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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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