Scientific Visualization with ParaView Robert Putnam [email protected] IS&T Scientific Visualization Tutorial – Spring 2011

Scientific Visualization with ParaViewScientific Visualization with ParaView

Robert Putnam

[email protected]

IS&T Scientific Visualization Tutorial – Spring 2011

OutlineOutline

• Introduction• ParaView overview• ParaView/VTK data geometry/topology• Case study• Interactive session

Scientific Visualization with ParaView – Spring 2011

IntroductionIntroduction


*Adapted from The ParaView Tutorial, Moreland

• Visualization: converting raw data to a form that is viewable and understandable to humans.

• Scientific visualization: specifically concerned with data that has a well-defined representation in 2D or 3D space (e.g., from simulation mesh or scanner).

IntroductionIntroduction


• Paraview – open-source application designed for visualizing two- and three-dimensional data sets.

• Begun in 2000 as a collaboration between Kitware, Inc. and LANL (funded by DOE)• Built on VTK (“Visualization Tool Kit”)• Graphics user interface• Python scripting• Architecture extensible by plugins• Available for MS Windows, Linux, OSX• Support for large dataset / distributed architecture (client/server model)• Online and printed documentation from Kitware

Generic visualization pipelineGeneric visualization pipeline


Source(s) Filters(s) Output (Rendering)

- - - - - - - - - - - - - - - - - - - - -

data/geometry/topology graphics

Slice displaySlice display


heat.vtk (3D dataset)

Slice (2D)

Display

Paraview user interfaceParaview user interface


Menu bar

Toolbars

Pipeline Browser

Object Inspector

3D View

Combined filters to fileCombined filters to file


heat.vtk (3D dataset)

Slice Filterheat2.jpg

Stream Tracer

Tube Filter

Glyph Filter

scalar data

Vectordata

Combined filters to fileCombined filters to file


heat.vtk Slice

StreamT

ube G

lyph

ParaView – Pipeline BrowserParaView – Pipeline Browser

Pipeline Browser

• located in the upper left corner of the user interface

• allows you to build a visualization pipeline

• allows you to interact with the current visualization

pipeline

• top of the pipeline browser is the name of the server to

which ParaView is connected

• below the server name is a tree structure representing

each of the reader, source, and filter objects that are in

the visualization pipeline.


ParaView - Object InspectorParaView - Object Inspector

– Object Inspector

• located beneath the Pipeline Browser in the user

interface

• contains controls and information for the reader,

source, or filter object selected in the Pipeline Browser

• allows you to interact with the current visualization

pipeline

• content changes based upon the specific object

selected


Object Inspector - Properties Object Inspector - Properties

– Object Inspector Tabs

• There are three tabs in the Object Inspector:

• Properties

• Display

• Information

• The Properties Tab contains controls for specifying

various parameters of the object selected in the Pipeline

Browser.

• Here is an example of what is shown in the Properties

Tab for a Slice filter.


Object Inspector - DisplayObject Inspector - Display


• The Display Tab contains controls for setting the

appearance of the object selected in the Pipeline

Browser.

• grouped into several sections: View, Color, Slice, Style,

Edge Style, Annotation, Lighting, and Transformation.

• Here is an example of what is shown in the Display Tab

for a Slice filter.


Object Inspector - InformationObject Inspector - Information


• The Information Tab contains statistical information

about the output of the object selected in the Pipeline

Browser.

• Here is an example of what is shown in the Information

Tab for a Slice filter.


ParaView - MenusParaView - Menus

– File menu• handles various tasks such as opening data files,

saving data files, loading state files, saving state files, saving screenshots, saving animations, and fileserver connections.



– View menu• allows you to modify the camera and center of rotation

for the 3D view. The view menu also allows you to toggle the visibility of the toolbars, inspectors, and views.



– Filters menu

• provides a list of available filters you can use to

process data sets.

• organized by recent, common, data analysis, temporal,

and alphabetical.

• The most commonly used filters, located under the

Common subdirectory, are also located on the

Common Filters Toolbar.

• The filters are context sensitive and will only be

available for selection if an appropriate data set has

been loaded first and selected in the Pipeline Browser.



– Help menu

• provides information on the ParaView version,

information on client server connections, and provides

access to the online manual.

