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Project description
Ontoviz
Ontology visualization with Python
Installation
python -m pip install ontoviz
Example
ontoviz_to_dot -o test.dot test.ttl -O ontology.ttl
dot -Tpng -o test.png test.dot
- Use
-oto indicate the path of output file - Use
-Oto indicate the input ontology (Optional). - Use
-Cto indicate the configuration file (Optional).-
max_label_length: config the max length of labels. If the text exceeds the length, exceeded part will be replaced with "…". Default value is0. -
blacklist: config the predicate that you don't want to see in the graph. -
class_inference_in_object: config the predicate that can inference the object is aClass, even if the class doesn't defined in the ontology. -
label_property: config the predicate that used for labeling nodes, if such a label exists, it will display inside the node. -
tooltip_property: config the predicate that contains the tooltip texts. -
bnode_regex: a list of regexes, if an uri matches, then it will be dispaly as a blank node without its uri nor label. It can be useful if you have a lot of reifications. -
colors: config the colors of nodes-
class,literal,instancecan accept HEX value(e.g."#ff0000"), MATLAB style(e.g."r"), and color name (e.g."red")."colors": { "class": "#ff0000", "literal": "r", "instance": "red", }
-
instancecan also accept a dict value to specify the color of each class instance. And use"default"to to set color for undefined instances."instance": { "https://tac.nist.gov/tracks/SM-KBP/2018/ontologies/SeedlingOntology#Facility": "#a6cee3", "default": "#ffff99" }
-
filled: config whether fill the node, default value:true.
-
-
- Classes defined in the ontology will be omitted in the output graph. This action can be switched with argument
-V.
Useful Graphviz flags
-Kto specify which layout algorithm to use. E.g.-Kneatoand-Ksfdp. Notice that inorder to usesfdplayout algorithm, you will need to build your graphviz with GTS.-Tto specify the output format.-Gto set a graph attribute. E.g.-Goverlap=prism
Requirements
All the minimal Python requirements are installed during
python -m pip install ontoviz
For a development setup do
git clone https://github.com/WWU-AMM/ontoviz
cd ontoviz
virtualenv venv
. venv/bin/activate
python -m pip install -e .[full]
pre-commit install
This will also install tools for documentation building and testing
In order to convert dot into png or svg image, you will need Graphviz.
Testing
Simply run pytest from the repository root. All tests are also run automatically by github actions on push/PR.
Project details
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