Welcome to abICS’s documentation!

Contents:

• 1. About abICS
  • 1.1. What is abICS ?
  • 1.2. Developers
  • 1.3. Version information
  • 1.4. License
  • 1.5. Copyright
• 2. Install
  • 2.1. Prerequisites
  • 2.2. Install from PyPI
  • 2.3. Install from source
  • 2.4. Uninstall
• 3. Basic Usage
  • 3.1. Active learning
  • 3.2. Preparing an abICS control file
  • 3.3. Preparing a reference file for first-principles solvers
  • 3.4. Preparing a reference file for training and evaluating the machine learning model
  • 3.5. Creating a set of training data
  • 3.6. Creating a neural network
  • 3.7. Monte Carlo sampling
  • 3.8. Post-processing
• 4. Tutorial
  • 4.1. Constructing a neural network model
  • 4.2. Monte Carlo sampling
  • 4.3. Sampling using other machine learning models
• 5. Input Files Format
  • 5.1. [sampling] section
  • 5.2. [mlref] section
  • 5.3. [sampling.solver], [mlref.solver] section
  • 5.4. [train] section
  • 5.5. [observer] section
  • 5.6. [config] section
  • 5.7. [log] section
• 6. Output Files Format
  • 6.1. RANK/structure.XXX.vasp
  • 6.2. RANK/minE.vasp
  • 6.3. RANK/obs.dat
  • 6.4. RANK/obs_save.npy
  • 6.5. RANK/kT_hist.npy
  • 6.6. RANK/Trank_hist.npy
  • 6.7. RANK/logweight_hist.npy
  • 6.8. RANK/acceptance_ratio.dat
  • 6.9. logZ.dat
  • 6.10. <name>.dat
• 7. Miscellaneous tools
  • 7.1. st2abics
  • 7.2. abicsRXsepT
• 8. Algorithm
  • 8.1. Replica exchange Monte Carlo method
  • 8.2. Population Annealing Monte Carlo
  • 8.3. About configuration and update
• 9. Acknowledgement
• 10. Contacts

Indices and tables

• Index

• Module Index

• Search Page