import collections
import ctypes
import fnmatch
import itertools as it
import logging
import re
import warnings
from collections.abc import Iterable
from functools import reduce
from keyword import iskeyword
from textwrap import dedent, TextWrapper
from ..tecutil import _tecutil, _tecutil_connector
from ..constant import *
from ..exception import *
from .. import layout, macro, session, tecutil, version
from ..tecutil import (IndexSet, ListWrapper, StringList,
flatten_args, lock, lock_attributes, sv)
from .variable import Variable
from .zone import ClassicFEZone, MixedFEZone, OrderedZone, PolyFEZone, Zone
log = logging.getLogger(__name__)
[docs]
@lock_attributes
class SolutionTimeClustering(object):
"""Settings for controlling solution time clustering of solution times.
By default, a dataset's zones solution times are organized into time steps
with the assumption that they are distributed linearly, and are grouped
together if they are within the following solution time tolerance::
(tolerance_factor)*(max_time - min_time) + absolute_tolerance
Where by default the tolerance_factor is 1.0e-6 and the absolute_tolerance
is 0.0.
"""
def __init__(self, dataset):
self.dataset = dataset
def __str__(self):
"""Brief string representation.
Returns:
`str`: Brief representation of this `SolutionTimeClustering`,
showing the options controlling how solution times are grouped into
time steps.
Example::
>>> dataset = frame.dataset
>>> print(dataset.solution_time_clustering)
SolutionTimeClustering
time_scaling: TimeScaling.Linear
absolute_tolerance: 0.0
tolerance_factor: 1.0e-6
"""
fmt = dedent('''\
SolutionTimeClustering:
time_scaling: {}
absolute_tolerance: {}
tolerance_factor: {}''')
return fmt.format(self.time_scaling, self.absolute_tolerance,
self.tolerance_factor)
@property
@lock()
def time_scaling(self):
"""`TimeScaling`: Scaling used to cluster zones by their solution times.
Identifies if the dataset's zone solution times are distributed linearly
or logarithmically. (Default: `TimeScaling.Linear`)
Possible values: `TimeScaling.Linear`, `TimeScaling.Logarithmic`.
Example usage::
>>> from tecplot.constant import TimeScaling
>>> dataset.solution_time_clustering.time_scaling = \\
... TimeScaling.Logarithmic
.. versionadded:: 2021.2
Solution time clustering requires Tecplot 360 2021 R2 or later.
"""
return _tecutil.SolutionTimeGetTimeScaling(self.dataset.uid)
@time_scaling.setter
@lock()
def time_scaling(self, time_scaling):
value = TimeScaling(time_scaling).value
if not _tecutil.SolutionTimeSetTimeScaling(self.dataset.uid, value):
raise TecplotSystemError()
@property
@lock()
def absolute_tolerance(self):
"""`float`: Absolute tolerance used to cluster zones by their solution times.
Absolute tolerance applied to each solution time when clustering with
nearby times. (Default: 0.0)
Example usage::
>>> dataset.solution_time_clustering.absolute_tolerance = 0.0025
.. versionadded:: 2021.2
Solution time clustering requires Tecplot 360 2021 R2 or later.
"""
return _tecutil.SolutionTimeGetAbsoluteTolerance(self.dataset.uid)
@absolute_tolerance.setter
@lock()
def absolute_tolerance(self, absolute_tolerance):
uid = self.dataset.uid
value = float(absolute_tolerance)
if not _tecutil.SolutionTimeSetAbsoluteTolerance(uid, value):
raise TecplotSystemError()
@property
@lock()
def tolerance_factor(self):
"""`float`: Tolerance factor used to cluster zones by solution times.
Tolerance factor, which is multiplied by the overall solution time
delta and applied to each solution time when clustering nearby times.
(Default: 1.0e-6)
Example usage::
>>> dataset.solution_time_clustering.tolerance_factor = 1.0e-4
.. versionadded:: 2021.2
Solution time clustering requires Tecplot 360 2021 R2 or later.
"""
return _tecutil.SolutionTimeGetToleranceFactor(self.dataset.uid)
@tolerance_factor.setter
@lock()
def tolerance_factor(self, tolerance_factor):
uid = self.dataset.uid
value = float(tolerance_factor)
if not _tecutil.SolutionTimeSetToleranceFactor(uid, value):
raise TecplotSystemError()
[docs]
@lock_attributes
class Dataset(object):
"""Table of `Arrays <Array>` identified by `Zone <data_access>` and `Variable`.
This is the primary data container within the Tecplot Engine. A `Dataset <tecplot.data.Dataset>`
can be shared among several `Frames <layout.Frame>`, though any particular
`Dataset <tecplot.data.Dataset>` object will have a handle to at least one of them. Any
modification of a shared `Dataset <tecplot.data.Dataset>` will be reflected in all `Frames
<layout.Frame>` that use it.
Though a `Dataset <tecplot.data.Dataset>` is usually attached to a `Frame <layout.Frame>` and the plot style
associated with that, it can be thought of as independent from any style or
plotting representation. Each `Dataset <tecplot.data.Dataset>` consists of a list of `Variables
<Variable>` which are used by one or more of a list of `Zones
<data_access>`. The `Variable` determines the data type, while the `Zone
<data_access>` determines the layout such as shape and ordered vs
unordered.
The actual data are found at the intersection of a `Zone <data_access>` and
`Variable` and the resulting object is an `Array`. The data array can be
obtained using either path::
>>> # These two lines obtain the same object "x"
>>> x = dataset.zone('My Zone').values('X')
>>> x = dataset.variable('X').values('My Zone')
A `Dataset <tecplot.data.Dataset>` is the object returned by most data-loading operations in
|PyTecplot|::
>>> dataset = tecplot.data.load_tecplot('my_data.plt')
Under `Dataset <tecplot.data.Dataset>`, there are a number methods to create and delete `Zones
<data_access>` and `variables <Variable>`.
"""
def __init__(self, uid, frame):
self.uid = uid
self.frame = frame
def __repr__(self):
"""Executable string representation.
Returns:
`str`: Internal representation of this `Dataset <tecplot.data.Dataset>`.
The string returned can be executed to generate a
clone of this `Dataset <tecplot.data.Dataset>` object::
>>> dataset = frame.dataset
>>> print(repr(dataset))
Dataset(uid=21, frame=Frame(uid=11, page=Page(uid=1)))
>>> exec('dataset_clone = '+repr(dataset))
>>> dataset_clone
Dataset(uid=21, frame=Frame(uid=11, page=Page(uid=1)))
>>> dataset == dataset_clone
True
"""
return 'Dataset(uid={uid}, frame={frame})'.format(
uid=self.uid, frame=repr(self.frame))
def __str__(self):
"""Brief string representation.
Returns:
`str`: Brief representation of this `Dataset <tecplot.data.Dataset>`, showing
`Zones <data_access>` and `Variables <Variable>`.
Example::
>>> dataset = frame.dataset
>>> print(dataset)
Dataset: 'My Dataset'
Zones: 'Rectangular zone'
Variables: 'x', 'y', 'z'
"""
fmt = dedent('''\
Dataset: '{}'
Zones: {}
Variables: {}''')
maxwidth = 79
wrapper = ListWrapper(initial_width=maxwidth - len(' Zones: '),
subsequent_indent=' ',
subsequent_width=maxwidth)
zones = wrapper.fill(self.zone_names)
wrapper.initial_width = maxwidth - len(' Variables: ')
variables = wrapper.fill(self.variable_names)
return fmt.format(self.title, zones, variables)
def __eq__(self, other):
"""Checks for equality in the |Tecplot Engine|.
