fe49565651
Stem grows an 8-hex sha1 digest of the (keys-sorted) embed_args dict, so runs differing only in embed_args (e.g. UMAP n_neighbors=5 vs 15) now produce distinct figs. The stem regex and parser both accept an optional _<hash> tail so pre-hash figs still render in the runs list and compare page; legacy filename is resolved on disk fallback. Duplicate-submission check now rejects against BOTH the hashed and the legacy hashless variant so users can't accidentally duplicate an old run either. Flow additionally writes a <stem>.frames.json sidecar next to the plotly HTML (same shape as app/web/plotly_parse returns). Server prefers the sidecar when present; falls back to parsing HTML for older runs. Sidecar emission is non-critical — any failure just logs and keeps going. |
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|---|---|---|
| app | ||
| flows | ||
| .gitignore | ||
| clean.sh | ||
| makefile | ||
| pyproject.toml | ||
| README.md | ||
| requirements-frozen.txt | ||
| uv.lock | ||
Dimension Reduction Lab
A Python project exploring various dimension reduction techniques using Prefect for workflow orchestration.
Overview
This project serves as an experimental sandbox for studying dimensionality reduction and embedding algorithms within a reproducible environment. The primary goal is to evaluate and compare different techniques (like UMAP, t-SNE, PaCMAP, and TriMap) while focusing on their stability characteristics, particularly in the context of changing or drifting data distributions. By leveraging Prefect's workflow management capabilities, we can systematically analyze how these algorithms perform across arbitrary datasets, track their behavior over time, and measure their sensitivity to various hyperparameters and data perturbations.
Requirements
The project uses several key dependencies (as seen in requirements.frozen.txt):
Package Management
This project uses UV (μv) as its package manager, a fast Python package installer and resolver written in Rust. The requirements.frozen.txt file was generated using UV to ensure reproducible dependencies.
To update dependencies:
uv pip compile pyproject.toml (--all-extras) -o requirements.frozen.txt
Modifying --all-extras to include either an individual optional dependency group or all of them. See the pyproject.toml file for more information.
This project uses Prefect for workflow orchestration, for it's lightweight approach to running experiments from a UI and compatibility with single-node deployments.