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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def to_volume(mesh, file_name=None, max_element=None, mesher_id=1):
 """ Convert a surface mesh to a 3D volume mesh generated by gmsh. An easy way to install the gmsh sdk is through the gmsh-sdk package on pypi, which downloads and sets up gmsh: pip install gmsh-sdk Algorithm details, although check gmsh docs for more information: The "Delaunay" algorithm is split into three separate steps. First, an initial mesh of the union of all the volumes in the model is performed, without inserting points in the volume. The surface mesh is then recovered using H. Si's boundary recovery algorithm Tetgen/BR. Then a three-dimensional version of the 2D Delaunay algorithm described above is applied to insert points in the volume to respect the mesh size constraints. The Frontal" algorithm uses J. Schoeberl's Netgen algorithm. The "HXT" algorithm is a new efficient and parallel reimplementaton of the Delaunay algorithm. The "MMG3D" algorithm (experimental) allows to generate anisotropic tetrahedralizations Parameters mesh : trimesh.Trimesh Surface mesh of input geometry file_name : str or None Location to save output, in .msh (gmsh) or .bdf (Nastran) format max_element : float or None Maximum length of an element in the volume mesh mesher_id : int 3D unstructured algorithms: 1: Delaunay, 4: Frontal, 7: MMG3D, 10: HXT Returns data : None or bytes MSH data, only returned if file_name is None """


    # checks mesher selection
    if mesher_id not in [1, 4, 7, 10]:
        raise ValueError('unavilable mesher selected!')
    else:
        mesher_id = int(mesher_id)

    # set max element length to a best guess if not specified
    if max_element is None:
        max_element = np.sqrt(np.mean(mesh.area_faces))

    if file_name is not None:
        # check extensions to make sure it is supported format
        if not any(file_name.lower().endswith(e)
                   for e in ['.bdf', '.msh', '.inp', '.diff', '.mesh']):
            raise ValueError(
                'Only Nastran (.bdf), Gmsh (.msh), Abaqus (*.inp), ' +
                'Diffpack (*.diff) and Inria Medit (*.mesh) formats ' +
                'are available!')

    # exports to disk for gmsh to read using a temp file
    mesh_file = tempfile.NamedTemporaryFile(suffix='.stl', delete=False)
    mesh_file.close()
    mesh.export(mesh_file.name)

    # starts Gmsh Python API script
    gmsh.initialize()
    gmsh.option.setNumber("General.Terminal", 1)
    gmsh.model.add('Nastran_stl')

    gmsh.merge(mesh_file.name)
    dimtag = gmsh.model.getEntities()[0]
    dim = dimtag[0]
    tag = dimtag[1]

    surf_loop = gmsh.model.geo.addSurfaceLoop([tag])
    gmsh.model.geo.addVolume([surf_loop])
    gmsh.model.geo.synchronize()

    # We can then generate a 3D mesh...
    gmsh.option.setNumber("Mesh.Algorithm3D", mesher_id)
    gmsh.option.setNumber("Mesh.CharacteristicLengthMax", max_element)
    gmsh.model.mesh.generate(3)

    dimtag2 = gmsh.model.getEntities()[1]
    dim2 = dimtag2[0]
    tag2 = dimtag2[1]
    p2 = gmsh.model.addPhysicalGroup(dim2, [tag2])
    gmsh.model.setPhysicalName(dim, p2, 'Nastran_bdf')

    data = None
    # if file name is None, return msh data using a tempfile
    if file_name is None:
        out_data = tempfile.NamedTemporaryFile(suffix='.msh', delete=False)
        # windows gets mad if two processes try to open the same file
        out_data.close()
        gmsh.write(out_data.name)
        with open(out_data.name, 'rb') as f:
            data = f.read()
    else:
        gmsh.write(file_name)

    # close up shop
    gmsh.finalize()

    return data