Returns:
`bool`: `True` if the unique ID numbers are the same for both
`Datasets <tecplot.data.Dataset>`.
This can be useful for determining if two `Frames <layout.Frame>`
are holding on to the same `Dataset <tecplot.data.Dataset>`::
>>> frame1.dataset == frame2.dataset
True
"""
return self.uid == other.uid
def __ne__(self, other):
return not self.__eq__(other)
def __contains__(self, obj):
if obj.dataset == self:
if isinstance(obj, Variable) and obj == self.variable(obj.index):
return True
elif isinstance(obj, Zone) and obj == self.zone(obj.index):
return True
return False
@property
def aux_data(self):
"""Auxiliary data for this dataset.
Returns:
`AuxData`
This is the auxiliary data attached to the dataset. Such data is
written to the layout file by default and can be retrieved later.
Example usage::
>>> frame = tp.active_frame()
>>> aux = frame.dataset.aux_data
>>> aux['Result'] = '3.14159'
>>> print(aux['Result'])
3.14159
"""
return session.AuxData(self.frame, AuxDataObjectType.Dataset)
@property
def title(self):
"""`str`: Title of this `Dataset <tecplot.data.Dataset>`.
Example usage::
>>> dataset.title = 'My Data'
.. versionchanged:: 2017.3 of Tecplot 360
The dataset title property requires Tecplot 360 2017 R3 or later.
"""
success, title, _, _ = _tecutil.DataSetGetInfoByUniqueID(self.uid)
if not success:
raise TecplotSystemError()
return title
@title.setter
@lock()
def title(self, title):
if not _tecutil.DataSetSetTitleByUniqueID(self.uid, title):
raise TecplotSystemError()
@property
def solution_time_clustering(self):
"""`SolutionTimeClustering`: Solution time clustering options.
Example usage::
>>> from tecplot.constant import TimeScaling
>>> dataset.solution_time_clustering.time_scaling = \\
... TimeScaling.Logarithmic
.. versionadded:: 2021.2
Solution time clustering requires Tecplot 360 2021 R2 or later.
"""
if __debug__:
reqver = (2021, 2)
if version.sdk_version_info < reqver:
msg = 'Solution time clustering options require 2021 R2 or later.'
raise TecplotOutOfDateEngineError(reqver, msg)
return SolutionTimeClustering(self)
@property
def num_zones(self):
"""`int`: Number of `Zones <data_access>` in this `Dataset <tecplot.data.Dataset>`.
This count includes disabled zones which were skipped when loading the
data. Example usage::
>>> for i in range(dataset.num_zones):
... zone = dataset.zone(i)
"""
return _tecutil.DataSetGetNumZonesByUniqueID(self.uid)
[docs]
def zone(self, pattern):
"""Returns `Zone <data_access>` by index or string pattern.
Parameters:
pattern (`int`, `str` or `re.Pattern <re.compile>`): Zero-based
index, case-insensitive `glob-style pattern string
<fnmatch.fnmatch>` or a compiled `regex pattern instance
<re.compile>` used to match the zones by name. A negative index
is interpreted as counting from the end of the available zones.
Returns:
`OrderedZone`, `ClassicFEZone` or `PolyFEZone` depending on the
zone type, `None` no matching `zone <data_access>` name was found.
Raises:
`TecplotIndexError`
.. note::
A `Dataset <tecplot.data.Dataset>` can contain `zones <data_access>` with identical names
and only the first match found is returned. This is not guaranteed
to be deterministic and care should be taken to have only
`zones <data_access>` with unique names when this feature is used.
The `Zone.name <OrderedZone.name>` attribute is used to match the
*pattern* to the desired `Zone <data_access>` though this is not
necessarily unique::
>>> ds = frame.dataset
>>> print(ds)
Dataset:
Zones: ['Rectangular zone']
Variables: ['x', 'y', 'z']
>>> rectzone = ds.zone('Rectangular zone')
>>> rectzone == ds.zone(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, Zone):
return pattern
_dispatch = {
ZoneType.Ordered: OrderedZone,
ZoneType.FELineSeg: ClassicFEZone,
ZoneType.FETriangle: ClassicFEZone,
ZoneType.FEQuad: ClassicFEZone,
ZoneType.FETetra: ClassicFEZone,
ZoneType.FEBrick: ClassicFEZone,
ZoneType.FEPolygon: PolyFEZone,
ZoneType.FEPolyhedron: PolyFEZone,
ZoneType.FEMixed: MixedFEZone}
pattern_type = getattr(re, 'Pattern', getattr(re, '_pattern_type', None))
if isinstance(pattern, (str, pattern_type)):
try:
return next(self.zones(pattern))
except StopIteration:
pass
else:
if pattern < 0:
pattern += self.num_zones
try:
if __debug__:
# ensure zone is enabled
if not _tecutil.ZoneIsEnabledByDataSetID(self.uid, pattern + 1):
msg = 'zone {} is not enabled'.format(pattern)
raise TecplotIndexError(msg)
uid = _tecutil.ZoneGetUniqueIDByDataSetID(self.uid,
pattern + 1)
ztype = _tecutil.ZoneGetTypeByDataSetID(self.uid, pattern + 1)
return _dispatch[ztype](uid, self)
except (TecplotSystemError, TecplotLogicError) as e:
raise TecplotIndexError(str(e))
@property
def _zone_indices(self):
"""Zero-based indices of all enabled zones in the dataset."""
success, ptr = _tecutil.ZoneGetEnabledByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
indices = ctypes.cast(ptr, IndexSet)
try:
return list(indices)
finally:
indices.dealloc()
@property
def _zone_uids(self):
"""Unique IDs for all enabled zones in the dataset."""
try:
success, nuids, uids_ptr = _tecutil.ZoneGetUniqueIDsByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
try:
return uids_ptr[:nuids]
finally:
if not _tecutil_connector.connected:
_tecutil.ArrayDealloc(uids_ptr)
except (AttributeError, TecplotSystemError) as err:
try:
return [_tecutil.ZoneGetUniqueIDByDataSetID(self.uid, zone_index + 1)
for zone_index in self._zone_indices]
except:
raise err
@property
def _zone_types(self):
"""`ZoneType`s of all enabled zones in the dataset."""
try:
success, ntypes, types_ptr = _tecutil.ZoneGetTypesByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
try:
return [ZoneType(types_ptr[i]) for i in range(ntypes)]
finally:
if not _tecutil_connector.connected:
_tecutil.ArrayDealloc(types_ptr)
except (AttributeError, TecplotSystemError) as err:
try:
return [_tecutil.ZoneGetTypeByDataSetID(self.uid, zone_index + 1)
for zone_index in self._zone_indices]
except:
try:
with self.frame.activated():
return [_tecutil.ZoneGetType(zone_index + 1)
for zone_index in self._zone_indices]
except:
raise err
@property
def zone_names(self):
"""A `list` of names for all zones in the dataset.
