introduction to opendx jon johansson academic information and communication technologies november...

Introduction to OpenDXIntroduction to OpenDX

Jon JohanssonAcademic Information and Communication

Technologies

November 20, 2006

Jon JohanssonAcademic Information and Communication

Technologies

November 20, 2006

Viz PackagesViz Packages

• OpenDX, VTK are AVS use a pipelined, component-based architecture

• a user can quickly assemble modular software components into a “finished application.”

• these systems are flexible in the sense that components can be combined in a multitude of ways, thereby allowing an application developer to accomplish a wide variety of visualization tasks

• they are extensible as they offer the means for developers to add new components to the system, thereby extending the system’s functionality

• OpenDX, VTK are AVS use a pipelined, component-based architecture

• a user can quickly assemble modular software components into a “finished application.”

• these systems are flexible in the sense that components can be combined in a multitude of ways, thereby allowing an application developer to accomplish a wide variety of visualization tasks

• they are extensible as they offer the means for developers to add new components to the system, thereby extending the system’s functionality

OpenDXOpenDX

• information on OpenDX can be found at– http://www.opendx.org/

• this site has the latest version of dx for download

• IBM has a site with older information– http://www.research.ibm.com/dx/

• information on OpenDX can be found at– http://www.opendx.org/

• this site has the latest version of dx for download

• IBM has a site with older information– http://www.research.ibm.com/dx/

http://www.opendx.org/

http://www.research.ibm.com/dx/

http://www.opendx.org/

http://www.research.ibm.com/dx/

OpenDXOpenDX

• 1991, IBM Research introduced as Visualization Data Explorer (dx)

• May 24 1999, IBM made Visualization Data Explorer (dx) open source as IBM Open Visualization Data Explorer (OpenDX)

• the last commercial version of dx was 3.1.4B

• OpenDX is now at 3.4.2

• 1991, IBM Research introduced as Visualization Data Explorer (dx)

• May 24 1999, IBM made Visualization Data Explorer (dx) open source as IBM Open Visualization Data Explorer (OpenDX)

• the last commercial version of dx was 3.1.4B

• OpenDX is now at 3.4.2

OpenDXOpenDX

• OpenDX provides a full set of tools for manipulating, transforming, processing, realizing, rendering and animating data

• allows for visualization and analysis methods based on points, lines, areas, volumes, images or geometric primitives in any combination

• OpenDX provides a full set of tools for manipulating, transforming, processing, realizing, rendering and animating data

• allows for visualization and analysis methods based on points, lines, areas, volumes, images or geometric primitives in any combination

OpenDX ArchitectureOpenDX Architecture

• dx uses a client-server execution model • the client process is the graphics user

interface:– it always runs on a workstation

• the server process does all of the computation:– it may reside on the same, or a different

machine

• dx uses a client-server execution model • the client process is the graphics user

interface:– it always runs on a workstation

• the server process does all of the computation:– it may reside on the same, or a different

machine

OpenDX ArchitectureOpenDX Architecture

Starting OpenDXStarting OpenDX

• to start the dx process: – on a Linux/Unix machine, type

•dx– on Windows click an OpenDX icon

• Start Menu -> OpenDX -> DX

• this will bring up the OpenDX Startup Window

• to start the dx process: – on a Linux/Unix machine, type

•dx– on Windows click an OpenDX icon

• Start Menu -> OpenDX -> DX

• this will bring up the OpenDX Startup Window

OpenDX InterfaceOpenDX Interface

• from the startup window we can:– import data through a wizard– run previously written visual

programs– create or edit visual programs– run the OpenDX tutorial– run sample programs

• process “startupui”

• from the startup window we can:– import data through a wizard– run previously written visual

programs– create or edit visual programs– run the OpenDX tutorial– run sample programs

• process “startupui”

OpenDX Data ImportOpenDX Data Import

• OpenDX import module will read the following data formats:– DX – Data Explorer native format– CDF (Common Data Format)

• from the National Space Science Data Center• a self-describing data abstraction for the storage and

manipulation of multidimensional data in a discipline-independent fashion.• http://nssdc.gsfc.nasa.gov/cdf/cdf_home.html

– NetCDF (network Common Data Format)• from the Unidata Program Center in Boulder, Colorado • an interface for array-oriented data access and a library that

providesan implementation of the interface• http://www.unidata.ucar.edu/packages/netcdf/

• OpenDX import module will read the following data formats:– DX – Data Explorer native format– CDF (Common Data Format)

