def test_continents_not_normalised():
p = GeoPickler('', 'out_dir')
data_dict = {}
data_dict['A_DIV'] = (np.random.randn(9, 18) * 255).astype(np.int8)
data_dict['A_cont'] = (np.random.randn(9, 18) * 255).astype(np.int8)
old_max = np.max(data_dict['A_cont'].ravel())
old_min = np.min(data_dict['A_cont'].ravel())
p.normalise_continuous_data(data_dict)
assert (np.max(data_dict['A_cont'].ravel()) == old_max)
assert (np.min(data_dict['A_cont'].ravel()) == old_min)
non_zero = np.where(data_dict['A_cont'] > 0)
zero = np.where(data_dict['A_cont'] <= 0)
assert (len(zero) > 0)
p.process_continents(data_dict)
assert (np.max(data_dict['cont'].ravel()) == 1)
assert (np.min(data_dict['cont'].ravel()) == 0)
assert ((data_dict['cont'][non_zero] == 1).all())
assert ((data_dict['cont'][zero] == 0).all())
def test_normalises_continuous_data(fake_geo_data):
dataroot, _, _, _ = fake_geo_data
p = GeoPickler(dataroot)
p.collect_all()
p.group_by_series()
data_dict = p.get_data_dict(0, 0)
p.normalise_continuous_data(data_dict)
assert (np.max(data_dict['A_DIV'].ravel()) == 1.0)
assert (np.min(data_dict['A_DIV'].ravel()) == -1.0)
assert (np.max(data_dict['A_Vx'].ravel()) == 1.0)
assert (np.min(data_dict['A_Vx'].ravel()) == -1.0)
assert (np.max(data_dict['A_Vy'].ravel()) == 1.0)
assert (np.min(data_dict['A_Vy'].ravel()) == -1.0)