ParaView 4.2 available for download

ParaView 4.2.0 is now available to download. The complete list of over 200 issues resolved for this release can be found the ParaView Bug Tracker. Some of major highlights of this release are as follows:

 

Introducing ParaView Cinema

 

The idea behind Cinema is to process large data in either batch mode or in-situ using Catalyst to produce smaller data products which could then be viewed in a Web environment while allowing some interactivity and exploration freedom. This new framework is now part of ParaView as additional Python modules will allow dynamic and interactive data exploration within a web environment.

 

Expanded Properties panel

 

Continuing the process of avoiding users to have to switch between panels, which started with combining the Properties and Display panels into one, in 4.2 the View properties are now accessible from the Properties panel itself. Of course, some users may still prefer to have separate panels for each. For those, we have added a mode to customize this as well.

 

Application Settings

 

The infrastructure for managing user preferences and application settings was refactored from ground up. You can not only only change the configuration options previously exposed through the Settings dialog, but also change the default values for properties for any pipeline module including readers, filters, views and displays.

 

 

Not to be left behind, the Settings dialog was also redesigned to follow the now increasingly ubiquitous panel design with default/advanced view modes and searching capabilities.

 

 

Improved Python scripting and tracing

 

The Python tracing infrastructure received a much needed facelift in this release. Several changes to the underpinnings of the ParaView application logic now make it possible for sharing application logic between the graphical and Python-based applications. Thus, performing operations such as setting up color maps, rescaling color maps, creating views and displays, initializing filter defaults are now consistent between the two modes. Furthermore, tracing was made more robust are reliable to include working with color maps, multiple views, etc. Multiple tracing modes allow you to control the trace verbosity, making tracing a useful tool in learning ParaView’s Python API.

 

Improved NumPy integration

 

For users of Programmable Filter, Programmable Source, scripting become easier with improved NumPy integration. Writing NumPy expressions that work with distributed and/or composite datasets is now greatly simplified. Refer to the series of blog posts for more details starting with Improved VTK – numpy integration. Improved NumPy support also means improvements to Python Calculator and Find Data mechanism. For the first time, global operations like max(TEMP), min(Pres) are supported and work across ranks and data blocks.

 

Additional color legend options

 

The color legend has a slimmer default width when in the vertical orientation. The ranges are now displayed in scientific notation format, which can be customized, and have been moved to the same side as the intermediate numeric labels. Optionally, the numeric labels and tick marks can now be moved to the left side. Additionally, justification options for the title have been added (left, centered, and right). Tick marks, tick labels, and range labels may be independently turned off if so desired. All settings for color legends can be saved as custom defaults using the new settings capabilities described under Application Settings above.

 

User’s guide

 

The ParaView Book (or User’s guide) is being updated quite extensively. Updated version of the pdf as well as the printed book will be available soon.

 

ParaView Catalyst improvements

 

The ParaView Catalyst library can now be initialized without all processes by passing in the desired communicator to be used. The ParaView Catalyst script pipeline is now read only by process 0 and broadcast to all of the other processes.

 

ParaView Catalyst Live

 

ParaView Catalyst is a library that adds ParaView analysis and visualization capabilities to a simulation program. Furthermore, Catalyst can exchange data with a remote ParaView enabling easy inspection of simulation status and modification of analysis and visualization parameters. We call this connection ParaView Catalyst Live. For more information about Catalyst Live see the Introduction to ParaView Catalyst Live blog post.

 

ParaView Web improvement

 

The main ParaViewWeb application had a facelift with new features and capabilities. It is becoming more flexible and getting closer to the actual ParaView Qt application UI philosophy.

 
Blog posts
 
As an experiment, we have been writing blog posts documenting new featrues as they are developed — something we will continue to do in future to keep the community updated and get early feedback. Here are some of the posts that covers features that went into this release.
 
  1. Paraview's View Settings is moving to the Properties Panel

  2. Why is ParaView using all that memory?

  3. ParaView Catalyst Editions: What Are They?

  4. New in ParaView: Settings UI

  5. New in ParaView: Specular highlights

  6. New in ParaView: Color bar placement

  7. New in ParaView: Specifying custom default values

  8. New in ParaView: Customizing the Properties panel — single panel or multiple tabs?

  9. New in ParaView: Rendering information in Render Views

  10. New in ParaView: Easy saving of custom defaults in ParaView

  11. ParaView: Python View is now more versatile

  12. New in ParaView: Python Trace On-the-fly

  13. New in ParaView: Histogram View

  14. ParaView: Improvements to Python script editors

  15. ParaView Trace Options: Controlling trace verbosity

  16. Slice Along a Polyline

  17. ParaViewWeb: Using ParaView's Visualization and Data Analysis Capabilities within Web Applications

  18. Updating the ParaView User's Guide

  19. ParaView Cinema: An Image-Based Approach to Extreme-Scale Data Analysis

  20. Introduction to ParaView Catalyst Live

4 Responses to ParaView 4.2 available for download

  1. Jean Favre says:

    I love it. Just on time for me to teach the next tutorial. Thanks.

  2. Will Schroeder says:

    Wow! All those ingested coffee beans seem to be working…

  3. Jean Favre says:

    I am certain that you meant to write “Writing NumPy expressions that work with distributed and/or composite datasets is NOW greatly simplified”.

  4. Utkarsh Ayachit says:

    Oops! Thanks Jean, I’ve just fixed it. You won’t believe how commonly I mistype “now” and “not”. I think my fingers really don’t trust me :).

Questions or comments are always welcome!