pygromos.simulations.modules package¶

Submodules¶

pygromos.simulations.modules.general_analysis_modules module¶

ideas:

Automatic Equilibration detection
property analysis
default analysis for emin ? eq?

Start with local submission system first. :)

pygromos.simulations.modules.general_simulation_modules module¶

pygromos.simulations.modules.general_simulation_modules.simulation(in_gromos_simulation_system: pygromos.files.gromos_system.gromos_system.Gromos_System, override_project_dir: typing.Optional[str] = None, step_name: str = 'sim', in_imd_path: typing.Optional[str] = None, submission_system: pygromos.simulations.hpc_queuing.submission_systems._submission_system._SubmissionSystem = <pygromos.simulations.hpc_queuing.submission_systems.local.LOCAL object>, simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: typing.Optional[int] = None, force_simulation: bool = False, initialize_first_run=False, reinitialize_every_run=False, analysis_script: callable = <function do>, analysis_control_dict: typing.Optional[dict] = None, _no_double_submit_check: bool = False, _work_dir: typing.Optional[str] = None, verbose: bool = True, verbose_lvl: int = 1, _template_imd_path: typing.Optional[str] = None) → pygromos.files.gromos_system.gromos_system.Gromos_System[source]¶

This function is a generic simulation block, that can be used to run and schedule simulations.

Parameters

in_gromos_simulation_system (Gromos_System) – gromos system that contains the information of the files, that are required for the simulation run.
override_project_dir (str) – parent project directory
step_name (str, optional) – name of the step - used as jobname and folder in the project dir.
in_imd_path (str, optional) – if a path to an imd file is given here, it will be used!
submission_system (_SubmissionSystem, optional) – the system, that should be used to submit a job
simulation_runs (int, optional) – number of sequential simulation runs
equilibration_runs (int, optional) – number of equilibration runs, that will not appear in the final traj
previous_simulation_run (int, optional) – job-ID of the previous simulation
force_simulation (bool, optional) – if simulation already exist, shall it be overwritten?
analysis_script (callable, optional) – script that is used to analyse the job
analysis_control_dict (dict, optional) – sub selection of steps, for the analysis script, that should be executed
verbose (bool, optional) – “baeh, baeh, baeh” - a wise black-nose sheep from ausserberg.
verbose_lvl (int, optional) – how much baeh?
_template_imd_path (str, optional) – default template imd

Returns

returns a new gromos system which is containing the simulation info

Return type

Gromos_System,

pygromos.simulations.modules.preset_simulation_modules module¶

pygromos.simulations.modules.preset_simulation_modules.emin(in_gromos_system: pygromos.files.gromos_system.gromos_system.Gromos_System, step_name: str = 'emin', override_project_dir: typing.Optional[str] = None, in_imd_path=None, submission_system: pygromos.simulations.hpc_queuing.submission_systems._submission_system._SubmissionSystem = <pygromos.simulations.hpc_queuing.submission_systems.local.LOCAL object>, simulation_runs: int = 1, equilibration_runs: int = 0, previous_simulation_run: typing.Optional[int] = None, _template_imd_path: str = '/home/mlehner/PyGromosTools/pygromos/data/simulation_parameters_templates/emin.imd', _no_double_submit_check: bool = False, initialize_first_run=False, analysis_script: callable = <function do>, verbose: bool = True) → Tuple[pygromos.files.gromos_system.gromos_system.Gromos_System, int][source]¶

pygromos.simulations.modules.preset_simulation_modules.md(in_gromos_system: pygromos.files.gromos_system.gromos_system.Gromos_System, step_name: str = 'md', override_project_dir: typing.Optional[str] = None, in_imd_path=None, submission_system: pygromos.simulations.hpc_queuing.submission_systems._submission_system._SubmissionSystem = <pygromos.simulations.hpc_queuing.submission_systems.local.LOCAL object>, simulation_runs: int = 1, equilibration_runs: int = 0, initialize_first_run=False, previous_simulation_run: typing.Optional[int] = None, _template_imd_path: str = '/home/mlehner/PyGromosTools/pygromos/data/simulation_parameters_templates/md.imd', _no_double_submit_check: bool = False, analysis_script: callable = <function do>, verbose: bool = True) → Tuple[pygromos.files.gromos_system.gromos_system.Gromos_System, int][source]¶

pygromos.simulations.modules.preset_simulation_modules.sd(in_gromos_system: pygromos.files.gromos_system.gromos_system.Gromos_System, step_name: str = 'sd', override_project_dir: typing.Optional[str] = None, in_imd_path=None, submission_system: pygromos.simulations.hpc_queuing.submission_systems._submission_system._SubmissionSystem = <pygromos.simulations.hpc_queuing.submission_systems.local.LOCAL object>, simulation_runs: int = 1, equilibration_runs: int = 0, initialize_first_run=False, previous_simulation_run: typing.Optional[int] = None, _template_imd_path: str = '/home/mlehner/PyGromosTools/pygromos/data/simulation_parameters_templates/vacuum_sd.imd', _no_double_submit_check: bool = False, analysis_script: callable = <function do>, verbose: bool = True) → Tuple[pygromos.files.gromos_system.gromos_system.Gromos_System, int][source]¶

pygromos.simulations.modules.ti_modules module¶

Free Energy

pygromos.simulations.modules.ti_modules.TI_sampling(in_gromos_system: pygromos.files.gromos_system.gromos_system.Gromos_System, project_dir: typing.Optional[str] = None, step_name='lambda_sampling', lambda_values: typing.List[float] = array([0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ]), subSystem: pygromos.simulations.hpc_queuing.submission_systems._submission_system._SubmissionSystem = <pygromos.simulations.hpc_queuing.submission_systems.local.LOCAL object>, n_productions: int = 3, n_equilibrations: int = 1, randomize: bool = False, dual_cnf: typing.Optional[typing.List[str]] = None, verbose: bool = True)[source]¶

This function will automatically submit N independent (different lambda) MD simulations with a lambda dependent potential energy.