""".. _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 collections
import logging
import textwrap
from functools import reduce
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 = textwrap.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 <tecplot.data.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 <tecplot.data.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 <tecplot.data.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
[docs]class OrderedZone(Zone):
"""An ordered ``(i, j, k)`` zone within a `Dataset <tecplot.data.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 <tecplot.data.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)
[docs] def copy(self, share_variables=False, i_range=None, j_range=None,
k_range=None):
"""Duplicate this `Zone <data_access>` in the parent `Dataset <tecplot.data.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 BlockUniformFEZone(FEZone):
@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
"""
[docs]class ClassicFEZone(BlockUniformFEZone):
"""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 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 nodemap(self):
"""`ClassicNodemap`: The connectivity for this finite-element zone.
Example usage::
>>> zone = dataset.zone(0)
>>> print(zone.nodemap.num_points_per_element)
4
"""
return nodemap.ClassicNodemap(self)
@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 following 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 elements specified (:math:`N`):
============== ============== ======================
Zone Type Points/Element Nodemap Shape
============== ============== ======================
``FELineSeg`` 2 (:math:`N`, :math:`2`)
``FETriangle`` 3 (:math:`N`, :math:`3`)
``FEQuad`` 4 (:math:`N`, :math:`4`)
``FETetra`` 4 (:math:`N`, :math:`4`)
``FEBrick`` 8 (:math:`N`, :math:`8`)
============== ============== ======================
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 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]
[docs]class MixedFEZone(BlockUniformFEZone):
"""A finite-element zone capable of storing high-order elements.
The nodemap for mixed finite-element zones consists of sections of
uniform cell types::
>>> zone = dataset.zone('My Zone')
.. seealso:: `Dataset.add_fe_mixed_zone()`
"""
def __init__(self, uid, dataset):
if __debug__:
reqver = (2023, 1)
if version.sdk_version_info < reqver:
msg = 'Mixed FE Zones requires 2023 R1 or later.'
raise TecplotOutOfDateEngineError(reqver, msg)
super().__init__(uid, dataset)
@tecutil.inherited_property(Zone)
def zone_type(self):
"""`ZoneType`: The `ZoneType` indicating structure of the data contained.
This will always return `ZoneType.FEMixed` for `MixedFEZone`::
>>> print(dataset.zone(0).zone_type)
ZoneType.FEMixed
"""
@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. All sections within an "FE-mixed zone" (a zone of
type `ZoneType.FEMixed`), must consist of sections with the same dimension.
.. note:: All sections within a zone are required to have the same
dimensionality and therefore only the first section is queried when
fetching the rank of the zone.
Example usage::
>>> zone = dataset.zone('My Zone')
>>> print(zone.zone_type)
ZoneType.FEMixed
>>> print(zone.section_metrics(0).cell_shape)
FECellShape.Tetrahedron
>>> print(zone.rank)
3
"""
_rank = {FECellShape.Bar: 1,
FECellShape.Triangle: 2,
FECellShape.Quadrilateral: 2,
FECellShape.Tetrahedron: 3,
FECellShape.Prism: 3,
FECellShape.Pyramid: 3,
FECellShape.Hexahedron: 3,}
if self.num_sections > 0:
return _rank[self.section_metrics(0).cell_shape]
else:
return 0
@property
def nodemap(self):
"""`Nodemap`: The connectivity `Nodemap` for this finite-element zone.
Example usage::
>>> zone = dataset.zone(0)
>>> print(zone.nodemap.num_points_per_element)
4
"""
return nodemap.Nodemap(self)
@property
@tecutil.lock()
def num_sections(self):
"""The number of sections of uniform cell type.
.. note:: This property is read-only.
Example usage::
>>> zone = dataset.zone('My Zone')
>>> print(zone.num_sections)
1
"""
success, result = _tecutil.ZoneGetNumSections(self.dataset.uid,
self.index + 1)
if not success:
msg = 'could not determine the number of sections'
raise TecplotSystemError(msg)
return result
SectionMetrics = collections.namedtuple(
'SectionMetrics',
('cell_shape', 'grid_order', 'basis_func', 'num_elements',
'num_corners_per_elem', 'num_nodes_per_elem'))
[docs] @tecutil.lock()
def section_metrics(self, section_index):
"""Returns the type and number of cells within a specific section.
Returns:
`collections.namedtuple`
cell_shape: `FECellShape`
The shape of all cells within this section.
grid_order: `int`
The grid-order for all cell in this section. A value of one
indicates a "linear" cell with corners only and no high-order
nodes.
basis_func: `FECellBasisFunction`
This determines the number of high-order nodes for a given shape
and grid order as well as the winding (ordering) of the nodes.
Currently, only `FECellBasisFunction.Lagrangian` is supported.
num_elements: `int`
The total number of elements or cells within this section.
num_corners_per_elem: `int`
The number of linear nodes (those nodes at the corners) for all
cells within this section.
num_nodes_per_elem: `int`
The total number of nodes for each cell within this section. This
will be the same as **num_corners_per_elem** for grid-order one
cells.
Example usage::
>>> zone = dataset.zone('My Zone')
>>> metrics = zone.section_metrics(0) # first section
>>> print(metrics.cell_shape)
FECellShape.Tetrahedron
>>> print(metrics.grid_order)
2
>>> print(metrics.basis_func)
FECellBasisFunction.Lagrangian
>>> print(metrics.num_elements)
1024
"""
success, *metrics = _tecutil.ZoneGetSectionMetrics(
self.dataset.uid, self.index + 1, section_index + 1)
if not success:
msg = 'could not get metrics for section ' + str(section_index)
raise TecplotSystemError(msg)
return MixedFEZone.SectionMetrics(*metrics)
[docs]class PolyFEZone(FEZone):
"""A polygonal finite-element zone within a `Dataset <tecplot.data.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 <tecplot.data.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
"""
