This repository contains an updated version of the Sigman group's "Get_Properties" script with parallelization. For the original script, please visit the original repository.
-
Create a conda environment using the gpenv_312.yml file.
conda env create -f gpenv_312.yml -
Activate the environment and use the notebook.
conda activate gpenv_312
Use the notebook get_properties.ipynb to collect your properties. Be sure to set your Jupyter kernel to gpenv_312.
Follow the instructions for each cell. Several comparisons between the old and new versions can be found in the
/tests/ directory.
- get_goodvibes_data
- get_frontierorbs
- get_polarizability
- get_dipole
- get_volume
- get_SASA
- get_nbo
- get_nmr
- get_distance
- get_angles
- get_dihedral
- get_vbur_scan
- get_sterimol_morfeus
- get_chelpg
- get_hirshfeld
- get_pyramidalization
- get_planeangle
- get_time
- get_IR
- get_sterimol_dbstep
- get_sterimol2vec
- Implement get_IR
- Implement get_sterimol_dbstep
- Implement get_sterimol2vec
- Implement get_enthalpies
- Switch to computing properties for one file at a time to reduce I/O operations by ~90% (major overhaul)
- Everything is parallelized
- Using logging module instead of print statements (easily redirected to file)
- Interactive 3D visualization of your files for easy atom name assignment
get_buried_sterimolhas been combined intoget_sterimol_morfeus. Specifying a radius will automatically bury the molecule while regular sterimol is calculated ifradiusisNone- Logfiles are automatically converted to .mol files
- Logfiles can be in any directory instead of the same directory as the Jupyter notebook
- File reading failures are decreased using a
.xyzcorrection process - Failure to read in files notifies user
- James R. Howard, PhD
- Brittany C. Haas, PhD
- Melissa A. Hardy, PhD
- Jordan P. Liles, PhD