Merge pull request #34 from MPI-Dortmund/docs_05

Updated documentation
MPI-Dortmund · Jul 18, 2023 · f4cf322 · f4cf322
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diff --git a/docs/changes.rst b/docs/changes.rst
@@ -1,13 +1,19 @@
 Changes
 =======
 
-Version 0.5.0 (upcoming)
+Version 0.5.0
 *************
 
-* The ``tomotwin_embed.py tomogram`` command has now a optional ``--mask`` option to select region of interestes for embeddings.
-* The ``tomotwin_tools.py embedding_mask`` now calculates a mask that masks out some portions of the tomogram volume that probably do not contain proteins. Using the generated mask when running ``tomotwin_embed.py tomogram``, the embeddings step is 2 times faster. CAUTION: In TomoTwin 0.4 the ``embeddings_mask`` command calculated a label mask for the clustering workflow. This functionality now happens automatically during the calculation of the umap (``tomotwin_tools.py umap``).
-* For the clustering workflow, you can now calculate the medoid instead of arithmetic mean. This should be a much better representation of the cluster center.
-
+* Speed up embedding using Masks
+    * The command ``tomotwin_embed.py tomogram`` now has an optional ``--mask`` argument to select the region of interest for embedding.
+    * The command ``tomotwin_tools.py embedding_mask`` now computes a by isonet inspired mask that hides some parts of the tomogram volume that are unlikely to contain proteins. If you use the generated mask with new ``--mask`` argument, the embedding step is up to 2 times faster. **CAUTION:** In TomoTwin 0.4, the ``embeddings_mask`` command calculated a label mask for the clustering workflow. This functionality now happens automatically during the calculation of the umap (``tomotwin_tools.py umap``).
+    * Thanks Caitie McCafferty and Ricardo Righetto for the feature request
+* More accurate cluster centers
+    * When selecting clusters in Napari during the clustering workflow, the `Medoid <https://en.wikipedia.org/wiki/Medoid>`_ is now calculated instead of the average of all cluster embeddings. This has the advantage that it is guaranteed to be on the embedding hypersphere and should be a better representation of the cluster center than the average.
+    * The coordinates of the found medoid for each cluster is written as a .coords file to disk.
+* Other
+    * Updated installation instructions for napari: Napari 0.4.17 -> Napari 0.4.18
+    * :ref:`Added some information snippets for developers <dev-info>`
 
 Version 0.4.3
 *************

diff --git a/docs/developer/devs.rst b/docs/developer/devs.rst
@@ -1,3 +1,4 @@
+.. _dev-info:
 Developer information
 =====================
 

diff --git a/docs/installation.rst b/docs/installation.rst
@@ -24,7 +24,7 @@ Here we assume that you don't have napari installed. Please do:
 
 .. prompt:: bash $
 
-    mamba create -y -n napari-tomotwin -c conda-forge python=3.10 napari=0.4.17 pyqt pip
+    mamba create -y -n napari-tomotwin -c conda-forge python=3.10 napari=0.4.18 pyqt pip
     conda activate napari-tomotwin
 
 Install the required plugins `napari-boxmanager` and `napari-tomotwin` via pip: