pygromos.files.trajectory package

Subpackages

Submodules

pygromos.files.trajectory.trc module

File: Class for trc files in pandas Description:

The pandas trajectory TRC class offers a easy method to process GROMOS’s .trc files in python The trc files are parsed into an easy to use pandas dataframe

Author: Marc Thierry Lehner

TODO: add stride option to all member functions TODO: add support for periodic boundary condition TODO: add support for rdkit mol selector TODO: add support for rdkit conformers

class pygromos.files.trajectory.trc.Trc[source]

Bases: mdtraj.core.trajectory.Trajectory

TITLE: pygromos.files.blocks._general_blocks.TITLE
distances(atom_pairs: List[Tuple[int, int]], periodic: bool = True, opt: bool = True) → pandas.core.frame.DataFrame[source]
generate_TITLE_entry()[source]
generate_entry_for_frame(frame_id: int)[source]
get_dummy_cnf(xyz: numpy.array) → pygromos.files.coord.cnf.Cnf[source]
classmethod load(in_path: str, in_cnf_path: Optional[str] = None, timestep_duration: float = 0.002) → any[source]

Load a trajectory from disk

Parameters

filenames ({path-like, [path-like]}) – Either a path or list of paths

Other Parameters

As requested by the various load functions – it depends on the extension

parse_trc_efficiently(traj_path: str) → Tuple[numpy.array, numpy.array, numpy.array][source]
path: str
recreate_view() → nglview.widget.NGLWidget[source]
rmsd(reference_frame: int = 0, reference: Optional[mdtraj.core.trajectory.Trajectory] = None) → pandas.core.frame.DataFrame[source]
save(out_path: str) → str[source]

Save trajectory to disk, in a format determined by the filename extension

Parameters

filename (path-like) – filesystem path in which to save the trajectory. The extension will be parsed and will control the format.

Other Parameters

  • lossy (bool) – For .h5 or .lh5, whether or not to use compression.

  • no_models (bool) – For .pdb. TODO: Document this?

  • force_overwrite (bool) – If filename already exists, overwrite it.

property step: numpy.array
to_cnf(frame_id: Optional[int] = None, base_cnf: Optional[pygromos.files.coord.cnf.Cnf] = None)[source]
property view: nglview.widget.NGLWidget
write(out_path: str) → str[source]
write_trc(out_path: str) → str[source]

pygromos.files.trajectory.tre module

File: Class for tre files in pandas Description:

The pandas trajectory TRE class offers a easy method to process GROMOS’s .tre files in python The tre files are parsed into an easy to use pandas dataframe.

This class should be a alternative for the data post processing with ene_ana in gromos++

Author: Marc Thierry Lehner

TODO: add stride option to all member functions TODO: add support for periodic boundary condition

TODO: add ene_ana functions

class pygromos.files.trajectory.tre.Tre(input_value: str, auto_save: bool = True, stride: int = 1, skip: int = 0, _ene_ana_names: pygromos.files.trajectory.tre_field_libs.ene_fields.gromos_tre_block_names_table = <class 'pygromos.files.trajectory.tre_field_libs.ene_fields.gromos_2021_tre_block_names_table'>)[source]

Bases: pygromos.files.trajectory._general_trajectory._General_Trajectory

The Tre files are results from Gromos simulations, that store all the calculated energies and properties during the simulation.

__init__(input_value: str, auto_save: bool = True, stride: int = 1, skip: int = 0, _ene_ana_names: pygromos.files.trajectory.tre_field_libs.ene_fields.gromos_tre_block_names_table = <class 'pygromos.files.trajectory.tre_field_libs.ene_fields.gromos_2021_tre_block_names_table'>)[source]

Build a Gromos energy trajectory file (.tre)

Parameters

  • input_value (str,None) – The input value can be None, or a string path to the .tre/.tre.gz file.

  • auto_save (bool, optional) – automatically save the file, by default True

  • stride (int, optional) – only read every x value, by default 1

  • skip (int, optional) – skip the first x timesteps, by default 0

  • _ene_ana_names (gromos_tre_block_names_table, optional) – get the field names after the provided standard., by default gromos_2020_tre_block_names_table

_get_numberOfForceGroupsFromNonbondeds() → int[source]

This function gets the number of Force groups in the simulation from the nonbonded block.

Returns

number of ForceGroups used for this tre.