.. 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::
>>> print(dataset.zone_names)
['Zone A', 'Zone B', 'Zone C']
"""
try:
success, ptr = _tecutil.ZoneGetNamesByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
names = ctypes.cast(ptr, StringList)
try:
return list(names)
finally:
names.dealloc()
except (AttributeError, TecplotSystemError) as err:
try:
success, ptr = _tecutil.ZoneGetEnabledNamesByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
names = ctypes.cast(ptr, StringList)
try:
return list(names)
finally:
names.dealloc()
except:
try:
return [z.name for z in self.zones()]
except:
raise err
[docs]
def zones(self, pattern=None):
"""Yields all `Zones <data_access>` matching a *pattern*.
Parameters:
pattern (`str` or `re.Pattern <re.compile>`, optional):
Case-insensitive `glob-style pattern string <fnmatch.fnmatch>`
or a compiled `regex pattern instance <re.compile>` used to
match zone names.
Returns:
Generator of `OrderedZones <OrderedZone>`, `ClassicFEZones
<ClassicFEZone>` or `PolyFEZones <PolyFEZone>` depending on the
zone types. All `zones <data_access>` if *pattern* is not
specified.
If **pattern** is a string, this will be interpreted as a
case-insensitive `glob-style pattern <fnmatch.fnmatch>`. Example using
glob which will match all zones starting with "A" or "a"::
>>> for zone in dataset.zones('A*'):
... x_array = zone.variable('X')
Alternatively, a regular-expression may be compiled using `re.compile`
which will be used directly. This example shows a case-sensitive regex
search::
>>> import re
>>> pattern = re.compile('[A-Z]*')
>>> for zone in dataset.zones(pattern):
... x_array = zone.variable('X')
Use list comprehension to construct a list of all zones with 'Wing'
in the zone name. In contrast to the `Dataset.zones()` method, this
is case-sensitive::
>>> wing_zones = [Z for Z in dataset.zones() if 'Wing' in Z.name]
.. 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.
"""
_dispatch = {
ZoneType.Ordered: OrderedZone,
ZoneType.FELineSeg: ClassicFEZone,
ZoneType.FETriangle: ClassicFEZone,
ZoneType.FEQuad: ClassicFEZone,
ZoneType.FETetra: ClassicFEZone,
ZoneType.FEBrick: ClassicFEZone,
ZoneType.FEPolygon: PolyFEZone,
ZoneType.FEPolyhedron: PolyFEZone,
ZoneType.FEMixed: MixedFEZone}
if pattern:
pattern_type = getattr(re, 'Pattern', getattr(re, '_pattern_type', None))
if not isinstance(pattern, pattern_type):
regex = re.compile(fnmatch.translate(pattern), re.IGNORECASE)
else:
regex = pattern
if __debug__:
found = False
for uid, typ, name in zip(self._zone_uids, self._zone_types, self.zone_names):
if regex.match(name):
if __debug__:
found = True
yield _dispatch[typ](uid, self)
if __debug__:
if (
not found and
isinstance(pattern, str) and
any(c in pattern for c in '*?[]')
):
msg = 'no zones found matching: "{}"'.format(pattern)
warning = TecplotPatternMatchWarning(pattern, msg, 'glob')
warnings.warn(warning)
else:
for uid, typ in zip(self._zone_uids, self._zone_types):
yield _dispatch[typ](uid, self)
@property
def num_variables(self):
"""`int`: Number of `Variables <Variable>` in this `Dataset <tecplot.data.Dataset>`.
This count includes disabled variables which were skipped when the data
was loaded. Example usage::
>>> for i in range(dataset.num_variables):
... variable = dataset.variable(i)
"""
return _tecutil.DataSetGetNumVarsByUniqueID(self.uid)
[docs]
def variable(self, pattern):
"""Returns the `Variable` by index or string pattern.
Parameters:
pattern (`int`, `str` or `re.Pattern <re.compile>`): Zero-based
index, case-insensitive `glob-style pattern string
<fnmatch.fnmatch>` or a compiled `regex pattern instance
<re.compile>` used to match the variable by name. A negative
index is interpreted as counting from the end of the available
variable.
Returns:
`Variable` or `None` if no matching `Variable` name was found.
Raises:
`TecplotIndexError`
.. note::
A `Dataset <tecplot.data.Dataset>` can contain `variables <Variable>` with identical names
and only the first match found is returned. This is not guaranteed
to be deterministic and care should be taken to have only
`variables <Variable>` with unique names when this feature is used.
The `Variable.name` attribute is used to match the *pattern* to the
desired `Variable` though this is not necessarily unique::
>>> ds = frame.dataset
>>> print(ds)
Dataset:
Zones: ['Rectangular zone']
Variables: ['x', 'y', 'z']
>>> x = ds.variable('x')
>>> x == ds.variable(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, Variable):
return pattern
pattern_type = getattr(re, 'Pattern', getattr(re, '_pattern_type', None))
if isinstance(pattern, (str, pattern_type)):
try:
return next(self.variables(pattern))
except StopIteration:
pass
else:
if pattern < 0:
pattern += self.num_variables
if 0 <= pattern < self.num_variables:
if __debug__:
if not _tecutil.VarIsEnabledByDataSetID(self.uid, pattern + 1):
msg = 'variable {} is not enabled'.format(pattern)
raise TecplotIndexError(msg)
return Variable(_tecutil.VarGetUniqueIDByDataSetID(
self.uid, pattern + 1), self)
raise TecplotIndexError
@property
def _variable_indices(self):
"""Yields zero-based indices for all enabled variables in the dataset."""
success, ptr = _tecutil.VarGetEnabledByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
indices = ctypes.cast(ptr, IndexSet)
try:
for i in indices:
yield i
finally:
indices.dealloc()
@property
def _variable_uids(self):
"""`list` of Unique IDs for all enabled variables in the dataset."""
try:
success, nuids, uids_ptr = _tecutil.VarGetUniqueIDsByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
try:
return uids_ptr[:nuids]
finally:
if not _tecutil_connector.connected:
_tecutil.ArrayDealloc(uids_ptr)
except (AttributeError, TecplotSystemError) as err:
try:
return [_tecutil.VarGetUniqueIDByDataSetID(self.uid, variable_index + 1)
for variable_index in self._variable_indices]
except:
raise err
@property
def variable_names(self):
"""A `list` of names for all variables in the dataset.
.. 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::
>>> print(dataset.variable_names)
['x', 'y', 'z', 's']
"""
try:
success, ptr = _tecutil.VarGetNamesByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
names = ctypes.cast(ptr, StringList)
try:
return list(names)
finally:
names.dealloc()
except (AttributeError, TecplotSystemError) as err:
try:
success, ptr = _tecutil.VarGetEnabledNamesByDataSetID(self.uid)
if not success:
raise TecplotSystemError()
names = ctypes.cast(ptr, StringList)
try:
return list(names)
finally:
names.dealloc()
except:
try:
return [z.name for z in self.variables()]
except:
raise err
[docs]
def variables(self, pattern=None):
"""Yields all `Variables <Variable>` matching a *pattern*.
Parameters:
pattern (`str` or `re.Pattern <re.compile>`, optional):
Case-insensitive `glob-style pattern string <fnmatch.fnmatch>`
or a compiled `regex pattern instance <re.compile>` used to
match variable names.
