New infer_intervals keyword for pcolormesh

doc/plotting.rst

@@ -522,3 +522,56 @@ the values on the y axis are decreasing with -0.5 on the top. This is because
 the pixels are centered over their coordinates, and the
 axis labels and ranges correspond to the values of the
 coordinates.
+
+Multidimensional coordinates
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+See also: :ref:`examples.multidim`.
+
+You can plot irregular grids defined by multidimensional coordinates with
+xarray, but you'll have to tell the plot function to use these coordinates
+instead of the default ones:
+
+.. ipython:: python
+
+    lon, lat = np.meshgrid(np.linspace(-20, 20, 5), np.linspace(0, 30, 4))
+    lon += lat/10
+    lat += lon/10
+    da = xr.DataArray(np.arange(20).reshape(4, 5), dims=['y', 'x'],
+                      coords = {'lat': (('y', 'x'), lat),
+                                'lon': (('y', 'x'), lon)})
+
+    @savefig plotting_example_2d_irreg.png width=4in
+    da.plot.pcolormesh('lon', 'lat');
+
+Note that in this case, xarray still follows the pixel centered convention.
+This might be undesirable in some cases, for example when your data is defined
+on a polar projection (:issue:`781`). This is why the default is to not follow
+this convention when plotting on a map:
+
+.. ipython:: python
+
+    import cartopy.crs as ccrs
+    ax = plt.subplot(projection=ccrs.PlateCarree());
+    da.plot.pcolormesh('lon', 'lat', ax=ax);
+    ax.scatter(lon, lat, transform=ccrs.PlateCarree());
+    @savefig plotting_example_2d_irreg_map.png width=4in
+    ax.coastlines(); ax.gridlines(draw_labels=True);
+
+You can however decide to infer the cell boundaries and use the
+``infer_intervals`` keyword:
+
+.. ipython:: python
+
+    ax = plt.subplot(projection=ccrs.PlateCarree());
+    da.plot.pcolormesh('lon', 'lat', ax=ax, infer_intervals=True);
+    ax.scatter(lon, lat, transform=ccrs.PlateCarree());
+    @savefig plotting_example_2d_irreg_map_infer.png width=4in
+    ax.coastlines(); ax.gridlines(draw_labels=True);
+
+.. note::
+    The data model of xarray does not support datasets with `cell boundaries`_
+    yet. If you want to use these coordinates, you'll have to make the plots
+    outside the xarray framework.
+
+.. _cell boundaries: http://cfconventions.org/cf-conventions/v1.6.0/cf-conventions.html#cell-boundaries

doc/whats-new.rst

@@ -108,6 +108,11 @@ Bug fixes
 - ``Dataset.concat()`` now preserves variables order (:issue:`1027`).
   By `Fabien Maussion <https://github.com/fmaussion>`_.
 
+- Fixed an issue with pcolormesh (:issue:`781`). A new
+  ``infer_intervals`` keyword gives control on whether the cell intervals
+  should be computed or not.
+  By `Fabien Maussion <https://github.com/fmaussion>`_.
+
 .. _whats-new.0.8.2:
 
 v0.8.2 (18 August 2016)

xarray/plot/plot.py

@@ -316,6 +316,12 @@ def _plot2d(plotfunc):
         provided, extend is inferred from vmin, vmax and the data limits.
     levels : int or list-like object, optional
         Split the colormap (cmap) into discrete color intervals.
+    infer_intervals : bool, optional
+        Only applies to pcolormesh. If True, the coordinate intervals are
+        passed to pcolormesh. If False, the original coordinates are used
+        (this can be useful for certain map projections). The default is to
+        always infer intervals, unless the mesh is irregular and plotted on
+        a map projection.
     subplot_kws : dict, optional
         Dictionary of keyword arguments for matplotlib subplots. Only applies
         to FacetGrid plotting.
@@ -341,8 +347,9 @@ def newplotfunc(darray, x=None, y=None, ax=None, row=None, col=None,
                     col_wrap=None, xincrease=True, yincrease=True,
                     add_colorbar=None, add_labels=True, vmin=None, vmax=None,
                     cmap=None, center=None, robust=False, extend=None,
-                    levels=None, colors=None, subplot_kws=None,
-                    cbar_ax=None, cbar_kwargs=None, **kwargs):
+                    levels=None, infer_intervals=None, colors=None,
+                    subplot_kws=None, cbar_ax=None, cbar_kwargs=None,
+                    **kwargs):
         # All 2d plots in xarray share this function signature.
         # Method signature below should be consistent.
 
