# Source code for tecplot.data.zone

    """.. _Zones:

    Zones describe the size, shape, element (cell) geometry, connectivity and
    solution time of arrays in a dataset. Zones created as "ordered," "classic
    finite-element," or "polytopal finite-element" along with the number of nodes
    and elements which can not be changed (without creating a new zone). Ordered
    zones are always considered to be logically-rectangular grids of one, two or
    three dimensions depending on the shape. Classic finite-element zones must use
    a fixed-type element throughout. This means that each element has the same
    number of faces and nodes. Polytopal zones can have a varying number of faces
    and nodes for each element. The connectivity is implied in ordered zones and
    explicitly provided by the user for finite-element zones.

    In PyTecplot, there are three zone class objects: `OrderedZone`,
    `ClassicFEZone` and `PolyFEZone`. The `OrderedZone` and `ClassicFEZone` classes
    use the `FaceNeighbors` class to handle "global" face-neighbor connections from
    one zone to another. The connectivity for the `ClassicFEZone` objects are
    accessed through the `Nodemap` class. The `PolyFEZone` objects provide element
    definition and connectivity access through the `Facemap` class.
    """
    import logging

    from functools import reduce
    from textwrap import dedent

    from ..tecutil import _tecutil, _tecutil_connector
    from ..constant import *
    from ..exception import *
    from .. import session, layout, tecutil, version
    from . import array, face_neighbors, facemap, nodemap

    log = logging.getLogger(__name__)

    @tecutil.lock_attributes
    class Zone(object):
        def __init__(self, uid, dataset):
            self.uid = uid
            self.dataset = dataset

        @property
        def _cache(self):
            if _tecutil_connector.suspended:
                _tecutil_connector._delete_caches.append(self._delete_cache)
                return True
            else:
                return False

        def _delete_cache(self):
            attrs = ['_index']
            for attr in attrs:
                try:
                    delattr(self, attr)
                except AttributeError:
                    pass

        def __str__(self):
            """Brief string representation.

            Returns:
                `str`: Brief representation of this `Zone <data_access>`,
                showing a list of associated `Variables <Variable>`.

            Example::

                >>> rect_zone = dataset.zone('Rectangular zone')
                >>> print(rect_zone)
                Zone: 'Rectangular zone'
                  Type: Ordered
                  Shape: (10, 10, 10)
            """
            fmt = dedent('''\
                Zone: '{}'
                  Type: {}
                  Shape: {}''')
            return fmt.format(self.name, self.zone_type.name, self._shape)

        def __repr__(self):
            """Executable string representation.

            Returns:
                `str`: Internal representation of this `Zone
                <data_access>`.

            The string returned can be executed to generate a clone of this
            `Zone <data_access>` object::

                >>> rectzone = dataset.zone('Rectangular zone')
                >>> print(repr(rectzone))
                Zone(uid=31, Dataset(uid=21, frame=Frame(uid=11, page=Page(uid=1)))
                >>> exec('rectzone_clone = '+repr(rectzone))
                >>> rectzone_clone
                Zone(uid=31, Dataset(uid=21, frame=Frame(uid=11, page=Page(uid=1)))
                >>> rectzone == rectzone_clone
                True
            """
            return 'Zone(uid={uid}, dataset={dataset})'.format(
                uid=self.uid, dataset=repr(self.dataset))

        def __eq__(self, other):
            """Checks for equality in the |Tecplot Engine|.

            Returns:
                `bool`: `True` if the unique ID numbers are the same for both
                `Zones <data_access>`.
            """
            return self.uid == other.uid

        def __ne__(self, other):
            return not (self == other)

        @property
        def aux_data(self):
            """Auxiliary data for this zone.

            Returns:
                `AuxData`

            This is the auxiliary data attached to the zone. Such data is
            written to the layout file by default and can be retrieved later.
            Example usage::

                >>> frame = tp.active_frame()
                >>> aux = frame.dataset.zone('My Zone').aux_data
                >>> aux['X_weighted_avg'] = '3.14159'
                >>> print(aux['X_weighted_avg'])
                3.14159
            """
            return session.AuxData(self.dataset.frame, AuxDataObjectType.Zone,
                                   self.index)

        @property
        def index(self):
            """`Index`: Zero-based position within the parent `Dataset`.

