for i in xrange(0, n_tries):
    dE = ROOT.gRandom.Gaus(0, 0.1 / 1000)

    new_g = TGraphErrors(t.GetEntries())
    for j in xrange(0, t.GetEntries()):
        dEps = ROOT.gRandom.Gaus(0, 0.01 * t.GetV1()[i] / 1.02)

        new_E = t.GetV1()[i] + dE
        new_Si = t.GetV2()[i] * (1 + dEps)

        new_g.SetPoint(i, new_E, new_Si)
        new_g.SetPointError(i, 0, t.GetV3()[i])

    new_fit_result = new_g.Fit("f", "QS")

    ### fnc.GetParameter(0) -> histogram
    ### fnc.GetParameter(1) -> histogram
    ### fnc.GetParameter(2) -> histogram