Source Code for Module mvpa.measures.ds

 1  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- 
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 4  # 
 5  #   See COPYING file distributed along with the PyMVPA package for the 
 6  #   copyright and license terms. 
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 9  """Dissimilarity measure. 
10   
11  """ 
12   
13  __docformat__ = 'restructuredtext' 
14   
15  import numpy as N 
16  from mvpa.measures.base import DatasetMeasure 
17  from mvpa.misc.stats import DSMatrix 
18   
19 -class DSMDatasetMeasure(DatasetMeasure): 
20      """DSMDatasetMeasure creates a DatasetMeasure object 
21         where metric can be one of 'euclidean', 'spearman', 'pearson' 
22         or 'confusion'""" 
23   
24 -    def __init__(self, dsmatrix, dset_metric, output_metric='spearman'): 
25          DatasetMeasure.__init__(self) 
26   
27          self.dsmatrix = dsmatrix 
28          self.dset_metric = dset_metric 
29          self.output_metric = output_metric 
30          self.dset_dsm = [] 
31   
32   
33 -    def __call__(self, dataset): 
34          # create the dissimilarity matrix for the data in the input dataset 
35          self.dset_dsm = DSMatrix(dataset.samples, self.dset_metric) 
36   
37          in_vec = self.dsmatrix.getVectorForm() 
38          dset_vec = self.dset_dsm.getVectorForm() 
39   
40          # concatenate the two vectors, send to dissimlarity function 
41          test_mat = N.asarray([in_vec, dset_vec]) 
42   
43          test_dsmatrix = DSMatrix(test_mat, self.output_metric) 
44   
45          # return correct dissimilarity value 
46          return test_dsmatrix.getFullMatrix()[0, 1] 
47