Skip to main content
`Ctrl`+`K`
scipy.linalg.

# sinm

scipy.linalg.sinm(A)

  Compute the matrix sine.

  This routine uses expm to compute the matrix exponentials.

  The documentation is written assuming array arguments are of specified “core” shapes. However, array argument(s) of this function may have additional “batch” dimensions prepended to the core shape. In this case, the array is treated as a batch of lower-dimensional slices; see Batched Linear Operations for details.

  Parameters:
    A(N, N) array_like

      Input array.

  Returns:
    sinm(N, N) ndarray

      Matrix sine of A

  Examples

      >>> import numpy as np
      >>> from scipy.linalg import expm, sinm, cosm

  Euler’s identity (exp(i*theta) = cos(theta) + i*sin(theta)) applied to a matrix:

      >>> a = np.array([[1.0, 2.0], [-1.0, 3.0]])
      >>> expm(1j*a)
      array([[ 0.42645930+1.89217551j, -2.13721484-0.97811252j],
             [ 1.06860742+0.48905626j, -1.71075555+0.91406299j]])
      >>> cosm(a) + 1j*sinm(a)
      array([[ 0.42645930+1.89217551j, -2.13721484-0.97811252j],
             [ 1.06860742+0.48905626j, -1.71075555+0.91406299j]])