Data

Dataset access and manipulation.

A Dataset consists of a matrix of Zones and Variables. Each Zone <data_access>-Variable pair corresponds to a data object which can always be treated as a 1D array, but which may be interpreted as 2D or 3D in the case of ijk-ordered data. In general, the Zone defines the size, shape and connectivity of the data while the Variable defines the underlying data type and whether the data is nodal or cell-centered.

Warning

Zero-based Indexing

It is important to know that all indexing in PyTecplot scripts are zero-based. This is a departure from the macro language which is one-based. This is to keep with the expectations when working in the python language. However, PyTecplot does not modify strings that are passed to the Tecplot Engine. This means that one-based indexing should be used when running macro commands from python or when using execute_equation().

Loading Data

tecplot.data.load_tecplot(filenames, frame=None, append=True, reset_style=None, initial_plot_first_zone_only=None, initial_plot_type=None, zones=None, variables=None, collapse=None, skip=None, assign_strand_ids=True, add_zones_to_existing_strands=None, include_text=None, include_geom=None, include_custom_labels=None, include_data=None)[source]

Read a tecplot data file.

Parameters:
  • filenames (string or list of strings) – Files to be read.
  • frame (Frame, optional) – The Frame to attach the resulting Dataset. If None, the currently active Frame is used and the zones are appended by default.
  • append (boolean, optional) – Append the data to the existing Dataset. If False, the existing data attached to the Frame is deleted and replaced. (default: True)
  • reset_style (boolean, optional) – Reset the style for destination Frame, if False, the Frame‘s current style is preserved. (default: True)
  • initial_plot_first_zone_only (boolean, optional) – Informs the Tecplot Engine that after the data is loaded it only needs to activate the first enabled Zone for the initial plot. This option is particularly useful if you have many Zones and want to get the data into the Tecplot Engine and the first Zone drawn as fast as possible. The inactive Zones can always be activated when needed. (default: False)
  • initial_plot_type (PlotType, optional) – Forces a specific type of plot upon loading of the data. Only used if resetstyle is True. To have Tecplot 360 EX determine the most appropriate plot type for the data, use PlotType.Automatic. Possible values are: PlotType.Automatic (default), Cartesian3D, Cartesian2D, XYLine, PlotType.Sketch, PolarLine.
  • zones (set of integers, optional) – Set of Zones to load. Use None to load all zones. (default: None)
  • variables (set of strings or integers, optional) – Set of Variables to load. Use None to load all variables. (default: None)
  • collapse (boolean, optional) – Reindex Zones and Variables if any are disabled. (default: False)
  • skip – (3-tuple of integers, optional) The ijk-skip. A value of (1,1,1) loads every data point in the (i,j,k) directions. A value of (2,2,2) loads every other data point and so forth. This only applies to ordered data. (default: (1,1,1))
  • assign_strand_ids (boolean, optional) – Assign strand ID’s to zones that have a strand ID of -1. (default: True)
  • add_zones_to_existing_strands (boolean, optional) – Add the Zones to matching strands, if they exist. Otherwise, if the new data specifies strands, new ones will be created beginning after the last strand in the Dataset. (default: False)
  • include_text (boolean, optional) – Load any text, geometries, or custom labels (default: True)
  • include_geom (boolean, optional) – Load geometries. (default: True)
  • include_custom_labels (boolean, optional) – (default: True)
  • include_data (boolean, optional) – Load data. Set this to False if you only want annotations such as text or geometries. (default: True)
Returns:

Dataset – The Dataset holding the loaded data.

Raises:
tecplot.data.load_cgns(filenames, frame=None, append=True, reset_style=None, initial_plot_first_zone_only=None, initial_plot_type=None, zones=None, variables=None, load_convergence_history=None, combine_fe_sections=None, average_to_nodes=None, uniform_grid=None, assign_strand_ids=None, add_zones_to_existing_strands=None, include_boundary_conditions=None)[source]

Read CGNS data files.

Parameters:
  • filenames (string or list of strings) – CGNS data files to be read. Note: Relative paths are considered to be from the running python script’s current working directory which can be obtained via os.getcwd().
  • frame (Frame, optional) – The Frame to attach the resulting Dataset. If None, the currently active Frame is used and the zones are appended by default.
  • append (boolean, optional) – Append the data to the existing Dataset. If False, the existing data attached to the Frame is deleted and replaced. (default: True)
  • reset_style (boolean, optional) – Reset the style for destination Frame, if False, the Frame‘s current style is preserved. (default: True)
  • initial_plot_first_zone_only (boolean, optional) – Informs the Tecplot Engine that after the data is loaded it only needs to activate the first enabled Zone for the initial plot. This option is particularly useful if you have many Zones and want to get the data into the Tecplot Engine and the first Zone drawn as fast as possible. The inactive Zones can always be activated when needed. (default: False)
  • initial_plot_type (PlotType, optional) – Forces a specific type of plot upon loading of the data. Only used if resetstyle is True. To have Tecplot 360 EX determine the most appropriate plot type for the data, use PlotType.Automatic. Possible values are: PlotType.Automatic (default), Cartesian3D, Cartesian2D, XYLine, PlotType.Sketch, PolarLine.
  • zones (list of integers, optional) – List of zone indexes to load starting from zero. None implies loading all zones. (default: None)
  • variables (list of integers, optional) – List of variable indexes, beyond the first coordinate variables, to load starting from zero. None implies loading all variables. The grid will always be loaded and an index of zero indicates the first non-coordinate variable. (default: None)
  • load_convergence_history (boolean, optional) – Load the global convergence history rather than any grid or solution data. (default: False)
  • combine_fe_sections (boolean, optional) – Combine all finite-element sections with the zone cell-dimension into one zone. (default: False)
  • average_to_nodes (string, optional) – Average cell-centered data to grid nodes using the specified method. (Options: None, “Arithmetic”, “Laplacian”)
  • uniform_grid (boolean, optional) – Indicates the grid structure is the same for all time steps. (default: True)
  • assign_strand_ids (boolean, optional) – Assign strand ID’s to zones that have a strand ID of -1. (default: True)
  • add_zones_to_existing_strands (boolean, optional) – Add the Zones to matching strands, if they exist. Otherwise, if the new data specifies strands, new ones will be created beginning after the last strand in the Dataset. (default: False)
  • include_boundary_conditions (boolean, optional) – Load the boundary conditions along with the data. (default: False)
Returns:

Dataset – The Dataset holding the loaded data.

