class_docstr: This class enables the extraction of image features (Harilick
  features) and basic statistics over a segmentation
class_docstr_tok: ["This","class","enables","the","extraction","of","image","features","(","Harilick","features",")","and","basic","statistics","over","a","segmentation"]
docstr: Calculates the sum of square variance over the glcm matrix
  
  :param matrix:
  :return:
docstr_tok: ["Calculates","the","sum","of","square","variance","over","the","glcm","matrix",":","param","matrix",":",":","return",":"]
code: def sum_square_variance(self, matrix):
      """
      Calculates the sum of square variance over the glcm matrix
  
      :param matrix:
      :return:
      """
      ssv = 0
      range_values = np.arange(0, matrix.shape[0])
      matrix_range = np.tile(range_values, [matrix.shape[0], 1])
      mean = np.average(matrix_range * matrix)
      for i in range(0, matrix.shape[0]):
          for j in range(0, matrix.shape[0]):
              ssv += (i - mean) ** 2 * matrix[i, j]
      return ssv
  
imports: from __future__ import absolute_import, print_function, division
  import numpy
  import numpy.ma
  import math
  import scipy.stats.mstats
  import scipy.ndimage
  from niftynet.utilities.util_common import MorphologyOps, CacheFunctionOutput
label_desc: Use image node_id 34 for calling the RegionProperties obj's underlying member method code with example usage: obj.sum_square_variance(matrix) and returns: ssv