ovito.vis

This module contains classes related to data visualization and rendering.

Rendering:

Rendering engines:

Data visualization elements:

Viewport overlays:

class ovito.vis.Viewport

A viewport represents a virtual “window” to the three-dimensional scene, showing the objects in the scene from a certain view point, which is determined by the viewport’s camera.

The virtual camera’s position and orientation are controlled by the camera_pos and camera_dir fields. Additionally, the type field allows you to switch between perspective and parallel projection modes or reset the camera to one of the standard axis-aligned orientations that are also found in the graphical version of OVITO. The zoom_all() method repositions the camera automatically such that the entire scene becomes fully visible within the view. See also the documentation of the Adjust View dialog of OVITO to learn more about the role of these settings.

After the viewport’s virtual camera has been set up, you can render an image or movie using the render_image() and render_anim() methods. For example:

from ovito.io import import_file
from ovito.vis import Viewport, TachyonRenderer

pipeline = import_file('input/simulation.dump')
pipeline.add_to_scene()

vp = Viewport(type = Viewport.Type.Ortho, camera_dir = (2, 1, -1))
vp.zoom_all()
vp.render_image(filename='output/simulation.png', 
                size=(320, 240), 
                renderer=TachyonRenderer())

Furthermore, so-called overlays may be assigned to a viewport. Overlays are function objects that draw additional two-dimensional content on top of the rendered scene, e.g. a coordinate axis tripod or a color legend. See the the overlays property for more information.

property camera_dir

The viewing direction vector of the viewport’s camera.

property camera_pos

The position of the viewport’s camera in the three-dimensional scene.

property camera_up

Direction vector specifying which coordinate axis will point upward in rendered images. Set this parameter to a non-zero vector in order to rotate the camera around the viewing direction and align the vertical direction in rendered images with a different simulation coordinate axis. If set to (0,0,0), then the upward axis is determined by the current user settings set in OVITO’s application settings dialog (z-axis by default).

Default

(0,0,0)

property fov

The field of view of the viewport’s camera. For perspective projections this is the camera’s angle in the vertical direction (in radians). For orthogonal projections this is the visible range in the vertical direction (in world units).

property overlays

A list of ViewportOverlay objects that are attached to this viewport. Overlays render graphical content on top of the three-dimensional scene. See the following classes for more information:

To attach a new overlay to the viewport, use the append() method:

from ovito.vis import Viewport, CoordinateTripodOverlay

vp = Viewport(type = Viewport.Type.Ortho)
tripod = CoordinateTripodOverlay(size = 0.07)
vp.overlays.append(tripod)
render_anim(filename, size=(640, 480), fps=10, background=(1.0, 1.0, 1.0), renderer=None, range=None, every_nth=1)

Renders an animation sequence.

Parameters

  • filename (str) – The filename under which the rendered animation should be saved. Supported video formats are: .avi, .mp4, .mov and .gif. Alternatively, an image format may be specified (.png, .jpeg). In this case, a series of image files will be produced, one for each frame, which may be combined into an animation using an external video encoding tool of your choice.

  • size – The resolution of the movie in pixels.

  • fps – The number of frames per second of the encoded movie. This determines the playback speed of the animation.

  • background – An RGB triplet in the range [0,1] specifying the background color of the rendered movie.

  • renderer – The rendering engine to use. If none is specified, either OpenGL or Tachyon are used, depending on the availablity of OpenGL in the script execution context.

  • range – The interval of frames to render, specified in the form (from,to). Frame numbering starts at 0. If no interval is specified, the entire animation is rendered, i.e. frame 0 through (FileSource.num_frames-1).

  • every_nth – Frame skipping interval in case you don’t want to render every frame of a very long animation.

See also the render_image() method for a more detailed discussion of some of these parameters.

render_image(size=(640, 480), frame=0, filename=None, background=(1.0, 1.0, 1.0), alpha=False, renderer=None)

Renders an image of the viewport’s view.

Parameters

  • size – A pair of integers specifying the horizontal and vertical dimensions of the output image in pixels.

  • frame (int) – The animation frame to render. Numbering starts at 0. See the FileSource.num_frames property for the number of loaded animation frames.

  • filename (str) – The file path under which the rendered image should be saved (optional). Supported output formats are: .png, .jpeg and .tiff.

  • background – A triplet of RGB values in the range [0,1] specifying the background color of the rendered image.

  • alpha – This option makes the background transparent so that the rendered image may later be superimposed on a different backdrop. When using this option, make sure to save the image in the PNG format in order to preserve the generated transparency information.

  • renderer – The rendering engine to use. If set to None, either OpenGL or Tachyon are used, depending on the availablity of OpenGL in the current execution context.

