Plot nans (#1782)

* Fix formatting

* Cross-reference matplotlib docs for plot methods

* Handle all-NaN data in plot.imshow

* Handle array dim with size one in plt.imshow

* Add whats-new entry

doc/conf.py

@@ -323,4 +323,5 @@
     'iris': ('http://scitools.org.uk/iris/docs/latest/', None),
     'numpy': ('https://docs.scipy.org/doc/numpy/', None),
     'numba': ('https://numba.pydata.org/numba-doc/latest/', None),
+    'matplotlib': ('https://matplotlib.org/', None),
 }

doc/whats-new.rst

@@ -32,25 +32,29 @@ Enhancements
   By `Ryan Abernathey <https://github.com/rabernat>`_.
 - Experimental support for parsing ENVI metadata to coordinates and attributes
   in :py:func:`xarray.open_rasterio`.
-  By `Matti Eskelinen <https://github.com/maaleske>`
+  By `Matti Eskelinen <https://github.com/maaleske>`_.
 
 .. _Zarr: http://zarr.readthedocs.io/
 
 
 Bug fixes
 ~~~~~~~~~
 
-- Bug fix in vectorized assignment  (:issue:`1743`, `1744`).
-  Now item assignment to :py:meth:`~DataArray.__setitem__` checks
+- Bug fix in vectorized assignment  (:issue:`1743`, :issue:`1744`).
+  Now item assignment to :py:meth:`DataArray.__setitem__` checks
   coordinates of target, destination and keys. If there are any conflict among
   these coordinates, ``IndexError`` will be raised.
   By `Keisuke Fujii <https://github.com/fujiisoup>`_.
+- Properly point :py:meth:`DataArray.__dask_scheduler__` to
+  ``dask.threaded.get``.  By `Matthew Rocklin <https://github.com/mrocklin>`_.
+- Bug fixes in :py:meth:`DataArray.plot.imshow`: all-NaN arrays and arrays
+  with size one in some dimension can now be plotted, which is good for
+  exploring satellite imagery.  (:issue:`1780`)
+  By `Zac Hatfield-Dodds <https://github.com/Zac-HD>`_.
 
 
 .. _whats-new.0.10.0:
 
-- Properly point DataArray.__dask_scheduler__ to dask.threaded.get
-
 v0.10.0 (20 November 2017)
 --------------------------
 

xarray/plot/plot.py

@@ -158,7 +158,7 @@ def line(darray, *args, **kwargs):
     """
     Line plot of 1 dimensional DataArray index against values
 
-    Wraps matplotlib.pyplot.plot
+    Wraps :func:`matplotlib:matplotlib.pyplot.plot`
 
     Parameters
     ----------
@@ -220,7 +220,7 @@ def hist(darray, figsize=None, size=None, aspect=None, ax=None, **kwargs):
     """
     Histogram of DataArray
 
-    Wraps matplotlib.pyplot.hist
+    Wraps :func:`matplotlib:matplotlib.pyplot.hist`
 
     Plots N dimensional arrays by first flattening the array.
 
@@ -565,10 +565,9 @@ def imshow(x, y, z, ax, **kwargs):
     """
     Image plot of 2d DataArray using matplotlib.pyplot
 
-    Wraps matplotlib.pyplot.imshow
-
-    ..note::
+    Wraps :func:`matplotlib:matplotlib.pyplot.imshow`
 
+    .. note::
         This function needs uniformly spaced coordinates to
         properly label the axes. Call DataArray.plot() to check.
 
@@ -581,8 +580,15 @@ def imshow(x, y, z, ax, **kwargs):
                          'pcolormesh or contour(f)')
 
     # Centering the pixels- Assumes uniform spacing
-    xstep = (x[1] - x[0]) / 2.0
-    ystep = (y[1] - y[0]) / 2.0
+    try:
+        xstep = (x[1] - x[0]) / 2.0
+    except IndexError:
+        # Arbitrary default value, similar to matplotlib behaviour
+        xstep = .1
+    try:
+        ystep = (y[1] - y[0]) / 2.0
+    except IndexError:
+        ystep = .1
     left, right = x[0] - xstep, x[-1] + xstep
     bottom, top = y[-1] + ystep, y[0] - ystep
 
@@ -608,7 +614,7 @@ def contour(x, y, z, ax, **kwargs):
     """
     Contour plot of 2d DataArray
 
-    Wraps matplotlib.pyplot.contour
+    Wraps :func:`matplotlib:matplotlib.pyplot.contour`
     """
     primitive = ax.contour(x, y, z, **kwargs)
     return primitive
@@ -619,7 +625,7 @@ def contourf(x, y, z, ax, **kwargs):
     """
     Filled contour plot of 2d DataArray
 
-    Wraps matplotlib.pyplot.contourf
+    Wraps :func:`matplotlib:matplotlib.pyplot.contourf`
     """
     primitive = ax.contourf(x, y, z, **kwargs)
     return primitive
@@ -635,6 +641,8 @@ def _infer_interval_breaks(coord, axis=0):
     """
     coord = np.asarray(coord)
     deltas = 0.5 * np.diff(coord, axis=axis)
+    if deltas.size == 0:
+        deltas = np.array(0.0)
     first = np.take(coord, [0], axis=axis) - np.take(deltas, [0], axis=axis)
     last = np.take(coord, [-1], axis=axis) + np.take(deltas, [-1], axis=axis)
     trim_last = tuple(slice(None, -1) if n == axis else slice(None)
@@ -647,7 +655,7 @@ def pcolormesh(x, y, z, ax, infer_intervals=None, **kwargs):
     """
     Pseudocolor plot of 2d DataArray
 
-    Wraps matplotlib.pyplot.pcolormesh
+    Wraps :func:`matplotlib:matplotlib.pyplot.pcolormesh`
     """
 
     # decide on a default for infer_intervals (GH781)

xarray/plot/utils.py

@@ -165,6 +165,11 @@ def _determine_cmap_params(plot_data, vmin=None, vmax=None, cmap=None,
 
     calc_data = np.ravel(plot_data[~pd.isnull(plot_data)])
 
+    # Handle all-NaN input data gracefully
+    if calc_data.size == 0:
+        # Arbitrary default for when all values are NaN
+        calc_data = np.array(0.0)
+
     # Setting center=False prevents a divergent cmap
     possibly_divergent = center is not False
 

xarray/tests/test_plot.py

@@ -624,6 +624,14 @@ def test_plot_nans(self):
         clim2 = self.plotfunc(x2).get_clim()
         self.assertEqual(clim1, clim2)
 
+    def test_can_plot_all_nans(self):
+        # regression test for issue #1780
+        self.plotfunc(DataArray(np.full((2, 2), np.nan)))
+
+    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_viridis_cmap(self):
         cmap_name = self.plotmethod(cmap='viridis').get_cmap().name
         self.assertEqual('viridis', cmap_name)