            This is the value used to obtain a specific zone if you have
            duplicately named zones in the dataset::

                >>> tp.new_layout()
                >>> frame = tp.active_frame()
                >>> dataset = frame.create_dataset('Dataset', ['x', 'y'])
                >>> dataset.add_ordered_zone('Zone', (10,10,10))
                >>> dataset.add_ordered_zone('Zone', (3,3,3))
                >>> # getting zone by name always returns first match
                >>> print(dataset.zone('Zone').index)
                0
                >>> # use index to get specific zone
                >>> print(dataset.zone(1).dimensions)
                (3, 3, 3)
            """
            if self._cache:
                if not hasattr(self, '_index'):
                    num = _tecutil.ZoneGetNumByUniqueID(self.uid)
                    self._index = tecutil.Index(num - 1)
                return self._index
            else:
                return tecutil.Index(_tecutil.ZoneGetNumByUniqueID(self.uid) - 1)

        @property
        def strand(self):
            """`int`: The strand ID number.

            Example usage::

                >>> dataset.zone('My Zone').strand = 2

            .. note:: **Possible side-effect when connected to Tecplot 360.**

                    Changing the solution times in the dataset or modifying the
                    active fieldmaps in a frame may trigger a change in the active
                    plot's solution time by the Tecplot 360 interface. This is done
                    to keep the GUI controls consistent. In batch mode, no such
                    side-effect will take place and the user must take care to set
                    the plot's solution time with the `plot.solution_time
                    <Cartesian3DFieldPlot.solution_time>` or
                    `plot.solution_timestep
                    <Cartesian3DFieldPlot.solution_timestep>` properties.
            """
            return _tecutil.ZoneGetStrandIDByDataSetID(self.dataset.uid,
                                                       self.index + 1)

        @strand.setter
        @tecutil.lock()
        def strand(self, value):
            if __debug__:
                if not isinstance(value, int):
                    raise TecplotTypeError('strand must be an integer.')
            _tecutil.ZoneSetStrandIDByDataSetID(self.dataset.uid,
                                                self.index + 1, int(value))

        @property
        def solution_time(self):
            """`float`: The solution time for this zone.

            Example usage::

                >>> dataset.zone('My Zone').solution_time = 3.14

            .. note:: **Possible side-effect when connected to Tecplot 360.**

                    Changing the solution times in the dataset or modifying the
                    active fieldmaps in a frame may trigger a change in the active
                    plot's solution time by the Tecplot 360 interface. This is done
                    to keep the GUI controls consistent. In batch mode, no such
                    side-effect will take place and the user must take care to set
                    the plot's solution time with the `plot.solution_time
                    <Cartesian3DFieldPlot.solution_time>` or
                    `plot.solution_timestep
                    <Cartesian3DFieldPlot.solution_timestep>` properties.
            """
            return _tecutil.ZoneGetSolutionTime(self.index + 1)

        @solution_time.setter
        @tecutil.lock()
        def solution_time(self, value):
            with self.dataset.frame.activated():
                _tecutil.ZoneSetSolutionTime(self.index + 1, float(value))

        @property
        def zone_type(self):
            return _tecutil.ZoneGetTypeByDataSetID(self.dataset.uid, self.index + 1)

        @property
        def name(self):
            """`str`: The name of the zone.

            .. warning:: **Newlines in string identifiers may affect performance.**

                When iterating over many items by name, such as must be done when
                fetching an item via pattern matching, PyTecplot will optimize the
                search only if there are no newline characters in the searched
                items. Iterating over strings that contain newlines will be slower
                and therefore, it is best to avoid using newlines in string
                identifiers or names of objects such as `Zones <data_access>` or
                `Variables <Variable>`.

            Example usage::

                >>> dataset.zone(0).name = 'Zone 0'
            """
            res, zname = _tecutil.ZoneGetNameByDataSetID(self.dataset.uid,
                                                         self.index + 1)
            if not res:
                raise TecplotSystemError()
            return zname

        @name.setter
        @tecutil.lock()
        def name(self, name):
            _tecutil.ZoneRenameByDataSetID(self.dataset.uid, self.index + 1, name)

        @property
        def num_variables(self):
            """`int`: Number of `Variables <Variable>` in the parent `Dataset`.

