How to use the pymatgen.core.structure.Structure.from_dict function in pymatgen

def from_dict(cls, d):
        """
        Returns Dos object from dict representation of Dos.
        """
        dos = Dos(d["efermi"], d["energies"],
                  {Spin(int(k)): v for k, v in d["densities"].items()})
        return FermiDos(dos, structure=Structure.from_dict(d["structure"]),
                        nelecs=d["nelecs"])

optional parameters to store along with the
                TransformedStructure. This can include tags (a list) or author
                which will be parsed.
        """
        history = [] if history is None else history
        self._source = {}
        self._structures = []
        self._changes = []
        self._change_parameters = []
        self._redo_trans = []
        self._other_parameters = {} if other_parameters is None \
            else deepcopy(other_parameters)
        if len(history) > 0:
            self._source = history[0]
            for i in xrange(1, len(history)):
                struct = Structure.from_dict(history[i]["input_structure"])
                trans = AbstractTransformation.from_dict(history[i])
                param = history[i].get("output_parameters", {})
                self._structures.append(struct)
                self._changes.append(trans)
                self._change_parameters.append(param)

        self._structures.append(structure)
        for t in transformations:
            self.append_transformation(t)

logger.error("BVAnalyzer error {e}.".format(e=str(ex)))

    max_force = None
    if d["state"] == "successful" and \
            d["calculations"][0]["input"]["parameters"].get("NSW", 0) > 0:
        # handle the max force and max force error
        max_force = max([np.linalg.norm(a)
                        for a in d["calculations"][-1]["output"]
                        ["ionic_steps"][-1]["forces"]])

        if max_force > max_force_threshold:
            error_msgs.append("Final max force exceeds {} eV"
                              .format(max_force_threshold))
            d["state"] = "error"

        s = Structure.from_dict(d["output"]["crystal"])
        if not s.is_valid():
            error_msgs.append("Bad structure (atoms are too close!)")
            d["state"] = "error"

    return {"delta_volume": delta_vol,
            "max_force": max_force,
            "percent_delta_volume": percent_delta_vol,
            "warnings": warning_msgs,
            "errors": error_msgs,
            "coordination_numbers": coord_num,
            "bandgap": gap, "cbm": cbm, "vbm": vbm,
            "is_gap_direct": is_direct,
            "bv_structure": bv_struct.as_dict()}

def from_old_dict(cls, d):
        """
        Args:
            d (dict): A dict with all data for a band structure symm line
                object.
        Returns:
            A BandStructureSymmLine object
        """
        # Strip the label to recover initial string (see trick used in as_dict to handle $ chars)
        labels_dict = {k.strip(): v for k, v in d['labels_dict'].items()}
        projections = {}
        structure = None
        if 'projections' in d and len(d['projections']) != 0:
            structure = Structure.from_dict(d['structure'])
            projections = {}
            for spin in d['projections']:
                dd = []
                for i in range(len(d['projections'][spin])):
                    ddd = []
                    for j in range(len(d['projections'][spin][i])):
                        dddd = []
                        for k in range(len(d['projections'][spin][i][j])):
                            ddddd = []
                            orb = Orbital(k).name
                            for l in range(len(d['projections'][spin][i][j][
                                                   orb])):
                                ddddd.append(d['projections'][spin][i][j][
                                                orb][l])
                            dddd.append(np.array(ddddd))
                        ddd.append(np.array(dddd))

def from_dict(d):
        """
        Returns CompleteDos object from dict representation.
        """
        tdos = Dos.from_dict(d)
        struct = Structure.from_dict(d["structure"])
        pdoss = {}
        for i in xrange(len(d["pdos"])):
            at = struct[i]
            orb_dos = {}
            for orb_str, odos in d["pdos"][i].items():
                orb = Orbital.from_string(orb_str)
                orb_dos[orb] = {Spin.from_int(int(k)): v
                                for k, v in odos["densities"].items()}
            pdoss[at] = orb_dos
        return CompleteDos(struct, tdos, pdoss)