• from the National Space Science Data Center• a self-describing data abstraction for the storage and

manipulation of multidimensional data in a discipline-independent fashion.• http://nssdc.gsfc.nasa.gov/cdf/cdf_home.html

– NetCDF (network Common Data Format)• from the Unidata Program Center in Boulder, Colorado • an interface for array-oriented data access and a library that

providesan implementation of the interface• http://www.unidata.ucar.edu/packages/netcdf/

http://nssdc.gsfc.nasa.gov/cdf/cdf_home.html


http://www.unidata.ucar.edu/packages/netcdf/









• OpenDX import module will read the following data formats:– HDF – Hierarchical Data Format (HDF version 4.1 only for

Windows)• from the National Center for Supercomputing Applications • software and file formats for scientific data management • http://hdf.ncsa.uiuc.edu/

– Image – TIFF, MIFF, GIF, RGB, R+G+B, YUV– Spreadsheet

• typically non-spatial data, for example:

• OpenDX import module will read the following data formats:– HDF – Hierarchical Data Format (HDF version 4.1 only for

Windows)• from the National Center for Supercomputing Applications • software and file formats for scientific data management • http://hdf.ncsa.uiuc.edu/

– Image – TIFF, MIFF, GIF, RGB, R+G+B, YUV– Spreadsheet

• typically non-spatial data, for example:

Date Halibut Sablefish

31-Mar-01 2.4 2.24

30-Apr-01 2.21 2.07

31-May-01 2.05 2

http://hdf.ncsa.uiuc.edu/







• OpenDX import module will read the following data formats:– General

• describe the data file with a “general array header file” which can describe a wide variety of formats for data

• use the Data Prompter tool started by the Import Data button to describe your data and create the header file

• OpenDX import module will read the following data formats:– General

• describe the data file with a “general array header file” which can describe a wide variety of formats for data

• use the Data Prompter tool started by the Import Data button to describe your data and create the header file


• the Data Prompter

• describe your data to OpenDX

• the Data Prompter with create a “.general” file which describes your data file

• the import module reads the general file

• the Data Prompter

• describe your data to OpenDX

• the Data Prompter with create a “.general” file which describes your data file

• the import module reads the general file


• the “.general” file is ascii text• it contains keyword statements that

describe important aspects of the data file– pathname to file– grid structure– data type– format– more …

• the “.general” file is ascii text• it contains keyword statements that

describe important aspects of the data file– pathname to file– grid structure– data type– format– more …

OpenDX Data ImportOpenDX Data Import• a data file might consist of ascii values, each line containing 4 values

…-8.50000000 14.72243186 48.00000000 326.96078431 -8.50000000 14.72243186 49.00000000 326.96078431 -8.50000000 14.72243186 50.00000000 326.96078431 -9.50627936 14.09363873 -50.00000000 365.66830060 -9.50627936 14.09363873 -49.00000000 365.66830060 -9.50627936 14.09363873 -48.00000000 365.66830060 …

• it’s important know how the file was written:• row major:

for( i = 0; i < nx; i++){ for( j = 0; j < ny; j++){ for( k = 0; k < nz; k++){ fprintf( outfh, "%12.8f %12.8f %12.8f %12.8f \n", x, y, z, V ); } }}

• row major is defined by the last index varying the fastest

• a data file might consist of ascii values, each line containing 4 values…

-8.50000000 14.72243186 48.00000000 326.96078431 -8.50000000 14.72243186 49.00000000 326.96078431 -8.50000000 14.72243186 50.00000000 326.96078431 -9.50627936 14.09363873 -50.00000000 365.66830060 -9.50627936 14.09363873 -49.00000000 365.66830060 -9.50627936 14.09363873 -48.00000000 365.66830060 …





• We have a data set that has regular spacings in the x, y and z directions• We don’t need to read the coordinates for each point from a file• The general header file to read in this data is:

• file = ./pot_cart.dat• grid = 101 x 101 x 101• format = ascii• interleaving = field• majority = row• header = lines 0• field = potential• structure = scalar• type = float• dependency = positions• positions = regular, regular, regular, -50.0, 1.0, -50.0, 1.0, -50.0, 1.0• end




• DX supports many techniques for generating renderable geometry from data.

• For scalar data these include: – color and opacity mapping– contours and isosurfaces– histograms– two-dimensional and three-dimensional plotting– surface deformation, etc

• For vector data– arrow plots– streamlines, streaklines, etc

• DX supports many techniques for generating renderable geometry from data.

