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Original file line number | Diff line number | Diff line change |
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@@ -10,6 +10,7 @@ dependencies: | |
- pandas>=0.15.0 | ||
- pynio | ||
- scipy | ||
- iris | ||
- pytest-cov | ||
- cyordereddict | ||
- pip: | ||
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Original file line number | Diff line number | Diff line change |
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@@ -3,24 +3,42 @@ | |
import numpy as np | ||
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from .core.dataarray import DataArray | ||
from .core.pycompat import OrderedDict | ||
from .conventions import ( | ||
maybe_encode_timedelta, maybe_encode_datetime, decode_cf) | ||
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ignored_attrs = set(['name', 'tileIndex']) | ||
cdms2_ignored_attrs = set(['name', 'tileIndex']) | ||
iris_forbidden_keys = set( | ||
['standard_name', 'long_name', 'units', 'bounds', 'axis', | ||
'calendar', 'leap_month', 'leap_year', 'month_lengths', | ||
'coordinates', 'grid_mapping', 'climatology', | ||
'cell_methods', 'formula_terms', 'compress', | ||
'missing_value', 'add_offset', 'scale_factor', | ||
'valid_max', 'valid_min', 'valid_range', '_FillValue']) | ||
cell_methods_strings = set(['point', 'sum', 'maximum', 'median', 'mid_range', | ||
'minimum', 'mean', 'mode', 'standard_deviation', | ||
'variance']) | ||
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def encode(var): | ||
return maybe_encode_timedelta(maybe_encode_datetime(var.variable)) | ||
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def _filter_attrs(attrs, ignored_attrs): | ||
""" Return attrs that are not in ignored_attrs | ||
""" | ||
return dict((k, v) for k, v in attrs.items() if k not in ignored_attrs) | ||
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def from_cdms2(variable): | ||
"""Convert a cdms2 variable into an DataArray | ||
""" | ||
def get_cdms2_attrs(var): | ||
return dict((k, v) for k, v in var.attributes.items() | ||
if k not in ignored_attrs) | ||
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values = np.asarray(variable) | ||
name = variable.id | ||
coords = [(v.id, np.asarray(v), get_cdms2_attrs(v)) | ||
coords = [(v.id, np.asarray(v), | ||
_filter_attrs(v.attributes, cdms2_ignored_attrs)) | ||
for v in variable.getAxisList()] | ||
attrs = get_cdms2_attrs(variable) | ||
attrs = _filter_attrs(variable.attributes, cdms2_ignored_attrs) | ||
dataarray = DataArray(values, coords=coords, name=name, attrs=attrs) | ||
return decode_cf(dataarray.to_dataset())[dataarray.name] | ||
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@@ -31,9 +49,6 @@ def to_cdms2(dataarray): | |
# we don't want cdms2 to be a hard dependency | ||
import cdms2 | ||
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def encode(var): | ||
return maybe_encode_timedelta(maybe_encode_datetime(var.variable)) | ||
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def set_cdms2_attrs(var, attrs): | ||
for k, v in attrs.items(): | ||
setattr(var, k, v) | ||
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@@ -49,3 +64,130 @@ def set_cdms2_attrs(var, attrs): | |
cdms2_var = cdms2.createVariable(var.values, axes=axes, id=dataarray.name) | ||
set_cdms2_attrs(cdms2_var, var.attrs) | ||
return cdms2_var | ||
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def _pick_attrs(attrs, keys): | ||
""" Return attrs with keys in keys list | ||
""" | ||
return dict((k, v) for k, v in attrs.items() if k in keys) | ||
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def _get_iris_args(attrs): | ||
""" Converts the xarray attrs into args that can be passed into Iris | ||
""" | ||
# iris.unit is deprecated in Iris v1.9 | ||
import cf_units | ||
args = {'attributes': _filter_attrs(attrs, iris_forbidden_keys)} | ||
args.update(_pick_attrs(attrs, ('standard_name', 'long_name',))) | ||
unit_args = _pick_attrs(attrs, ('calendar',)) | ||
if 'units' in attrs: | ||
args['units'] = cf_units.Unit(attrs['units'], **unit_args) | ||
return args | ||
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# TODO: Add converting bounds from xarray to Iris and back | ||
def to_iris(dataarray): | ||
""" Convert a DataArray into a Iris Cube | ||
""" | ||
# Iris not a hard dependency | ||
import iris | ||
try: | ||
from iris.fileformats.netcdf import parse_cell_methods | ||
except ImportError: | ||
# prior to v1.10 | ||
from iris.fileformats._pyke_rules.compiled_krb.fc_rules_cf_fc \ | ||
import _parse_cell_methods as parse_cell_methods | ||
