ptapplot

A python library for making pressure tap plots

Click the images to view interactive Plotly visualizations

Plot Type	Preview
2D Line Plot
2D Needle Plot
3D Dot Plot

The data for these demos was obtained from https://autocfd.org/

Installation

# Clone the repository
git clone https://github.com/PaulENorman/ptapplot.git
cd ptapplot

# Install in editable mode
pip install -e .

Usage Flow

2D Line Plots

1. Source Configuration: Define your vehicle image, physical extents, and CSV tap data in a .json file.
2. Preprocessing: (Optional) Calculate surface normals.
3. Rendering: Generate the interactive HTML Plotly visualization.

# 1. Prepare (Optional if running plot directly)
ptap-2d-prep demo_data/drivAer_lineplot/drivAer_top.json

# 2. Render plot
ptap-2d-plot demo_data/drivAer_lineplot/drivAer_top_complete.json

Note: ptap-2d-plot will automatically trigger the prep step if normals are missing from the configuration.

3D Dot Plots (Geometry Overlay)

1. Source Configuration: Define paths to your STL geometry, tap positions, and results CSVs in a .json file.
2. Rendering: Generate a 3D Plotly scene with side-by-side comparison and synced cameras.

ptap-3d-plot demo_data/drivAer_dotplot/dotplot_config.json

2D Needle Plots

1. Source Configuration: Same as Line Plots (normals auto-generated if missing).
2. Rendering: Generates a plot with individual $C_p$ bars at each tap location.

ptap-needle-plot demo_data/drivAer_needleplot/needleplot_config.json

Needle plots show individual bars instead of a connected line. Positive $C_p$ (pressure) points inward toward the body, negative $C_p$ (suction) points outward. Multiple series are offset perpendicular to the normal for clarity. Note that the needles are more or less normal to the adjacent normal y-axes, not the exact surface at that point (although these are close).