Raises:
tecplot.data.load_fluent(case_filenames=None, data_filenames=None, frame=None, append=True, reset_style=None, initial_plot_first_zone_only=None, initial_plot_type=None, zones=None, variables=None, all_poly_zones=None, average_to_nodes=None, time_interval=None, assign_strand_ids=True, add_zones_to_existing_strands=None, include_particle_data=None)[source]

Read Fluent data files.

Parameters:
  • case_filenames (string or list of strings, optional) – Case (.cas) files to be read.
  • data_filenames (string or list of strings, optional) – Data (.dat, .xml etc.) files to be read.
  • frame (Frame, optional) – The Frame to attach the resulting Dataset. If None, the currently active Frame is used and the zones are appended by default.
  • append (boolean, optional) – Append the data to the existing Dataset. If False, the existing data attached to the Frame is deleted and replaced. (default: True)
  • reset_style (boolean, optional) – Reset the style for destination Frame, if False, the Frame‘s current style is preserved. (default: True)
  • initial_plot_first_zone_only (boolean, optional) – Informs the Tecplot Engine that after the data is loaded it only needs to activate the first enabled Zone for the initial plot. This option is particularly useful if you have many Zones and want to get the data into the Tecplot Engine and the first Zone drawn as fast as possible. The inactive Zones can always be activated when needed. (default: False)
  • initial_plot_type (PlotType, optional) – Forces a specific type of plot upon loading of the data. Only used if resetstyle is True. To have Tecplot 360 EX determine the most appropriate plot type for the data, use PlotType.Automatic. Possible values are: PlotType.Automatic (default), Cartesian3D, Cartesian2D, XYLine, PlotType.Sketch, PolarLine.
  • zones (string or list of integers, optional) – List of zone indexes (zero-based) to load or string specifying the type of zones to load. Possible values are: “CellsAndBoundaries”, “CellsOnly” and “BoundariesOnly”. Specifying one of these options is mutually exclusive with the variables option. (default: “CellsAndBoundaries”)
  • variables (list of strings, optional) – List of variable names to load. None implies loading all variables. (default: None)
  • all_poly_zones (boolean, optional) – Converts all zones to Tecplot polytope (polyhedral or polygonal) zones. (default: False)
  • average_to_nodes (string, optional) – Average cell-centered data to grid nodes using the specified method. (Options: None, “Arithmetic”, “Laplacian”)
  • time_interval (float, optional) – Use a constant time interval between each .dat file. If None, the flow-data parameter of each solution .dat file is used. (default: None)
  • assign_strand_ids (boolean, optional) –

    Assign strand ID’s to zones that have a strand ID of -1. (default: True)

    Note

    assign_strand_ids only applies if you have also provided a time_interval, otherwise it will be ignored.

  • add_zones_to_existing_strands (boolean, optional) – Add the Zones to matching strands, if they exist. Otherwise, if the new data specifies strands, new ones will be created beginning after the last strand in the Dataset. (default: False)
  • include_particle_data (boolean, optional) – Load particle data from the .dat files. If loading particle data from an XML file, the XML file should be included in the data_filenames list. (default: False)
Returns:

Dataset – The Dataset holding the loaded data.

Raises:

Notes

The zones option takes either a list of zone indexes to be imported or one of “CellsAndBoundaries”, “CellsOnly” or “BoundariesOnly” to indicate the type of zones the user wants to load, however these options are mutually exclusive with the variables option:

>>> import tecplot
>>> dataset = tecplot.data.load_fluent(['one.cas', 'two.cas'],
...     data_filenames=['one.dat', 'two.dat'],
...     variables = ['Pressure','Velocity'],
...     zones = [0,1,3])
tecplot.data.load_plot3d(grid_filenames=None, solution_filenames=None, function_filenames=None, name_filename=None, frame=None, append=True, reset_style=None, initial_plot_first_zone_only=None, initial_plot_type=None, data_structure=None, is_multi_grid=None, style=None, ascii_is_double=None, ascii_has_blanking=None, uniform_grid=None, assign_strand_ids=True, add_zones_to_existing_strands=True, append_function_variables=None, include_boundaries=True)[source]

Read Plot3D data files.

Parameters:
  • grid_filenames (string or list of strings, optional) – One or more grid file names to be read.
  • solution_filenames (string or list of strings, optional) – One or more solution data file names to be read.
  • function_filenames (string or list of strings, optional) – One or more function file names.
  • name_filename (string, optional) – Path to the name file.
  • frame (Frame, optional) – The Frame to attach the resulting Dataset. If None, the currently active Frame is used and the zones are appended by default.
  • append (boolean, optional) – Append the data to the existing Dataset. If False, the existing data attached to the Frame is deleted and replaced. (default: True)
  • reset_style (boolean, optional) – Reset the style for destination Frame, if False, the Frame‘s current style is preserved. (default: True)
  • initial_plot_first_zone_only (boolean, optional) – Informs the Tecplot Engine that after the data is loaded it only needs to activate the first enabled Zone for the initial plot. This option is particularly useful if you have many Zones and want to get the data into the Tecplot Engine and the first Zone drawn as fast as possible. The inactive Zones can always be activated when needed. (default: False)
  • initial_plot_type (PlotType, optional) – Forces a specific type of plot upon loading of the data. Only used if resetstyle is True. To have Tecplot 360 EX determine the most appropriate plot type for the data, use PlotType.Automatic. Possible values are: PlotType.Automatic (default), Cartesian3D, Cartesian2D, XYLine, PlotType.Sketch, PolarLine.
  • data_structure (string, optional) – Specifies the data structure and overrides the automatic detection. Options are: 1D, 2D, 3DP, 3DW, UNSTRUCTURED. Setting this requires is_multi_grid and style to be set as well.
  • is_multi_grid (boolean, optional) – Sets data as multi-grid and overrides the automatic data structure detection. Setting this requires data_structure and style to be set as well.
  • style (boolean, optional) – Specifies the data style and overrides the automatic data structure detection. Options are: PLOT3DCLASSIC, PLOT3DFUNCTION, OVERFLOW. Setting this requires data_structure and is_multi_grid to be set as well.
  • ascii_is_double (boolean, optional) – Indicates that floating-point numbers found in the text data files should be store with 64-bit precision. (default: False)
  • ascii_has_blanking (boolean, optional) – Indicates that the text data files contain blanking. (default: False)
  • uniform_grid (boolean, optional) – Indicates the grid structure is the same for all time steps. (default: True)
  • assign_strand_ids (boolean, optional) – Assign strand ID’s to zones that have a strand ID of -1. (default: True)
  • add_zones_to_existing_strands (boolean, optional) – Add the Zones to matching strands, if they exist. Otherwise, if the new data specifies strands, new ones will be created beginning after the last strand in the Dataset. (default: True)
  • append_function_variables (boolean, optional) – Append variables in function files to those found in solution files. (default: False)
  • include_boundaries (boolean, optional) – Loads boundary zones found in the ”.g.fvbnd” file located in the same directory as the grid file, if available. (default: True)
Returns:

Dataset – The Dataset holding the loaded data.

