Python AtomNetwork.read_from_CSSR方法代码示例

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
    """
    Analyze the void space in the input structure using voronoi decomposition
    Calls Zeo++ for Voronoi decomposition

    Args:
        structure: pymatgen.core.structure.Structure
        rad_dict (optional): Dictionary of radii of elements in structure.
            If not given, Zeo++ default values are used.
            Note: Zeo++ uses atomic radii of elements.
            For ionic structures, pass rad_dict with ionic radii
        probe_rad (optional): Sampling probe radius in Angstroms. Default is
            0.1 A

    Returns:
        voronoi nodes as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
    """

    temp_dir = tempfile.mkdtemp()
    current_dir = os.getcwd()
    name = "temp_zeo1"
    zeo_inp_filename = name + ".cssr"
    os.chdir(temp_dir)
    ZeoCssr(structure).write_file(zeo_inp_filename)
    rad_file = None
    rad_flag = False

    if rad_dict:
        rad_file = name + ".rad"
        rad_flag = True
        with open(rad_file, 'w+') as fp:
            for el in rad_dict.keys():
                print >>fp, "{} {}".format(el, rad_dict[el].real)

    atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
    vornet = atmnet.perform_voronoi_decomposition()
    vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
    voronoi_out_filename = name + '_voro.xyz'
    voronoi_node_mol = ZeoVoronoiXYZ.from_file(voronoi_out_filename).molecule
    #print voronoi_node_mol
    species = ["X"] * len(voronoi_node_mol.sites)
    coords = []
    prop = []
    for site in voronoi_node_mol.sites:
        coords.append(list(site.coords))
        prop.append(site.properties['voronoi_radius'])

    lattice = Lattice.from_lengths_and_angles(
        structure.lattice.abc, structure.lattice.angles
    )
    voronoi_node_struct = Structure(
        lattice, species, coords, coords_are_cartesian=True,
        site_properties={"voronoi_radius": prop}
    )

    os.chdir(current_dir)
    shutil.rmtree(temp_dir)

    return voronoi_node_struct

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_void_volume_surfarea(structure, rad_dict=None, chan_rad=0.3,
                             probe_rad=0.1):
    """
    Computes the volume and surface area of isolated void using Zeo++.
    Useful to compute the volume and surface area of vacant site.

    Args:
        structure: pymatgen Structure containing vacancy
        rad_dict(optional): Dictionary with short name of elements and their
            radii.
        chan_rad(optional): Minimum channel Radius.
        probe_rad(optional): Probe radius for Monte Carlo sampling.

    Returns:
        volume: floating number representing the volume of void
    """
    with ScratchDir('.'):
        name = "temp_zeo"
        zeo_inp_filename = name + ".cssr"
        ZeoCssr(structure).write_file(zeo_inp_filename)

        rad_file = None
        if rad_dict:
            rad_file = name + ".rad"
            with open(rad_file, 'w') as fp:
                for el in rad_dict.keys():
                    fp.write("{0}     {1}".format(el, rad_dict[el]))

        atmnet = AtomNetwork.read_from_CSSR(zeo_inp_filename, True, rad_file)
        vol_str = volume(atmnet, 0.3, probe_rad, 10000)
        sa_str = surface_area(atmnet, 0.3, probe_rad, 10000)
        print vol_str, sa_str
        vol = None
        sa = None
        for line in vol_str.split("\n"):
            if "Number_of_pockets" in line:
                fields = line.split()
                if float(fields[1]) > 1:
                    vol = -1.0
                    break
                if float(fields[1]) == 0:
                    vol = -1.0
                    break
                vol = float(fields[3])
        for line in sa_str.split("\n"):
            if "Number_of_pockets" in line:
                fields = line.split()
                if float(fields[1]) > 1:
                    #raise ValueError("Too many voids")
                    sa = -1.0
                    break
                if float(fields[1]) == 0:
                    sa = -1.0
                    break
                sa = float(fields[3])

    if not vol or not sa:
        raise ValueError("Error in zeo++ output stream")
    return vol, sa

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_high_accuracy_voronoi_nodes(structure, rad_dict, probe_rad=0.1):
    """
    Analyze the void space in the input structure using high accuracy
    voronoi decomposition.
    Calls Zeo++ for Voronoi decomposition.