Returns

A QImage object containing the rendered picture.

Populating the scene

Before rendering an image using this method, you should make sure the three-dimensional contains some visible objects. Typically this involves calling the Pipeline.add_to_scene() method on a pipeline to insert its output data into the scene:

pipeline = import_file('simulation.dump')
pipeline.add_to_scene()

Selecting a rendering engine

OVITO supports several different rendering backends for producing pictures of the three-dimensional scene:

Each of these backends exhibits specific parameters that control the image quality and other aspect of the image generation process. Typically, you would create an instance of one of these renderer classes, configure it and pass it to the render_image() method:

vp.render_image(filename='output/simulation.png', 
                size=(320,240),
                background=(0,0,0), 
                renderer=TachyonRenderer(ambient_occlusion=False, shadows=False))

Note that the OpenGLRenderer backend may not be available when you are executing the script in a headless environment, e.g. on a remote HPC cluster without X display and OpenGL support.

Post-processing images

If the filename parameter is omitted, the method does not save the rendered image to disk. This gives you the opportunity to paint additional graphics on top before saving the QImage later using its save() method:

from ovito.vis import Viewport, TachyonRenderer
from PyQt5.QtGui import QPainter

# Render an image of the three-dimensional scene:
vp = Viewport(type=Viewport.Type.Ortho, camera_dir=(2, 1, -1))
vp.zoom_all()
image = vp.render_image(size=(320,240), renderer=TachyonRenderer())

# Paint on top of the rendered image using Qt's drawing functions:
painter = QPainter(image)
painter.drawText(10, 20, "Hello world!")
del painter

# Save image to disk:
image.save("output/image.png")

As an alternative to the direct method demonstrated above, you can also make use of a PythonViewportOverlay to paint custom graphics on top of rendered images.

property type

Specifies the projection type of the viewport. The following standard modes are available:

  • Viewport.Type.Perspective

  • Viewport.Type.Ortho

  • Viewport.Type.Top

  • Viewport.Type.Bottom

  • Viewport.Type.Front

  • Viewport.Type.Back

  • Viewport.Type.Left

  • Viewport.Type.Right

The first two types (Perspective and Ortho) allow you to set up custom views with arbitrary camera orientations.

zoom_all()

Repositions the viewport camera such that all objects in the scene become completely visible. The camera direction is maintained by the method.

class ovito.vis.OpenGLRenderer

The standard OpenGL-based renderer.

This is the default built-in rendering engine that is also used by OVITO to render the contents of the interactive viewports. Since it accelerates the generation of images by using the computer’s graphics hardware, it is very fast. See the corresponding user manual page for more information on this rendering engine.

Note that this renderer requires OpenGL graphics support, and Python scripts may be running in environments where it is not available. A typical example for such situations are remote SSH connections, which can prevent OVITO from accessing the X window and OpenGL systems. In this case, the OpenGL renderer will refuse to work and you have to use one of the software-based rendering engines instead. See the Viewport.render_image() method.

property antialiasing_level

A positive integer controlling the level of supersampling. If 1, no supersampling is performed. For larger values, the image in rendered at a higher resolution and then scaled back to the output size to reduce aliasing artifacts.

Default

3

class ovito.vis.DataVis

Abstract base class for visualization elements that are reponsible for the visual appearance of data objects in the visualization. Some DataObjects are associated with a corresponding DataVis element (see DataObject.vis property), making them visual data objects that appear in the viewports and in rendered images.

See the ovito.vis module for the list of visual element types available in OVITO.

property enabled

Boolean flag controlling the visibility of the data. If set to False, the data will not be visible in the viewports or in rendered images.

Default

True

property title

A custom title string assigned to the visual element, which will show in the pipeline editor of OVITO.

Default

''

class ovito.vis.CoordinateTripodOverlay
Base class

ovito.vis.ViewportOverlay

Displays a coordinate tripod in rendered images. You can attach an instance of this class to a viewport by adding it to the viewport’s overlays collection:

from ovito.vis import CoordinateTripodOverlay, Viewport
from PyQt5 import QtCore

# Create the overlay.
tripod = CoordinateTripodOverlay()
tripod.size = 0.07
tripod.alignment = QtCore.Qt.AlignRight ^ QtCore.Qt.AlignBottom
tripod.style = CoordinateTripodOverlay.Style.Solid

# Attach overlay to a newly created viewport.
viewport = Viewport(type=Viewport.Type.Perspective, camera_dir=(1,2,-1))
viewport.overlays.append(tripod)
property alignment

Selects the corner of the viewport where the tripod is displayed. This must be a valid Qt.Alignment value value as shown in the example above.

Default

PyQt5.QtCore.Qt.AlignLeft ^ PyQt5.QtCore.Qt.AlignBottom

property axis1_color

RGB display color of the first axis.

