Roadmap

Themes

Our roadmap covers the following themes:

• Become the best ready-to-use library for CECT data analysis.
• performance, scalability, serviceability
• tackle some of the most wanted user feature

Common Functions

• Dog particle picking
  • main function added:
• fast subtomogram alignment
  • main function added: aitom.align.util.align_vols
• template search
  • just add an example tutorial is ok
• Fast alignment based subtomogram averaging
  • Need to write functions and add to: aitom.average.align.simple_iterative
• Fast alignment based subtomogram classification
  • Need to write functions and add to: aitom.classify.align.simple_iterative
• autoencoder with pose normalization
  • Please add this code inside aitom.classify.unsupervised.autoencoder
  • code can be found at: https://github.com/xulabs/projects/tree/master/autoencoder
• FAML
  • main function added: aitom.average.ml.faml
• deep learning based subtomogram classification
  • Please add the code inside aitom.classify.supervised.cnn
  • code can be found at
    • https://github.com/xulabs/projects/tree/master/particle_subdivision
    • https://github.com/xulabs/projects/tree/master/improved_classification

User Tutorial

• For python users.

Installation and Deployment

• A pip package

Documentation

• Pydoc

GUI

• For normal user.