Support RGB[A] arrays in plot.imshow()

doc/gallery/plot_rasterio.py

@@ -44,13 +44,10 @@
 da.coords['lon'] = (('y', 'x'), lon)
 da.coords['lat'] = (('y', 'x'), lat)
 
-# Compute a greyscale out of the rgb image
-greyscale = da.mean(dim='band')
-
 # Plot on a map
 ax = plt.subplot(projection=ccrs.PlateCarree())
-greyscale.plot(ax=ax, x='lon', y='lat', transform=ccrs.PlateCarree(),
-               cmap='Greys_r', add_colorbar=False)
+da.plot.imshow(ax=ax, x='lon', y='lat', rgb='band',
+               transform=ccrs.PlateCarree())
 ax.coastlines('10m', color='r')
 plt.show()
 

doc/whats-new.rst

@@ -33,6 +33,8 @@ Enhancements
   By `Joe Hamman <https://github.com/jhamman>`_.
 - Support for using `Zarr`_ as storage layer for xarray.
   By `Ryan Abernathey <https://github.com/rabernat>`_.
+- :func:`xarray.plot.imshow` now handles RGB and RGBA images.
+  By `Zac Hatfield-Dodds <https://github.com/Zac-HD>`_.
 - Experimental support for parsing ENVI metadata to coordinates and attributes
   in :py:func:`xarray.open_rasterio`.
   By `Matti Eskelinen <https://github.com/maaleske>`_.

xarray/plot/facetgrid.py

@@ -239,8 +239,9 @@ def map_dataarray(self, func, x, y, **kwargs):
         func_kwargs.update({'add_colorbar': False, 'add_labels': False})
 
         # Get x, y labels for the first subplot
-        x, y = _infer_xy_labels(darray=self.data.loc[self.name_dicts.flat[0]],
-                                x=x, y=y)
+        x, y = _infer_xy_labels(
+            darray=self.data.loc[self.name_dicts.flat[0]], x=x, y=y,
+            imshow=func.__name__ == 'imshow', rgb=kwargs.get('rgb', None))
 
         for d, ax in zip(self.name_dicts.flat, self.axes.flat):
             # None is the sentinel value

xarray/plot/plot.py

@@ -443,10 +443,17 @@ def newplotfunc(darray, x=None, y=None, figsize=None, size=None,
         # Decide on a default for the colorbar before facetgrids
         if add_colorbar is None:
             add_colorbar = plotfunc.__name__ != 'contour'
+        imshow_rgb = (
+            plotfunc.__name__ == 'imshow' and
+            darray.ndim == (3 + (row is not None) + (col is not None)))
+        if imshow_rgb:
+            # Don't add a colorbar when showing an image with explicit colors
+            add_colorbar = False
 
         # Handle facetgrids first
         if row or col:
             allargs = locals().copy()
+            allargs.pop('imshow_rgb')
             allargs.update(allargs.pop('kwargs'))
 
             # Need the decorated plotting function
@@ -470,12 +477,19 @@ def newplotfunc(darray, x=None, y=None, figsize=None, size=None,
                           "Use colors keyword instead.",
                           DeprecationWarning, stacklevel=3)
 
-        xlab, ylab = _infer_xy_labels(darray=darray, x=x, y=y)
+        rgb = kwargs.pop('rgb', None)
+        xlab, ylab = _infer_xy_labels(
+            darray=darray, x=x, y=y, imshow=imshow_rgb, rgb=rgb)
+
+        if rgb is not None and plotfunc.__name__ != 'imshow':
+            raise ValueError('The "rgb" keyword is only valid for imshow()')
+        elif rgb is not None and not imshow_rgb:
+            raise ValueError('The "rgb" keyword is only valid for imshow()'
+                             'with a three-dimensional array (per facet)')
 
         # better to pass the ndarrays directly to plotting functions
         xval = darray[xlab].values
         yval = darray[ylab].values
-        zval = darray.to_masked_array(copy=False)
 
         # check if we need to broadcast one dimension
         if xval.ndim < yval.ndim:
@@ -486,8 +500,19 @@ def newplotfunc(darray, x=None, y=None, figsize=None, size=None,
 
