def test_most_common_class_with_valid(self):
*_, gl30_10 = random_test_data()
expected = 50
actual = most_common_class(gl30_10)[0]
self.assertEqual(expected, actual)
def test_sample_occupied_with_valid_and_affine(self):
*_, gl30_10 = random_test_data((2, 2))
affine = Affine(30, 0, 0, 0, 30, 0)
expected = [{
'col': 0,
'row': 1,
'x': 0.0,
'y': 30.0,
'label': 80
}, {
'col': 1,
'row': 0,
'x': 30.0,
'y': 0.0,
'label': 50
}, {
'col': 0,
'row': 0,
'x': 0.0,
'y': 0.0,
'label': 90
}]
actual = sample_occupied(gl30_10, affine=affine, seed=42)
self.assertEqual(expected, actual)
def test_superimpose_with_equal_shaped(self):
treecover, loss, gain, _, gl30_10 = random_test_data()
expected = (100, 100)
actual = superimpose(gl30_10, treecover, gain, loss)
self.assertEqual(expected, actual.shape)
self.assertEqual(np.uint8, actual.dtype)
def test_frequency_with_valid(self):
*_, gl30_10 = random_test_data()
expected = OrderedDict(OrderedDict([(0, 877), (10, 888), (20, 919),
(30, 876), (40, 938), (50, 957),
(60, 916), (70, 915), (80, 930),
(90, 903), (100, 881)]))
actual = frequency(gl30_10)
self.assertEqual(expected, actual)
def test_superimpose_with_valid_data(self):
treecover, loss, gain, _, gl30_10 = random_test_data((5, 5))
expected = np.array(
[[0, 0, 0, 0, 0], [30, 60, 0, 0, 0], [10, 0, 0, 40, 50],
[25, 0, 0, 0, 0], [0, 0, 25, 0, 0]],
dtype=np.uint8)
actual = superimpose(gl30_10, treecover, gain, loss)
self.assertTrue(np.array_equal(expected, actual))
def test_reclassify_with_resolution(self):
*_, gl30_10 = random_test_data((5, 5))
expected = np.array(
[[0, 0, 0, 0, 0], [0, 0, 0, 50, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]],
dtype=np.uint8)
actual = reclassify(gl30_10, res=30, side_length=90)
self.assertTrue(np.array_equal(expected, actual))
def test_treecover_similarity_with_mock_data(self):
gfc, *_, gl30, _ = random_test_data()
expected = [0.7075, 0.786, 0.881, 1.0]
actual = treecover_agreement(gl30,
gfc,
canopy_densities=(0, 10, 20, 30),
cover_classes=(20, ))
self.assertEqual(expected, actual)
def test_sample_occupied_with_valid(self):
*_, gl30_10 = random_test_data((2, 2))
expected = [{
'label': 80,
'col': 0,
'row': 1
}, {
'label': 50,
'col': 1,
'row': 0
}, {
'label': 90,
'col': 0,
'row': 0
}]
actual = sample_occupied(gl30_10, seed=42)
self.assertEqual(expected, actual)
def test_superimpose_with_malicious_shapes(self):
a = np.zeros((10, 10), dtype=np.uint8)
treecover, loss, gain, *_ = random_test_data()
with self.assertRaises(ValueError) as err:
superimpose(a, treecover, gain, loss)
