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timescales

Set of functions for analyzing the MD trajectory.

This submodule contains methods for estimating various timescales based on a given state trajectory.

estimate_waiting_times(trajs, start, final)

Estimates waiting times between stated states.

The stated states (from/to) will be treated as a basin. The function calculates all transitions from first entering the start-basin until first reaching the final-basin.

Parameters:

  • trajs (statetraj or list or ndarray or list of ndarray) –

    State trajectory/trajectories. The states should start from zero and need to be integers.

  • start (int or list of) –

    States to start counting.

  • final (int or list of) –

    States to start counting.

Returns:

  • wt ( ndarray ) –

    List of waiting times, given in frames.

Source code in src/msmhelper/md/timescales.py 
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@decorit.alias('estimate_wt')
def estimate_waiting_times(trajs, start, final):
    """Estimates waiting times between stated states.

    The stated states (from/to) will be treated as a basin. The function
    calculates all transitions from first entering the start-basin until first
    reaching the final-basin.

    Parameters
    ----------
    trajs : statetraj or list or ndarray or list of ndarray
        State trajectory/trajectories. The states should start from zero and
        need to be integers.
    start : int or list of
        States to start counting.
    final : int or list of
        States to start counting.

    Returns
    -------
    wt : ndarray
        List of waiting times, given in frames.

    """
    # check correct input format
    trajs = StateTraj(trajs)

    states_start, states_final = np.unique(start), np.unique(final)

    if intersect(states_start, states_final):
        raise ValueError('States `start` and `final` do overlap.')

    # check that all states exist in trajectory
    for states in (states_start, states_final):
        if intersect(states, trajs.states) != len(states):
            raise ValueError(
                'Selected states does not exist in state trajectory.',
            )

    # do not convert for pytest coverage
    if numba.config.DISABLE_JIT:
        return _estimate_waiting_times(trajs, states_start, states_final)
    return _estimate_waiting_times(  # pragma: no cover
        numba.typed.List(trajs),
        numba.typed.List(states_start),
        numba.typed.List(states_final),
    )

estimate_paths(trajs, start, final)

Estimates paths and waiting times between stated states.

The stated states (from/to) will be treated as a basin. The function calculates all transitions from first entering the start-basin until first reaching the final-basin. The results will be listed by the corresponding pathways, where loops are removed occuring first.

Parameters:

  • trajs (statetraj or list or ndarray or list of ndarray) –

    State trajectory/trajectories. The states should start from zero and need to be integers.

  • start (int or list of) –

    States to start counting.

  • final (int or list of) –

    States to start counting.

Returns:

  • paths ( dict ) –

    Dictionary containing the the paths as keys and and an array holding the times of all paths as value.

Source code in src/msmhelper/md/timescales.py 
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def estimate_paths(trajs, start, final):
    """Estimates paths and waiting times between stated states.

    The stated states (from/to) will be treated as a basin. The function
    calculates all transitions from first entering the start-basin until first
    reaching the final-basin. The results will be listed by the corresponding
    pathways, where loops are removed occuring first.

    Parameters
    ----------
    trajs : statetraj or list or ndarray or list of ndarray
        State trajectory/trajectories. The states should start from zero and
        need to be integers.
    start : int or list of
        States to start counting.
    final : int or list of
        States to start counting.

    Returns
    -------
    paths : dict
        Dictionary containing the the paths as keys and and an array holding
        the times of all paths as value.

    """
    # check correct input format
    trajs = StateTraj(trajs)

    states_start, states_final = np.unique(start), np.unique(final)

    if intersect(states_start, states_final):
        raise ValueError('States `start` and `final` do overlap.')

    # check that all states exist in trajectory
    for states in (states_start, states_final):
        if intersect(states, trajs.states) != len(states):
            raise ValueError(
                'Selected states does not exist in state trajectory.',
            )

    # do not convert for pytest coverage
    if numba.config.DISABLE_JIT:  # pragma: no cover
        path_tuples = _estimate_paths(trajs, states_start, states_final)
    else:
        path_tuples = _estimate_paths(  # pragma: no cover
            numba.typed.List(trajs),
            numba.typed.List(states_start),
            numba.typed.List(states_final),
        )
    paths = defaultdict(list)
    for path, time in path_tuples:
        paths[tuple(path)].append(time)

    return paths