Raises:

Note

Data structure is automatically detected by default.

The options data_structure, is_multi_grid and style must be supplied together or not at all. When all of these are None, the data structure is automatically detected.

The variables from the function files can be appended to the dataset upon loading:

>>> import tecplot as tp
>>> dataset = tp.data.load_plot3d(
...     grid_filenames = 'data.g',
...     solution_filenames = ['t0.q', 't1.q'],
...     function_filenames = ['t0.f', 't1.f'],
...     append_function_variables = True)

Saving Data

tecplot.data.save_tecplot_binary(filename, frame=None, dataset=None, zones=None, variables=None, version=None, include_text=None, include_geom=None, include_data=None, include_data_share_linkage=None, include_autogen_face_neighbors=None, associate_with_layout=None)[source]

Write tecplot binary data file.

Parameters:
  • filename (string) – Name of the data file to write.
  • frame (Frame, optional) – The Frame which holds the Dataset to be written. If this option and dataset are both None, the currently active Frame is used. (default: None)
  • dataset (Dataset, optional) – The Dataset to write out. If this and frame are both None, the Dataset of the currently active Frame is used. (default: None)
  • zones (list of Zones, optional) – Zones to write out. If None, all Zones will be saved.
  • variables (list of Variables, optional) – Variables to write out. If None, all Variables will be saved.
  • include_text (boolean, optional) – Write out all text, geometries and custom labels. (default: True)
  • include_geom (boolean, optional) – Write out all geometries. (default: True)
  • include_data (boolean, optional) – Write out the data. Set this to False if you only want to write out annotations. (default: True)
  • include_data_share_linkage (boolean, optional) – Conserve space and write the variable and connectivity linkage wherever possible. If False, this will write out all data, losing the connectivity sharing linkage for future dataset reads of the file. (default: True)
  • include_autogen_face_neighbors (boolean, optional) – Save the face neighbor connectivity. This may produce very large data files. (default: False)
  • associate_with_layout (boolean, optional) – Associate this data file with the current layout. Set to False to write the datafile without modifying Tecplot’s current data file to layout association. If version is set to anything other than BinaryFileVersion.Current, this association is not possible, and this parameter will be ignored. (default: True)
  • version (BinaryFileVersion, optional) – Specifies the file version to write. Note that some data may be excluded from the file if it cannot be supported in the specified version. Possible values are: Tecplot2006, Tecplot2008, Tecplot2009 and BinaryFileVersion.Current. (default: BinaryFileVersion.Current)
Returns:

Dataset – The Dataset read from when saving.

Raises:

Example

In this example, we load sample data and save the data in Tecplot binary format.

from os import path
import tecplot
examples_directory = tecplot.session.tecplot_examples_directory()
infile = path.join(examples_directory,
                   'OneraM6wing', 'OneraM6_SU2_RANS.plt')
dataset = tecplot.data.load_tecplot(infile)
variables_to_save = [dataset.variable(V)
                     for V in ('x', 'y', 'z', 'Pressure_Coefficient')]

zone_to_save = dataset.zone('WingSurface')
# write data out to a binary file
tecplot.data.save_tecplot_binary('wing.plt', dataset=dataset,
                                variables=variables_to_save,
                                zones=[zone_to_save])
tecplot.data.save_tecplot_ascii(filename, frame=None, dataset=None, zones=None, variables=None, include_text=None, precision=None, include_geom=None, include_data=None, include_data_share_linkage=None, include_autogen_face_neighbors=None, use_point_format=None)[source]

Write tecplot ASCII data file.

Parameters:
  • filename (string) – Name of the data file to write.
  • frame (Frame, optional) – The Frame which holds the Dataset to be written. If this option and dataset are both None, the currently active Frame is used. (default: None)
  • dataset (Dataset, optional) – The Dataset to write out. If this and frame are both None, the Dataset of the currently active Frame is used. (default: None)
  • include_text (boolean, optional) – Write out all text, geometries and custom labels. (default: True)
  • include_geom (boolean, optional) – Write out all geometries. (default: True)
  • include_data (boolean, optional) – Write out the data. Set this to False if you only want to write out annotations. (default: True)
  • include_data_share_linkage (boolean, optional) – Conserve space and write the variable and connectivity linkage wherever possible. If False, this will write out all data, losing the connectivity sharing linkage for future dataset reads of the file. (default: True)
  • include_autogen_face_neighbors (boolean, optional) – Save the face neighbor connectivity. This may produce very large data files. (default: False)
  • use_point_format (boolean, optional) – Write out point format, otherwise use block format. (default: False)
  • zones (list of Zones, optional) – Zones to write out. Use None to write out all Zones. (default: None)
  • variables (list of Variables, optional) – Variables to write out. Use None to write out all Variables. (default: None)
  • precision (integer, optional) – ASCII decimal precision to use. (default: 12)
Returns:

Dataset – The Dataset read from when saving.

Raises:

Example

In this example, we load sample data and save the data in Tecplot ASCII format.

from os import path
import tecplot
examples_directory = tecplot.session.tecplot_examples_directory()
infile = path.join(examples_directory,
                   'OneraM6wing', 'OneraM6_SU2_RANS.plt')
dataset = tecplot.data.load_tecplot(infile)
variables_to_save = [dataset.variable(V)
                     for V in ('x','y','z','Pressure_Coefficient')]

zone_to_save = dataset.zone('WingSurface')
# write data out to an ascii file
tecplot.data.save_tecplot_ascii('wing.dat', dataset=dataset,
                                variables=variables_to_save,
                                zones=[zone_to_save])

Data Queries

tecplot.data.query.probe_at_position(x, y, z=None, nearest=False, starting_cell=None, starting_zone=None, zones=None, dataset=None, frame=None)[source]

Returns field values at a point in space.