• For scalar data these include: – color and opacity mapping– contours and isosurfaces– histograms– two-dimensional and three-dimensional plotting– surface deformation, etc

• For vector data– arrow plots– streamlines, streaklines, etc


• Visualizations can be annotated with:– ribbons– tubes– axes– glyphs– text– display of data locations, meshes and boundaries

• Data interactions are also supported: – probing– picking– arbitrary surface and volume sampling– arbitrary cutting/mapping planes

• Visualizations can be annotated with:– ribbons– tubes– axes– glyphs– text– display of data locations, meshes and boundaries

• Data interactions are also supported: – probing– picking– arbitrary surface and volume sampling– arbitrary cutting/mapping planes

OpenDX Visual Program EditorOpenDX Visual Program Editor

• Click on “New Visual Program …” in the Startup Window

• starts the VPE

• create “Visual Programs” by connecting modules

• connections represent data flow

• Click on “New Visual Program …” in the Startup Window

• starts the VPE

• create “Visual Programs” by connecting modules

• connections represent data flow


• to move a module from the palette on the left to the canvas on the right of the VPE:– click on the module to highlight it– move the cursor to the canvas – the cursor

becomes a right-angle to show where the upper left corner of the module will be

– left-click to place the module

• to move a module from the palette on the left to the canvas on the right of the VPE:– click on the module to highlight it– move the cursor to the canvas – the cursor

becomes a right-angle to show where the upper left corner of the module will be

– left-click to place the module


• input ports are at the top of the module

• output ports are at the bottom

• some modules have no input or no output ports

• double click on a module to see the interface for the module

• input ports are at the top of the module

• output ports are at the bottom

• some modules have no input or no output ports

• double click on a module to see the interface for the module


• the Import module reads data from a file

• three inputs (from left to right):– file name– the variable to read from the file

(depends on the data format)– data format (select general)

• one output– the data (as a field)

• the Import module reads data from a file

• three inputs (from left to right):– file name– the variable to read from the file

(depends on the data format)– data format (select general)

• one output– the data (as a field)


• the interface to the Import module allows you to set values

• the interface to the Import module allows you to set values

Data ImportData Import

• A big hurdle in using any visualization system can be getting the data into the package

• Once your data is in the package the data can be manipulated using the tools built into the package

• The form of the data is frequently dictated by the form of the geometry in the problem– E.g. Spherically symmetric problem results in

spherical-polar coords in the data set

• A big hurdle in using any visualization system can be getting the data into the package

• Once your data is in the package the data can be manipulated using the tools built into the package

• The form of the data is frequently dictated by the form of the geometry in the problem– E.g. Spherically symmetric problem results in

spherical-polar coords in the data set


• Each visualization package has defined a set of data types upon which the algorithms depend to function

• A well chosen data structure can permit the development powerful algorithms

• A poorly chosen data structure can hinder the performance of the package

• Each visualization package has defined a set of data types upon which the algorithms depend to function

• A well chosen data structure can permit the development powerful algorithms

• A poorly chosen data structure can hinder the performance of the package

Data ImportData Import• Data sets come at many scales and in

many formats:– Computer simulations of cellular processes– Electro-magnetic fields around the Earth and

through the Solar system– Nuclear interactions– Crystal formation– Scans of human bodies: CT, MRI, PET

• need a taxonomy for data

• Data sets come at many scales and in many formats:– Computer simulations of cellular processes– Electro-magnetic fields around the Earth and

through the Solar system– Nuclear interactions– Crystal formation– Scans of human bodies: CT, MRI, PET

• need a taxonomy for data

Data Sets – Uniform MeshData Sets – Uniform Mesh• represents data

organized in a regular array

• only need to enter the min and max values of the axes: (x0, y0) and (xmax, ymax)

• can describe the data file with another text file having a “fld” extension

• represents data organized in a regular array

• only need to enter the min and max values of the axes: (x0, y0) and (xmax, ymax)

• can describe the data file with another text file having a “fld” extension

Data Sets – Rectilinear MeshData Sets – Rectilinear Mesh• represents data

organized on orthogonal axes, but the spacing between data points may be irregular

• need to provide lists of the x and y coords and the grid is constructed

• represents data organized on orthogonal axes, but the spacing between data points may be irregular

• need to provide lists of the x and y coords and the grid is constructed

Data Sets – Irregular MeshData Sets – Irregular Mesh• less symmetry than

uniform or rectilinear meshes

• provide the coordinates of all the points in the mesh

• the connectivity can be inferred

• less symmetry than uniform or rectilinear meshes

• provide the coordinates of all the points in the mesh

• the connectivity can be inferred

Data Sets – Structured MeshData Sets – Structured Mesh• the meshes above are all classified as “Structured”

