Python(Numpy)数组排序

Question

我有一个名为v的dtype('float64')数组:

array([[  9.33350000e+05,   8.75886500e+06,   3.45765000e+02],
       [  4.33350000e+05,   8.75886500e+06,   6.19200000e+00],
       [  1.33360000e+05,   8.75886500e+06,   6.76650000e+02]])

...我通过使用np.loadtxt命令从文件中获取的.我想在第一列的值之后对其进行排序,而不会混淆将数字列在同一行上的结构.使用v.sort(axis = 0)给我:

array([[  1.33360000e+05,   8.75886500e+06,   6.19200000e+00],
       [  4.33350000e+05,   8.75886500e+06,   3.45765000e+02],
       [  9.33350000e+05,   8.75886500e+06,   6.76650000e+02]])

...即将第三列中最小数量的第一列放在第一行等等.我宁愿想要这样的东西......

array([[  1.33360000e+05,   8.75886500e+06,   6.76650000e+02],
       [  4.33350000e+05,   8.75886500e+06,   6.19200000e+00],
       [  9.33350000e+05,   8.75886500e+06,   3.45765000e+02]])

......每条线的元素没有相对移动.

Answer 1

尝试

v[v[:,0].argsort()]

(v作为阵列). v[:,0]是第一列,并.argsort()返回将第一列排序的索引.然后使用高级索引将此排序应用于整个数组.请注意,您将获得该阵列的sorte副本.

我知道对数组进行排序的唯一方法是使用记录dtype:

v.dtype = [("x", float), ("y", float), ("z", float)]
v.shape = v.size
v.sort(order="x")

Answer 2

另外

尝试

import numpy as np

order = v[:, 0].argsort()
sorted = np.take(v, order, 0)

'order'具有第一行的顺序.然后'np.take'将列按相应的顺序排列.

请参阅'np.take'的帮助

help(np.take)

take(a,indices,axis = None,out = None,mode ='raise')沿轴取一个数组中的元素.

This function does the same thing as "fancy" indexing (indexing arrays
using arrays); however, it can be easier to use if you need elements
along a given axis.

Parameters
----------
a : array_like
    The source array.
indices : array_like
    The indices of the values to extract.
axis : int, optional
    The axis over which to select values. By default, the flattened
    input array is used.
out : ndarray, optional
    If provided, the result will be placed in this array. It should
    be of the appropriate shape and dtype.
mode : {'raise', 'wrap', 'clip'}, optional
    Specifies how out-of-bounds indices will behave.

    * 'raise' -- raise an error (default)
    * 'wrap' -- wrap around
    * 'clip' -- clip to the range

    'clip' mode means that all indices that are too large are

由追踪该轴的最后一个元素的索引替换.请注意,这会禁用带负数的索引.

Returns
-------
subarray : ndarray
    The returned array has the same type as `a`.

See Also
--------
ndarray.take : equivalent method

Examples
--------
>>> a = [4, 3, 5, 7, 6, 8]
>>> indices = [0, 1, 4]
>>> np.take(a, indices)
array([4, 3, 6])

In this example if `a` is an ndarray, "fancy" indexing can be used.

>>> a = np.array(a)
>>> a[indices]
array([4, 3, 6])