def test_BulkFormula_KH07(accuracy):
x = np.array([1, 10])
X = xr.Dataset({
"w": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1))
})
y = 1.3e-3
tau = processing.BulkFormula("ncep_ncar_2007").calculate(X, "w")
for i, _ in enumerate(X.w):
assert math.isclose(tau[i] / np.power(X.w[i], 2), y, rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula_T90(accuracy):
x = np.array([0.5, 1.5, 3 + 1e-10, 15])
X = xr.Dataset({
"w": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1))
})
y = np.array([0.00218, 0.00166, 0.00114, 0.001465])
tau = processing.BulkFormula("trenberth_etal_1990").calculate(X, "w")
for i, _ in enumerate(X.w):
assert math.isclose(tau[i] / np.power(X.w[i], 2),
y[i],
rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula_K00(accuracy):
x = np.array([1, 10])
X = xr.Dataset({
"w": (("x"), x),
"sea_surface_temperature": (("x"), x),
"air_temperature": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1)),
})
y = np.array([0.0010764375, 0.001653, np.nan])
tau = processing.BulkFormula("kara_etal_2000").calculate(X, "w")
for i, _ in enumerate(X.w):
assert math.isclose(tau[i] / np.power(X.w[i], 2),
y[i],
rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula_LY04(accuracy):
x = np.array([1, 2, 0])
X = xr.Dataset({
"w": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1))
})
y = np.array([0.002918, 0.001644, np.nan])
tau = processing.BulkFormula("large_and_yeager_2004").calculate(X, "w")
for i, _ in enumerate(X.w):
if np.isnan(y[i]):
assert np.isnan(tau[i])
else:
assert math.isclose(tau[i] / np.power(X.w[i], 2),
y[i],
rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula_LP81(accuracy):
x = np.array([5, 12, 1, 26])
X = xr.Dataset({
"w": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1))
})
y = np.array([1.2e-3, 0.00127, np.nan, np.nan])
tau = processing.BulkFormula("large_and_pond_1981").calculate(X, "w")
for i, _ in enumerate(X.w):
if np.isnan(y[i]):
assert np.isnan(tau[i])
else:
assert math.isclose(tau[i] / np.power(X.w[i], 2),
y[i],
rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula_YT96(accuracy):
x = np.array([3, 5.9, 6, 12, 26, 27, 1])
X = xr.Dataset({
"w": (("x"), x),
"air_density": (("x"), np.full(x.shape, 1))
})
y = np.array([
0.00217888888888889,
0.001036624533180121,
0.00102,
0.00144,
0.00242,
np.nan,
np.nan,
])
tau = processing.BulkFormula("yelland_and_taylor_1996").calculate(X, "w")
for i, _ in enumerate(X.w):
if np.isnan(y[i]):
assert np.isnan(tau[i])
else:
assert math.isclose(tau[i] / np.power(X.w[i], 2),
y[i],
rel_tol=accuracy)
assert tau.shape == X.w.shape
def test_BulkFormula():
BFC = processing.BulkFormula
assert inspect.isclass(BFC)
BFI = processing.BulkFormula()
assert isinstance(BFI, BFC)