• the points can be characterized by dimensions along some axes

• the grid below is 7x3 – that’s enough to infer the connectivity

• the meshes above are all classified as “Structured”

• the points can be characterized by dimensions along some axes

• the grid below is 7x3 – that’s enough to infer the connectivity

Data Sets – Unstructured MeshData Sets – Unstructured Mesh

• represents data points that aren’t organized in a regular pattern• must provide all coordinates for points as well as explicit connection

information• data and its description in a file with the extension “inp”• this is referred to as “Unstructured Cell Data”• the 12 points below can be connected in many ways, for example:

5 triangles and 4 quads 1 triangle and 6 quads 13 triangles

• represents data points that aren’t organized in a regular pattern• must provide all coordinates for points as well as explicit connection

information• data and its description in a file with the extension “inp”• this is referred to as “Unstructured Cell Data”• the 12 points below can be connected in many ways, for example:

5 triangles and 4 quads 1 triangle and 6 quads 13 triangles

Data Sets – Scattered PointsData Sets – Scattered Points

• only concerned with the points in space – not with the connections

• read the points in as a list – connections are implied P0 → P1 → … → Pn-1

• points in 3D have 1D connections

• use either .fld or .inp – the .fld is probably easier

• only concerned with the points in space – not with the connections

• read the points in as a list – connections are implied P0 → P1 → … → Pn-1

• points in 3D have 1D connections

• use either .fld or .inp – the .fld is probably easier

Data Sets – Important ParametersData Sets – Important Parameters

• nspace – number of spatial coordinates per node: (x, y, z) nspace = 3

• ndim – number of grid dimensions (also called the computational dimension). This is the space of the connections. For scattered points ndim = 1.

• dims – an array of grid dimensions {nx, ny, nz}

• nspace – number of spatial coordinates per node: (x, y, z) nspace = 3

• ndim – number of grid dimensions (also called the computational dimension). This is the space of the connections. For scattered points ndim = 1.

• dims – an array of grid dimensions {nx, ny, nz}

OpenDX Data ModelOpenDX Data Model

• Fields are the fundamental objects in the Data Explorer data model.

• A field represents a mapping from some domain to some data space.

• The domain of the mapping is specified by a set of positions and (generally) a set of connections that allow interpolation of data values for points between positions.

• Fields are the fundamental objects in the Data Explorer data model.

• A field represents a mapping from some domain to some data space.

• The domain of the mapping is specified by a set of positions and (generally) a set of connections that allow interpolation of data values for points between positions.


• Positions represent what can be thought of as (and often really are) locations in space; the data are the values associated with the space of the positions.

• The mapping at all points in a domain (not just those specified by the given positions) is represented implicitly by specifying that the data are dependent on (located at) the sample points or on the connections between points.

• Positions represent what can be thought of as (and often really are) locations in space; the data are the values associated with the space of the positions.

• The mapping at all points in a domain (not just those specified by the given positions) is represented implicitly by specifying that the data are dependent on (located at) the sample points or on the connections between points.


• the positions and data are said to be components of a field, and every field must contain at least a "positions" component and a "data" component. Fields may also contain other components (e.g., "connections").

• An OpenDX field consists of data and the additional components needed to describe that data so that OpenDX can process it.

• the positions and data are said to be components of a field, and every field must contain at least a "positions" component and a "data" component. Fields may also contain other components (e.g., "connections").

• An OpenDX field consists of data and the additional components needed to describe that data so that OpenDX can process it.


• If your data is basically a number of arrays you can use the General Array Importer

• To import data through the General Array Importer, you must be able to answer the following questions:

• If your data is basically a number of arrays you can use the General Array Importer

• To import data through the General Array Importer, you must be able to answer the following questions:


• What are the independent and dependent variables? – Scalar field and positions?– independent variable constitute the "positions"

component of a data field

• What is the dimensionality of the positions and data components ?– 1-D 2-D 3-D …

• What are the independent and dependent variables? – Scalar field and positions?– independent variable constitute the "positions"

component of a data field

• What is the dimensionality of the positions and data components ?– 1-D 2-D 3-D …


• How is the independent variable (the set of positions) to be described? – regular grid (which can be completely

described by an origin and a set of deltas) – an explicit list (which may or may not be part

of the data file)? – E.g. data measurements might be on a grid of

1-degree increments in latitude and 5-degree increments in longitude

• How is the independent variable (the set of positions) to be described? – regular grid (which can be completely

described by an origin and a set of deltas) – an explicit list (which may or may not be part

of the data file)? – E.g. data measurements might be on a grid of

1-degree increments in latitude and 5-degree increments in longitude

OpenDX Data TypesOpenDX Data Types

• How are the positions connected to one another?– Are they connected?

