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ParaView Mastery

Name: ParaView Mastery
Rating: 4.5 (23 reviews)

Automating postprocessing for researchers and engineers with Python scripts

Created byCesar Jimenez Navarro

Last updated 11/2025

English

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

Course content

9 sections • 42 lectures • 5h 11m total length

Presentation and course motivation7:00
Paraview environment, course material and Python terminal5:19
Filter visibility and display properties3:35
Access and modify display properties in ParaView using get display properties, hide, and show across different render views. Change attributes like color, representation type, and opacity to control visualization.
Launch script in a terminal and pass an argument2:29
Launch a Python script from a terminal and pass an argument to enable generic postprocessing without changing parameters, using a PowerShell launcher or ParaView's Python executable, and print the argument.
Remote and parallel visualization7:27
Connect to local or remote Paraview servers to use multiple CPUs for post-processing, comparing PV server and Devbox on Windows and Linux with MPI for scalable performance.

Calculator2:43
Integrate Variables and Glyphs12:34
Visualize surface pressure integration with glyphs to show direction and magnitude of forces on a wing; non-dimensionalize by dynamic pressure and reference area, compute pressure coefficients, lift and drag.
Transform4:24
Learn to use the transform filter in ParaView to translate, rotate, and scale 3D datasets, then visualize results in a single or side-by-side view with a linked camera.
Gradients, divergence, vorticity and Q-criterion6:47

Probe3:58
Create a Paraview probe to extract freestream data, access the values in Python, and support parametric studies and non-dimensionalization of lift, drag, and pressure coefficients.
Plot on line4:28
Plot on sorted lines3:04
Use the plot unsorted lines filter in ParaView to identify connected curves from unstructured data, producing closed curves for wing slice visualizations and ordering points reliably.
Stream Tracer3:42
Surface vector fields (i.e. skin fiction)4:06
Plot data on normal lines with Matplotlib22:00

Loading and handling unsteady datasets4:56
Record an animation4:59
Temporal Shift Scale4:21
Temporal Statistics2:39
Compute the mean velocity magnitude and other statistics from unsteady flow snapshots using the temporal statistics filter, then view the averaged arrays named with an _average suffix.
Particle tracer (steaklines)5:00
Use the particle tracer in ParaView to visualize the flow field by releasing seeds from a line, tracing trajectories, and observing von Karman vortices and recirculation regions.
Extract data per iteration4:20

Dataset presentation11:21
Calculation of pressure, viscous and total forces8:01
Calculation of pressure, viscous and total moments8:15
Cutplanes13:14
Streamlines6:22
Cummulative forces15:50
Orbit around the CFD render and new camera functions24:44
Learn to generate animated camera sequences in ParaView by storing views in JSON, loading them, and interpolating paths for smooth orbiting around the CFD render.

Install new libraries and modules10:44
Master how to import libraries for Paraview by using Anaconda, create and update conda environments from an environment file, and load the Python environment into a Paraview session.
Extract volumetric regions11:20
Center of pressures (COP)14:40
Learn to compute the center of pressures (COP) on a wing surface and generate an animation using the Python calculator in Paraview and matplotlib.

Requirements

Fundamentals of python programming
Familiarity with scientific data
ParaView 5.13 software installed on your machine

Description

Automate ParaView Post-Processing with Python — Save Time, Boost Insight, and Create Stunning Visuals

Do you work with CFD or FEA simulation data from tools like ANSYS Fluent, STAR-CCM+, OpenFOAM, SU2, COMSOL, Abaqus, or LS-DYNA?

Tired of repetitive post-processing and manual visualization steps?

This course teaches you how to automate ParaView workflows with Python, helping you process large datasets faster, eliminate repetitive tasks, and create professional-quality scientific visualizations.

What You’ll Learn

Automate ParaView post-processing with Python scripting
Apply advanced filters for CFD and FEA data analysis
Extract key quantities such as gradients, vorticity, and Q-criterion
Work with both steady-state and unsteady (transient) data
Create high-quality animations and presentation-ready visuals
Set up and use remote or parallel processing for large datasets

Course Structure

Introduction to ParaView and Scripting – Learn the interface, key filters, and remote visualization setup
Steady-State Data – Load, organize, and visualize simulation results efficiently
Common and Advanced Filters – Use colormaps, thresholds, gradients, and advanced field operations
Data Extraction – Generate plots, streamlines, and vector visualizations
Unsteady Data – Manage time-dependent simulations and record dynamic animations
Advanced Animations – Produce smooth, high-quality visual sequences for presentations and reports

Why Take This Course

Automate repetitive tasks and save hours of manual work
Turn complex simulation data into clear, insightful visualizations
Improve efficiency and productivity in CFD and FEA workflows
Apply skills across engineering, research, and scientific visualization
Learn from practical, real-world aerospace and engineering examples

Who This Course Is For

Engineers, researchers, and students working with simulation data
Professionals in aerospace, mechanical, and computational sciences
Anyone who wants to master ParaView scripting and streamline their analysis

Enroll Now

Learn how to automate ParaView post-processing with Python, analyze your simulation data more effectively, and create visualizations that communicate results with impact.

Who this course is for:

Engineers and Scientists
Researchers and Academics
Data Visualization Enthusiasts
Advanced ParaView Users

ParaView Mastery

What you'll learn

Explore related topics

Course content

Introduction5 lectures • 26min

Working with steady-state data3 lectures • 14min

Common filters5 lectures • 16min

Data Analysis and Manipulation Filters4 lectures • 26min

Data extraction6 lectures • 41min

Unsteady data6 lectures • 26min

Advanced animations3 lectures • 37min

Formula Student CFD Analysis7 lectures • 1hr 28min

Advanced Post-Processing3 lectures • 37min

Requirements

Description

Who this course is for: