numpy的argsort可以给相同元素相同的等级吗? [英] Can numpy's argsort give equal element the same rank?
问题描述
我想获取每个元素的排名,所以我在numpy
中使用argsort
:
I want to get the rank of each element, so I use argsort
in numpy
:
np.argsort(np.array((1,1,1,2,2,3,3,3,3)))
array([0, 1, 2, 3, 4, 5, 6, 7, 8])
它给同一元素不同的等级,我可以得到相同的等级吗?
it give the same element the different rank, can I get the same rank like:
array([0, 0, 0, 3, 3, 5, 5, 5, 5])
推荐答案
If you don't mind a dependency on scipy, you can use scipy.stats.rankdata
, with method='min'
:
In [14]: a
Out[14]: array([1, 1, 1, 2, 2, 3, 3, 3, 3])
In [15]: from scipy.stats import rankdata
In [16]: rankdata(a, method='min')
Out[16]: array([1, 1, 1, 4, 4, 6, 6, 6, 6])
请注意,rankdata
将排名从1开始.要从0开始,请从结果中减去1:
Note that rankdata
starts the ranks at 1. To start at 0, subtract 1 from the result:
In [17]: rankdata(a, method='min') - 1
Out[17]: array([0, 0, 0, 3, 3, 5, 5, 5, 5])
如果您不希望scipy依赖,则可以使用 numpy.unique
来计算排名.这是一个计算与rankdata(x, method='min') - 1
相同结果的函数:
If you don't want the scipy dependency, you can use numpy.unique
to compute the ranking. Here's a function that computes the same result as rankdata(x, method='min') - 1
:
import numpy as np
def rankmin(x):
u, inv, counts = np.unique(x, return_inverse=True, return_counts=True)
csum = np.zeros_like(counts)
csum[1:] = counts[:-1].cumsum()
return csum[inv]
例如,
In [137]: x = np.array([60, 10, 0, 30, 20, 40, 50])
In [138]: rankdata(x, method='min') - 1
Out[138]: array([6, 1, 0, 3, 2, 4, 5])
In [139]: rankmin(x)
Out[139]: array([6, 1, 0, 3, 2, 4, 5])
In [140]: a = np.array([1,1,1,2,2,3,3,3,3])
In [141]: rankdata(a, method='min') - 1
Out[141]: array([0, 0, 0, 3, 3, 5, 5, 5, 5])
In [142]: rankmin(a)
Out[142]: array([0, 0, 0, 3, 3, 5, 5, 5, 5])
顺便说一句,对argsort()
的单次调用不会给出排名.您可以在问题数组使用Python/NumPy ,包括如何使用argsort()
来实现.
By the way, a single call to argsort()
does not give ranks. You can find an assortment of approaches to ranking in the question Rank items in an array using Python/NumPy, including how to do it using argsort()
.
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