Plots get labels from pint arrays (#5561)

* test labels come from pint units

* values demotes pint arrays before returning

* plot labels look for pint units first

* pre-commit

* added to_numpy() and as_numpy() methods

* remove special-casing of cupy arrays in .values in favour of using .to_numpy()

* .values -> .to_numpy()

* lint

* Fix mypy (I think?)

* added Dataset.as_numpy()

* improved docstrings

* add what's new

* add to API docs

* linting

* fix failures by only importing pint when needed

* refactor pycompat into class

* pycompat import changes applied to plotting code

* what's new

* compute instead of load

* added tests

* fixed sparse test

* tests and fixes for ds.as_numpy()

* fix sparse tests

* fix linting

* tests for Variable

* test IndexVariable too

* use numpy.asarray to avoid a copy

* also convert coords

* Force tests again after #5600

Co-authored-by: Maximilian Roos <m@maxroos.com>

doc/whats-new.rst

@@ -58,6 +58,8 @@ New Features
   By `Elle Smith <https://github.com/ellesmith88>`_.
 - Added :py:meth:`DataArray.to_numpy`, :py:meth:`DataArray.as_numpy`, and :py:meth:`Dataset.as_numpy`. (:pull:`5568`).
   By `Tom Nicholas <https://github.com/TomNicholas>`_.
+- Units in plot labels are now automatically inferred from wrapped :py:meth:`pint.Quantity` arrays. (:pull:`5561`).
+  By `Tom Nicholas <https://github.com/TomNicholas>`_.
 
