stroke.py

matrix_shape = matrix.shape
flat_matrix = matrix.flatten()
ls_matrix = flat_matrix.tolist()

num_items = len(ls_matrix)

for stricken in range(int(num_items * self.v_ratio)):
    if self.value:
        ls_matrix[random.randint(0, len(ls_matrix) - 1)] = self.value
    else:
        ls_matrix[random.randint(0, len(ls_matrix) - 1)] = random.uniform(self.low_bound, self.high_bound)

matrix = np.array(ls_matrix)
matrix = np.reshape(matrix, matrix_shape)