Default

(1.0, 0.0, 0.0)

property axis1_dir

Vector specifying direction and length of first axis, expressed in the global Cartesian coordinate system.

Default

(1,0,0)

property axis1_enabled

Enables the display of the first axis.

Default

True

property axis1_label

Text label for the first axis.

Default

“x”

property axis2_color

RGB display color of the second axis.

Default

(0.0, 0.8, 0.0)

property axis2_dir

Vector specifying direction and length of second axis, expressed in the global Cartesian coordinate system.

Default

(0,1,0)

property axis2_enabled

Enables the display of the second axis.

Default

True

property axis2_label

Text label for the second axis.

Default

“y”

property axis3_color

RGB display color of the third axis.

Default

(0.2, 0.2, 1.0)

property axis3_dir

Vector specifying direction and length of third axis, expressed in the global Cartesian coordinate system.

Default

(0,0,1)

property axis3_enabled

Enables the display of the third axis.

Default

True

property axis3_label

Text label for the third axis.

Default

“z”

property axis4_color

RGB display color of the fourth axis.

Default

(1.0, 0.0, 1.0)

property axis4_dir

Vector specifying direction and length of fourth axis, expressed in the global Cartesian coordinate system.

Default

(0.7071, 0.7071, 0.0)

property axis4_enabled

Enables the display of the fourth axis.

Default

False

property axis4_label

Label for the fourth axis.

Default

“w”

property font_size

The font size for rendering the text labels of the tripod. The font size is specified in terms of the tripod size.

Default

0.4

property line_width

Controls the width of axis arrows. The line width is specified relative to the tripod size.

Default

0.06

property offset_x

This parameter allows to displace the tripod horizontally. The offset is specified as a fraction of the output image width.

Default

0.0

property offset_y

This parameter allows to displace the tripod vertically. The offset is specified as a fraction of the output image height.

Default

0.0

property size

Scaling factor controlling the overall size of the tripod. The size is specified as a fraction of the output image height.

Default

0.075

property style

Selects the visual style of the coordinate axis tripod. Supported values are:

  • CoordinateTripodOverlay.Style.Flat (default)

  • CoordinateTripodOverlay.Style.Solid

class ovito.vis.PythonViewportOverlay
Base class

ovito.vis.ViewportOverlay

This type of viewport overlay runs a custom Python script function every time an image of the viewport is rendered. The user-defined script function can paint arbitrary graphics on top of the three-dimensional scene.

Note that instead of using a PythonViewportOverlay it is also possible to directly manipulate the image returned by the Viewport.render_image() method before saving the image to disk. A PythonViewportOverlay is only necessary when rendering animations or if you want the overlay to be usable from in the graphical program version.

You can attach the Python overlay to a viewport by adding it to the viewport’s overlays collection:

from ovito.vis import PythonViewportOverlay, Viewport

# Create a viewport:
viewport = Viewport(type = Viewport.Type.Top)

# The user-defined function that will paint on top of rendered images:
def render_some_text(args):
    args.painter.drawText(10, 10, "Hello world")

# Attach overlay function to viewport:
viewport.overlays.append(PythonViewportOverlay(function = render_some_text))

The user-defined Python function must accept a single argument (named args in the example above). The system will pass in an instance of the Arguments class to the function, which contains various state information, including the current animation frame number and the viewport being rendered as well as a QPainter object, which the function should use to issue drawing calls.

class Arguments

This is the type of data structure passed by the system to the user-defined render() function of the viewport overlay. It holds various context information about the frame being rendered and provides utility methods for projecting points from 3d to 2d space.

property fov

The field of view of the viewport’s camera. For perspective projections, this is the frustum angle in the vertical direction (in radians). For orthogonal projections this is the visible range in the vertical direction (in world units).

property frame

The animation frame number being rendered (0-based).

property is_perspective

Flag indicating whether the viewport uses a perspective projection or parallel projection.

property painter

The QPainter object, which provides painting methods for drawing on top of the image canvas.

property proj_tm

The projection matrix. This 4x4 matrix transforms points from camera space to screen space.

project_point(world_xyz)

Projects a point, given in world-space coordinates, to screen space. This method can be used to determine where a 3d point would appear in the rendered image.

Note that the projected point may lay outside of the visible viewport region. Furthermore, for viewports with a perspective projection, the input point may lie behind the virtual camera. In this case no corresponding projected point in 2d screen space exists and the method returns None.

Parameters

world_xyz – The (x,y,z) coordinates of the input point

Returns

A (x,y) pair of pixel coordinates; or None if world_xyz is behind the viewer.

project_size(world_xyz, r)

Projects a size from 3d world space to 2d screen space. This method can be used to determine how large a 3d object, for example a sphere with the given radius r, would appear in the rendered image.

