def test_append_iwc(iwc_source_file, iwc_cat_file):
from cloudnetpy.products.iwc import _append_iwc
ice_class = _IceClassification(iwc_cat_file)
ice_class.ice_above_rain = np.array([0, 0, 1])
ice_data = IwcSource(iwc_source_file)
ice_data.data['iwc_inc_rain'] = [1, 1, 1]
_append_iwc(ice_data, ice_class)
assert 'iwc' in ice_data.data.keys()
def test_append_iwc_indices(iwc_source_file, iwc_cat_file):
from cloudnetpy.products.iwc import _append_iwc
ice_class = _IceClassification(iwc_cat_file)
ice_class.ice_above_rain = np.array([0, 0, 1])
ice_data = IwcSource(iwc_source_file)
ice_data.data['iwc_inc_rain'] = [1, 1, 1]
_append_iwc(ice_data, ice_class)
x = ice_data.data['iwc'][:]
x = x.mask
assert np.alltrue(x[:2])
def test_append_iwc_status(iwc_source_file, value):
from cloudnetpy.products.iwc import _append_iwc_status
ice_class = IceClass()
ice_data = IwcSource(iwc_source_file)
ice_data.data['iwc'] = np.ma.array([[1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1]],
mask=[[True, True, False, False, False, False],
[True, True, True, False, False, False]])
_append_iwc_status(ice_data, ice_class)
assert value in ice_data.data['iwc_retrieval_status'][:]
def test_append_iwc_status(categorize_file):
iwc_source = IwcSource(categorize_file)
ice_class = IceClassification(categorize_file)
iwc_source.data['iwc'] = ma.array([[1, 1], [1, 1], [1, 1]],
dtype=float,
mask=[[1, 0], [0, 0], [0, 0]])
ice_class.is_ice = np.array([[1, 0], [0, 0], [0, 0]], dtype=bool)
ice_class.corrected_ice = np.array([[0, 0], [1, 0], [0, 1]], dtype=bool)
ice_class.uncorrected_ice = np.array([[0, 0], [0, 1], [1, 0]], dtype=bool)
ice_class.cold_above_rain = np.array([[0, 0], [0, 0], [1, 0]], dtype=bool)
ice_class.ice_above_rain = np.array([[0, 0], [0, 0], [0, 1]], dtype=bool)
ice_class.would_be_ice = np.array([[0, 0], [0, 0], [0, 0]], dtype=bool)
iwc_source.append_status(ice_class)
for value in range(1, 7):
assert value in iwc_source.data['iwc_retrieval_status'][:]
def test_append_iwc_including_rain(iwc_source_file, iwc_cat_file):
from cloudnetpy.products.iwc import _append_iwc_including_rain
ice_class = _IceClassification(iwc_cat_file)
ice_class.is_ice = np.array([0, 0, 1])
ice_data = IwcSource(iwc_source_file)
_append_iwc_including_rain(ice_data, ice_class)
assert 'iwc_inc_rain' in ice_data.data.keys()
def test_iwc_error(iwc_source_file, iwc_cat_file):
from cloudnetpy.products.iwc import _append_iwc_error
ice_data = IwcSource(iwc_source_file)
ice_class = _IceClassification(iwc_cat_file)
ice_class.uncorrected_ice = np.array([1, 0, 1])
ice_class.is_ice = np.array([0, 0, 1])
ice_class.ice_above_rain = np.array([1, 1, 0])
_append_iwc_error(ice_data, ice_class)
assert 'iwc_error' in ice_data.data.keys()
def test_append_iwc_including_rain_indices(iwc_source_file, iwc_cat_file):
from cloudnetpy.products.iwc import _append_iwc_including_rain
ice_class = _IceClassification(iwc_cat_file)
ice_class.is_ice = np.array([0, 0, 1])
ice_data = IwcSource(iwc_source_file)
_append_iwc_including_rain(ice_data, ice_class)
x = ice_data.data['iwc_inc_rain'][:]
x = x.mask
assert np.alltrue(x[1:])
class TestAppending:
@pytest.fixture(autouse=True)
def run_before_tests(self, categorize_file):
self.ice_class = IceClassification(categorize_file)
self.iwc_source = IwcSource(categorize_file)
def test_append_iwc_including_rain(self):
self.ice_class.is_ice = np.array([[0, 1], [1, 1], [0, 0]], dtype=bool)
