# numpy——数组的计算

1.数组和数字进行运算——广播

``````t5
Out[3]:
array([[ 0,  1,  2,  3,  4,  5],
[ 6,  7,  8,  9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23]])
``````

``````t5+2
Out[4]:
array([[ 2,  3,  4,  5,  6,  7],
[ 8,  9, 10, 11, 12, 13],
[14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25]])
``````

2.数组和数组计算：

``````t6=np.arange(100,124).reshape((4,6))
t6
Out[6]:
array([[100, 101, 102, 103, 104, 105],
[106, 107, 108, 109, 110, 111],
[112, 113, 114, 115, 116, 117],
[118, 119, 120, 121, 122, 123]])
t6+t5
Out[7]:
array([[100, 102, 104, 106, 108, 110],
[112, 114, 116, 118, 120, 122],
[124, 126, 128, 130, 132, 134],
[136, 138, 140, 142, 144, 146]])

``````

2.维度不同相加减

``````t7=np.arange(0,6)
t7
Out[10]: array([0, 1, 2, 3, 4, 5])
t5
Out[11]:
array([[ 0,  1,  2,  3,  4,  5],
[ 6,  7,  8,  9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23]])
t5-t7
Out[12]:
array([[ 0,  0,  0,  0,  0,  0],
[ 6,  6,  6,  6,  6,  6],
[12, 12, 12, 12, 12, 12],
[18, 18, 18, 18, 18, 18]])

``````

``````t8
Out[19]: array([[0, 1, 2, 3]])
t8=t8.reshape((4,1))
t8
Out[21]:
array([[0],
[1],
[2],
[3]])
t5-t8
Out[22]:
array([[ 0,  1,  2,  3,  4,  5],
[ 5,  6,  7,  8,  9, 10],
[10, 11, 12, 13, 14, 15],
[15, 16, 17, 18, 19, 20]])
``````

shape(3,3,3)的数组不能和shape（3，2）的数组计算
shape（3，3，2）的数组可以和shape（3，2）的数组计算