def test_factories(self):
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm = fixmat.FixmatFactory(ntf.name)
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm2 = fixmat.DirectoryFixmatFactory(os.path.dirname(ntf.name),
glob_str='fix_occ_test*.mat')
self.compare_fixmats(fm, fm2)
self.assertRaises(
ValueError, lambda: fixmat.DirectoryFixmatFactory(
'.', glob_str='xxx*.mat'))
def test_cmp2fixmat(self):
# This test only works with some scipy versions.
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm = fixmat.FixmatFactory(ntf.name)
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm_ref = loadmat(ntf.name, struct_as_record=True)['fixmat'][0][0]
for field in fm._fields:
l1 = fm_ref[field]
l2 = fm.__dict__[field]
self.assertEquals(l1.size, l2.size)
self.assertTrue((l1 == l2).all())
def test_fixmat_input_factory(self):
# Another way to create an input object is with the
# FixmatInputFactory
features = ['a', 'b', 'c', 'd']
img_per_cat = {7: range(1, 65), 8: range(1, 65)}
l = loader.TestLoader(img_per_cat, features, size=(10, 10))
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm = fixmat.FixmatFactory(ntf.name)
fm = fm[fm.category > 0]
inp = stimuli.FixmatStimuliFactory(fm, l)
# Now we can iterate over the input object and get fixations on each image
for cat in inp:
for img in cat:
self.assertEquals(img.fixations.filenumber[0], img.image)
self.assertEquals(img.fixations.category[0], img.category)
def test_fixations(self):
img_per_cat = {7: range(1, 65), 8: range(1, 65)}
l = loader.TestLoader(img_per_cat, size=(10, 10))
with NamedTemporaryFile(mode='w', prefix='fix_occ_test',
suffix='.mat') as ntf:
ntf.write(get_data('ocupy.tests', 'fixmat_demo.mat'))
ntf.seek(0)
fm = fixmat.FixmatFactory(ntf.name)
fm = fm[fm.category > 0]
inp = stimuli.FixmatStimuliFactory(fm, l)
# Now we can iterate over the input object and get fixations on each image
for cat in inp:
for img in cat:
self.assertEqual(img.fixations.filenumber[0], img.image)
self.assertEqual(img.fixations.category[0], img.category)
inp = stimuli.Categories(l, img_per_cat)
self.assertRaises(RuntimeError, lambda: inp.fixations)
self.assertRaises(RuntimeError, lambda: inp[7].fixations)
self.assertRaises(RuntimeError, lambda: inp[7][1].fixations)
def test_anglendiff(self):
fm = fixmat.FixmatFactory('/net/store/users/nwilming/eq/analysis/qoamp/fixmat_photos.mat')
gen = simulator.FixGen(fm)
for angle in [-180, -90, 0, 45, 90, 135]:
print "Running anglendiff test on "+repr(angle)+" degrees."
coord = [(0,0)]
length = 1
cur_angle = [np.nan]
cur_angle.append(angle)
# Create artificial fixmat with fixed angle differences
for j in range(len(fm.x)-1):
coord.append(simulator.calc_xy(coord[-1], cur_angle[-1], length))
cur_angle.append(cur_angle[-1]+angle)
fm.x = np.array([x[0] for x in coord])
fm.y = np.array([x[1] for x in coord])
#XXX Parameter should be None, not "None"
gen.initialize_data(fit=None)
# Use anglendiff to calculate angles and angle_diff
a, l, ad, ld = simulator.anglendiff(fm, return_abs=True)
a = np.round(a[0])
a[a==-180]=180
cur_angle = simulator.reshift(np.array(cur_angle[0:-1]))
# Assign nans to make arrays comparable
cur_angle[np.isnan(a)]=np.nan
cur_angle[np.round(cur_angle)==-180]=180
ad = np.round(simulator.reshift(ad[0][~np.isnan(ad[0])]))
if (angle==180 or angle==-180):
self.assertTrue(np.logical_or(ad==angle, ad==-angle).all())
else:
self.assertTrue((ad==angle).all())
self.assertTrue((a[~np.isnan(a)]==cur_angle[~np.isnan(cur_angle)]).all())