Additionally to the size r to be projected, the method takes a coordinate triplet (x,y,z) as input. It specifies the location of the base point from where the distance is measured.

Parameters

  • world_xyz – The (x,y,z) world-space coordinates of the base point

  • r – The world-space size or distance to be converted to screen-space

Returns

The computed screen-space size measured in pixels.

property scene

The current three-dimensional Scene being rendered, including all visible data pipelines.

property size

A tuple with the width and height of the image being rendered in pixels.

property view_tm

The affine camera transformation matrix. This 3x4 matrix transforms points/vectors from world space to camera space.

property viewport

The Viewport being rendered.

property function

A reference to the Python function to be called every time the viewport is repainted or when an output image is rendered.

The user-defined function must accept exactly one argument as shown in the example above. The system will pass an Arguments object to the function, providing various contextual information on the current frame being rendered.

Implementation note: Exceptions raised within the custom rendering function are not propagated to the calling context.

Default

None

class ovito.vis.TextLabelOverlay
Base class

ovito.vis.ViewportOverlay

Displays a text label in a viewport and in rendered images. You can attach an instance of this class to a viewport by adding it to the viewport’s overlays collection:

from ovito.vis import TextLabelOverlay, Viewport
from PyQt5 import QtCore

# Create the overlay:
overlay = TextLabelOverlay(
    text = 'Some text', 
    alignment = QtCore.Qt.AlignHCenter ^ QtCore.Qt.AlignBottom,
    offset_y = 0.1,
    font_size = 0.03,
    text_color = (0,0,0))

# Attach the overlay to a newly created viewport:
viewport = Viewport(type = Viewport.Type.Top)
viewport.overlays.append(overlay)

Text labels can display dynamically computed values. See the text property for an example.

property alignment

Selects the corner of the viewport where the text is displayed (anchor position). This must be a valid Qt.Alignment value as shown in the example above.

Default

PyQt5.QtCore.Qt.AlignLeft ^ PyQt5.QtCore.Qt.AlignTop

property font_size

The font size, which is specified as a fraction of the output image height.

Default

0.02

property offset_x

This parameter allows to displace the label horizontally from its anchor position. The offset is specified as a fraction of the output image width.

Default

0.0

property offset_y

This parameter allows to displace the label vertically from its anchor position. The offset is specified as a fraction of the output image height.

Default

0.0

property outline_color

The text outline color. This is used only if outline_enabled is set.

Default

(1.0,1.0,1.0)

property outline_enabled

Enables the painting of a font outline to make the text easier to read.

Default

False

property source_pipeline

The Pipeline that is queried to obtain the attribute values referenced in the text string. See the text property for more information.

property text

The text string to be rendered.

The string can contain placeholder references to dynamically computed attributes of the form [attribute], which will be replaced by their actual value before rendering the text label. Attributes are taken from the pipeline output of the Pipeline assigned to the overlay’s source_pipeline property.

The following example demonstrates how to insert a text label that displays the number of currently selected particles:

from ovito.io import import_file
from ovito.vis import TextLabelOverlay, Viewport
from ovito.modifiers import ExpressionSelectionModifier

# Import a simulation dataset and select some atoms based on their potential energy:
pipeline = import_file("input/simulation.dump")
pipeline.add_to_scene()
pipeline.modifiers.append(ExpressionSelectionModifier(expression='peatom > -4.2'))

# Create the overlay. Note that the text string contains a reference
# to an output attribute of the ExpressionSelectionModifier.
overlay = TextLabelOverlay(text = 'Number of selected atoms: [SelectExpression.num_selected]')
# Specify the source of dynamically computed attributes.
overlay.source_pipeline = pipeline

# Attach overlay to a newly created viewport:
viewport = Viewport(type = Viewport.Type.Top)
viewport.overlays.append(overlay)
Default

“Text label”

property text_color

The text rendering color.

Default

(0.0,0.0,0.5)

class ovito.vis.ViewportOverlay

Abstract base class for viewport overlays, which render two-dimensional graphics on top of (or behind) the three-dimensional scene. Examples are CoordinateTripodOverlay, TextLabelOverlay and ColorLegendOverlay.

property behind_scene

This option allows to put the overlay behind the three-dimensional scene, i.e. it becomes an “underlay” instead of an “overlay”. If set to True, objects of the three-dimensional scene will occclude the graphics of the overlay.

Default

False

property enabled

Controls whether the overlay gets rendered. An overlay can be hidden by setting its enabled property to False.

