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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, X1Y1, Morphologika, 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

Create a New Dataset

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

Drag and drop 2D images or 3D models onto your dataset’s object table, or use Data → Import (Ctrl+I) to load a landmark file (TPS, NTS, X1Y1, Morphologika) as a new dataset.
Place Landmarks

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

Select your dataset and click Analyze (Ctrl+G) to perform:
- Superimposition (Procrustes or Bookstein; aligns shapes)
- Principal Component Analysis (PCA)
- Canonical Variate Analysis (CVA)
- MANOVA (multivariate analysis of variance)
Explore Results

Select the analysis in the tree to see its PCA, CVA (with classification accuracy) and MANOVA results; on the PCA tab, click Data Exploration for interactive plots and shape variations, or Analysis Details for the result tables.

Keyboard Shortcuts:

Ctrl+N - New Dataset
Ctrl+Shift+N - New Object
Ctrl+S - Save changes
Ctrl+I - Import
Ctrl+G - Analyze
Delete - Clear the selected cells in the object table

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