Note

The position is taken according the axis assignments of the Frame which may be any of the associated variables in the Dataset and not necessarily (X, Y, Z). See: Cartesian3DFieldAxis.variable.

Parameters:
  • x,y,z (float, z is optional) – position to probe for field values.
  • nearest (bool) – Returns the values at the nearest node to the given position.
  • starting_cell (3-tuple of integers, optional) – The (i,j,k)-index of the cell to start looking for the given position. This must be used with starting_zone.
  • starting_zone (Zone, required only when starting_cell is given) – The first zone to start searching.
  • zones (list of Zones, optional) – Limits the search to the given zones. None implies searching all zones. (default: None)
  • dataset (Dataset, optional) – The Dataset to probe. (defaults to the active Dataset.)
  • frame (Frame, optional) – The Frame which determines the spatial variable assignment (X,Y,Z). (defaults to the active Frame.)
Returns:

namedtuple

(data, cell, zone):

data (list of floats)

The values of each variable in the dataset at the given position.

cell (3-tuple of integers)

(i,j,k) of the cell containing the given position.

zone (Zone)

Zone containing the given position

Data Operations

tecplot.data.operate.Range(min, max, step)

Limit the data altered by the execute_equation function.

The Range specification of I,J,K range indices for execute_equation follow these rules:

  • All indices start with 0 and go to some maximum index m.
  • Negative values represent the indexes starting with the maximum at -1 and continuing back to the beginning of the range.
  • A step of None, 0 and 1 are all equivalent and mean that no elements are skipped.
  • A negative step indicates a skip less than the maximum.

Example

Add one to variable ‘X’ for a zone ‘Rectangular’ for data points in I Range 1 to max, skipping every three points:

>>> execute_equation('{X} = {X}+1', i_range=Range(min=1, max=None, step=3),
...                  zone_set='Rectangular')
tecplot.data.operate.execute_equation(equation, zones=None, i_range=None, j_range=None, k_range=None, value_location=None, variable_data_type=None, ignore_divide_by_zero=None)[source]

The execute_equation function operates on a data set within the Tecplot Engine using FORTRAN-like equations.

Parameters:
  • equation (string) –

    String containing the equation. Multiple equations can be processed by separating each equation with a newline. See Section 20 - 1 “Data Alteration through Equations” in the Tecplot User’s Manual for more information on using equations. Iterable container of Zone objects to operate on. May be a list, set, tuple, or any iterable container. If None, the equation will be applied to all zones.

    Note

    In the equation string, variable names should be enclosed in curly braces. For example, ‘{X} = {X} + 1’

  • zones – (Iterable container of Zone objects, optional): Iterable container of Zone objects to operate on. May be a list, set, tuple, or any iterable container. If None, the equation will be applied to all zones.
  • i_range (Range, optional) – Tuple of integers for I: (min, max, step). If None, then the equation will operate on the entire range. Not used for finite element nodal data.
  • j_range (Range, optional) – Tuple of integers for J: (min, max, step). If None, then the equation will operate on the entire range. Not used for finite element nodal data.
  • k_range (Range, optional) – Tuple of integers for K: (min, max, step). If None, then the equation will operate on the entire range. Not used for finite element nodal data.
  • value_location (ValueLocation, optional) – Variable ValueLocation for the variable on the left hand side. This is used only if this variable is being created for the first time. If None, Tecplot Engine will choose the location for you.
  • variable_data_type (FieldDataType, optional) – Data type for the variable on the left hand side. This is used only if this variable is being created for the first time. If None, Tecplot Engine will choose the type for you.
  • ignore_divide_by_zero (bool, optional) – bool value which instructs Tecplot Engine to ignore divide by zero errors. The result is clamped such that 0/0 is clamped to zero and (+/-N)/0 where N != 0 clamps to +/-maximum value for the given type.
Raises:

TecplotSystemError

Warning

Zero-based Indexing

It is important to know that all indexing in PyTecplot scripts are zero-based. This is a departure from the macro language which is one-based. This is to keep with the expectations when working in the python language. However, PyTecplot does not modify strings that are passed to the Tecplot Engine. This means that one-based indexing should be used when running macro commands from python or when using execute_equation().

Add one to variable ‘X’ for zones ‘Rectangular’ and ‘Circular’ for every data point: >>> import tecplot >>> dataset = tecplot.active_frame().dataset >>> execute_equation(‘{X} = {X} + 1’, zones=[dataset.zone(‘Rectangular’), >>> dataset.zone(‘Circular’)])

Create a new, double precision variable called DIST:

>>> execute_equation('{DIST} = SQRT({X}**2 + {Y}**2)',
...                  variable_data_type=FieldDataType.double)

Set a variable called P to zero along the boundary of an IJ-ordered zone:

>>> execute_equation('{P} = 0', i_range=Range(step=-1))
>>> execute_equation('{P} = 0', j_range=Range(step=-1))

Data Access

Dataset

class tecplot.data.Dataset(uid, frame)[source]

A table of Arrays identified by Zone and Variable.

This is the primary data container within the Tecplot Engine. A Dataset can be shared among several Frames, though any particular Dataset object will have a handle to at least one of them. Any modification of a shared Dataset will be reflected in all Frames that use it.

Though a Dataset is usually attached to a Frame and the plot style associated with that, it can be thought of as independent from any style or plotting representation. Each Dataset consists of a list of Variables which are used by one or more of a list of Zones. The Variable determines the data type while the Zone determines the layout such as shape and ordered vs unordered.

The actual data are found at the intersection of a Zone 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 is the object returned by most data-loading operations in PyTecplot:

>>> dataset = tecplot.data.load_tecplot('my_data.plt')

Under Dataset, there are a number methods to create and delete Zones and variables.

Attributes

VariablesNamedTuple A collections.namedtuple object using variable names.
num_variables Number of Variables in this Dataset.
num_zones Number of Zones in this Dataset.
title Title of this Dataset.

