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# Examples

- Hello World
- Loading Layouts
- Extracting Slices
- Numpy Integration
- Execute Equation
- Line Plots
- Creating Slices
- Creating Iso-surfaces
- Wing Surface Slices
- Mach Iso-surfaces
- Exception Handling
- Streamtraces
- Legend
- 3D View

## Hello World

A simple “Hello, World!” adds text to the active frame and exports the frame to an image file.

    import tecplot

    frame = tecplot.active_frame()
    frame.add_text('Hello, World!', position=(36, 50), size=34)
    tecplot.export.save_png('hello_world.png', 600, supersample=3)

## Loading Layouts

Layouts can be loaded with the `tecplot.load_layout()` method. This will accept both `lay` and `lpk` (packaged) files. The exported image interprets the image type by the extension you give it. See `tecplot.export.save_png()` for more details. Notice in this example, we turn on logging down to the `DEBUG` level which is extremely verbose. This is useful for debugging the connection between the script and Tecplot 360.

    import logging
    import os
    import sys

    logging.basicConfig(stream=sys.stdout, level=logging.INFO)

    import tecplot

    examples_dir = tecplot.session.tecplot_examples_directory()
    infile = os.path.join(examples_dir, '3D', 'JetSurface.lay')

    tecplot.load_layout(infile)
    tecplot.export.save_jpeg('jet_surface.jpeg', 600)

## Extracting Slices

This script produces two images: a 3D view of the wing and a simplified pressure coefficient plot half-way down the wing:

    import os
    import sys
    import logging

    logging.basicConfig(stream=sys.stdout, level=logging.INFO)

    import tecplot

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, 'OneraM6wing', 'OneraM6_SU2_RANS.plt')
    dataset = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    frame.plot_type = tecplot.constant.PlotType.Cartesian3D
    frame.plot().show_contour = True

    # export image of wing
    tecplot.export.save_png('wing.png', 600)

    # extract an arbitrary slice from the surface data on the wing
    extracted_slice = tecplot.data.extract.extract_slice(
        origin=(0, 0.25, 0),
        normal=(0, 1, 0),
        source=tecplot.constant.SliceSource.SurfaceZones,
        dataset=dataset)

    extracted_slice.name = 'Quarter-chord C_p'

    # get x from slice
    extracted_x = extracted_slice.values('x')

    # copy of data as a numpy array
    x = extracted_x.as_numpy_array()

    # normalize x
    xc = (x - x.min()) / (x.max() - x.min())
    extracted_x[:] = xc

    # switch plot type in current frame
    frame.plot_type = tecplot.constant.PlotType.XYLine
    plot = frame.plot()

    # clear plot
    plot.delete_linemaps()

    # create line plot from extracted zone data
    cp_linemap = plot.add_linemap(
        name=extracted_slice.name,
        zone=extracted_slice,
        x=dataset.variable('x'),
        y=dataset.variable('Pressure_Coefficient'))

    # integrate over the normalized extracted slice values
    # notice we have to convert zero-based index to one-based for CFDAnalyzer
    tecplot.macro.execute_extended_command('CFDAnalyzer4', '''
        Integrate
        VariableOption='Average'
        XOrigin=0 YOrigin=0
        ScalarVar={scalar_var}
        XVariable=1
    '''.format(scalar_var=dataset.variable('Pressure_Coefficient').index + 1))

    # get integral result from Frame's aux data
    total = float(frame.aux_data['CFDA.INTEGRATION_TOTAL'])

    # overlay result on plot in upper right corner
    frame.add_text('integration result: {:.5f}'.format(total), (60,90))

    # set style of linemap plot
    cp_linemap.line.color = tecplot.constant.Color.Blue
    cp_linemap.line.line_thickness = 0.8
    cp_linemap.y_axis.reverse = True

    # update axes limits to show data
    plot.view.fit()

    # export image of pressure coefficient as a function of x/c
    tecplot.export.save_png('wing_pressure_coefficient.png', 600, supersample=3)

## Numpy Integration

Note

Numpy, SciPy Required

This example requires both numpy and scipy installed. SciPy, in turn, requires a conforming linear algebra system such as OpenBLAS, LAPACK, ATLAS or MKL. It is recommended to use your operating system’s package manager to do this. Windows users and/or users that do not have root access to their machines might consider using Anaconda to setup a virtual environment where they can install python, numpy, scipy and all of its dependencies.

