Tony,
I know this is a year later but your code was hugely helpful to me last
week, so thank you. I needed to make a few modifications to get exactly what
I needed, so I thought I'd add to the post for posterity...
First, here is the graphic that the sample code generates (>>
execfile('radarPlotExample.py'):
http://www.nabble.com/file/p24688050/profileComparisonPub.png
profileComparisonPub.png
Suffice it to say, I think this looks way better than what you get out of R
or MATLAB (e.g.
http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=123).
Here is the code. I have tried to add comments in places that differ from
Tony's code. I am a relatively new Python and matplotlib convert, so please
feel free to comment on better ways to do this. But, like Tony said,
hopefully this will help someone.
Josh
---------------------------------------------------------------------------------------
radarPlotExample.py
---------------------------------------------------------------------------------------
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection
from pylab import *
def radar_factory(num_vars, frame='polygon'):
"""Create a radar chart with `num_vars` axes.
"""
# calculate evenly-spaced axis angles
theta = 2*pi * linspace(0, 1-1/float(num_vars), num_vars)
#print theta
#print
# rotate theta such that the first axis is at the top
theta += pi/2
def draw_poly_frame(self, x0, y0, r):
# TODO: should use transforms to convert (x, y) to (r, theta)
verts = [(r*cos(t) + x0, r*sin(t) + y0) for t in theta]
return Polygon(verts, closed=True)
def draw_circle_frame(self, x0, y0, r):
return 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 = concatenate((x, [x[0]]))
y = concatenate((y, [y[0]]))
line.set_data(x, y)
def set_varlabels(self, labels, rvals, rlabels):
self.set_thetagrids(theta * 180/pi, labels)
#Josh says: The rvals and rlabels parameters were added to
support
#the call to the set_rgrid method so you can control the
position
#and labelling of the circular grid lines. Make the radii labels
#smaller than the default size...
self.set_rgrids(rvals, labels=rlabels, size='small')
def get_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)
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 = [0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 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 = [0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 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 = figure(figsize=(9,9))
fig.subplots_adjust(wspace=0.25, hspace=0.20)
axlist = []
axisNum = 0
#The base vs with-gas ordering of the modeled profiles is swapped for
#factors 4/5, so we'll swap their ordering in the basecase list just to
keep
#the coloring consistent across the four plots...
bases = [f1_base, f2_base, f3_base, f5_base, f4_base]
COs = [f1_CO, f2_CO, f3_CO, f4_CO, f5_CO]
O3s = [f1_O3, f2_O3, f3_O3, f4_O3, f5_O3]
boths = [f1_both, f2_both, f3_both, f4_both, f5_both]
everything = [bases, COs, O3s, boths]
titles = ['Basecase', 'With CO', 'With O3', 'CO & O3']
colors = ['b', 'r', 'g', 'm', 'y']
for row in range(2):
for col in range(2):
axisNum += 1
if axisNum == 2:
#Unfortunately, it looks like the loc keyword to legend() is
#relative to a specific subplot, rather than the figure
itself.
#So, the positioning seen looks good, but if you resize the
#figure to be larger the legend becomes obviously bound to a
#specific subplot. This is in contrast to how the position
works
#in something like figtext(). Had trouble using figlegend(),
but
#need to try some more...
legend(('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4',
'Factor 5'), loc=(0.95, 0.895), borderpad=0.01,
shadow=False, prop=matplotlib.font_manager
.FontProperties(size='smaller'), markerscale=0.4)
data = everything[axisNum-1]
ax = fig.add_subplot(2, 2, axisNum, projection='radar')
ax.set_title(titles[axisNum-1], weight='bold', size='medium',
horizontalalignment='center',
verticalalignment='center',
backgroundcolor='white',
position=(0.5, 1.1))
p1 = ax.plot(theta, data[0], color=colors[0])
p2 = ax.plot(theta, data[1], color=colors[1])
p3 = ax.plot(theta, data[2], color=colors[2])
p4 = ax.plot(theta, data[3], color=colors[3])
p5 = ax.plot(theta, data[4], color=colors[4])
ax.fill(theta, data[0], facecolor=colors[0])
ax.fill(theta, data[1], facecolor=colors[1])
ax.fill(theta, data[2], facecolor=colors[2])
ax.fill(theta, data[3], facecolor=colors[3])
ax.fill(theta, data[4], facecolor=colors[4])
#axlist.extend(ax) #This does not work because ax is a
#RadarAxesSubplot object, which is not
iterable
axlist.append(ax) #append() works because it simply tacks on to
#the list, as opposed to merging items from
two
#lists
for patch in ax.patches:
patch.set_alpha(0.25)
figtext(0.5, 0.965, '5-Factor Solution Profiles Across Four Scenarios
',
ha='center', color='black', weight='bold', size='large')
#Crudely plot the grid lines I want to see: normalized concentrations of
#chemicals range from 0 to 1...
radiiGrid = [0.2, 0.4, 0.6, 0.8]
theta_rgrid = radar_factory(100)
for ax in axlist:
for r in radiiGrid:
radii = repeat(r, 100)
ax.plot(theta_rgrid, radii, color='lightgrey')
# FIXME: legend doesn't work when fill is called
spokeLabels = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP',
'CO',
'O3']
radiiLabels = [str(rg) for rg in radiiGrid]
for ax in axlist:
ax.set_varlabels(spokeLabels, radiiGrid, radiiLabels)
show()
--
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