Paraview Mastery
Published 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.60 GB | Duration: 2h 45m
Published 3/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.60 GB | Duration: 2h 45m
Automating postprocessing for researchers and engineers with Python scripts
What you'll learn
Using Filters and Processing Data Programmatically
Automating Visualization Tasks
Creating and Customizing Visualizations
Working with Time-Dependent Data
Batch Processing and Remote Visualization
Requirements
Fundamentals of python programming
Familiarity with scientific data
ParaView 5.13 software installed on your machine
Description
Welcome to this comprehensive course on automating post-processing in ParaView with Python scripting! This course is designed for students, researchers, and engineers who work with complex datasets and want to streamline their workflows, automate repetitive tasks, and create visually impactful scientific visualizations.Whether you’re in aerospace CFD or another field, this course will help you unlock ParaView’s powerful capabilities and take your post-processing skills to the next level. Here's what you'll learn:Section 1: IntroductionWe’ll begin with an overview of ParaView’s interface and scripting capabilities. You’ll learn how to apply basic filters, execute scripts, and dive into remote and parallel visualization. By the end of this section, you’ll know how to set up local or remote servers and harness the power of multiple CPUs to efficiently process large datasets.Section 2: Working with Steady-State DataIn this section, we’ll focus on handling steady-state data. You’ll discover how to load datasets, manipulate the scene, and create clear and effective visualizations. We’ll also cover how to set up custom layouts using multiple tabs and windows, enabling you to organize your work environment and tailor it to your project needs.Section 3: Common FiltersFilters are at the heart of ParaView, and in this section, we’ll cover the most commonly used ones. You’ll explore colormaps for visualizing data distributions, learn thresholding techniques for filtering datasets, and use clipping to isolate specific regions of interest. These tools are essential for creating impactful visualizations.Section 4: Data Analysis and Manipulation FiltersNext, we’ll dive into advanced data analysis. You’ll learn how to use the Calculator filter to create new data fields, integrate variables over surfaces, and compute gradients, divergence, vorticity, and Q-criterion. These techniques will empower you to extract deeper insights from your data and perform detailed analyses with confidence.Section 5: Data ExtractionExtracting data is an essential step in any analysis. In this section, you’ll learn how to sample data using probes, generate line plots, and utilize the Plot On Sorted Lines filter to analyze connected curves. We’ll also delve into the Stream Tracer filter for visualizing vector fields with streamlines and demonstrate how to display surface vector fields, such as skin friction. These techniques will enable you to focus on and effectively visualize the data that matters most to your goals.Section 6: Unsteady DataWe’ll tackle time-dependent or unsteady datasets in this section. You’ll learn how to import and manage these datasets, record animations, and apply temporal filters. Additionally, you’ll master particle tracing techniques, such as streaklines, and how to extract data across iterations for thorough time-based analyses.Section 7: Advanced AnimationsFinally, we’ll explore how to create advanced animations that make your visualizations more dynamic and engaging. You’ll learn techniques like orbiting the camera around objects, applying smooth transitions between filters, and combining these methods to produce complex animations. We’ll also discuss how to add realistic renderings for a professional finish to your projects.Why Take This Course?This course is packed with practical, hands-on examples that will make you more efficient and effective at post-processing large datasets. While many examples are drawn from aerospace CFD, the skills and concepts are versatile and can be applied across engineering, scientific research, climate modeling, and more.Your input matters! If you work in a non-aerospace field, I’d love to hear your suggestions for additional topics that could address your unique challenges. Your feedback could shape future on-demand videos tailored specifically to your needs.Let’s get started on this journey to mastering ParaView scripting and transforming your post-processing workflows!
Overview
Section 1: Introduction
Lecture 1 Presentation and course motivation
Lecture 2 Paraview environment, course material and Python terminal
Lecture 3 Filter visibility and display properties
Lecture 4 Launch script in a terminal and pass an argument
Lecture 5 Remote and parallel visualization
Section 2: Working with steady-state data
Lecture 6 Loading and Handling Steady Datasets
Lecture 7 Manipulate scenes
Lecture 8 Create windows and tabs
Section 3: Common filters
Lecture 9 Color maps
Lecture 10 Clip
Lecture 11 Threshold
Lecture 12 Slice
Lecture 13 Contours (Isosurfaces)
Section 4: Data Analysis and Manipulation Filters
Lecture 14 Calculator
Lecture 15 Integrate Variables and Glyphs
Lecture 16 Transform
Lecture 17 Gradients, divergence, vorticity and Q-criterion
Section 5: Data extraction
Lecture 18 Probe
Lecture 19 Plot on line
Lecture 20 Plot on sorted lines
Lecture 21 Stream Tracer
Lecture 22 Surface vector fields (i.e. skin fiction)
Section 6: Unsteady data
Lecture 23 Loading and handling unsteady datasets
Lecture 24 Record an animation
Lecture 25 Temporal Shift Scale
Lecture 26 Temporal Statistics
Lecture 27 Particle tracer (steaklines)
Lecture 28 Extract data per iteration
Section 7: Advanced animations
Lecture 29 Orbit around an object
Lecture 30 Filter transitions
Lecture 31 Example of orbiting with transitions
Engineers and Scientists,Researchers and Academics,Data Visualization Enthusiasts,Advanced ParaView Users