The spherical harmonic `(n,m) = (5,4)` is calculated at unit radius. The magnitude is then used to create a 3D shape. The plot-style is modified and the following image is exported and the layout is saved in “packaged format.”

    import logging as log
    import numpy as np
    from numpy import abs, pi, cos, sin
    from scipy import special

    log.basicConfig(level=log.INFO)

    import tecplot as tp
    from tecplot.session import set_style
    from tecplot.constant import ColorMapDistribution

    shape = (200, 300)

    log.info('creating spherical harmonic data')
    r = 0.3
    phi = np.linspace(0, pi, shape[0])
    theta = np.linspace(0, 2*pi, shape[1])

    ttheta, pphi = np.meshgrid(theta, phi, indexing='ij')

    xx = r * sin(pphi) * cos(ttheta)
    yy = r * sin(pphi) * sin(ttheta)
    zz = r * cos(pphi)

    n = 5
    m = 4

    ss = special.sph_harm(m, n, ttheta, pphi).real
    ss /= ss.max()

    log.info('creating tecplot dataset')
    ds = tp.active_frame().create_dataset('Data', ['x','y','z','s'])

    sphere_zone = ds.add_ordered_zone(
        'SphericalHarmonic({}, {}) Sphere'.format(m, n),
        shape)

    sphere_zone.values('x')[:] = xx.ravel()
    sphere_zone.values('y')[:] = yy.ravel()
    sphere_zone.values('z')[:] = zz.ravel()
    sphere_zone.values('s')[:] = ss.ravel()

    tp.session.zones_added(sphere_zone)

    log.info('creating shaped zone')
    shaped_zone = ds.add_ordered_zone(
        'SphericalHarmonic({}, {}) Shaped'.format(m, n),
        shape)

    shaped_zone.values('x')[:] = (abs(ss)*xx).ravel()
    shaped_zone.values('y')[:] = (abs(ss)*yy).ravel()
    shaped_zone.values('z')[:] = (abs(ss)*zz).ravel()
    shaped_zone.values('s')[:] = ss.ravel()

    log.info('state changed: zones added')
    tp.session.zones_added(shaped_zone)

    log.info('setting plot type to Cart3D')
    tp.active_frame().plot_type = tp.constant.PlotType.Cartesian3D
    plot = tp.active_frame().plot()

    '''
    The lines below are equivalent to the macro commands.

    Notice that PyTecplot indexes universally from zero where the
    macro indexes from one.

    $!FIELDLAYERS SHOWCONTOUR = YES
    $!FIELDLAYERS USETRANSLUCENCY = YES
    $!FIELDMAP [1]  EFFECTS { SURFACETRANSLUCENCY = 70 }
    $!FIELDMAP [2]  EFFECTS { SURFACETRANSLUCENCY = 30 }
    $!GLOBALCONTOUR 1  COLORMAPFILTER { COLORMAPDISTRIBUTION = CONTINUOUS }
    $!GLOBALCONTOUR 1  COLORMAPNAME = 'Sequential - Yellow/Green/Blue'
    '''
    plot.show_contour = True
    plot.use_translucency = True
    plot.fieldmap(sphere_zone).effects.surface_translucency = 70
    plot.fieldmap(shaped_zone).effects.surface_translucency = 30
    plot.contour(0).colormap_filter.distribution = ColorMapDistribution.Continuous
    plot.contour(0).colormap_name = 'Sequential - Yellow/Green/Blue'

    filename = 'spherical_harmonic_{}_{}'.format(m, n)

    for axis in plot.axes:
        axis.fit_range()

    log.info('saving image')
    tp.export.save_png(filename + '.png', 600, supersample=3)

    log.info('saving packaged layout file')
    tp.save_layout(filename + '.lpk', include_data=True)

    log.info('releasing license')

## Execute Equation

This example illustrates altering data through equations in two zones. For complete information on the Tecplot Engine “data alter” syntax, see Chapter 21, Data Operations, in the Tecplot 360 User’s Manual. This script outputs the original data followed by the same image where we’ve modified the scaling of `Nj` only on the wings.

    import os
    import tecplot

    examples_dir = tecplot.session.tecplot_examples_directory()
    infile = os.path.join(examples_dir, '3D', 'JetSurface.lay')

    # Load a stylized layout where the contour variable is set to 'Nj'
    tecplot.load_layout(infile)
    current_dataset = tecplot.active_frame().dataset

