原
花式索引与np.ix_函数
花式索引(Fancy indexing)是Numpy的一个术语，指的是利用整数数组进行索引。（不仅是1维，也可以是多维）
用法与例子如下：
创建 arr 数组
- >>> arr1 = np.empty((8,4)) # 创建一个8行4列的二维数组
-
- >>> for i in range(8): # 每一行赋值为0~7
- arr1[i] = i
-
- >>> arr1
-
- array([[ 0., 0., 0., 0.],
- [ 1., 1., 1., 1.],
- [ 2., 2., 2., 2.],
- [ 3., 3., 3., 3.],
- [ 4., 4., 4., 4.],
- [ 5., 5., 5., 5.],
- [ 6., 6., 6., 6.],
- [ 7., 7., 7., 7.]])
1、用1维数组进行索引
- >>> arr1[[4,3,0,6]]
- # 选取第4行、第3行、第0行、第6行
-
- array([[ 4., 4., 4., 4.],
- [ 3., 3., 3., 3.],
- [ 0., 0., 0., 0.],
- [ 6., 6., 6., 6.]])
2、用有负数的1维数组进行索引，就是从末尾开始选取行
- >>> arr1[[-3,-5,-7]]
- # 选取倒数第3行，倒数第5行，倒数第7行
-
- array([[ 5., 5., 5., 5.],
- [ 3., 3., 3., 3.],
- [ 1., 1., 1., 1.]])
在这里必须注意！
顺序选取是从0开始数的，a[0]代表第一个；而逆序选取是从1开始数的，a[-1]是倒数第一个
新建一个数组 arr2
- >>> arr2 = np.arange(32).reshape((8,4))
-
- >>> arr2
-
- array([[ 0, 1, 2, 3],
- [ 4, 5, 6, 7],
- [ 8, 9, 10, 11],
- [12, 13, 14, 15],
- [16, 17, 18, 19],
- [20, 21, 22, 23],
- [24, 25, 26, 27],
- [28, 29, 30, 31]])
3、按坐标选取每一个数
- >>> arr2[[1,5,7,2],[0,3,1,2]]
- # 意思就是，取坐标所对应的数(1,0)——4,(5,3)——23,(7,1)——29,(2,2)——10，然后返回一个数组
-
- array([ 4, 23, 29, 10])
4、希望先按我们要求选取行，再按顺序将列排序，获得一个矩形
- >>> arr2[[1,5,7,2]][:,[0,3,1,2]]
-
- array([[ 4, 7, 5, 6],
- [20, 23, 21, 22],
- [28, 31, 29, 30],
- [ 8, 11, 9, 10]])
先按先选取第1、5、2、7行，每一行再按第0个、第3个、第1个、第2个排序
5、np.ix_函数，能把两个一维数组 转换为 一个用于选取方形区域的索引器
实际意思就是，直接往np.ix_()里扔进两个一维数组[1,5,7,2]，[0,3,1,2]，就能先按我们要求选取行，再按顺序将列排序，跟上面得到的结果一样，而不用写“[ : , [0,3,1,2] ]”
原理：np.ix_函数就是输入两个数组，产生笛卡尔积的映射关系
- >>> arr2[np.ix_([1,5,7,2],[0,3,1,2])]
-
- array([[ 4, 7, 5, 6],
- [20, 23, 21, 22],
- [28, 31, 29, 30],
- [ 8, 11, 9, 10]])
例如就这个例子，np.ix_函数，将数组[1,5,7,2]和数组[0,3,1,2]产生笛卡尔积，就是得到(1,0)，(1,3)，(1,1)，(1,2)；(5,0)，(5,3)，(5,1)，(5,2)；(7,0)，(7,3)，(7,1)，(7,2)；(2,0)，(2,3)，(2,1)，(2,2)；
就是按照坐标(1,0)，(1,3)，(1,1)，(1,2)取得 arr2 所对应的元素4，7，5，6
(5,0)，(5,3)，(5,1)，(5,2)取得 arr2 所对应的元素20，23，21，22
如此类推。
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