         # 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 darray[xlab].dims[-1] == darray.dims[0]:
-            zval = zval.T
+        if imshow_rgb:
+            # For RGB[A] images, matplotlib requires the color dimension
+            # to be last.  In Xarray the order should be unimportant, so
+            # we transpose to (y, x, color) to make this work.
+            yx_dims = (ylab, xlab)
+            dims = yx_dims + tuple(d for d in darray.dims if d not in yx_dims)
+            if dims != darray.dims:
+                darray = darray.transpose(*dims)
+        elif darray[xlab].dims[-1] == darray.dims[0]:
+            darray = darray.transpose()
+
+        # Pass the data as a masked ndarray too
+        zval = darray.to_masked_array(copy=False)
 
         _ensure_plottable(xval, yval)
 
@@ -595,6 +620,11 @@ def imshow(x, y, z, ax, **kwargs):
 
     Wraps :func:`matplotlib:matplotlib.pyplot.imshow`
 
+    While other plot methods require the DataArray to be strictly
+    two-dimensional, ``imshow`` also accepts a 3D array where some
+    dimension can be interpreted as RGB or RGBA color channels and
+    allows this dimension to be specified via the kwarg ``rgb=``.
+
     .. note::
         This function needs uniformly spaced coordinates to
         properly label the axes. Call DataArray.plot() to check.
@@ -632,6 +662,15 @@ def imshow(x, y, z, ax, **kwargs):
     # Allow user to override these defaults
     defaults.update(kwargs)
 
+    if z.ndim == 3:
+        # matplotlib imshow uses black for missing data, but Xarray makes
+        # missing data transparent.  We therefore add an alpha channel if
+        # there isn't one, and set it to transparent where data is masked.
+        if z.shape[-1] == 3:
+            z = np.ma.concatenate((z, np.ma.ones(z.shape[:2] + (1,))), 2)
+        z = z.copy()
+        z[np.any(z.mask, axis=-1), -1] = 0
+
     primitive = ax.imshow(z, **defaults)
 
     return primitive

xarray/plot/utils.py

@@ -258,12 +258,65 @@ def _determine_cmap_params(plot_data, vmin=None, vmax=None, cmap=None,
                 levels=levels, norm=norm)
 
 
-def _infer_xy_labels(darray, x, y):
+def _infer_xy_labels_3d(darray, x, y, rgb):
+    """
+    Determine x and y labels for showing RGB images.
+
+    Attempts to infer which dimension is RGB/RGBA by size and order of dims.
+
+    """
+    assert rgb is None or rgb != x
+    assert rgb is None or rgb != y
+    # Start by detecting and reporting invalid combinations of arguments
+    assert darray.ndim == 3
+    not_none = [a for a in (x, y, rgb) if a is not None]
+    if len(set(not_none)) < len(not_none):
+        raise ValueError(
+            'Dimension names must be None or unique strings, but imshow was '
+            'passed x=%r, y=%r, and rgb=%r.' % (x, y, rgb))
+    for label in not_none:
+        if label not in darray.dims:
+            raise ValueError('%r is not a dimension' % (label,))
+
+    # Then calculate rgb dimension if certain and check validity
+    could_be_color = [label for label in darray.dims
+                      if darray[label].size in (3, 4) and label not in (x, y)]
+    if rgb is None and not could_be_color:
+        raise ValueError(
+            'A 3-dimensional array was passed to imshow(), but there is no '
+            'dimension that could be color.  At least one dimension must be '
+            'of size 3 (RGB) or 4 (RGBA), and not given as x or y.')
+    if rgb is None and len(could_be_color) == 1:
+        rgb = could_be_color[0]
+    if rgb is not None and darray[rgb].size not in (3, 4):
+        raise ValueError('Cannot interpret dim %r of size %s as RGB or RGBA.'
+                         % (rgb, darray[rgb].size))
+
+    # If rgb dimension is still unknown, there must be two or three dimensions
+    # in could_be_color.  We therefore warn, and use a heuristic to break ties.
+    if rgb is None:
+        assert len(could_be_color) in (2, 3)
+        rgb = could_be_color[-1]
+        warnings.warn(
+            'Several dimensions of this array could be colors.  Xarray '
+            'will use the last possible dimension (%r) to match '
+            'matplotlib.pyplot.imshow.  You can pass names of x, y, '
+            'and/or rgb dimensions to override this guess.' % rgb)
+    assert rgb is not None
+
+    # Finally, we pick out the red slice and delegate to the 2D version:
+    return _infer_xy_labels(darray.isel(**{rgb: 0}).squeeze(), x, y)
+
+
+def _infer_xy_labels(darray, x, y, imshow=False, rgb=None):
     """
     Determine x and y labels. For use in _plot2d
 
