# 12572 - Python2020 Quiz7 Problem2
###### tags: `Quiz`

[TOC]

## Description
Define a Matrix class to represent numbers as a two-dimensional array.
The constructor for the matrix is a list of lists of numbers. A 3x3 matrix

would be constructed as
M = Matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]])

The Matrix class would support several methods, and the usage is as follows:

>>> import random
>>> random.seed(0) # set the seed so that the result of randomize() will be predictable.
>>> M = Matrix([[1, 2, 3], [4, 5, 6]])
>>> M = M.randomize()
>>> M.row(1)
[1, 6, 4]
>>> N = Matrix([[1, 2, 3], [4, 5, 6]])
>>> N = N.transpose()
>>> N.column(0)
[1, 2, 3]

#### Input
6 statements.
Instantiate a Matrix M.
Execute M = M.randomize()
Print a specific row of Matrix M.
Instantiate a Matrix N.
Execute N = N.transpose()
Print a specific column of Matrix N.

###### Sample Input

M = Matrix([[1, 2, 3], [4, 5, 6]])
M = M.randomize()
print(M.row(1))
N = Matrix([[1, 2, 3], [4, 5, 6]])
N = N.transpose()
print(N.column(0))

#### Output
2 lines.
The specific row of Matrix M after executing M = M.randomize()
The specific column of Matrix N after executing N = N.transpose()

###### Sample Output

[1, 6, 4]
[1, 2, 3]

## Solution

import random
random.seed(0) # You must initiate the random seed to 0 for judging purpose.

class Matrix:
    def __init__(self, data):
        # data is the list of lists of value
        self._data = data

    def row(self, r):
        # return the r-th row in the form of a list
        # r is from 0.. number of rows
        # in the exmaple above, M.row(1) would return
        # [4, 5, 6]
        return self._data[r]

    def column(self, c):
        # return a the c-th column in the form of a list.
        # in the example above, M.column(2) would return 
        # [3, 6, 9]
        return [i[c] for i in self._data]

    @property
    def nrows(self):
        # return the number of rows
        return len(self._data)

    @property
    def ncolumns(self):
        # return the number of columns
        return len(self._data[0])

    def transpose(self):
        # return a new Matrix whose content is same as this 
        # Matrix except the row and column positions are 
        # switched.  In the example above, 
        # M.transpose() would return
        # Matrix([[1, 4, 7], [2, 5, 8], [3, 6, 9]])
        # Note: use zip() to do the transpose
        return Matrix(zip(*self._data))

    def randomize(self):
        # return another matrix whose content is the same as
        # this matrix except their positions are randomized.
        # Notice that you must reduce the dimensions of the matrix to one dimension(flatten it) 
        # and then randomize it using random.shuffle, and finally form the two dimensional matrix again.
        temp = []
        for i in self._data:
            temp.extend(i)
        random.shuffle(temp)
        ans = []
        for i in range(0, self.nrows*self.ncolumns, self.ncolumns):
            ans.append(temp[i:i+self.ncolumns])
        return Matrix(ans)

# For judging purpose
instantiate_M = input()
exec(instantiate_M)
randomize_M = input()
exec(randomize_M)
print_row_M = input()
exec(print_row_M)
instantiate_N = input()
exec(instantiate_N )
transpose_N = input()
exec(transpose_N )
print_row_N = input()
exec(print_row_N)