SciPy 0.6.0 API Documentation Generated by Endo, 2007-10-17

Function summary

• center_of_mass(input, labels = None, index = None)
• extrema(input, labels = None, index = None)
• find_objects(input, max_label = 0)
• histogram(input, min, max, bins, labels = None, index = None)
• label(input, structure = None, output = None)
• maximum(input, labels = None, index = None)
• maximum_position(input, labels = None, index = None)
• mean(input, labels = None, index = None)
• minimum(input, labels = None, index = None)
• minimum_position(input, labels = None, index = None)
• standard_deviation(input, labels = None, index = None)
• sum(input, labels = None, index = None)
• variance(input, labels = None, index = None)
• watershed_ift(input, markers, structure = None, output = None)

Functions

• center_of_mass(input, labels = None, index = None)

  Calculate the center of mass of of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• extrema(input, labels = None, index = None)

  Calculate the minimum, the maximum and their positions of the

  values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• find_objects(input, max_label = 0)

  Find objects in a labeled array.

  The input must be an array with labeled objects. A list of slices into the array is returned that contain the objects. The list represents a sequence of the numbered objects. If a number is missing, None is returned instead of a slice. If max_label > 0, it gives the largest object number that is searched for, otherwise all are returned.

• histogram(input, min, max, bins, labels = None, index = None)

  Calculate a histogram of of the array.

  The histogram is defined by its minimum and maximum value and the number of bins.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• label(input, structure = None, output = None)

  Label an array of objects.

  The structure that defines the object connections must be symmetric. If no structuring element is provided an element is generated with a squared connectivity equal to one. This function returns a tuple consisting of the array of labels and the number of objects found. If an output array is provided only the number of objects found is returned.

• maximum(input, labels = None, index = None)

  Calculate the maximum of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• maximum_position(input, labels = None, index = None)

  Find the position of the maximum of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• mean(input, labels = None, index = None)

  Calculate the mean of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• minimum(input, labels = None, index = None)

  Calculate the minimum of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• minimum_position(input, labels = None, index = None)

  Find the position of the minimum of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• standard_deviation(input, labels = None, index = None)

  Calculate the standard deviation of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• sum(input, labels = None, index = None)

  Calculate the sum of the values of the array.

  Parameters:	labels : array of integers, same shape as input Assign labels to the values of the array. index : scalar or array A single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where 'labels' is larger than zero.

  Examples

  >>> input =  [0,1,2,3]
  >>> labels = [1,1,2,2]
  >>> sum(input, labels, index=[1,2])
  [1.0, 5.0]
  

• variance(input, labels = None, index = None)

  Calculate the variance of the values of the array.

  The index parameter is a single label number or a sequence of label numbers of the objects to be measured. If index is None, all values are used where labels is larger than zero.

• watershed_ift(input, markers, structure = None, output = None)

  Apply watershed from markers using a iterative forest transform algorithm.

  Negative markers are considered background markers which are processed after the other markers. A structuring element defining the connectivity of the object can be provided. If none is provided an element is generated iwth a squared connecitiviy equal to one. An output array can optionally be provided.

Imported Names