-
Notifications
You must be signed in to change notification settings - Fork 5
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Showing
1 changed file
with
71 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,71 @@ | ||
==================== | ||
vO.1.3 Release Notes | ||
==================== | ||
|
||
This release includes some minor bug-fixes, several new features and API changes described below. In particular, it adds compatibility with :code:`pandas` version 1.3. | ||
|
||
|
||
Blue Graph's core | ||
================= | ||
|
||
PGFrame | ||
------- | ||
|
||
Updates to the :code:`PGFrame` interface include: | ||
|
||
- Several minor bugfixes; | ||
- New :code:`from_ontology` method of :code:`PGFrame` allowing to import ontologies as property graphs (based on `rdflib`). | ||
|
||
|
||
Backend support | ||
=============== | ||
|
||
graph-tool | ||
---------- | ||
|
||
In this release we have fixed the version of :code:`graph-tool` to 2.37 due to the breaking changes in the new API of 2.4X (in particular, removal of `B_min` parameter from the interface of :code:`minimize_blockmodel_dl`). | ||
|
||
|
||
Neo4j | ||
----- | ||
|
||
Neo4j-based analytics utils was updated to use the lastest Neo4j GDS 1.6.X, a couple of minor bugfixes to :code:`bluegraph.backends.neo4j.pgframe_to_neo4j` were added. | ||
|
||
|
||
Graph preprocessing with BlueGraph | ||
================================== | ||
|
||
|
||
Semantic property encoding | ||
-------------------------- | ||
|
||
Added PCA-based dimensionality reduction as a part of :code:`SklearnPGEncoder`. This allows adding an optional dimensionality reduction step as a part of preprocessing. | ||
|
||
For example, the following snippet creates an encoder that processes node and edge properties of the input graph and further performs dimensionality reduction to 10 components for resulting node features and 3 components for edges features. | ||
|
||
.. code-block:: python | ||
encoder = SklearnPGEncoder( | ||
node_properties=["nprop1", "nprop2", "nprop3"], | ||
edge_properties=["eprop1", "eprop2", "eprop3"], | ||
reduce_node_dims=True, | ||
reduce_edge_dims=True, | ||
n_node_components=10, | ||
n_edge_components=3) | ||
Services | ||
======== | ||
|
||
|
||
Embedder | ||
-------- | ||
|
||
Changes to the API of the embedding service were introduced: | ||
|
||
- :code:`models/{model_id}/details/{component}` | ||
- :code:`/models/{model_id}/{component}` | ||
- :code:`model/{model_id>}/...` is replaced by :code:`models/{model_id}/...` | ||
- :code:`model/{model_id}/similar-points` is replaced by :code:`models/{model_id}/neighbors` | ||
- :code:`models/<model_id>/embedding` returns :code:`{"vectors": [..., ..., ...] }` | ||
|