[semver:patch] Compatibility fixes for matplotlib 3.5 (#32)

Compatibility fixes

Changed
=======

- We now use the new `convert_coordinate` method that has been introduced with
  psyplot v1.4.1 (see psyplot/psyplot#39 and #30)

Fixed
=====
- psy-simple is now compatible with matplotlib 3.5 (see #31)

Author: Chilipp

.appveyor.yml

@@ -18,6 +18,7 @@ install:
     - pip install -i https://pypi.anaconda.org/psyplot/simple --no-deps psyplot-ci-orb
     - conda config --add channels conda-forge
     - conda config --add channels psyplot
+    - conda config --add channels psyplot/label/develop
     - conda info -a
     - conda list
     # windows config
@@ -43,7 +44,7 @@ after_test:
 deploy_script:
     - cmd: "
         IF NOT DEFINED APPVEYOR_REPO_TAG_NAME (
-            deploy-conda-recipe -l %APPVEYOR_REPO_BRANCH% -py %PYTHON_VERSION% ci/conda-recipe
+            deploy-conda-recipe -l %APPVEYOR_REPO_BRANCH:/=-% -py %PYTHON_VERSION% ci/conda-recipe
         ) ELSE (
             deploy-conda-recipe -py %PYTHON_VERSION% ci/conda-recipe
         )"

.circleci/config.yml

@@ -1,7 +1,7 @@
 version: 2.1
 
 orbs:
-  psyplot: psyplot/[email protected].25
+  psyplot: psyplot/[email protected].29
   mattermost-plugin-notify: nathanaelhoun/[email protected]
 
 executors:
@@ -28,7 +28,7 @@ parameters:
   parallelism:
     description: How many parallel jobs to execute
     type: integer
-    default: 2
+    default: 4
   build_docs:
     description: Build the documentation
     type: boolean
@@ -46,6 +46,7 @@ workflows:
           build_args: "--no-test"
           build_docs: << pipeline.parameters.build_docs >>
           env_packages: pytest-cov dask psyplot-gui statsmodels netcdf4 seaborn
+          default_branch: develop
       - psyplot/test-parallel:
           name: test-matplotlib-latest
           parallelism: << pipeline.parameters.parallelism >>

CHANGELOG.rst

@@ -1,3 +1,19 @@
+v1.4.1
+======
+Compatibility fixes
+
+Changed
+-------
+- We now use the new ``convert_coordinate`` method that has been introduced
+  with psyplot v1.4.1 (see
+  `psyplot/psyplot#39 <https://github.com/psyplot/psyplot/pull/39>`__ and
+  `#30 <https://github.com/psyplot/psy-simple/pull/30>`__)
+
+Fixed
+-----
+- psy-simple is now compatible with matplotlib 3.5 (see
+  `#31 <https://github.com/psyplot/psy-simple/pull/31>`__)
+
 v1.4.0
 ======
 Compatibility fixes and LGPL license

docs/environment.yml

@@ -1,6 +1,7 @@
 name: psyplot_docs
 channels:
     - local
+    - psyplot/label/__CURRENTBRANCH__
     - psyplot/label/master
     - conda-forge
 dependencies:

psy_simple/colors.py

@@ -28,6 +28,7 @@
 # You should have received a copy of the GNU LGPL-3.0 license
 # along with this program.  If not, see <https://www.gnu.org/licenses/>.
 
+from psyplot.compat.pycompat import isstring
 import six
 import matplotlib as mpl
 from matplotlib.colors import Colormap, LinearSegmentedColormap, BoundaryNorm
@@ -203,11 +204,11 @@ def get_cmap(name, lut=None):
     Different from the :func::`matpltolib.pyplot.get_cmap` function, this
     function changes the number of colors if `name` is a
     :class:`matplotlib.colors.Colormap` instance to match the given `lut`."""
-    if name in rcParams['colors.cmaps']:
+    if isstring(name) and name in rcParams['colors.cmaps']:
         colors = rcParams['colors.cmaps'][name]
         lut = lut or len(colors)
         return FixedColorMap.from_list(name=name, colors=colors, N=lut)
-    elif name in _cmapnames:
+    elif isstring(name) and name in _cmapnames:
         colors = _cmapnames[name]
         lut = lut or len(colors)
         return FixedColorMap.from_list(name=name, colors=colors, N=lut)

psy_simple/plotters.py

@@ -138,6 +138,11 @@ def convert_radian(coord, *variables):
     xr.Variable
         The transformed variable if one of the given `variables` has units in
         radian"""
+    warn(
+        "The psy_simple.plotters.convert_radian method has been deprecated."
+        "Please use the `plotter.convert_coordinate` instead.",
+        DeprecationWarning
+    )
     if any(v.attrs.get('units', '').startswith('radian') for v in variables):
         return coord * 180. / np.pi
     return coord
@@ -2807,8 +2812,7 @@ def array(self):
                 data, axis='x', coords=data.coords)
             if bounds is None:
                 bounds = xcoord
-            if self.plotter.convert_radian:
-                bounds = convert_radian(bounds, xcoord, bounds)
+            bounds = self.convert_coordinate(bounds, xcoord)
             return bounds.values.ravel()
         return self.decoder.get_plotbounds(xcoord)
 