Default

True

class ovito.vis.SimulationCellVis
Base class

ovito.vis.DataVis

Controls the visual appearance of the simulation cell. An instance of this class is attached to the SimulationCell object and can be accessed through its vis field. See also the corresponding user manual page for this visual element.

The following example script demonstrates how to change the display line width and rendering color of the simulation cell loaded from an input simulation file:

from ovito.io import import_file

pipeline = import_file("input/simulation.dump")
pipeline.add_to_scene()

cell_vis = pipeline.source.data.cell.vis
cell_vis.line_width = 1.3
cell_vis.rendering_color = (0.0, 0.0, 0.8)
property line_width

The width of the simulation cell line (in simulation units of length).

Default

0.14% of the simulation box diameter

property render_cell

Boolean flag controlling the cell’s visibility in rendered images. If False, the cell will only be visible in the interactive viewports.

Default

True

property rendering_color

The line color used when rendering the cell.

Default

(0, 0, 0)

class ovito.vis.SurfaceMeshVis
Base class

ovito.vis.DataVis

Controls the visual appearance of a SurfaceMesh object, which is typically generated by modifiers such as ConstructSurfaceModifier or CreateIsosurfaceModifier. See also the corresponding user manual page for this visual element.

property cap_color

The display color of the cap polygons at periodic boundaries.

Default

(0.8, 0.8, 1.0)

property cap_transparency

The level of transparency of the displayed cap polygons. Valid range is 0.0 – 1.0.

Default

0.0

property highlight_edges

Activates the highlighted rendering of the polygonal edges of the mesh.

Default

False

property reverse_orientation

Flips the orientation of the surface. This affects the generation of cap polygons.

Default

False

property show_cap

Controls the visibility of cap polygons, which are created at the intersection of the surface mesh with periodic box boundaries.

Default

True

property smooth_shading

Enables smooth shading of the triangulated surface mesh.

Default

True

property surface_color

The display color of the surface mesh.

Default

(1.0, 1.0, 1.0)

property surface_transparency

The level of transparency of the displayed surface. Valid range is 0.0 – 1.0.

Default

0.0

class ovito.vis.ColorLegendOverlay
Base class

ovito.vis.ViewportOverlay

Renders a color legend for a ColorCodingModifier on top of the three-dimensional scene. You can attach an instance of this class to a Viewport by adding it to the viewport’s overlays collection:

from ovito.io import import_file
from ovito.vis import ColorLegendOverlay, Viewport
from ovito.modifiers import ColorCodingModifier
from PyQt5.QtCore import Qt

# Prepare a data pipeline containing a ColorCodingModifier:
pipeline = import_file("input/simulation.dump")
color_mod = ColorCodingModifier(property = 'peatom')
pipeline.modifiers.append(color_mod)
pipeline.add_to_scene()

# Configure the viewport overlay and link it to the ColorCodingModifier:
overlay = ColorLegendOverlay(
    modifier = color_mod,
    title = 'Potential energy per atom:', 
    alignment = Qt.AlignLeft ^ Qt.AlignTop,
    orientation = Qt.Vertical,
    offset_y = -0.04,
    font_size = 0.12,
    format_string = '%.2f eV')

# Attach the overlay to a Viewport, which is going to be used for image rendering:
viewport = Viewport(type = Viewport.Type.Top)
viewport.overlays.append(overlay)
property alignment

Selects the corner of the viewport where the color bar is displayed (anchor position). This must be a valid Qt.Alignment value as shown in the code example above.

Default

PyQt5.QtCore.Qt.AlignHCenter ^ PyQt5.QtCore.Qt.AlignBottom

property aspect_ratio

The aspect ratio of the color bar. Larger values make it more narrow.

Default

8.0

property font_size

The relative size of the font used for text labels.

Default

0.1

property format_string

The format string used with the sprintf() function to generate the text representation of floating-point values. You can change this format string to control the number of decimal places or add units to the numeric values, for example.

Default

‘%g’

property label1

Sets the text string displayed at the upper end of the bar. If empty, the end_value of the ColorCodingModifier is used.

Default

‘’

property label2

Sets the text string displayed at the lower end of the bar. If empty, the start_value of the ColorCodingModifier is used.

Default

‘’

property legend_size

Controls the overall size of the color bar relative to the output image size.

Default

0.3

property modifier

The ColorCodingModifier for which the color legend should be rendered.

property offset_x

This parameter allows to displace the color bar horizontally from its anchor position. The offset is specified as a fraction of the output image width.

Default

0.0

property offset_y

This parameter allows to displace the color bar vertically from its anchor position. The offset is specified as a fraction of the output image height.

Default

0.0

property orientation

Selects the orientation of the color bar. This must be a valid Qt.Orientation value as shown in the code example above.

Default

PyQt5.QtCore.Qt.Horizontal

property outline_color

The text outline color. This is used only if outline_enabled is set.