            Example usage, iterating over all variables by index::

                >>> for i in range(dataset.num_variables):
                ...     variable = dataset.variable(i)
            """
            return self.dataset.num_variables

        def values(self, pattern):
            """Returns an `Array` by index or string pattern.

            Parameters:
                pattern (`int`, `str` or `Variable`): Zero-based index,
                    `glob-style pattern <fnmatch.fnmatch>` in which case, the first
                    match is returned, or a `Variable` object.

            .. note:: **Data operations can make use of Numpy when installed.**

                When doing large data transfers into and out of Tecplot using
                PyTecplot, it is recommended to install the Python array-processing
                module `Numpy <https://scipy.org>`_. PyTecplot will automatically
                use this to optimize data transfers which may result in significant
                performance gains.

            The `Variable.name` attribute is used to match the *pattern* to the
            desired `Array` though this is not necessarily unique::

                >>> ds = frame.dataset
                >>> print(ds)
                Dataset:
                  Zones: ['Rectangular zone']
                  Variables: ['x', 'y', 'z']
                >>> zone = ds.zone('Rectangular zone')
                >>> x = zone.values('x')
                >>> x == zone.values(0)
                True

            .. warning:: **Zone and variable ordering may change between releases**

                Due to possible changes in data loaders or data formats over time,
                the ordering of zones and variables may be different between
                versions of Tecplot 360. Therefore it is recommended to always
                reference zones and variables **by name** instead of by index.
            """
            if isinstance(pattern, (str, int)):
                variable = self.dataset.variable(pattern)
            else:
                variable = pattern
            return array.Array(self, variable)

        def copy(self, share_variables=False):
            """Duplicate this `Zone <data_access>` in the parent `Dataset`.

            The name is also copied but can be changed after duplication.

            Parameters:
                share_variables (`bool` or `list` of `Variables <Variable>`):
                    Share all variables between the original and generated zones if
                    `True` or the list of Variables to be shared. Variable sharing
                    allows you to lower the use of physical memory (RAM).  When
                    sharing a variable the memory used by the source zone is shared
                    with the copied zone.  Alterations to the variable in one zone
                    will affect the other.  See also `Dataset.branch_variables()`.
                    Default: `False`.

            Returns:
                `Zone <data_access>`: The newly created zone.

            Example::

                >>> new_zone = dataset.zone('My Zone').copy()
                >>> print(new_zone.name)
                My Zone
                >>> new_zone.name = 'My Zone Copy'
                >>> print(new_zone.name)
                My Zone Copy
            """
            return self.dataset.copy_zones(self, share_variables=share_variables)[0]

        def mirror(self, mirror_variables):
            """Mirror this `Zone <data_access>`.

            The name of the resulting zone will be "Mirror of zone *sourcezone*",
            where *sourcezone* is the number of the zone from which the mirrored
            zone was created. The variables in the newly created zones are shared
            with their corresponding source zones, except for variables to be
            mirrored as specified.

            Parameters:
                mirror_variables (`Variable` or `list` of `Variables <Variable>`):
                    Variables in the new zone to be multiplied by :math:`-1` after
                    the zone is copied. the variables may be `Variable` objects,
                    `str` names or `int` indices.

            Returns:
                A zone of the same type as the source.

            This example show how to mirror the first zone across the xy-plane in
            3D::

                >>> mirrored_zone = dataset.zone(0).mirror('Z')
            """
            return next(self.dataset.mirror_zones(mirror_variables, self))

        @property
        def _shape(self):
            return _tecutil.ZoneGetIJKByUniqueID(self.dataset.uid, self.index + 1)

        @property
        def num_faces(self):
            """`int`: Number of faces in this zone.

            This is the same as the number of elements times the number of faces
            per element. Example usage::

                >>> print(dataset.zone('My Zone').num_faces)
                1048576
            """
            return self.num_elements * self.num_faces_per_element

    class OrderedZone(Zone):
        """An ordered ``(i, j, k)`` zone within a `Dataset`.

        Ordered zones contain nodal or cell-centered arrays where the connectivity
        is implied by the dimensions and ordering of the data.

