Josh Hemann wrote:
Tony,
I know this is a year later but your code was hugely helpful to me
last
week, so thank you
I'm glad you found it helpful.
On Jul 28, 2009, at 12:56 PM, Michael Droettboom wrote:
Would you (Josh and Tony) be amenable to us including this in the
set of
examples? It would make it easier for users to find it.
Eventually, it
might be nice to include this as a core plotting command, but in the
meantime, I think it would still be useful as-is.
Mike
Hey Mike,
I'm always happy to contribute what little I can to matplotlib.
However, if it's going to be an official example, it should be cleaned
up a bit (see attached). Summary of changes.
* My original example (i.e. not Josh's fault) didn't play well with
namespaces (i.e. from pylab import *). This has been changed to use
the proper imports (i.e. np and plt).
* Also, there were problems with rgrids when I originally wrote the
code, which has since been fixed (at least on trunk it is). This
eliminates the need to manually draw a grid.
* I made a few other clean ups for clarity. (Josh: I hope you don't
mind, I switched the data for f4_base and f5_base so that I could
remove the associated comment.)
* Final note. The polygon frame no longer works properly and I
couldn't really figure out how to fix it.
Best,
-Tony
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()
------------------------------------------------------------------------------
Let Crystal Reports handle the reporting - Free Crystal Reports 2008 30-Day
trial. Simplify your report design, integration and deployment - and focus on
what you do best, core application coding. Discover what's new with
Crystal Reports now. http://p.sf.net/sfu/bobj-july
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