Default

(1.0,1.0,1.0)

property outline_enabled

Enables the painting of a font outline to make the text easier to read.

Default

False

property text_color

The RGB color used for text labels.

Default

(0.0,0.0,0.0)

property title

The text displayed next to the color bar. If empty, the name of the input property selected in the ColorCodingModifier is used.

Default

‘’

class ovito.vis.ParticlesVis
Base class

ovito.vis.DataVis

This type of visual element is responsible for rendering particles and is attached to every Particles data object. You can access the element through the vis field of the data object and adjust its parameters to control the visual appearance of particles in rendered images:

from ovito.io import import_file
from ovito.vis import ParticlesVis

pipeline = import_file("input/simulation.dump")
pipeline.add_to_scene()

vis_element = pipeline.source.data.particles.vis
vis_element.shape = ParticlesVis.Shape.Square

See also the corresponding user manual page for more information on this visual element.

property radius

The standard display radius of particles. This value is only used if no per-particle or per-type radii have been set. A per-type radius can be set via ParticleType.radius. An individual display radius can be assigned to each particle by setting the Radius particle property, e.g. using the ComputePropertyModifier.

Default

1.2

property shape

The display shape of particles. Possible values are:

  • ParticlesVis.Shape.Sphere (default)

  • ParticlesVis.Shape.Box

  • ParticlesVis.Shape.Circle

  • ParticlesVis.Shape.Square

  • ParticlesVis.Shape.Cylinder

  • ParticlesVis.Shape.Spherocylinder

class ovito.vis.VectorVis
Base class

ovito.vis.DataVis

This type of visual element is responsible for rendering arrows to visualize per-particle vector quantities. An instance of this class is typically attached to a Property data object that represents a vectorial quantity, e.g. the Force and the Displacement particle properties. See also the corresponding user manual page for a description of this visual element.

The parameters of the vector visual element let you control the visual appearance of the arrows in rendered images. For the standard particle properties Force, Dipole and Displacement, OVITO automatically creates and attaches a VectorVis element to these properties and you can access it through their vis field:

pipeline = import_file('input/simulation.dump')
pipeline.add_to_scene()
vector_vis = pipeline.source.data.particles.forces.vis
vector_vis.color = (1,0,0)
vector_vis.enabled = True  # This activates the display of arrows

In the example above, the Force particle property was loaded from the input simulation file, and the code accesses the corresponding Property data object in the source data collection of the pipeline.

Some modifiers dynamically generate new vector particle properties. For instance, the CalculateDisplacementsModifier generates the Displacement property and will automatically attach a new VectorVis element to it. In this case, the visual element is managed by the modifier and may be configured as needed:

modifier = CalculateDisplacementsModifier()
pipeline.modifiers.append(modifier)
modifier.vis.enabled = True  # This activates the display of displacement vectors
modifier.vis.shading = VectorVis.Shading.Flat

If you write your own modifier function in Python for computing a vector particle property, and you want to visualize these vectors as arrows, you need to create the VectorVis element programmatically and attached it to the Property generated by your user-defined modifier function. For example:

from ovito.vis import VectorVis
import numpy

# Set up the visual element outside of the modifier function:
vector_vis = VectorVis(
    alignment = VectorVis.Alignment.Center, 
    color = (1.0, 0.0, 0.4))

def my_modifier_function(frame, data):
    vector_data = numpy.random.random_sample(size=(data.particles.count, 3))
    my_prop = data.particles_.create_property('My Property', data=vector_data)
    my_prop.vis = vector_vis  # Attach the visual element to output property
property alignment

Controls the positioning of arrows with respect to the particles. Possible values:

  • VectorVis.Alignment.Base (default)

  • VectorVis.Alignment.Center

  • VectorVis.Alignment.Head

property color

The display color of arrows.

Default

(1.0, 1.0, 0.0)

property reverse

Boolean flag controlling the reversal of arrow directions.

Default

False

property scaling

The uniform scaling factor applied to vectors.

Default

1.0

property shading

The shading style used for the arrows. Possible values:

  • VectorVis.Shading.Normal (default)

  • VectorVis.Shading.Flat

property width

Controls the width of arrows (in natural length units).

Default

0.5

class ovito.vis.BondsVis
Base class

ovito.vis.DataVis

A visualization element that renders cylindrical bonds between particles. An instance of this class is attached to every Bonds data object and controls the visual appearance of the bonds in rendered images.

