`deepmd.utils.out_stat`

Output statistics.

Module Contents

`compute_stats_from_redu`(→ Tuple[numpy.ndarray, ...)	Compute the output statistics.
`compute_stats_from_atomic`(→ Tuple[numpy.ndarray, ...)	Compute the output statistics.

deepmd.utils.out_stat.compute_stats_from_redu(output_redu: numpy.ndarray, natoms: numpy.ndarray, assigned_bias: numpy.ndarray | None = None, rcond: float | None = None) → Tuple[numpy.ndarray, numpy.ndarray][source]

Compute the output statistics.

Given the reduced output value and the number of atoms for each atom, compute the least-squares solution as the atomic output bais and std.

Parameters:

output_redu: The reduced output value, shape is [nframes, *(odim0, odim1, …)].
natoms: The number of atoms for each atom, shape is [nframes, ntypes].
assigned_bias: The assigned output bias, shape is [ntypes, *(odim0, odim1, …)]. Set to a tensor of shape (odim0, odim1, …) filled with nan if the bias of the type is not assigned.
rcond: Cut-off ratio for small singular values of a.

Returns:

np.ndarray: The computed output bias, shape is [ntypes, *(odim0, odim1, …)].
np.ndarray: The computed output std, shape is [*(odim0, odim1, …)].

deepmd.utils.out_stat.compute_stats_from_atomic(output: numpy.ndarray, atype: numpy.ndarray) → Tuple[numpy.ndarray, numpy.ndarray][source]

Compute the output statistics.

Given the output value and the type of atoms, compute the atomic output bais and std.

Parameters:

Returns: