def from_iris(cube):
""" Convert a Iris cube into an DataArray
"""
import iris.exceptions
from xarray.core.pycompat import dask_array_type
name = _name(cube)
if name == "unknown":
name = None
dims = []
for i in range(cube.ndim):
try:
dim_coord = cube.coord(dim_coords=True, dimensions=(i, ))
dims.append(_name(dim_coord))
except iris.exceptions.CoordinateNotFoundError:
dims.append("dim_{}".format(i))
if len(set(dims)) != len(dims):
duplicates = [k for k, v in Counter(dims).items() if v > 1]
raise ValueError("Duplicate coordinate name {}.".format(duplicates))
coords = OrderedDict()
for coord in cube.coords():
coord_attrs = _iris_obj_to_attrs(coord)
coord_dims = [dims[i] for i in cube.coord_dims(coord)]
if coord_dims:
coords[_name(coord)] = (coord_dims, coord.points, coord_attrs)
else:
coords[_name(coord)] = ((), coord.points.item(), coord_attrs)
array_attrs = _iris_obj_to_attrs(cube)
cell_methods = _iris_cell_methods_to_str(cube.cell_methods)
if cell_methods:
array_attrs["cell_methods"] = cell_methods
# Deal with iris 1.* and 2.*
cube_data = cube.core_data() if hasattr(cube, "core_data") else cube.data
# Deal with dask and numpy masked arrays
if isinstance(cube_data, dask_array_type):
from dask.array import ma as dask_ma
filled_data = dask_ma.filled(cube_data, get_fill_value(cube.dtype))
elif isinstance(cube_data, np.ma.MaskedArray):
filled_data = np.ma.filled(cube_data, get_fill_value(cube.dtype))
else:
filled_data = cube_data
dataarray = DataArray(filled_data,
coords=coords,
name=name,
attrs=array_attrs,
dims=dims)
decoded_ds = decode_cf(dataarray._to_temp_dataset())
return dataarray._from_temp_dataset(decoded_ds)
def from_iris(cube):
""" Convert a Iris cube into an DataArray
"""
import iris.exceptions
from xarray.core.pycompat import dask_array_type
name = cube.var_name
dims = []
for i in range(cube.ndim):
try:
dim_coord = cube.coord(dim_coords=True, dimensions=(i, ))
dims.append(dim_coord.var_name)
except iris.exceptions.CoordinateNotFoundError:
dims.append("dim_{}".format(i))
coords = OrderedDict()
for coord in cube.coords():
coord_attrs = _iris_obj_to_attrs(coord)
coord_dims = [dims[i] for i in cube.coord_dims(coord)]
if not coord.var_name:
raise ValueError("Coordinate '{}' has no "
"var_name attribute".format(coord.name()))
if coord_dims:
coords[coord.var_name] = (coord_dims, coord.points, coord_attrs)
else:
coords[coord.var_name] = ((), np.asscalar(coord.points),
coord_attrs)
array_attrs = _iris_obj_to_attrs(cube)
cell_methods = _iris_cell_methods_to_str(cube.cell_methods)
if cell_methods:
array_attrs['cell_methods'] = cell_methods
# Deal with iris 1.* and 2.*
cube_data = cube.core_data() if hasattr(cube, 'core_data') else cube.data
# Deal with dask and numpy masked arrays
if isinstance(cube_data, dask_array_type):
from dask.array import ma as dask_ma
filled_data = dask_ma.filled(cube_data, get_fill_value(cube.dtype))
elif isinstance(cube_data, np.ma.MaskedArray):
filled_data = np.ma.filled(cube_data, get_fill_value(cube.dtype))
else:
filled_data = cube_data
dataarray = DataArray(filled_data,
coords=coords,
name=name,
attrs=array_attrs,
dims=dims)
decoded_ds = decode_cf(dataarray._to_temp_dataset())
return dataarray._from_temp_dataset(decoded_ds)
def from_iris(cube):
""" Convert a Iris cube into an DataArray
"""
import iris.exceptions
from xarray.core.pycompat import dask_array_type
name = _name(cube)
if name == 'unknown':
name = None
dims = []
for i in range(cube.ndim):
try:
dim_coord = cube.coord(dim_coords=True, dimensions=(i,))
dims.append(_name(dim_coord))
except iris.exceptions.CoordinateNotFoundError:
dims.append("dim_{}".format(i))
if len(set(dims)) != len(dims):
duplicates = [k for k, v in Counter(dims).items() if v > 1]
raise ValueError('Duplicate coordinate name {}.'.format(duplicates))
coords = OrderedDict()
for coord in cube.coords():
coord_attrs = _iris_obj_to_attrs(coord)
coord_dims = [dims[i] for i in cube.coord_dims(coord)]
if coord_dims:
coords[_name(coord)] = (coord_dims, coord.points, coord_attrs)
else:
coords[_name(coord)] = ((), np.asscalar(coord.points), coord_attrs)
array_attrs = _iris_obj_to_attrs(cube)
cell_methods = _iris_cell_methods_to_str(cube.cell_methods)
if cell_methods:
array_attrs['cell_methods'] = cell_methods
# Deal with iris 1.* and 2.*
cube_data = cube.core_data() if hasattr(cube, 'core_data') else cube.data
# Deal with dask and numpy masked arrays
if isinstance(cube_data, dask_array_type):
from dask.array import ma as dask_ma
filled_data = dask_ma.filled(cube_data, get_fill_value(cube.dtype))
elif isinstance(cube_data, np.ma.MaskedArray):
filled_data = np.ma.filled(cube_data, get_fill_value(cube.dtype))
else:
filled_data = cube_data
dataarray = DataArray(filled_data, coords=coords, name=name,
attrs=array_attrs, dims=dims)
decoded_ds = decode_cf(dataarray._to_temp_dataset())
return dataarray._from_temp_dataset(decoded_ds)