Claude Skill MartBrowse skillsQuick linesLearn by videoTerminal guideWhat is a Skill?
 
← Back to list

OpenPIV Flow Field Analysis

Extract, validate and post-process velocity fields from PIV image pairs, including vorticity, strain rate and turbulence statistics.

Data & AnalyticsAdvanced★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Cross-correlates PIV image pairs to produce 2D velocity fields plus signal-to-noise maps.
  • Validates vectors (S2N, global range, local median) and replaces outliers by interpolation.
  • Covers multi-pass window deformation via windef.PIVSettings, dynamic masking, smoothn smoothing and physical-unit scaling.
  • Computes vorticity, the 2D strain-rate tensor, RMS and TKE, and plots vector/magnitude fields.
  • Ships a CLI (scripts/runner.py), an example checker (scripts/run_example.py) and a PIVAnalyzer helper.

Who it's for

  • Experimental fluid-dynamics researchers and grad students processing PIV or flow-visualization data.
  • Anyone tuning window size, overlap and S2N thresholds who wants defensible defaults.
  • Users burned by OpenPIV's API gotchas: px/frame vs px/s units, masking return values, vorticity sign after transform_coordinates.

Example uses

  1. "Process frame_a.bmp / frame_b.bmp at dt=0.02 s and save vectors.txt plus an overlaid vector plot."
  2. "This jet has strong velocity gradients" → configure a 64→32→16 multi-pass run with windef.
  3. "From results/params.npz, compute vorticity and TKE with correct grid spacing and plot them."

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/openpiv/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/openpiv folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/openpiv/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/scientific-agent-skills && mkdir -p ~/.claude/skills && cp -r /tmp/scientific-agent-skills/skills/openpiv ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Confirm Python 3.10+ is available: python --version.
  2. Install the library: uv pip install "openpiv==0.25.4" (numpy, scipy, scikit-image and matplotlib come along).
  3. Clone the repo: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  4. Create the skills folder: mkdir -p ~/.claude/skills
  5. Copy the skill in: cp -r scientific-agent-skills/skills/openpiv ~/.claude/skills/
  6. Restart Claude Code and ask something like "analyze this PIV image pair".
  7. Smoke-test the install: python ~/.claude/skills/openpiv/scripts/run_example.py --output_dir /tmp/openpiv-demo
View source on GitHub ↗License: MIT