old_contents: # Import numerical and plotting libraries
  import numpy as np
  import itertools 
  from scipy.ndimage.filters import gaussian_filter
  
  def smooth(input, sigma, slice):
  	'''
  	Return array of same shape as input.
  	The multidimensional filter is implemented as a sequence of one-dimensional
  	filters.
  	The intermediate arrays are sorted in the same data type as the output.
  
  	Parameters
  	----------
  	input: A numpy array of an image data in one task run
  
  	sigma: The standard deviations for Gaussian kernel.
  
  	slice: The index time of the fourth dimension.
  
  	Returns
  	-------
  	Returned array of same shape as input.
  
  	'''
  	input_slice = input[...,slice]
  	data_array = gaussian_filter(input, sigma)
  	return data_array
  
  
new_contents: 
  # Import Gaussian filter from scipy module
  
  import numpy as np
  import itertools 
  from scipy.ndimage.filters import gaussian_filter
  
  def smooth(input, sigma, slice):
  	'''
  	Return array of same shape as input.
  	The multidimensional filter is implemented as a sequence of one-dimensional
  	filters.
  	The intermediate arrays are sorted in the same data type as the output.
  
  	Parameters
  	----------
  	input: A numpy array of an image data in one task run
  
  	sigma: The standard deviations for Gaussian kernel.
  
  	slice: The index time of the fourth dimension.
  
  	Returns
  	-------
  	Returned array of same shape as input.
  
  	'''
  	input_slice = input[...,slice]
  	data_array = gaussian_filter(input, sigma)
  	return data_array
  
  
subject: Update in smoothingpy