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Run the code via Make It So!

The easiest way to configure models coupled to the LFM is via the script generator affectionately named "Make It So". MakeItSo requires Python >= 2.4.


Once you've set the corresponding environment variables, learn more about MakeItSo via the --help flag: --help

There are two ways to run the script generator:

  1. Interactive mode: At the command-line, type
    and follow the prompts. You will be asked to set a series of parameters. Press <enter> for the default value or ? <enter> for more information on a particular variable. Once you've entered all model parameters & environment setup, MakeItSo will create input files & job scripts necessary to run the code.
  1. Preconfigured run mode: Each time you run the script generator, it writes a makeItSo.config file at:
    Output directory/RUN_IDENTIFIER_makeItSo.config
    Once you've run the script generator via interactive mode (see above), open up a *makeItSo.config file with a text editor. You can edit run parameters, save the file and configure a new run using this simple text file. Execute:
    /path/to/ -c /path/to/RUN_IDENTIFIER_makeItSo.config
    MakeItSo will create all the input files & job scripts necessary to run the code.

Make It So will print instructions and create a set of files:

  • Input files that set model parameters
  • Shell script to configure the models (
  • Run scripts to execute the models (RUN_IDENTIFIER-001.*)

Follow the instructions displayed by Make It So to run the code.


How do I restart or continue a long run?

Say you ran MakeItSo to generate a 2 hour run of LFM. You should have several files in your run directory, including:

  • 50 minute spinup interval
  • Job script for 1st hour of run
  • Job script for 2nd hour of run
  • SW-SM-DAT: 6 hours of solar wind data from OMNI
  • LFM_makeItSo.config: configuration file for MakeItSo.

You execute the job scripts and your 2 hour run (plus 50 minute spinup) have completed.  Let's say you want to restart the run and continue for an additional 2 hours.  There are two ways to do this:

  1. Extend the run (recommended)
    1. Edit LFM_makeItSo.config and set the stop top tim 2 hours later
    2. Re-run MakeItSo: -c LFM_makeItSo.config
    3. Submit the next job script in the iteration: This will pick up where the previous job script left off and continue executing the model.
  2. Configure a restart run (advanced)
    1. Edit LFM_makeItSo.config and
      1. change start time to 2 hours later
      2. change stop time to 2 hours later
      3. add the the parameter SPINUP: false to Shared model settings
    2. Re-run MakeItSo: -c LFM_makeItSo.config
      This will create the following run scripts:
      • {}}: Job script for 3rd hour of run
      • {}}: Job script for 4th hour of run
        Note: if you ran MakeItSo in the original run directory, you may have overwritten the pre-existing job scripts!

Extending MakeItSo


Adding a new environment to MakeItSo is an advanced topic. Do not hesitate to ask for help with initial configuration.

We have tested MakeItSo on a variety of systems.  You can customize for your particular machine in two ways:

Create Config File (recommended)

You can permanently add your environment by defining all parameters in a QUEING-ENVIRONMENT.yml file. This file must reside in the MakeItSo/Environments subdirectory. It describes the computer (MPI installation, flags for the number of processors, etc) and any queue information that is required. We recommend that you start with a pre-existing environment & extend it to your own environment. For example, see LSF.yml or SGE.yml.

At runtime, MakeItSo will locate this YAML file & provide an interface to the user to set up the environment.

Modify at Run Time

You can modify a pre-configured environment at run-time. Start in "expert" mode (Warning: This may prompt you to enter dozens of model parameters)

misc/python/ --expert

When prompted for an environment, select the one most similar to yours. If you are working on a Linux desktop computer, select "Standard Linux Bourne shell without a queue". You will be asked to enter a series of parameters related to your compute environment. You must know the settings used to compile the LTR prerequisites.

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