• For example, a regular grid of positions might be connected by a regular grid of connections (lines, quads, or cubes). The connections specify how data values should be interpolated between positions. Positions that are explicitly specified (i.e., not regular) can also be connected by a regular grid of connections (e.g., if the grid is deformed, or warped)

• How are the positions connected to one another?– Are they connected?

• For example, a regular grid of positions might be connected by a regular grid of connections (lines, quads, or cubes). The connections specify how data values should be interpolated between positions. Positions that are explicitly specified (i.e., not regular) can also be connected by a regular grid of connections (e.g., if the grid is deformed, or warped)

OpenDX Data TypesOpenDX Data Types

OpenDX Data TypesOpenDX Data Types• top row represent surfaces• bottom row represent volumes• the three types of grid are (left to right)

– irregular (irregular positions, irregular connections),

– deformed regular (irregular positions, regular connections)

– regular (regular positions, regular connections),

• top row represent surfaces• bottom row represent volumes• the three types of grid are (left to right)

– irregular (irregular positions, irregular connections),

– deformed regular (irregular positions, regular connections)

– regular (regular positions, regular connections),


• What is the format of the stored data values– ASCII or binary? – floating point, integer, signed or unsigned

byte, etc.?

• What is the order of the data items with respect to the grid? – column major (first index varies fastest)– row major (last index varies fastest)

• What is the format of the stored data values– ASCII or binary? – floating point, integer, signed or unsigned

byte, etc.?

• What is the order of the data items with respect to the grid? – column major (first index varies fastest)– row major (last index varies fastest)


• Are the data dependent on "positions" or on "connections"? – i.e. are the data values associated one-to-one

with positions or with the connections between positions?

• Data associated with connections are often referred to as "cell-centered"

• Are the data dependent on "positions" or on "connections"? – i.e. are the data values associated one-to-one

with positions or with the connections between positions?

• Data associated with connections are often referred to as "cell-centered"


• What kind of embedded text (comments, etc.) in the data file must be "skipped" when the data values are read– # of lines of header?– # of bytes of header?

• What kind of embedded text (comments, etc.) in the data file must be "skipped" when the data values are read– # of lines of header?– # of bytes of header?

Importing Data to OpenDXImporting Data to OpenDX• A field can be specified by an ascii header file which describes

the data in your data file• Data file BField_10x10x10_.5.dat

• A field can be specified by an ascii header file which describes the data in your data file

• Data file BField_10x10x10_.5.dat!! Magnetic field due to a coil with:! rCoil = 4.000000e+006 m! ICoil = 1.500000e+009 A! rEarth = 6.371000e+006 m!! Grid parameters:! xMin = -10.000000 Re xMax = 10.000000 Re dx = 0.500000 Re nx = 41! yMin = -10.000000 Re yMax = 10.000000 Re dy = 0.500000 Re ny = 41! zMin = -10.000000 Re zMax = 10.000000 Re dz = 0.500000 Re nz = 41!! The data are in the order:! x y z Bx By Bz!! x, y, z are measured in Earth radii! Bx, By, Bz have units of microTesla (10^-6 T).!

-10.000000 -10.000000 -10.000000 -5.614274e-003 -5.614274e-003 -8.609813e-006-9.500000 -10.000000 -10.000000 -5.792536e-003 -6.097407e-003 -2.076287e-004-9.000000 -10.000000 -10.000000 -5.950169e-003 -6.611299e-003 -4.290995e-004-8.500000 -10.000000 -10.000000 -6.081721e-003 -7.154966e-003 -6.732067e-004

!! Magnetic field due to a coil with:! rCoil = 4.000000e+006 m! ICoil = 1.500000e+009 A! rEarth = 6.371000e+006 m!! Grid parameters:! xMin = -10.000000 Re xMax = 10.000000 Re dx = 0.500000 Re nx = 41! yMin = -10.000000 Re yMax = 10.000000 Re dy = 0.500000 Re ny = 41! zMin = -10.000000 Re zMax = 10.000000 Re dz = 0.500000 Re nz = 41!! The data are in the order:! x y z Bx By Bz!! x, y, z are measured in Earth radii! Bx, By, Bz have units of microTesla (10^-6 T).!

