Source Code for Module mvpa.tests.tests_warehouse_clfs

 1  #emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*- 
 2  #ex: set sts=4 ts=4 sw=4 et: 
 3  ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## 
 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  # 
14  # first deal with classifiers which do not have external deps 
15  # 
16  from mvpa.clfs.smlr import SMLR 
17  from mvpa.clfs.knn import * 
18   
19  from mvpa.clfs.warehouse import clfswh, regrswh 
20  from mvpa.base import externals 
21   
22  # if have ANY svm implementation 
23  if externals.exists('libsvm') or externals.exists('shogun'): 
24      from mvpa.clfs.svm import * 
25   
26  # 
27  # Few silly classifiers 
28  # 
29 -class SameSignClassifier(Classifier): 
30      """Dummy classifier which reports +1 class if both features have 
31      the same sign, -1 otherwise""" 
32   
33      _clf_internals = ['notrain2predict'] 
34 -    def __init__(self, **kwargs): 
35          Classifier.__init__(self, **kwargs) 
36   
37 -    def _train(self, data): 
38          # we don't need that ;-) 
39          pass 
40   
41 -    def _predict(self, data): 
42          datalen = len(data) 
43          values = [] 
44          for d in data: 
45              values.append(2*int( (d[0]>=0) == (d[1]>=0) )-1) 
46          self.predictions = values 
47          self.values = values            # just for the sake of having values 
48          return values 
49   
50   
51 -class Less1Classifier(SameSignClassifier): 
52      """Dummy classifier which reports +1 class if abs value of max less than 1""" 
53 -    def _predict(self, data): 
54          datalen = len(data) 
55          values = [] 
56          for d in data: 
57              values.append(2*int(max(d)<=1)-1) 
58          self.predictions = values 
59          return values 
60   
61  # Sample universal classifiers (linear and non-linear) which should be 
62  # used whenever it doesn't matter what classifier it is for testing 
63  # some higher level creations -- chosen so it is the fastest universal 
64  # one. Also it should not punch state.py in the face how it is 
65  # happening with kNN... 
66  sample_clf_lin = SMLR(lm=0.1)#sg.svm.LinearCSVMC(svm_impl='libsvm') 
67   
68  #if externals.exists('shogun'): 
69  #    sample_clf_nl = sg.SVM(kernel_type='RBF', svm_impl='libsvm') 
70  #else: 
71  #classical one which was used for a while 
72  #and surprisingly it is not bad at all for the unittests 
73  sample_clf_nl = kNN(k=5) 
74   
75  # and also a regression-based classifier 
76  r = clfswh['linear', 'regression', 'has_sensitivity'] 
77  if len(r) > 0: sample_clf_reg = r[0] 
78  else: sample_clf_reg = None 
79