8000 DOC: switch pylab example `mri_with_eeg.py` to OO interface + cosmetick fixes by afvincent · Pull Request #7192 · matplotlib/matplotlib · GitHub
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DOC: switch pylab example mri_with_eeg.py to OO interface + cosmetick fixes #7192

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Merged
merged 11 commits into from
Oct 3, 2016
Merged

DOC: switch pylab example mri_with_eeg.py to OO interface + cosmetick fixes #7192

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86bf335
DOC: switch to pyplot OO interface
afvincent Sep 28, 2016
330a807
DOC: cosmetick adjustements (tight_layout, labels and comments)
afvincent Sep 28, 2016
2d65280
Replace (unfortunate) manual xticks with example of MultipleLocator
afvincent Sep 28, 2016
0c204d2
DOC: correct statement in docstring
afvincent Sep 28, 2016
d06e572
Switch to triple quotes comment blocks as visual separators
afvincent Sep 28, 2016
f5da34f
DOC: structure blocks of code with only a top real comment line
afvincent Sep 30, 2016
c8388f9
Close files or use safer access functions
afvincent Oct 1, 2016
38d92b5
Remove top comment 'pcolor vs imshow'
afvincent Oct 2, 2016
dfc9cca
Normalize intensity values in [0, 1] and adjust x-ticks
afvincent Oct 2, 2016
db3d206
Add a top dosctring and perform small cleaning/fixing ops to mri_with…
afvincent Oct 2, 2016
96ff817
Switch mri_demo.py to OO interface
afvincent Oct 2, 2016
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DOC: switch to pyplot OO interface
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@afvincent
afvincent committed Sep 28, 2016
commit 86bf3359d5af20fe912f5e75915e820d6900cfd1
60 changes: 30 additions & 30 deletions examples/pylab_examples/mri_with_eeg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,33 +6,36 @@
from __future__ import division, print_function

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import matplotlib.cm as cm

from matplotlib.pyplot import *
from matplotlib.collections import LineCollection
import matplotlib.cbook as cbook
# I use if 1 to break up the different regions of code visually

fig = plt.figure("MRI_with_EEG")

if 1: # load the data
# data are 256x256 16 bit integers
dfile = cbook.get_sample_data('s1045.ima.gz')
im = np.fromstring(dfile.read(), np.uint16).astype(float)
im.shape = 256, 256
im.shape = (256, 256)

if 1: # plot the MRI in pcolor
subplot(221)
imshow(im, cmap=cm.gray)
axis('off')
ax0 = fig.add_subplot(2, 2, 1)
ax0.imshow(im, cmap=cm.gray)
ax0.axis('off')

if 1: # plot the histogram of MRI intensity
subplot(222)
ax1 = fig.add_subplot(2, 2, 2)
im = np.ravel(im)
im = im[np.nonzero(im)] # ignore the background
im = im/(2.0**15) # normalize
hist(im, 100)
xticks([-1, -.5, 0, .5, 1])
yticks([])
xlabel('intensity')
ylabel('MRI density')
im = im / (2**15) # normalize
ax1.hist(im, 100)
ax1.set_xticks([-1, -0.5, 0, 0.5, 1])
ax1.set_yticks([])
ax1.set_xlabel('intensity')
ax1.set_ylabel('MRI density')

if 1: # plot the EEG
# load the data
Expand All @@ -41,37 +44,34 @@
eegfile = cbook.get_sample_data('eeg.dat', asfileobj=False)
print('loading eeg %s' % eegfile)
data = np.fromstring(open(eegfile, 'rb').read(), float)
data.shape = numSamples, numRows
t = 10.0 * np.arange(numSamples, dtype=float)/numSamples
data.shape = (numSamples, numRows)
t = 10.0 * np.arange(numSamples) / numSamples
ticklocs = []
ax = subplot(212)
xlim(0, 10)
xticks(np.arange(10))
ax2 = fig.add_subplot(2, 1, 2)
ax2.set_xlim(0, 10)
ax2.set_xticks(np.arange(10))
dmin = data.min()
dmax = data.max()
dr = (dmax - dmin)*0.7 # Crowd them a bit.
dr = (dmax - dmin) * 0.7 # Crowd them a bit.
y0 = dmin
y1 = (numRows - 1) * dr + dmax
ylim(y0, y1)
ax2.set_ylim(y0, y1)

segs = []
for i in range(numRows):
segs.append(np.hstack((t[:, np.newaxis], data[:, i, np.newaxis])))
ticklocs.append(i*dr)
ticklocs.append(i * dr)

offsets = np.zeros((numRows, 2), dtype=float)
offsets[:, 1] = ticklocs

lines = LineCollection(segs, offsets=offsets,
transOffset=None,
)

ax.add_collection(lines)
lines = LineCollection(segs, offsets=offsets, transOffset=None)
ax2.add_collection(lines)

# set the yticks to use axes coords on the y axis
ax.set_yticks(ticklocs)
ax.set_yticklabels(['PG3', 'PG5', 'PG7', 'PG9'])
ax2.set_yticks(ticklocs)
ax2.set_yticklabels(['PG3', 'PG5', 'PG7', 'PG9'])

xlabel('time (s)')
ax2.set_xlabel('time (s)')

show()
plt.show()
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