def test_kf_1d_nonzero_mean(uvw_and_known_kf_nonzero_mean):
"""Test kinematic flux calculation in 1D with non-zero-mean time series."""
u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
assert_array_equal(kinematic_flux(u, v, perturbation=False),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False),
kf_true['vw'])
def test_kf_1d_nonzero_mean(uvw_and_known_kf_nonzero_mean):
"""Test kinematic flux calculation in 1D with non-zero-mean time series."""
u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
assert_array_equal(kinematic_flux(u, v, perturbation=False),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False),
kf_true['vw'])
def test_kf_2d_axis_first_nonzero_mean(uvw_and_known_kf_nonzero_mean):
"""Test kinematic flux in 2D with non-zero-mean time series along first axis."""
u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
u = np.array([u, u, u]).transpose()
v = np.array([v, v, v]).transpose()
w = np.array([w, w, w]).transpose()
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
kf_true['vw'])
def test_kf_2d_axis_last_nonzero_mean(uvw_and_known_kf_nonzero_mean):
"""Test kinematic flux calculation in 2D with non-zero-mean time series along last axis."""
u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
u = np.array([u, u, u])
v = np.array([v, v, v])
w = np.array([w, w, w])
for key in kf_true.keys():
tmp = kf_true[key]
kf_true[key] = np.array([tmp, tmp, tmp])
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kf_true['vw'])
def test_kf_2d_axis_last_nonzero_mean(uvw_and_known_kf_nonzero_mean):
"""Test kinematic flux calculation in 2D with non-zero-mean time series along last axis."""
u, v, w, kf_true = uvw_and_known_kf_nonzero_mean
u = np.array([u, u, u])
v = np.array([v, v, v])
w = np.array([w, w, w])
for key in kf_true.keys():
tmp = kf_true[key]
kf_true[key] = np.array([tmp, tmp, tmp])
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kf_true['vw'])
def test_kf_1d_zero_mean(uvw_and_known_kf_zero_mean):
"""Test kinematic flux calculation in 1D with zero-mean time series."""
u, v, w, kf_true = uvw_and_known_kf_zero_mean
assert_array_equal(kinematic_flux(u, v, perturbation=False), kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False), kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False), kf_true['vw'])
# given u, v, and w have a zero mean, the kf computed with
# perturbation=True and perturbation=False should be the same
assert_array_equal(kinematic_flux(u, v, perturbation=False),
kinematic_flux(u, v, perturbation=True))
assert_array_equal(kinematic_flux(u, w, perturbation=False),
kinematic_flux(u, w, perturbation=True))
assert_array_equal(kinematic_flux(v, w, perturbation=False),
kinematic_flux(v, w, perturbation=True))
def test_kf_1d_zero_mean(uvw_and_known_kf_zero_mean):
"""Test kinematic flux calculation in 1D with zero-mean time series."""
u, v, w, kf_true = uvw_and_known_kf_zero_mean
assert_array_equal(kinematic_flux(u, v, perturbation=False),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False),
kf_true['vw'])
# given u, v, and w have a zero mean, the kf computed with
# perturbation=True and perturbation=False should be the same
assert_array_equal(kinematic_flux(u, v, perturbation=False),
kinematic_flux(u, v, perturbation=True))
assert_array_equal(kinematic_flux(u, w, perturbation=False),
kinematic_flux(u, w, perturbation=True))
assert_array_equal(kinematic_flux(v, w, perturbation=False),
kinematic_flux(v, w, perturbation=True))
def test_kf_2d_axis_first_zero_mean(uvw_and_known_kf_zero_mean):
"""Test kinematic flux calculation in 2D with zero-mean time series along first axis."""
u, v, w, kf_true = uvw_and_known_kf_zero_mean
u = np.array([u, u, u]).transpose()
v = np.array([v, v, v]).transpose()
w = np.array([w, w, w]).transpose()
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
kf_true['vw'])
# given u, v, and w have a zero mean, the kf computed with
# perturbation=True and perturbation=False should be the same
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=0),
kinematic_flux(u, v, perturbation=True, axis=0))
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=0),
kinematic_flux(u, w, perturbation=True, axis=0))
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=0),
kinematic_flux(v, w, perturbation=True, axis=0))
def test_kf_2d_axis_last_zero_mean(uvw_and_known_kf_zero_mean):
"""Test kinematic flux calculation in 2D with zero-mean time series along last axis."""
u, v, w, kf_true = uvw_and_known_kf_zero_mean
u = np.array([u, u, u])
v = np.array([v, v, v])
w = np.array([w, w, w])
for key in kf_true.keys():
tmp = kf_true[key]
kf_true[key] = np.array([tmp, tmp, tmp])
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kf_true['vw'])
# given u, v, and w have a zero mean, the kf computed with
# perturbation=True and perturbation=False should be the same
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kinematic_flux(u, v, perturbation=True, axis=-1))
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kinematic_flux(u, w, perturbation=True, axis=-1))
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kinematic_flux(v, w, perturbation=True, axis=-1))
def test_kf_2d_axis_last_zero_mean(uvw_and_known_kf_zero_mean):
"""Test kinematic flux calculation in 2D with zero-mean time series along last axis."""
u, v, w, kf_true = uvw_and_known_kf_zero_mean
u = np.array([u, u, u])
v = np.array([v, v, v])
w = np.array([w, w, w])
for key in kf_true.keys():
tmp = kf_true[key]
kf_true[key] = np.array([tmp, tmp, tmp])
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kf_true['uv'])
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kf_true['uw'])
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kf_true['vw'])
# given u, v, and w have a zero mean, the kf computed with
# perturbation=True and perturbation=False should be the same
assert_array_equal(kinematic_flux(u, v, perturbation=False, axis=-1),
kinematic_flux(u, v, perturbation=True, axis=-1))
assert_array_equal(kinematic_flux(u, w, perturbation=False, axis=-1),
kinematic_flux(u, w, perturbation=True, axis=-1))
assert_array_equal(kinematic_flux(v, w, perturbation=False, axis=-1),
kinematic_flux(v, w, perturbation=True, axis=-1))