self.iwc_source.append_iwc_including_rain(self.ice_class)
expected_mask = [[1, 0], [0, 0], [1, 1]]
assert_array_equal(self.iwc_source.data['iwc_inc_rain'][:].mask,
expected_mask)
def test_append_iwc(self):
self.ice_class.ice_above_rain = np.array([0, 0, 0, 1, 1], dtype=bool)
self.iwc_source.data['iwc_inc_rain'] = ma.array([1, 2, 3, 4, 5],
mask=[1, 0, 1, 0, 1])
self.iwc_source.append_iwc(self.ice_class)
expected_mask = [1, 0, 1, 1, 1]
assert_array_equal(self.iwc_source.data['iwc'][:].mask, expected_mask)
def test_iwc_error(self):
self.ice_class.is_ice = np.array([[0, 0], [0, 1], [1, 1]], dtype=bool)
self.ice_class.ice_above_rain = np.array([[1, 0], [1, 0], [1, 0]],
dtype=bool)
self.iwc_source.append_error(self.ice_class)
expected_mask = [[1, 1], [1, 0], [1, 0]]
assert_array_equal(self.iwc_source.data['iwc_error'][:].mask,
expected_mask)
def test_append_sensitivity(self):
self.iwc_source.append_sensitivity()
assert self.iwc_source.data['iwc_sensitivity'][:].shape == (2, )
def test_append_bias(self):
self.iwc_source.append_bias()
assert isinstance(self.iwc_source.data['iwc_bias'].data[()], float)
def test_iwc_spec_liq_atten(iwc_source_file):
obj = IwcSource(iwc_source_file)
compare = 1
assert compare == obj.spec_liq_atten
def test_iwc_wl_band(iwc_source_file):
obj = IwcSource(iwc_source_file)
compare = 0
assert compare == obj.wl_band
def test_append_bias(iwc_source_file):
from cloudnetpy.products.iwc import _append_iwc_bias
ice_data = IwcSource(iwc_source_file)
_append_iwc_bias(ice_data)
assert 'iwc_bias' in ice_data.data.keys()
def test_append_sensitivity(iwc_source_file):
from cloudnetpy.products.iwc import _append_iwc_sensitivity
ice_data = IwcSource(iwc_source_file)
ice_data.mean_temperature = np.array([1.5])
_append_iwc_sensitivity(ice_data)
assert 'iwc_sensitivity' in ice_data.data.keys()
def test_iwc_temperature(iwc_source_file):
obj = IwcSource(iwc_source_file)
compare = np.array([[8.85, 6.85, 4.85],
[12.85, 10.85, 8.85],
[10.85, 8.85, 6.85]])
testing.assert_almost_equal(compare, obj.temperature)
def test_iwc_temperature(categorize_file):
obj = IwcSource(categorize_file)
expected = [[6.85, 16.85], [6.85, 16.85], [6.85, 16.85]]
testing.assert_almost_equal(obj.temperature, expected)
def test_iwc_coeffs(result, categorize_file):
obj = IwcSource(categorize_file)
assert result in obj.coeffs._fields
assert obj.coeffs == (0.878, 0.000242, -0.0186, 0.0699, -1.63)
def test_iwc_wl_band(categorize_file):
obj = IwcSource(categorize_file)
assert obj.wl_band == 0
def test_iwc_z_factor(iwc_source_file):
obj = IwcSource(iwc_source_file)
Coefficients = namedtuple('Coefficients', 'K2liquid0')
obj.coeffs = Coefficients(10)
compare = -0.25
assert compare == round(obj.z_factor, 3)
def test_iwc_coeffs(result, iwc_source_file):
obj = IwcSource(iwc_source_file)
assert result in obj.coeffs._fields
def run_before_tests(self, categorize_file):
self.ice_class = IceClassification(categorize_file)
self.iwc_source = IwcSource(categorize_file)
def test_iwc_mean_temperature(iwc_source_file):
obj = IwcSource(iwc_source_file)
compare = np.array([10.85, 8.85, 6.85])
testing.assert_almost_equal(compare, obj.mean_temperature)
def test_iwc_mean_temperature(iwc_source_file):
# TODO: test with different model grid
obj = IwcSource(iwc_source_file)
compare = np.array([10.85, 8.85, 6.85])
testing.assert_almost_equal(compare, obj.mean_temperature)