    Args:
        structure: pymatgen.core.structure.Structure
        rad_dict (optional): Dictionary of radii of elements in structure.
            If not given, Zeo++ default values are used.
            Note: Zeo++ uses atomic radii of elements.
            For ionic structures, pass rad_dict with ionic radii
        probe_rad (optional): Sampling probe radius in Angstroms.
            Default is 0.1 A

    Returns:
        voronoi nodes as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
        voronoi face centers as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
    """

    with ScratchDir('.'):
        name = "temp_zeo1"
        zeo_inp_filename = name + ".cssr"
        ZeoCssr(structure).write_file(zeo_inp_filename)
        rad_flag = True
        rad_file = name + ".rad"
        with open(rad_file, 'w+') as fp:
            for el in rad_dict.keys():
                print("{} {}".format(el, rad_dict[el].real), file=fp)

        atmnet = AtomNetwork.read_from_CSSR(
            zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
        # vornet, vor_edge_centers, vor_face_centers = \
        #        atmnet.perform_voronoi_decomposition()
        red_ha_vornet = \
            prune_voronoi_network_close_node(atmnet)
        # generate_simplified_highaccuracy_voronoi_network(atmnet)
        # get_nearest_largest_diameter_highaccuracy_vornode(atmnet)
        red_ha_vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
        voro_out_filename = name + '_voro.xyz'
        voro_node_mol = ZeoVoronoiXYZ.from_file(voro_out_filename).molecule

    species = ["X"] * len(voro_node_mol.sites)
    coords = []
    prop = []
    for site in voro_node_mol.sites:
        coords.append(list(site.coords))
        prop.append(site.properties['voronoi_radius'])

    lattice = Lattice.from_lengths_and_angles(
        structure.lattice.abc, structure.lattice.angles)
    vor_node_struct = Structure(
        lattice, species, coords, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})

    return vor_node_struct

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_free_sphere_params(structure, rad_dict=None, probe_rad=0.1):
    """
    Analyze the void space in the input structure using voronoi decomposition
    Calls Zeo++ for Voronoi decomposition.

    Args:
        structure: pymatgen.core.structure.Structure
        rad_dict (optional): Dictionary of radii of elements in structure.
            If not given, Zeo++ default values are used.
            Note: Zeo++ uses atomic radii of elements.
            For ionic structures, pass rad_dict with ionic radii
        probe_rad (optional): Sampling probe radius in Angstroms. Default is
            0.1 A

    Returns:
        voronoi nodes as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
        voronoi face centers as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
    """

    with ScratchDir('.'):
        name = "temp_zeo1"
        zeo_inp_filename = name + ".cssr"
        ZeoCssr(structure).write_file(zeo_inp_filename)
        rad_file = None
        rad_flag = False

        if rad_dict:
            rad_file = name + ".rad"
            rad_flag = True
            with open(rad_file, 'w+') as fp:
                for el in rad_dict.keys():
                    fp.write("{} {}\n".format(el, rad_dict[el].real))

        atmnet = AtomNetwork.read_from_CSSR(
            zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
        out_file = "temp.res"
        atmnet.calculate_free_sphere_parameters(out_file)
        if os.path.isfile(out_file) and os.path.getsize(out_file) > 0:
            with open(out_file, "rt") as fp:
                output = fp.readline()
        else:
            output = ""
    fields = [val.strip() for val in output.split()][1:4]
    if len(fields) == 3:
        fields = [float(field) for field in fields]
        free_sphere_params = {'inc_sph_max_dia': fields[0],
                              'free_sph_max_dia': fields[1],
                              'inc_sph_along_free_sph_path_max_dia': fields[2]}
    return free_sphere_params

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
    """
    Analyze the void space in the input structure using voronoi decomposition
    Calls Zeo++ for Voronoi decomposition.

    Args:
        structure: pymatgen.core.structure.Structure
        rad_dict (optional): Dictionary of radii of elements in structure.
            If not given, Zeo++ default values are used.
            Note: Zeo++ uses atomic radii of elements.
            For ionic structures, pass rad_dict with ionic radii
        probe_rad (optional): Sampling probe radius in Angstroms. Default is
            0.1 A

