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sponge.function.calc_torsion

sponge.function.calc_torsion(position_a: Tensor, position_b: Tensor, position_c: Tensor, position_d: Tensor, pbc_box: Tensor = None, keepdims: bool = False)

Compute torsion angle $A-B-C-D$ formed by four positions $A$, $B$, $C$ and $D$ with or without periodic boundary condition.

Parameters

• position_a (Tensor) – Tensor of shape $(...,D)$. Data type is float. D is spatial dimension of the simulation system. Usually is 3. Position coordinate of point $A$.

• position_b (Tensor) – Tensor of shape $(...,D)$. Data type is float. Position coordinate of point $B$.

• position_c (Tensor) – Tensor of shape $(...,D)$. Data type is float. Position coordinate of point $C$.

• position_d (Tensor) – Tensor of shape $(...,D)$. Data type is float. Position coordinate of point $D$.

• pbc_box (Tensor) – Tensor of shape $(D)$ or $(B,D)$. Data type is float. B is batchsize, i.e. number of walkers in simulation. Size of PBC box $\overrightarrow{L}$. Default: None.

• keepdims (bool) – If this is set to True , the last axis will be left in the result as dimensions with size one. Default: False .

Returns

torsion (Tensor), a tensor of shape $(...)$ or $(...,1)$. Data type is float.

Supported Platforms:

Ascend GPU

Examples

>>> import mindspore as ms
>>> import numpy as np
>>> from mindspore import Tensor
>>> from sponge.function import calc_torsion
>>> crd = Tensor(np.random.random((4, 3)), ms.float32)
>>> pbc_box = Tensor([[3, 3, 3]], ms.float32)
>>> calc_torsion(crd[0], crd[1], crd[2], crd[3], pbc_box)
Tensor(shape=[1], dtype=Float32, value= [-2.33294296e+00])