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Modan2 Documentation

Welcome to Modan2’s documentation!

Modan2 is a user-friendly desktop application that empowers researchers to explore and understand shape variations through geometric morphometrics. It streamlines the entire workflow from data acquisition (2D/3D) to statistical analysis and visualization.

Contents:

Features

  • Hierarchical Data Management: Organize data into nested datasets with a clear structure

  • 2D & 3D Visualization: Integrated viewers for 2D images and 3D models with landmark plotting

  • Semi-landmark Curves: Trace curves on specimens and resample them into evenly-spaced semi-landmarks, with edge-snapping (live-wire) auto-detection

  • Statistical Analysis: Perform Principal Component Analysis (PCA), Canonical Variate Analysis (CVA), and MANOVA

  • Missing Landmark Support: Advanced handling of incomplete landmark data with shape-fitted visual estimation

  • Digitizing Aids: Dataset-wide landmark names/descriptions and a “Show Expected” guide that predicts remaining landmark positions

  • Data Import/Export: Supports various file types (TPS, NTS, Morphologika, CSV, OBJ, PLY, STL) plus a JSON+ZIP package format that bundles images and 3D models, all with drag-and-drop

  • Persistent Storage: All data and analyses saved in a local SQLite database managed by Peewee ORM

Quick Start

Installation

Download the latest version from the releases page. Package names carry the version and build number.

For Windows:

Download the installer ZIP and run the installer inside it

For macOS:

Download the DMG and drag Modan2.app to Applications

For Linux:

Download the AppImage, make it executable, and run it

Only the Windows build is well tested; see Installation for details.

Basic Usage

  1. Create a New Dataset

    Click “New Dataset” or press Ctrl+N to create a dataset for your morphometric study.

  2. Import Objects

    Drag and drop 2D images or 3D models into your dataset, or use File → Import to load landmark files (TPS, NTS).

  3. Place Landmarks

    Double-click an object to open the Object Dialog, then click on the image/model to place landmarks.

  4. Run Analysis

    Select your dataset and click “Analyze Dataset” to perform:

    • Procrustes superimposition (aligns shapes)

    • Principal Component Analysis (PCA)

    • Canonical Variate Analysis (CVA)

    • MANOVA (multivariate analysis of variance)

  5. Explore Results

    View PC plots, shape variations, and statistical outputs in the Data Exploration dialog.

Keyboard Shortcuts:

  • Ctrl+N - New Dataset

  • Ctrl+Shift+N - New Object

  • Ctrl+S - Save changes

  • Ctrl+O - Open database

  • Delete - Delete selected items

For more detailed instructions, see the User Guide.

Technology Stack

  • Language: Python 3.12+

  • GUI Framework: PyQt5

  • Core Libraries:

    • Database ORM: Peewee

    • Numerical/Scientific: NumPy, SciPy, Pandas, Statsmodels

    • 3D Graphics & Image Processing: PyOpenGL, Trimesh, Pillow, OpenCV

Indices and tables