How to use the pyqmc.testwf.test_updateinternals function in pyqmc

for k, item in testwf.test_updateinternals(wf, epos).items():
            assert item < epsilon
        assert testwf.test_wf_gradient(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_laplacian(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_pgradient(wf, epos, delta=delta)[0] < epsilon

        # Test different number of elecs
        mc = mcscf.CASCI(mf, ncas=4, nelecas=(2, 0))
        mc.kernel()
        wf = MultiSlater(mol, mf, mc)

        nelec = np.sum(mol.nelec)
        epos = initial_guess(mol, nconf)

        for k, item in testwf.test_updateinternals(wf, epos).items():
            assert item < epsilon
        assert testwf.test_wf_gradient(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_laplacian(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_pgradient(wf, epos, delta=delta)[0] < epsilon

        # Quick VMC test
        nconf = 1000
        coords = initial_guess(mol, nconf)
        df, coords = vmc(
            wf, coords, nsteps=nsteps, accumulators={"energy": EnergyAccumulator(mol)}
        )

        df = pd.DataFrame(df)
        df = reblock(df["energytotal"][warmup:], 20)
        en = df.mean()
        err = df.sem()

wf.parameters[k] = np.random.rand(*wf.parameters[k].shape)
        for fname, func in zip(
            ["gradient", "laplacian", "pgradient"],
            [
                testwf.test_wf_gradient,
                testwf.test_wf_laplacian,
                testwf.test_wf_pgradient,
            ],
        ):
            err = []
            for delta in [1e-4, 1e-5, 1e-6, 1e-7, 1e-8]:
                err.append(func(wf, epos, delta)[0])
            print(fname, min(err))
            assert min(err) < epsilon, "epsilon {0}".format(epsilon)

        for k, item in testwf.test_updateinternals(wf, epos).items():
            print(k, item)
            assert item < epsilon

wf.parameters[k] = np.random.rand(*wf.parameters[k].shape)
        for fname, func in zip(
            ["gradient", "laplacian", "pgradient"],
            [
                testwf.test_wf_gradient,
                testwf.test_wf_laplacian,
                testwf.test_wf_pgradient,
            ],
        ):
            err = []
            for delta in [1e-4, 1e-5, 1e-6, 1e-7, 1e-8]:
                err.append(func(wf, epos, delta)[0])
            print(fname, min(err))
            assert min(err) < epsilon

        for k, item in testwf.test_updateinternals(wf, epos).items():
            print(k, item)
            assert item < epsilon

for k, item in testwf.test_updateinternals(wf, epos).items():
            assert item < epsilon
        assert testwf.test_wf_gradient(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_laplacian(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_pgradient(wf, epos, delta=delta)[0] < epsilon

        # Test same number of elecs
        mc = mcscf.CASCI(mf, ncas=4, nelecas=(1, 1))
        mc.kernel()
        wf = pyqmc.default_msj(mol, mf, mc)[0]

        nelec = np.sum(mol.nelec)
        epos = initial_guess(mol, nconf)

        for k, item in testwf.test_updateinternals(wf, epos).items():
            assert item < epsilon
        assert testwf.test_wf_gradient(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_laplacian(wf, epos, delta=delta)[0] < epsilon
        assert testwf.test_wf_pgradient(wf, epos, delta=delta)[0] < epsilon

        # Test different number of elecs
        mc = mcscf.CASCI(mf, ncas=4, nelecas=(2, 0))
        mc.kernel()
        wf = MultiSlater(mol, mf, mc)

        nelec = np.sum(mol.nelec)
        epos = initial_guess(mol, nconf)

        for k, item in testwf.test_updateinternals(wf, epos).items():
            assert item < epsilon
        assert testwf.test_wf_gradient(wf, epos, delta=delta)[0] < epsilon

def test(): 
    from pyscf import gto,scf
    mol = gto.M(atom='Li 0. 0. 0.; H 0. 0. 1.5', basis='cc-pvtz',unit='bohr')
    mf = scf.RHF(mol).run()
    nconf=10
    nelec=np.sum(mol.nelec)
    slater=PySCFSlaterRHF(mol,mf)
    configs=np.random.randn(nconf,nelec,3)
    import pyqmc.testwf as testwf
    for delta in [1e-3,1e-4,1e-5,1e-6,1e-7]:
        print('delta', delta, "Testing gradient",testwf.test_wf_gradient(slater,configs,delta=delta))
        print('delta', delta, "Testing laplacian", testwf.test_wf_laplacian(slater,configs,delta=delta))
        print('delta', delta, "Testing pgradient", testwf.test_wf_pgradient(slater,configs,delta=delta))


    print("testing internals:", testwf.test_updateinternals(slater,configs))
    quit()
    #Test the internal update
    e=3
    slater.recompute(configs)
    inv=slater._inverse.copy()
    configsnew=configs.copy()
    configsnew[:,e,:]+=0.1
    slater.updateinternals(e,configsnew[:,e,:])
    inv_update=slater._inverse.copy()
    slater.recompute(configsnew)
    inv_recalc=slater._inverse.copy()
    print(inv_recalc-inv_update)

def test(): 
    from pyscf import lib, gto, scf
    np.random.seed(10)
    
    mol = gto.M(atom='Li 0. 0. 0.; H 0. 0. 1.5', basis='cc-pvtz',unit='bohr')
    l = dir(mol)
    nconf=20
    configs=np.random.randn(nconf,np.sum(mol.nelec),3)
    
    jastrow=Jastrow2B(mol)
    jastrow.parameters['coeff']=np.random.random(jastrow.parameters['coeff'].shape)
    import pyqmc.testwf as testwf
    #print(testwf.test_updateinternals(jastrow,configs))
    for key, val in testwf.test_updateinternals(jastrow, configs).items():
        print(key, val)

    print()
    for delta in [1e-3,1e-4,1e-5,1e-6,1e-7]:
        print('delta', delta, "Testing gradient",
              testwf.test_wf_gradient(jastrow,configs,delta=delta))
        print('delta', delta, "Testing laplacian",
              testwf.test_wf_laplacian(jastrow,configs,delta=delta))
        print('delta', delta, "Testing pgradient",
              testwf.test_wf_pgradient(jastrow,configs,delta=delta))
        print()