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