Markov Chain One-Step

Problem

One-step update of a Markov chain distribution.

Given a probability vector state and a transition matrix where matrix[i][j] = P(i -> j), return the row vector with entries sum_i state[i] * matrix[i][j].

Hint

Multiply the row vector by the transition matrix.

Test cases

case 1

in: [[1,0],[[0.5,0.5],[0.2,0.8]]]

expected: [0.5,0.5]

case 2

in: [[0,1],[[0.5,0.5],[0.2,0.8]]]

expected: [0.2,0.8]

case 3

in: [[0.3,0.7],[[1,0],[0.4,0.6]]]

expected: [0.58,0.42]

case 4

in: [[0.5,0.5],[[1,0],[1,0]]]

expected: [1,0]

Starter codePython

def markov_one_step(state, matrix):
    # Your code here
    pass

4 test cases · run your code against them in the editor