Source Code for Module mvpa.tests.test_datasetfx_sp

  1  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- 
  2  # vi: set ft=python 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  """Unit tests for PyMVPA miscelaneouse functions operating on datasets and requiring SciPy""" 
 10   
 11  import unittest 
 12   
 13  import numpy as N 
 14   
 15  from mvpa.base import externals 
 16   
 17  from mvpa.datasets import Dataset 
 18  from mvpa.datasets.miscfx import removeInvariantFeatures 
 19   
 20  if externals.exists('scipy', raiseException=True): 
 21      from scipy import linalg 
 22  from mvpa.datasets.miscfx import detrend 
 23   
 24 -class MiscDatasetFxSpTests(unittest.TestCase): 
 25   
 26 -    def testDetrend(self): 
 27          thr = 1e-9;                    # threshold for comparison 
 28          samples = N.array( [[1.0, 2, 3, 3, 2, 1], 
 29                              [-2.0, -4, -6, -6, -4, -2]], ndmin=2 ).T 
 30   
 31          chunks = [0, 0, 0, 1, 1, 1] 
 32          chunks_bad = [ 0, 0, 1, 1, 1, 0] 
 33          target_all = N.array( [[-1.0, 0, 1, 1, 0, -1], 
 34                                 [2, 0, -2, -2, 0, 2]], ndmin=2 ).T 
 35   
 36   
 37          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
 38                       copy_samples=True) 
 39          detrend(ds, perchunk=False) 
 40   
 41          self.failUnless(linalg.norm(ds.samples - target_all) < thr, 
 42                  msg="Detrend should have detrended all the samples at once") 
 43   
 44   
 45          ds_bad = Dataset(samples=samples, labels=chunks, chunks=chunks_bad, 
 46                           copy_samples=True) 
 47          self.failUnlessRaises(ValueError, detrend, ds_bad, perchunk=True) 
 48   
 49   
 50          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
 51                       copy_samples=True) 
 52          detrend(ds, perchunk=True) 
 53   
 54          self.failUnless(linalg.norm(ds.samples) < thr, 
 55                      msg="Detrend should have detrended each chunk separately") 
 56   
 57          self.failUnless(ds.samples.shape == samples.shape, 
 58                          msg="Detrend must preserve the size of dataset") 
 59   
 60   
 61          # small additional test for break points 
 62          ds = Dataset(samples=N.array([[1.0, 2, 3, 1, 2, 3]], ndmin=2).T, 
 63                       labels=chunks, chunks=chunks, copy_samples=True) 
 64          detrend(ds, perchunk=True) 
 65          self.failUnless(linalg.norm(ds.samples) < thr, 
 66                          msg="Detrend should have removed all the signal") 
 67   
 68          # tests of the regress version of detrend 
 69          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
 70                       copy_samples=True) 
 71          detrend(ds, perchunk=False, model='regress', polyord=1) 
 72          self.failUnless(linalg.norm(ds.samples - target_all) < thr, 
 73                  msg="Detrend should have detrended all the samples at once") 
 74   
 75          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
 76                       copy_samples=True) 
 77          (res, reg) = detrend(ds, perchunk=True, model='regress', polyord=2) 
 78          psamps = ds.samples.copy() 
 79          self.failUnless(linalg.norm(ds.samples) < thr, 
 80                  msg="Detrend should have detrended each chunk separately") 
 81   
 82          self.failUnless(ds.samples.shape == samples.shape, 
 83                          msg="Detrend must preserve the size of dataset") 
 84   
 85          ods = Dataset(samples=samples, labels=chunks, chunks=chunks, 
 86                        copy_samples=True) 
 87          opt_reg = reg.copy() 
 88          (ores, oreg) = detrend(ods, perchunk=True, model='regress', 
 89                                 opt_reg=opt_reg) 
 90          dsamples = (ods.samples - psamps).sum() 
 91          self.failUnless(abs(dsamples) <= 1e-10, 
 92              msg="Detrend for polyord reg should be same as opt_reg " + \ 
 93                  "when popt_reg is the same as the polyord reg. But got %g" \ 
 94                  % dsamples) 
 95   
 96          self.failUnless(linalg.norm(ds.samples) < thr, 
 97                  msg="Detrend should have detrended each chunk separately") 
 98   
 99   
100          # test of different polyord on each chunk 
101          target_mixed = N.array( [[-1.0, 0, 1, 0, 0, 0], 
102                                   [2.0, 0, -2, 0, 0, 0]], ndmin=2 ).T 
103   
104          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
105                       copy_samples=True) 
106          (res, reg) = detrend(ds, perchunk=True, model='regress', polyord=[0,1]) 
107          self.failUnless(linalg.norm(ds.samples - target_mixed) < thr, 
108              msg="Detrend should have baseline corrected the first chunk, " + \ 
109                  "but baseline and linear detrended the second.") 
110   
111          # test applying detrend in sequence 
112          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
113                       copy_samples=True) 
114          (res, reg) = detrend(ds, perchunk=True, model='regress', polyord=1) 
115          opt_reg = reg[N.ix_(range(reg.shape[0]),[1,3])] 
116          final_samps = ds.samples.copy() 
117          ds = Dataset(samples=samples, labels=chunks, chunks=chunks, 
118                       copy_samples=True) 
119          (res, reg) = detrend(ds, perchunk=True, model='regress', polyord=0) 
120          (res, reg) = detrend(ds, perchunk=True, model='regress', 
121                               opt_reg=opt_reg) 
122          self.failUnless(linalg.norm(ds.samples - final_samps) < thr, 
123                  msg="Detrend of polyord 1 should be same as detrend with " + \ 
124                      "0 followed by opt_reg the same as a 1st order.") 
125   
126   
127   
128 -def suite(): 
129      return unittest.makeSuite(MiscDatasetFxSpTests) 
130   
131   
132  if __name__ == '__main__': 
133      import runner 
134