8000 Doc AHA bullseye by tacaswell · Pull Request #4550 · matplotlib/matplotlib · GitHub
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merged 5 commits into from
Jun 23, 2015
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Doc AHA bullseye #4550

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a425953
Left ventricle bull eye
curiale Sep 15, 2014
ce91884
Style corrections
curiale Sep 15, 2014
45cef15
Improve the documentation
curiale Oct 3, 2014
0709202
Added the colormap and normalize as arguments
curiale Oct 18, 2014
1b831cb
MNT: minor doc + convention clean up
tacaswell Jun 23, 2015
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@curiale
curiale committed Sep 15, 2014
commit ce918847ad70c2c9e37b0ec756a7c9325457448c
123 changes: 68 additions & 55 deletions examples/pylab_examples/leftventricle_bulleye.py
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@@ -1,115 +1,128 @@
def bulleye_plot(data, ax=None, figsize=(12,8), vlim=None, segBold=[]):
#!/usr/bin/env python
"""
In this example we create the bull eye representation for the left ventricle
according to the American Heart Association (AHA)
"""

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt


def bulleye_plot(data, ax, vlim=None, segBold=[]):
"""
Left Ventricle bull eye for the Left Ventricle according to the
Left Ventricle bull eye for the Left Ventricle according to the
American Heart Association (AHA)
Use Example:
data = range(17)
bulleye_plot(data)
"""

linewidth = 2
data = np.array(data).ravel()

if vlim is None:
vlim = [data.min(), data.max()]

axnone = False
if ax is None:
fig, ax = plt.subplots(figsize=figsize, subplot_kw=dict(projection='polar'))
fig.canvas.set_window_title('Left Ventricle Bull Eyes (AHA)')
axnone = True


theta = np.linspace(0, 2*np.pi, 768)
r = np.linspace(0.2, 1, 4)


# Create the bound for the segment 17
linewidth = 2
for i in range(r.shape[0]):
ax.plot(theta, np.repeat(r[i], theta.shape), '-k', lw=linewidth)

# Create the bounds for the segments 1-12
for i in range(6):
theta_i = i * 60 * np.pi/180
theta_i = i*60*np.pi/180
ax.plot([theta_i, theta_i], [r[1], 1], '-k', lw=linewidth)

# Create the bounds for the segmentss 13-16
for i in range(4):
theta_i = i * 90 * np.pi/180 - 45*np.pi/180
theta_i = i*90*np.pi/180 - 45*np.pi/180
ax.plot([theta_i, theta_i], [r[0], r[1]], '-k', lw=linewidth)





# Fill the segments 1-6
r0 = r[2:4]
r0 = np.repeat(r0[:,np.newaxis], 128, axis=1).T
r0 = np.repeat(r0[:, np.newaxis], 128, axis=1).T
for i in range(6):
theta0 = theta[i*128:i*128+128] + 60*np.pi/180 # First segment start at 60 degrees
theta0 = np.repeat(theta0[:,np.newaxis], 2, axis=1)
z = np.ones((128,2)) * data[i]
# First segment start at 60 degrees
theta0 = theta[i*128:i*128+128] + 60*np.pi/180
theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
z = np.ones((128, 2))*data[i]
ax.pcolormesh(theta0, r0, z, vmin=vlim[0], vmax=vlim[1])
if i+1 in segBold:
ax.plot(theta0, r0, '-k', lw=linewidth+2)
ax.plot(theta0[0], [r[2],r[3]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[2],r[3]], '-k', lw=linewidth+1)
ax.plot(theta0[0], [r[2], r[3]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[2], r[3]], '-k', lw=linewidth+1)

# Fill the segments 7-12
r0 = r[1:3]
r0 = np.repeat(r0[:,np.newaxis], 128, axis=1).T
r0 = np.repeat(r0[:, np.newaxis], 128, axis=1).T
for i in range(6):
theta0 = theta[i*128:i*128+128] + 60*np.pi/180 # First segment start at 60 degrees
theta0 = np.repeat(theta0[:,np.newaxis], 2, axis=1)
z = np.ones((128,2)) * data[i+6]
# First segment start at 60 degrees
theta0 = theta[i*128:i*128+128] + 60*np.pi/180
theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
z = np.ones((128, 2))*data[i+6]
ax.pcolormesh(theta0, r0, z, vmin=vlim[0], vmax=vlim[1])
if i+7 in segBold:
ax.plot(theta0, r0, '-k', lw=linewidth+2)
ax.plot(theta0[0], [r[1],r[2]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[1],r[2]], '-k', lw=linewidth+1)

ax.plot(theta0[0], [r[1], r[2]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[1], r[2]], '-k', lw=linewidth+1)