• You can also visit the online version of the ParaView

documentation: http://paraview.org/OnlineHelpCurrent/


ParaView - HelpParaView - Help


ParaView – Geometry v. ParaView – Geometry v. TopologyTopology Geometry of a dataset ~= points


0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

Topology ~= connections among points, which define cells

So, what’s the topology here?

ParaView – Geometry v. ParaView – Geometry v. TopologyTopology


0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0



0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0



or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0



or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

or

0,1 1,1 2,1 3,1

0,0 1,0 2,0 3,0

Geometry/Topology StructureGeometry/Topology Structure

Structure may be regular or irregular– Regular (structured)

• need to store only beginning position, spacing, number of points

• smaller memory footprint per cell (topology can be generated on the fly)

• examples: image data, rectilinear grid, structured grid

– Irregular (unstructured)• information can be represented more densely where it changes quickly

• higher memory footprint (topology must be explicitly written) but more freedom

• examples: polygonal data, unstructured grid


Characteristics of DataCharacteristics of Data

Data is organized into datasets for visualization– Datasets consist of two pieces

• organizing structure– points (geometry)

– cells (topology)

• data attributes associated with the structure

– File format derived from organizing structure


Data is discrete– Interpolation functions generate data values in between known points

Examples of Dataset TypesExamples of Dataset Types

Structured Points (Image Data)– regular in both topology and geometry

– examples: lines, pixels, voxels

– applications: imaging CT, MRI

Rectilinear Grid– regular topology but geometry only partially

regular

– examples: pixels, voxels

Structured Grid (Curvilinear)– regular topology and irregular geometry

– examples: quadrilaterals, hexahedron

– applications: fluid flow, heat transfer


Examples of Dataset Types (cont)Examples of Dataset Types (cont)

Polygonal Data– irregular in both topology and geometry

– examples: vertices, polyvertices, lines, polylines, polygons, triangle strips

Unstructured Grid – irregular in both topology and geometry

– examples: any combination of cells

– applications: finite element analysis, structural design, vibration


Examples of Cell TypesExamples of Cell Types


Data AttributesData Attributes

Data attributes associated with the organizing structure– Scalars

• single valued

• examples: temperature, pressure, density, elevation

– Vectors• magnitude and direction

• examples: velocity, momentum

– Normals • direction vectors (magnitude of 1) used for shading

– Texture Coordinates• used to map a point in Cartesian space into 1, 2, or 3D texture space

• used for texture mapping

– Tensors • 3x3 only

• examples: stress, strain


File Format – Structured PointsFile Format – Structured Points


Editor structured-points.vtk:

# vtk DataFile Version 2.0

first dataset

ASCII

DATASET STRUCTURED_POINTS

DIMENSIONS 3 4 5

ORIGIN 0 0 0

SPACING 1 1 2

POINT_DATA 60

SCALARS temp-point float

LOOKUP_TABLE default

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0





first dataset

ASCII


DIMENSIONS 3 4 5

ORIGIN 0 0 0

SPACING 1 1 2

POINT_DATA 60

SCALARS temp-point float


0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0

0 0 0 1 1 1 1 1 1 0 0 0





first dataset

ASCII


DIMENSIONS 3 4 5

ORIGIN 0 0 0

SPACING 1 1 2

CELL_DATA 24

SCALARS temp-cell float


0 0 1 1 0 0

0 0 1 1 0 0

0 0 1 1 0 0

0 0 1 1 0 0





first dataset

ASCII


DIMENSIONS 3 4 5

ORIGIN 0 0 0

SPACING 1 1 2

CELL_DATA 24

SCALARS temp-cell float


0 0 1 1 0 0

0 0 1 1 0 0

0 0 1 1 0 0

0 0 1 1 0 0

Work flow – Case StudyWork flow – Case Study

Student summer project: visualize MRI lung imagery 10 slices of 256x256 MATLAB

Read in data Noise removal, isolation of lung Some visualization



MATLAB -> VTK file Write 256x256x10 float array to ASCII

file:

Add header , save with ‘.vtk’ extension:



Read VTK file into Paraview, choose “Volume Visualization” display option, add Cut Filter:



Change color map, use Paraview animation feature to move cut plane through volume:



Produce movie Save animation from

Paraview, which produces image files (jpegs).

Read image files into Adobe Premiere Pro

Save as movie (.mov, .wmv, .avi. , etc.)


