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...

 import numpy as np
 print "<== print version ==>"
 print np.version.version
 print "<== 1-dimensional array ==>"
 print np.array([1, 2, 3, 4, 5])
 print "<== 2-dimentional array ==>"
 print np.array([[1,2],[3,4]])
 print "<== int32,int16,etc. ==>"
 print np.array((1, 2, 3, 4), dtype = np.float64)
 print "<== get a 3*5 array ==>"
 print np.arange(15).reshape(3, 5)
 print "<== generate 4 data from 1 to 5 ==>"
 print np.linspace(1, 5, 4)
 print "<== like what in matlab ==>"
 print np.zeros((2, 5))#
 print '\n'
 print np.ones((2,5))
 print '\n'
 print np.eye(3)
 
 a = np.eye(4)
 print "<== sum ==>"
 a.sum()
 a.sum(axis=0)
 print "<== min and max ==>"
 a.min()
 a.max()
 np.sin(a)
 np.floor(a)
 np.exp(a)
 np.dot(a, a)
 
 a = np.ones((2,2))
 b = np.eye(2)
 print "<== visit array ==>"
 print a[0, 0]
 print "<== merge: shallow copy: learn from v and h ==>"
 print np.vstack((a,b))
 print np.hstack((a,b))
 print "<== deep copy ==>"
 c = a.copy()
 print "<== transpose ==>"
 print c.transpose()
 print "<== trace ==>"
 print c.trace()
 print "<== more matrix operations in linalg ==>"
 import numpy.linalg as nplg
 print nplg.eig(a)