old_contents: # -*- coding: utf-8 -*-
  
  import numpy as np
  
  NEURON_COMPONENTS = ('soma', 'axon', 'dendrite', 'synapse')
  
  def mean_plus_one(x):
      """Calculate the mean_plus_one value, plus 1 of an input matrix
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      mean_plus_one : float
          The mean_plus_one value in the entire array
      """
      return np.mean(x) + 1
  
  def std_plus_one(x):
      """Calculate the standard deviation, plus 1 of an input matrix
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      std_plus_one : float
          The standard deviation of the entire array
      """
      return np.std(x) + 1
  
  def cv(x):
      """Calculate the coefficient of variation of an entire array
  
      The coefficient of variation is the standard deviation divided by the
      mean_plus_one. It is a measure of the overall dispersion, and is used to
      compare features with different variances and means on the same scale.
      For more reading: http://en.wikipedia.org/wiki/Coefficient_of_variation
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      cv : float
          The coefficient of variation of the entire array
      """
      return mean_plus_one(x)/std_plus_one(x)
  
  def is_neuron_component(component):
      return component in NEURON_COMPONENTS
new_contents: # -*- coding: utf-8 -*-
  
  import numpy as np
  
  __all__ = ['mean_plus_one', 'std_plus_one', 'cv', 'is_neuron_component',
             'NEURON_COMPONENTS']
  
  
  NEURON_COMPONENTS = ('soma', 'axon', 'dendrite', 'synapse')
  
  
  def mean_plus_one(x):
      """Calculate the mean_plus_one value, plus 1 of an input matrix
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      mean_plus_one : float
          The mean_plus_one value in the entire array
      """
      return np.mean(x) + 1
  
  def std_plus_one(x):
      """Calculate the standard deviation, plus 1 of an input matrix
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      std_plus_one : float
          The standard deviation of the entire array
      """
      return np.std(x) + 1
  
  def cv(x):
      """Calculate the coefficient of variation of an entire array
  
      The coefficient of variation is the standard deviation divided by the
      mean_plus_one. It is a measure of the overall dispersion, and is used to
      compare features with different variances and means on the same scale.
      For more reading: http://en.wikipedia.org/wiki/Coefficient_of_variation
  
      Parameters
      ----------
      x : numpy.array
          An n-dimensional numpy array
  
      Returns
      -------
      cv : float
          The coefficient of variation of the entire array
      """
      return mean_plus_one(x)/std_plus_one(x)
  
  def is_neuron_component(component):
      return component in NEURON_COMPONENTS
subject: Add __all__ for export