The numpy (np) and scipy.linalg modules provide a variety of functions for matrix operations:

• Addition & Subtraction: np.add(A, D), np.subtract(A, D)
• Division: np.divide(A, D)
• Multiplication: A @ D (matrix multiplication operator), np.multiply(D, A) (element-wise), np.dot(A, D) (dot product), np.vdot(A, D) (vector dot product), np.inner(A, D) (inner product), np.outer(A, D) (outer product), np.tensordot(A, D) (tensor dot product), np.kron(A, D) (Kronecker product)
• Exponential: linalg.expm(A) (matrix exponential), linalg.expm2(A) (Taylor series), linalg.expm3(D) (eigenvalue decomposition)
• Logarithmic: linalg.logm(A)
• Trigonometric: linalg.sinm(D), linalg.cosm(D), linalg.tanm(A)
• Hyperbolic: linalg.sinhm(D), linalg.coshm(D), linalg.tanhm(A)
• Sign: np.signm(A)
• Square Root: linalg.sqrtm(A)
• Arbitrary: linalg.funm(A, lambda x: x*x)