def test_land_average(self):
"""check land average is correct when all neighbours contain
missing data."""
data = np.array([[1, -999, 1], [-999, -999, -999], [1, -999, 1]])
pixel_loc = np.array([1, 1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = 1
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
def test_partial_pixel_average(self):
"""check neighbourhood average is correct when some neighbours contain
missing data."""
data = np.array([[3, 4, 5], [4, -999, -999], [2, -999, 5]])
pixel_loc = np.array([1, 1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = 4
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
def test_complete_pixel_average(self):
"""check neighbourhood average is correct when no neighbours contain
missing data."""
data = np.array([[3, 4, 5], [4, -999, 6], [2, 8, 5]])
pixel_loc = np.array([1, 1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = int(5.5) # All values must be integers
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
def test_land_average(self):
"""check land average is correct when all neighbours contain
missing data."""
data = np.array([[1,-999,1],
[-999,-999,-999],
[1,-999,1]])
pixel_loc = np.array([1,1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = 1
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
def test_partial_pixel_average(self):
"""check neighbourhood average is correct when some neighbours contain
missing data."""
data = np.array([[3,4,5],
[4,-999,-999],
[2,-999,5]])
pixel_loc = np.array([1,1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = 4
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
def test_complete_pixel_average(self):
"""check neighbourhood average is correct when no neighbours contain
missing data."""
data = np.array([[3,4,5],
[4,-999,6],
[2,8,5]])
pixel_loc = np.array([1,1])
neighbours = {
'left_nbor': np.array([0, 1]),
'right_nbor': np.array([2, 1]),
'up_nbor': np.array([1, 0]),
'down_nbor': np.array([1, 1])
}
expected_average = int(5.5) # All values must be integers
average = pixel_average(pixel_loc, neighbours, data)
self.assertEqual(expected_average, average)