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dim_coords = [] | ||
aux_coords = [] | ||
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for coord_name in dataarray.coords: | ||
coord = encode(dataarray.coords[coord_name]) | ||
coord_args = _get_iris_args(coord.attrs) | ||
coord_args['var_name'] = coord_name | ||
axis = None | ||
if coord.dims: | ||
axis = dataarray.get_axis_num(coord.dims) | ||
if coord_name in dataarray.dims: | ||
iris_coord = iris.coords.DimCoord(coord.values, **coord_args) | ||
dim_coords.append((iris_coord, axis)) | ||
else: | ||
iris_coord = iris.coords.AuxCoord(coord.values, **coord_args) | ||
aux_coords.append((iris_coord, axis)) | ||
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args = _get_iris_args(dataarray.attrs) | ||
args['var_name'] = dataarray.name | ||
args['dim_coords_and_dims'] = dim_coords | ||
args['aux_coords_and_dims'] = aux_coords | ||
if 'cell_methods' in dataarray.attrs: | ||
args['cell_methods'] = parse_cell_methods( | ||
dataarray.name, dataarray.attrs['cell_methods']) | ||
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cube = iris.cube.Cube(dataarray.to_masked_array(), **args) | ||
return cube | ||
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def _iris_obj_to_attrs(obj): | ||
""" Return a dictionary of attrs when given a Iris object | ||
""" | ||
attrs = {'standard_name': obj.standard_name, | ||
'long_name': obj.long_name} | ||
if obj.units.calendar: | ||
attrs['calendar'] = obj.units.calendar | ||
if obj.units.origin != '1': | ||
attrs['units'] = obj.units.origin | ||
attrs.update(obj.attributes) | ||
return dict((k, v) for k, v in attrs.items() if v is not None) | ||
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def _iris_cell_methods_to_str(cell_methods_obj): | ||
""" Converts a Iris cell methods into a string | ||
""" | ||
cell_methods = [] | ||
for cell_method in cell_methods_obj: | ||
names = ''.join(['{}: '.format(n) for n in cell_method.coord_names]) | ||
intervals = ' '.join(['interval: {}'.format(interval) | ||
for interval in cell_method.intervals]) | ||
comments = ' '.join(['comment: {}'.format(comment) | ||
for comment in cell_method.comments]) | ||
extra = ' '.join([intervals, comments]).strip() | ||
if extra: | ||
extra = ' ({})'.format(extra) | ||
cell_methods.append(names + cell_method.method + extra) | ||
return ' '.join(cell_methods) | ||
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def from_iris(cube): | ||
""" Convert a Iris cube into an DataArray | ||
""" | ||
import iris.exceptions | ||
name = cube.var_name | ||
dims = [] | ||
for i in xrange(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)) | ||
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coords = OrderedDict() | ||
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for coord in cube.coords(): | ||
coord_attrs = _iris_obj_to_attrs(coord) | ||
coord_dims = [dims[i] for i in cube.coord_dims(coord)] | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Is it possible to have coord_dims(coord) return a tuple that does not have length equal to it's number of dimensions? There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. coord_dims(coord):
So I think it's ok. |
||
if not coord.var_name: | ||
raise ValueError('Coordinate has no var_name') | ||
if coord_dims: | ||
coords[coord.var_name] = (coord_dims, coord.points, coord_attrs) | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I think it's also possible to There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Is there an xarray exception that might make sense for the error? Or just There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. We usually just raise ValueError for cases like this where we cannot handle On Wed, Aug 10, 2016 at 2:01 PM, Neil Parley [email protected]
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else: | ||
coords[coord.var_name] = ((), | ||
np.asscalar(coord.points), coord_attrs) | ||
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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 | ||
dataarray = DataArray(cube.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) |
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Is it possible for a cube not to have variable name?
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I think this could possible be None. It's the CF variable name but I think the cube could have been made with out reading in a file so that the Name would be None.
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A quick search in the Iris source gives this:
So would conclude that's it's not an empty string or None