    Returns:
        voronoi nodes as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
        voronoi face centers as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
    """

    with ScratchDir('.'):
        name = "temp_zeo1"
        zeo_inp_filename = name + ".cssr"
        ZeoCssr(structure).write_file(zeo_inp_filename)
        rad_file = None
        rad_flag = False

        if rad_dict:
            rad_file = name + ".rad"
            rad_flag = True
            with open(rad_file, 'w+') as fp:
                for el in rad_dict.keys():
                    fp.write("{} {}\n".format(el, rad_dict[el].real))

        atmnet = AtomNetwork.read_from_CSSR(
            zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
        vornet, vor_edge_centers, vor_face_centers = \
            atmnet.perform_voronoi_decomposition()
        vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
        voro_out_filename = name + '_voro.xyz'
        voro_node_mol = ZeoVoronoiXYZ.from_file(voro_out_filename).molecule

    species = ["X"] * len(voro_node_mol.sites)
    coords = []
    prop = []
    for site in voro_node_mol.sites:
        coords.append(list(site.coords))
        prop.append(site.properties['voronoi_radius'])

    lattice = Lattice.from_lengths_and_angles(
        structure.lattice.abc, structure.lattice.angles)
    vor_node_struct = Structure(
        lattice, species, coords, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})

    # PMG-Zeo c<->a transformation for voronoi face centers
    rot_face_centers = [(center[1], center[2], center[0]) for center in
                        vor_face_centers]
    rot_edge_centers = [(center[1], center[2], center[0]) for center in
                        vor_edge_centers]

    species = ["X"] * len(rot_face_centers)
    prop = [0.0] * len(rot_face_centers)  # Vor radius not evaluated for fc
    vor_facecenter_struct = Structure(
        lattice, species, rot_face_centers, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})

    species = ["X"] * len(rot_edge_centers)
    prop = [0.0] * len(rot_edge_centers)  # Vor radius not evaluated for fc
    vor_edgecenter_struct = Structure(
        lattice, species, rot_edge_centers, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})

    return vor_node_struct, vor_edgecenter_struct, vor_facecenter_struct

# 需要导入模块: from zeo.netstorage import AtomNetwork [as 别名]
# 或者: from zeo.netstorage.AtomNetwork import read_from_CSSR [as 别名]
def get_high_accuracy_voronoi_nodes_alt(structure, rad_dict, probe_rad=0.1):
    """
    Function to replace high_accuracy_voronoi_nodes function. In testing
    mode.
    Analyze the void space in the input structure using high accuracy 
    voronoi decomposition.
    Calls Zeo++ for Voronoi decomposition.

    Args:
        structure: pymatgen.core.structure.Structure
        rad_dict (optional): Dictionary of radii of elements in structure.
            For ionic structures, pass rad_dict with ionic radii
        probe_rad (optional): Sampling probe radius in Angstroms. 
            Default is 0.1 A

    Returns:
        voronoi nodes as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
        voronoi face centers as pymatgen.core.structure.Strucutre within the
        unit cell defined by the lattice of input structure
    """

    with ScratchDir('.'):
        name = "temp_zeo1"
        zeo_inp_filename = name + ".cssr"
        ZeoCssr(structure).write_file(zeo_inp_filename)
        rad_flag = True
        rad_file = name + ".rad"
        with open(rad_file, 'w+') as fp:
            for el in rad_dict.keys():
                print >>fp, "{} {}".format(el, rad_dict[el].real)

        atmnet = AtomNetwork.read_from_CSSR(
                zeo_inp_filename, rad_flag=rad_flag, rad_file=rad_file)
        vornet, voronoi_face_centers = atmnet.perform_voronoi_decomposition()
        red_ha_vornet = \
                generate_simplified_highaccuracy_voronoi_network(atmnet)
        red_ha_vornet.analyze_writeto_XYZ(name, probe_rad, atmnet)
        voro_out_filename = name + '_voro.xyz'
        voro_node_mol = ZeoVoronoiXYZ.from_file(voro_out_filename).molecule

    species = ["X"] * len(voro_node_mol.sites)
    coords = []
    prop = []
    for site in voro_node_mol.sites:
        coords.append(list(site.coords))
        prop.append(site.properties['voronoi_radius'])

    lattice = Lattice.from_lengths_and_angles(
        structure.lattice.abc, structure.lattice.angles)
    voronoi_node_struct = Structure(
        lattice, species, coords, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})


    #PMG-Zeo c<->a transformation for voronoi face centers
    rot_face_centers = [(center[1],center[2],center[0]) for center in 
                        voronoi_face_centers]
    species = ["X"] * len(rot_face_centers)
    # Voronoi radius not evaluated for fc. Fix in future versions
    prop = [0.0] * len(rot_face_centers)  
    voronoi_facecenter_struct = Structure(
        lattice, species, rot_face_centers, coords_are_cartesian=True,
        to_unit_cell=True, site_properties={"voronoi_radius": prop})

    return voronoi_node_struct, voronoi_facecenter_struct