Merge pull request #2156 from kgoebber/add_declarative_smooth

add smoothing for declarative

src/metpy/plots/declarative.py

@@ -20,7 +20,7 @@
 from ._mpl import TextCollection
 from .cartopy_utils import import_cartopy
 from .station_plot import StationPlot
-from ..calc import reduce_point_density
+from ..calc import reduce_point_density, smooth_n_point
 from ..package_tools import Exporter
 from ..units import units
 
@@ -1062,6 +1062,19 @@ class PlotScalar(Plots2D):
     `list(ds)`
     """
 
+    smooth_field = Int(allow_none=True, default_value=None)
+    smooth_field.__doc__ = """Number of smoothing passes using 9-pt smoother.
+
+    By setting this parameter with an integer value it will call the MetPy 9-pt smoother and
+    provide a smoothed field for plotting. It is best to use this smoothing for data with
+    finer resolutions (e.g., smaller grid spacings with a lot of grid points).
+
+    See Also
+    --------
+    metpy.calc.smooth_n_point
+
+    """
+
     @observe('field')
     def _update_data(self, _=None):
         """Handle updating the internal cache of data.
@@ -1099,6 +1112,10 @@ def griddata(self):
                     'for plotting'
                 )
 
+            # Handle smoothing of data
+            if self.smooth_field is not None:
+                data_subset = smooth_n_point(data_subset, 9, self.smooth_field)
+
             # Handle unit conversion (both direct unit specification and scaling)
             if self.plot_units is not None:
                 data_subset = data_subset.metpy.convert_units(self.plot_units)

tests/plots/test_declarative.py

@@ -106,6 +106,36 @@ def test_declarative_figsize():
     return pc.figure
 
 
+@pytest.mark.mpl_image_compare(remove_text=True,
+                               tolerance={'3.0': 0.216}.get(MPL_VERSION, 0.022))
+@needs_cartopy
+def test_declarative_smooth_field():
+    """Test the smoothing of the field with smooth_field trait."""
+    data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
+
+    contour = ContourPlot()
+    contour.data = data
+    contour.field = 'Geopotential_height'
+    contour.level = 700 * units.hPa
+    contour.contours = list(range(0, 4000, 30))
+    contour.linewidth = 1
+    contour.linecolor = 'black'
+    contour.smooth_field = 3
+
+    panel = MapPanel()
+    panel.area = 'us'
+    panel.projection = 'lcc'
+    panel.layers = ['coastline', 'borders', 'usstates']
+    panel.plots = [contour]
+
+    pc = PanelContainer()
+    pc.size = (10.5, 10.5)
+    pc.panels = [panel]
+    pc.draw()
+
+    return pc.figure
+
+
 @pytest.mark.mpl_image_compare(remove_text=True,
                                tolerance={'3.0': 0.328}.get(MPL_VERSION, 0.022))
 @needs_cartopy