计算 numy.ndarray 中大于某个值的元素数

Question

我想计算 numpy.ndarry 中大于某个值的元素数。 我如何获得所需的结果？

例如：

[[0.25656927 0.31030828 0.23430803 0.25999823 0.20450112 0.19383106
  0.35779405 0.36355627 0.16837767 0.1933686  0.20630316 0.17804974
  0.06902786 0.26209944 0.21310201 0.12016498 0.14213449 0.16639964
  0.33461425 0.15897344 0.20293266 0.14630634 0.2509769  0.17211646
  0.3922994  0.14036047 0.12571093 0.25565785 0.18216616 0.0728473
  0.25328827 0.1476636  0.1873344  0.12253726 0.16082433 0.20678088
  0.33296013 0.03104548 0.14949016 0.05495472 0.1494042  0.32033417
  0.05361898 0.14325878 0.16196126 0.15796155 0.10990247 0.14499696]]

是数组，我想要大于0.19214945092486838的元素数。 这里的值为 21。如何计算？

Answer 1

你可以简单地做：

import numpy

arr = numpy.asarray([0.25656927, 0.31030828, 0.23430803, 0.25999823, 0.20450112, 0.19383106, 0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974, 0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964, 0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646, 0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473, 0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088, 0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417, 0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696])

print((arr > 0.19214945092486838).sum())

输出为： 21

Answer 2

ar[ar>0.19214945092486838]将为您提供高于当前值的元素列表。 你可以拿len来得到长度

>>> import numpy as np
>>> ar = np.array([0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,0.35779405,0.36355627,0.16837767,0.1933686,0.20630316,0.17804974    ,0.06902786,0.26209944,0.21310201,0.12016498,0.14213449,0.16639964,0.33461425,0.15897344,0.20293266,0.14630634,0.2509769,0.17211646    ,0.3922994,0.14036047,0.12571093,0.25565785,0.18216616,0.0728473,0.25328827,0.1476636,0.1873344,0.12253726,0.16082433,0.20678088    ,0.33296013,0.03104548,0.14949016,0.05495472,0.1494042,0.32033417,0.05361898,0.14325878,0.16196126,0.15796155,0.10990247,0.14499696])

>>> print(len(ar[ar>0.19214945092486838]))
>>> 21

Answer 3

这是一种方法

my_array = ... the target array ...
result = sum(0.19214945092486838 < x for x in my_array)

Answer 4

使用 numpy，您可以尝试：

Myarray= [ [ your array]]
Value_to_search=0.19214945092486838

Array_greater_than=Myarray>Value_to_search
Nb_Val_greater_than=Array_greater_than.sum()
print(Nb_Val_greater_than)

Answer 5

要获取项目大于/小于的数组：

>>> import numpy as np
>>> data = np.arange(12)
>>> data > 5
array([False, False, False, False, False, False,  True,  True,  True,
        True,  True,  True])

然后你只需要找到数组的总和：

>>> (data > 5).sum()
6

现在用您的值替换data ，并使用(data > 0.19214945092486838)代替。

Answer 6

以下代码片段将实现您的愿望:)

import numpy as np
arrayToCheck=np.array([0.25656927, 0.31030828, 0.23430803, 0.25999823, 0.20450112, 0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646,
  0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417,
  0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696])
print ("The number of float numbers above your threshold is " + str(np.sum(a>0.19214945092486838)))

Answer 7

最干净的方式（恕我直言）：

x > 1会将数组x转换为布尔数组，其中大于 1 的元素为 True。 然后你可以通过np.count_nonzero()计算 True 值

因此， np.count_nonzero(x > 1)

Answer 8

arr=np.array([0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686,  0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634 ,0.2509769 , 0.17211646,
  0.3922994 , 0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636 , 0.1873344 , 0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042 , 0.32033417,
  0.05361898, 0.14325878 ,0.16196126, 0.15796155, 0.10990247, 0.14499696])

数数：

arr[np.where(arr>0.19214945092486838)].shape[0]
    

Answer 9

您可以使用 len 来计算这样的结果：

import numpy as np

matrix = np.array([[0.25656927,0.31030828,0.23430803,0.25999823,0.20450112,0.19383106,
  0.35779405, 0.36355627, 0.16837767, 0.1933686, 0.20630316, 0.17804974,
  0.06902786, 0.26209944, 0.21310201, 0.12016498, 0.14213449, 0.16639964,
  0.33461425, 0.15897344, 0.20293266, 0.14630634, 0.2509769,  0.17211646,
  0.3922994,  0.14036047, 0.12571093, 0.25565785, 0.18216616, 0.0728473,
  0.25328827, 0.1476636,  0.1873344,  0.12253726, 0.16082433, 0.20678088,
  0.33296013, 0.03104548, 0.14949016, 0.05495472, 0.1494042,  0.32033417,
  0.05361898, 0.14325878, 0.16196126, 0.15796155, 0.10990247, 0.14499696]])

n = len(matrix[matrix > 0.18])
print(n)