sponge.metrics.Metric

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class sponge.metrics.Metric[source]

Metric is fundamental tool used to assess the state and performance of a simulation system. Which provides a mechanism to track the changes in various physical quantities within the simulation system. The base class of Metrics defines a set of methods that are used to update the state information of the simulation system and to calculate the corresponding metrics.

update(coordinate: Tensor, pbc_box: Tensor = None, energy: Tensor = None, force: Tensor = None, potentials: Tensor = None, total_bias: Tensor = None, biases: Tensor = None)[source]

update the state information of the simulation system.

Parameters

  • coordinate (Tensor) – Tensor of shape (B, A, D). Data type is float. Position coordinate of atoms in system.

  • pbc_box (Tensor, optional) – Tensor of shape (B, D). Data type is float. Tensor of PBC box. Default: None.

  • energy (Tensor, optional) – Tensor of shape (B, 1). Data type is float. Total energy of the simulation system. Default: None.

  • force (Tensor, optional) – Tensor of shape (B, A, D). Data type is float. Force on each atoms of the simulation system. Default: None.

  • potentials (Tensor, optional) – Tensor of shape (B, U). Data type is float. All potential energies. Default: None.

  • total_bias (Tensor, optional) – Tensor of shape (B, 1). Data type is float. Total bias energy for reweighting. Default: None.

  • biases (Tensor, optional) – Tensor of shape (B, V). Data type is float All bias potential energies. Default: None.

Note

  • B: Batchsize, i.e. number of walkers in simulation.

  • A: Number of atoms of the simulation system.

  • D: Dimension of the space of the simulation system. Usually is 3.

  • U: Number of potential energies.

  • V: Number of bias potential energies.

Supported Platforms:

Ascend GPU

Examples

>>> import numpy as np
>>> from mindspore import Tensor
>>> from sponge.metrics import Metric
>>> net = Metric()