All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Added
load_corpus
tomowl.base_models.SyntacticModel
- Added
.jar
files to enable pip install from GitHub - Tested with Python 3.12
- Refactored Evaluation module.
- Added PPIEvaluator, GDAEvaluator, SubsumptionEvaluator
- Refactored
model
object and introducedmodel.train()
andmodel.evaluate()
methods. - Added
GDADatasetV2
andGDADatasetV2EL
. Datasets were introduced in https://github.com/bio-ontology-research-group/gda_analysis
- Removed
.mean()
for GCI losses in BoxSquaredELModule - Property
evaluation_classes
inmowl.datasets.builtin.PPIYeastDataset
returns a pair ofOWLClasses
objects instead of a singleOWLClasses
object.
mowl.nn.ELBoxModule
changed name tomowl.nn.ELBEModule
- Fix bug in GCI2 score for ELEmbeddings
- Fix bottleneck in ELBE example for PPI.
- Fix bugs in BoxSquaredEL model.
- Fix bug on OWL2VecStarProjector about projecting with literals
- Implemented
CategoricalProjector
based on https://arxiv.org/abs/2305.07163. (#59)
- Removed redundant class
based_models.EmbeddingModel
Fixed issue related to importing graph-based models due to missing __init__.py
files. (#60)
- BoxSquaredEL module added to
mowl.nn
- Implemented
model.from_pretrained
method. Related to issue #43 - Implemented
model.add_axioms
method. Related to issue #43 - Added models
RandomWalkPlusW2VModel
,GraphPlusPyKEENModel
,SyntacticPlusW2VModel
, - Updated dependencies: JPype-1.3.0 --> JPype-1.4.1, pykeen-1.9.0 --> pykeen-1.10.1
- Support for Python 3.8, 3.9, 3.10, 3.11. (#42)
- Bug fixed in corpus generation methods. Issue #36.
- Updated dependencies to work with Python 3.8 and 3.9. Issue #42
Family
dataset: a small ontology containing 12 axioms.- Unit tests up to 88% of coverage
DL2VecProjector
includes assertion axioms with named individualsFastTensorDataLoader
is part of mOWL in the modulemowl.utils.data
DeepGOZero
implementation in mOWL- Module
mowl.owlapi
with shortcuts to the OWLAPI - Extended
Dataset
class.
- Added Patch for bug CVE-2007-4559. Based on pull request #32
- Modules
mowl.ontology.extend
andmowl.ontology.create
created includinginsert_annotations
andcreate_from_triples
methods, respectively. - Package
deprecated
as dependency. - ELEmbeddingModel abstract class that contains basic functionality for models embedding the EL language.
- Implementation of ELBoxEmbeddings
- ELDataset class to work with EL models.
- Module
mowl.nn
wheretorch.nn
-based modules will reside. The first module existing there is the abstract module for EL models. - Module
mowl.models
where implementation of ELEmbeddings and ELBoxEmbeddings reside. - PyKEEN as dependency
GDAHumanELDataset
andGDAMouseELDataset
, which are reduced versions ofGDAHumanDataset
andGDAMouseDataset
, respectively. The new datasets can be normalized into theEL
language using the jcel library.- Started implementation of unit tests for
datasets
andwalking
modules.
- All builtin datasets can be imported from
mowl.datasets.builtin
module. - Updated implementation of ELEmbeddings
- Changed method
mowl.datasets.PathDataset.get_evaluation_classes
to propertymowl.datasets.PathDataset.evaluation_classes
- #25 Walking methods now accept an optional parameter for a list of nodes to filter the random walks.
- Modules
mowl.datasets.ppi_yeast
andmowl.datasets.gda
. - File
mowl.datasets.build_ontology
. - Class
mowl.embeddings.elembeddings.ELEmbeddings
. Future versions will point tomowl.models.ELEmbeddings
- Method
mowl.corpus.base.extract_annotation_corpus
. Future versions will split this method into two:mowl.corpus.base.extract_annotation_corpus
andmowl.corpus.base.extract_and_save_annotation_corpus
. - Method
mowl.datasets.PathDataset.get_evaluation_classes
.
0.0.30 - 2022-07-03
- Added
matplotlib
andtqdm
as dependencies of the package.
- Walking methods accept optional
outfile
parameter and corpus extraction methods do not append by default. - Documentation updated and fixed some typos.