def round_coordinates(cubes, decimals=5):
"""Round all dimensional coordinates of all cubes."""
for cube in cubes:
for coord in cube.coords(dim_coords=True):
coord.points = da.round(da.asarray(coord.core_points()), decimals)
if coord.bounds is not None:
coord.bounds = da.round(da.asarray(coord.core_bounds()),
decimals)
return cubes
def _fix_units(cube):
"""Correct the units."""
if cube.var_name in {'e', 'sf'}:
# Change evaporation and snowfall units from
# 'm of water equivalent' to m
cube.units = 'm'
if cube.var_name == 'tcc':
# Change cloud cover units '(0 - 1)' to valid fraction unit
cube.units = 1
if cube.var_name in {'e', 'ro', 'sf', 'tp', 'pev'}:
# Change units from meters of water to kg of water
# and add missing 'per hour'
cube.units = cube.units * 'kg m-3 h-1'
cube.data = cube.core_data() * 1000.
if cube.var_name in {'ssr', 'ssrd', 'strd', 'tisr'}:
# Add missing 'per hour'
cube.units = cube.units * 'h-1'
if cube.var_name in {'msnlwrf', 'ssrd', 'strd', 'tisr', 'ssr'}:
# Radiation fluxes are positive in downward direction
cube.attributes['positive'] = 'down'
if cube.var_name == 'ptype':
cube.units = 1
# Fix rounding errors and mask out 0 (reserved value)
cube.data = da.ma.masked_equal(da.round(cube.core_data()), 0)
return cube
def test_round():
x = np.random.random(10)
d = da.from_array(x, chunks=4)
for i in (0, 1, 4, 5):
assert_eq(x.round(i), d.round(i))
assert_eq(d.round(2), da.round(d, 2))
def test_round():
x = np.random.random(10)
d = da.from_array(x, chunks=4)
for i in (0, 1, 4, 5):
assert_eq(x.round(i), d.round(i))
assert_eq(d.round(2), da.round(d, 2))
def round_coordinates(cubes, decimals=5, coord_names=None):
"""Round all dimensional coordinates of all cubes in place.
Cubes can be a list of Iris cubes, or an Iris `CubeList`.
Cubes are modified *in place*. The return value is simply for
convenience.
Parameters
----------
cubes : iris.cube.CubeList or list of iris.cube.Cube
Cubes which are modified in place.
decimals : int
Number of decimals to round to.
coord_names : list of str or None
If ``None`` (or a falsey value), all dimensional coordinates will be
rounded. Otherwise, only coordinates given by the names in
``coord_names`` are rounded.
Returns
-------
iris.cube.CubeList or list of iris.cube.Cube
The modified input ``cubes``.
"""
for cube in cubes:
if not coord_names:
coords = cube.coords(dim_coords=True)
else:
coords = [cube.coord(c) for c in coord_names if cube.coords(c)]
for coord in coords:
coord.points = da.round(da.asarray(coord.core_points()), decimals)
if coord.bounds is not None:
coord.bounds = da.round(da.asarray(coord.core_bounds()),
decimals)
return cubes
def pad(array, pad_width, mode="constant", **kwargs):
padded = da.pad(array, pad_width, mode=mode, **kwargs)
# workaround for inconsistency between numpy and dask: https://github.com/dask/dask/issues/5303
if mode == "mean" and issubclass(array.dtype.type, np.integer):
warnings.warn(
'dask.array.pad(mode="mean") converts integers to floats. xarray converts '
"these floats back to integers to keep the interface consistent. There is a chance that "
"this introduces rounding errors. If you wish to keep the values as floats, first change "
"the dtype to a float before calling pad.",
UserWarning,
)
return da.round(padded).astype(array.dtype)
_validate_pad_output_shape(array.shape, pad_width, padded.shape)
return padded
def integer_cbf_dumps(w):
return da.round(w / accs_per_cbf_dump) * accs_per_cbf_dump