@@ -2826,8 +2830,7 @@ def array(self):
                 data, axis='y', coords=data.coords)
             if bounds is None:
                 bounds = ycoord
-            if self.plotter.convert_radian:
-                bounds = convert_radian(bounds, ycoord, bounds)
+            bounds = self.convert_coordinate(bounds, ycoord)
             return bounds.values.ravel()
         return self.decoder.get_plotbounds(self.transpose.get_y(self.data))
 
@@ -3128,6 +3131,9 @@ def update(self, value):
         else:
             if isinstance(value[0], six.string_types):
                 value = self.calc_funcs[value[0]](*value[1:])
+            if value[0] == value[-1]:
+                # make sure we have a small difference between the values
+                value[-1] += value[-1] * 0.5
             self.bounds = value
             self.norm = mpl.colors.BoundaryNorm(
                 value, len(value) - 1)
@@ -3216,8 +3222,7 @@ class Plot2D(Formatoption):
         dataset, we will interpolate them
     'contourf'
         Make a filled contour plot using the :func:`matplotlib.pyplot.contourf`
-        function or the :func:`matplotlib.pyplot.tricontourf` for unstructured
-        data. The levels for the contour plot are controlled by the
+        function. The levels for the contour plot are controlled by the
         :attr:`levels` formatoption
     'contour'
         Same a ``'contourf'``, but does not make a filled contour plot, only
@@ -3351,19 +3356,15 @@ def _contourf(self):
             self.remove()
         arr = self.array
         cmap = self.cmap.get_cmap(arr)
-        filled = self.value not in ['contour', 'tricontour']
+        filled = self.value != 'contour'
         if hasattr(self, '_plot'):
             self._plot.set_cmap(cmap)
             self._plot.set_norm(self.bounds.norm)
         else:
             levels = self.levels.norm.boundaries
-            xcoord = self.xcoord
-            ycoord = self.ycoord
-            if self.plotter.convert_radian:
-                xcoord = convert_radian(xcoord, xcoord)
-                ycoord = convert_radian(ycoord, ycoord)
-            if (self.value in ['tricontourf', 'tricontour'] or
-                    self.decoder.is_unstructured(self.raw_data)):
+            xcoord = self.convert_coordinate(self.xcoord)
+            ycoord = self.convert_coordinate(self.ycoord)
+            if self.decoder.is_unstructured(self.raw_data):
                 pm = self.ax.tricontourf if filled else self.ax.tricontour
                 mask = ~np.isnan(arr)
                 x = xcoord.values[mask]
@@ -3385,8 +3386,7 @@ def cell_nodes_x(self):
         data = self.data
         xbounds = decoder.get_cell_node_coord(
             data, coords=data.coords, axis='x')
-        if self.plotter.convert_radian:
-            xbounds = convert_radian(xbounds, xcoord, xbounds)
+        xbounds = self.convert_coordinate(xbounds, xcoord)
         return xbounds.values
 
     @property
@@ -3397,8 +3397,7 @@ def cell_nodes_y(self):
         data = self.data
         ybounds = decoder.get_cell_node_coord(
             data, coords=data.coords, axis='y')
-        if self.plotter.convert_radian:
-            ybounds = convert_radian(ybounds, ycoord, ybounds)
+        ybounds = self.convert_coordinate(ybounds, ycoord)
         return ybounds.values
 
     def _polycolor(self):
@@ -3631,8 +3630,7 @@ def cell_nodes_x(self):
         xbounds = decoder.get_cell_node_coord(
             data, coords=data.coords, axis='x',
             nans='skip' if self.mask_datagrid.value else None)
-        if self.plotter.convert_radian:
-            xbounds = convert_radian(xbounds, xcoord, xbounds)
+        xbounds = self.convert_coordinate(xbounds, xcoord)
         return xbounds.values
 
     @property
@@ -3644,8 +3642,7 @@ def cell_nodes_y(self):
         ybounds = decoder.get_cell_node_coord(
             data, coords=data.coords, axis='y',
             nans='skip' if self.mask_datagrid.value else None)
-        if self.plotter.convert_radian:
-            ybounds = convert_radian(ybounds, ycoord, ybounds)
+        ybounds = self.convert_coordinate(ybounds, ycoord, ybounds)
         return ybounds.values
 
