def test_ddeta():
testvars = ["salt", "u", "v", "z_w"]
for testvar in testvars:
acc = ds[testvar].xroms.ddeta()
assert np.allclose(acc, xroms.ddeta(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.ddeta(testvar)
assert np.allclose(acc, xroms.ddeta(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_ddeta():
ddeta = (v[2] - v[0]) / (2 * dy)
assert np.allclose(xroms.ddeta(ds.v, grid)[0, 1, 1, 0], ddeta)
def ddeta(
self,
varname,
hcoord=None,
scoord=None,
hboundary="extend",
hfill_value=None,
sboundary="extend",
sfill_value=None,
attrs=None,
):
"""Calculate d/deta for a variable.
Inputs
------
varname: str
Name of variable in Dataset to operate on.
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 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 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 dqdeta, the gradient of q in the eta-direction with
attributes altered to reflect calculation.
Notes
-----
dqdeta = dqdy*dzdz - dqdz*dzdy
Derivatives are taken in the ROMS curvilinear grid native eta-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 eta and s dimensions.
Example usage
-------------
>>> ds.xroms.ddeta('salt')
"""
assert isinstance(
varname, str
), "varname should be a string of the name of a variable stored in the Dataset"
assert varname in self.ds, 'variable called "varname" must be in Dataset'
return xroms.ddeta(
self.ds[varname],
self.grid,
hcoord=hcoord,
scoord=scoord,
hboundary=hboundary,
hfill_value=hfill_value,
sboundary=sboundary,
sfill_value=sfill_value,
attrs=attrs,
)