## matplotlib-checkins

 SF.net SVN: matplotlib:[7301] trunk/matplotlib/examples/api/radar_chart.py From: - 2009-07-28 19:55:42 ```Revision: 7301 http://matplotlib.svn.sourceforge.net/matplotlib/?rev=7301&view=rev Author: jdh2358 Date: 2009-07-28 19:55:30 +0000 (Tue, 28 Jul 2009) Log Message: ----------- added Tony's radar chart demo Added Paths: ----------- trunk/matplotlib/examples/api/radar_chart.py Added: trunk/matplotlib/examples/api/radar_chart.py =================================================================== --- trunk/matplotlib/examples/api/radar_chart.py (rev 0) +++ trunk/matplotlib/examples/api/radar_chart.py 2009-07-28 19:55:30 UTC (rev 7301) @@ -0,0 +1,144 @@ +import numpy as np + +import matplotlib.pyplot as plt +from matplotlib.projections.polar import PolarAxes +from matplotlib.projections import register_projection + +def radar_factory(num_vars, frame='circle'): + """Create a radar chart with `num_vars` axes.""" + # calculate evenly-spaced axis angles + theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars) + # rotate theta such that the first axis is at the top + theta += np.pi/2 + + def draw_poly_frame(self, x0, y0, r): + # TODO: use transforms to convert (x, y) to (r, theta) + verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta] + return plt.Polygon(verts, closed=True, edgecolor='k') + + def draw_circle_frame(self, x0, y0, r): + return plt.Circle((x0, y0), r) + + frame_dict = {'polygon': draw_poly_frame, 'circle': draw_circle_frame} + if frame not in frame_dict: + raise ValueError, 'unknown value for `frame`: %s' % frame + + class RadarAxes(PolarAxes): + """Class for creating a radar chart (a.k.a. a spider or star chart) + + http://en.wikipedia.org/wiki/Radar_chart + """ + name = 'radar' + # use 1 line segment to connect specified points + RESOLUTION = 1 + # define draw_frame method + draw_frame = frame_dict[frame] + + def fill(self, *args, **kwargs): + """Override fill so that line is closed by default""" + closed = kwargs.pop('closed', True) + return super(RadarAxes, self).fill(closed=closed, *args, **kwargs) + + def plot(self, *args, **kwargs): + """Override plot so that line is closed by default""" + lines = super(RadarAxes, self).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.concatenate((x, [x[0]])) + y = np.concatenate((y, [y[0]])) + line.set_data(x, y) + + def set_varlabels(self, labels): + self.set_thetagrids(theta * 180/np.pi, labels) + + def _gen_axes_patch(self): + x0, y0 = (0.5, 0.5) + r = 0.5 + return self.draw_frame(x0, y0, r) + + register_projection(RadarAxes) + return theta + + +if __name__ == '__main__': + #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 speciesis present... + N = 9 + theta = radar_factory(N) + spoke_labels = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', + 'O3'] + f1_base = [0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00] + f1_CO = [0.88, 0.02, 0.02, 0.02, 0.00, 0.05, 0.00, 0.05, 0.00] + f1_O3 = [0.89, 0.01, 0.07, 0.00, 0.00, 0.05, 0.00, 0.00, 0.03] + f1_both = [0.87, 0.01, 0.08, 0.00, 0.00, 0.04, 0.00, 0.00, 0.01] + + f2_base = [0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00] + f2_CO = [0.08, 0.94, 0.04, 0.02, 0.00, 0.01, 0.12, 0.04, 0.00] + f2_O3 = [0.07, 0.95, 0.05, 0.04, 0.00, 0.02, 0.12, 0.00, 0.00] + f2_both = [0.09, 0.95, 0.02, 0.03, 0.00, 0.01, 0.13, 0.06, 0.00] + + f3_base = [0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00] + f3_CO = [0.01, 0.01, 0.79, 0.10, 0.00, 0.05, 0.00, 0.31, 0.00] + f3_O3 = [0.01, 0.02, 0.86, 0.27, 0.16, 0.19, 0.00, 0.00, 0.00] + f3_both = [0.01, 0.02, 0.71, 0.24, 0.13, 0.16, 0.00, 0.50, 0.00] + + f4_base = [0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00] + f4_CO = [0.00, 0.02, 0.03, 0.38, 0.31, 0.31, 0.00, 0.59, 0.00] + f4_O3 = [0.01, 0.03, 0.00, 0.32, 0.29, 0.27, 0.00, 0.00, 0.95] + f4_both = [0.01, 0.03, 0.00, 0.28, 0.24, 0.23, 0.00, 0.44, 0.88] + + f5_base = [0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00] + f5_CO = [0.02, 0.02, 0.11, 0.47, 0.69, 0.58, 0.88, 0.00, 0.00] + f5_O3 = [0.02, 0.00, 0.03, 0.37, 0.56, 0.47, 0.87, 0.00, 0.00] + f5_both = [0.02, 0.00, 0.18, 0.45, 0.64, 0.55, 0.86, 0.00, 0.16] + + fig = plt.figure(figsize=(9,9)) + # adjust spacing around the subplots + fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05) + title_list = ['Basecase', 'With CO', 'With O3', 'CO & O3'] + data = {'Basecase': [f1_base, f2_base, f3_base, f4_base, f5_base], + 'With CO': [f1_CO, f2_CO, f3_CO, f4_CO, f5_CO], + 'With O3': [f1_O3, f2_O3, f3_O3, f4_O3, f5_O3], + 'CO & O3': [f1_both, f2_both, f3_both, f4_both, f5_both]} + colors = ['b', 'r', 'g', 'm', 'y'] + # chemicals range from 0 to 1 + radial_grid = [0.2, 0.4, 0.6, 0.8] + # If you don't care about the order, you can loop over data_dict.items() + for n, title in enumerate(title_list): + ax = fig.add_subplot(2, 2, n+1, projection='radar') + plt.rgrids(radial_grid) + ax.set_title(title, weight='bold', size='medium', position=(0.5, 1.1), + horizontalalignment='center', verticalalignment='center') + for d, color in zip(data[title], 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 + plt.subplot(2,2,1) + labels = ('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4', 'Factor 5') + legend = plt.legend(labels, loc=(0.9, .95), labelspacing=0.1) + plt.setp(legend.get_texts(), fontsize='small') + plt.figtext(0.5, 0.965, '5-Factor Solution Profiles Across Four Scenarios', + ha='center', color='black', weight='bold', size='large') + plt.show() This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site. ```

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