def METHOD_NAME(res, X, Y, roiSize = 5, errScale = 1, cutoffErr=[0,100], cutoffSigma = [200/2.35, 400/2.35], cutoffA = [10, 200]):
    im = np.zeros((len(X), len(Y)), 'f')
    #record our image resolution so we can plot pts with a minimum size equal to res (to avoid missing small pts)
    delX = abs(X[1] - X[0]) 
    for r1 in res:
        for r in r1.results:
            ix = abs(X - r.x0()).argmin()
            iy = abs(Y - r.y0()).argmin()
            if (ix > roiSize) and (ix < (len(X) - roiSize)) and  (iy > roiSize) and (iy < (len(Y) - roiSize)) and  not r.fitErr is None and r.fitErr[1] > cutoffErr[0] and r.fitErr[1] < cutoffErr[1] and r.sigma() > cutoffSigma[0]  and r.sigma() < cutoffSigma[1] and r.A() > cutoffA[0] and r.A() < cutoffA[1]:
                imp = Gauss2D(X[(ix - roiSize):(ix + roiSize + 1)], Y[(iy - roiSize):(iy + roiSize + 1)],1, r.x0(),r.y0(),max(r.fitErr[1]*errScale, delX))
                im[(ix - roiSize):(ix + roiSize + 1), (iy - roiSize):(iy + roiSize + 1)] += imp
    return im