 Breaking changes
 ~~~~~~~~~~~~~~~~

xarray/core/dataarray.py

@@ -2784,7 +2784,7 @@ def to_masked_array(self, copy: bool = True) -> np.ma.MaskedArray:
         result : MaskedArray
             Masked where invalid values (nan or inf) occur.
         """
-        values = self.values  # only compute lazy arrays once
+        values = self.to_numpy()  # only compute lazy arrays once
         isnull = pd.isnull(values)
         return np.ma.MaskedArray(data=values, mask=isnull, copy=copy)
 

xarray/core/variable.py

@@ -1075,6 +1075,7 @@ def to_numpy(self) -> np.ndarray:
         """Coerces wrapped data to numpy and returns a numpy.ndarray"""
         # TODO an entrypoint so array libraries can choose coercion method?
         data = self.data
+
         # TODO first attempt to call .to_numpy() once some libraries implement it
         if isinstance(data, dask_array_type):
             data = data.compute()

xarray/plot/plot.py

@@ -430,7 +430,7 @@ def line(
 
     # Remove pd.Intervals if contained in xplt.values and/or yplt.values.
     xplt_val, yplt_val, x_suffix, y_suffix, kwargs = _resolve_intervals_1dplot(
-        xplt.values, yplt.values, kwargs
+        xplt.to_numpy(), yplt.to_numpy(), kwargs
     )
     xlabel = label_from_attrs(xplt, extra=x_suffix)
     ylabel = label_from_attrs(yplt, extra=y_suffix)
@@ -449,7 +449,7 @@ def line(
         ax.set_title(darray._title_for_slice())
 
     if darray.ndim == 2 and add_legend:
-        ax.legend(handles=primitive, labels=list(hueplt.values), title=hue_label)
+        ax.legend(handles=primitive, labels=list(hueplt.to_numpy()), title=hue_label)
 
     # Rotate dates on xlabels
     # Do this without calling autofmt_xdate so that x-axes ticks
@@ -551,7 +551,7 @@ def hist(
     """
     ax = get_axis(figsize, size, aspect, ax)
 
-    no_nan = np.ravel(darray.values)
+    no_nan = np.ravel(darray.to_numpy())
     no_nan = no_nan[pd.notnull(no_nan)]
 
     primitive = ax.hist(no_nan, **kwargs)
@@ -1153,8 +1153,8 @@ def newplotfunc(
             dims = (yval.dims[0], xval.dims[0])
 
         # better to pass the ndarrays directly to plotting functions
-        xval = xval.values
-        yval = yval.values
+        xval = xval.to_numpy()
+        yval = yval.to_numpy()
 
         # May need to transpose for correct x, y labels
         # xlab may be the name of a coord, we have to check for dim names

xarray/plot/utils.py

@@ -9,6 +9,7 @@
 import pandas as pd
 
 from ..core.options import OPTIONS
+from ..core.pycompat import DuckArrayModule
 from ..core.utils import is_scalar
 
 try:
@@ -474,12 +475,20 @@ def label_from_attrs(da, extra=""):
     else:
         name = ""
 
-    if da.attrs.get("units"):
-        units = " [{}]".format(da.attrs["units"])
-    elif da.attrs.get("unit"):
-        units = " [{}]".format(da.attrs["unit"])
+    def _get_units_from_attrs(da):
+        if da.attrs.get("units"):
+            units = " [{}]".format(da.attrs["units"])
+        elif da.attrs.get("unit"):
+            units = " [{}]".format(da.attrs["unit"])
+        else:
+            units = ""
+        return units
+
+    pint_array_type = DuckArrayModule("pint").type
+    if isinstance(da.data, pint_array_type):
+        units = " [{}]".format(str(da.data.units))
     else:
-        units = ""
+        units = _get_units_from_attrs(da)
 
     return "\n".join(textwrap.wrap(name + extra + units, 30))
 
@@ -896,7 +905,7 @@ def _get_nice_quiver_magnitude(u, v):
     import matplotlib as mpl
 
     ticker = mpl.ticker.MaxNLocator(3)
-    mean = np.mean(np.hypot(u.values, v.values))
+    mean = np.mean(np.hypot(u.to_numpy(), v.to_numpy()))
     magnitude = ticker.tick_values(0, mean)[-2]
     return magnitude
 

xarray/tests/test_units.py

@@ -5,10 +5,22 @@
 import pandas as pd
 import pytest
 
+try:
+    import matplotlib.pyplot as plt
+except ImportError:
+    pass
+
 import xarray as xr
 from xarray.core import dtypes, duck_array_ops
 
-from . import assert_allclose, assert_duckarray_allclose, assert_equal, assert_identical
+from . import (
+    assert_allclose,
+    assert_duckarray_allclose,
+    assert_equal,
+    assert_identical,
+    requires_matplotlib,
+)
+from .test_plot import PlotTestCase
 from .test_variable import _PAD_XR_NP_ARGS
 
 pint = pytest.importorskip("pint")
@@ -5564,3 +5576,29 @@ def test_merge(self, variant, unit, error, dtype):
 
         assert_units_equal(expected, actual)
         assert_equal(expected, actual)
+
+
+@requires_matplotlib
+class TestPlots(PlotTestCase):
+    def test_units_in_line_plot_labels(self):
+        arr = np.linspace(1, 10, 3) * unit_registry.Pa
+        # TODO make coord a Quantity once unit-aware indexes supported
+        x_coord = xr.DataArray(
+            np.linspace(1, 3, 3), dims="x", attrs={"units": "meters"}
+        )
+        da = xr.DataArray(data=arr, dims="x", coords={"x": x_coord}, name="pressure")
+
+        da.plot.line()
+
+        ax = plt.gca()
+        assert ax.get_ylabel() == "pressure [pascal]"
+        assert ax.get_xlabel() == "x [meters]"
+
+    def test_units_in_2d_plot_labels(self):
+        arr = np.ones((2, 3)) * unit_registry.Pa
+        da = xr.DataArray(data=arr, dims=["x", "y"], name="pressure")
+
+        fig, (ax, cax) = plt.subplots(1, 2)
+        ax = da.plot.contourf(ax=ax, cbar_ax=cax, add_colorbar=True)
+
+        assert cax.get_ylabel() == "pressure [pascal]"