Recreate @gajomi's #2070 to keep attrs when calling astype()

doc/whats-new.rst

@@ -21,7 +21,9 @@ v0.16.1 (unreleased)
 
 Breaking changes
 ~~~~~~~~~~~~~~~~
-
+- :py:meth:`DataArray.astype` and :py:meth:`Dataset.astype` now preserve attributes. Keep the
+  old behavior by passing `keep_attrs=False` (:issue:`2049`, :pull:`4314`).
+  By `Dan Nowacki <https://github.com/dnowacki-usgs>`_ and `Gabriel Joel Mitchell <https://github.com/gajomi>`_.
 
 New Features
 ~~~~~~~~~~~~

xarray/core/common.py

@@ -1305,6 +1305,53 @@ def isin(self, test_elements):
             dask="allowed",
         )
 
+    def astype(self, dtype, casting="unsafe", copy=True, keep_attrs=True):
+        """
+        Copy of the xarray object, with data cast to a specified type.
+        Leaves coordinate dtype unchanged.
+
+        Parameters
+        ----------
+        dtype : str or dtype
+            Typecode or data-type to which the array is cast.
+        casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
+            Controls what kind of data casting may occur. Defaults to 'unsafe'
+            for backwards compatibility.
+
+            * 'no' means the data types should not be cast at all.
+            * 'equiv' means only byte-order changes are allowed.
+            * 'safe' means only casts which can preserve values are allowed.
+            * 'same_kind' means only safe casts or casts within a kind,
+                like float64 to float32, are allowed.
+            * 'unsafe' means any data conversions may be done.
+        copy : bool, optional
+            By default, astype always returns a newly allocated array. If this
+            is set to False and the `dtype` requirement is satisfied, the input
+            array is returned instead of a copy.
+        keep_attrs : bool, optional
+            By default, astype keeps attributes. Set to False to remove
+            attributes in the returned object.
+
+        Returns
+        -------
+        out : same as object
+            New object with data cast to the specified type.
+
+        See also
+        --------
+        np.ndarray.astype
+        dask.array.Array.astype
+        """
+        from .computation import apply_ufunc
+
+        return apply_ufunc(
+            duck_array_ops.astype,
+            self,
+            kwargs=dict(dtype=dtype, casting=casting, copy=copy),
+            keep_attrs=keep_attrs,
+            dask="allowed",
+        )
+
     def __enter__(self: T) -> T:
         return self
 

xarray/core/duck_array_ops.py

@@ -6,6 +6,7 @@
 import contextlib
 import inspect
 import warnings
+from distutils.version import LooseVersion
 from functools import partial
 
 import numpy as np
@@ -149,6 +150,28 @@ def trapz(y, x, axis):
 )
 
 
+def astype(data, **kwargs):
+    try:
+        import sparse
+    except ImportError:
+        sparse = None
+
+    if (
+        sparse is not None
+        and isinstance(data, sparse._coo.core.COO)
+        and LooseVersion(sparse.__version__) < LooseVersion("0.11.0")
+        and "casting" in kwargs
+    ):
+        warnings.warn(
+            "The current version of sparse does not support the 'casting' argument. It will be ignored in the call to astype().",
+            RuntimeWarning,
+            stacklevel=4,
+        )
+        kwargs.pop("casting")
+
+    return data.astype(**kwargs)
+
+
 def asarray(data, xp=np):
     return (
         data

xarray/core/ops.py

@@ -42,7 +42,7 @@
 NUMPY_SAME_METHODS = ["item", "searchsorted"]
 # methods which don't modify the data shape, so the result should still be
 # wrapped in an Variable/DataArray
-NUMPY_UNARY_METHODS = ["astype", "argsort", "clip", "conj", "conjugate"]
+NUMPY_UNARY_METHODS = ["argsort", "clip", "conj", "conjugate"]
 PANDAS_UNARY_FUNCTIONS = ["isnull", "notnull"]
 # methods which remove an axis
 REDUCE_METHODS = ["all", "any"]

xarray/core/variable.py

@@ -360,6 +360,52 @@ def data(self, data):
             )
         self._data = data
 
+    def astype(self, dtype, casting="unsafe", copy=True, keep_attrs=True):
+        """
+        Copy of the Variable object, with data cast to a specified type.
+
+        Parameters
+        ----------
+        dtype : str or dtype
+             Typecode or data-type to which the array is cast.
+        casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
+             Controls what kind of data casting may occur. Defaults to 'unsafe'
+             for backwards compatibility.
+
+             * 'no' means the data types should not be cast at all.
+             * 'equiv' means only byte-order changes are allowed.
+             * 'safe' means only casts which can preserve values are allowed.
+             * 'same_kind' means only safe casts or casts within a kind,
+                 like float64 to float32, are allowed.
+             * 'unsafe' means any data conversions may be done.
+        copy : bool, optional
+             By default, astype always returns a newly allocated array. If this
+             is set to False and the `dtype` requirement is satisfied, the input
+             array is returned instead of a copy.
+        keep_attrs : bool, optional
+            By default, astype keeps attributes. Set to False to remove
+            attributes in the returned object.
+
+        Returns
+        -------
+        out : same as object
+            New object with data cast to the specified type.
+
+        See also
+        --------
+        np.ndarray.astype
+        dask.array.Array.astype
+        """
+        from .computation import apply_ufunc
+
+        return apply_ufunc(
+            duck_array_ops.astype,
+            self,
+            kwargs=dict(dtype=dtype, casting=casting, copy=copy),
+            keep_attrs=keep_attrs,
+            dask="allowed",
+        )
+
     def load(self, **kwargs):
         """Manually trigger loading of this variable's data from disk or a
         remote source into memory and return this variable.

xarray/tests/test_dataarray.py

@@ -1874,6 +1874,19 @@ def test_array_interface(self):
         bar = Variable(["x", "y"], np.zeros((10, 20)))
         assert_equal(self.dv, np.maximum(self.dv, bar))
 
+    def test_astype_attrs(self):
+        for v in [self.va.copy(), self.mda.copy(), self.ds.copy()]:
+            v.attrs["foo"] = "bar"
+            assert v.attrs == v.astype(float).attrs
+            assert not v.astype(float, keep_attrs=False).attrs
+
+    def test_astype_dtype(self):
+        original = DataArray([-1, 1, 2, 3, 1000])
+        converted = original.astype(float)
+        assert_array_equal(original, converted)
+        assert np.issubdtype(original.dtype, np.integer)
+        assert np.issubdtype(converted.dtype, np.floating)
+
     def test_is_null(self):
         x = np.random.RandomState(42).randn(5, 6)
         x[x < 0] = np.nan

xarray/tests/test_dataset.py

@@ -5607,6 +5607,15 @@ def test_pad(self):
         np.testing.assert_equal(padded["var1"].isel(dim2=[0, -1]).data, 42)
         np.testing.assert_equal(padded["dim2"][[0, -1]].data, np.nan)
 
+    def test_astype_attrs(self):
+        data = create_test_data(seed=123)
+        data.attrs["foo"] = "bar"
+
+        assert data.attrs == data.astype(float).attrs
+        assert data.var1.attrs == data.astype(float).var1.attrs
+        assert not data.astype(float, keep_attrs=False).attrs
+        assert not data.astype(float, keep_attrs=False).var1.attrs
+
 
 # Py.test tests