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high

deepdrivewe.recyclers.high

Recycle simulations above a certain progress coordinate threshold.

HighRecycler

Bases: Recycler

Recycle simulations above a certain progress coordinate threshold.

Source code in deepdrivewe/recyclers/high.py 
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class HighRecycler(Recycler):
    """Recycle simulations above a certain progress coordinate threshold."""

    def __init__(
        self,
        basis_states: BasisStates,
        target_threshold: float,
        pcoord_idx: int = 0,
    ) -> None:
        """Initialize the recycler.

        Parameters
        ----------
        basis_states : BasisStates
            The basis states for the weighted ensemble.
        target_threshold : float
            The target threshold for the progress coordinate to be considered
            in the target state.
        pcoord_idx : int
            The index of the progress coordinate to use for recycling. Only
            applicable if a multi-dimensional pcoord is used, will choose the
            specified index of the pcoord for recycling. Default is 0.
        """
        super().__init__(basis_states)
        self.target_threshold = target_threshold
        self.pcoord_idx = pcoord_idx

    def recycle(self, pcoords: np.ndarray) -> np.ndarray:
        """Recycle the simulations above the target threshold.

        Parameters
        ----------
        pcoords : np.ndarray
            The progress coordinates for the simulations.
            Shape: (n_simulations, n_dims).

        Returns
        -------
        np.ndarray
            The list of simulation indices to recycle. Shape: (n_recycled,)
        """
        return np.where(pcoords[:, self.pcoord_idx] > self.target_threshold)[0]

__init__ 

__init__(
    basis_states: BasisStates,
    target_threshold: float,
    pcoord_idx: int = 0,
) -> None

Initialize the recycler.

Parameters:

Name Type Description Default
basis_states BasisStates

The basis states for the weighted ensemble.

 required
target_threshold float

The target threshold for the progress coordinate to be considered in the target state.

 required
pcoord_idx int

The index of the progress coordinate to use for recycling. Only applicable if a multi-dimensional pcoord is used, will choose the specified index of the pcoord for recycling. Default is 0.

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Source code in deepdrivewe/recyclers/high.py 
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def __init__(
    self,
    basis_states: BasisStates,
    target_threshold: float,
    pcoord_idx: int = 0,
) -> None:
    """Initialize the recycler.

    Parameters
    ----------
    basis_states : BasisStates
        The basis states for the weighted ensemble.
    target_threshold : float
        The target threshold for the progress coordinate to be considered
        in the target state.
    pcoord_idx : int
        The index of the progress coordinate to use for recycling. Only
        applicable if a multi-dimensional pcoord is used, will choose the
        specified index of the pcoord for recycling. Default is 0.
    """
    super().__init__(basis_states)
    self.target_threshold = target_threshold
    self.pcoord_idx = pcoord_idx

recycle 

recycle(pcoords: ndarray) -> np.ndarray

Recycle the simulations above the target threshold.

Parameters:

Name Type Description Default
pcoords ndarray

The progress coordinates for the simulations. Shape: (n_simulations, n_dims).

 required

Returns:

Type Description
ndarray

The list of simulation indices to recycle. Shape: (n_recycled,)
Source code in deepdrivewe/recyclers/high.py 
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def recycle(self, pcoords: np.ndarray) -> np.ndarray:
    """Recycle the simulations above the target threshold.

    Parameters
    ----------
    pcoords : np.ndarray
        The progress coordinates for the simulations.
        Shape: (n_simulations, n_dims).

    Returns
    -------
    np.ndarray
        The list of simulation indices to recycle. Shape: (n_recycled,)
    """
    return np.where(pcoords[:, self.pcoord_idx] > self.target_threshold)[0]