def loess( x, h, xp, yp ):

    """args:
        x => location
        h => bandwidth (not sure how to choose this automatically)
        xp => vector
        yp => vector

    example:
        X = np.arange(1, 501)
        y = np.random.random_integers(low=75, high=130, size=len(X))
        data = np.array(zip(X,y))

        s1, s2 = [], []

        for k in data[:,0]:
            s1.append( loess( k, 5, data[:,0], data[:,1] ) )
            s2.append( loess( k, 100, data[:,0], data[:,1] ) )

        pl.plot( data[:,0], data[:,1], 'o', color="white", markersize=1, linewidth=3 )
        pl.plot( data[:,0], np.array(s1), 'k-', data[:,0], np.array(s2), 'k--' )
        pl.show()
    """
    w = np.exp( -0.5*( ((x-xp)/h)**2 )/np.sqrt(2*np.pi*h**2) )
    b = sum(w*xp)*sum(w*yp) - sum(w)*sum(w*xp*yp)
    b /= sum(w*xp)**2 - sum(w)*sum(w*xp**2)
    a = ( sum(w*yp) - b*sum(w*xp) )/sum(w)
    return a + b*x
Return a new graph of G composed with H.
dataset/ETHPy150Open yhat/ggplot/ggplot/components/loess.py/loess--crossover with--dataset/ETHPy150Open gkno/gkno_launcher/src/networkx/algorithms/operators/binary.py/compose