.venv_haddock/lib/python3.12/site-packages/haddock/modules/defaults.yaml

cns_exec:
  default: ""
  type: file
  title: "Path to the CNS executable"
  short: If not provided, HADDOCK3 will use the cns path configured
    during the installation.
  long: CNS is a required component to run HADDOCK. Ideally it should have been
    configured during installation. If not you can specify with the cns_exec parameter
    its path.
  group: "execution"
  explevel: easy
ncores:
  default: 4
  type: integer
  min: 1
  max: 500
  title: Number of CPU cores
  short: Number of CPU cores to use for the CNS calculations.
    It is truncated to max available CPUs  minus 1.
  long: Number of CPU cores to use for the CNS calculations.
    This will define the number of concurrent jobs being executed.
    Note that is truncated to the total number of available CPUs minus 1.
  group: "execution"
  explevel: easy
max_cpus:
  default: true
  type: boolean
  title: The max number of CPUs allowed.
  short: By default the max number of CPUs allowed is the max available on the system.
  long:
    If you want to spare a minimum amount of resources for daily tasks, set max_cpus
    to false; in that case the maximum number of CPUs allowed will be the total available
    in the machine minus 1. This calculation is done automatically.
  group: "execution"
  explevel: expert
mode:
  default: local
  type: string
  minchars: 0
  maxchars: 20
  choices:
    - local
    - batch
  title: Mode of execution
  short: Mode of execution of the jobs, either local or using a batch system.
  long: Mode of execution of the jobs, either local or using a batch system.
    Currently slurm and torque are supported. For the batch mode the queue command must be
    specified in the queue parameter.
  group: "execution"
  explevel: easy
batch_type:
  default: "slurm"
  type: string
  minchars: 0
  maxchars: 100
  choices:
    - slurm
    - torque
  title: Batch system
  short: Type of batch system running on your server
  long: Type of batch system running on your server. Only slurm and torque are supported at this time
  group: "execution"
  explevel: "easy"
queue:
  default: ""
  type: string
  minchars: 0
  maxchars: 100
  title: Queue name
  short: Name of the batch queue to which jobs will be submitted
  long: Name of the batch queue to which jobs will be submitted. If not defined the batch system default will be used.
  group: "execution"
  explevel: easy
queue_limit:
  default: 100
  type: integer
  min: 1
  max: 9999
  title: Number of jobs to submit to the batch system
  short: Number of jobs to submit to the batch system
  long: This parameter controls the number of jobs that will be submitted to the batch system. In combination with the concat parameter this allow to limit the load on the queueing system and also make sure jobs remain in the queue for some time (if concat > 1) to avoid high system loads on the batch system.
  group: "execution"
  explevel: easy
concat:
  default: 1
  type: integer
  min: 1
  max: 9999
  precision: 0
  title: Number of models to produce per job.
  short: Multiple models can be calculated within one job
  long:
    This defines the number of models that will be generated within on job script.
    This allows to concatenate the generation of models into one script.
    In that way jobs might run longer in the batch system and reduce the load on the scheduler.
  group: "execution"
  explevel: easy
self_contained:
  default: false
  type: boolean
  title: Create a self-contained run
  short: This option will copy the CNS scripts and executable to the run folder.
  long:
    This option will copy the CNS scripts and executable to the run folder to ensure that all scripts are available within the run dir.
    This can be useful for for example remote execution of a job or for debugging purpose to allow to edit the scripts without touching the
    main installation.
  group: "execution"
  explevel: guru
clean:
  default: true
  type: boolean
  title: Clean the module output files.
  short: Clean the module if run succeeds by compressing or removing output files.
  long:
    When running haddock through the command-line, the 'clean' parameter will
    instruct the workflow to clean the output files of the module if the whole
    run succeeds. In this process, PDB and PSF files are compressed to gzip,
    with the extension `.gz`. While files with extension `.seed`, `.inp`, and
    `.out` files are archived, and the original files deleted. The time to
    perform a cleaning operation depends on the number of files in the folders
    and the size of the files. However, it should not represent a limit step in
    the workflow. For example, a rigidbody sampling 10,000 structures takes
    about 4 minutes in our servers. This operation uses as many cores as allowed
    by the user in the 'ncores' parameter. SSD disks will perform faster by
    definition. See also the 'haddock3-clean' and 'haddock3-unpack' command-line
    clients.
  group: "clean"
  explevel: easy
offline:
  default: false
  type: boolean
  title: Isolate haddock3 from internet.
  short: Completely isolate the haddock3 run & results from internet.
  long: For interactive plots, we are using the plotly library. It can be
    embedded as a link to the plotly.js library and fetched from the web,
    or directly copied on the html files AT THE COST OF ~3Mb per file.
    Setting this parameter to `true` will add the javascript library in
    generated files, therefore completely isolating haddock3 from any web call.
  group: "execution"
  explevel: easy
debug:
  default: false
  type: boolean
  title: Write intermediate and stdout files.
  short: Write intermediate and stdout files.
  long: When set to true, this option will increase the amount of I/O 
    operations by writing intermediate input, output and error files on disk.
    Turning it to false can be useful for example when running on a network
    file system where I/O operations are slow.
  group: "execution"
  explevel: easy
  incompatible:
    false:
      mode: batch