零基础学python-19.3 列表解析与矩阵

这一章节我们来讨论一下列表解析与矩阵

1.矩阵

矩阵（Matrix）是指纵横排列的二维数据表格

我们先从idle里面顶一个两个矩阵

>>> M=[ [1,2,3],
	[2,3,4],
	[3,4,5] ]
>>> N=[ [5,6,7],
	[-2,-3,-4],
	[13,14,15] ]
>>>

从上面来看，列表嵌套列表暂时成为一个矩阵，根据列表的特性，我们总是可以根据索引来操作矩阵

>>> M=[ [1,2,3],
	[2,3,4],
	[3,4,5] ]
>>> N=[ [5,6,7],
	[-2,-3,-4],
	[13,14,15] ]
>>> M[1]
[2, 3, 4]
>>> N[0][0]
5
>>>

2.列表解析与矩阵

由于列表解析是迭代所有的行与列，因此，对于矩阵这种数据格式的操作尤为好用

下面是遍历每一行

>>> [row for row in M]
[[1, 2, 3], [2, 3, 4], [3, 4, 5]]

遍历某一列

>>> [M[row][1] for row in range(3)]
[2, 3, 4]

遍历对角线

>>> [M[i][i] for i in range(3)]
[1, 3, 5]
>>>

遍历每一个元素

>>> [M[row][col] for row in range(3) for col in range(3)]
[1, 2, 3, 2, 3, 4, 3, 4, 5]
>>>

列举M+N之后的元素

>>> M=[ [1,2,3],
	[2,3,4],
	[3,4,5] ]
>>> N=[ [5,6,7],
	[-2,-3,-4],
	[13,14,15] ]
>>> [M[row][col]+N[row][col] for row in range(3) for col in range(3)]
[6, 8, 10, 0, 0, 0, 16, 18, 20]
>>>

M+N之后组成新矩阵

>>> M=[ [1,2,3],
	[2,3,4],
	[3,4,5] ]
>>> N=[ [5,6,7],
	[-2,-3,-4],
	[13,14,15] ]
>>> [[M[row][col]+N[row][col] for col in range(3)] for row in range(3)]
[[6, 8, 10], [0, 0, 0], [16, 18, 20]]
>>>

M*N之后组成新矩阵

>>> M=[ [1,2,3],
	[2,3,4],
	[3,4,5] ]
>>> N=[ [5,6,7],
	[-2,-3,-4],
	[13,14,15] ]
>>> [[M[row][col]*N[col][row] for col in range(3)] for row in range(3)]
[[5, -4, 39], [12, -9, 56], [21, -16, 75]]
>>>

总结：这一章节主要讲述了通过列表的特性操作矩阵，以及列表解析与矩阵结合的矩阵运算

这一章节就说到这里，谢谢大家

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