Returns:
Generator of `Variables <Variable>`. All `Variables <Variable>` if
*pattern* is not specified.
Example using case-insensitive glob-style matching::
>>> for variable in dataset.variables('A*'):
... array = variable.values('My Zone')
Example using (case-sensitive) regex::
>>> import re
>>> for variable in dataset.variables(re.compile(r'A.*')):
... array = variable.values('My Zone')
.. 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 pattern:
pattern_type = getattr(re, 'Pattern', getattr(re, '_pattern_type', None))
if not isinstance(pattern, pattern_type):
regex = re.compile(fnmatch.translate(pattern), re.IGNORECASE)
else:
regex = pattern
if __debug__:
found = False
for uid, name in zip(self._variable_uids, self.variable_names):
if regex.match(name):
if __debug__:
found = True
yield Variable(uid, self)
if __debug__:
if (
not found and
isinstance(pattern, str) and
any(c in pattern for c in '*?[]')
):
msg = 'no variables found matching: "{}"'.format(pattern)
warning = TecplotPatternMatchWarning(pattern, msg)
warnings.warn(warning)
else:
for uid in self._variable_uids:
yield Variable(uid, self)
@property
def VariablesNamedTuple(self):
r"""A `collections.namedtuple` object using variable names.
The variable names are transformed to be unique, valid identifiers
suitable for use as the key-list for a `collections.namedtuple`.
This means that all invalid characters such as spaces and dashes
are converted to underscores, Python keywords are appended by an
underscore, leading numbers or empty names are prepended with a "v"
and duplicate variable names are indexed starting with zero, padded
left with zeros variable names duplicated more than nine times. The
following table gives some specific examples:
==================== ===========================
Variable names Resulting namedtuple fields
==================== ===========================
``'x', 'y'`` ``'x', 'y'``
``'x', 'x'`` ``'x0', 'x1'``
``'X', 'Y=f(X)'`` ``'X', 'Y_f_X_'``
``'x 2', '_', '_'`` ``'x_2', 'v0', 'v1'``
``'def', 'if'`` ``'def_', 'if_'``
``'1', '2', '3'`` ``'v1', 'v2', 'v3'``
==================== ===========================
This example shows how one can use this n-tuple type with the
result from a call to `tecplot.data.query.probe_at_position`:
.. code-block:: python
from os import path
import tecplot as tp
examples_dir = tp.session.tecplot_examples_directory()
datafile = path.join(examples_dir,'SimpleData','DownDraft.plt')
dataset = tp.data.load_tecplot(datafile)
result = tp.data.query.probe_at_position(0,0.1,0.3)
data = dataset.VariablesNamedTuple(*result.data)
# prints: (RHO, E) = (1.17, 252930.37)
msg = '(RHO, E) = ({:.2f}, {:.2f})'
print(msg.format(data.RHO, data.E))
"""
# First we clean up variable names
# and keep a count of each name used
names = []
count = {}
for vname in self.variable_names:
# sub invalid characters with underscores
name = re.sub(r'\W|^(?=\d)', r'_', vname)
# remove leading underscores
name = re.sub(r'^_+', r'', name)
# prepend leading number with 'v'
name = re.sub(r'^(\d)', r'v\1', name)
# append keywords with underscore
if iskeyword(name):
name = name + '_'
# force non-empty variable names using 'v'
if name == '':
name = 'v'
# add name to list
names.append(name)
# keep track of names to identify duplicates
if name not in count:
count[name] = 0
count[name] += 1
# append index, with padded zeros
numbered = count.copy()
for i,name in enumerate(names):
if count[name] > 1:
names[i] = '{0}{1:0{2}d}'.format(name,
count[name] - numbered[name], len(str(count[name] - 1)))
numbered[name] -= 1
return collections.namedtuple('DatasetVariables', names)
[docs]
@lock()
def copy_zones(self, *zones, **kwargs):
"""Copies `Zones <data_access>` within this `Dataset <tecplot.data.Dataset>`.
Parameters:
*zones (`Zone <data_access>`, optional): Specific `Zones
<data_access>` to copy. All zones will be copied if none are
supplied.
shared_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:
`list` of the newly created `Zones <data_access>`.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
.. 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))
ds.copy_zones(z, i_range=(1, -1, 2), share_variables=True)
"""
share_variables = kwargs.pop('share_variables', False)
i_range = kwargs.pop('i_range', None)
j_range = kwargs.pop('j_range', None)
k_range = kwargs.pop('k_range', None)
if not share_variables:
branch_variables = list(self.variables())
elif isinstance(share_variables, Iterable):
for idx, var in enumerate(share_variables):
if not isinstance(var, Variable):
share_variables[idx]= self.variable(var)
branch_variables = [v for v in self.variables()
if v not in share_variables]
else:
branch_variables = []
num_zones = self.num_zones
with tecutil.ArgList() as arglist:
if not zones:
zones = self.zones()
with IndexSet(*zones) as zoneset:
arglist[sv.SOURCEZONES] = zoneset
for dim, rng in zip(['I', 'J', 'K'], [i_range, j_range, k_range]):
if rng is not None:
rng = tecutil.IndexRange(*rng)
if rng.min is not None:
arglist[dim + 'MIN'] = tecutil.Index(rng.min)
if rng.max is not None:
arglist[dim + 'MAX'] = tecutil.Index(rng.max)
if rng.step is not None:
step = int(rng.step)
if step > 0:
arglist[dim + 'SKIP'] = step
elif step < 0:
msg = 'Negative step not supported.'
raise TecplotLogicError(msg)
_tecutil.ZoneCopyX(arglist)
new_zones = [self.zone(i) for i in range(num_zones, self.num_zones)]
for zone in new_zones:
for var in branch_variables:
self.branch_variables(zone, var, True)
return new_zones
[docs]
def mirror_zones(self, mirror_variables, *zones):
"""Mirrors `Zones <data_access>` within this `Dataset <tecplot.data.Dataset>`.
Each mirror zone has a name of the form "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.
*zones (`Zones <data_access>`, optional): Specific `Zones
<data_access>` to mirror. All zones will be mirrored if none
are supplied. The values may also be `str` names or `int`
indices.
Returns:
Generator of mirrored zones.
This example show how to mirror all zones across the xy-plane in 3D::
>>> mirrored_zones = dataset.mirror_zones('Z')
"""
if (
isinstance(mirror_variables, str) or
not isinstance(mirror_variables, Iterable)
):
mirror_variables = [mirror_variables]
mvars = (v if isinstance(v, Variable) else self.variable(v)
for v in mirror_variables)
mvars = ','.join([str(v.index + 1) for v in mvars])
if not zones:
mzones = '1-{}'.format(self.num_zones)
else:
mzones = (z if isinstance(z, Zone) else self.zone(z)
for z in tecutil.flatten_args(*zones))
mzones = ','.join([str(z.index + 1) for z in mzones])
num_zones = self.num_zones
cmd = '$!CreateMirrorZones SourceZones = [{0}] MirrorVars = [{1}]'
macro.execute_command(cmd.format(mzones, mvars))
return (self.zone(i) for i in range(num_zones, self.num_zones))
[docs]
@lock()
def add_variable(self, name, dtypes=None, locations=None):
"""Add a single `Variable` to the active `Dataset <tecplot.data.Dataset>`.