-    darray must be a 2 dimensional data array.
+    darray must be a 2 dimensional data array, or 3d for imshow only.
     """
+    assert x is None or x != y
+    if imshow and darray.ndim == 3:
+        return _infer_xy_labels_3d(darray, x, y, rgb)
 
     if x is None and y is None:
         if darray.ndim != 2:

xarray/tests/test_plot.py

@@ -619,6 +619,8 @@ def test_1d_raises_valueerror(self):
 
     def test_3d_raises_valueerror(self):
         a = DataArray(easy_array((2, 3, 4)))
+        if self.plotfunc.__name__ == 'imshow':
+            pytest.skip()
         with raises_regex(ValueError, r'DataArray must be 2d'):
             self.plotfunc(a)
 
@@ -670,6 +672,11 @@ def test_can_plot_axis_size_one(self):
         if self.plotfunc.__name__ not in ('contour', 'contourf'):
             self.plotfunc(DataArray(np.ones((1, 1))))
 
+    def test_disallows_rgb_arg(self):
+        with pytest.raises(ValueError):
+            # Always invalid for most plots.  Invalid for imshow with 2D data.
+            self.plotfunc(DataArray(np.ones((2, 2))), rgb='not None')
+
     def test_viridis_cmap(self):
         cmap_name = self.plotmethod(cmap='viridis').get_cmap().name
         self.assertEqual('viridis', cmap_name)
@@ -1062,6 +1069,52 @@ def test_2d_coord_names(self):
         with raises_regex(ValueError, 'requires 1D coordinates'):
             self.plotmethod(x='x2d', y='y2d')
 
+    def test_plot_rgb_image(self):
+        DataArray(
+            easy_array((10, 15, 3), start=0),
+            dims=['y', 'x', 'band'],
+        ).plot.imshow()
+        self.assertEqual(0, len(find_possible_colorbars()))
+
+    def test_plot_rgb_image_explicit(self):
+        DataArray(
+            easy_array((10, 15, 3), start=0),
+            dims=['y', 'x', 'band'],
+        ).plot.imshow(y='y', x='x', rgb='band')
+        self.assertEqual(0, len(find_possible_colorbars()))
+
+    def test_plot_rgb_faceted(self):
+        DataArray(
+            easy_array((2, 2, 10, 15, 3), start=0),
+            dims=['a', 'b', 'y', 'x', 'band'],
+        ).plot.imshow(row='a', col='b')
+        self.assertEqual(0, len(find_possible_colorbars()))
+
+    def test_plot_rgba_image_transposed(self):
+        # We can handle the color axis being in any position
+        DataArray(
+            easy_array((4, 10, 15), start=0),
+            dims=['band', 'y', 'x'],
+        ).plot.imshow()
+
+    def test_warns_ambigious_dim(self):
+        arr = DataArray(easy_array((3, 3, 3)), dims=['y', 'x', 'band'])
+        with pytest.warns(UserWarning):
+            arr.plot.imshow()
+        # but doesn't warn if dimensions specified
+        arr.plot.imshow(rgb='band')
+        arr.plot.imshow(x='x', y='y')
+
+    def test_rgb_errors_too_many_dims(self):
+        arr = DataArray(easy_array((3, 3, 3, 3)), dims=['y', 'x', 'z', 'band'])
+        with pytest.raises(ValueError):
+            arr.plot.imshow(rgb='band')
+
+    def test_rgb_errors_bad_dim_sizes(self):
+        arr = DataArray(easy_array((5, 5, 5)), dims=['y', 'x', 'band'])
+        with pytest.raises(ValueError):
+            arr.plot.imshow(rgb='band')
+
 
 class TestFacetGrid(PlotTestCase):