-10.000000 -10.000000 -10.000000 -5.614274e-003 -5.614274e-003 -8.609813e-006-9.500000 -10.000000 -10.000000 -5.792536e-003 -6.097407e-003 -2.076287e-004-9.000000 -10.000000 -10.000000 -5.950169e-003 -6.611299e-003 -4.290995e-004-8.500000 -10.000000 -10.000000 -6.081721e-003 -7.154966e-003 -6.732067e-004

Importing Data to OpenDXImporting Data to OpenDX

• file = C:/Courses/DataSets/BField/BField_10x10x10_.5_B_col.dat• grid = 41 x 41 x 41• format = ascii• interleaving = field• majority = column• header = lines 18• field = density• structure = 3-vector• type = float• dependency = positions• positions = regular, regular, regular, -10.0, 0.5, -10.0, 0.5, -10.0, 0.5

• end

• file = C:/Courses/DataSets/BField/BField_10x10x10_.5_B_col.dat• grid = 41 x 41 x 41• format = ascii• interleaving = field• majority = column• header = lines 18• field = density• structure = 3-vector• type = float• dependency = positions• positions = regular, regular, regular, -10.0, 0.5, -10.0, 0.5, -10.0, 0.5

• end

Importing Data to OpenDXImporting Data to OpenDX

• For a list of header file keywords see: – OpenDX QuickStart Guide 5.3, Page 85, and– OpenDX User’s Guide – Appendix B

• header – indicates how many # lines at the top of the file to skip before reading the data

• majority – row or column• positions – gives the origin and delta for each axis of the grid.

• interleaving – indicates how several data sets are interleaved. • layout – describes how the data are formatted.

– layout = skip1, width1, skip2, width2, …• skip – # of bytes to skip before reading the data value• width – # of bytes to read for the data value

• For a list of header file keywords see: – OpenDX QuickStart Guide 5.3, Page 85, and– OpenDX User’s Guide – Appendix B

• header – indicates how many # lines at the top of the file to skip before reading the data

• majority – row or column• positions – gives the origin and delta for each axis of the grid.

• interleaving – indicates how several data sets are interleaved. • layout – describes how the data are formatted.

– layout = skip1, width1, skip2, width2, …• skip – # of bytes to skip before reading the data value• width – # of bytes to read for the data value


• create a program by dragging from the output port of one module to the input of another module

• the data types for the ports must be compatible to form the connection

• the connection is represented as a line

• create a program by dragging from the output port of one module to the input of another module

• the data types for the ports must be compatible to form the connection

• the connection is represented as a line


• create a simple program– read in a data file– create colors for the data– render the data

• get a sample data set from– http://sciviz.aict.ualberta.ca– Bumps.dat– Bumps.general

• create a simple program– read in a data file– create colors for the data– render the data

• get a sample data set from– http://sciviz.aict.ualberta.ca– Bumps.dat– Bumps.general

http://sciviz.aict.ualberta.ca/



• the data set is 2d

• get a “flat” image

• the data set is 2d

• get a “flat” image


• try the RubberSheet module

• set the Scale parameter to 5

• try the RubberSheet module

• set the Scale parameter to 5

Our Data SetOur Data Set

• Consider the electric potential due to a dielectric cylinder introduced into a constant electric field E0

• the parameters I used are:– E0 = 50 V/m– dielectric constant = 5– Rcyl = 10 m– -50 m ≤ x, y, z ≤ 50 m

• Consider the electric potential due to a dielectric cylinder introduced into a constant electric field E0

• the parameters I used are:– E0 = 50 V/m– dielectric constant = 5– Rcyl = 10 m– -50 m ≤ x, y, z ≤ 50 m

OpenDX Data ImportOpenDX Data Import• a data file might consist of ascii values, each line containing 4 values

…-8.50000000 14.72243186 48.00000000 326.96078431 -8.50000000 14.72243186 49.00000000 326.96078431 -8.50000000 14.72243186 50.00000000 326.96078431 -9.50627936 14.09363873 -50.00000000 365.66830060 -9.50627936 14.09363873 -49.00000000 365.66830060 -9.50627936 14.09363873 -48.00000000 365.66830060 …




• a data file might consist of ascii values, each line containing 4 values…

-8.50000000 14.72243186 48.00000000 326.96078431 -8.50000000 14.72243186 49.00000000 326.96078431 -8.50000000 14.72243186 50.00000000 326.96078431 -9.50627936 14.09363873 -50.00000000 365.66830060 -9.50627936 14.09363873 -49.00000000 365.66830060 -9.50627936 14.09363873 -48.00000000 365.66830060 …





