Python numpy学习笔记（一）

下边代码是关于numpy的一些基本用法，包括数组和矩阵操作等...

 

 1 import numpy as np

 2 print "<== print version ==>"

 3 print np.version.version

 4 print "<== 1-dimensional array ==>"

 5 print np.array([1, 2, 3, 4, 5])

 6 print "<== 2-dimentional array ==>"

 7 print np.array([[1,2],[3,4]])

 8 print "<== int32,int16,etc. ==>"

 9 print np.array((1, 2, 3, 4), dtype = np.float64)

10 print "<== get a 3*5 array ==>"

11 print np.arange(15).reshape(3, 5)

12 print "<== generate 4 data from 1 to 5 ==>"

13 print np.linspace(1, 5, 4)

14 print "<== like what in matlab ==>"

15 print np.zeros((2, 5))#

16 print '\n'

17 print np.ones((2,5))

18 print '\n'

19 print np.eye(3)

20 

21 a = np.eye(4)

22 print "<== sum ==>"

23 a.sum()

24 a.sum(axis=0)

25 print "<== min and max ==>"

26 a.min()

27 a.max()

28 np.sin(a)

29 np.floor(a)

30 np.exp(a)

31 np.dot(a, a)

32 

33 a = np.ones((2,2))

34 b = np.eye(2)

35 print "<== visit array ==>"

36 print a[0, 0]

37 print "<== merge: shallow copy: learn from v and h ==>"

38 print np.vstack((a,b))

39 print np.hstack((a,b))

40 print "<== deep copy ==>"

41 c = a.copy()

42 print "<== transpose ==>"

43 print c.transpose()

44 print "<== trace ==>"

45 print c.trace()

46 print "<== more matrix operations in linalg ==>"

47 import numpy.linalg as nplg

48 print nplg.eig(a)

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