Add SPC hatch effect for PlotGeometry

Add hatching effect to mimic hatching used for SPC probabilistic severe
weather outlooks. Testing and an example were also added.

Closes Unidata#2063

Author: nawendt

examples/plots/spc_probabilistic_tornado_outlook.py

@@ -0,0 +1,56 @@
+#  Copyright (c) 2021 MetPy Developers.
+#  Distributed under the terms of the BSD 3-Clause License.
+#  SPDX-License-Identifier: BSD-3-Clause
+"""
+NOAA SPC Probabilistic Outlook
+==============================
+
+Demonstrate the use of geoJSON and shapefile data with PlotGeometry in MetPy's simplified
+plotting interface. This example walks through plotting the Day 1 Probabilistic Tornado
+Outlook from NOAA Storm Prediction Center. The geoJSON file was retrieved from the
+`Storm Prediction Center's archives <https://www.spc.noaa.gov/archive/>`_.
+"""
+
+import geopandas
+
+from metpy.cbook import get_test_data
+from metpy.plots import MapPanel, PanelContainer, PlotGeometry
+
+###########################
+# Read in the geoJSON file containing the convective outlook.
+day1_outlook = geopandas.read_file(
+    get_test_data('spc_day1otlk_20210317_1200_torn.lyr.geojson')
+)
+
+###########################
+# Preview the data.
+day1_outlook
+
+###########################
+# Plot the shapes from the 'geometry' column. Give the shapes their fill and stroke color by
+# providing the 'fill' and 'stroke' columns. Use text from the 'LABEL' column as labels for the
+# shapes. For the SIG area, remove the fill and label while adding the proper hatch effect.
+geo = PlotGeometry()
+geo.geometry = day1_outlook['geometry']
+geo.fill = day1_outlook['fill']
+geo.stroke = day1_outlook['stroke']
+geo.labels = day1_outlook['LABEL']
+sig_index = day1_outlook['LABEL'].values.tolist().index('SIGN')
+geo.fill[sig_index] = 'none'
+geo.labels[sig_index] = None
+geo.label_fontsize = 'large'
+geo.hatch = ['SS' if label == 'SIGN' else None for label in day1_outlook['LABEL']]
+
+###########################
+# Add the geometry plot to a panel and container.
+panel = MapPanel()
+panel.title = 'SPC Day 1 Probabilistic Tornado Outlook (Valid 12z Mar 17 2021)'
+panel.plots = [geo]
+panel.area = [-120, -75, 25, 50]
+panel.projection = 'lcc'
+panel.layers = ['lakes', 'land', 'ocean', 'states', 'coastline', 'borders']
+
+pc = PanelContainer()
+pc.size = (12, 8)
+pc.panels = [panel]
+pc.show()

src/metpy/plots/__init__.py

@@ -3,6 +3,8 @@
 # SPDX-License-Identifier: BSD-3-Clause
 r"""Contains functionality for making meteorological plots."""
 
+import matplotlib.hatch
+
 # Trigger matplotlib wrappers
 from . import _mpl  # noqa: F401
 from . import cartopy_utils
@@ -25,6 +27,8 @@
 
 set_module(globals())
 
+matplotlib.hatch._hatch_types.append(SPCHatch)
+
 
 def __getattr__(name):
     """Handle warning if Cartopy map features are not available."""

src/metpy/plots/declarative.py

@@ -9,6 +9,8 @@
 from itertools import cycle
 import re
 
+import matplotlib.hatch
+import matplotlib.patches as mpatches
 import matplotlib.patheffects as patheffects
 import matplotlib.pyplot as plt
 import numpy as np
@@ -498,6 +500,23 @@ def lookup_map_feature(feature_name):
     return feat.with_scale(scaler)
 
 
+@exporter.export
+class SPCHatch(matplotlib.hatch.Shapes):
+    """Class to create hatching for significant severe areas."""
+
+    filled = True
+    size = 1.0
+    path = mpatches.Polygon([[0, 0], [0.4, 0.4]],
+                            closed=True,
+                            fill=False).get_path()
+
+    def __init__(self: 'SPCHatch', hatch: str, density: float):
+        self.num_rows = (hatch.count('S')) * density
+        self.shape_vertices = self.path.vertices
+        self.shape_codes = self.path.codes
+        matplotlib.hatch.Shapes.__init__(self, hatch, density)
+
+
 class MetPyHasTraits(HasTraits):
     """Provides modification layer on HasTraits for declarative classes."""
 
