Meg Contour Plot

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Plot MEG data using delaunay triangulation

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from pylab import plot, show, contour, pcolor, figure, cm, colorbar, contourf,scatter
from scikits.delaunay import *
import numpy.core.ma as ma
from scipy.io import write_array
from scipy.io import read_array
from numpy import shape, mgrid, interp, isnan
 
"""how to use: 
        eg. megcontour.display(data)"""
 
def plot_data(xi,yi,zi,intx,inty):
    """provide...
        xi=grid x data
        yi=grided y data
        zi=interpolated MEG data for contour
        intx and inty= sensor coords for channel plotting"""
    zim = ma.masked_where(isnan(zi),zi)
    pcolor(xi,yi,zim,shading='interp',cmap=cm.jet)
    contourf(xi,yi,zim,cmap=cm.jet)
    scatter(intx,inty, alpha=.5,s=.5)
    #contour(xi,yi,zim,cmap=cm.jet)
    show()
 
def display(data):
    xi, yi = mgrid[-.5:.5:67j,-.5:.5:67j]
    chanlocs=read_array("/home/danc/programming/python/configs/megchannels.cfg")
    intx=chanlocs[1,:]
    inty=chanlocs[0,:]
    z = data
    tri = Triangulation(intx,inty)
    interp = tri.nn_interpolator(z)
    zi = interp(xi,yi)
    plot_data(xi,yi,zi,intx,inty)
 
if __name__ == '__main__':
    main()

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In [7]: from meg import megcontour
In [10]: slices = pdf.GetSliceRangeMEGChannels(0, 1000)
In [11]: data=slices[:,110]
In [12]: megcontour.display(data)