Each 2DMS sample is a large 2D map. Comparing many samples, for example which ones differ or whether they can be told apart, needed code. So the analysis methods were only available to whoever could write and run that code. To allow for wider use of these methods, I developed a desktop application that lets users load, explore and classify sets of samples without writing code.
Data
Load a set of samples and their labels, derive new labels from existing ones, and choose which samples each analysis uses.
Exploration
Explore samples with PCA, LDA and t-SNE projections, k-means and hierarchical clustering, sample correlation matrices, and per-pixel F-statistic heatmaps.
Classification
Build and validate classifiers step by step, with built-in checks against common validation mistakes such as test data leaking into training.
Custom
Assemble custom analyses from drag-and-drop blocks, including user-written Python.
The application also:
- Exports figures, tables, and notebooks that reproduce the analysis in standard Python.
- Runs on Windows and macOS, with automatic updates.
- Is accompanied by comprehensive analysis to establish best practices and reliable default settings.
- Connects to the wider Verdel data ecosystem.
