Visual-graph-datasets

Latest version: v0.15.5

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0.15.4

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- Fixed the dependency error where utils imported from ``graph_attention_student`` have caused a circular import error

0.15.3

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- Changed the version requirement to be compatible with newer python versions

0.15.2

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- Added the function ``create_combined_importances_pdf" to generate a visualization PDF that visualizes the explanations
not as separate figures, but all the explanation channels into the same figure, encoding the different channels as different
colors.

0.15.1

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- The "load" method of the Config instance now returns the itself, which is just a small quality of life improvement
for the scripts that will use have to use the config instance.
- Added some additional documentation for the Processing classes

0.15.0

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- Added some more graph utility functions such as functions to extract sub graphs, add and remove nodes and
to identify connected regions of a graph.
- Added documentation for the ``ColorProcessing`` class
- Changed the ``ColorProcessing.visualize_as_figure`` method to now also accept external graph dict parameter
and external node_positions array.
- Modified the ``generate_molecule_dataset_from_csv.py`` experiment so that it is now possible to optionally
define a indices blacklist of elements that should be skipped during processing.
- Moved the dependencies to the most recent version of RDKit. This seems to have fixed the issue of the molecule
image generation occasionally crashing with a segmentation fault.
- Added the ``generic`` graph type. This is a graph type that can be used to represent any kind of graph
that cannot be associated with any kind of specific domain. Added the ``GenericProcessing`` class which
can be used to process these generic graphs.
- Modifed the ``colors_layout`` function such that it is possible to pass a partially defined list of
node_positions as an argument, such that the positions of some nodes can be fixed during the layouting.

0.14.3

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- Added back in the dictionaries defining the alternative versions for the node and edge importance plotting

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