Python Numpy matrix multiplication using loop to multiply multiple matrices together

Question

I have written code which creates matrices with name matrixi, where i is replaced with the current loop number:

for i in range(len(node2)):
    if sOrP[i] == 'S':
        #print('series connection')
        matrixTemplate = numpy.array([[1.0, 0.0], [0.0, 1.0]])  #Got to put 1.0 else it doesnt work
        matrixTemplate[0][1] = frequenciesList[0][i]
        globals()['matrix%s' % i] = matrixTemplate
        #print(matrixTemplate)
    elif sOrP[i] == 'P':
        #print('parallel connection')
        matrixTemplate = numpy.array([[1.0, 0.0], [0.0, 1.0]])
        matrixTemplate[1][0] = 1 / frequenciesList[0][i]
        globals()['matrix%s' % i] = matrixTemplate
        #print(matrixTemplate)

I then need to multiply the created matrices together:

Ty = matrix0 @ matrix1 @ matrix2 @ matrix3 @ matrix4 @ matrix5 @ matrix6 @ matrix7 @ matrix8 @ matrix9

This works but the code has to be able to take multiple inputs with potentially more or fewer matrices being created. In that case it wouldn't work.

Would it be possible to do the multiplication part using a loop or function?

Answer 1

You could use a list (or a dictionary) to hold your matrices:

matrices = []

for i in range(len(node2)):

    if (sOrP[i] == 'S'):
        #print('series connection')
        matrixTemplate = numpy.array([[1.0, 0.0],[0.0, 1.0]]) #Got to put 1.0 else it doesnt work

        matrixTemplate[0][1] = frequenciesList[0][i]

        matrices.append(matrixTemplate)

        #print(matrixTemplate)

    elif (sOrP[i] == 'P'):
        #print('parallel connection')
        matrixTemplate = numpy.array([[1.0, 0.0],[0.0, 1.0]])

        matrixTemplate[1][0] = 1/frequenciesList[0][i]

        matrices.append(matrixTemplate)

        #print(matrixTemplate)

And then use reduce and numpy.matmul to compute your total matrix product:

from functools import reduce

Ty = reduce(numpy.matmul, matrices)