Methods

add_fe_zone(zone_type, name, num_points, ...) Add a single finite-element Zone to this Dataset.
add_ordered_zone(name, shape, **kwargs) Add a single ordered Zone to this Dataset.
add_poly_zone(zone_type, name, num_points, ...) Add a single polygonal Zone to this Dataset.
add_variable(name[, dtypes, locations]) Add a single Variable to the active Dataset.
add_zone(zone_type, name, shape[, dtypes, ...]) Add a single Zone to this Dataset.
copy_zones(*zones) Copies Zones within this Dataset.
delete_variables(*variables) Remove Variables from this Dataset.
delete_zones(*zones) Remove Zones from this Dataset.
variable(pattern) Returns the Variable by index or string pattern.
variables([pattern]) Yields all Variables matching a pattern.
zone(pattern) Returns Zone by index or string pattern.
zones([pattern]) Yields all Zones matching a pattern.
Dataset.VariablesNamedTuple

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:

>>> from os import path
>>> import tecplot as tp
>>> examples_dir = tp.session.tecplot_examples_directory()
>>> datafile = path.join(examples_dir,'3D_Volume','jetflow.plt')
>>> dataset = tp.data.load_tecplot(datafile)
>>> result = tp.data.query.probe_at_position(0,0.1,0.3)
>>> data = dataset.VariablesNamedTuple(*result.data)
>>> msg = '(RHO, E) = ({:.2f}, {:.2f})'
>>> print(msg.format(data.RHO, data.E))
(RHO, E) = (1.17, 252930.37)
Dataset.add_fe_zone(zone_type, name, num_points, num_elements, **kwargs)[source]

Add a single finite-element Zone to this Dataset.

Parameters:

See also

Dataset.add_zone

Keyword arguments are passed to the parent zone creation method Dataset.add_zone.

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 (\(N\)):

Zone Type Points/Element Nodemap Shape
FELineSeg 2 (\(N\), \(2 N\))
FETriangle 3 (\(N\), \(3 N\))
FEQuad 4 (\(N\), \(4 N\))
FETetra 4 (\(N\), \(4 N\))
FEBrick 8 (\(N\), \(8 N\))
Dataset.add_ordered_zone(name, shape, **kwargs)[source]

Add a single ordered Zone to this Dataset.

Parameters:
  • name (string) – Name of the new Zone. This does not have to be unique.
  • shape (integer or list of integers) – Specifies the length and dimension (i, j, k) of the new Zone. A 1D Zone is assumed if a single int is given.
  • **kwargs – These arguments are passed to Dataset.add_zone.

See also

Dataset.add_zone

Keyword arguments are passed to the parent zone creation method Dataset.add_zone.

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),
...                            dtype=FieldDataType.Double)

Here is a full example:

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)
../_images/add_ordered_zones.png
Dataset.add_poly_zone(zone_type, name, num_points, num_elements, num_faces, **kwargs)[source]

Add a single polygonal Zone to this Dataset.

Parameters:
  • zone_type (ZoneType) – The type of Zone to be created. Possible values are: FEPolyhedron and FEPolygon.
  • name (string) – Name of the new Zone. This does not have to be unique.
  • num_points (integer) – Number of points in this zone.
  • num_elements (integer) – Number of elements in this zone.
  • num_faces (integer) – Number of faces in this zone.
  • **kwargs – These arguments are passed to Dataset.add_zone.

See also

Dataset.add_zone

Keyword arguments are passed to the parent zone creation method Dataset.add_zone.

Dataset.add_variable(name, dtypes=None, locations=None)[source]

Add a single Variable to the active Dataset.

Parameters:
Returns:

Variable

The added Variable will be available for use in each Zone of the dataset. This method should be used in conjunction with other data creation methods such as Dataset.add_zone:

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)
../_images/add_variables.png
Dataset.add_zone(zone_type, name, shape, dtypes=None, locations=None, parent_zone=None, solution_time=None, strand_id=None, index=None)[source]

Add a single Zone to this Dataset.

Parameters:

Returns: Zone

The added Zone will be able to use all Variables 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.copy_zones(*zones)[source]

Copies Zones within this Dataset.

Parameters:zones (Zone, optional) – Specific Zones to copy. All zones will be copied if none are supplied.

Returns: list of the newly created Zones.

Example usage:

>>> new_zones = dataset.copy_zones()
Dataset.delete_variables(*variables)[source]

Remove Variables from this Dataset.

Parameters:*variables (Variable or index integer) – Variables to remove from this dataset.
>>> print([v.name for v in dataset.variables()])
['X','Y','Z']
>>> dataset.delete_variables(dataset.variable('Z'))
>>> print([v.name for v in dataset.variables()])
['X','Y']

Notes

Multiple Variables can be deleted at once, though the last Variable can not be deleted. This command deletes all but the first Variable in the 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([v.name for v in dataset.variables()])
['X']
Dataset.delete_zones(*zones)[source]

Remove Zones from this Dataset.

Parameters:*zones (Zones or index integers) – Zones to remove from this dataset.
>>> print([z.name for z in dataset.zones()])
['Zone 1', 'Zone 2']
>>> dataset.delete_zones(dataset.zone('Zone 2'))
>>> print([z.name for z in dataset.zones()])
['Zone 1']

Notes

Multiple Zones can be deleted at once, though the at least one Zone must remain. This command deletes all but the first Zone in the Dataset:

>>> dataset.delete_zones(dataset.zones())
Dataset.num_variables

Number of Variables in this Dataset.

Type:integer

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)
Dataset.num_zones

Number of Zones in this Dataset.

Type:integer

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)
Dataset.title

Title of this Dataset.

Type:string

Example usage:

>>> dataset.title = 'My Data'
Dataset.variable(pattern)[source]

Returns the Variable by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.
Raises:TecplotIndexError

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
Dataset.variables(pattern=None)[source]

Yields all Variables matching a pattern.

Parameters:pattern (string pattern, optional) – glob-style pattern used to match variable names or None which will return all variables. (default: None)

Example usage:

>>> for variable in dataset.variables('A*'):
...     array = variable.values('My Zone')
Dataset.zone(pattern)[source]

Returns Zone by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.
Returns:OrderedZone, ClassicFEZone or PolyFEZone depending on the zone type.
Raises:TecplotIndexError

The Zone.name attribute is used to match the pattern to the desired Zone 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
Dataset.zones(pattern=None)[source]

Yields all Zones matching a pattern.

Parameters:pattern (string pattern, optional) – glob-style pattern used to match zone names or None which will return all zones. (default: None)
Yields:OrderedZone, ClassicFEZone or PolyFEZone depending on the zone type.

Example usage:

>>> for zone in dataset.zones('A*'):
...     x_array = zone.variable('X')

Variable

class tecplot.data.Variable(uid, dataset)[source]

Key value for a data array within a Dataset.

