add a reduce_rings method

[tjlane]

@dermen I agree this function is a good idea. I got rid of it in the memory branch temporarily, but I think we should add it back in with a few tweaks. Curious what you think about the following:

Have it automatically deal with the mask (should be possible)
Have an option to discard shots (by index) as well as phi values
Adding a unit test

Original Code:

    def reduce_rings ( self, factor ):
        """ reduce self.num_phi by factor; WARNING: removes the mask; must make a new one """
        if self.num_phi % factor != 0:
            raise NotImplementedError( 'As of now, *factor* must be a multiple of *self.num_phi*' )
        rp = np.copy( self.polar_intensities)
        new_rp = np.zeros(( rp.shape[0], rp.shape[1],rp.shape[2] / factor ) )
        # convolve algor. taken from stack overflow
        for q in self.q_values:
            for i in xrange( rp.shape[0] ) :
                d = rp[ i,self.q_index(q),:]
                d = np.convolve( d + [d[-1]], [1./factor]*factor,mode='valid' )[::factor]
                new_rp[i,self.q_index(q),:] = d

        return Rings( self.q_values, new_rp, self.k )