        `Zones <data_access>` can be identified (uniquely) by the index with their
        parent `Dataset` or (non-uniquely) by name. In general, a `Variable` must
        be selected to access the underlying data array. This object is used by
        fieldmaps and linemaps to apply style to specific zones. Here we obtain the
        fieldmap associated with the zone named 'My Zone'::

            >>> fmap = plot.fieldmap(dataset.zone('My Zone'))
        """

        @property
        def dimensions(self):
            """Nodal dimensions along ``(i, j, k)``.

            Returns:
                `tuple` of `integers <int>`: ``(i, j, k)`` for ordered data.

            Example usage::

                >>> print(zone.dimensions)
                (128, 128, 128)
            """
            return self._shape

        @property
        def rank(self):
            """`int`: Number of dimensions of the data array.

            This will return the number of dimensions which contain more than one
            value::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.dimensions)
                (10, 10, 1)
                >>> print(zone.rank)
                2
            """
            return sum(s > 1 for s in self.dimensions)

        @property
        def num_points(self):
            """`int`: Total number of nodes within this zone.

            This is number of nodes within the zone and is equivalent to the
            product of the values in `OrderedZone.dimensions`. Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.dimensions)
                (128, 128, 128)
                >>> print(zone.num_points)
                2097152
            """
            return reduce(lambda x, y: x * y, self.dimensions, 1)

        @property
        def num_elements(self):
            """`int`: Number of cells in this zone.

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.dimensions)
                (128, 128, 128)
                >>> print(zone.num_elements)
                2048383
            """
            reduced_shape = list(filter(lambda x: x > 1, self.dimensions))
            return reduce(lambda x, y: x * (y - 1), reduced_shape or [1], 1)

        @property
        def num_points_per_element(self):
            """`int`: Points per cell for ordered zones.

            For ordered zones, this is :math:`2^{d}` where :math:`d` is the number
            of dimensions greater than one:

                ==== =================
                Rank Faces Per Element
                ==== =================
                0    0
                1    2
                2    4
                3    8
                ==== =================

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.dimensions)
                (10, 10, 1)
                >>> print(zone.rank)
                2
                >>> print(zone.num_points_per_element)
                4
            """
            ndim = self.rank
            return 2**ndim if ndim > 0 else 0

        @property
        def num_faces_per_element(self):
            """`int`: Number of faces per element in this ordered zone.

            This is determined by the rank of the zone:

                ==== =================
                Rank Faces Per Element
                ==== =================
                0    0
                1    1
                2    4
                3    6
                ==== =================

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.dimensions)
                (1, 10, 10)
                >>> print(zone.rank)
                2
                >>> print(zone.num_faces_per_element)
                4
            """
            _fpe = {0: 0, 1: 1, 2: 4, 3: 6}
            return _fpe[self.rank]

        @tecutil.inherited_property(Zone)
        def zone_type(self):
            """`ZoneType`: The `ZoneType` indicating structure of the data contained.

            The specific type of zone this object represents::

                >>> print(dataset.zone(0).zone_type)
                ZoneType.Ordered
            """

        @property
        def face_neighbors(self):
            """`FaceNeighbors`: The face neighbor list for this ordered zone.

            Example usage::

                >>> zone = dataset.zone(0)
                >>> print(zone.face_neighbors.mode)
                FaceNeighborMode.LocalOneToOne
            """
            return face_neighbors.FaceNeighbors(self)

        def copy(self, share_variables=False, i_range=None, j_range=None,
                 k_range=None):
            """Duplicate this `Zone <data_access>` in the parent `Dataset`.

            The name is also copied but can be changed after duplication.

            Parameters:
                share_variables (`bool` or `list` of `Variables <Variable>`):
                    Share all variables between the original and generated zones if
                    `True` or the list of Variables to be shared. Variable sharing
                    allows you to lower the use of physical memory (RAM).  When
                    sharing a variable the memory used by the source zone is shared
                    with the copied zone.  Alterations to the variable in one zone
                    will affect the other.  See also `Dataset.branch_variables()`.
                    Default: `False`.
                i_range (`tuple` of `integers <int>`, optional):
                    Range (min, max, step) along the ``i`` dimension for ordered
                    data. Min and max are zero-based indicies where max is
                    inclusive. If step causes max to be skipped, max will be
                    included. If `None` (default), the entire range will be copied.
                j_range (`tuple` of `integers <int>`, optional):
                    Range (min, max, step) along the ``j`` dimension for ordered
                    data. Min and max are zero-based indicies where max is
                    inclusive. If step causes max to be skipped, max will be
                    included. If `None` (default), the entire range will be copied.
                k_range (`tuple` of `integers <int>`, optional):
                    Range (min, max, step) along the ``k`` dimension for ordered
                    data. Min and max are zero-based indicies where max is
                    inclusive. If step causes max to be skipped, max will be
                    included. If `None` (default), the entire range will be copied.