Starting out - create sphereStarting out - create sphere


ParaView:

1. Choose Sources -> Sphere

2. Click Apply in Object Inspector

3. User Interface:

- Undo

- Color

- Lighting

- Camera Movement

Example – Loading dataExample – Loading data


ParaView:1. Disconnect from Server

File -> Disconnect

which clears the pipeline

2. Open data file

File -> Open (cylinder.vtk)

3. Click Apply in Object Inspector

4. In Toolbar area (or Object Inspector /

Display), color by Pres. Show

Legend.

5. Try Multi-view option (above upper

right-hand corner of 3D window).

Clipping, Cutting, SubsamplingClipping, Cutting, Subsampling

Selection Algorithms - Clipping

• can reveal internal details of surface

• ParaView - Clip Filter

- Cutting/Slicing• cutting through a dataset with a surface

• ParaView - Slice Filter

- Subsampling• reduces data size by selecting a subset of

the original data

• ParaView - ExtractSubset Filter


Example – ClippingExample – Clipping


ParaView:1. disconnect from Server

File -> Disconnect

2. open data file

File -> Open (density.vtk)

3. apply Clip filter to density.vtk

click on density.vtk in pipeline

Filter -> Clip

Example – Cutting/SlicingExample – Cutting/Slicing



File -> Disconnect

2. open data file


3. apply Slice filter to density.vtk


Filter -> Slice

Example – SubsamplingExample – Subsampling



File -> Disconnect

2. open data file


3. Apply Extract Subset filter to density.vtk


Filter -> Extract Subset

4. Apply Threshold filter to ExtractSubset

click on ExtractSubset filter

Filter -> Threshold

Color MappingColor Mapping

Scalar Algorithms– Color Mapping

• maps scalar data to colors

• implemented by using scalar values as an index into a color lookup table

– ParaView • Color panel in Display tab of object inspector of data

– Color by

– Edit Color Map


Example – Color MappingExample – Color Mapping


1. Disconnect from Server

File -> Disconnect

2. Open data file

File -> Open (subset.vtk)

3. go to the the color section in the

Display Tab in the Object Inspector

The "Color by" menu lists the names

of the attribute arrays. Selecting an

array name causes the dataset’s

coloring to be based on the

underlying scalar values in that

array.

Example – Color Mapping (cont)Example – Color Mapping (cont)


ParaView:1. The color map may be edited in the Color

Scale Editor window which appears when you click the Edit Color Map button in the Color section of the Display Tab.

2. Another way to change the mapping of data

values to colors is by setting the Data

Range.

-- The default Data Range is set from the

minimum data value in the data set to the

maximum data value.

-- click on the Rescale Range button to

explicitly set these values. The values

between the minimum and maximum are

then linearly interpolated into the color table.

ContouringContouring

Scalar Algorithms (cont)– Contouring

• construct a boundary between distinct regions, two steps:– explore space to find points near contour

– connect points into contour (2D) or surface (3D)

• 2D contour map (isoline):– applications: elevation contours from topography, pressure contours

(weather maps) from meteorology3D isosurface:

• 3D isosurface:– applications: tissue surfaces from tomography, constant pressure or

temperature in fluid flow, implicit surfaces from math and CAD

– ParaView• Contour Filter


Example – Isoline / 2D ContoursExample – Isoline / 2D Contours



File -> Disconnect

2. Open data file

File -> Open (subset.vtk)

3. Apply Contour filter to subset.vtk

click on subset.vtk in pipeline

Filter -> Contour

4. to color the contour line based upon its

scalar value and the current color map,

make sure the Compute Scalars

checkbox in the Contour section of the

Properties tab is selected

Example – Isosurface / 3D ContoursExample – Isosurface / 3D Contours



File -> Disconnect

2. Open data file


3. Apply Contour filter to density.vtk


Filter -> Contour

Scalar GenerationScalar Generation

Scalar Algorithms (cont)– Scalar Generation

• extract scalars from part of data

• example: extracting z coordinate (elevation) from terrain data to create scalar values

– ParaView• Elevation Filter


Example – Scalar GenerationExample – Scalar Generation



File -> Disconnect

2. open data file

File -> Open (honolulu.vtk)

