How to use the abipy.abilab.MultiDataset function in abipy

#structure.perturb(distance=0.01)

    # Compress the lattice so that ABINIT complains about dilatmx
    structure.scale_lattice(structure.volume * scalevol)

    global_vars = dict(
        ecut=6,
        ecutsm=0.5,
        ngkpt=[4,4,4],
        shiftk=[0,0,0],
        nshiftk=1,
        chksymbreak=0,
        paral_kgb=tvars.paral_kgb,
    )

    multi = abilab.MultiDataset(structure, pseudos=abidata.pseudos("14si.pspnc"), ndtset=2)

    # Global variables
    multi.set_vars(global_vars)

    # Dataset 1 (Atom Relaxation)
    multi[0].set_vars(
        optcell=0,
        ionmov=2,
        tolrff=0.02,
        tolmxf=5.0e-5,
        ntime=ntime,
    )

    # Dataset 2 (Atom + Cell Relaxation)
    multi[1].set_vars(
        optcell=1,

def make_scf_nscf_inputs(structure, paral_kgb=1):
    multi = abilab.MultiDataset(structure, pseudos=data.pseudos("14si.pspnc"), ndtset=2)

    # Global variables
    global_vars = dict(
        ecut=6,
        nband=8,
        timopt=-1,
        paral_kgb=0,
        #nstep=4, # This is not enough to converge. Used to test the automatic restart.
        nstep=10,
        iomode=3,
    )

    multi.set_vars(global_vars)

    # Dataset 1 (GS run)
    multi[0].set_kmesh(ngkpt=[8,8,8], shiftk=[0,0,0])

Build and return a `Flow` to perform a convergence study wrt to ecut.

    Args:
        structure_file: (optional) file containing the crystalline structure.
            If None, crystalline silicon structure.
        ecut_list: List of cutoff energies to be investigated.
    """
    # Define the structure and add the necessary pseudos:
    if structure_file is None:
        multi = abilab.MultiDataset(structure=abidata.cif_file("si.cif"),
                                  pseudos=abidata.pseudos("14si.pspnc"), ndtset=len(ecut_list))
        workdir = "flow_Si_ecut_convergence"
    else:
        structure = abilab.Structure.from_file(structure_file)
        pseudos = abilab.PseudoTable()  ## todo fix this
        multi = abilab.MultiDataset(structure, pseudos=pseudos, ndtset=len(ecut_list))
        workdir = "flow_" + structure.composition.reduced_formula + "_ecut_convergence"

    # Add mnemonics to the input files.
    multi.set_mnemonics(True)

    # Global variables
    multi.set_vars(tolvrs=1e-9)
    multi.set_kmesh(ngkpt=[4, 4, 4], shiftk=[0, 0, 0])

    # Here we set the value of ecut used by the i-th task.
    for i, ecut in enumerate(ecut_list):
        multi[i].set_vars(ecut=ecut)

    return flowtk.Flow.from_inputs(workdir=workdir, inputs=multi.split_datasets())

# Perturb the structure (random perturbation of 0.1 Angstrom)
    # then compress the volume to trigger dilatmx.
    #structure.perturb(distance=0.1)
    #structure.scale_lattice(structure.volume * 0.6)

    global_vars = dict(
        ecut=28,
        ngkpt=[4,4,4],
        shiftk=[0,0,0],
        nshiftk=1,
        chksymbreak=0,
        paral_kgb=paral_kgb,
        #prtwf=0,
    )

    multi = abilab.MultiDataset(structure, pseudos=pseudos, ndtset=2)

    # Global variables
    multi.set_vars(global_vars)

    # Dataset 1 (Atom Relaxation)
    multi[0].set_vars(
        optcell=0,
        ionmov=2,
        tolrff=0.02,
        tolmxf=5.0e-5,
        ntime=50,
        #ntime=3,  #To test the restart
        #dilatmx=1.1, # FIXME: abinit crashes if I don't use this
    )

    # Dataset 2 (Atom + Cell Relaxation)

def make_scf_nscf_inputs(nsppol, paral_kgb=1):
    """
    Generate two input files for the GS and the NSCF run for given `nsppol`.
    """
    # Fe normal bcc structure for test of a ferromagnetic calculation
    multi = abilab.MultiDataset(structure=data.structure_from_ucell("Fe-fm"),
                                pseudos=data.pseudos("26fe.pspnc"), ndtset=2)

    # Global variables
    global_vars = dict(
        nsppol=nsppol,
        ecut=18,
        nband=8,
        occopt=3,
        tsmear=0.01,
        paral_kgb=paral_kgb,
    )
    if nsppol == 2:
        global_vars.update(spinat=[0.0, 0.0, 4.0])

    multi.set_vars(global_vars)

def make_scf_nscf_dos_inputs(structure, pseudos, luj_params, paral_kgb=1):
    # Input file taken from tldau_2.in
    multi = abilab.MultiDataset(structure, pseudos=pseudos, ndtset=3)

    # Global variables
    global_vars = dict(
        #
        ecut=12,
        pawecutdg=30,
        nband=40,
        occopt=7,
        tsmear=0.015,
        nstep=50,
        paral_kgb=paral_kgb,
        #
        # Spin
        nsppol=1,
        nspden=2,
        nspinor=1,

def make_inputs(paral_kgb=1):
    """
    Returns a tuple of 4 input files for SCF, NSCF, SCR, SIGMA calculations.
    These files are then used as templates for the convergence study
    wrt ecuteps and the number of bands in W.
    """
    multi = abilab.MultiDataset(abidata.structure_from_ucell("SiC"),
                                pseudos=abidata.pseudos("14si.pspnc", "6c.pspnc"), ndtset=4)

    ecut = 12
    global_vars = dict(
        ecut=ecut,
        istwfk="*1",
        paral_kgb=paral_kgb,
        gwpara=2,
        iomode=1,
    )

    ecuteps = 4
    ngkpt = [4, 4, 4]
    shiftk = [0, 0, 0]

    multi.set_vars(global_vars)