ROMSA (Right Dihedra Method Stress Analysis) is a high-performance Python tool for determining paleostress orientations from fault-slip data.

It is a modern re-implementation of the original C++ program published by Bruno Ciscato (1994), based on the structural analysis method developed by Lisle (1987).

• 1994 (Original): Written in C++ for Unix/DOS/Windows. It introduced Object-Oriented Programming to geological stress analysis to handle the heavy computational load of evaluating ~500,000 tensors.
• 2025 (Modernization): Ported to Python 3. Using Numba (Just-In-Time compilation), this version achieves the same execution speed as C++ on modern multi-core processors while offering interactive visualisation via Matplotlib.

ROMSA solves the inverse problem of finding the stress tensor that best explains a population of faults measured in the field. It uses a comprehensive grid search rather than numerical inversion, allowing visualisation of the entire solution space and its stability.

If slickenlines (striae) on a fault represent the direction of maximum resolved shear stress, the principal compressive stress (σ1) must lie within a specific "pressure" quadrant (dihedra), and the principal extension stress (σ3) must lie in the opposing "tension" quadrant. This forms the basis of the Angelier & Mechler (1977) method.

Standard Right Dihedra methods treat σ1 and σ3 independently. Lisle (1987) introduced a kinematic constraint: a specific σ1 orientation is only valid if there exists a corresponding σ3 (perpendicular to it) that also satisfies the fault movement.

1. Scan: The program generates a grid of thousands of potential σ1 orientations on a stereonet.
2. Check: For every potential σ1, it scans all orthogonal directions to find the best possible σ3 that satisfies Lisle's constraint for the maximum number of faults.
3. Map: The result is a probability map where bright areas represent orientations consistent with the majority of the field data.

Before installing ROMSA, you only need Python installed on your computer.

1. Download the "Windows installer (64-bit)" from python.org.
   • Crucial: When installing, check the box at the bottom that says "Add Python to PATH".

1. Download the "macOS 64-bit universal2 installer" from python.org.
2. Run the installer.

Most distributions require you to install Tkinter (for the GUI) and venv (for the virtual environment) separately.

Ubuntu / Debian / Mint:

sudo apt update
sudo apt install python3 python3-pip python3-venv python3-tk

Fedora / RHEL / CentOS:

sudo dnf install python3 python3-pip python3-tkinter

Arch Linux / Manjaro:

sudo pacman -S python python-pip tk

The easiest way to get ROMSA is to download it as a ZIP file:

1. Scroll to the top of this GitHub page.
2. Click the green <> Code button.
3. Select Download ZIP.
4. Extract (Unzip) the folder to your Desktop or Documents.

Navigate to the extracted folder using your terminal:

• Windows 11: Open the extracted folder. Right-click anywhere in the empty space and select "Open in Terminal".
• Windows 10: Open the extracted folder. Hold the Shift key, Right-click in the empty space, and select "Open PowerShell window here".
• macOS: Open the extracted folder in Finder. Right-click (or Ctrl-click) inside the folder and select "New Terminal at Folder".
• Linux: Open the extracted folder in your File Manager. Right-click inside the folder (in the empty white space) and select "Open in Terminal".

Once your terminal is open in the correct folder, run the following command to install the necessary libraries:

🪟 Windows:

python -m pip install -r requirements.txt

🍎 macOS

pip3 install -r requirements.txt

🐧 Linux (Required for Virtual Environment): Note: Modern Linux blocks global pip installs. You must create a virtual environment first.

# 1. Create a virtual environment named 'venv'
python3 -m venv venv

# 2. Activate the environment
source venv/bin/activate

# 3. Install the libraries inside the environment
pip install -r requirements.txt

Run the program by pointing it to your data file:

🪟 Windows:

python romsa.py examples\data.dat

🍎 macOS:

python3 romsa.py examples/data.dat

🐧 Linux: (Make sure you have activated your environment first: source venv/bin/activate)

python3 romsa.py examples/data.dat

After calculation, an interactive window will open with a control panel at the bottom:

• Hover: Move your mouse over the stereonet to see the exact Trend / Plunge coordinates.

• Overlays (Top Row): Toggle the visibility of Fault Planes, Striae, and Stress Axes.

• Palettes (Bottom Row): Switch between colour schemes instantly.

You can control the resolution, colour palette, and default visibility of overlays directly from the terminal. This is ideal for generating publication-ready images automatically.

Example: Generate a high-res plot with all geological data visible:

Windows:

python romsa.py examples\data.dat --res high --faults --striae --axes

Mac / Linux:

python3 romsa.py examples/data.dat --res high --faults --striae --axes

ROMSA automatically generates two files in the same folder as your input data:

1. filename_plot.png: A high-resolution (300 DPI) image.

   • Note: This image captures the state defined by your CLI flags (e.g., if you run with --faults, the saved image will include fault planes).

2. filename_tensors.csv: A spreadsheet containing the calculated stress tensors sorted by probability.

The input .dat file is a plain text file compatible with the original 1994 software.

• Header (Optional): The first line can be the integer count of faults. If omitted, the program auto-detects it.
• Data: Each row represents one fault with six columns:

The interactive plot distinguishes striae based on the geometry derived from your input columns:

• White dots: Standard measurements (Normal, Dextral).
• Black dots: "Inverted" measurements (Reverse, Sinistral).

This visual distinction is particularly useful for verifying that your Vertical/Horizontal slip sense (Columns 5 & 6) produces the expected kinematic orientation.

Example data.dat:

11
10 52 4 116 1 0
54 290 53 272 1 0
55 302 35 242 1 0
40 280 28 332 1 0
85 240 6 151 -1 0
82 56 14 144 1 0
58 278 4 5 1 0
37 232 4 315 1 0
69 200 57 147 1 0
32 214 32 224 1 0
50 231 50 220 -1 0

1. Ciscato, B. (1994). Principal Stress Orientations from Faults: a C++ program. Structural Geology and Personal Computers, 325-342.
2. Lisle, R. J. (1988). ROMSA: a basic program for paleostress analysis using fault-striation data. Computers & Geosciences 14: 255-259.
3. Lisle, R. J. (1987). Principal stress orientations from faults: an additional constraint. Annales Tectonicae 1: 155-158.
4. Angelier, J. & Mechler, P. (1977). Sur une méthode graphique de recherche des contraintes principales.... Bull. Soc. Geol. France 19: 1309-1318.
5. McKenzie, D. P. (1969). The relation between fault plane solutions and the directions of the principal stresses. Bull. Seismolog. Soc. America 59: 591-601.

This project is licensed under the MIT License.

If you use ROMSA in your research, please cite both the code and the original paper:

The Code:

Ciscato, B. (2025). ROMSA: Right Dihedra Method Stress Analysis (Python) [Computer software]. https://github.com/bciscato/romsa-py

The Methodology:

Ciscato, B. (1994). Principal Stress Orientations from Faults: a C++ program. Structural Geology and Personal Computers, 325-342.

Community contributions are welcome! Feel free to submit your plots to be featured here.

Just open a Pull Request with your image added to the examples folder or simply open a new Issue and drag-and-drop your image into the description.

Fig. 1 - Example from the 1994 paper (data.dat above) rendered in the Blues colour palette. Unpublished data by Harper.