def test_derivative_uniform_grid(self):
# this is a uniform grid
# a non-uniform grid would provide a more rigorous test
dx = 10.0
dy = 10.0
arr = [
[1.0, 2.0, 4.0, 3.0],
[4.0, 7.0, 1.0, 2.0],
[3.0, 1.0, 0.0, 9.0],
[8.0, 5.0, 2.0, 1.0],
]
ds = xr.Dataset(
{"foo": (("XC", "YC"), arr)},
coords={
"XC": (("XC", ), [0.5, 1.5, 2.5, 3.5]),
"XG": (("XG", ), [0, 1.0, 2.0, 3.0]),
"dXC": (("XC", ), [dx, dx, dx, dx]),
"dXG": (("XG", ), [dx, dx, dx, dx]),
"YC": (("YC", ), [0.5, 1.5, 2.5, 3.5]),
"YG": (("YG", ), [0, 1.0, 2.0, 3.0]),
"dYC": (("YC", ), [dy, dy, dy, dy]),
"dYG": (("YG", ), [dy, dy, dy, dy]),
},
)
grid = Grid(
ds,
coords={
"X": {
"center": "XC",
"left": "XG"
},
"Y": {
"center": "YC",
"left": "YG"
},
},
metrics={
("X", ): ["dXC", "dXG"],
("Y", ): ["dYC", "dYG"]
},
periodic=True,
)
# Test x direction
dfoo_dx = grid.derivative(ds.foo, "X")
expected = grid.diff(ds.foo, "X") / dx
assert dfoo_dx.equals(expected)
# Test y direction
dfoo_dy = grid.derivative(ds.foo, "Y")
expected = grid.diff(ds.foo, "Y") / dy
assert dfoo_dy.equals(expected)
def test_derivative_uniform_grid():
# this is a uniform grid
# a non-uniform grid would provide a more rigorous test
dx = 10.0
ds = xr.Dataset(
{"foo": (("XC",), [1.0, 2.0, 4.0, 3.0])},
coords={
"XC": (("XC",), [0.5, 1.5, 2.5, 3.5]),
"XG": (("XG",), [0, 1.0, 2.0, 3.0]),
"dXC": (("XC",), [dx, dx, dx, dx]),
"dXG": (("XG",), [dx, dx, dx, dx]),
},
)
grid = Grid(
ds,
coords={"X": {"center": "XC", "left": "XG"}},
metrics={("X",): ["dXC", "dXG"]},
periodic=True,
)
dfoo_dx = grid.derivative(ds.foo, "X")
expected = grid.diff(ds.foo, "X") / dx
assert dfoo_dx.equals(expected)
