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Python之Numpy实践笔记(1)

Python之Numpy实践笔记(1)

作者: ankiyang | 来源:发表于2016-04-28 17:52 被阅读0次

1.向量加法:

(1)纯python代码:

#!/usr/bin/env python

# -*- coding:utf-8 -*-

defpythonsum(n):

a =range(n)

b =range(n)

c = []

foriinrange(len(a)):

a[i] = i **2

b[i] = i **3

c.append(a[i] + b[i])

returnc

n =input('please give me an n value:')

c = pythonsum(n)

printc

注:这里使用raw_input 会报错

运行:

please give me an n value:5

[0, 2, 12, 36, 80]

(2)使用Numpy:

#!/usr/bin/env python

# -*- coding:utf-8 -*-

importnumpy

defnumpysum(n):

a = numpy.arange(n) **2

b = numpy.arange(n) **3

c = a + b

returnc

n =input('please give me an n value:')

c =numpysum(n)

printc

运行:

please give me an n value:5

[ 02 12 36 80]

这里,使用numpy中的arange函数来创建包含0~n的整数的numpy数组(arange函数从numpy模块中导入)。

numpysum()函数的输出不包括逗号,因为,我们在这里使用的是numpy数组,而非python自身的list容器。numpy数组对象以专用数据结构来存储数值。

接下来的程序将以微妙的精度分别记录numpysum()和pythonsum()函数的耗时,还将输出向量相加之后最末的两个元素

#!/usr/bin/env python

# -*- coding:utf-8 -*-

importsys

importnumpyasnp

fromdatetimeimportdatetime

'''

put this command to run :

python numpy_practice.py n

'''

defnumpysum(n):

a = np.arange(n) **2

b = np.arange(n) **3

c = a + b

returnc

defpythonsum(n):

a =range(n)

b =range(n)

c = []

foriinrange(len(a)):

a[i] = i **2

b[i] = i **3

c.append(a[i] + b[i])

returnc

size =int(sys.argv[1])

start = datetime.now()

c = pythonsum(size)

delta =  datetime.now() - start

print"The last 2 elements of the sum",c[-2:]

print"PythonSum elapsed time in microseconds",delta.microseconds

start = datetime.now()

c = numpysum(size)

delta = datetime.now() - start

print"The last 2 elements of the sum",c[-2:]

print"NumPySum elapsed time in microseconds",delta.microseconds

运行(python 文件名 n)(n为指定向量大小的整数) :

$ python2 numpy_practice.py 2000

The last 2 elements of the sum [7980015996, 7992002000]

PythonSum elapsed time in microseconds 1034

The last 2 elements of the sum [7980015996 7992002000]

NumPySum elapsed time in microseconds 271

$ python2 numpy_practice.py 3000

The last 2 elements of the sum [26955023996, 26982003000]

PythonSum elapsed time in microseconds 1661

The last 2 elements of the sum [26955023996 26982003000]

NumPySum elapsed time in microseconds 371

注:使用ipython ,在pylab模式下,ipython将自动导入scipy numpy和matplotlib模块

$ipython2 --pylab

在当前目录下,可以按照下面这样自运行python脚本

In [3]: %run -i numpy_practice.py 1000

%run的-d参数将开启ipdb调试器,键入c后,脚本开始逐行执行了,在ipdb提示符后键入quit可以关闭调试器

%run的-p参数对脚本进行性能分析

%hist命令可以查看命令行历史记录

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