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Multivariate Pattern Analysis in Python |
Example demonstrating a topography plot.
>>> from mvpa.suite import *
>>>
>>> # Sanity check if we have griddata available
>>> externals.exists("griddata", raiseException=True)
>>>
>>> # EEG example splot
>>> P.subplot(1, 2, 1)
>>>
>>> # load the sensor information from their definition file.
>>> # This file has sensor names, as well as their 3D coordinates
>>> sensors=XAVRSensorLocations(os.path.join('data', 'xavr1010.dat'))
>>>
>>> # make up some artifical topography
>>> # 'enable' to channels, all others set to off ;-)
>>> topo = N.zeros(len(sensors.names))
>>> topo[sensors.names.index('O1')] = 1
>>> topo[sensors.names.index('F4')] = 1
>>>
>>> # plot with sensor locations shown
>>> plotHeadTopography(topo, sensors.locations(), plotsensors=True)
>>>
>>>
>>> # MEG example plot
>>> P.subplot(1, 2, 2)
>>>
>>> # load MEG sensor locations
>>> sensors=TuebingenMEGSensorLocations(
>>> os.path.join('data', 'tueb_meg_coord.xyz'))
>>>
>>> # random values this time
>>> topo = N.random.randn(len(sensors.names))
>>>
>>> # plot without additional interpolation
>>> plotHeadTopography(topo, sensors.locations(),
>>> interpolation='nearest')
>>>
>>>
>>> if cfg.getboolean('examples', 'interactive', True):
>>> # show all the cool figures
>>> P.show()
>>>
The ouput of the provided example should look like
See also
The full source code of this example is included in the PyMVPA source distribution (doc/examples/topo_plot.py).