            Returns:
                `Zone <data_access>`: The newly created zone.

            .. code-block:: python

                import tecplot as tp

                ds = tp.active_page().add_frame().create_dataset('D', ['x','y','z'])
                z = ds.add_ordered_zone('Z1', (3,3,3))
                zcopy = z.copy(i_range=(1, -1, 2))
            """
            return self.dataset.copy_zones(self, share_variables=share_variables,
                                           i_range=i_range, j_range=j_range,
                                           k_range=k_range)[0]

    class FEZone(Zone):
        @property
        def num_points(self):
            """`int`: Total number of nodes within this zone.

            This is the total number of nodes in the zone. Example usage::

                >>> print(dataset.zone('My Zone').num_points)
                2048
            """
            return self._shape[0]

        @property
        def num_elements(self):
            """`int`: Number of cells in this finite-element zone.

            Example usage::

                >>> print(dataset.zone('My Zone').num_elements)
                1048576
            """
            return self._shape[1]

        @property
        def shared_connectivity(self):
            """`list` of `Zones <data_access>`: `Zones <data_access>` sharing connectivity.

            Example usage::

                >>> dataset.zone('My Zone').copy()
                >>> for zone in dataset.zone('My Zone').shared_connectivity:
                ...     print(zone.index)
                0
                1
            """
            indices = _tecutil.ConnectGetShareZoneSet(self.index + 1)
            ret = [self.dataset.zone(i) for i in indices]
            indices.dealloc()
            return ret

    class ClassicFEZone(FEZone):
        """A classic finite-element zone within a `Dataset`.

        Classic finite-element zones are arrays of nodes that are connected
        explicitly into pre-defined geometric shapes called "elements." The
        geometry is consistent across the whole zone so that the number of nodes
        per element is constant.

        `Zones <data_access>` can be identified (uniquely) by the index with their
        parent `Dataset` or (non-uniquely) by name. In general, a `Variable` must
        be selected to access the underlying data array. This object is used by
        fieldmaps and linemaps to apply style to specific zones. Here we obtain the
        fieldmap associated with the zone named 'My Zone'::

            >>> fmap = plot.fieldmap(dataset.zone('My Zone'))
        """

        @property
        def num_points_per_element(self):
            """`int`: Points per element for classic finite-element zones.

            The number of points (also known as nodes) per finite-element is
            determined from the ``zone_type`` parameter. The follow table shows the
            number of points per element for the available zone types along with
            the resulting shape of the nodemap based on the number of points
            specified (:math:`N`):

                ============== ============== ========================
                Zone Type      Points/Element Nodemap Shape
                ============== ============== ========================
                ``FELineSeg``  2              (:math:`N`, :math:`2 N`)
                ``FETriangle`` 3              (:math:`N`, :math:`3 N`)
                ``FEQuad``     4              (:math:`N`, :math:`4 N`)
                ``FETetra``    4              (:math:`N`, :math:`4 N`)
                ``FEBrick``    8              (:math:`N`, :math:`8 N`)
                ============== ============== ========================

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.zone_type)
                ZoneType.FETriangle
                >>> print(zone.num_points_per_element)
                3
            """
            return self.nodemap.num_points_per_element

        @property
        def nodemap(self):
            """`Nodemap`: The connectivity `Nodemap` for this classic finite-element zone.

            Example usage::

                >>> zone = dataset.zone(0)
                >>> print(zone.nodemap.num_points_per_element)
                4
            """
            return nodemap.Nodemap(self)

        @property
        def face_neighbors(self):
            """`FaceNeighbors`: The face neighbor list for this finite-element zone.

            Example usage::

                >>> zone = dataset.zone(0)
                >>> print(zone.face_neighbors.mode)
                FaceNeighborMode.LocalOneToMany
            """
            return face_neighbors.FaceNeighbors(self)

        @tecutil.inherited_property(Zone)
        def zone_type(self):
            """`ZoneType`: The `ZoneType` indicating structure of the data contained.