    # export original image
    tecplot.export.save_png('jet_surface_orig.png', 600)

    # alter variable 'Nj' for the the two wing zones in the dataset
    # In this simple example, just multiply it by 10.
    tecplot.data.operate.execute_equation('{Nj}={Nj}*10',
        zones=[current_dataset.zone('right wing'),
               current_dataset.zone('left wing')])

    # The contour color of the wings in the exported image will now be
    # red, since we have altered the 'Nj' variable by multiplying it by 10.
    tecplot.export.save_png('jet_surface_altered.png', 600)

## Line Plots

This example shows how to set the style for a plot of three lines. The y-axis label and legend labels are changed and the axes are adjusted to fit the data.

    from os import path
    import tecplot as tp
    from tecplot.constant import PlotType, Color, LinePattern, AxisTitleMode

    # load data from examples directory
    examples_dir = tp.session.tecplot_examples_directory()
    infile = path.join(examples_dir, 'XY', 'rainfall.plt')
    dataset = tp.data.load_tecplot(infile)

    # get handle to the active frame and set plot type to XY Line
    frame = tp.active_frame()
    frame.plot_type = PlotType.XYLine
    plot = frame.plot()

    # We will set the name, color and a few other properties
    # for the first three linemaps in the dataset.
    names = ['Seattle', 'Dallas', 'Miami']
    colors = [Color.Blue, Color.DeepRed, Color.Khaki]

    # loop over the linemaps, setting style for each
    for lmap,name,color in zip(plot.linemaps(),names,colors):
        lmap.show = True
        lmap.name = name # This will be used in the legend

        # Changing some line attributes
        line = lmap.line
        line.color = color
        line.line_thickness = 1
        line.line_pattern = LinePattern.LongDash
        line.pattern_length = 2

    # Set the y-axis label
    plot.axes.y_axis(0).title.title_mode = AxisTitleMode.UseText
    plot.axes.y_axis(0).title.text = 'Rainfall'

    # Turn on legend
    plot.legend.show = True

    # Adjust the axes limits to show all the data
    plot.view.fit()

    # save image to file
    tp.export.save_png('linemap.png', 600)

## Creating Slices

This example illustrates reading a dataset then creating and showing arbitrary slices of the dataset. A primary slice, start, end, and 3 intermediate slices are shown.

    from os import path
    import tecplot as tp
    from tecplot.constant import SliceSurface, ContourType

    examples_dir = tp.session.tecplot_examples_directory()
    datafile = path.join(examples_dir, '3D_Volume', 'ductflow.plt')
    dataset = tp.data.load_tecplot(datafile)

    plot = tp.active_frame().plot()
    plot.contour(0).variable = dataset.variable('U(M/S)')

    plot.show_slices = True
    slice_0 = plot.slice(0)

    slice_0.contour.show = True
    slice_0.contour.contour_type = ContourType.Overlay  # AKA "Both lines and flood"

    slice_0.effects.use_translucency = True
    slice_0.effects.surface_translucency = 30

    slice_0.show_primary_slice = False
    slice_0.show_start_and_end_slices = True
    slice_0.show_intermediate_slices = True
    slice_0.start_position = (-.21, .05, .025)
    slice_0.end_position = (1.342, .95, .475)
    slice_0.num_intermediate_slices = 2

    tp.export.save_png('slice_example.png', 600)

## Creating Iso-surfaces

This example illustrates reading a dataset, then creating and showing isosurfaces.

    from os import path

    import tecplot as tp
    from tecplot.constant import LightingEffect, IsoSurfaceSelection

    examples_dir = tp.session.tecplot_examples_directory()
    datafile = path.join(examples_dir, '3D_Volume', 'ductflow.plt')
    dataset = tp.data.load_tecplot(datafile)

    plot = tp.active_frame().plot()
    plot.contour(0).variable = dataset.variable('U(M/S)')

    plot.show_isosurfaces = True

    iso = plot.isosurface(0)

    iso.isosurface_selection = IsoSurfaceSelection.ThreeSpecificValues
    iso.isosurface_values = (135.674706817, 264.930212259, 394.185717702)

    iso.shade.use_lighting_effect = True
    iso.effects.lighting_effect = LightingEffect.Paneled
    iso.contour.show = True
    iso.effects.use_translucency = True
    iso.effects.surface_translucency = 50

    tp.export.save_png('isosurface_example.png', 600)