Variables can be identified (uniquely) by the index within their parent Dataset or (non-uniquely) by name. In general, a Zone must also be selected to access the underlying data array. This object is used by several style controlling classes such as contours and vectors. The following example sets the contour variable for the first contour group to the first variable named ‘S’:

>>> plot.contour(0).variable = dataset.variable('S')

Attributes

index Zero-based position within the parent Dataset.
name Returns or sets the name.
num_zones Number of Zones in the parent Dataset.

Methods

values(pattern) Returns Array by index or string pattern.
Variable.index

Zero-based position within the parent Dataset.

Type:Index

Example usage:

>>> plot.contour(0).variable_index = dataset.variable('S').index
Variable.name

Returns or sets the name.

Type:string

Example usage:

>>> print(dataset.variable(0).name)
X
Variable.num_zones

Number of Zones in the parent Dataset.

Type:integer

Example usage, looping over all zones by index:

>>> for zindex in range(dataset.num_zones):
...     zone = dataset.zone(zindex)
Variable.values(pattern)[source]

Returns Array by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.

The Zone.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']
>>> x = ds.variable('x')
>>> rectzone = x.values('Rectangular zone')
>>> rectzone == x.values(0)
True

Zones

OrderedZone

class tecplot.data.OrderedZone(uid, dataset)[source]

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 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'))

Attributes

dimensions Nodal dimensions along (i, j, k).
index Zero-based position within the parent Dataset.
name The name of the zone.
num_elements Number of cells in this zone.
num_points Total number of nodes within this zone.
num_points_per_element Points per cell for ordered zones.
num_variables Number of Variables in the parent Dataset.
rank Number of dimensions of the data array.
solution_time The solution time for this zone.
strand The strand ID number.
zone_type The ZoneType indicating structure of the data contained.

Methods

copy() Duplicate this Zone in the parent Dataset.
values(pattern) Returns an Array by index or string pattern.
OrderedZone.copy()

Duplicate this Zone in the parent Dataset.

The name is copied as well but can be set after duplication:

>>> 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
OrderedZone.dimensions

Nodal dimensions along (i, j, k).

Returns:tuple of integers(i, j, k) for ordered data.

Example usage:

>>> print(zone.dimensions)
(128, 128, 128)
OrderedZone.index

Zero-based position within the parent Dataset.

Type:Index

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)
OrderedZone.name

The name of the zone.

Type:string

Example usage:

>>> dataset.zone(0).name = 'Zone 0'
OrderedZone.num_elements

Number of cells in this zone.

Type:integer

Example usage:

>>> zone = dataset.zone('My Zone')
>>> print(zone.dimensions)
(128, 128, 128)
>>> print(zone.num_elements)
2048383
OrderedZone.num_points

Total number of nodes within this zone.

Type:integer

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
OrderedZone.num_points_per_element

Points per cell for ordered zones.

Type:integer

For ordered zones, this is \(2^{d}\) where \(d\) is the number of dimensions:

>>> zone = dataset.zone('My Zone')
>>> print(zone.dimensions)
(10, 10, 1)
>>> print(zone.rank)
2
>>> print(zone.num_points_per_element)
4
OrderedZone.num_variables

Number of Variables in the parent Dataset.

Type:integer

Example usage, iterating over all variables by index:

>>> for i in range(dataset.num_variables):
...     variable = dataset.variable(i)
OrderedZone.rank

Number of dimensions of the data array.

Type:integer

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
OrderedZone.solution_time

The solution time for this zone.

Type:float

Example usage:

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

The strand ID number.

Type:integer

Example usage:

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

Returns an Array by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.

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
OrderedZone.zone_type

The ZoneType indicating structure of the data contained.

Type:ZoneType

The specific type of zone this object represents:

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

ClassicFEZone

class tecplot.data.ClassicFEZone(uid, dataset)[source]

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 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'))

Attributes

index Zero-based position within the parent Dataset.
name The name of the zone.
nodemap The connectivity Nodemap for this classic finite-element zone.
num_elements Number of cells in this finite-element zone.
num_points Total number of nodes within this zone.
num_points_per_element Points per element for classic finite-element zones.
num_variables Number of Variables in the parent Dataset.
rank Number of dimensions of the data array.
solution_time The solution time for this zone.
strand The strand ID number.
zone_type The ZoneType indicating structure of the data contained.

Methods

copy() Duplicate this Zone in the parent Dataset.
values(pattern) Returns an Array by index or string pattern.
ClassicFEZone.copy()

Duplicate this Zone in the parent Dataset.

The name is copied as well but can be set after duplication:

>>> 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
ClassicFEZone.index

Zero-based position within the parent Dataset.

Type:Index

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)
ClassicFEZone.name

The name of the zone.

Type:string

Example usage:

>>> dataset.zone(0).name = 'Zone 0'
ClassicFEZone.nodemap

The connectivity Nodemap for this classic finite-element zone.

Type:Nodemap

Example usage:

>>> zone = dataset.zone(0)
>>> print(zone.nodemap.num_points_per_element)
4
ClassicFEZone.num_elements

Number of cells in this finite-element zone.

Type:integer

Example usage:

>>> print(dataset.zone('My Zone').num_elements)
1048576
ClassicFEZone.num_points

Total number of nodes within this zone.

Type:integer

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

>>> print(dataset.zone('My Zone').num_points)
2048
ClassicFEZone.num_points_per_element

Points per element for classic finite-element zones.

Type:integer

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 (\(N\)):

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

Example usage:

>>> zone = dataset.zone('My Zone')
>>> print(zone.zone_type)
ZoneType.FETriangle
>>> print(zone.num_points_per_element)
3
ClassicFEZone.num_variables

Number of Variables in the parent Dataset.

Type:integer

Example usage, iterating over all variables by index:

>>> for i in range(dataset.num_variables):
...     variable = dataset.variable(i)
ClassicFEZone.rank

Number of dimensions of the data array.

Type:integer

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
ClassicFEZone.solution_time

The solution time for this zone.

Type:float

Example usage:

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

The strand ID number.

Type:integer

Example usage:

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

Returns an Array by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.

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
ClassicFEZone.zone_type

The ZoneType indicating structure of the data contained.

Type:ZoneType

The specific type of zone this object represents:

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

PolyFEZone

class tecplot.data.PolyFEZone(uid, dataset)[source]

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 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'))

Attributes

face_neighbors The face neighbor list for this polygonal finite-element zone.
facemap The connectivity Facemap for this polygonal finite-element zone.
index Zero-based position within the parent Dataset.
name The name of the zone.
num_elements Number of cells in this finite-element zone.
num_faces Number of faces in this finite-element zone.
num_points Total number of nodes within this zone.
num_variables Number of Variables in the parent Dataset.
rank Number of dimensions of the data array.
solution_time The solution time for this zone.
strand The strand ID number.
zone_type The ZoneType indicating structure of the data contained.

