def test_anova(self):
"""Do some extended testing of OneWayAnova
in particular -- compound estimation
"""
m = OneWayAnova() # default must be not compound ?
mc = CompoundOneWayAnova()
ds = datasets['uni2medium']
# For 2 labels it must be identical for both and equal to
# simple OneWayAnova
a, ac = m(ds), mc(ds)
self.assertTrue(a.shape == (1, ds.nfeatures))
self.assertTrue(ac.shape == (len(ds.UT), ds.nfeatures))
assert_array_equal(ac[0], ac[1])
assert_array_equal(a, ac[1])
# check for p-value attrs
if externals.exists('scipy'):
assert_true('fprob' in a.fa.keys())
assert_equal(len(ac.fa), len(ac))
ds = datasets['uni4large']
ac = mc(ds)
if cfg.getboolean('tests', 'labile', default='yes'):
# All non-bogus features must be high for a corresponding feature
self.assertTrue(
(ac.samples[np.arange(4),
np.array(ds.a.nonbogus_features)] >= 1).all())
# All features should have slightly but different CompoundAnova
# values. I really doubt that there will be a case when this
# test would fail just to being 'labile'
self.assertTrue(np.max(np.std(ac, axis=1)) > 0,
msg='In compound anova, we should get different'
' results for different labels. Got %s' % ac)
from mvpa2.generators.partition import NFoldPartitioner
from mvpa2.generators.resampling import Balancer
from mvpa2.misc.errorfx import mean_mismatch_error
from mvpa2.misc.transformers import Absolute, \
DistPValue
from mvpa2.measures.base import Measure, \
TransferMeasure, RepeatedMeasure, CrossValidation
from mvpa2.measures.anova import OneWayAnova, CompoundOneWayAnova
from mvpa2.measures.irelief import IterativeRelief, IterativeReliefOnline, \
IterativeRelief_Devel, IterativeReliefOnline_Devel
_MEASURES_2_SWEEP = [
OneWayAnova(),
CompoundOneWayAnova(postproc=sumofabs_sample()),
IterativeRelief(),
IterativeReliefOnline(),
IterativeRelief_Devel(),
IterativeReliefOnline_Devel()
]
if externals.exists('scipy'):
from mvpa2.measures.corrcoef import CorrCoef
_MEASURES_2_SWEEP += [
CorrCoef(),
# that one is good when small... handle later
#CorrCoef(pvalue=True)
]
class SensitivityAnalysersTests(unittest.TestCase):