.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_specialty_plots_radar_chart.py: ====================================== 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] http://en.wikipedia.org/wiki/Radar_chart .. code-block:: default import numpy as np import matplotlib.pyplot as plt from matplotlib.patches import Circle, RegularPolygon from matplotlib.path import Path from matplotlib.projections.polar import PolarAxes from matplotlib.projections import register_projection from matplotlib.spines import Spine 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 RadarAxes(PolarAxes): name = 'radar' # use 1 line segment to connect specified points RESOLUTION = 1 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]) line.set_data(x, y) def set_varlabels(self, labels): 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': return RegularPolygon((0.5, 0.5), num_vars, radius=.5, edgecolor="k") else: raise ValueError("Unknown value for 'frame': %s" % frame) def _gen_axes_spines(self): 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} else: raise ValueError("Unknown value for 'frame': %s" % frame) register_projection(RadarAxes) return theta 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) # Pyrolized 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', [ [0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00], [0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00], [0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00], [0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00], [0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00]]), ('With CO', [ [0.88, 0.02, 0.02, 0.02, 0.00, 0.05, 0.00, 0.05, 0.00], [0.08, 0.94, 0.04, 0.02, 0.00, 0.01, 0.12, 0.04, 0.00], [0.01, 0.01, 0.79, 0.10, 0.00, 0.05, 0.00, 0.31, 0.00], [0.00, 0.02, 0.03, 0.38, 0.31, 0.31, 0.00, 0.59, 0.00], [0.02, 0.02, 0.11, 0.47, 0.69, 0.58, 0.88, 0.00, 0.00]]), ('With O3', [ [0.89, 0.01, 0.07, 0.00, 0.00, 0.05, 0.00, 0.00, 0.03], [0.07, 0.95, 0.05, 0.04, 0.00, 0.02, 0.12, 0.00, 0.00], [0.01, 0.02, 0.86, 0.27, 0.16, 0.19, 0.00, 0.00, 0.00], [0.01, 0.03, 0.00, 0.32, 0.29, 0.27, 0.00, 0.00, 0.95], [0.02, 0.00, 0.03, 0.37, 0.56, 0.47, 0.87, 0.00, 0.00]]), ('CO & O3', [ [0.87, 0.01, 0.08, 0.00, 0.00, 0.04, 0.00, 0.00, 0.01], [0.09, 0.95, 0.02, 0.03, 0.00, 0.01, 0.13, 0.06, 0.00], [0.01, 0.02, 0.71, 0.24, 0.13, 0.16, 0.00, 0.50, 0.00], [0.01, 0.03, 0.00, 0.28, 0.24, 0.23, 0.00, 0.44, 0.88], [0.02, 0.00, 0.18, 0.45, 0.64, 0.55, 0.86, 0.00, 0.16]]) ] return data if __name__ == '__main__': N = 9 theta = radar_factory(N, frame='polygon') data = example_data() spoke_labels = data.pop(0) fig, axs = plt.subplots(figsize=(9, 9), nrows=2, ncols=2, subplot_kw=dict(projection='radar')) fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05) 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) 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() .. image:: /gallery/specialty_plots/images/sphx_glr_radar_chart_001.png :alt: Basecase, With CO, With O3, CO & O3 :class: sphx-glr-single-img ------------ References """""""""" The use of the following functions, methods, classes and modules is shown in this example: .. code-block:: default import matplotlib matplotlib.path matplotlib.path.Path matplotlib.spines matplotlib.spines.Spine matplotlib.projections matplotlib.projections.polar matplotlib.projections.polar.PolarAxes matplotlib.projections.register_projection .. rst-class:: sphx-glr-script-out Out: .. code-block:: none .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 1.244 seconds) .. _sphx_glr_download_gallery_specialty_plots_radar_chart.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: radar_chart.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: radar_chart.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature Keywords: matplotlib code example, codex, python plot, pyplot `Gallery generated by Sphinx-Gallery `_