elif 'mps' in old_task and old_task['mps']:
            snl = mps_dict_to_snl(old_task['mps'])
            mpsnl, snlgroup_id = sma.add_snl(snl)
            d['snl'] = mpsnl.to_dict
            d['snlgroup_id'] = snlgroup_id
        else:
            s = Structure.from_dict(old_task['input']['crystal'])
            snl = StructureNL(s, 'Anubhav Jain ', remarks=['origin unknown'])
            mpsnl, snlgroup_id = sma.add_snl(snl)
            d['snl'] = mpsnl.to_dict
            d['snlgroup_id'] = snlgroup_id


        if 'optimize structure' in d['task_type'] and 'output' in d:
            # create a new SNL based on optimized structure
            new_s = Structure.from_dict(d['output']['crystal'])
            old_snl = StructureNL.from_dict(d['snl'])
            history = old_snl.history
            history.append(
                {'name': 'Materials Project structure optimization',
                 'url': 'http://www.materialsproject.org',
                 'description': {'task_type': d['task_type'],
                                 'fw_id': d['fw_id'],
                                 'task_id': d['task_id']}})
            new_snl = StructureNL(new_s, old_snl.authors, old_snl.projects,
                                  old_snl.references, old_snl.remarks,
                                  old_snl.data, history)

            # add snl
            mpsnl, snlgroup_id = sma.add_snl(new_snl, snlgroup_guess=d['snlgroup_id'])

            d['snl_final'] = mpsnl.to_dict

def from_dict(cls, d):
        """
        Creates a TransformedStructure from a dict.
        """
        s = Structure.from_dict(d)
        return cls(s, history=d["history"],
                   other_parameters=d.get("other_parameters", None))

d["input_mp_id"] = tag["input_id"]
        d["snl_final"] = o["snl_final"]
        d["pretty_formula"] = o["pretty_formula"]

        # Old input mp-id style
        if o["snl"]["about"].get("_mp_id"):
            d["material_id"] = o["snl"]["about"]["_mp_id"]

        # New style
        elif "input_mp_id" in d:
            d["material_id"] = d["input_mp_id"]
        else:
            d["material_id"] = None
        d["relaxation_task_id"] = i

        calc_struct = Structure.from_dict(o["snl_final"])
        # TODO:
        # JHM: This test is unnecessary at the moment, but should be redone
        """
        conventional = is_conventional(calc_struct)
        if conventional:
            d["analysis"]["is_conventional"] = True
        else:
            d["analysis"]["is_conventional"] = False
        """
        d["spacegroup"]=o.get("spacegroup", "Unknown")
        
        if ndocs >= 20:
            # Perform Elastic tensor fitting and analysis
            result = ElasticTensor.from_stress_dict(ss_dict)
            d["elastic_tensor"] = result.tolist()
            kg_average = result.kg_average

percent_delta_vol = delta_vol / initial_vol
    coord_num = get_coordination_numbers(d)
    calc = d["calculations"][-1]
    gap = calc["output"]["bandgap"]
    cbm = calc["output"]["cbm"]
    vbm = calc["output"]["vbm"]
    is_direct = calc["output"]["is_gap_direct"]

    warning_msgs = []
    error_msgs = []

    if abs(percent_delta_vol) > volume_change_threshold:
        warning_msgs.append("Volume change > {}%"
                            .format(volume_change_threshold * 100))

    bv_struct = Structure.from_dict(d["output"]["crystal"])
    try:
        bva = BVAnalyzer()
        bv_struct = bva.get_oxi_state_decorated_structure(bv_struct)
    except ValueError as e:
        logger.error("Valence cannot be determined due to {e}."
                     .format(e=e))
    except Exception as ex:
        logger.error("BVAnalyzer error {e}.".format(e=str(ex)))

    max_force = None
    if d["state"] == "successful" and \
            d["calculations"][0]["input"]["parameters"].get("NSW", 0) > 0:
        # handle the max force and max force error
        max_force = max([np.linalg.norm(a)
                        for a in d["calculations"][-1]["output"]
                        ["ionic_steps"][-1]["forces"]])