Organisms: A Genetic Algorithm for Nanoclusters Logo
stable
  • How the Otago Research Genetic Algorithm for Nanoclusters, Including Structural Methods and Similatity (Organisms) Program Works
  • Installation: Setting Up the Organisms Program and Pre-Requisites Packages
  • How To Use The Organisms Program
  • Run.py - Running the Genetic Algorithm
  • Examples of Running the Organisms Program with Run.py
  • RunMinimisation.py - Writing a Local Minimisation Function for the Genetic Algorithm
  • MakeTrials.py - Creating Multiple, Repeated Genetic Algorithm Trials
  • Safely Finishing the Genetic Algorithm Midway through the Algorithm
  • Restarting the Genetic Algorithm
  • Common Issues of the Genetic Algorithm and Ways to Solve Them
  • Helpful Programs to Create and Run the Genetic Algorithm
  • Helpful Programs for Gathering data and Post-processing Data
  • Information about using the make_energy_vs_similarity_results.py script
  • Other Helpful Programs for Gathering data and Post-processing Data
  • Initialising a New Population
  • Using Predation Operators with the Genetic Algorithm
  • Using Fitness Operators with the Genetic Algorithm
  • The Structural Comparison Method (SCM)
  • Using the Memory Operator
  • Using Epoch Methods
  • Recording Clusters From The Genetic Algorithm
  • Using Databases with the Genetic Algorithm
  • Adding Surfaces
  • The Genetic Algorithm Python Files
  • Index
  • Python Module Index
Organisms: A Genetic Algorithm for Nanoclusters
  • »
  • Search

© Copyright 2021, Geoffrey Weal and Dr. Anna Garden. Revision f79cfeab.

Built with Sphinx using a theme provided by Read the Docs.