Use .to_numpy() for quantified facetgrids (pydata#5886)

Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>

doc/whats-new.rst

@@ -82,6 +82,9 @@ Bug fixes
   By `Jimmy Westling <https://github.com/illviljan>`_.
 - Numbers are properly formatted in a plot's title (:issue:`5788`, :pull:`5789`).
   By `Maxime Liquet <https://github.com/maximlt>`_.
+- Faceted plots will no longer raise a `pint.UnitStrippedWarning` when a `pint.Quantity` array is plotted,
+  and will correctly display the units of the data in the colorbar (if there is one) (:pull:`5886`).
+  By `Tom Nicholas <https://github.com/TomNicholas>`_.
 - With backends, check for path-like objects rather than ``pathlib.Path``
   type, use ``os.fspath`` (:pull:`5879`).
   By `Mike Taves <https://github.com/mwtoews>`_.

xarray/plot/facetgrid.py

@@ -173,11 +173,11 @@ def __init__(
         )
 
         # Set up the lists of names for the row and column facet variables
-        col_names = list(data[col].values) if col else []
-        row_names = list(data[row].values) if row else []
+        col_names = list(data[col].to_numpy()) if col else []
+        row_names = list(data[row].to_numpy()) if row else []
 
         if single_group:
-            full = [{single_group: x} for x in data[single_group].values]
+            full = [{single_group: x} for x in data[single_group].to_numpy()]
             empty = [None for x in range(nrow * ncol - len(full))]
             name_dicts = full + empty
         else:
@@ -251,7 +251,7 @@ def map_dataarray(self, func, x, y, **kwargs):
             raise ValueError("cbar_ax not supported by FacetGrid.")
 
         cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
-            func, self.data.values, **kwargs
+            func, self.data.to_numpy(), **kwargs
         )
 
         self._cmap_extend = cmap_params.get("extend")
@@ -347,7 +347,7 @@ def map_dataset(
 
         if hue and meta_data["hue_style"] == "continuous":
             cmap_params, cbar_kwargs = _process_cmap_cbar_kwargs(
-                func, self.data[hue].values, **kwargs
+                func, self.data[hue].to_numpy(), **kwargs
             )
             kwargs["meta_data"]["cmap_params"] = cmap_params
             kwargs["meta_data"]["cbar_kwargs"] = cbar_kwargs
@@ -423,7 +423,7 @@ def _adjust_fig_for_guide(self, guide):
     def add_legend(self, **kwargs):
         self.figlegend = self.fig.legend(
             handles=self._mappables[-1],
-            labels=list(self._hue_var.values),
+            labels=list(self._hue_var.to_numpy()),
             title=self._hue_label,
             loc="center right",
             **kwargs,
@@ -619,7 +619,7 @@ def map(self, func, *args, **kwargs):
             if namedict is not None:
                 data = self.data.loc[namedict]
                 plt.sca(ax)
-                innerargs = [data[a].values for a in args]
+                innerargs = [data[a].to_numpy() for a in args]
                 maybe_mappable = func(*innerargs, **kwargs)
                 # TODO: better way to verify that an artist is mappable?
                 # https://stackoverflow.com/questions/33023036/is-it-possible-to-detect-if-a-matplotlib-artist-is-a-mappable-suitable-for-use-w#33023522

xarray/plot/plot.py

@@ -1075,7 +1075,7 @@ def newplotfunc(
             # Matplotlib does not support normalising RGB data, so do it here.
             # See eg. https://github.com/matplotlib/matplotlib/pull/10220
             if robust or vmax is not None or vmin is not None:
-                darray = _rescale_imshow_rgb(darray, vmin, vmax, robust)
+                darray = _rescale_imshow_rgb(darray.as_numpy(), vmin, vmax, robust)
                 vmin, vmax, robust = None, None, False
 
         if subplot_kws is None:
@@ -1146,10 +1146,6 @@ def newplotfunc(
         else:
             dims = (yval.dims[0], xval.dims[0])
 
-        # better to pass the ndarrays directly to plotting functions
-        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
         if imshow_rgb:
@@ -1162,6 +1158,10 @@ def newplotfunc(
         if dims != darray.dims:
             darray = darray.transpose(*dims, transpose_coords=True)
 
+        # better to pass the ndarrays directly to plotting functions
+        xval = xval.to_numpy()
+        yval = yval.to_numpy()
+
         # Pass the data as a masked ndarray too
         zval = darray.to_masked_array(copy=False)
 

xarray/tests/test_units.py

@@ -5614,11 +5614,35 @@ def test_units_in_line_plot_labels(self):
         assert ax.get_ylabel() == "pressure [pascal]"
         assert ax.get_xlabel() == "x [meters]"
 
-    def test_units_in_2d_plot_labels(self):
+    def test_units_in_2d_plot_colorbar_label(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]"
+
+    def test_units_facetgrid_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)
+        fgrid = da.plot.line(x="x", col="y")
+
+        assert fgrid.axes[0, 0].get_ylabel() == "pressure [pascal]"
+
+    def test_units_facetgrid_2d_imshow_plot_colorbar_labels(self):
+        arr = np.ones((2, 3, 4, 5)) * unit_registry.Pa
+        da = xr.DataArray(data=arr, dims=["x", "y", "z", "w"], name="pressure")
+
+        da.plot.imshow(x="x", y="y", col="w")  # no colorbar to check labels of
+
+    def test_units_facetgrid_2d_contourf_plot_colorbar_labels(self):
+        arr = np.ones((2, 3, 4)) * unit_registry.Pa
+        da = xr.DataArray(data=arr, dims=["x", "y", "z"], name="pressure")
+
+        fig, (ax1, ax2, ax3, cax) = plt.subplots(1, 4)
+        fgrid = da.plot.contourf(x="x", y="y", col="z")
+
+        assert fgrid.cbar.ax.get_ylabel() == "pressure [pascal]"