Pipeline Configuration: Mean Volume Backscattering Strength on AWS

In this section, we will provide you with the pipeline configuration that we’ll be using for our MVBS processing. The configuration is presented in YAML format, which is a structured and human-readable way to define settings for data processing.

Here’s the configuration we’ll be using:

active_recipe: standard 
use_local_dask: true
n_workers: 3
pipeline:
- recipe_name: standard 
  stages: 
  - name: echodataflow_open_raw 
    module: echodataflow.stages.subflows.open_raw 
    options: 
      save_raw_file: true
      use_raw_offline: true 
      use_offline: true 
  - name: echodataflow_combine_echodata
    module: echodataflow.stages.subflows.combine_echodata
    options:
      use_offline: true
  - name: echodataflow_compute_Sv
    module: echodataflow.stages.subflows.compute_Sv
    options:
      use_offline: true
  - name: echodataflow_compute_MVBS
    module: echodataflow.stages.subflows.compute_MVBS
    options:
      use_offline: true
    external_params:
      range_meter_bin: 20 
      ping_time_bin: 20S

Note: For a more comprehensive understanding of each option and its functionality, you can refer to the Pipeline documentation.

Keep in mind that in this example, we’ll be setting up a local Dask Cluster with 3 workers for parallel processing. This configuration will enable us to efficiently process our data for MVBS analysis. To turn it off, toggle use_local_dask to false.

Feel free to explore and modify the configuration to understand better.