How to use the zfit.pdf.Gauss function in zfit

def test_with_zfit():

    import zfit
    from zfit.core.loss import UnbinnedNLL
    from zfit.minimizers.minimizer_minuit import MinuitMinimizer

    data = np.random.normal(1.2, 0.1, 10000)

    obs = zfit.Space('x', limits=(0.1, 2.0))

    mean = zfit.Parameter("mcalc", 1.2, 0.1, 2.)
    sigma = zfit.Parameter("scalc", 0.1, 0.02, 0.2)
    model = zfit.pdf.Gauss(obs=obs, mu=mean, sigma=sigma)

    data_ = zfit.data.Data.from_numpy(obs=obs, array=data)

    def lossbuilder(model, data, weights=None):
        loss = UnbinnedNLL(model=model, data=data, fit_range=[obs])
        return loss

    minimizer = MinuitMinimizer()

    config = Config(model, data_, lossbuilder, minimizer)

    calc = Calculator(config)

    assert calc.minimizer == minimizer
    calc.obsbestfit
    assert calc.obsbestfit == config.bestfit

def test_fail_on_nan_strategy():
    sigma = zfit.Parameter("sigma", 2.)
    obs = zfit.Space("obs1", limits=(-4, 5))
    gauss = zfit.pdf.Gauss(1., sigma, obs=obs)

    sampler = gauss.create_sampler(3000)
    sampler.set_data_range(obs)
    nll = zfit.loss.UnbinnedNLL(model=gauss, data=sampler)
    minimizer = zfit.minimize.Minuit(strategy=ToyStrategyFail())
    sampler.resample()
    sigma.set_value(2.1)
    fitresult1 = minimizer.minimize(nll)
    assert fitresult1.converged

    sampler.resample()
    sigma.set_value(math.inf)
    fitresult2 = minimizer.minimize(nll)
    assert not fitresult2.converged
    assert fitresult2.edm == -999
    assert fitresult2.fmin == -999

def test_truncated_gauss():
    high = 2.
    low = -0.5
    truncated_gauss = zfit.pdf.TruncatedGauss(mu=1, sigma=2, low=low, high=high, obs=limits1)
    gauss = zfit.pdf.Gauss(mu=1., sigma=2, obs=limits1)

    probs_truncated = truncated_gauss.pdf(test_values)
    probs_gauss = gauss.pdf(test_values)

    probs_truncated_np, probs_gauss_np = [probs_truncated.numpy(), probs_gauss.numpy()]

    bool_index_inside = np.logical_and(low < test_values, test_values < high)
    inside_probs_truncated = probs_truncated_np[bool_index_inside]
    outside_probs_truncated = probs_truncated_np[np.logical_not(bool_index_inside)]
    inside_probs_gauss = probs_gauss_np[bool_index_inside]

    assert inside_probs_gauss == pytest.approx(inside_probs_truncated, rel=1e-3)
    assert all(outside_probs_truncated == 0)

def create_pdf(params):
        param1, param2, param3, param4 = params
        gauss1 = zfit.pdf.Gauss(param1, param2, obs=obs)
        gauss2 = zfit.pdf.Gauss(param2, param2, obs=obs)
        gauss3 = zfit.pdf.Gauss(param2, param4, obs=obs)
        gauss4 = zfit.pdf.Gauss(param3, param1, obs=obs)
        sum_pdf = zfit.pdf.SumPDF([gauss1, gauss2, gauss3, gauss4], fracs=[0.1, 0.3, 0.4])
        return sum_pdf

def test_extract_extended_pdfs():
    gauss1 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)
    gauss2 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)
    gauss3 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)
    gauss4 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)
    gauss5 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)
    gauss6 = zfit.pdf.Gauss(obs=obs1, mu=1.3, sigma=5.4)

    yield1 = zfit.Parameter('yield123' + str(np.random.random()), 200.)

    # sum1 = 0.3 * gauss1 + gauss2
    gauss3_ext = gauss3.create_extended(45)
    gauss4_ext = gauss4.create_extended(100)
    sum2_ext_daughters = gauss3_ext + gauss4_ext
    sum3 = zfit.pdf.SumPDF((gauss5, gauss6), 0.4)
    sum3_ext = sum3.create_extended(yield1)

    sum_all = zfit.pdf.SumPDF(pdfs=[sum2_ext_daughters, sum3_ext])
    sum_all.set_norm_range((-5, 5))

    extracted_pdfs = extract_extended_pdfs(pdfs=sum_all)
    assert frozenset(extracted_pdfs) == {gauss3_ext, gauss4_ext, sum3_ext}

def create_gauss3(nameadd=""):
    mu3 = Parameter("mu3" + nameadd, mu_true, mu_true - 2., mu_true + 7.)
    sigma3 = Parameter("sigma3" + nameadd, sigma_true, sigma_true - 10., sigma_true + 5.)
    gauss3 = zfit.pdf.Gauss(mu=mu3, sigma=sigma3, obs=obs1)
    return gauss3

def create_pdf(params):
        param1, param2, param3, param4 = params
        gauss1 = zfit.pdf.Gauss(param1, param2, obs=obs)
        gauss2 = zfit.pdf.Gauss(param2, param2, obs=obs)
        gauss3 = zfit.pdf.Gauss(param2, param4, obs=obs)
        gauss4 = zfit.pdf.Gauss(param3, param1, obs=obs)
        sum_pdf = zfit.pdf.SumPDF([gauss1, gauss2, gauss3, gauss4], fracs=[0.1, 0.3, 0.4])
        return sum_pdf