Source Code for Module mvpa.tests.test_splitsensana

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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  """Unit tests for PyMVPA SplittingSensitivityAnalyzer""" 
10   
11  from mvpa.datasets.splitters import NFoldSplitter 
12  from mvpa.measures.splitmeasure import SplitFeaturewiseMeasure, \ 
13          TScoredFeaturewiseMeasure 
14  from mvpa.misc.data_generators import normalFeatureDataset 
15  from mvpa.misc.transformers import Absolute 
16  from tests_warehouse import * 
17  from tests_warehouse_clfs import * 
18   
19   
20 -class SplitSensitivityAnalyserTests(unittest.TestCase): 
21   
22      # XXX meta should work TODO 
23      @sweepargs(svm=clfswh['linear', 'svm', '!meta']) 
24 -    def testAnalyzer(self, svm): 
25          dataset = datasets['uni2small'] 
26   
27          svm_weigths = svm.getSensitivityAnalyzer() 
28   
29          sana = SplitFeaturewiseMeasure( 
30                      svm_weigths, 
31                      NFoldSplitter(cvtype=1), 
32                      enable_states=['maps']) 
33   
34          maps = sana(dataset) 
35          nchunks = len(dataset.uniquechunks) 
36          nfeatures = dataset.nfeatures 
37          self.failUnless(len(maps) == nfeatures, 
38              msg='Lengths of the map %d is different from number of features %d' 
39                   % (len(maps), nfeatures)) 
40          self.failUnless(sana.states.isKnown('maps')) 
41          allmaps = N.array(sana.maps) 
42          self.failUnless(allmaps[:,0].mean() == maps[0]) 
43          self.failUnless(allmaps.shape == (nchunks, nfeatures)) 
44   
45   
46      @sweepargs(svm=clfswh['linear', 'svm', '!meta']) 
47 -    def testTScoredAnalyzer(self, svm): 
48          self.dataset = normalFeatureDataset(perlabel=100, 
49                                              nlabels=2, 
50                                              nchunks=20, 
51                                              nonbogus_features=[0,1], 
52                                              nfeatures=4, 
53                                              snr=10) 
54          svm_weigths = svm.getSensitivityAnalyzer() 
55   
56          sana = TScoredFeaturewiseMeasure( 
57                      svm_weigths, 
58                      NFoldSplitter(cvtype=1), 
59                      enable_states=['maps']) 
60   
61          t = sana(self.dataset) 
62   
63          # correct size? 
64          self.failUnlessEqual(t.shape, (4,)) 
65   
66          # check reasonable sensitivities 
67          t = Absolute(t) 
68          self.failUnless(N.mean(t[:2]) > N.mean(t[2:])) 
69   
70          # check whether SplitSensitivityAnalyzer 'maps' state is accessible 
71          self.failUnless(sana.states.isKnown('maps')) 
72          self.failUnless(N.array(sana.maps).shape == (20,4)) 
73   
74   
75   
76 -def suite(): 
77      return unittest.makeSuite(SplitSensitivityAnalyserTests) 
78   
79   
80  if __name__ == '__main__': 
81      import runner 
82