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Switch to triple quotes comment blocks as visual separators
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‎examples/pylab_examples/mri_with_eeg.py

Lines changed: 67 additions & 58 deletions
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@@ -14,66 +14,75 @@
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from matplotlib.collections import LineCollection
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from matplotlib.ticker import MultipleLocator
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# NB: one uses "if 1:" to break up the different regions of code visually
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fig = plt.figure("MRI_with_EEG")
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if 1: # Load the data
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# Data are 256x256 16 bit integers
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dfile = cbook.get_sample_data('s1045.ima.gz')
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im = np.fromstring(dfile.read(), np.uint16).astype(float)
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im.shape = (256, 256)
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if 1: # Plot the MRI image
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ax0 = fig.add_subplot(2, 2, 1)
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ax0.imshow(im, cmap=cm.gray)
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ax0.axis('off')
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if 1: # Plot the histogram of MRI intensity
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ax1 = fig.add_subplot(2, 2, 2)
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im = np.ravel(im)
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im = im[np.nonzero(im)] # Ignore the background
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im = im / (2**15) # Normalize
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ax1.hist(im, 100)
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ax1.xaxis.set_major_locator(MultipleLocator(0.5))
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ax1.set_yticks([])
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ax1.set_xlabel('Intensity')
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ax1.set_ylabel('MRI density')
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if 1: # Plot the EEG
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# Load the data
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numSamples, numRows = 800, 4
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eegfile = cbook.get_sample_data('eeg.dat', asfileobj=False)
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print('Loading EEG %s' % eegfile)
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data = np.fromstring(open(eegfile, 'rb').read(), float)
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data.shape = (numSamples, numRows)
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t = 10.0 * np.arange(numSamples) / numSamples
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ticklocs = []
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ax2 = fig.add_subplot(2, 1, 2)
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ax2.set_xlim(0, 10)
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ax2.set_xticks(np.arange(10))
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dmin = data.min()
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dmax = data.max()
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dr = (dmax - dmin) * 0.7 # Crowd them a bit.
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y0 = dmin
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y1 = (numRows - 1) * dr + dmax
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ax2.set_ylim(y0, y1)
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segs = []
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for i in range(numRows):
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segs.append(np.hstack((t[:, np.newaxis], data[:, i, np.newaxis])))
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ticklocs.append(i * dr)
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offsets = np.zeros((numRows, 2), dtype=float)
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offsets[:, 1] = ticklocs
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lines = LineCollection(segs, offsets=offsets, transOffset=None)
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ax2.add_collection(lines)
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# Set the yticks to use axes coords on the y axis
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ax2.set_yticks(ticklocs)
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ax2.set_yticklabels(['PG3', 'PG5', 'PG7', 'PG9'])
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ax2.set_xlabel('Time (s)')
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"""
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Load the data
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"""
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# Data are 256x256 16 bit integers
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dfile = cbook.get_sample_data('s1045.ima.gz')
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im = np.fromstring(dfile.read(), np.uint16).astype(float)
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im.shape = (256, 256)
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"""
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Plot the MRI image
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"""
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ax0 = fig.add_subplot(2, 2, 1)
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ax0.imshow(im, cmap=cm.gray)
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ax0.axis('off')
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"""
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Plot the histogram of MRI intensity
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"""
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ax1 = fig.add_subplot(2, 2, 2)
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im = np.ravel(im)
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im = im[np.nonzero(im)] # Ignore the background
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im = im / (2**15) # Normalize
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ax1.hist(im, 100)
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ax1.xaxis.set_major_locator(MultipleLocator(0.5))
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ax1.set_yticks([])
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ax1.set_xlabel('Intensity')
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ax1.set_ylabel('MRI density')
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"""
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Plot the EEG
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"""
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# Load the data
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numSamples, numRows = 800, 4
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eegfile = cbook.get_sample_data('eeg.dat', asfileobj=False)
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print('Loading EEG %s' % eegfile)
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data = np.fromstring(open(eegfile, 'rb').read(), float)
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data.shape = (numSamples, numRows)
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t = 10.0 * np.arange(numSamples) / numSamples
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ticklocs = []
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ax2 = fig.add_subplot(2, 1, 2)
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ax2.set_xlim(0, 10)
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ax2.set_xticks(np.arange(10))
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dmin = data.min()
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dmax = data.max()
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dr = (dmax - dmin) * 0.7 # Crowd them a bit.
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y0 = dmin
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y1 = (numRows - 1) * dr + dmax
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ax2.set_ylim(y0, y1)
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segs = []
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for i in range(numRows):
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segs.append(np.hstack((t[:, np.newaxis], data[:, i, np.newaxis])))
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ticklocs.append(i * dr)
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offsets = np.zeros((numRows, 2), dtype=float)
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offsets[:, 1] = ticklocs
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lines = LineCollection(segs, offsets=offsets, transOffset=None)
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ax2.add_collection(lines)
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# Set the yticks to use axes coords on the y axis
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ax2.set_yticks(ticklocs)
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ax2.set_yticklabels(['PG3', 'PG5', 'PG7', 'PG9'])
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ax2.set_xlabel('Time (s)')
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plt.tight_layout()
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plt.show()

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