies are met, otherwise
          it returns an empty function which prints why it is not running.
  
      """
  
      # Check the required modules, add missing ones in the list `missing`.
      missing = []
      for key, item in modules.items():
          if item is False:
              missing.append(key)
  
      def decorated_function(function):
          """Wrap function."""
          if not missing:
              return function
          else:
              def passer(*args, **kwargs):
                  print(('Missing dependencies: {d}.'.format(d=missing)))
                  print(('Not running `{}`.'.format(function.__name__)))
              return passer
  
      return decorated_function
  
subject: use np.number in the isinstance check of isScalar - I think this is related to https://github.com/numpy/numpy/issues/2543