This tool allows the user to buld ESPs either from precomputed QM calcs or a machine learning charge model.
- Create a conda environment with the required packages with the ENV.yml available
conda create -n esp_vis --file ENV.yml
- Activate this environment. Now in a separate directory, clone the molesp repo
git clone git@github.com:SimonBoothroyd/molesp.git
- Install the gui in molesp by entering the molesp directory and running
pip install -e .
then
python setup.py build_gui
then
python setup.py install
- Now we need to install the ML charge models in order to produce ESPs quickly. First clone this repo
git clone https://github.com/bismuthadams1/nagl-mbis
then install a key dependecy with
pip install git+https://github.com/bismuthadams1/nagl.git
finally, in the nagl-mbis repo run
pip install -e . --no-build-isolation
update the molesp env
- In order to produce ESPs from QM calcs, we need a bespoke .db file generated in my code Chargecraft. Charge craft can be cloned here
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There are two modes that you can use this visualizer:
-
Visualize an ESP with a charge model
-
Visualize an ESP with precomputed QM values
To use charge models you must first follow the install instructions from this repo and install the ChargeAPI in this esp_vis environment:
https://github.com/bismuthadams1/ChargeAPI
For this mode, we need to go the 'esp_visualize_esp.py' file. Add your chosen .sdf file and then run the code. A GUI will then be available at http://localhost:8000.