def test_all(self):
data_path = 'data'
data_splits_path = '../outputs/data_splits.json'
input_patch_size = core.patch_size()
dat = core.Data(data_splits_path, data_path, input_patch_size)
self.assertTrue(len(dat.train_set) > 0)
self.assertTrue(len(dat.validation_set) > 0)
self.assertTrue(len(dat.test_set) > 0)
self.assertTrue(len(dat.train_files) > 0)
self.assertTrue(len(dat.validation_files) > 0)
self.assertTrue(len(dat.test_files) > 0)
def test_generator_len2(self):
data_list = [('data/input1.npy', 'data/output1.npy'),
('data/input2.npy', 'data/output2.npy')]
input_patch_size = core.patch_size()
gen = core.keras_generator(data_list, input_patch_size)
i = 1
for sample in gen:
if i > 15:
break
self.assertEqual(2, len(sample))
self.assertEqual((8, 360, 50, 6), sample[0].shape)
self.assertEqual((8, 360, 50), sample[1].shape)
i += 1
def test_example(self):
fpath_in = 'data/input1.npy'
fpath_out = 'data/output1.npy'
input_patch_size = core.patch_size()
gen = core.patch_generator(fpath_in, fpath_out, input_patch_size)
i = 1
for sample in gen:
if i > 15:
break
self.assertEqual(sorted(['X', 'Y']), sorted(sample.keys()))
self.assertEqual((1, 360, 50, 6), sample['X'].shape)
self.assertEqual((1, 360, 50), sample['Y'].shape)
i += 1
def test_patch_size(self):
expected = (360, 50)
actual = core.patch_size()
self.assertEqual(expected, actual)