Releases: alkidbaci/OntoSample
ontosample 0.2.5
ontosample 0.2.3
Bug fixing patch
- Updated imports for owlapy 1.0.2
- Added latest changes from ontolearn into ontolearn_light
To get the latest release:
pip install -U ontosample
ontosample 0.2.2
When trying to use ontosample in ontolearn we found that there are some compatibility issues because classes of ontolearn_light
are not recognized as classes of ontolearn
.
That is why in this release we made ontolearn
related imports of ontosample
conditional, based on the presence of ontolearn
package. This way, when both packages are installed at the same environment, ontosample
will use ontolearn
module and not ontolearn_light
.
In case of any issue please reach us on the Issues tab.
ontosample 0.2.0
Happy to share the new release of Ontosample.
We got some important changes to the base structure this time. The logic of the samplers stays unchanged.
The following changes were made:
- All the generated knowledge bases/ontologies point to different worlds and no longer conflict with each other.
- Because of that a sampler object can now be reused to perform multiple samples on the initial knowledge base.
- The
save_sample
method now is static and takes 2 arguments:kb
the sampled knowledge base that you want to save andfilename
the name of the file that will store the ontology (the file will be created at runtime if it does not exist). ontolearn
module renamed toontolearn_light
so it does not conflict with the main ontolearn package.- Updated
ontolearn_light
sub modules with recent changes from main ontolearn package where triplestore logic is removed (a triple store knowledge base is not able to be sampled anyway because it stored in a server). - Removed methods
get_sampled_nodes
(can usesampled_kb.individuals_count()
instead). get_removed_nodes
is now renamed to_get_removed_nodes
indicating that is only for internal usage. Removed individuals can be retrieved as follows:removed_individuals = set(kb.individuals()) - set(sampled_kb.individuals())
As always you can use pip install ontosample
to get the lates version via the Python Package index.
Don't hesitate to open an issue in case you are having a problem or you just want to suggest something.
Full Changelog: v0.1.1...v0.2.0
ontosample 0.1.1
We are happy to announce the first release of ontosample.
You can now use pip install ontosample
to get it via the Python Package index.
Changes since the initialization commit:
- We are keeping only the ontolearn files that are necessary to make the sampling work. Everything else is removed from ontolearn module.
- Refactored the code of samplers, now the code is more compact and they are divided in three modules:
classic_samplers.py
lpc_samplers.py
lpf_samplers.py
Note: If you want to try concept learning algorithms of ontolearn, you have to install the whole ontolearn package because ontosample is using a light version of it.