Parameters:
name (`str`): The name of the new `Variable`. This does not
have to be unique.
dtypes (`FieldDataType` or `list` of `FieldDataType`, optional):
Data types of this `Variable` for each `Zone <data_access>` in
the currently active `Dataset <tecplot.data.Dataset>`. Options are:
`FieldDataType.Float`, `Double <FieldDataType.Double>`,
`Int32`, `Int16`, `Byte` and `Bit`. If a single value, this
will be duplicated for all `Zones <data_access>`. (default:
`None`)
locations (`ValueLocation` or `list` of `ValueLocation`, optional):
Point locations of this `Variable` for each
`Zone <data_access>` in the currently active `Dataset <tecplot.data.Dataset>`. Options
are: `Nodal` and `CellCentered`. If a single value, this will
be duplicated for all `Zones <data_access>`. (default: `None`)
Returns:
`Variable`
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
The added `Variable` will be available for use in each `Zone
<data_access>` of the dataset. This method should be used in
conjunction with other data creation methods such as
`Dataset.add_zone`:
.. code-block:: python
:emphasize-lines: 7-8
import math
import tecplot as tp
from tecplot.constant import PlotType
# Setup Tecplot dataset
dataset = tp.active_frame().create_dataset('Data')
dataset.add_variable('x')
dataset.add_variable('s')
zone = dataset.add_ordered_zone('Zone', 100)
# Fill the dataset
x = [0.1 * i for i in range(100)]
zone.values('x')[:] = x
zone.values('s')[:] = [math.sin(i) for i in x]
# Set plot type to XYLine
tp.active_frame().plot(PlotType.XYLine).activate()
tp.export.save_png('add_variables.png', 600, supersample=3)
.. figure:: /_static/images/add_variables.png
:width: 300px
:figwidth: 300px
"""
assert len(name) <= 128, 'Variable names are limited to 128 characters'
with self.frame.activated():
dataset = self.frame.dataset
new_variable_index = dataset.num_variables
with tecutil.ArgList(NAME=name) as arglist:
if dtypes is not None:
if not hasattr(dtypes, '__iter__'):
dtypes = [dtypes] * dataset.num_zones
arglist['VARDATATYPE'] = dtypes
if locations is not None:
if not hasattr(locations, '__iter__'):
locations = [locations] * dataset.num_zones
arglist['VALUELOCATION'] = locations
if __debug__:
msg = 'new variable: ' + name
for k, v in arglist.items():
msg += '\n {} = {}'.format(k, v)
log.debug(msg)
if not _tecutil.DataSetAddVarX(arglist):
raise TecplotSystemError()
return dataset.variable(new_variable_index)
[docs]
@lock()
def add_zone(self, zone_type, name, shape, dtypes=None, locations=None,
face_neighbor_mode=None, parent_zone=None, solution_time=None,
strand_id=None, index=None, sections=None):
"""Add a single `Zone <data_access>` to this `Dataset`.
Parameters:
zone_type (`ZoneType`): The type of `Zone <data_access>` to be
created. Possible values are: `Ordered`, `FETriangle`,
`FEQuad`, `FETetra`, `FEBrick`, `FELineSeg`, `FEPolyhedron`,
`FEPolygon` and `FEMixed`.
name (`str`): Name of the new `Zone <data_access>`. This
does not have to be unique.
shape (`int` or `list` of `integers <int>`): Specifies
the length and dimension (up to three) of the new `Zone
<data_access>`. A 1D `Zone <data_access>` is assumed if a
single `int` is given. This is **(i, j, k)** for ordered `Zones
<data_access>`, **(num_points, num_elements)** for
finite-element `Zones <data_access>` and **(num_points,
num_elements, num_faces)** for polytope `Zones <data_access>`
where the number of faces is known.
dtypes (`FieldDataType`, `list` of `FieldDataType`, optional): Data
types of this `Zone <data_access>` for each `Variable` in the
currently active `Dataset <tecplot.data.Dataset>`. Options are: `Float
<FieldDataType.Float>`, `Double <FieldDataType.Double>`,
`Int32`, `Int16`, `Byte` and `Bit`. If a single value, this
will be duplicated for all `Variables <Variable>`. If `None`
then the type of the first `Variable`, defaulting to
`FieldDataType.Float`, is used for all. (default: `None`)
locations (`ValueLocation`, `list` of `ValueLocation`, optional):
Point locations of this `Zone <data_access>` for each
`Variable` in the currently active `Dataset <tecplot.data.Dataset>`. Options are:
`Nodal` and `CellCentered`. If a single value, this will be
duplicated for all `Variables <Variable>`. If `None` then the
type of the first `Variable`, defaulting to `Nodal`, is used
for all. (default: `None`)
face_neighbor_mode (`FaceNeighborMode`, optional): Specifies the
face-neighbor mode for this zone. Options are:
`FaceNeighborMode.LocalOneToOne` (default),
`FaceNeighborMode.LocalOneToMany`,
`FaceNeighborMode.GlobalOneToOne` or
`FaceNeighborMode.GlobalOneToMany`.
parent_zone (`Zone <data_access>`, optional): A parent `Zone
<data_access>` to be used when generating surface-restricted
streamtraces.
solution_time (`float`, optional): Solution time for this zone.
(default: 0)
strand_id (`int`, optional): Associate this new `Zone
<data_access>` with a particular strand.
index (`int`, optional): Number of the zone to add or
replace. If omitted or set to `None`, the new zone will be
appended to the dataset. This value can be set to the number of
a zone that already exists thereby replacing the existing zone.
(default: `None`)
sections (`list` or `tuples <tuple>`): A list of the properties of
the sections in the form: ``(num_element, cell_shape,
grid_order, basis_function)``. The **grid_order** and
**basis_func** items may be omitted and will default to **1**
(linear) and `FECellBasisFunction.Lagrangian` respectively.
This parameter is only used when **zone_type** is set to `FEMixed`.
Returns:
`Zone <data_access>`
.. warning:: **Setting connectivity in connected mode.**
When connected to a running instance of Tecplot 360 using the
TecUtil Server, care must be taken to ensure that the GUI does not
try to render the data between the creation of the zone and the
setting of the connectivity, through the `Facemap` or `Nodemap`
objects. This can be achieved by setting the plot type of the
frame(s) holding on to the dataset to `PlotType.Sketch` before
creating the zone and only going to `PlotType.Cartesian3D` after
the connectivity is set. Tecplot 360 may get into a bad state,
corrupting loaded data, if it attempts to render (especially
polytope) data without connectivity.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
The added `Zone <data_access>` will be able to use all `Variables
<Variable>` defined in the dataset. This method should be used in
conjunction with other data creation methods such as
`Frame.create_dataset`. Example usage::
>>> from tecplot.constant import ZoneType
>>> zone = dataset.add_zone(ZoneType.Ordered, 'Zone', (10, 10, 10))
.. note::
The relationship and meaning of this method's parameters change
depending on the type of zone being created. Therefore, it is
recommended to use the more specific zone creation methods:
* `Dataset.add_ordered_zone`
* `Dataset.add_fe_zone`
* `Dataset.add_poly_zone`
"""
if __debug__:
if self.num_variables == 0:
errmsg = dedent('''\
Can not create a zone on a dataset with no variables.
