Numpy基本操作

(1)numpy.sum() #相加。没有axis参数表示全部相加，axis＝0表示按列相加，axis＝1表示按照行的方向相加.

 import numpy as np  >>> a=np.sum([[0,1,2],[2,1,3]])  >>> a  9  >>> a=np.sum([[0,1,2],[2,1,3]],axis=0)  >>> a  array([2, 2, 5])  >>> a.shape  (3,)  >>> a=np.sum([[0,1,2],[2,1,3]],axis=1)  >>> a  array([3, 6])  >>> a.shape  (2,)  

(2)random.rand(3,3) #构造一个3*3的随机数组

In [23]:random.rand(3,3)Out[23]: array([[ 0.68078538,  0.04810055,  0.89237689],       [ 0.52380624,  0.74562381,  0.50066403],       [ 0.57931518,  0.86270485,  0.089004  ]])

(3)mat(random.rand(3,3)) #将3*3的随机数组转化为一个3*3的矩阵

In [24]:mat(random.rand(3,3))Out[24]: matrix([[ 0.11921999,  0.62176972,  0.57668133],        [ 0.36761748,  0.32223052,  0.60415149],        [ 0.16873549,  0.03998786,  0.33666076]])

(4)shape() #读取矩阵的长度。shape[0]就是读取矩阵第一维度的长度，shape[1]就是读取矩阵第二维度的长度。

In [26]:matDemo = mat(random.rand(3,5))In [27]:matDemo.shape[0]Out[27]: 3In [28]:matDemo.shape[1]Out[28]: 5In [29]:shape(matDemo)Out[29]: (3, 5)

（5）means( ) #求平均值，axis=None时计算数组中的所有值的平均值 ，axis=0时以列为单位计算数组的每列的所有值的平均值 ，axis=1时计算数组的每行为单位的所有值的平均值 ，dtype为指定数组中元素的类型，默认为float64

In [41]:aOut[41]: array([[1, 2],       [3, 4]])In [42]:mean(a)Out[42]: 2.5In [43]:mean(a,axis = 0)Out[43]: array([ 2.,  3.])In [44]:mean(a,axis = 1)Out[44]: array([ 1.5,  3.5])

(6)a.T #转置

In [48]:a = array([[1, 2], [3, 4]])In [48]:a.TOut[49]: array([[1, 3],       [2, 4]])

(7)reshape() #重塑数组的维数而不改变原来的数据

In [50]: b = array([1,2,3,4,5,6,7,8])In [51]: c = b.reshape((2,4))In [52]: cOut[52]: array([[1, 2, 3, 4],       [5, 6, 7, 8]])In [53]: d = b.reshape((2,2,2))In [54]: dOut[54]: array([[[1, 2],        [3, 4]],       [[5, 6],        [7, 8]]])In [55]: e = b.reshape((3,3))  #不能改变数组原来的元素Traceback (most recent call last):  File "<ipython-input-55-b3c555f1a0b0>", line 1, in <module>    e = b.reshape((3,3))ValueError: cannot reshape array of size 8 into shape (3,3)

(8)dot() #矩阵点乘

In [58]: a = array([[1,2],[3,4]])In [59]: b = array([[2,3],[4,5]])In [60]: c = dot(a,b)In [61]: cOut[61]: array([[10, 13],       [22, 29]])