3. apply Elevation filter to density.vtk

click on honolulu.vtk in pipeline

Filter -> Elevation

Oriented GlyphsOriented Glyphs

Vector Algorithms – Oriented Glyphs

• orientation indicates direction

• length indicates magnitude

• color indicates magnitude, pressure, temperature, or any variable

– ParaView• Glyph Filter

– Set type to arrow


Example – Oriented GlyphsExample – Oriented Glyphs



File -> Disconnect

2. open data file


3. apply Glyph filter to density.vtk


Filter -> Glyph

4. in the Object Inspector (Properties Tab)

set the “Scalars” menu to Density

set the “Vectors” menu to Momentum

set the “Glyph Type” to Arrow

Field LinesField Lines

Vector Algorithms (cont)– Field Lines

• Fluid flow is described by a vector field in three dimensions for steady (fixed time) flows or four dimensions for unsteady (time varying) flows

• Three techniques for determining flow– Pathline (Trace)

• tracks particle through unsteady (time-varying) flow

• shows particle trajectories over time

• rake releases particles from multiple positions at the same time instant

• reveals compression, vorticity

– Streamline

• tracks particle through steady (fixed-time) flow

• holds flow steady at a fixed time

• snapshot of flow at a given time instant

– Streakline

• particles released from the same position over a time interval (time-varying)

• snapshot of the variation of flow over time

• example: dye steadily injected into fluid at a fixed point


Field LinesField LinesStreamlines

• Lines show particle flow

• ParaView - StreamTracer Filter

Streamlets• half way between streamlines and glyphs

• ParaView - StreamTracer and Glyph Filters

Streamribbon• rake of two particles to create a ribbon

• ParaView - StreamTracer and Ribbon Filters

Streamtube• circular rake of particles to create a tube

• ParaView - StreamTracer and Tube Filters


Stream Tracer FilterStream Tracer FilterStreamTracer Filter

• generates streamlines in vector field from collection of seed points

• first need to set up the integrator to do the numerical integration

• next need to specify the seeds points


Example – StreamlinesExample – Streamlines


ParaView:1. open data file


2. apply StreamTracer filter to density.vtk


Filter -> Stream Tracer

3. in the Object Inspector (Properties Tab)

set “Vectors” menu to Momentum

set “Max Propagation” to Time 100

set “Initial Step Length” to Cell Length 0.1

set “Integration Direction” to Both

set “Max Steps” to 1000

set “Integrator Type” to Runge-Kutta 4

set “Seed Type” to Point Source,

Center on Bounds

set “Number of Points” to 100

AnnotationAnnotation

Annotation– used for annotating visualizations

– ParaView• Text Source

• Source -> Text

• Color Legend•“Edit Color Map” button in Display tab•“Show Color Legend” box in color legend tab of the Color Scale Editor

• Axes

• Edit -> View Settings


Example – AnnotationExample – Annotation


ParaView:

1. open data file




Filter -> Clip

3. Create a Text source

Sources -> Text

4. Turn on Color Legend

Edit Color Map for Clip in Display Tab

Color Legend tab in Color Scale Editor

select “Show Color Legend” check box

5. Turn on orientation axis

Edit -> View Settings

select “Orientation Axes” check box

Saving ImagesSaving Images


Saving Images– common formats:

• jpg (lossy)

• png (lossless)

• pdf

• tiff (lossless)

– ParaView• File -> Save Screenshot

Example – Saving ImagesExample – Saving Images


ParaView:

1. open data file




Filter -> Clip

3. save Screenshot

File -> Save Screenshot

4. set Resolution

5. set File Type to JPG

ParaView - ResourcesParaView - Resources


Tutorials– Using ParaView to Visualize Scientific Data

scv.bu.edu/documentation/tutorials/ParaView/

– ParaView Examples

scv.bu.edu/documentation/software-help/scivis/paraview_examples/index.html

-- “The Tutorial”

www.paraview.org/Wiki/The_ParaView_Tutorial

Texts– The ParaView Guide, v3 Edition, Kitware, Inc, 2006.

– The Visualization Toolkit, 4th Edition, Will Schroeder, Ken Martin, Bill Lorensen, Kitware , 2006.

Websites– www.paraview.org

– www.paraview.org/OnlineHelpCurrent/

– www.paraview.org/Wiki/ParaView

– www.kitware.com

Questions?Questions?

Tutorial survey:

- http://scv.bu.edu/survey/spring11tut_survey.html


Documents

Scientific Visualization with ParaView Robert Putnam [email protected] IS&T Scientific Visualization Tutorial – Spring 2011