mindspore.ops.DihedralAtomEnergy

class mindspore.ops.DihedralAtomEnergy(dihedral_numbers)[source]

Add the potential energy caused by dihedral terms to the total potential energy of each atom.

Because there is a large amount of inputs and each of them are related, there is no way to construct Examples using random methods. For details, refer the webpage SPONGE in MindSpore.

The calculation formula is the same as operator DihedralEnergy().

Parameters

dihedral_numbers (int32) – the number of dihedral terms m.

Inputs:

  • uint_crd_f (Tensor) - The unsigned int coordinates value of each atom. The data type is uint32 and the shape is \((n, 3)\).

  • scaler_f (Tensor) - The 3-D scale factor between the real space float coordinates and the unsigned int coordinates. The data type is float32 and the shape is \((3,)\).

  • atom_a (Tensor) - The 1st atom index of each dihedral. The data type is int32 and the shape is \((m,)\).

  • atom_b (Tensor) - The 2nd atom index of each dihedral. The data type is int32 and the shape is \((m,)\).

  • atom_c (Tenso) - The 3rd atom index of each dihedral. The data type is int32 and the shape is \((m,)\).

  • atom_d (Tensor) - The 4th atom index of each dihedral. 4 atoms are connected in the form a-b-c-d. The data type is int32 and the shape is \((m,)\).

  • ipn (Tensor) - The period of dihedral angle of each dihedral. The data type is int32 and the shape is \((m,)\).

  • pk (Tensor) - The force constant of each dihedral. The data type is float32 and the shape is \((m,)\).

  • gamc (Tensor) - k*cos(phi_0) of each dihedral. The data type is float32 and the shape is \((m,)\).

  • gams (Tensor) - k*sin(phi_0) of each dihedral. The data type is float32 and the shape is \((m,)\).

  • pn (Tensor) - The floating point form of ipn. The data type is float32 and the shape is \((m,)\).

Outputs:

  • ene (Tensor) - The accumulated potential energy for each atom. The data type is float32 and the shape is \((n,)\).

Supported Platforms:

GPU