# run Module¶

run.add_covariance_matrix(command)[source]

Make sure that the command uses the covariance matrix from the folder

run.from_run_to_info(command)[source]

Translate a command corresponding to a run into one for analysis

run.mock_update_run(custom_command='')[source]

Tentative covmat update run

Not reachable yet by any option.

run.mpi_run(custom_command='')[source]

Launch a simple MPI run, with no communication of covariance matrix

Each process will make sure to initialise the folder if needed. Then and only then, it will send the signal to its next in line to proceed. This allows for initialisation over an arbitrary cluster geometry (you can have a single node with many cores, and all the chains living there, or many nodes with few cores). The speed loss due to the time spend checking if the folder is created should be negligible when running decently sized chains.

Each process will send the number that it found to be the first available to its friends, so that the gathering of information post-run is made easier. If a chain number is specified, this will be used as the first number, and then incremented afterwards with the rank of the process.

run.run(custom_command='')[source]

Main call of the function

It recovers the initialised instances of cosmo Class, Data and the NameSpace containing the command line arguments, feeding into the sampler.

Parameters: custom_command (str) – allows for testing the code
run.safe_initialisation(custom_command='', comm=None, nprocs=1)[source]

Wrapper around the init function to handle errors

Keyword Arguments:

• custom_command (str) – testing purposes
• comm (MPI.Intracomm) – object that helps communicating between the processes
• nprocs (int) – number of processes