def test_generate_coord():
s = CoordinateSchema(
name="zaxis_1",
dims=["zaxis_1"],
value=[1.0],
)
expected = xr.DataArray(name="zaxis_1", dims=["zaxis_1"], data=[1.0])
xr.testing.assert_equal(generate(s), expected)
def test_generate_and_pickle_integration():
x = CoordinateSchema("x", ["x"], np.array([1, 2, 3]))
a = VariableSchema(
"a", ["x"],
ChunkedArray(shape=[3], chunks=[1], dtype=np.dtype("float32")))
ranges = {"a": Range(0, 10)}
ds = DatasetSchema(coords={x.name: x}, variables={a.name: a})
d = generate(ds, ranges)
pickle.dumps(d)
def data_path(tmpdir):
schema_path = pathlib.Path(__file__).parent / "data.zarr.json"
with open(schema_path) as f:
schema = synth.load(f)
ranges = {
"pressure_thickness_of_atmospheric_layer": synth.Range(0.99, 1.01)
}
ds = synth.generate(schema, ranges)
ds.to_zarr(str(tmpdir), consolidated=True)
return str(tmpdir)
def test_cftime_generate():
julian_time_attrs = {
"calendar": "julian",
"calendar_type": "JULIAN",
"cartesian_axis": "T",
"long_name": "time",
"units": "seconds since 2016-08-01T00:15:00.000026",
}
store = {}
group = zarr.open_group(store, mode="w")
arr = group.zeros("time", shape=[1], dtype=np.float64)
arr.attrs.update(julian_time_attrs)
arr.attrs["_ARRAY_DIMENSIONS"] = ["time"]
schema = read_schema_from_zarr(group, coords=["time"])
ds = generate(schema, {})
assert dict(ds.time.attrs) == dict(julian_time_attrs)
def test_generate_regression(regtest):
"""
Note:
regtest fixture provided by pytest-regtest plugin:
https://pypi.org/project/pytest-regtest/
"""
x = CoordinateSchema("x", ["x"], np.array([1, 2, 3]))
a = VariableSchema(
"a",
["x"],
ChunkedArray(shape=[3], chunks=[1], dtype=np.dtype("float32")),
)
ranges = {"a": Range(0, 10)}
ds = DatasetSchema(coords={x.name: x}, variables={a.name: a})
d = generate(ds, ranges)
arr = d.a.values
print(arr, file=regtest)
def _grid_spec(datadir, nx):
scaling_factor = 384 / nx
ranges = {
"dx":
synth.Range(20000 * scaling_factor, 28800 * scaling_factor),
"dy":
synth.Range(20000 * scaling_factor, 28800 * scaling_factor),
"area":
synth.Range(3.6205933e08 * scaling_factor**2,
8.3428736e08 * scaling_factor**2),
}
path = str(datadir.join("grid_spec.json"))
with open(path) as f:
schema = synth.load(f)
ds = synth.generate(schema, ranges)
subset = ds.isel(grid_xt=slice(nx),
grid_yt=slice(nx),
grid_x=slice(nx + 1),
grid_y=slice(nx + 1))
return subset
def __getitem__(self, key: str) -> xr.Dataset:
ds = synth.generate(self._schema).drop("initial_time")
return ds
def open_schema(path_relative_to_file: str) -> xr.Dataset:
path = Path(__file__)
abspath = path.parent / path_relative_to_file
with open(abspath) as f:
return synth.generate(synth.load(f), ranges)
def _generate_from_schema(schema: DatasetSchema):
return {tile: synth.generate(schema, ranges) for tile in tiles}