subtract

metatensor.subtract(A: TensorMap, B: float | int | TensorMap) → TensorMap

Return a new TensorMap with the values being the subtract of A and B.

If B is a TensorMap it has to have the same metadata as A.

If gradients are present in A:

• B is a scalar:

  $$\mathrm{\nabla }(A-B)=\mathrm{\nabla }A$$

• B is a TensorMap with the same metadata of A:

  $$\mathrm{\nabla }(A-B)=\mathrm{\nabla }A-\mathrm{\nabla }B$$

Parameters:

• A (TensorMap) – First TensorMap for the subtraction.

• B (float | int | TensorMap) – Second instance for the subtraction. Parameter can be a scalar or a TensorMap. In the latter case B must have the same metadata of A.

Returns:

New TensorMap with the same metadata as A.

Return type:

TensorMap