def test_ddxi():
testvars = ["salt", "u", "v", "z_w"]
for testvar in testvars:
acc = ds[testvar].xroms.ddxi()
assert np.allclose(acc, xroms.ddxi(ds[testvar], grid))
acc.name == acc.attrs["name"]
acc.attrs["grid"] == ds.xroms.grid
items = [
"T", "X", "Y", "Z", "longitude", "latitude", "vertical", "time"
]
assert set(items).issubset(acc.cf.get_valid_keys())
acc = ds.xroms.ddxi(testvar)
assert np.allclose(acc, xroms.ddxi(ds[testvar], grid))
acc.name == acc.attrs["name"]
acc.attrs["grid"] == ds.xroms.grid
items = [
"T", "X", "Y", "Z", "longitude", "latitude", "vertical", "time"
]
assert set(items).issubset(acc.cf.get_valid_keys())
def test_ddxi():
# compare away from boundaries and for
# correct dx value (eta=0)
ddxi = (u[2] - u[0]) / (2 * dx)
assert np.allclose(xroms.ddxi(ds.u, grid)[0, 1, 0, 1], ddxi)
def ddxi(
self,
hcoord=None,
scoord=None,
hboundary="extend",
hfill_value=None,
sboundary="extend",
sfill_value=None,
attrs=None,
):
"""Calculate d/dxi for variable.
Inputs
------
hcoord: string, optional.
Name of horizontal grid to interpolate output to.
Options are 'rho', 'psi', 'u', 'v'.
scoord: string, optional.
Name of vertical grid to interpolate output to.
Options are 's_rho', 's_w', 'rho', 'w'.
hboundary: string, optional
Passed to `grid` method calls; horizontal boundary selection
for calculating horizontal derivative of var. This same value
will be used for all horizontal grid changes too.
From xgcm documentation:
A flag indicating how to handle boundaries:
* None: Do not apply any boundary conditions. Raise an error if
boundary conditions are required for the operation.
* 'fill': Set values outside the array boundary to fill_value
(i.e. a Neumann boundary condition.)
* 'extend': Set values outside the array to the nearest array
value. (i.e. a limited form of Dirichlet boundary condition.
hfill_value: float, optional
Passed to `grid` method calls; horizontal boundary selection
fill value.
From xgcm documentation:
The value to use in the boundary condition with `boundary='fill'`.
sboundary: string, optional
Passed to `grid` method calls; vertical boundary selection
for calculating horizontal derivative of var. This same value will
be used for all vertical grid changes too.
From xgcm documentation:
A flag indicating how to handle boundaries:
* None: Do not apply any boundary conditions. Raise an error if
boundary conditions are required for the operation.
* 'fill': Set values outside the array boundary to fill_value
(i.e. a Neumann boundary condition.)
* 'extend': Set values outside the array to the nearest array
value. (i.e. a limited form of Dirichlet boundary condition.
sfill_value: float, optional
Passed to `grid` method calls; vertical boundary selection
fill value.
From xgcm documentation:
The value to use in the boundary condition with `boundary='fill'`.
attrs: dict, optional
Dictionary of attributes to add to resultant arrays. Requires that
q is DataArray. For example:
`attrs={'name': 'varname', 'long_name': 'longvarname', 'units': 'units'}`
Returns
-------
DataArray of dqdxi, the gradient of q in the xi-direction with
attributes altered to reflect calculation.
Notes
-----
dqdxi = dqdx*dzdz - dqdz*dzdx
Derivatives are taken in the ROMS curvilinear grid native xi-direction.
These derivatives properly account for the fact that ROMS vertical coordinates are
s coordinates and therefore can vary in time and space.
This will alter the number of points in the xi and s dimensions.
Example usage
-------------
>>> ds.salt.xroms.ddxi()
"""
return xroms.ddxi(
self.da,
self.da.attrs["grid"],
attrs=attrs,
hcoord=hcoord,
scoord=scoord,
hboundary=hboundary,
hfill_value=hfill_value,
sboundary=sboundary,
sfill_value=sfill_value,
)