Lightweight utilities for free-association processing: cleaning, embedding, projection, clustering, and label inference.
Project description
freeassoc
Lightweight utilities for processing free-association responses.
Features
- Clean short text responses
- Average and manage embeddings
- Grouping / hierarchical clustering
- Projections (classical MDS, UMAP, PaCMAP)
- Label-frequency matrices and a small cross-validated OLS report
Quick start
-
Create and activate a virtual environment.
-
Install requirements:
pip install freeassoc
Development & tests
- The project uses a
src/layout. When running tests from the repo root, make the package importable with PYTHONPATH:
PYTHONPATH=src python -m pytest -q
Examples
- See
examples/simple_df_example.pyfor a quick runnable demonstration of embedding, caching, and label inference.
Status
- Work in progress. Use at your own risk;
Compatibility
- Tested with Python 3.10.
Attribution
- This repository is a Python adaptation of the R project
associatoR(https://github.com/samuelae/associatoR) originally created by Dirk Wulff.
Author
- Ali Alhosseini
Project details
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