     def __init__(self, *args, **kwargs):
@@ -3993,8 +3990,14 @@ def update_colorbar(self, pos):
                     old.callbacksSM.disconnect(old.colorbar_cid)
                     old.colorbar = None
                     old.colorbar_cid = None
-                cid = mappable.callbacksSM.connect(
-                    'changed', cbar.on_mappable_changed)
+                if mpl.__version__ < "3.3":
+                    cid = mappable.callbacksSM.connect(
+                        'changed', cbar.on_mappable_changed
+                    )
+                else:
+                    cid = mappable.callbacksSM.connect(
+                        'changed', cbar.update_normal
+                    )
                 mappable.colorbar = cbar
                 mappable.colorbar_cid = cid
             cbar.update_normal(cbar.mappable)
@@ -4092,6 +4095,18 @@ def draw_colorbar(self, pos):
             kwargs['extend'] = self.extend.value
         if 'location' not in kwargs:
             kwargs['orientation'] = orientation
+        if mpl.__version__.startswith("3.5.0"):
+            from matplotlib.contour import ContourSet
+            if (
+                kwargs.get("orientation") == "horizontal" and
+                isinstance(self.plot.mappable, ContourSet)
+            ):
+                warn(
+                    "Horizontal colorbars are not possible for contour plots "
+                    "with matplotlib 3.5.0, see "
+                    "https://github.com/matplotlib/matplotlib/issues/21683"
+                )
+                kwargs.pop("orientation")
         self.cbars[pos] = cbar = fig.colorbar(self.plot.mappable, **kwargs)
         self._just_drawn.add(cbar)
         self.set_label_pos(pos)
@@ -4897,8 +4912,9 @@ def keep(x):
             except ValueError:
                 pass
             # remove arrows
-            self.ax.patches = [patch for patch in self.ax.patches
-                               if keep(patch)]
+            for patch in list(self.ax.patches):
+                if not keep(patch):
+                    self.ax.patches.remove(patch)
         else:
             try:
                 self._plot.remove()
@@ -5650,10 +5666,6 @@ class Base2D(Plotter):
     """Base plotter for 2-dimensional plots
     """
 
-    #: Boolean that is True if coordinates with units in radian should be
-    #: converted to degrees
-    convert_radian = False
-
     _rcparams_string = ['plotter.plot2d.']
 
     cmap = CMap('cmap')

psy_simple/plugin.py

@@ -40,8 +40,8 @@
     validate_stringset)
 from matplotlib.rcsetup import (
     validate_bool, validate_color, validate_fontsize,
-    ValidateInStrings, validate_int, validate_legend_loc,
-    validate_colorlist)
+    ValidateInStrings, validate_int, validate_colorlist
+)
 from psy_simple import __version__ as plugin_version
 import xarray as xr
 
@@ -437,6 +437,16 @@ def validate_sym_lims(val):
     return list(map(validator, val))
 
 
+valid_legend_locs = [
+    "best",
+    "upper right", "upper left", "lower left", "lower right", "right",
+    "center left", "center right", "lower center", "upper center",
+    "center"
+]
+
+validate_legend_loc = ValidateInStrings("legend_loc", valid_legend_locs, True)
+
+
 def validate_legend(value):
     if isinstance(value, dict):
         return value
@@ -713,19 +723,9 @@ def __call__(self, val):
 
 def validate_plot(val):
     validator = ValidateInStrings(
-        '2d plot', ['mesh', 'contourf', 'contour', 'poly',
-                    'tri', 'tricontourf', 'tricontour'], True)
+        '2d plot', ['mesh', 'contourf', 'contour', 'poly'], True)
 
     val = validator(val)
-    depr_map = {
-        "tri": "poly", "tricontourf": "contourf", "tricontour": "contour"
-    }
-    if val in depr_map:
-        warn("plot=%r is depreceated for the plot formatoption and will be "
-             "removed in psy-simple 1.4.0. Please use plot=%r instead." % (
-                 val, depr_map[val]),
-             DeprecationWarning)
-        return depr_map[val]
     return val
 
 

tests/test_plot2d.py

@@ -402,20 +402,7 @@ def test_single_level(self):
         ds = xr.Dataset()
         ds["test"] = (("y", "x"), np.ones((4, 5)))
         sp = ds.psy.plot.plot2d(cmap="Reds", bounds=["rounded", 3])
-        self.assertEqual(list(sp.plotters[0].bounds.bounds), [1.0, 1.0, 1.0])
-
-
-@pytest.mark.parametrize(
-    "old,new",
-    (("tri", "poly"), ("tricontour", "contour"), ("tricontourf", "contourf")),
-)
-def test_plot_deprecation(old, new):
-    """Test if tri is deprecated correctly"""
-    with psy.open_dataset(os.path.join(bt.test_dir, "icon_test.nc")) as ds:
-        with pytest.warns(DeprecationWarning, match="plot=[\"']%s[\"']" % old):
-            sp = ds.psy.plot.plot2d(name="t2m", plot=old)
-    plotter = sp.plotters[0]
-    assert plotter.plot.value == new
+        self.assertEqual(list(sp.plotters[0].bounds.bounds), [1.0, 1.0, 1.5])
 
 
 def test_plot_poly_3D_bounds():