1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
|
#!/usr/bin/env python
"""
This now uses the imshow command instead of pcolor which *is much
faster*
"""
from __future__ import division
from pylab import *
from matplotlib.lines import Line2D
from matplotlib.transforms import Bbox, BboxTransform, BboxTransformTo, Affine2D
# I use if 1 to break up the different regions of code visually
if 1: # load the data
# data are 256x256 16 bit integers
dfile = '../data/s1045.ima'
im = fromstring(file(dfile, 'rb').read(), uint16).astype(float)
im.shape = 256, 256
if 1: # plot the MRI in pcolor
subplot(221)
imshow(im, cmap=cm.jet)
axis('off')
if 1: # plot the histogram of MRI intensity
subplot(222)
im = ravel(im)
im = take(im, 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')
if 1: # plot the EEG
# load the data
numSamples, numRows = 800,4
data = fromstring(file('../data/eeg.dat', 'rb').read(), float)
data.shape = numSamples, numRows
t = arange(numSamples)/float(numSamples)*10.0
ticklocs = []
ax = subplot(212)
xlim(0,10)
xticks(arange(10))
boxin = Bbox.from_extents(ax.viewLim.x0, -20, ax.viewLim.x1, 20)
height = ax.bbox.height
boxout = Bbox.from_extents(ax.bbox.x0, -1.0 * height,
ax.bbox.x1, 1.0 * height)
transOffset = BboxTransformTo(
Bbox.from_extents(0.0, ax.bbox.y0, 1.0, ax.bbox.y1))
for i in range(numRows):
# effectively a copy of transData
trans = BboxTransform(boxin, boxout)
offset = (i+1)/(numRows+1)
trans += Affine2D().translate(*transOffset.transform_point((0, offset)))
thisLine = Line2D(
t, data[:,i]-data[0,i],
)
thisLine.set_transform(trans)
ax.add_line(thisLine)
ticklocs.append(offset)
setp(gca(), 'yticklabels', ['PG3', 'PG5', 'PG7', 'PG9'])
# set the yticks to use axes coords on the y axis
ax.set_yticks(ticklocs)
for tick in ax.yaxis.get_major_ticks():
tick.label1.set_transform(ax.transAxes)
tick.label2.set_transform(ax.transAxes)
tick.tick1line.set_transform(ax.transAxes)
tick.tick2line.set_transform(ax.transAxes)
tick.gridline.set_transform(ax.transAxes)
xlabel('time (s)')
show()
|
