def test_load_from_disk(self):
# Generate a tmp fake data structure
img_per_cat = {2: range(1, 10), 8: range(30, 40), 111: range(6, 15)}
path, _ = create_tmp_structure(img_per_cat)
l = loader.LoadFromDisk(impath=path)
for cat in img_per_cat.keys():
for image in img_per_cat[cat]:
l.get_image(cat, image)
self.assertTrue(l.test_for_category(cat))
self.assertTrue(l.test_for_image(cat, image))
# Test checks for non existing images
no_img_per_cat = {0: range(1, 10), 7: range(30, 40), 110: range(6, 15)}
for cat in no_img_per_cat.keys():
for image in no_img_per_cat[cat]:
self.assertTrue(not l.test_for_category(cat))
self.assertTrue(not l.test_for_image(cat, image))
no_img_per_cat = {
2: range(11, 20),
8: range(20, 30),
111: range(16, 40)
}
for cat in no_img_per_cat.keys():
for image in no_img_per_cat[cat]:
self.assertTrue(not l.test_for_image(cat, image))
rm_tmp_structure(path)
def test_save_to_disk(self):
path = mkdtemp()
ftrpath = mkdtemp()
im_tmp = np.ones((100, 100))
l = loader.SaveToDisk(impath=path, ftrpath=ftrpath, size=(10, 10))
# Generate a tmp fake data structure
img_per_cat = {
2: list(range(1, 10)),
8: list(range(30, 40)),
111: list(range(6, 15))
}
for cat in list(img_per_cat.keys()):
# Create category dir
for image in img_per_cat[cat]:
l.save_image(cat, image, im_tmp)
for f in ['a', 'b']:
l.save_feature(cat, image, f, np.ones((10, 10)))
l = loader.LoadFromDisk(impath=path, ftrpath=ftrpath, size=(10, 10))
for cat in list(img_per_cat.keys()):
for image in img_per_cat[cat]:
im = l.get_image(cat, image)
self.assertTrue(im.shape[0] == 10 and im.shape[1] == 10)
self.assertTrue(l.test_for_category(cat))
self.assertTrue(l.test_for_image(cat, image))
self.assertTrue(l.test_for_feature(cat, image, 'a'), True)
os.system('rm -rf %s' % path)
os.system('rm -rf %s' % ftrpath)
def test_load_from_disk_scaling(self):
# Generate a tmp fake data structure
img_per_cat = {2: range(1, 10), 8: range(30, 40), 111: range(6, 15)}
path, _ = create_tmp_structure(img_per_cat)
l = loader.LoadFromDisk(impath=path, size=(10, 10))
for cat in img_per_cat.keys():
for image in img_per_cat[cat]:
im = l.get_image(cat, image)
self.assertTrue(im.shape[0] == 10 and im.shape[1] == 10)
self.assertTrue(l.test_for_category(cat))
self.assertTrue(l.test_for_image(cat, image))
rm_tmp_structure(path)
def test_getattr(self):
# Test the
# Set up a fake dir structure to generate an aligned fixmat
img_per_cat = {1: range(1, 11), 2: range(1, 11)}
features = ['a', 'b']
path, ftrpath = test_loader.create_tmp_structure(img_per_cat,
features=features)
l = loader.LoadFromDisk(impath=path, ftrpath=ftrpath, size=(100, 100))
inp = stimuli.Categories(l, img_per_cat, features)
fm = fixmat.TestFixmatFactory(categories=[1, 2],
filenumbers=range(1, 11),
subjectindices=[1, 2, 3, 4, 5, 6],
params={
'pixels_per_degree': 10,
'image_size': [100, 100]
},
categories_obj=inp)
fm_err = fixmat.TestFixmatFactory(categories=[1, 2],
filenumbers=range(1, 11),
subjectindices=[1, 2, 3, 4, 5, 6],
params={
'pixels_per_degree': 10,
'image_size': [100, 100]
})
# Now let's check if we can access all the images
# and all the features.
fm.add_feature_values(['a', 'b'])
self.assertRaises(RuntimeError,
lambda: fm_err.add_feature_values(['a', 'b']))
for cat_mat, cat_inp in fm.by_cat():
self.assertEquals(cat_mat.category[0], cat_inp.category)
for img_mat, img_inp in cat_mat.by_filenumber():
self.assertEquals(img_mat.filenumber[0], img_inp.image)
self.assertEquals(len(fm.a), len(fm.x))
self.assertEquals(len(fm.b), len(fm.x))
# Let's also check if make_reg_data works
a, b = fm.make_reg_data(features)
self.assertEquals(a.shape[1], len(fm.x))
self.assertEquals(a.shape[0], len(features))
self.assertEquals(b.shape[1], len(fm.x))
self.assertEquals(b.shape[0], len(features))
self.assertEquals(b.sum(), a.sum())
a, b = fm.make_reg_data(features, all_controls=True)
self.assertEquals(a.shape[1], len(fm.x))
self.assertEquals(a.shape[0], len(features))
self.assertEquals(b.shape[1], len(fm.x))
self.assertEquals(b.shape[0], len(features))
self.assertEquals(b.sum(), a.sum())
test_loader.rm_tmp_structure(path)
test_loader.rm_tmp_structure(ftrpath)
def test_directory_stimuli_factory(self):
img_per_cat = {1: range(1, 11), 2: range(1, 11)}
features = ['a', 'b']
path, ftrpath = test_loader.create_tmp_structure(img_per_cat,
features=features)
l = loader.LoadFromDisk(impath=path, ftrpath=ftrpath, size=(100, 100))
inp = stimuli.DirectoryStimuliFactory(l)
for cat in img_per_cat.keys():
inp[cat]
for img in img_per_cat[cat]:
inp[cat][img]
inp[cat][img]['a']
inp[cat][img].data
test_loader.rm_tmp_structure(path)
test_loader.rm_tmp_structure(ftrpath)
