Using

• bokeh server
• sqlite database backend (AiiDA database backend in alpha)
• jsmol for structure visualization

• python
• nodejs >= 6

pip install -e .     # install python dependencies
./prepare.sh         # download the data (run only once)
bokeh serve --show figure detail   # run app

Feel free to adapt this app to your own needs:

• a set of structures in data/structures
  • Allowed file extensions: cif, xyz
• a CSV file data/properties.csv with their properties
  • has a column name whose value <name> links each row to a file in structures/<name>.<extension>xyz.

The plots can be configured using a few YAML files:

• figure/columns.yml: defines metadata for columns of CSV file
• figure/filters.yml: defines filters available in plot
• figure/presets.yml: defines presets for axis + filter settings

pip install -e .
./prepare.sh
docker-compose build
docker-compose up
# open http://localhost:3245/ccg/select-figure

Download the structures at: https://drive.google.com/open?id=1lcB8jNXpgm22Tu1F9uym4Oa54daxV-Yo Download the allcomplexes.csv file at: https://drive.google.com/open?id=1lcB8jNXpgm22Tu1F9uym4Oa54daxV-Yo Add "export PYTHONPATH=$PYTHONPATH:/current-location/lsmo-bokeh-app" in the bashrc For creating the databse: python import_db.py For running the app: bokeh serve --show figure detail select-figure