New properties Dataset.sizes and DataArray.sizes

This allows for consistent access to dimension lengths on ``Dataset`` and
``DataArray``

xref pydata#921 (doesn't resolve it 100%, but should help significantly)

Author: shoyer

doc/api.rst

@@ -39,6 +39,7 @@ Attributes
    :toctree: generated/
 
    Dataset.dims
+   Dataset.sizes
    Dataset.data_vars
    Dataset.coords
    Dataset.attrs
@@ -187,6 +188,7 @@ Attributes
    DataArray.data
    DataArray.coords
    DataArray.dims
+   DataArray.sizes
    DataArray.name
    DataArray.attrs
    DataArray.encoding

doc/whats-new.rst

@@ -77,6 +77,11 @@ Enhancements
   :py:meth:`~xarray.DataArray.cumprod`.  By `Phillip J. Wolfram
   <https://github.com/pwolfram>`_.
 
+- New properties :py:attr:`Dataset.sizes` and :py:attr:`DataArray.sizes` for
+  providing consistent access to dimension length on both ``Dataset`` and
+  ``DataArray`` (:issue:`921`).
+  By `Stephan Hoyer <https://github.com/shoyer>`_.
+
 Bug fixes
 ~~~~~~~~~
 - ``groupby_bins`` now restores empty bins by default (:issue:`1019`).

xarray/core/common.py

@@ -1,9 +1,10 @@
 import numpy as np
 import pandas as pd
 
-from .pycompat import basestring, iteritems, suppress, dask_array_type, bytes_type
+from .pycompat import (basestring, iteritems, suppress, dask_array_type,
+                       OrderedDict)
 from . import formatting
-from .utils import SortedKeysDict, not_implemented
+from .utils import SortedKeysDict, not_implemented, Frozen
 
 
 class ImplementsArrayReduce(object):
@@ -124,6 +125,8 @@ def wrapped_func(self, **kwargs):
 
 
 class AbstractArray(ImplementsArrayReduce, formatting.ReprMixin):
+    """Shared base class for DataArray and Variable."""
+
     def __bool__(self):
         return bool(self.values)
 
@@ -186,6 +189,18 @@ def _get_axis_num(self, dim):
             raise ValueError("%r not found in array dimensions %r" %
                              (dim, self.dims))
 
+    @property
+    def sizes(self):
+        """Ordered mapping from dimension names to lengths.
+
+        Immutable.
+
+        See also
+        --------
+        Dataset.sizes
+        """
+        return Frozen(OrderedDict(zip(self.dims, self.shape)))
+
 
 class AttrAccessMixin(object):
     """Mixin class that allows getting keys with attribute access
@@ -231,7 +246,43 @@ def __dir__(self):
         return sorted(set(dir(type(self)) + extra_attrs))
 
 
-class BaseDataObject(AttrAccessMixin):
+class SharedMethodsMixin(object):
+    """Shared methods for Dataset, DataArray and Variable."""
+
+    def squeeze(self, dim=None):
+        """Return a new object with squeezed data.
+
+        Parameters
+        ----------
+        dim : None or str or tuple of str, optional
+            Selects a subset of the length one dimensions. If a dimension is
+            selected with length greater than one, an error is raised. If
+            None, all length one dimensions are squeezed.
+
+        Returns
+        -------
+        squeezed : same type as caller
+            This object, but with with all or a subset of the dimensions of
+            length 1 removed.
+
+        See Also
+        --------
+        numpy.squeeze
+        """
+        if dim is None:
+            dim = [d for d, s in self.sizes.items() if s == 1]
+        else:
+            if isinstance(dim, basestring):
+                dim = [dim]
+            if any(self.sizes[k] > 1 for k in dim):
+                raise ValueError('cannot select a dimension to squeeze out '
+                                 'which has length greater than one')
+        return self.isel(**{d: 0 for d in dim})
+
+
+class BaseDataObject(SharedMethodsMixin, AttrAccessMixin):
+    """Shared base class for Dataset and DataArray."""
+
     def _calc_assign_results(self, kwargs):
         results = SortedKeysDict()
         for k, v in kwargs.items():
@@ -615,19 +666,6 @@ def __exit__(self, exc_type, exc_value, traceback):
     __or__ = __div__ = __eq__ = __ne__ = not_implemented
 
 
-def squeeze(xarray_obj, dims, dim=None):
-    """Squeeze the dims of an xarray object."""
-    if dim is None:
-        dim = [d for d, s in iteritems(dims) if s == 1]
-    else:
-        if isinstance(dim, basestring):
-            dim = [dim]
-        if any(dims[k] > 1 for k in dim):
-            raise ValueError('cannot select a dimension to squeeze out '
-                             'which has length greater than one')
-    return xarray_obj.isel(**dict((d, 0) for d in dim))
-
-
