radar_chart.py updated

radar_chart.py

@@ -1,19 +1,3 @@
-"""
-======================================
-Radar chart (aka spider or star chart)
-======================================
-
-This example creates a radar chart, also known as a spider or star chart [1]_.
-
-Although this example allows a frame of either 'circle' or 'polygon', polygon
-frames don't have proper gridlines (the lines are circles instead of polygons).
-It's possible to get a polygon grid by setting GRIDLINE_INTERPOLATION_STEPS in
-matplotlib.axis to the desired number of vertices, but the orientation of the
-polygon is not aligned with the radial axes.
-
-.. [1] https://en.wikipedia.org/wiki/Radar_chart
-"""
-
 import numpy as np
 
 import matplotlib.pyplot as plt
@@ -26,28 +10,11 @@ from matplotlib.transforms import Affine2D
 
 
 def radar_factory(num_vars, frame='circle'):
-    """
-    Create a radar chart with `num_vars` axes.
-
-    This function creates a RadarAxes projection and registers it.
-
-    Parameters
-    ----------
-    num_vars : int
-        Number of variables for radar chart.
-    frame : {'circle', 'polygon'}
-        Shape of frame surrounding axes.
-
-    """
-    # calculate evenly-spaced axis angles
     theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False)
 
     class RadarTransform(PolarAxes.PolarTransform):
 
         def transform_path_non_affine(self, path):
-            # Paths with non-unit interpolation steps correspond to gridlines,
-            # in which case we force interpolation (to defeat PolarTransform's
-            # autoconversion to circular arcs).
             if path._interpolation_steps > 1:
                 path = path.interpolated(num_vars)
             return Path(self.transform(path.vertices), path.codes)
@@ -59,22 +26,18 @@ def radar_factory(num_vars, frame='circle'):
 
         def __init__(self, *args, **kwargs):
             super().__init__(*args, **kwargs)
-            # rotate plot such that the first axis is at the top
             self.set_theta_zero_location('N')
 
         def fill(self, *args, closed=True, **kwargs):
-            """Override fill so that line is closed by default"""
             return super().fill(closed=closed, *args, **kwargs)
 
         def plot(self, *args, **kwargs):
-            """Override plot so that line is closed by default"""
             lines = super().plot(*args, **kwargs)
             for line in lines:
                 self._close_line(line)
 
         def _close_line(self, line):
             x, y = line.get_data()
-            # FIXME: markers at x[0], y[0] get doubled-up
             if x[0] != x[-1]:
                 x = np.append(x, x[0])
                 y = np.append(y, y[0])
@@ -84,8 +47,6 @@ def radar_factory(num_vars, frame='circle'):
             self.set_thetagrids(np.degrees(theta), labels)
 
         def _gen_axes_patch(self):
-            # The Axes patch must be centered at (0.5, 0.5) and of radius 0.5
-            # in axes coordinates.
             if frame == 'circle':
                 return Circle((0.5, 0.5), 0.5)
             elif frame == 'polygon':
@@ -98,13 +59,9 @@ def radar_factory(num_vars, frame='circle'):
             if frame == 'circle':
                 return super()._gen_axes_spines()
             elif frame == 'polygon':
-                # spine_type must be 'left'/'right'/'top'/'bottom'/'circle'.
                 spine = Spine(axes=self,
                               spine_type='circle',
                               path=Path.unit_regular_polygon(num_vars))
-                # unit_regular_polygon gives a polygon of radius 1 centered at
-                # (0, 0) but we want a polygon of radius 0.5 centered at (0.5,
-                # 0.5) in axes coordinates.
                 spine.set_transform(Affine2D().scale(.5).translate(.5, .5)
                                     + self.transAxes)
                 return {'polar': spine}
@@ -116,25 +73,6 @@ def radar_factory(num_vars, frame='circle'):
 
 
 def example_data():
-    # The following data is from the Denver Aerosol Sources and Health study.
-    # See doi:10.1016/j.atmosenv.2008.12.017
-    #
-    # The data are pollution source profile estimates for five modeled
-    # pollution sources (e.g., cars, wood-burning, etc) that emit 7-9 chemical
-    # species. The radar charts are experimented with here to see if we can
-    # nicely visualize how the modeled source profiles change across four
-    # scenarios:
-    #  1) No gas-phase species present, just seven particulate counts on
-    #     Sulfate
-    #     Nitrate
-    #     Elemental Carbon (EC)
-    #     Organic Carbon fraction 1 (OC)
-    #     Organic Carbon fraction 2 (OC2)
-    #     Organic Carbon fraction 3 (OC3)
-    #     Pyrolyzed Organic Carbon (OP)
-    #  2)Inclusion of gas-phase specie carbon monoxide (CO)
-    #  3)Inclusion of gas-phase specie ozone (O3).
-    #  4)Inclusion of both gas-phase species is present...
     data = [
         ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 'O3'],
         ('Basecase', [
@@ -181,45 +119,8 @@ if __name__ == '__main__':
                             'surprised'])
     fig, axs = plt.subplots(figsize=(8, 8), nrows=1, ncols=1,
                             subplot_kw=dict(projection='radar'))
-    # fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05)
     vec = np.array([0.1, 0.05, 0.2, 0.05, 0.3, 0, 0.15, 0.15])
     axs.plot(vec)
     axs.set_varlabels(spoke_labels)
-    # colors = ['b', 'r', 'g', 'm', 'y']
-    # # Plot the four cases from the example data on separate axes
-    # for ax, (title, case_data) in zip(axs.flat, data):
-    #     ax.set_rgrids([0.2, 0.4, 0.6, 0.8])
-    #     ax.set_title(title, weight='bold', size='medium', position=(0.5, 1.1),
-    #                  horizontalalignment='center', verticalalignment='center')
-    #     for d, color in zip(case_data, colors):
-    #         ax.plot(theta, d, color=color)
-    #         ax.fill(theta, d, facecolor=color, alpha=0.25, label='_nolegend_')
-    #     ax.set_varlabels(spoke_labels)
-
-    # # add legend relative to top-left plot
-    # labels = ('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4', 'Factor 5')
-    # legend = axs[0, 0].legend(labels, loc=(0.9, .95),
-    #                           labelspacing=0.1, fontsize='small')
-
-    # fig.text(0.5, 0.965, '5-Factor Solution Profiles Across Four Scenarios',
-    #          horizontalalignment='center', color='black', weight='bold',
-    #          size='large')
-
+    
     plt.show()
-
-
-#############################################################################
-#
-# .. admonition:: References
-#
-#    The use of the following functions, methods, classes and modules is shown
-#    in this example:
-#
-#    - `matplotlib.path`
-#    - `matplotlib.path.Path`
-#    - `matplotlib.spines`
-#    - `matplotlib.spines.Spine`
-#    - `matplotlib.projections`
-#    - `matplotlib.projections.polar`
-#    - `matplotlib.projections.polar.PolarAxes`
-#    - `matplotlib.projections.register_projection`