Add at least one variable to this dataset before
creating any zones.''')
raise TecplotLogicError(errmsg)
if zone_type == ZoneType.FEMixed:
reqver = (2023, 1)
if version.sdk_version_info < reqver:
msg = 'FEMixed zone type requires 2023 R1 or later.'
raise TecplotOutOfDateEngineError(reqver, msg)
with self.frame.activated():
dataset = self.frame.dataset
new_zone_index = dataset.num_zones if index is None else index
with tecutil.ArgList(ZONETYPE=zone_type, NAME=name) as arglist:
# convert shape to (imax, jmax, kmax)
if not hasattr(shape, '__iter__'):
shape = [shape]
for k, v in zip([sv.IMAX, sv.JMAX, sv.KMAX], shape):
arglist[k] = v
# expand data types and locations to length of num_variables
for key, val in zip([sv.VARDATATYPE, sv.VALUELOCATION],
[dtypes, locations]):
if val is not None:
if not hasattr(val, '__iter__'):
val = [val] * dataset.num_variables
arglist[key] = val
if solution_time is not None:
arglist[sv.SOLUTIONTIME] = float(solution_time)
if strand_id is not None:
arglist[sv.STRANDID] = int(strand_id)
if parent_zone is not None:
arglist[sv.PARENTZONE] = parent_zone.index + 1
if face_neighbor_mode is not None:
arglist[sv.FACENEIGHBORMODE] = FaceNeighborMode(
face_neighbor_mode)
if index is not None:
arglist[sv.ZONE] = index + 1
if sections is not None:
num_elems, cell_shapes, grid_orders, basis_funcs = \
[], [], [], []
for sec in sections:
num_elems.append(int(sec[0]))
cell_shapes.append(FECellShape(sec[1]))
if len(sec) > 2:
grid_orders.append(int(sec[2]))
else:
grid_orders.append(1)
if len(sec) > 3:
basis_funcs.append(FECellBasisFunction(sec[3]))
else:
basis_funcs.append(FECellBasisFunction.Lagrangian)
if __debug__:
for bf in basis_funcs:
if bf != FECellBasisFunction.Lagrangian:
msg = str(bf) + ' is not yet supported.'
raise NotImplementedError(msg)
arglist[sv.NUMSECTIONS] = len(sections)
arglist[sv.NUMELEMSPERSECTION] = (ctypes.c_int64 * len(num_elems))(*num_elems)
arglist[sv.CELLSHAPEPERSECTION] = cell_shapes
arglist[sv.GRIDORDERPERSECTION] = (ctypes.c_int32 * len(grid_orders))(*grid_orders)
#arglist[sv.BASISFUNCSPERSECTION] = basis_funcs
arglist[sv.JMAX] = sum(num_elems)
if __debug__:
shp = '({})'.format(','.join(str(s) for s in shape))
msg = 'new dataset shape: ' + shp
for k, v in arglist.items():
msg += '\n {} = {}'.format(k, v)
log.debug(msg)
if not _tecutil.DataSetAddZoneX(arglist):
raise TecplotSystemError()
new_zone = dataset.zone(new_zone_index)
session.zone_added(new_zone)
return new_zone
[docs]
def add_ordered_zone(self, name, shape, **kwargs):
"""Add a single ordered `Zone <data_access>` to this `Dataset <tecplot.data.Dataset>`.
Parameters:
name (`str`): Name of the new `Zone <data_access>`. This
does not have to be unique.
shape (`int` or `list` of `integers <int>`): Specifies
the length and dimension **(i, j, k)** of the new
`Zone <data_access>`. A 1D `Zone <data_access>` is assumed if a
single `int` is given.
**kwargs: These arguments are passed to `Dataset.add_zone`.
.. seealso:: `Dataset.add_zone`
Keyword arguments are passed to the parent zone creation method
`Dataset.add_zone`.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
This example creates a 10x10x10 ordered zone of double-precision
floating-point numbers::
>>> from tecplot.constant import FieldDataType
>>> my_zone = dataset.add_zone('My Zone', (10, 10, 10),
... dtypes=FieldDataType.Double)
Here is a full example:
.. code-block:: python
:emphasize-lines: 12,17,22
import numpy as np
import tecplot as tp
from tecplot.constant import PlotType, Color
# Generate data
x = np.linspace(-4, 4, 100)
# Setup Tecplot dataset
dataset = tp.active_frame().create_dataset('Data', ['x', 'y'])
# Create a zone
zone = dataset.add_ordered_zone('sin(x)', len(x))
zone.values('x')[:] = x
zone.values('y')[:] = np.sin(x)
# Create another zone
zone = dataset.add_ordered_zone('cos(x)', len(x))
zone.values('x')[:] = x
zone.values('y')[:] = np.cos(x)
# And one more zone
zone = dataset.add_ordered_zone('tan(x)', len(x))
zone.values('x')[:] = x
zone.values('y')[:] = np.tan(x)
# Set plot type to XYLine
plot = tp.active_frame().plot(PlotType.XYLine)
plot.activate()
# Show all linemaps and make the lines a bit thicker
for lmap in plot.linemaps():
lmap.show = True
lmap.line.line_thickness = 0.6
plot.legend.show = True
tp.export.save_png('add_ordered_zones.png', 600, supersample=3)
.. figure:: /_static/images/add_ordered_zones.png
:width: 300px
:figwidth: 300px
"""
return self.add_zone(ZoneType.Ordered, name, shape, **kwargs)
[docs]
def add_fe_zone(self, zone_type, name, num_points, num_elements, **kwargs):
r"""Add a single finite-element `Zone <data_access>` to this `Dataset <tecplot.data.Dataset>`.
Parameters:
zone_type (`ZoneType`): The type of `Zone <data_access>` to be
created. Possible values are: `FETriangle`, `FEQuad`,
`FETetra`, `FEBrick` and `FELineSeg`.
name (`str`): Name of the new `Zone <data_access>`. This
does not have to be unique.
num_points (`int`): Number of points (nodes) in this
zone.
num_elements (`int`): Number of elements in this zone.
The nodemap will have the shape (num_points, num_elements).
**kwargs: These arguments are passed to `Dataset.add_zone`.
.. seealso:: `Dataset.add_zone`
Keyword arguments are passed to the parent zone creation method
`Dataset.add_zone`.
.. warning:: **Setting connectivity in connected mode.**
When connected to a running instance of Tecplot 360 using the
TecUtil Server, care must be taken to ensure that the GUI does not
try to render the data between the creation of the zone and the
setting of the connectivity, through the `Facemap` or `Nodemap`
objects. This can be achieved by setting the plot type of the
frame(s) holding on to the dataset to `PlotType.Sketch` before
creating the zone and only going to `PlotType.Cartesian3D` after
the connectivity is set. Tecplot 360 may get into a bad state,
corrupting loaded data, if it attempts to render (especially
polytope) data without connectivity.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
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`)
============== ============== ========================
For more details, see the "working with datasets" examples shipped with
PyTecplot in the Tecplot 360 distribution.
"""
assert zone_type in [ZoneType.FETriangle, ZoneType.FEQuad,
ZoneType.FETetra, ZoneType.FEBrick,
ZoneType.FELineSeg]
return self.add_zone(zone_type, name, (num_points, num_elements),
**kwargs)
[docs]
def add_fe_mixed_zone(self, name, num_points, sections, **kwargs):
"""Add a finite-element `Zone <data_access>` consisting of one or
more blocks of uniform cell-type (sections).
