amep.load.evaluation#

amep.load.evaluation(path: str, key: None | str = None, database: bool = False, verbose: bool = False) → BaseEvalData | BaseDatabase#

Loads evaluation data stored in an HDF5 file.

Parameters:

path (str) – Path of the HDF5 file.
key (str or None, optional) – If database = False, the element key of the HDF5 file is returned. The default is None.
database (bool, optional) – If True, a BaseDatabase object is returned. If False, a BaseEvalData object is returned if the given HDF5 file only contains results of one evaluation (otherwise, an error is raised) or if a key is supplied. The default is False.
verbose (bool, optional) – If True, runtime information is printed. The default is False.

Returns:

Object providing access to the HDF5 data file.

Return type:

BaseEvalData or BaseDatabase

Examples

Calculate the MSD, save it, and load the saved data:

>>> import amep
>>> traj = amep.load.traj("../examples/data/lammps.h5amep")
>>> msd = amep.evaluate.MSD(traj)
>>> msd.save('./eval/msd.h5')
>>> data = amep.load.evaluation('./eval/msd.h5')
>>> print(data.keys())
['frames', 'indices', 'times', 'avg', 'name', 'ptype']
>>>

Calculate the VACF and save it together with the MSD in one HDF5 file. Then, load the results again:

>>> vacf = amep.evaluate.VACF(traj)
>>> vacf.save('./eval/db.h5')
>>> msd.save('./eval/db.h5', database=True)
>>> db = amep.load.evaluation('./eval/db.h5', database=True)
>>> print(db.keys())
['msd', 'vacf']
>>>

Load only a specific observable from the HDF5 file (here: the MSD):

>>> msd = amep.load.evaluation('./eval/db.h5', key='msd')
>>> print(msd.keys())
['frames', 'indices', 'times', 'avg', 'name', 'ptype']
>>>

amep.load.evaluation#

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