Processing

Introduction

Automatic processing of simulated data sets using the ETSimulations software revolves around “Processors”. Each Processor is a module of the software designed to facilitate processing of simulated data sets. Currently, the EMAN2 Processor and the IMOD Processor are available. As each software has differing project structure and workflows, the exact behavior of each processor will be quite different and personalized to each software. However, setting up and running any processor will always revolve around the ets_process_data.py program. Here as well, we provide input via a configuration YAML file.

The YAML file provided to the ets_process_data.py run should have:

• rootstring

  The path to the folder which contains the raw_data and sim_metadata.json files created by ets_generate_data.py

• namestring

  The project name - should be the same one used for the simulations

• processorslist of strings

  A list of processor objects which have a “name” and “args” arguments. The specifics to what goes into these fields can be found in more details in the section of the manual particular to that processor.

To run the processor module (assuming a YAML file called processor_configs.yaml), run:

python src/ets_process_data.py -i processor_configs.yaml

Available processors

• The EMAN2 Processor
  • Parameters
    • steps_to_run
    • particle_coordinates_parameters
    • e2*_parameters objects
  • Running the generated script
• The IMOD Processor
  • Reconstruction
  • Parameters
  • Using the IMOD Processor on real data
• The Dynamo Processor
  • Required arguments
    • Using the Dynamo Processor on real data
      • Starting from IMOD
      • Starting from EMAN2
• The I3 Processor
  • Parameters
  • Using the I3 Processor on real data
    • Starting from IMOD
    • Starting from EMAN2
• The Artiatomi Processor
  • Introduction
    • A note on EMAN2
  • Parameters
    • General parameters
    • Artiatomi-specific parameters
    • Real data mode parameters
  • Further details by step
    • Reconstruction and Motivelist
    • Averaging
    • Refinement
  • Examples