Return type

int

_set_data(attibute_name: str, rows_name: str, field_names: Tuple[str]) → pandas.core.frame.DataFrame[source]
_summary_

This function extracts generially the information of a column per time

Parameters

  • attibute_name (str) – name of the target attribute

  • rows_name (str) – name of the block, that shall be extracted

  • field_names (Tuple[str]) – name of the fields in each row

Returns

contains the extracted information

Return type

pd.DataFrame

get_Hvap(gas_traj: pygromos.utils.typing.Tre_Type, nMolecules: int = 1, temperature: Optional[float] = None) → float[source]
get_baths() → pandas.core.frame.DataFrame[source]

extract data of the baths block

get_bondedContributions() → Dict[int, pandas.core.frame.DataFrame][source]

extract data of the bonded block

get_density() → pandas.core.frame.DataFrame[source]

Calculate the density for every frame. (Uses mass and the first volume entry)

Returns

Dataframe with the densities for all time steps

Return type

pd.DataFrame

get_eds() → pandas.core.frame.DataFrame[source]

Get EDS energies if present.

Returns

returns datafrae with columns for each endstate.

Return type

pd.DataFrame

get_mass() → pandas.core.series.Series[source]

returns the systems mass per timestep

Returns

series of mass per time

Return type

pd.Series

get_nonbondedContributions() → Dict[int, Dict[int, pandas.core.frame.DataFrame]][source]

This function returns a nice formatted dictionary for the nonbonded Contributions according to the Force groups of the tre file.

Returns

The dictionary containing the nonbonded contributions of the single ForceGroups with each other. Dict[ForceGroupI, Dict[ForceGroupJ, NonbondedEnergyContribs]]

Return type

Dict[int, Dict[int, pd.DataFrame]]

Raises

ValueError – returns Value error, if the dimensionality of the different contributions does not fit to the _nonbonded_contribution_names.

get_precalclam() → pandas.core.frame.DataFrame[source]

Get the energies calculated for the different defined lambda values in a trajectory.

Returns

return the energies calculated for the different lambda values.

Return type

pd.DataFrame

get_specialContributions() → Dict[int, pandas.core.frame.DataFrame][source]

extract data of the special block

get_temperature() → pandas.core.frame.DataFrame[source]

Get the temperature in Kelvin for all temperature baths for every time step

Returns

pandas dataframe with all temperatures

Return type

pd.DataFrame

get_temperature_Info() → Dict[int, pandas.core.frame.DataFrame][source]

temperature baths

Returns

returns the full info of the temperature baths per bath

Return type

Dict[int,pd.DataFrame]

get_totals() → pandas.core.frame.DataFrame[source]

get all totals of the system

get_totangle() → pandas.core.frame.DataFrame[source]

get the total angle contribution/ per time

get_totbonded() → pandas.core.frame.DataFrame[source]

get the total bonded contribution/ per time

get_totcov() → pandas.core.frame.DataFrame[source]

get the total covalent contribution/ per time

get_totcrf() → pandas.core.frame.DataFrame[source]

get the total columbic reactionfield contribution/ per time

get_totdihedral() → pandas.core.frame.DataFrame[source]

get the total dihedral contribution/ per time

get_totene() → pandas.core.frame.DataFrame[source]

get the total System energy / per time

get_totkin() → pandas.core.frame.DataFrame[source]

get the total kinetic Energy / per time

get_totlj() → pandas.core.frame.DataFrame[source]

get the total lennard jones contribution/ per time

get_totnonbonded() → pandas.core.frame.DataFrame[source]

get the total nonbonded contribution/ per time

get_totpot() → pandas.core.frame.DataFrame[source]

get the total potential Energy / per time

pygromos.files.trajectory.trg module

File: Class for tre files in pandas Description:

The pandas trajectory TRE class offers a easy method to process GROMOS’s .trg files in python The tre files are parsed into an easy to use pandas dataframe.

This class should be a alternative for the data post processing with ene_ana in gromos++

Author: Marc Thierry Lehner & Benjamin Ries

TODO: add stride option to all member functions TODO: add support for periodic boundary condition

TODO: add ene_ana functions

class pygromos.files.trajectory.trg.Trg(input_value: str, auto_save=True, stride: int = 1, skip: int = 0)[source]

Bases: pygromos.files.trajectory._general_trajectory._General_Trajectory

get_lambdas() → pandas.core.frame.DataFrame[source]
get_precalclam() → pandas.core.frame.DataFrame[source]
get_totals() → pandas.core.frame.DataFrame[source]
class pygromos.files.trajectory.trg.gromos_2020_trg_block_names_table[source]

Bases: object

precalclam_subblock = ['nr_lambdas', 'A_e_lj', 'B_e_lj', 'A_e_crf', 'B_e_crf', 'AB_kinetic', 'AB_bond', 'AB_angle', 'AB_improper', 'AB_disres', 'AB_dihres', 'AB_disfld']
totals_subblock_names = ['dHdl', 'dKdl', 'dVdl', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP', 'WIP']

Module contents