 def _maybe_promote(dtype):
     """Simpler equivalent of pandas.core.common._maybe_promote"""
     # N.B. these casting rules should match pandas

xarray/core/dataarray.py

@@ -1,4 +1,3 @@
-import contextlib
 import functools
 import warnings
 
@@ -13,7 +12,7 @@
 from . import ops
 from . import utils
 from .alignment import align
-from .common import AbstractArray, BaseDataObject, squeeze
+from .common import AbstractArray, BaseDataObject
 from .coordinates import (DataArrayCoordinates, LevelCoordinates,
                           Indexes)
 from .dataset import Dataset
@@ -411,7 +410,12 @@ def to_index(self):
 
     @property
     def dims(self):
-        """Dimension names associated with this array."""
+        """Tuple of dimension names associated with this array.
+
+        Note that the type of this property is inconsistent with `Dataset.dims`.
+        See `Dataset.sizes` and `DataArray.sizes` for consistently named
+        properties.
+        """
         return self.variable.dims
 
     @dims.setter
@@ -911,33 +915,6 @@ def transpose(self, *dims):
         variable = self.variable.transpose(*dims)
         return self._replace(variable)
 
-    def squeeze(self, dim=None):
-        """Return a new DataArray object with squeezed data.
-
-        Parameters
-        ----------
-        dim : None or str or tuple of str, optional
-            Selects a subset of the length one dimensions. If a dimension is
-            selected with length greater than one, an error is raised. If
-            None, all length one dimensions are squeezed.
-
-        Returns
-        -------
-        squeezed : DataArray
-            This array, but with with all or a subset of the dimensions of
-            length 1 removed.
-
-        Notes
-        -----
-        Although this operation returns a view of this array's data, it is
-        not lazy -- the data will be fully loaded.
-
-        See Also
-        --------
-        numpy.squeeze
-        """
-        return squeeze(self, dict(zip(self.dims, self.shape)), dim)
-
     def drop(self, labels, dim=None):
         """Drop coordinates or index labels from this DataArray.
 

xarray/core/dataset.py

@@ -291,11 +291,29 @@ def attrs(self, value):
     def dims(self):
         """Mapping from dimension names to lengths.
 
-        This dictionary cannot be modified directly, but is updated when adding
-        new variables.
+        Cannot be modified directly, but is updated when adding new variables.
+
+        Note that type of this object differs from `DataArray.dims`.
+        See `Dataset.sizes` and `DataArray.sizes` for consistently named
+        properties.
         """
         return Frozen(SortedKeysDict(self._dims))
 
+    @property
+    def sizes(self):
+        """Mapping from dimension names to lengths.
+
+        Cannot be modified directly, but is updated when adding new variables.
+
+        This is an alias for `Dataset.dims` provided for the benefit of
+        consistency with `DataArray.sizes`.
+
+        See also
+        --------
+        DataArray.sizes
+        """
+        return self.dims
+
     def load(self):
         """Manually trigger loading of this dataset's data from disk or a
         remote source into memory and return this dataset.
@@ -1584,33 +1602,6 @@ def transpose(self, *dims):
     def T(self):
         return self.transpose()
 
-    def squeeze(self, dim=None):
-        """Returns a new dataset with squeezed data.
-
-        Parameters
-        ----------
-        dim : None or str or tuple of str, optional
-            Selects a subset of the length one dimensions. If a dimension is
-            selected with length greater than one, an error is raised.  If
-            None, all length one dimensions are squeezed.
-
-        Returns
-        -------
-        squeezed : Dataset
-            This dataset, but with with all or a subset of the dimensions of
-            length 1 removed.
-
-        Notes
-        -----
-        Although this operation returns a view of each variable's data, it is
-        not lazy -- all variable data will be fully loaded.
-
-        See Also
-        --------
-        numpy.squeeze
-        """
-        return common.squeeze(self, self.dims, dim)
-
     def dropna(self, dim, how='any', thresh=None, subset=None):
         """Returns a new dataset with dropped labels for missing values along
         the provided dimension.

xarray/core/groupby.py