## Wing Surface Slices

This example illustrates reading a dataset and showing surface slices with colored mesh on the Onera M6 Wing. Seven surface slices are shown, colored by the distance along the Y axis.

    import tecplot
    from tecplot.constant import *
    import os
    import numpy as np

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, 'OneraM6wing', 'OneraM6_SU2_RANS.plt')
    dataset = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    plot = frame.plot()

    # Turn on only the periodic slices (start, end and intermeidate)
    # and set them to span the length of the wing
    plot.show_slices = True
    slices = plot.slice(0)
    slices.slice_source = SliceSource.SurfaceZones
    slices.orientation = SliceSurface.YPlanes
    slices.show_primary_slice = False
    slices.show_start_and_end_slices = True
    slices.show_intermediate_slices = True
    slices.num_intermediate_slices = 5
    slices.start_position = (0, 0.02, 0)
    slices.end_position = (0,1.19,0)

    # Setup First Contour Group to color by the distance along the Y axis (Span)
    cont = plot.contour(0)
    cont.variable = frame.dataset.variable('y')
    cont.levels.reset_levels(np.linspace(0,1.2,13))
    cont.legend.show = False

    # Color the Surface Slices by the contour, this must be done on the mesh
    slices.contour.show = False
    slices.mesh.show = True
    slices.mesh.color = cont
    slices.mesh.line_thickness = 0.6
    slices.edge.show = False

    # Turn translucency on globally
    plot.use_translucency = True

    tecplot.export.save_png("wing_slices.png",600)

## Mach Iso-surfaces

This example illustrates using contour group properties to define multiple Iso-surfaces. In this case, multiple Mach values are shown as Iso-surfaces.

    import tecplot
    from tecplot.constant import *
    import os

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, 'OneraM6wing', 'OneraM6_SU2_RANS.plt')
    ds = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    plot = frame.plot()

    # Set Isosurface to match Contour Levels of the first group.
    iso = plot.isosurface(0)
    iso.isosurface_selection = IsoSurfaceSelection.AllContourLevels
    cont = plot.contour(0)
    iso.definition_contour_group = cont
    cont.colormap_name = 'Magma'

    # Setup definition Isosurface layers
    cont.variable = ds.variable('Mach')
    cont.levels.reset_levels( [.95,1.0,1.1,1.4])
    print(list(cont.levels))

    # Turn on Translucency
    iso.effects.use_translucency = True
    iso.effects.surface_translucency = 80

    # Turn on Isosurfaces
    plot.show_isosurfaces = True
    iso.show = True

    cont.legend.show = False

    view = plot.view
    view.psi = 65.777
    view.theta = 166.415
    view.alpha = -1.05394
    view.position = (-23.92541680486183, 101.8931504712126, 47.04269529295333)
    view.width = 1.3844

    tecplot.export.save_png("wing_iso.png",width=600, supersample=4)

## Exception Handling

It is the policy of the PyTecplot Python module to raise exceptions on any failure. It is the user’s job to catch them or otherwise prevent them by ensuring the Tecplot Engine is properly setup to the task you ask of it. Aside from exceptions raised by the underlying Python core libraries, PyTecplot may raise a subclass of `TecplotError`, the most common being `TecplotRuntimeError`.

    import logging
    import os

    # turn on exceptionally verbose logging!!!
    logging.basicConfig(level=logging.DEBUG)

    import tecplot
    from tecplot.exception import *

    # Calling tecplot.session.acquire_license() is optional.
    # If you do not call it, it will be called automatically for you
    # the first time you call any |PyTecplot| API.
    #
    # acquire_license() may also be called manually. It will raise an exception
    # if Tecplot cannot be initialized. The most common reason that
    # Tecplot cannot be initialized is if a valid license is not found.
    # If you call start yourself, you can catch and recover from the
    # exception.
    #
    # Note that calling tecplot.session.stop() will release the license acquired
    # when calling tecplot.session.|PyTecplot|().
    #
    # Also note that once tecplot.session.stop() is called, |Tecplot Engine|
    # cannot be restarted again during the current python session.
    #
    try:
        tecplot.session.acquire_license()
        logging.info('License acquired, Tecplot Engine started.')
    except TecplotLicenseError:
        logging.exception('Missing or invalid license:')
    except TecplotError:
        logging.exception('Could not initialize pytecplot')
        exit(1)