See also the corresponding user manual page for this visual element. If you import a simulation file containing bonds, you can subsequently access the BondsVis element through the vis field of the bonds data object, which is part in the data collection managed by the pipeline’s source object:

pipeline = import_file('input/bonds.data.gz', atom_style='bond')
pipeline.add_to_scene()
bonds_vis = pipeline.source.data.particles.bonds.vis
bonds_vis.width = 0.4

In cases where the Bonds data is dynamically generated by a modifier, e.g. the CreateBondsModifier, the BondsVis element is managed by the modifier:

modifier = CreateBondsModifier(cutoff = 2.8)
modifier.vis.shading = BondsVis.Shading.Flat
pipeline.modifiers.append(modifier)
property color

The uniform display color of bonds. This value is only used if use_particle_colors is false and if the Color BondProperty is not defined.

Default

(0.6, 0.6, 0.6)

property shading

Controls the shading style of bonds. Possible values:

  • BondsVis.Shading.Normal (default)

  • BondsVis.Shading.Flat

property use_particle_colors

If set to True, bonds are rendered in the same color as the particles they are incident to. Otherwise, a uniform color is used. If the BondProperty named Color is defined, then the per-bond colors are used in any case.

Default

True

property width

The display width of bonds (in natural length units).

Default

0.4

class ovito.vis.TrajectoryVis
Base class

ovito.vis.DataVis

Controls the visual appearance of particle trajectory lines. An instance of this class is attached to every TrajectoryLines data object.

property color

The display color of trajectory lines.

Default

(0.6, 0.6, 0.6)

property shading

The shading style used for trajectory lines. Possible values:

  • TrajectoryVis.Shading.Normal

  • TrajectoryVis.Shading.Flat (default)

property upto_current_time

If True, trajectory lines are only rendered up to the particle positions at the current animation time. Otherwise, the complete trajectory lines are displayed.

Default

False

property width

The display width of trajectory lines.

Default

0.2

property wrapped_lines

If True, the continuous trajectory lines will automatically be wrapped back into the simulation box during rendering. Thus, they will be shown as several discontinuous segments if they cross periodic boundaries of the simulation box.

Default

False

class ovito.vis.DislocationVis
Base class

ovito.vis.DataVis

Controls the visual appearance of dislocation lines extracted by a DislocationAnalysisModifier. An instance of this class is attached to every DislocationNetwork data object.

See also the corresponding user manual page for more information on this visual element.

property burgers_vector_color

The color of Burgers vector arrows.

Default

(0.7, 0.7, 0.7)

property burgers_vector_width

The scaling factor applied to displayed Burgers vectors. This can be used to exaggerate the arrow size.

Default

1.0

property indicate_character

Controls how the display color of dislocation lines is chosen.Possible values:

  • DislocationVis.ColoringMode.ByDislocationType (default)

  • DislocationVis.ColoringMode.ByBurgersVector

  • DislocationVis.ColoringMode.ByCharacter

property line_width

Controls the display width (in units of length of the simulation) of dislocation lines.

Default

1.0

property shading

The shading style used for the lines. Possible values:

  • DislocationVis.Shading.Normal (default)

  • DislocationVis.Shading.Flat

property show_burgers_vectors

Boolean flag that enables the display of Burgers vector arrows.

Default

False

property show_line_directions

Boolean flag that enables the visualization of line directions.

Default

False

class ovito.vis.OSPRayRenderer

This is one of the software-based rendering backends of OVITO. OSPRay is an open-source raytracing system integrated into OVITO.

An instance of this class can be passed to the Viewport.render_image() or Viewport.render_anim() methods.

OSPRay can render scenes with ambient occlusion lighting, semi-transparent objects, and depth-of-field focal blur. For technical details of the supported rendering algorithms and parameters, see the www.ospray.org website. See also the corresponding user manual page for more information on this rendering engine.

property ambient_brightness

Controls the radiance of the ambient light.

Default

0.8

property ambient_light_enabled

Enables the ambient light, which surrounds the scene and illuminates it from infinity with constant radiance.

Default

True

property aperture

The aperture radius controls how blurred objects will appear that are out of focus if dof_enabled was set.

Default

0.5

property default_light_angular_diameter

Specifies the apparent size (angle in radians) of the default directional light source. Setting the angular diameter to a value greater than zero will result in soft shadows when the rendering backend uses stochastic sampling (which is only the case for the Path Tracer backend).

Default

0.0

property default_light_intensity

The intensity of the default directional light source. The light source must be enabled by setting direct_light_enabled.

Default

3.0

property direct_light_enabled

Enables the default directional light source that is positioned behind the camera and is pointing roughly along the viewing direction. The brightness of the light source is controlled by the default_light_intensity parameter.

Default

True

property dof_enabled

Enables the depth-of-field effect. Only objects exactly at the distance from the camera specified by the focal_length will appear sharp when depth-of-field rendering is active. Objects closer to or further from the camera will appear blurred.