@@ -416,6 +423,9 @@ def newplotfunc(darray, x=None, y=None, ax=None, row=None, col=None,
             kwargs['extend'] = cmap_params['extend']
             kwargs['levels'] = cmap_params['levels']
 
+        if 'pcolormesh' == plotfunc.__name__:
+            kwargs['infer_intervals'] = infer_intervals
+
         # This allows the user to pass in a custom norm coming via kwargs
         kwargs.setdefault('norm', cmap_params['norm'])
 
@@ -456,8 +466,8 @@ def plotmethod(_PlotMethods_obj, x=None, y=None, ax=None, row=None,
                    col=None, col_wrap=None, xincrease=True, yincrease=True,
                    add_colorbar=None, add_labels=True, vmin=None, vmax=None,
                    cmap=None, colors=None, center=None, robust=False,
-                   extend=None, levels=None, subplot_kws=None,
-                   cbar_ax=None, cbar_kwargs=None, **kwargs):
+                   extend=None, levels=None, infer_intervals=None,
+                   subplot_kws=None, cbar_ax=None, cbar_kwargs=None, **kwargs):
         """
         The method should have the same signature as the function.
 
@@ -542,29 +552,52 @@ def contourf(x, y, z, ax, **kwargs):
     return ax, primitive
 
 
-def _infer_interval_breaks(coord):
+def _infer_interval_breaks(coord, axis=0):
     """
     >>> _infer_interval_breaks(np.arange(5))
     array([-0.5,  0.5,  1.5,  2.5,  3.5,  4.5])
+    >>> _infer_interval_breaks([[0, 1], [3, 4]], axis=1)
+    array([[-0.5,  0.5,  1.5],
+           [ 2.5,  3.5,  4.5]])
     """
     coord = np.asarray(coord)
-    deltas = 0.5 * (coord[1:] - coord[:-1])
-    first = coord[0] - deltas[0]
-    last = coord[-1] + deltas[-1]
-    return np.r_[[first], coord[:-1] + deltas, [last]]
+    deltas = 0.5 * np.diff(coord, axis=axis)
+    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)
+                      for n in range(coord.ndim))
+    return np.concatenate([first, coord[trim_last] + deltas, last], axis=axis)
 
 
 @_plot2d
-def pcolormesh(x, y, z, ax, **kwargs):
+def pcolormesh(x, y, z, ax, infer_intervals=None, **kwargs):
     """
     Pseudocolor plot of 2d DataArray
 
     Wraps matplotlib.pyplot.pcolormesh
     """
 
-    if not hasattr(ax, 'projection'):
-        x = _infer_interval_breaks(x)
-        y = _infer_interval_breaks(y)
+    # decide on a default for infer_intervals (GH781)
+    x = np.asarray(x)
+    if infer_intervals is None:
+        if hasattr(ax, 'projection'):
+            if len(x.shape) == 1:
+                infer_intervals = True
+            else:
+                infer_intervals = False
+        else:
+            infer_intervals = True
+
+    if infer_intervals:
+        if len(x.shape) == 1:
+            x = _infer_interval_breaks(x)
+            y = _infer_interval_breaks(y)
+        else:
+            # we have to infer the intervals on both axes
+            x = _infer_interval_breaks(x, axis=1)
+            x = _infer_interval_breaks(x, axis=0)
+            y = _infer_interval_breaks(y, axis=1)
+            y = _infer_interval_breaks(y, axis=0)
 
     primitive = ax.pcolormesh(x, y, z, **kwargs)
 

xarray/test/test_plot.py

@@ -1,3 +1,5 @@
+from __future__ import division
+
 import inspect
 
 import numpy as np
@@ -112,6 +114,17 @@ def test__infer_interval_breaks(self):
         self.assertArrayEqual(pd.date_range('20000101', periods=4) - np.timedelta64(12, 'h'),
                               _infer_interval_breaks(pd.date_range('20000101', periods=3)))
 
+        # make a bounded 2D array that we will center and re-infer
+        xref, yref = np.meshgrid(np.arange(6), np.arange(5))
+        cx = (xref[1:, 1:] + xref[:-1, :-1]) / 2
+        cy = (yref[1:, 1:] + yref[:-1, :-1]) / 2
+        x = _infer_interval_breaks(cx, axis=1)
+        x = _infer_interval_breaks(x, axis=0)
+        y = _infer_interval_breaks(cy, axis=1)
+        y = _infer_interval_breaks(y, axis=0)
+        np.testing.assert_allclose(xref, x)
+        np.testing.assert_allclose(yref, y)
+
     def test_datetime_dimension(self):
         nrow = 3
         ncol = 4