# Fill the segments 13-16
r0 = r[0:2]
r0 = np.repeat(r0[:,np.newaxis], 192, axis=1).T
r0 = np.repeat(r0[:, np.newaxis], 192, axis=1).T
for i in range(4):
theta0 = theta[i*192:i*192+192] + 45*np.pi/180 # First segment start at 45 degrees
theta0 = np.repeat(theta0[:,np.newaxis], 2, axis=1)
z = np.ones((192,2)) * data[i+12]
# First segment start at 45 degrees
theta0 = theta[i*192:i*192+192] + 45*np.pi/180
theta0 = np.repeat(theta0[:, np.newaxis], 2, axis=1)
z = np.ones((192, 2))*data[i+12]
ax.pcolormesh(theta0, r0, z, vmin=vlim[0], vmax=vlim[1])
if i+13 in segBold:
ax.plot(theta0, r0, '-k', lw=linewidth+2)
ax.plot(theta0[0], [r[0],r[1]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[0],r[1]], '-k', lw=linewidth+1)
ax.plot(theta0[0], [r[0], r[1]], '-k', lw=linewidth+1)
ax.plot(theta0[-1], [r[0], r[1]], '-k', lw=linewidth+1)

#Fill the segments 17
if data.size == 17:
r0 = np.array([0, r[0]])
r0 = np.repeat(r0[:,np.newaxis], theta.size, axis=1).T
theta0 = np.repeat(theta[:,np.newaxis], 2, axis=1)
z = np.ones((theta.size,2)) * data[16]
r0 = np.repeat(r0[:, np.newaxis], theta.size, axis=1).T
theta0 = np.repeat(theta[:, np.newaxis], 2, axis=1)
z = np.ones((theta.size, 2))*data[16]
ax.pcolormesh(theta0, r0, z, vmin=vlim[0], vmax=vlim[1])
if 17 in segBold:
ax.plot(theta0, r0, '-k', lw=linewidth+2)


ax.set_ylim([0, 1])
ax.set_yticklabels([])
ax.set_xticklabels([])


#Add legend
if axnone:
cm = plt.cm.jet
# Create the fake data
data = np.array(range(17)) + 1
vlim = [data.min(), data.max()]

fig, ax = plt.subplots(figsize=(12, 8), nrows=1, ncols=2,
subplot_kw=dict(projection='polar'))
fig.canvas.set_window_title('Left Ventricle Bull Eyes (AHA)')

bulleye_plot(data, ax[0], vlim=vlim)
ax[0].set_title('Bull Eye (AHA)')

bulleye_plot(data, ax[1], segBold=[3,5,6,11,12,16],
vlim=vlim)
ax[1].set_title('Segments [3,5,6,11,12,16] in bold')


#define the bins and normalize
cNorm = mpl.colors.Normalize(vmin=vlim[0], vmax=vlim[1])
#Add legend
cm = plt.cm.jet

ax = fig.add_axes([0.3, 0.04, 0.45, 0.05])
ticks = [vlim[0], 0, vlim[1]]
cb = mpl.colorbar.ColorbarBase(ax, cmap=cm, norm=cNorm,
orientation='horizontal', ticks=ticks)
#define the bins and normalize
cNorm = mpl.colors.Normalize(vmin=vlim[0], vmax=vlim[1])

plt.show()
ticks = [vlim[0], 0, vlim[1]]
ax[0] = fig.add_axes([0.2, 0.15, 0.2, 0.05])
cb = mpl.colorbar.ColorbarBase(ax[0], cmap=cm, norm=cNorm, ticks=ticks,
orientation='horizontal')
ax[1] = fig.add_axes([0.62, 0.15, 0.2, 0.05])
cb = mpl.colorbar.ColorbarBase(ax[1], cmap=cm, norm=cNorm, ticks=ticks,
orientation='horizontal')

if axnone:
return fig, ax
plt.show()
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