Python – A mapping function for numpy matrices

I have two numpy matrices. One contains a lambda function. The other contains the value.

Is there a function like Python’s map function that allows me to get the expected result?

Is there a better way?

functionMatrix = np.array([[lambda x:x**2, lambda x:x**3],[lambda x: x**2, 
lambda x: np.sqrt(x)]])
valueMatrix = np.array([[1,2],[3,4]])

expectedResult = np.array([[1,8],[9,2]])

It’s just grammatical sugar, but it gets the job done.

@np.vectorize
def apply_vec(f, x):
    return f(x)

result = apply_vec(functionMatrix, valueMatrix)