    examples_dir = tecplot.session.tecplot_examples_directory()
    infile = os.path.join(examples_dir, '3D', 'spaceship.lpk')
    outfile = 'spaceship.png'

    try:
        logging.info('Opening layout file: ' + infile)
        tecplot.load_layout(infile)

        logging.info('Exporting Image: ' + outfile)
        tecplot.export.save_png(outfile, 600)

        logging.info('Finished, no errors')

    except IOError:
        logging.debug("I/O Error: Check disk space and permissions")
    except TecplotSystemError:
        logging.exception('Failed to export image: ' + outfile)
    finally:
        # tecplot.session.stop() may be called manually to shut down Tecplot and release
        # the license.
        # If tecplot.session.stop() is not called manually it will be called automatically
        # when the script exits.
        tecplot.session.stop()

    logging.info('Done')

## Streamtraces

Using the transient Vortex Shedding layout a rake of 2D streamtrace lines are added.

    import tecplot
    import os

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, '2D', 'VortexShedding.lpk')
    tecplot.load_layout(datafile)

    frame = tecplot.active_frame()
    frame.plot_type = tecplot.constant.PlotType.Cartesian2D
    plot = frame.plot()
    ds = frame.dataset

    plot.vector.u_variable = ds.variable('U(M/S)')
    plot.vector.v_variable = ds.variable('V(M/S)')

    strace = plot.streamtraces

    strace.add_rake([-0.002, 0.002],[-0.002, -0.002], tecplot.constant.Streamtrace.TwoDLine)
    strace.show_arrows = False
    strace.line_thickness = .4
    plot.show_streamtraces = True

    # Remove countour lines setup in LPK
    plot.fieldmap(0).contour.contour_type = tecplot.constant.ContourType.Flood

    # Delete textboxes setup for LPK
    for txt in frame.texts():
        frame.delete_text(txt)

    tecplot.export.save_png('streamtrace_2D.png', 600, supersample=4)

This example illustrates adding a rake of streamtraces.

    import os
    import tecplot
    from tecplot.constant import *
    from tecplot.plot import Cartesian3DFieldPlot

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, '3D_Volume', 'eddy.plt')
    dataset = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    frame.plot_type = tecplot.constant.PlotType.Cartesian3D

    plot = frame.plot()
    plot.fieldmap(0).surfaces.surfaces_to_plot = SurfacesToPlot.BoundaryFaces
    plot.show_mesh = True
    plot.show_shade = False

    plot.vector.u_variable_index = 4
    plot.vector.v_variable_index = 5
    plot.vector.w_variable_index = 6
    plot.show_streamtraces = True

    streamtrace = plot.streamtraces
    streamtrace.color = Color.Green

    streamtrace.show_paths = True
    streamtrace.show_arrows = True
    streamtrace.arrowhead_size = 3
    streamtrace.step_size = .25
    streamtrace.line_thickness = .4
    streamtrace.max_steps = 10

    # Streamtraces termination line:
    streamtrace.set_termination_line([(-25.521, 39.866),
                                      (-4.618, -11.180)])

    # Streamtraces will stop at the termination line when active
    streamtrace.termination_line.is_active = True

    # We can also show the termination line itself
    streamtrace.termination_line.show = True
    streamtrace.termination_line.color = Color.Red
    streamtrace.termination_line.line_thickness = 0.4
    streamtrace.termination_line.line_pattern = LinePattern.LongDash

    # Markers
    streamtrace.show_markers = True
    streamtrace.marker_color = Color.Blue
    streamtrace.marker_symbol_type = SymbolType.Geometry
    streamtrace.marker_symbol().shape = GeomShape.Diamond

    # Add surface line streamtraces
    streamtrace.add_rake(start_position=(45.49, 15.32, 59.1),
                         end_position=(48.89, 53.2, 47.6),
                         stream_type=Streamtrace.SurfaceLine)

    tecplot.export.save_png('streamtrace_line_example.png', 600)

This example illustrates adding ribbon streamtrace.

    import os
    import tecplot
    from tecplot.constant import *
    import numpy as np

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, '3D_Volume', 'ductflow.plt')
    dataset = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    frame.plot_type = tecplot.constant.PlotType.Cartesian3D

    plot = frame.plot()
    plot.contour(0).variable = dataset.variable('P(N/m2)')
    plot.contour(0).levels.reset_to_nice()
    plot.contour(0).legend.show = False

    plot.vector.u_variable = dataset.variable('U(M/S)')
    plot.vector.v_variable = dataset.variable('V(M/S)')
    plot.vector.w_variable = dataset.variable('W(M/S)')

