Source Code for Module mvpa.tests.tests_warehouse_clfs

 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. 
 7  # 
 8  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## 
 9  """Provides `clfs` dictionary with instances of all available classifiers.""" 
10   
11  __docformat__ = 'restructuredtext' 
12   
13  # Some global imports useful through out unittests 
14  from mvpa.base import cfg 
15   
16  # 
17  # first deal with classifiers which do not have external deps 
18  # 
19  from mvpa.clfs.smlr import SMLR 
20  from mvpa.clfs.knn import * 
21   
22  from mvpa.clfs.warehouse import clfswh, regrswh 
23  from mvpa.base import externals 
24   
25  # if have ANY svm implementation 
26  if externals.exists('libsvm') or externals.exists('shogun'): 
27      from mvpa.clfs.svm import * 
28   
29  # 
30  # Few silly classifiers 
31  # 
32 -class SameSignClassifier(Classifier): 
33      """Dummy classifier which reports +1 class if both features have 
34      the same sign, -1 otherwise""" 
35   
36      _clf_internals = ['notrain2predict'] 
37 -    def __init__(self, **kwargs): 
38          Classifier.__init__(self, **kwargs) 
39   
40 -    def _train(self, data): 
41          # we don't need that ;-) 
42          pass 
43   
44 -    def _predict(self, data): 
45          datalen = len(data) 
46          values = [] 
47          for d in data: 
48              values.append(2*int( (d[0]>=0) == (d[1]>=0) )-1) 
49          self.predictions = values 
50          self.values = values            # just for the sake of having values 
51          return values 
52   
53   
54 -class Less1Classifier(SameSignClassifier): 
55      """Dummy classifier which reports +1 class if abs value of max less than 1""" 
56 -    def _predict(self, data): 
57          datalen = len(data) 
58          values = [] 
59          for d in data: 
60              values.append(2*int(max(d)<=1)-1) 
61          self.predictions = values 
62          return values 
63   
64  # Sample universal classifiers (linear and non-linear) which should be 
65  # used whenever it doesn't matter what classifier it is for testing 
66  # some higher level creations -- chosen so it is the fastest universal 
67  # one. Also it should not punch state.py in the face how it is 
68  # happening with kNN... 
69  sample_clf_lin = SMLR(lm=0.1)#sg.svm.LinearCSVMC(svm_impl='libsvm') 
70   
71  #if externals.exists('shogun'): 
72  #    sample_clf_nl = sg.SVM(kernel_type='RBF', svm_impl='libsvm') 
73  #else: 
74  #classical one which was used for a while 
75  #and surprisingly it is not bad at all for the unittests 
76  sample_clf_nl = kNN(k=5) 
77   
78  # and also a regression-based classifier 
79  r = clfswh['linear', 'regression', 'has_sensitivity'] 
80  if len(r) > 0: sample_clf_reg = r[0] 
81  else: sample_clf_reg = None 
82