Parameters:
name (`str`): Name of the new `Zone <data_access>`. This does not
have to be unique.
num_points (`int`): Number of points (nodes) in this zone.
sections (`list` or `tuples <tuple>`): A list of the properties of
the sections in the form: ``(num_elements, cell_shape,
grid_order, basis_function)``. The **grid_order** and
**basis_func** items may be omitted and will default to **1**
(linear) and `FECellBasisFunction.Lagrangian` respectively.
**kwargs: These arguments are passed to `Dataset.add_zone`.
.. seealso:: `Dataset.add_zone`
Keyword arguments are passed to the parent zone creation method
`Dataset.add_zone`.
.. warning:: **Setting connectivity in connected mode.**
When connected to a running instance of Tecplot 360 using the
TecUtil Server, care must be taken to ensure that the GUI does not
try to render the data between the creation of the zone and the
setting of the connectivity, through the `Facemap` or `Nodemap`
objects. This can be achieved by setting the plot type of the
frame(s) holding on to the dataset to `PlotType.Sketch` before
creating the zone and only going to `PlotType.Cartesian3D` after
the connectivity is set. Tecplot 360 may get into a bad state,
corrupting loaded data, if it attempts to render (especially
polytope) data without connectivity.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
For more details, see the "working with datasets" examples shipped with
PyTecplot in the Tecplot 360 distribution.
"""
return self.add_zone(ZoneType.FEMixed, name, num_points,
sections=sections, **kwargs)
[docs]
def add_poly_zone(self, zone_type, name, num_points, num_elements,
num_faces, **kwargs):
"""Add a single polygonal `Zone <data_access>` to this `Dataset <tecplot.data.Dataset>`.
Parameters:
zone_type (`ZoneType`): The type of `Zone <data_access>` to be
created. Possible values are: `FEPolyhedron` and `FEPolygon`.
name (`str`): Name of the new `Zone <data_access>`. This
does not have to be unique.
num_points (`int`): Number of points in this zone.
num_elements (`int`): Number of elements in this zone.
num_faces (`int`): Number of faces in this zone.
**kwargs: These arguments are passed to `Dataset.add_zone`.
.. seealso:: `Dataset.add_zone`
Keyword arguments are passed to the parent zone creation method
`Dataset.add_zone`.
.. warning:: **Setting connectivity in connected mode.**
When connected to a running instance of Tecplot 360 using the
TecUtil Server, care must be taken to ensure that the GUI does not
try to render the data between the creation of the zone and the
setting of the connectivity, through the `Facemap` or `Nodemap`
objects. This can be achieved by setting the plot type of the
frame(s) holding on to the dataset to `PlotType.Sketch` before
creating the zone and only going to `PlotType.Cartesian3D` after
the connectivity is set. Tecplot 360 may get into a bad state,
corrupting loaded data, if it attempts to render (especially
polytope) data without connectivity.
.. note:: **Performance considerations for data manipulations.**
When performing many data-manipulation operations including adding
zones, adding variables, modifying field data or connectivity, and
especially in connected mode, it is recommended to do this all with
the `tecplot.session.suspend()`. This will prevent the Tecplot
engine from trying to "keep up" with the changes. Tecplot will be
notified of all changes made upon exit of this context. This may
result in significant performance gains for long operations.
.. note:: The **num_faces** is the number of *unique faces*.
The number of unique faces, given an element map can be obtained
using the following function for polygon data::
def num_unique_faces(elementmap):
return len(set( tuple(sorted([e[i], e[(i+1)%len(e)]]))
for e in elementmap for i in range(len(e)) ))
This function creates a unique set of node pairs (edges around
the polygons) and counts them. For polyhedron data, the following
can be used::
def num_unique_faces(elementmap):
return len(set( tuple(sorted(f)) for e in elementmap
for f in e ))
which merely counts the number of unique faces defined in the
element map.
For more details, see the "working with datasets" examples shipped with
PyTecplot in the Tecplot 360 distribution.
"""
assert zone_type in [ZoneType.FEPolyhedron, ZoneType.FEPolygon]
return self.add_zone(zone_type, name, (num_points, num_elements,
num_faces), **kwargs)
[docs]
@lock()
def delete_variables(self, *variables):
"""Remove `Variables <Variable>` from this `Dataset <tecplot.data.Dataset>`.
Parameters:
*variables (`Variable` or index `int`): Variables to
remove from this dataset.
.. code-block:: python
:emphasize-lines: 3
>>> print(dataset.variable_names)
['X','Y','Z']
>>> dataset.delete_variables(dataset.variable('Z'))
>>> print(dataset.variable_names)
['X','Y']
.. Warning::
Deleting `Variables <Variable>` invalidates iterators referencing
them in the containing `Dataset <tecplot.data.Dataset>` such as those obtained from
`Dataset.variables()`. It is recommended to create a list of the
`Variables <Variable>` you want to delete and to pass that into a
single call to `Dataset.delete_variables()`
Notes:
Multiple `Variables <Variable>` can be deleted at once, though the
last `Variable` can not be deleted. The following example deletes
all but the first `Variable` in the `Dataset <tecplot.data.Dataset>` (usually ``X``)::
>>> # Try to delete all variables:
>>> dataset.delete_variables(dataset.variables())
>>> # Dataset requires at least one variable to
>>> # exist, so it leaves the first one:
>>> print(dataset.variable_names)
['X']
"""
variables = flatten_args(*variables)
with self.frame.activated():
with IndexSet(*variables) as vlist:
_tecutil.DataSetDeleteVar(vlist)
[docs]
@lock()
def delete_zones(self, *zones):
"""Remove `Zones <data_access>` from this `Dataset <tecplot.data.Dataset>`.
Parameters:
*zones (`Zones <data_access>` or index `integers <int>`): Zones to
remove from this dataset.
.. code-block:: python
:emphasize-lines: 3
>>> print(dataset.zone_names)
['Zone 1', 'Zone 2']
>>> dataset.delete_zones(dataset.zone('Zone 2'))
>>> print(dataset.zone_names)
['Zone 1']
.. Warning::
Deleting `Zones <data_access>` invalidates iterators referencing
them in the containing `Dataset <tecplot.data.Dataset>` such as those obtained from
`Dataset.zones()`. It is recommended to create a list of the `Zones
<data_access>` you want to delete and to pass that into a single
call to `Dataset.delete_zones()`
Notes:
Multiple `Zones <data_access>` can be deleted at once, though the
last `Zone <data_access>` can not be deleted. The following example
deletes all but the first `Zone <data_access>` in the `Dataset <tecplot.data.Dataset>`::
>>> dataset.delete_zones(dataset.zones())
"""
zones = flatten_args(*zones)
with self.frame.activated():
with IndexSet(*zones) as zlist:
_tecutil.DataSetDeleteZone(zlist)
@property
def num_solution_times(self):
"""`int` (read-only): Number of solution times in the dataset.
This property is read-only. Solution times are grouped according to the
current solution time clustering settings (see
`Dataset.solution_time_clustering`). Example usage::
>>> print(dataset.num_solution_times)
10
.. versionadded:: 2017.3
Solution time manipulation requires Tecplot 360 2017 R3 or later.