    # Goal: create a grid of 12 stream trace ribbons on a slice
    x_slice_location = .79
    y_start = .077
    y_end = .914
    z_start = .052
    z_end = .415

    num_left_right_slices = 4  # Must be >= 2
    num_top_bottom_slices = 3  # Must be >= 2

    # Show and add a slice.
    plot.show_slices = True
    slice_0 = plot.slice(0)

    # Set the x position of the slice.
    slice_0.origin = [x_slice_location, 0, 0]

    slice_0.contour.show = True

    plot.show_streamtraces = True
    streamtraces = plot.streamtraces
    streamtraces.show_paths = True

    rod = streamtraces.rod_ribbon
    rod.width = .03
    rod.contour.show = True

    for y in np.linspace(y_start, y_end, num=num_left_right_slices):
        for z in np.linspace(z_start, z_end, num=num_top_bottom_slices):
            streamtraces.add([x_slice_location,y,z], Streamtrace.VolumeRibbon)

    tecplot.export.save_png('streamtrace_ribbon_example.png', 600)

## Legend

This example illustrates displaying an XY line legend and changing its attributes.

    import os

    import tecplot
    from tecplot.constant import *

    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, 'XY', 'rainfall.plt')
    dataset = tecplot.data.load_tecplot(datafile)

    frame = tecplot.active_frame()
    plot = frame.plot()
    frame.plot_type = tecplot.constant.PlotType.XYLine

    for i in range(3):
        plot.linemap(i).show = True
        plot.linemap(i).line.line_thickness = .4

    y_axis = plot.axes.y_axis(0)
    y_axis.title.title_mode = AxisTitleMode.UseText
    y_axis.title.text = 'Rainfall (in)'
    y_axis.fit_range_to_nice()

    legend = plot.legend
    legend.show = True
    legend.box.box_type = TextBox.Filled
    legend.box.color = Color.Purple
    legend.box.fill_color = Color.LightGrey
    legend.box.line_thickness = .4
    legend.box.margin = 5

    legend.anchor_alignment = AnchorAlignment.MiddleRight
    legend.row_spacing = 1.5
    legend.show_text = True
    legend.font.typeface = 'Arial'
    legend.font.italic = True

    legend.text_color = Color.Black
    legend.position = (90, 88)

    tecplot.export.save_png('legend_line.png', 600, supersample=4)

This example illustrates displaying a contour legend and changing its attributes.

    import os

    import numpy as np

    import tecplot
    from tecplot.constant import *

    # By loading a layout many style and view properties are set up already
    examples_dir = tecplot.session.tecplot_examples_directory()
    datafile = os.path.join(examples_dir, '3D', 'RainierElevation.lay')
    tecplot.load_layout(datafile)

    frame = tecplot.active_frame()
    plot = frame.plot()

    # Rename the elevation variable
    frame.dataset.variable('E').name = "Elevation (m)"

    # Set the levels to nice values
    plot.contour(0).levels.reset_levels(np.linspace(200,4400,22))

    legend = plot.contour(0).legend
    legend.show = True
    legend.vertical = False  # Horizontal
    legend.auto_resize = False
    legend.label_step = 5

    legend.overlay_bar_grid = False
    legend.position = (55, 94)  # Frame percentages

    legend.box.box_type = TextBox.None_ # Remove Text box

    legend.header_font.typeface = 'Courier'
    legend.header_font.bold = True

    legend.number_font.typeface = 'Courier'
    legend.number_font.bold = True

    tecplot.export.save_png('legend_contour.png', 600, supersample=5)

## 3D View

This example illustrates changing the attributes of the 3D view.

    import tecplot
    import os
    from tecplot.constant import *

    examples_dir = tecplot.session.tecplot_examples_directory()
    infile = os.path.join(examples_dir, '3D', 'jet_surface.plt')
    ds = tecplot.data.load_tecplot(infile)
    plot = tecplot.active_frame().plot(PlotType.Cartesian3D)
    plot.activate()
    plot.view.width = 17.5
    plot.view.alpha = 0
    plot.view.theta = 125
    plot.view.psi = 65
    plot.view.position = (-100, 80, 65)

    tecplot.export.save_jpeg('jet_surface.jpeg', 600, supersample=3)

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