            The specific type of zone this object represents::

                >>> print(dataset.zone(0).zone_type)
                ZoneType.FEBrick
            """

        @property
        def rank(self):
            """`int`: Number of dimensions of the data array.

            This indicates the dimensionality of the data and is dependent on the
            type of element this zone contains:

                ============== ====
                Zone Type      Rank
                ============== ====
                ``FELineSeg``  1
                ``FETriangle`` 2
                ``FEQuad``     2
                ``FETetra``    3
                ``FEBrick``    3
                ============== ====

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.zone_type)
                ZoneType.FEBrick
                >>> print(zone.rank)
                3
            """
            _rank = {ZoneType.FELineSeg: 1,
                     ZoneType.FETriangle: 2,
                     ZoneType.FEQuad: 2,
                     ZoneType.FETetra: 3,
                     ZoneType.FEBrick: 3}
            return _rank[self.zone_type]

        @property
        def num_faces_per_element(self):
            """`int`: Number of faces per element.

            This is dependent on the type of element this zone contains:

                ============== =================
                Zone Type      Faces Per Element
                ============== =================
                ``FELineSeg``  1
                ``FETriangle`` 3
                ``FEQuad``     4
                ``FETetra``    4
                ``FEBrick``    6
                ============== =================

            Example usage::

                >>> print(dataset.zone('My Zone').num_faces_per_element)
                4
            """
            _fpe = {ZoneType.FELineSeg: 1,
                    ZoneType.FETriangle: 3,
                    ZoneType.FEQuad: 4,
                    ZoneType.FETetra: 4,
                    ZoneType.FEBrick: 6}
            return _fpe[self.zone_type]

    class PolyFEZone(FEZone):
        """A polygonal finite-element zone within a `Dataset`.

        A polygonal zone consists of arrays of nodes which are connected explicitly
        into arbitrary and varying geometric elements. These elements are 2D or 3D
        in nature and have a number of faces (connections between nodes) which hold
        the concept of a left and right neighbor.

        `Zones <data_access>` can be identified (uniquely) by the index with their
        parent `Dataset` or (non-uniquely) by name. In general, a `Variable` must
        be selected to access the underlying data array. This object is used by
        fieldmaps and linemaps to apply style to specific zones. Here we obtain the
        fieldmap associated with the zone named 'My Zone'::

            >>> fmap = plot.fieldmap(dataset.zone('My Zone'))
        """

        @property
        @tecutil.lock()
        def num_faces(self):
            """`int`: Number of faces in this finite-element zone.

            The number of faces may be ``0`` if unknown or facemap creation is
            deferred. Example usage::

                >>> print(dataset.zone('My Zone').num_faces)
                1048576
            """
            try:
                with self.dataset.frame.activated():
                    _ = _tecutil.DataFaceMapGetReadableRef(self.index + 1)
            except TecplotLogicError:
                return 0
            return self._shape[2]

        @property
        def rank(self):
            """`int`: Number of dimensions of the data array.

            This indicates the dimensionality of the data and is dependent on the
            type of element this zone contains:

                ================ ====
                Zone Type        Rank
                ================ ====
                ``FEPolygon``    2
                ``FEPolyhedron`` 3
                ================ ====

            Example usage::

                >>> zone = dataset.zone('My Zone')
                >>> print(zone.zone_type)
                ZoneType.FEPolygon
                >>> print(zone.rank)
                2
            """
            _rank = {ZoneType.FEPolygon: 2,
                     ZoneType.FEPolyhedron: 3}
            return _rank[self.zone_type]

        @property
        def facemap(self):
            """`Facemap`: The connectivity `Facemap` for this polygonal finite-element zone.

            Example usage::

                >>> zone = dataset.zone(0)
                >>> print(zone.facemap.num_faces)
                4500
            """
            return facemap.Facemap(self)

        @tecutil.inherited_property(Zone)
        def zone_type(self):
            """`ZoneType`: The `ZoneType` indicating structure of the data contained.

            The specific type of zone this object represents::

                >>> print(dataset.zone(0).zone_type)
                ZoneType.FEPolygon
            """