From ccdc2f36859bb6f1ba561c1cc49e21a4138b7f06 Mon Sep 17 00:00:00 2001 From: rbroc Date: Thu, 11 Apr 2024 18:39:37 +0200 Subject: [PATCH 1/2] reframe warnings in README --- README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.md b/README.md index cdcb8f7..c223326 100644 --- a/README.md +++ b/README.md @@ -12,8 +12,7 @@ - Make the models' API streamlined and compatible with topicwizard and scikit-learn. - Develop smarter, transformer-based evaluation metrics. -!!!This package is still a prototype, and no papers are published about the models. Until these are out, and most features are implemented -I DO NOT recommend using this package for production and academic use!!! +**Note**: This package is still work in progress and scientific papers on some of the novel methods (e.g., decomposition-based methods) are currently undergoing peer-review. If you use this package and you encounter any problem, let us know by opening relevant issues. ## Roadmap - [x] Model Implementation From 26e56c911ec3215ecf151f5ad8af3007be5b1160 Mon Sep 17 00:00:00 2001 From: rbroc Date: Thu, 6 Jun 2024 11:45:00 +0200 Subject: [PATCH 2/2] return lowest ranking documents in descending order --- turftopic/base.py | 1 + 1 file changed, 1 insertion(+) diff --git a/turftopic/base.py b/turftopic/base.py index 4f722fe..b738dea 100644 --- a/turftopic/base.py +++ b/turftopic/base.py @@ -217,6 +217,7 @@ def _representative_docs( lowest = lowest[ np.argsort(document_topic_matrix[lowest, topic_id]) ] + lowest = lowest[::-1] scores = document_topic_matrix[lowest, topic_id] for document_id, score in zip(lowest, scores): doc = raw_documents[document_id]