def empirical_retinotopy_data(hemi, retino_type):
dat = _empirical_retinotopy_names[retino_type.lower()]<EOL>hdat = {s.lower(): s for s in six.iterkeys(hemi.properties)}<EOL>return next((hemi.prop(hdat[s.lower()]) for s in dat if s.lower() in hdat), None)<EOL>
empirical_retinotopy_data(hemi, t) yields a numpy array of data for the given cortex object hemi
and retinotopy type t; it does this by looking at the properties in hemi and picking out any
combination that is commonly used to denote empirical retinotopy data. These common names are
stored in _empirical_retintopy_names, in order of preference, which may be modified.
The argument t should be one of 'polar_angle', 'eccentricity', 'weight'.