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Replace hard-coded attribute keys (#110)
* replace hard-coded node attribute "atom_number" * replace hard-coded node attribute "element_symbol" * replace hard-coded node attributes of the coordinates * replace hard-coded node attribute "partition" * forgot one replacement of "element_symbol" * replace hard-coded node attribute "chg" * replace hard-coded node attribute "rad" intoduce a mapping in the (de-)serialization of TUCAN strings * add test for V2000 Molfile charge mechanics (implemented via MOLFILE_V2000_CHARGES) * replace hard-coded node attribute "mass" * replace hard-coded node attribute "explored" * replace hard-coded node attribute "invariant_code" * replace hard-coded edge attribute "bond_type" * cleanup, add/correct type hints
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@flange-ipb Nice (-:= That will make further "custom node attributes" more easy to handle - further modifications planned?
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@flange-ipb This change is not in the main package yet, isn't it? I tried to update a local installation but it did not modify any files
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Hi @schatzsc
Happy new year! Just a bit of code cleanup to avoid any confusion about the use of attribute keys. And it makes it easier to keep track where an attribute is used. :)
The pull request went to bliss-canonicalization, which is the default branch.
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Do you know where the TUCAN files get stores on a Windows 10 or Linux system?!? In the place where I'd expect them there are only the only ones without those modifications.
Furthermore, with the new installation also mention in relation to the other issue, the probem disappeared, at least when I try to run the functions instead a script
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Depends on your package management tool.
I usually use pip in a virtual environment (created via
python -m venv .env
in the TUCAN project directory). Then all the installed dependencies are stored in.env/lib/python3.11/site-packages/
. My IDE (PyCharm) also integrates that nicely.In principle it is also possible to work without a virtual environment and install dependencies globally, i.e. for a user. This goes into
$HOME/.local/lib/python3.9/site-packages/
. In Ubuntu/Debian pip refuses to support this mode since Python 3.11, but there are workarounds.432889e
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@flange-ipb
In this particular case, It's more complicated, since the CSD Python API comes with its own separate python installation
But thanks to your hint I found the files, which on my Ubuntu Linux machine reside here
~/CCDC/ccdc-software/csd-python-api/miniconda/lib/python3.9/site-packages/tucan
and now also include the latest code changes (-:=
I like the new
graph_attributes.py
definitions since they will facilitate addition of custom node attributes for ML in a simple way, which only need to be carried along, but should not be evaluated in the canonicalizationBTW - at the moment I'm working again on the "implict H preprocessor" and try to store the rules in a sqlite3 database, as you suggested, but first need to familiarize more with that package