Not the most intelligent way of doing it, but it works.

shuffle_jets.py

d = io.load('yourfile.hdf5')
#ix = [random.sample(range(4), 4) for _ in xrange(d['X'].shape[0])]
ix = np.argsort(d['X'][:, :4])[:, ::-1]

def _pairwise(iterable):
        '''s -> (s0, s1), (s2, s3), (s4, s5), ...'''
        a = iter(iterable)
        return izip(a, a)

cols = list(_pairwise(range(d['X'].shape[-1])[::4])) # or you can just type [(0, 4), (8, 12), (16, 20), (24, 28)]
for slc in cols:
  print 'Shuffling columns {}'.format(slc)
  d['X'][:, slice(*slc)] = np.array([row[sh] for row, sh in zip(d['X'][:, slice(*slc)], ix)])