@@ -1927,6 +1946,16 @@ class PlotGeometry(MetPyHasTraits):
     object, and so on. Default value is `fill`.
     """
 
+    hatch = Union([Instance(collections.abc.Iterable), Unicode()], default_value=None,
+                  allow_none=True)
+    hatch.__doc__ = """Hatch style for plotted polygons.
+
+    A single string or collection of strings for the hatch style If a collection, the first
+    string corresponds to the hatching of the first Shapely polygon in `geometry`, the second
+    string corresponds to the label of the second Shapely polygon, and so on. Default value
+    is `None`.
+    """
+
     @staticmethod
     @validate('geometry')
     def _valid_geometry(_, proposal):
@@ -1975,6 +2004,17 @@ def _update_label_colors(self, change):
         elif change['name'] == 'stroke' and self.label_facecolor is None:
             self.label_facecolor = self.stroke
 
+    @staticmethod
+    @validate('hatch')
+    def _valid_hatch(_, proposal):
+        """Cast `hatch` into a list once it is provided by user.
+
+        This is necessary because _build() expects to cycle through a list of hatch styles
+        when assigning them to the geometry.
+        """
+        hatch = proposal['value']
+        return list(hatch) if not isinstance(hatch, str) else [hatch]
+
     @property
     def name(self):
         """Generate a name for the plot."""
@@ -2065,14 +2105,15 @@ def _build(self):
                                 else self.label_edgecolor)
         self.label_facecolor = (['none'] if self.label_facecolor is None
                                 else self.label_facecolor)
+        self.hatch = [None] if self.hatch is None else self.hatch
 
         # Each Shapely object is plotted separately with its corresponding colors and label
-        for geo_obj, stroke, fill, label, fontcolor, fontoutline in zip(
+        for geo_obj, stroke, fill, label, fontcolor, fontoutline, hatch in zip(
                 self.geometry, cycle(self.stroke), cycle(self.fill), cycle(self.labels),
-                cycle(self.label_facecolor), cycle(self.label_edgecolor)):
+                cycle(self.label_facecolor), cycle(self.label_edgecolor), cycle(self.hatch)):
             # Plot the Shapely object with the appropriate method and colors
             if isinstance(geo_obj, (MultiPolygon, Polygon)):
-                self.parent.ax.add_geometries([geo_obj], edgecolor=stroke,
+                self.parent.ax.add_geometries([geo_obj], hatch=hatch, edgecolor=stroke,
                                               facecolor=fill, crs=ccrs.PlateCarree())
             elif isinstance(geo_obj, (MultiLineString, LineString)):
                 self.parent.ax.add_geometries([geo_obj], edgecolor=stroke,

src/metpy/static-data-manifest.txt

@@ -207,6 +207,7 @@ nov11_sounding.txt 6fa3e0920314a7d55d6e1020eb934e18d9623c5fb1a40aaad546a25ed225e
 rbf_test.npz f035f4415ea9bf04dcaf8affd7748f6519638655dcce90dad2b54fe0032bf32d
 sfstns.tbl f665188f5d5f2ffa892e8c082101adf8245b8f03fbb8e740912d618ac46802c7
 spc_day1otlk_20210317_1200_lyr.geojson 785f548d059658340b1b70f69924696c1918b36588c3c083675e725090421484
+spc_day1otlk_20210317_1200_torn.lyr.geojson 500d15f3449e8f3d34491ddc007279bb6dc59099025471000cce985d11debd50
 station_data.txt 3c1b71abb95ef8fe4adf57e47e2ce67f3529c6fe025b546dd40c862999fc5ffe
 stations.txt 5052f237edf0d89f4bcb8fc4a338769ad435177b4361a59ffb80cea64e0f2266
 timeseries.csv 2d79f8f21ad1fcec12d0e24750d0958631e92c9148adfbd1b7dc8defe8c56fc5

