Tutorials for developers

This section is dedicated to helping developers to contribute to the CIF. The following tutorials explain how to implement some plugins to pycif:

• How to add, register and initialize a new plugin
  • Adding a plugin to pyCIF
  • Registering your new plugin to pyCIF
  • Adding requirements to your plugin
  • Input arguments for your plugin
  • Initializing your plugin
  • Attaching functions to the plugin
• How to implement a new model
  • Include the model sources to the CIF
  • Create and register the plugin module
  • Create a domain for your model
  • Define the “mapper” of your model
    • 1. Setting an empty mapper
    • 2. Setting the mapper with output concentrations
    • 3. Running the model executable
    • 4. Setting the mapper with input fluxes
  • Generate a monitor file compatible with the CIF
  • Pre-process observations to fit in model realm
    • Temporal fit to the model time steps
    • Horizontal fit to model domain
  • Preparing inputs
    • native2inputs
  • Comparing outputs to observations
    • native2inputs
    • run
    • outputs2native
• How to add a new type of flux data to be processed by the CIF into a model’s inputs
  • Pre-requisites
  • Switch from working fluxes to the reference template
  • Document your plugin
  • Build and check the documentation
  • Updating functions and data to implement your flux data
    • fetch
    • get_domain (optional)
    • read
    • write (optional)
• How to add a new type of data for boundary conditions to be processed by the CIF into a model’s inputs
• How to add a new formula for computing the equivalent of satellite data
• How to add a new basic transformation
  • Pre-requisites
  • Switch from a working basic transformation to the reference template
  • Document your plugin
  • Build and check the documentation
  • Updating functions and data to implement your flux data
    • fetch
• Developments around CHIMERE
  • How to pass a new parameter from the yaml to CHIMERE
• Miscellaneous hints
  • Debugging hints
  • Inputs of a CTM
  • Running two versions of the CIF
  • Quick check of a datastore file
• Main principles for using pytest to manage tests of the CIF
  • 0. Organization of pytest in the CIF
  • 1. Default tests
  • 2. Run tests locally
  • 3. Add a test
    • a) Add a new fixture
  • b) Use the new fixture(s) in a new test
  • 4. Automated local tests
• Modifying a model to use with EnSRF
  • Set-up a working case with independent sampling
  • Implementing the batch_sampling for a specific model
    • Creating a restart_inicond component
    • Defining a correspondence between perturbed outputs and inputs
    • Perturbing the behaviour of the model
    • Improving the native2inputs routines to handle multiple tracers efficiently
• Parallel computing in CIF
  • Using threads
    • The thread decorator
    • The AutoThreads class
  • Using multiple cores
    • The multicore decorator