Visualization Tools User Guides

The KVL supports the following software at KAUST through user training, software installations on KAUST computing resources, and direct user support. For user support, email our ticketing system: help@vis.kaust.edu.sa

Not sure which tool you need? Ask us — or start here:

Tool Best for Where you can run it
Avizo / Amira Segmentation, 3D analysis and measurement of tomography and microscopy image stacks IT Remote Workstations, local install, KVL workstations
ParaView Large-scale simulation data, tiled and immersive displays, Python scripting, in-situ via Catalyst Ibex (interactive), Shaheen III (batch only), local install
VisIt 2D/3D structured and unstructured meshes, remote parallel rendering, Python/Java control Ibex (interactive), Shaheen III (batch only), local install
Ilastik Machine-learning image segmentation, including large datasets Ibex, IT Remote Workstations, local install

Avizo

Avizo (also called Amira) is a software application which enables users to perform interactive visualization, automatic segmentation, analysis, and computation on 3D data sets such as tomography and microscopy image stacks. The Avizo interface is modelled on visual programming. Users manipulate data and module components, organized in an interactive graph representation (called Pool), or in a Tree view. Data and modules can be interactively connected together, and controlled with several parameters, creating a visual processing network whose output is displayed in a 3D viewer. With this interface, complex data can be interactively explored and analyzed by applying a controlled sequence of computation and display processes resulting in a meaningful visual representation and associated derived data.

Getting Help with Avizo

The Avizo user guide is the best place to start when trying something new with Avizo or when searching for functionality. To access it, go to Help → User's Guide in the main menu bar.

KVL Training on Avizo

Getting Access to Avizo

ParaView

ParaView is an open-source, multi-platform scientific data analysis and visualization tool that enables analysis and visualization of extremely large datasets. ParaView is both a general purpose, end-user application with a distributed architecture that can be seamlessly leveraged by your desktop or other remote parallel computing resources and an extensible framework with a collection of tools and libraries for various applications including scripting (using Python), web visualization (through ParaViewWeb), or in-situ analysis (with Catalyst). ParaView leverages parallel data processing and rendering to enable interactive visualization for extremely large datasets. It also includes support for large displays including tiled displays and immersive 3D displays with head tracking and wand control capabilities. ParaView also supports scripting and batch processing using Python. Using included Python modules, you can write scripts that can perform almost all the functionality exposed by the interactive application and much more.

Getting Help with ParaView

The ParaView user manual is the best place to start when trying something new with ParaView or when searching for functionality: ParaView User Manual

KVL Training on ParaView

ParaView on KAUST Supercomputing Resources

ParaView FAQ

Reading a series of *.nc (NetCDF) files as a time series

Combine the individual in_*.nc files into a single out.nc: 

ncrcat in_*.nc -O out.nc

ParaView won't read my NetCDF file correctly

This is usually because the time variables are not set the way ParaView expects. ParaView imports *.nc files but expects Time to be both a coordinate and a variable. Time units must be in the form <time_units> since <date>, where <time_units> is days, hours, etc.

The following adds the missing Time variable (absent from wrfout_*.nc files): 

#!/usr/bin/env python
import netCDF4 as nc
import numpy as np
 
ncf = nc.Dataset('filename', 'a')
t = ncf.createVariable('Time', 'i', ('Time',))
t.units = "hours since 2009-11-24 00:00:00"
t[:] = np.arange(t.size)
ncf.close()

VisIt

VisIt is a free, open source, platform independent, distributed, parallel, visualization tool for visualizing data defined on two- and three-dimensional structured and unstructured meshes. VisIt's distributed architecture allows it to leverage both the compute power of a large parallel computer and the graphics acceleration hardware of a local workstation. VisIt's user interface is often run locally on a Windows, Linux, or macOS desktop computer while its compute engine component runs in parallel on a remote computer. VisIt's distributed architecture allows VisIt to visualize simulation data where it was generated, eliminating the need to move the data to a visualization server. VisIt can be controlled by its Graphical User Interface (GUI), through the Python and Java programming languages, or from a custom user interface that you develop yourself. More information about VisIt can be found online at https://visit.llnl.gov/.

Getting Help with VisIt

The VisIt user manual is the best place to start when trying something new with VisIt or when searching for functionality: VisIt User Manual

KVL Training on VisIt

VisIt on KAUST Supercomputing Resources

Ilastik

Ilastik is a free and open-source tool for image segmentation. It allows users to easily leverage machine learning for segmentation. KVL supports running Ilastik on the Ibex cluster in order to process large datasets (tutorial here).

Getting Help with Ilastik

The Ilastik user manual is the best place to start when trying something new with Ilastik or when searching for functionality: Ilastik User Manual

KVL Training on Ilastik

Getting Access to Ilastik

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