• the connections between the points are inferred when you tell OpenDX that the data are “row major”

• these are Cartesian connections

• the connections between the points are inferred when you tell OpenDX that the data are “row major”

• these are Cartesian connections


• you can also work in non-Cartesian coordinates

• the grid is row major in cylindrical coordinates (r, phi, z)

• write Cartesian coordinates in the file and connections are inferred from the cylindrical grid

• you can also work in non-Cartesian coordinates

• the grid is row major in cylindrical coordinates (r, phi, z)

• write Cartesian coordinates in the file and connections are inferred from the cylindrical grid


• Start with a FileSelector module to browse to the general file describing the data set and connect it to an import module which actually does the reading

• Double click on the FileSelector to get a widget to browse the file system

• When the data is in the package we can start applying algorithms to it and look for interesting features

• Start with a FileSelector module to browse to the general file describing the data set and connect it to an import module which actually does the reading

• Double click on the FileSelector to get a widget to browse the file system

• When the data is in the package we can start applying algorithms to it and look for interesting features

Components of the visualizationComponents of the visualization

• Isovalues of the electric potential• The lower slice shows the electric potential

with contour lines to give a sense of the shape change close to the cylinder– Use a slab module to extract a slice of the

potential field– Use the Isosurface module to extract contour

lines at values• -1750, -1250, -750, -250, 250, 750, 1250, 1750 volts

• Isovalues of the electric potential• The lower slice shows the electric potential

with contour lines to give a sense of the shape change close to the cylinder– Use a slab module to extract a slice of the

potential field– Use the Isosurface module to extract contour

lines at values• -1750, -1250, -750, -250, 250, 750, 1250, 1750 volts


• In the Slab module set the parameters:– dimension: “z”– position: 0– thickness: (0 or 1)

• this is the default

• The AutoColor module generates a color map so that we have something to see

• In the Slab module set the parameters:– dimension: “z”– position: 0– thickness: (0 or 1)


• The AutoColor module generates a color map so that we have something to see


• Take the output of the Slab module and attach it to the input of an Isosurface module– The 2D slab data will result in contour lines– Set the isovalues at

• -1750, -1250, -750, -250, 250, 750, 1250, 1750 volts

• The contour lines are then passed to a Tube module– Set the diameter of the tube to 1.0

• Take the output of the Slab module and attach it to the input of an Isosurface module– The 2D slab data will result in contour lines– Set the isovalues at

• -1750, -1250, -750, -250, 250, 750, 1250, 1750 volts

• The contour lines are then passed to a Tube module– Set the diameter of the tube to 1.0


• Electric field lines

• The middle slice is color mapped to the magnitude of the electric field and shows some field lines– The lines are diverted in the region of the cylinder

• Use the Gradient module and the Compute module to calculate the elctric field from the electric potential

E = -

• Electric field lines

• The middle slice is color mapped to the magnitude of the electric field and shows some field lines– The lines are diverted in the region of the cylinder

• Use the Gradient module and the Compute module to calculate the elctric field from the electric potential

E = -


– Use a Slab module to extract a slice of the electric field

– Use the Streamline module to extract contour lines at values• The Streamline module needs the vector field as

one input, and a set of seed points as the next input

– Use the Tube module to produce lines with some thickness

– Use a Slab module to extract a slice of the electric field

– Use the Streamline module to extract contour lines at values• The Streamline module needs the vector field as

one input, and a set of seed points as the next input

– Use the Tube module to produce lines with some thickness


• Use the Compute module after the gradient to negate the vector components

• In the Compute module set “expression” to

[-a.x, -a.y, -a.z]

• In Slab set– dimension: “z”– position: 50– thickness: (0 or 1)


• Use the Compute module after the gradient to negate the vector components

• In the Compute module set “expression” to

[-a.x, -a.y, -a.z]

• In Slab set– dimension: “z”– position: 50– thickness: (0 or 1)



• To calculate streamlines connect the Electric Field (output of Compute) to the left input of the Streamlines module

• Use another Slab module to extract a line of points to use as seeds for the stream line– Dimension: “x”– Position: 0

• Use Reduce to decrease the number of points by 4

• Use Tube with diameter 1.0

• To calculate streamlines connect the Electric Field (output of Compute) to the left input of the Streamlines module