staticdata/spc_day1otlk_20210317_1200_torn.lyr.geojson

@@ -0,0 +1 @@
+{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-85.71543812233286, 29.550281650071128], [-85.767, 29.696], [-85.985, 29.876], [-86.462, 30.068], [-87.771, 29.878], [-88.406, 29.863], [-88.432, 29.714], [-88.695, 29.394], [-88.581, 29.249], [-88.619, 29.022], [-88.937, 28.691], [-89.175, 28.63], [-89.399, 28.577], [-89.712, 28.693], [-89.828, 28.916], [-90.102, 28.755], [-90.54, 28.711], [-90.745, 28.711], [-91.083, 28.732], [-91.315, 28.893], [-91.556, 28.983], [-91.655, 29.121], [-91.742, 29.058], [-92.079, 29.114], [-92.164, 29.181], [-92.629, 29.233], [-93.243, 29.441], [-93.588, 29.43], [-93.777, 29.35], [-93.79386784706185, 29.349816653836285], [-95.26, 30.12], [-95.62, 30.99], [-95.51, 33.3], [-95.95, 35.35], [-96.39, 36.97], [-96.07, 37.81], [-93.57, 38.27], [-89.44, 38.06], [-87.08, 37.25], [-85.28, 35.81], [-83.15, 34.2], [-82.45, 33.45], [-82.09, 32.83], [-82.37, 32.26], [-83.31, 31.96], [-83.8, 31.79], [-84.55, 31.18], [-85.71543812233286, 29.550281650071128]]]]}, "properties": {"DN": 2, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "0.02", "LABEL2": "2% Tornado Risk", "stroke": "#005500", "fill": "#66A366"}}, {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-85.94673006258833, 29.844400969109632], [-85.985, 29.876], [-86.462, 30.068], [-87.771, 29.878], [-88.406, 29.863], [-88.432, 29.714], [-88.695, 29.394], [-88.581, 29.249], [-88.619, 29.022], [-88.937, 28.691], [-89.175, 28.63], [-89.399, 28.577], [-89.712, 28.693], [-89.828, 28.916], [-90.102, 28.755], [-90.54, 28.711], [-90.623, 28.711], [-91.59277142857142, 29.03425714285714], [-91.655, 29.121], [-91.71741304347826, 29.075804347826086], [-93.2, 29.57], [-94.73, 31.29], [-95.13, 33.76], [-95.69, 35.79], [-95.96, 36.86], [-95.34, 37.43], [-95.09, 37.7], [-94.17, 37.91], [-91.96, 37.95], [-91.16, 37.84], [-89.38, 37.45], [-87.47, 36.59], [-85.52, 35.29], [-84.14, 34.2], [-82.58, 32.8], [-82.89, 32.4], [-83.96, 31.97], [-84.66, 31.4], [-85.94673006258833, 29.844400969109632]]]]}, "properties": {"DN": 5, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "0.05", "LABEL2": "5% Tornado Risk", "stroke": "#70380f", "fill": "#9d4e15"}}, {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-94.27, 33.9], [-94.39, 35.51], [-94.41, 36.65], [-93.85, 37.18], [-92.93, 37.29], [-92.0, 37.33], [-90.56, 37.15], [-88.38, 36.42], [-85.71, 35.04], [-84.99, 33.96], [-84.58, 33.08], [-84.65, 31.96], [-85.07, 31.47], [-86.45, 30.71], [-88.17, 30.2], [-90.09, 29.87], [-91.34, 29.83], [-92.79, 29.94], [-93.61, 30.64], [-93.99, 31.91], [-94.27, 33.9]]]]}, "properties": {"DN": 10, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "0.10", "LABEL2": "10% Tornado Risk", "stroke": "#DDAA00", "fill": "#FFE066"}}, {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-92.64, 33.93], [-92.62, 35.22], [-91.77, 36.14], [-90.41, 35.88], [-88.66, 35.48], [-86.14, 34.51], [-85.45, 33.01], [-85.97, 32.07], [-87.05, 31.65], [-88.57, 30.99], [-89.81, 30.81], [-91.8, 30.52], [-92.83, 30.82], [-93.18, 31.8], [-92.65, 33.31], [-92.64, 33.93]]]]}, "properties": {"DN": 15, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "0.15", "LABEL2": "15% Tornado Risk", "stroke": "#CC0000", "fill": "#E06666"}}, {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-91.91, 33.06], [-89.87, 34.37], [-88.23, 34.22], [-87.71, 33.5], [-88.22, 32.55], [-90.62, 32.03], [-91.75, 32.06], [-91.91, 33.06]]]]}, "properties": {"DN": 30, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "0.30", "LABEL2": "30% Tornado Risk", "stroke": "#CC00CC", "fill": "#EE99EE"}}, {"type": "Feature", "geometry": {"type": "MultiPolygon", "coordinates": [[[[-93.04, 32.56], [-92.91, 34.11], [-93.14, 35.76], [-92.16, 36.64], [-91.06, 36.76], [-89.0, 36.28], [-87.76, 35.78], [-85.79, 34.52], [-85.4, 33.51], [-85.34, 32.95], [-85.92, 31.87], [-89.09, 30.42], [-91.29, 30.22], [-92.93, 30.6], [-93.28, 31.54], [-93.04, 32.56]]]]}, "properties": {"DN": 10, "VALID": "202103171200", "EXPIRE": "202103181200", "ISSUE": "202103170552", "LABEL": "SIGN", "LABEL2": "10% Significant Tornado Risk", "stroke": "#000000", "fill": "#888888"}}]}

tests/plots/baseline/test_declarative_spc_hatch.png

@@ -7,6 +7,7 @@
 from io import BytesIO
 import warnings
 
+import geopandas
 import matplotlib
 import numpy as np
 import pandas as pd
@@ -1581,6 +1582,36 @@ def test_declarative_plot_geometry_points(ccrs):
     return pc.figure
 
 
+@pytest.mark.mpl_image_compare(remove_text=True)
+def test_declarative_spc_hatch():
+    """Test SPC hatching effect."""
+    day1_outlook = geopandas.read_file(
+        get_test_data('spc_day1otlk_20210317_1200_torn.lyr.geojson')
+    )
+
+    sig_area = day1_outlook.loc[day1_outlook.LABEL == 'SIGN', :]
+
+    geo = PlotGeometry()
+    geo.geometry = sig_area['geometry']
+    geo.fill = 'none'
+    geo.stroke = sig_area['stroke']
+    geo.labels = None
+    geo.hatch = 'SS'
+
+    panel = MapPanel()
+    panel.plots = [geo]
+    panel.area = [-120, -75, 25, 50]
+    panel.projection = 'lcc'
+    panel.layers = ['states', 'coastline', 'borders']
+
+    pc = PanelContainer()
+    pc.size = (12, 8)
+    pc.panels = [panel]
+    pc.draw()
+
+    return pc.figure
+
+
 @needs_cartopy
 def test_drop_traitlets_dir():
     """Test successful drop of inherited members from HasTraits and any '_' or '__' members."""