### We're updating the default styles for Matplotlib 2.0

Learn what to expect in the new updates

#### Next topic

api example code: sankey_demo_basics.py

```"""
Example of creating a radar chart (a.k.a. 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.

"""
import numpy as np

import matplotlib.pyplot as plt
from matplotlib.path import Path
from matplotlib.spines import Spine
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection

"""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 = 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_patch(self):
verts = unit_poly_verts(theta)
return plt.Polygon(verts, closed=True, edgecolor='k')

def draw_circle_patch(self):
# unit circle centered on (0.5, 0.5)
return plt.Circle((0.5, 0.5), 0.5)

patch_dict = {'polygon': draw_poly_patch, 'circle': draw_circle_patch}
if frame not in patch_dict:
raise ValueError('unknown value for `frame`: %s' % frame)

# use 1 line segment to connect specified points
RESOLUTION = 1
# define draw_frame method
draw_patch = patch_dict[frame]

def fill(self, *args, **kwargs):
"""Override fill so that line is closed by default"""
closed = kwargs.pop('closed', True)

def plot(self, *args, **kwargs):
"""Override plot so that line is closed by default"""
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):
return self.draw_patch()

def _gen_axes_spines(self):
if frame == 'circle':
return PolarAxes._gen_axes_spines(self)
# The following is a hack to get the spines (i.e. the axes frame)
# to draw correctly for a polygon frame.

# spine_type must be 'left', 'right', 'top', 'bottom', or `circle`.
spine_type = 'circle'
verts = unit_poly_verts(theta)
# close off polygon by repeating first vertex
verts.append(verts[0])
path = Path(verts)

spine = Spine(self, spine_type, path)
spine.set_transform(self.transAxes)
return {'polar': spine}

return theta

def unit_poly_verts(theta):
"""Return vertices of polygon for subplot axes.

This polygon is circumscribed by a unit circle centered at (0.5, 0.5)
"""
x0, y0, r = [0.5] * 3
verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
return verts

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 speciesis present...
data = {
'column names':
['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

data = example_data()
spoke_labels = data.pop('column names')

fig = plt.figure(figsize=(9, 9))

colors = ['b', 'r', 'g', 'm', 'y']
# Plot the four cases from the example data on separate axes
for n, title in enumerate(data.keys()):
plt.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(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()
```

Keywords: python, matplotlib, pylab, example, codex (see Search examples)