• Use another Slab module to extract a line of points to use as seeds for the stream line– Dimension: “x”– Position: 0

• Use Reduce to decrease the number of points by 4

• Use Tube with diameter 1.0


• The top slice shows vector glyphs at some grid points of the electric field– The glyphs show the direction of the field– The size of the glyphs is scaled to the

magnitude of the field

• The top slice shows vector glyphs at some grid points of the electric field– The glyphs show the direction of the field– The size of the glyphs is scaled to the

magnitude of the field


• Insert a Reduce module and a Glyph module between Slab and Collect

• The Slab module parameters:– Dimension: “z”– Position: 100

• The Reduce module has – Factor: 4.0

• In the Glyph module– Type: “rocket”– Shape: 1.0– Scale: 0.15– Ratio: 0.1

• Insert a Reduce module and a Glyph module between Slab and Collect

• The Slab module parameters:– Dimension: “z”– Position: 100

• The Reduce module has – Factor: 4.0

• In the Glyph module– Type: “rocket”– Shape: 1.0– Scale: 0.15– Ratio: 0.1


• We have applied some visualization techniques to the data and created 3 slices

• pretty, but what does it mean??

• this lacks context• need some information to

help the viewer understand what we are looking at

• We have applied some visualization techniques to the data and created 3 slices

• pretty, but what does it mean??

• this lacks context• need some information to

help the viewer understand what we are looking at


• Annotations – add these to provide the context for the visualization

• ShowBox lets the viewer know the volume of space occupied by the data

• Text: titles, labels – explain a bit• Axes provide orientation and scale• ColorBar – shows how the numbers are mapped

to color• Draw the cylinder so we see the cause of all the

trouble

• Annotations – add these to provide the context for the visualization

• ShowBox lets the viewer know the volume of space occupied by the data

• Text: titles, labels – explain a bit• Axes provide orientation and scale• ColorBar – shows how the numbers are mapped

to color• Draw the cylinder so we see the cause of all the

trouble


• The ShowBox module draws a box around the extents of the data set– Use a Tube module to get

nicely rendered lines

• Caption modules allow you to place text in the 2D plane of the screen– Set the text and location in

the interface

• The ShowBox module draws a box around the extents of the data set– Use a Tube module to get

nicely rendered lines

• Caption modules allow you to place text in the 2D plane of the screen– Set the text and location in

the interface


• A very useful annotation in this visualization is some indication of where the cylinder actually is– It is, after all, the

source of all the disruption in the field

• A very useful annotation in this visualization is some indication of where the cylinder actually is– It is, after all, the

source of all the disruption in the field


• Use the Construct module to create a line– Origin: {[0 0 -50]}– Deltas: {[0 0 1]}– Counts: [1 1 101]– Data: {1}

• The Tube module creates a cylinder around the line– Diameter: 20.0– Ngon: 25

• The Color module does just that– Color: “purple”– Opacity: 0.3

• Use the Construct module to create a line– Origin: {[0 0 -50]}– Deltas: {[0 0 1]}– Counts: [1 1 101]– Data: {1}

• The Tube module creates a cylinder around the line– Diameter: 20.0– Ngon: 25

• The Color module does just that– Color: “purple”– Opacity: 0.3


• When we put it all together and select the camera angle that we want we hopefully have what we want …

• My goals– Show a variety of techniques that I can apply

to this data set– Provide enough annotation to orient the

viewer– Make it look nice

• When we put it all together and select the camera angle that we want we hopefully have what we want …

• My goals– Show a variety of techniques that I can apply

to this data set– Provide enough annotation to orient the

viewer– Make it look nice

DebuggingDebugging

• Debugging• Sometimes things aren’t working and you just

don’t know why• OpenDX’s equivalent of the “print” statement is

the Describe module• Attach the Describe module to the output port of

any module that is providing a field and Describe will give you a summary of what the module is providing in the Message Window.

• Debugging• Sometimes things aren’t working and you just

don’t know why• OpenDX’s equivalent of the “print” statement is

the Describe module• Attach the Describe module to the output port of

any module that is providing a field and Describe will give you a summary of what the module is providing in the Message Window.

DebuggingDebugging

Scientific VisualizationScientific Visualization

• lots of info on the web

• we have some introductory pages at– http://sciviz.aict.ualberta.ca

• lots of info on the web

• we have some introductory pages at– http://sciviz.aict.ualberta.ca



introduction to opendx jon johansson academic information and communication technologies november...

Documents

data file

following data formats

import data button

data prompter tool

arrayoriented data access

file formats

dx process

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