"""
res = _tecutil.SolutionTimeGetNumTimeStepsByDataSetID(self.uid)
success, value = res
if not success:
raise TecplotSystemError()
return value
@property
def solution_times(self):
"""`list` of `floats <float>`: Solution times in the dataset.
This property is read-only. Solution times are grouped according to the
current solution time clustering settings (see
`Dataset.solution_time_clustering`). Example usage::
>>> print(dataset.solution_times)
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
.. versionadded:: 2017.3
Solution time manipulation requires Tecplot 360 2017 R3 or later.
"""
res = _tecutil.SolutionTimeGetSolutionTimesByDataSetID(self.uid)
success, ntimes, times = res
if not success:
raise TecplotSystemError()
ret = list(times[:ntimes])
if not _tecutil_connector.connected:
_tecutil.ArrayDealloc(times)
return ret
[docs]
@lock()
def branch_variables(self, zones, variables, copy_data=True):
"""Breaks data sharing between zones.
Parameters:
zones (`list` of `Zones <data_access>`): Zones to be branched.
variables (`list` of `Variables <Variable>`): Variables to be
branched.
copy_data (`bool`, optional): Allocate space for the branched
values and copy the data. If `False`, the new variables will
be passive. (default: `True`)
.. seealso:: `Dataset.share_variables()`
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. Example usage::
>>> z = dataset.zone('My Zone')
>>> zcopy = z.copy(share_variables=True)
>>> print([zn.index for zn in z.values(0).shared_zones])
[0,1]
>>> dataset.branch_variables(zcopy,dataset.variable(0))
>>> print([zn.index for zn in z.values(0).shared_zones])
[]
>>> print([zn.index for zn in z.values(1).shared_zones])
[0,1]
"""
if not isinstance(zones, Iterable):
zones = [zones]
if not isinstance(variables, Iterable):
variables = [variables]
for var in variables:
varidx = getattr(var, 'index', self.variable(var).index)
for zone in zones:
zoneidx = getattr(zone, 'index', self.zone(zone).index)
if not _tecutil.DataValueBranchShared(zoneidx + 1, varidx + 1,
copy_data):
raise TecplotSystemError()
[docs]
@lock()
def share_variables(self, source_zone, destination_zones, variables):
"""Share field data between zones.
This method links the underlying data `arrays <Array>` of the
destination `zones <data_access>` to the data of the source `zone
<data_access>`. Modifying the array data of one zone will affect all
others in this group.
Parameters:
source_zone (`Zone <data_access>`): Zone which provides data to be
shared.
destination_zones (`list` of `Zones <data_access>`): Zones
where data will be overwritten.
variables (`list` of `Variables <Variable>`): Variables to be
shared.
.. seealso:: `Dataset.branch_variables()`
Example usage::
>>> z = dataset.zone('My Zone')
>>> zcopy = z.copy(share_variables=False)
>>> print([zn.index for zn in z.values(0).shared_zones])
[]
>>> dataset.share_variables(zcopy,[z],[dataset.variable(0)])
>>> print([zn.index for zn in z.values(0).shared_zones])
[0,1]
>>> print([zn.index for zn in z.values(1).shared_zones])
[]
"""
if not isinstance(destination_zones, Iterable):
destination_zones = [destination_zones]
if not isinstance(variables, Iterable):
variables = [variables]
for var in variables:
varidx = getattr(var, 'index', self.variable(var).index)
for zone in destination_zones:
zoneidx = getattr(zone, 'index', self.zone(zone).index)
source_zoneidx = getattr(source_zone, 'index',
self.zone(source_zone).index)
if not _tecutil.DataValueIsSharingOk(source_zoneidx+1,
zoneidx+1, varidx+1):
raise TecplotSystemError()
_tecutil.DataValueShare(source_zoneidx+1, zoneidx+1, varidx+1)
[docs]
@lock()
def branch_connectivity(self, zones):
"""Breaks connectivity sharing between zones.
Parameters:
zones (`list` of `Zones <data_access>`): Zones to be branched.
.. seealso:: `Dataset.share_connectivity()`
Example usage::
>>> z = dataset.zone('My Zone')
>>> zcopy = z.copy()
>>> print([zn.index for zn in z.shared_connectivity])
[0,1]
>>> dataset.branch_connectivity(zcopy)
>>> print([zn.index for zn in z.shared_connectivity])
[]
"""
if not isinstance(zones, Iterable):
zones = [zones]
for zone in zones:
try:
zoneidx = getattr(zone, 'index')
except:
zoneidx = self.zone(zone).index
if not _tecutil.DataConnectBranchShared(zoneidx + 1):
raise TecplotSystemError()
[docs]
@lock()
def share_connectivity(self, source_zone, destination_zones):
"""Share connectivity between zones.
This method links the connectivity (`nodemap` or `facemap`) of the
destination `zones <data_access>` to the connectivity of the source
zone. Modifying the connectivity of one zone will affect all others in
this group.
Parameters:
source_zone (`Zone <data_access>`): Zone which provides data to be
shared.
destination_zones (`list` of `Zones <data_access>`): Zones where
connectivity list will be overwritten.
.. seealso:: `Dataset.branch_connectivity()`
Example usage::
>>> z = dataset.zone('My Zone')
>>> zcopy = z.copy()
>>> print([zn.index for zn in z.shared_connectivity])
[0,1]
>>> dataset.branch_connectivity(zcopy)
>>> print([zn.index for zn in z.shared_connectivity])
[]
>>> dataset.share_connectivity(z,zcopy)
>>> print([zn.index for zn in z.shared_connectivity])
[0,1]
"""
if not isinstance(destination_zones, Iterable):
destination_zones = [destination_zones]
def _index(obj):
i = getattr(obj, 'index', None)
if i is None:
i = self.zone(obj).index
return i
for zone in destination_zones:
idst = _index(zone)
isrc = _index(source_zone)
if not _tecutil.DataConnectIsSharingOk(isrc + 1, idst + 1):
raise TecplotSystemError()
_tecutil.DataConnectShare(isrc + 1, idst + 1)
@property
@lock()
def dataset(frame):
"""`Dataset <tecplot.data.Dataset>` attached to this `Frame <layout.Frame>`.
Returns:
`Dataset <tecplot.data.Dataset>`: The object holding onto the data associated with this
`Frame <layout.Frame>`.
If no `Dataset <tecplot.data.Dataset>` has been created for this `Frame <layout.Frame>`, a new one is created
and returned::
>>> dataset = frame.dataset
"""
if not frame.has_dataset:
frame.create_dataset(frame.name + ' Dataset')
dataset_uid = _tecutil.FrameGetDataSetUniqueIDByFrameID(frame.uid)
return Dataset(dataset_uid, frame)
@property
def has_dataset(frame):
"""`bool`: Checks to see if the `Frame <layout.Frame>` as an attached `Dataset <tecplot.data.Dataset>`
Example usage::
>>> if not frame.has_dataset:
... dataset = frame.create_dataset('Dataset', ['x','y','z','p'])
"""
return _tecutil.DataSetIsAvailableForFrame(frame.uid)
layout.Frame.dataset = dataset
layout.Frame.has_dataset = has_dataset
