def test_multiple_missing_value_replacement(self):
"""check neighbourhood average is correct when no neighbours contain
missing data."""
missing_data = np.array([[3, 4, 5], [4, -999, -999], [2, -999, 5]])
expected_data = np.array([[3, 4, 5], [4, 4, 5], [2, 3, 5]])
data = replace_missing_values(missing_data)
np.testing.assert_array_equal(expected_data, data)
def handle_missing_data(data):
### Handle Missing Data
for date in data.keys():
missing_data_ratio = missing_ratio(data[date])
#Replace missing data with average of neighbours
if missing_data_ratio:
data[date] = replace_missing_values(data[date])
return data
def test_multiple_missing_value_replacement(self): """check neighbourhood average is correct when no neighbours contain missing data.""" missing_data = np.array([[3,4,5], [4,-999,-999], [2,-999,5]]) expected_data = np.array([[3,4,5], [4,4,5], [2,3,5]]) data = replace_missing_values(missing_data) np.testing.assert_array_equal(expected_data, data)