Default

False

property focal_length

Only objects exactly at this distance from the camera will appear sharp when dof_enabled is set. Objects closer to or further from the camera will appear blurred.

Default

40.0

property material_shininess

Specular Phong exponent value for the default material. Usually in the range between 2.0 and 10,000.

Default

10.0

property material_specular_brightness

Controls the specular reflectivity of the default material.

Default

0.05

property max_ray_recursion

The maximum number of recursion steps during raytracing. Normally, 1 or 2 is enough, but when rendering semi-transparent objects, a larger recursion depth is needed.

Default

20

property refinement_iterations

The OSPRay renderer supports a feature called adaptive accumulation, which is a progressive rendering method. During each rendering pass, the rendered image is progressively refined. This parameter controls the number of iterations until the refinement stops.

Default

8

property samples_per_pixel

The number of raytracing samples computed per pixel. Larger values can help to reduce aliasing artifacts.

Default

4

class ovito.vis.POVRayRenderer

This is one of the rendering backends of OVITO.

POV-Ray (The Persistence of Vision Raytracer) is an open-source raytracing program. The POV-Ray rendering backend streams the scene data to a temporary file, which is then processed and rendered by the external POV-Ray program. The final rendered image is read back into OVITO.

The rendering backend requires the POV-Ray executable to be installed on the system. It will automatically look for the executable povray in the system path. If the executable is not in the default search path, its location must be explicitly specified by setting the povray_executable attribute.

For a more detailed description of the rendering parameters exposed by this Python class, please consult the official POV-Ray documentation. See also the corresponding user manual page for more information on this rendering backend.

property antialiasing

Enables supersampling to reduce aliasing effects.

Default

True

property aperture

Controls the aperture of the camera, which is used for depth-of-field rendering.

Default

1.0

property blur_samples

Controls the maximum number of rays to use for each pixel to compute focus blur (depth-of-field).

Default

1.0

property depth_of_field

This flag enables focus blur (depth-of-field) rendering.

Default

False

property focal_length

Controls the focal length of the camera, which is used for depth-of-field rendering.

Default

40.0

property interpupillary_distance

Controls interpupillary distance (eye separation) for stereoscopic rendering. This setting is only used if the omni_stereo option has been set.

Default

0.5

property omni_stereo

This flag enables omni­directional stereo projection for stereoscopic 360-degree VR videos and images. Note that this requires POV-Ray 3.7.1 or newer. The eye separation distance is controlled by the interpupillary_distance parameter.

Default

False

property povray_executable

The absolute path to the external POV-Ray executable on the local computer, which is called by this rendering backend to render an image. If no path is set, OVITO will look for povray in the default executable search path.

Default

""

property quality_level

The image rendering quality parameter passed to POV-Ray.

Default

9

property radiosity

Enables radiosity light calculations.

Default

False

property radiosity_raycount

The number of rays that are sent out whenever a new radiosity value has to be calculated.

Default

50

property show_window

Controls whether the POV-Ray window is shown during rendering. This allows you to follow the image generation process.

Default

True

class ovito.vis.TachyonRenderer

This is one of the software-based rendering backends of OVITO. Tachyon is an open-source raytracing engine integrated into OVITO.

An instance of this class can be passed to the Viewport.render_image() or Viewport.render_anim() methods.

Tachyon can render scenes with ambient occlusion lighting, semi-transparent objects, and depth-of-field focal blur. See the corresponding user manual page for more information on this rendering backend.

property ambient_occlusion

Enables ambient occlusion shading. Enabling this lighting technique mimics some of the effects that occur under conditions of omnidirectional diffuse illumination, e.g. outdoors on an overcast day.

Default

True

property ambient_occlusion_brightness

Controls the brightness of the sky light source used for ambient occlusion.

Default

0.8

property ambient_occlusion_samples

Ambient occlusion is implemented using a Monte Carlo technique. This parameters controls the number of samples to compute. A higher sample count leads to a more even shading, but requires more computation time.

Default

12

property antialiasing

Enables supersampling to reduce aliasing effects.

Default

True

property antialiasing_samples

The number of supersampling rays to generate per pixel to reduce aliasing effects.

Default

12

property aperture

Controls the aperture of the camera, which is used for depth-of-field rendering.

Default

0.01

property depth_of_field

This flag enables depth-of-field rendering.

Default

False

property direct_light

Enables the parallel light source, which is positioned at an angle behind the camera.

Default

True

property direct_light_intensity

Controls the brightness of the directional light source.

Default

0.9

property focal_length

Controls the focal length of the camera, which is used for depth-of-field rendering.

Default

40.0

property shadows

Enables cast shadows for the directional light source.

Default

True

© 2019, Alexander Stukowski.
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