Methods

copy() Duplicate this Zone in the parent Dataset.
create_facemap(face_nodes, boundary_faces, ...) Allocate space for the facemap.
values(pattern) Returns an Array by index or string pattern.
PolyFEZone.copy()

Duplicate this Zone in the parent Dataset.

The name is copied as well but can be set after duplication:

>>> 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
PolyFEZone.create_facemap(face_nodes, boundary_faces, boundary_connections)[source]

Allocate space for the facemap.

Parameters:
  • face_nodes (int) – Total number of nodes for all faces. This is not the number of unique nodes but the total number. For example if a facemap defines two triangle polygons that share a common face, faces would be 5 and face_nodes would be 6, not 4.
  • boundary_faces (int) – Total number of boundary faces.
  • boundary_connections (int) – Total number of boundary face elements or boundary face element/zone pairs.

If the zone does not already have space allocated for a facemap, then this must be called before accessing it:

>>> zone.create_facemap(400, 25, 50)
>>> facemap = zone.facemap
PolyFEZone.face_neighbors

The face neighbor list for this polygonal finite-element zone.

Type:FaceNeighbors

Example usage:

>>> zone = dataset.zone(0)
>>> print(zone.face_neighbors.mode)
FaceNeighborMode.LocalOneToMany
PolyFEZone.facemap

The connectivity Facemap for this polygonal finite-element zone.

Type:Facemap

Example usage:

>>> zone = dataset.zone(0)
>>> print(zone.facemap.num_faces)
4500
PolyFEZone.index

Zero-based position within the parent Dataset.

Type:Index

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)
PolyFEZone.name

The name of the zone.

Type:string

Example usage:

>>> dataset.zone(0).name = 'Zone 0'
PolyFEZone.num_elements

Number of cells in this finite-element zone.

Type:integer

Example usage:

>>> print(dataset.zone('My Zone').num_elements)
1048576
PolyFEZone.num_faces

Number of faces in this finite-element zone.

Type:integer

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

>>> print(dataset.zone('My Zone').num_faces)
1048576
PolyFEZone.num_points

Total number of nodes within this zone.

Type:integer

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

>>> print(dataset.zone('My Zone').num_points)
2048
PolyFEZone.num_variables

Number of Variables in the parent Dataset.

Type:integer

Example usage, iterating over all variables by index:

>>> for i in range(dataset.num_variables):
...     variable = dataset.variable(i)
PolyFEZone.rank

Number of dimensions of the data array.

Type:integer

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
PolyFEZone.solution_time

The solution time for this zone.

Type:float

Example usage:

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

The strand ID number.

Type:integer

Example usage:

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

Returns an Array by index or string pattern.

Parameters:pattern (integer or string) – Zero-based index or glob-style pattern in which case, the first match is returned.

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
PolyFEZone.zone_type

The ZoneType indicating structure of the data contained.

Type:ZoneType

The specific type of zone this object represents:

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

Array

class tecplot.data.Array(zone, variable)[source]

Low-level accessor for underlying data within a Dataset.

Note

The data manipulation context referred to below is currently being developed and should show up in an up-coming revision.

This object exposes a list-like interface to the underlying data array. Using it, values can be directly queried and modified. After any modification to the data, the Tecplot Engine will have to be notified of the change. This notification will happen automatically in most cases, but can be turned off using the data manipulation context for a significant performance increase on large datasets.

Accessing values within an Array is done through the standard [] syntax:

>>> print(array[3])
3.1415

The numbers passed are interpreted just like Python’s built-in slice object:

>>> # print the values at indices: 5, 7, 9
>>> print(array[5:10:2])
[1.0, 1.0, 1.0]

Elements within an array can be manipulated in-place with the assignment operator:

>>> array[3] = 5.0
>>> print(array[3])
5.0

Element-by-element access is not guaranteed to be performant and users should avoid writing loops over indices in Python. Instead, whole arrays should be used. This will effectively push the loop down to the underlying native library and will be much faster in virtually all cases.

Consider this array of 10k elements:

>>> import tecplot as tp
>>> ds = tp.active_frame().create_dataset('Dataset', ['x'])
>>> zn = ds.add_ordered_zone('Zone', 10000)
>>> array = zn.values('x')

The following loop, which takes the sine of all values in the array will require several Python function calls per element which is a tremendous overhead:

>>> import math
>>> for i in range(len(ar)):
...     ar[i] = math.sin(ar[i])

An immediate improvement on this can be made by looping over the elements in Python only when reading the values, but assigning them using the whole array. This will be several times faster for even modest arrays:

>>> ar[:] = [math.sin(x) for x in ar]

But there is still a large performance penalty for looping over elements directly in Python and PyTecplot supports two solutions for large arrays: tecplot.data.operate.execute_equation and tecplot.extension.numpy. Please refer to these for details. Continuing with the example above, we could accomplish the same thing with either of the following using execute_equation (assuming the array is identified by the first zone, first variable):

>>> from tecplot.data.operate import execute_equation
>>> execute_equaion('V1 = SIN(V1)', zones=[dataset.zone(0)])

or by using the numpy library:

>>> import numpy as np
>>> ar[:] = np.sin(ar[:])

In both of these cases, the calculation of the sine and loop over elements is pushed to the low level library and is much faster.

Attributes

c_type ctypes compatible data type of this array.
data_type FieldDataType indicating the underlying value type of this array.
location The location of the data points with respect to the elements.
max Upper bound of the values stored in this array.
min Lower bound of the values stored in this array.
minmax Limits of the values stored in this array.
shape (i, j, k) shape for this array.
size The number of values in this array.

Methods

as_numpy_array(arr)
copy([offset, size]) Copy the whole or part of the array into a ctypes array.
Array.as_numpy_array(arr)
Array.c_type

ctypes compatible data type of this array.

This is the ctypes equivalent of Array.data_type and will return one of the following:

and can be used to create a ctypes array to store a copy of the data:

import tecplot as tp
frame = tp.active_frame()
dataset = frame.create_dataset('Dataset', ['x'])
dataset.add_ordered_zone('Zone', (3,3,3))
x = dataset.zone('Zone').values('x')
# allocate array using Python's ctypes
x_array = (x.c_type * x.size)()
# copy values from Dataset into ctypes array
x_array[:] = x[:]
Array.copy(offset=0, size=None)[source]

Copy the whole or part of the array into a ctypes array.