@@ -178,10 +178,7 @@ def __init__(self, obj, group, squeeze=False, grouper=None, bins=None,
             raise ValueError("`group` must have a 'dims' attribute")
         group_dim, = group.dims
 
-        try:
-            expected_size = obj.dims[group_dim]
-        except TypeError:
-            expected_size = obj.shape[obj.get_axis_num(group_dim)]
+        expected_size = obj.sizes[group_dim]
         if group.size != expected_size:
             raise ValueError('the group variable\'s length does not '
                              'match the length of this variable along its '

xarray/core/variable.py

@@ -2,7 +2,6 @@
 from collections import defaultdict
 import functools
 import itertools
-import warnings
 
 import numpy as np
 import pandas as pd
@@ -192,7 +191,8 @@ def _as_array_or_item(data):
     return data
 
 
-class Variable(common.AbstractArray, utils.NdimSizeLenMixin):
+class Variable(common.AbstractArray, common.SharedMethodsMixin,
+               utils.NdimSizeLenMixin):
 
     """A netcdf-like variable consisting of dimensions, data and attributes
     which describe a single Array. A single Variable object is not fully
@@ -678,34 +678,6 @@ def transpose(self, *dims):
         data = ops.transpose(self.data, axes)
         return type(self)(dims, data, self._attrs, self._encoding, fastpath=True)
 
-    def squeeze(self, dim=None):
-        """Return a new Variable object with squeezed data.
-
-        Parameters
-        ----------
-        dim : None or str or tuple of str, optional
-            Selects a subset of the length one dimensions. If a dimension is
-            selected with length greater than one, an error is raised. If
-            None, all length one dimensions are squeezed.
-
-        Returns
-        -------
-        squeezed : Variable
-            This array, but with with all or a subset of the dimensions of
-            length 1 removed.
-
-        Notes
-        -----
-        Although this operation returns a view of this variable's data, it is
-        not lazy -- the data will be fully loaded.
-
-        See Also
-        --------
-        numpy.squeeze
-        """
-        dims = dict(zip(self.dims, self.shape))
-        return common.squeeze(self, dims, dim)
-
     def expand_dims(self, dims, shape=None):
         """Return a new variable with expanded dimensions.
 
@@ -814,8 +786,7 @@ def _unstack_once(self, dims, old_dim):
             raise ValueError('cannot create a new dimension with the same '
                              'name as an existing dimension')
 
-        axis = self.get_axis_num(old_dim)
-        if np.prod(new_dim_sizes) != self.shape[axis]:
+        if np.prod(new_dim_sizes) != self.sizes[old_dim]:
             raise ValueError('the product of the new dimension sizes must '
                              'equal the size of the old dimension')
 
@@ -914,7 +885,6 @@ def reduce(self, func, dim=None, axis=None, keep_attrs=False,
             dims = [adim for n, adim in enumerate(self.dims)
                     if n not in removed_axes]
 
-
         attrs = self._attrs if keep_attrs else None
 
         return Variable(dims, data, attrs=attrs)

xarray/test/test_dataarray.py

@@ -159,6 +159,13 @@ def test_dims(self):
         with self.assertRaisesRegexp(AttributeError, 'you cannot assign'):
             arr.dims = ('w', 'z')
 
+    def test_sizes(self):
+        array = DataArray(np.zeros((3, 4)), dims=['x', 'y'])
+        self.assertEqual(array.sizes, {'x': 3, 'y': 4})
+        self.assertEqual(tuple(array.sizes), array.dims)
+        with self.assertRaises(TypeError):
+            array.sizes['foo'] = 5
+
     def test_encoding(self):
         expected = {'foo': 'bar'}
         self.dv.encoding['foo'] = 'bar'

xarray/test/test_dataset.py

@@ -338,6 +338,7 @@ def test_properties(self):
         self.assertEqual(ds.dims,
                          {'dim1': 8, 'dim2': 9, 'dim3': 10, 'time': 20})
         self.assertEqual(list(ds.dims), sorted(ds.dims))
+        self.assertEqual(ds.sizes, ds.dims)
 
         # These exact types aren't public API, but this makes sure we don't
         # change them inadvertently:

xarray/test/test_variable.py

@@ -26,6 +26,7 @@ def test_properties(self):
         self.assertEqual(v.dtype, float)
         self.assertEqual(v.shape, (10,))
         self.assertEqual(v.size, 10)
+        self.assertEqual(v.sizes, {'time': 10})
         self.assertEqual(v.nbytes, 80)
         self.assertEqual(v.ndim, 1)
         self.assertEqual(len(v), 10)