Python_Numpy教程_3_numpy a[:3]-优快云博客

本文详细介绍了使用NumPy进行数组操作的方法，包括复制与视图的区别、数组的创建与转换等，并通过实例演示了不同操作的效果。对于理解NumPy数组的行为特征非常有用。

复制和视图

完全不拷贝

>>> a = np.arange(12)
>>> b = a
>>> b is a
True
>>> b.shape = 3,4
>>> a.shape
(3, 4)
>>> def f(x):
	print(id(x))

	
>>> id(a)
2445715670480
>>> f(a)
2445715670480

视图view和浅拷贝

>>> c = a.view()
>>> c is a
False
>>> c.base is a
True
>>> c.flags.owndata
False
>>> c.shape = 2,6
>>> a.shape
(3, 4)
>>> c[0,4]  = 1234
>>> a
array([[   0,    1,    2,    3],
       [1234,    5,    6,    7],
       [   8,    9,   10,   11]])
>>> #a's shape doesn't change
>>> #a's data chages

深复制

>>> d = a.copy()
>>> d is a
False
>>> d.base is a
False
>>> d[0,0] = 9999
>>> a
array([[   0,    1,    2,    3],
       [1234,    5,    6,    7],
       [   8,    9,   10,   11]])

函数和方法method总览

创建数组

arange, array, copy, empty, empty_like, eye, fromfile, fromfunction, identity, linspace, logspace, mgrid, ogrid, ones, ones_like, r , zeros, zeros_like

转化

astype, atleast 1d, atleast 2d, atleast 3d, mat

操作

array split, column stack, concatenate, diagonal, dsplit, dstack, hsplit, hstack, item, newaxis, ravel, repeat, reshape, resize, squeeze, swapaxes, take, transpose, vsplit, vstack

询问

all, any, nonzero, where

排序

argmax, argmin, argsort, max, min, ptp, searchsorted, sort

运算

choose, compress, cumprod, cumsum, inner, fill, imag, prod, put, putmask, real, sum

基本统计

cov, mean, std, var

基本线性代数

cross, dot, outer, svd, vdot