Parameters:
  • offset (integer, optional) – Zero-based offset for starting index to copy. (default: 0)
  • size (integer, optional) – Number of values to copy into the resulting array. A value of None will copy to the end of the array. (default: None)

Here we will copy out chunks of the data, do some operation and set the values back into the dataset:

>>> import tecplot as tp
>>> tp.new_layout()
>>> frame = tp.active_frame()
>>> dataset = frame.create_dataset('Dataset', ['x'])
>>> dataset.add_ordered_zone('Zone', (2, 2, 2))
>>> x = dataset.zone('Zone').values('x')
>>> # loop over array copying out 4 values at a time
>>> for i, offset in enumerate(range(0, x.size, 4)):
...     x_array = x.copy(offset, 4)
...     x_array[:] = [i] * 4
...     x[offset:offset + 4] = x_array
>>> print(x[:])
[0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0]
Array.data_type

FieldDataType indicating the underlying value type of this array.

Type:FieldDataType

Example usage:

>>> print(dataset.zone('Zone').values('X').data_type)
FieldDataType.Float
Array.location

The location of the data points with respect to the elements.

Type:ValueLocation

Possible values are ValueLocation.CellCentered and ValueLocation.Nodal. Example usage:

>>> print(dataset.variable('X').zone(0).location)
ValueLocation.Nodal
Array.max

Upper bound of the values stored in this array.

Type:float

This always returns a float regardless of the underlying data type:

>>> print(dataset.zone('Zone').values('x').max)
10
Array.min

Lower bound of the values stored in this array.

Type:float

This always returns a float regardless of the underlying data type:

>>> print(dataset.zone('Zone').values('x').min)
0
Array.minmax

Limits of the values stored in this array.

Type:2-tuple of floats

This always returns floats regardless of the underlying data type:

>>> print(dataset.zone('Zone').values('x').minmax)
(0, 10)
Array.shape

(i, j, k) shape for this array.

Type:tuple of floats

This is defined by the parent zone and can be used to reshape arrays. The following example assumes 32-bit floating point array and copies the Tecplot-owned data into the numpy-owned array:

>>> import numpy as np
>>> data = dataset.zone('Zone').values('X')
>>> array = np.empty(data.shape, dtype=np.float32)
>>> arr_ptr = array.ctypes.data_as(POINTER(data.c_type))
>>> memmove(arr_ptr, data.copy(), sizeof(data.c_type) * data.size)

The data array presented is normally one-dimensional. For ordered data, you may wish to reshape the array indexing according to the dimensionality given by the shape attribute:

>>> import numpy as np
>>> import tecplot as tp
>>> frame = tp.active_frame()
>>> dataset = frame.create_dataset('Dataset', ['x'])
>>> zone = dataset.add_ordered_zone('Zone', shape=(3,3,3))
>>> x = np.array(zone.values('X')[:])
>>> print(x)
[ 0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.
  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.]
>>> x.shape = zone.values('X').shape
>>> print(x)
[[[ 0.  0.  0.]
  [ 0.  0.  0.]
  [ 0.  0.  0.]]

 [[ 0.  0.  0.]
  [ 0.  0.  0.]
  [ 0.  0.  0.]]

 [[ 0.  0.  0.]
  [ 0.  0.  0.]
  [ 0.  0.  0.]]]
Array.size

The number of values in this array.

Type:integer

Example showing size of ordered data:

>>> x = dataset.zone('Zone').values('X')
>>> print(x.shape)
(10, 10, 10)
>>> print(x.size)
1000

Nodemap

class tecplot.data.Nodemap(zone)[source]

Connectivity list definition and control.

Nodemap access in PyTecplot is a work in progress. While we provide some functionality, it sould be considered “beta” quality at best.

Attributes

c_type
num_points_per_element Points per element for classic finite-element zones.
shape

Methods

copy()
Nodemap.c_type
Nodemap.copy()[source]
Nodemap.num_points_per_element

Points per element for classic finite-element zones.

Type:integer

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 points specified (\(N\)):

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

Example usage:

>>> zone = dataset.zone('My Zone')
>>> print(zone.zone_type)
ZoneType.FETriangle
>>> print(zone.nodemap.num_points_per_element)
3
Nodemap.shape

Facemap

class tecplot.data.Facemap(zone)[source]

Connectivity list definition and control.

Facemap access in PyTecplot is a work in progress. While we provide some functionality, it sould be considered “beta” quality at best.

Attributes

element_c_type
node_c_type
num_faces

Methods

assign_mapping(facemap, elements)
Facemap.assign_mapping(facemap, elements)[source]
Facemap.element_c_type
Facemap.node_c_type
Facemap.num_faces

FaceNeighbors

class tecplot.data.FaceNeighbors(zone)[source]

Face neighbor definition and control.

Face neighbor access in PyTecplot is a work in progress. While we provide some functionality, it sould be considered “beta” quality at best.

Attributes

c_type
mode Face neighbor mode.

Methods

set_connection(element, face, neighbors[, ...]) Connect boundary of an element’s face to a neighboring face.
FaceNeighbors.c_type
FaceNeighbors.mode

Face neighbor mode.

Type:FaceNeighborMode
Possible values: FaceNeighborMode.LocalOneToOne,
FaceNeighborMode.LocalOneToMany, FaceNeighborMode.GlobalOneToOne, FaceNeighborMode.GlobalOneToMany.

Example usage:

>>> print(zone.face_neighbors.mode)
FaceNeighborMode.LocalOneToMany
FaceNeighbors.set_connection(element, face, neighbors, zones=None, obscure=False)[source]

Connect boundary of an element’s face to a neighboring face.

This sets the boundary connection face neighbors within an open face neighbor assignment sequence for the specified element and face.

Parameters:
  • element (int) – The element number (zero-based).
  • face (int) – The face number on the element (zero-based).
  • neighbors (list of integers) – List of zero-based indices of the neighboring faces.
  • zones (list of PolyFEZone objects, optional) – List of zones for global neighbors. This must be the same length as neighbors. Use None to indicate these are local neighbors. (default: None)
  • obscure (boolean, optional) – Indicates that the neighbors completely obscure the face. (default: False)

Auxiliary Data

AuxData

class tecplot.data.AuxData(frame)[source]

Methods

item(i) item by number
AuxData.item(i)[source]

item by number