[英]Replace values in numpy array equal to list of values
I have a numpy array - image with various values: example image = [1,2,2, 3, 4, 4, 4, 4, 5, 6, 6,7,8,8,8,8] I want to replace only those numbers occurring less than twice - by a specific number, let's say 0. I managed to create the list of those numbers like this:我有一个 numpy 数组 - 具有各种值的图像:示例图像 = [1,2,2, 3, 4, 4, 4, 4, 5, 6, 6,7,8,8,8,8] 我想只替换那些出现少于两次的数字 - 用一个特定的数字,比如说 0。我设法创建了这些数字的列表,如下所示:
(unique, counts) = np.unique(image, return_counts=True)
frequencies = np.asarray((unique, counts)).T
freq = frequencies[frequencies[:,1] < 2,0]
print(freq)
array([1, 3, 5, 7], dtype=int64)
How do I replace those numbers by zero?如何用零替换这些数字?
the outcome should look like: [0,2,2, 0, 4, 4, 4, 4, 0, 6, 6,0,8,8,8,8]结果应如下所示: [0,2,2, 0, 4, 4, 4, 4, 0, 6, 6,0,8,8,8,8]
Thanks in advance!提前致谢!
If both image
and freq
are numpy arrays:如果
image
和freq
都是 numpy arrays:
freq = np.array([1, 3, 5, 7])
image = np.array([1 ,2 ,2, 3, 4, 4, 4, 4, 5, 6, 6 ,7 ,8 ,8 ,8 ,8])
Solution 1解决方案 1
You can then find the indices of image
entries appearing in freq
, then set them to zero:然后,您可以找到出现在
freq
中的image
条目的索引,然后将它们设置为零:
image[np.argwhere(np.isin(image, freq)).ravel()] = 0
Based on: Get indices of items in numpy array, where values is in list .基于: 获取 numpy 数组中项目的索引,其中值在 list 中。
Solution 2解决方案 2
Use np.in1d
:使用
np.in1d
:
image = np.where(np.in1d(image,freq),0,image)
More info: Numpy - check if elements of a array belong to another array更多信息: Numpy - 检查一个数组的元素是否属于另一个数组
Solution 3解决方案 3
You can also use a list comprehension:您还可以使用列表推导:
image = [each if each not in freq else 0 for each in image]
Can find more info here: if/else in a list comprehension .可以在这里找到更多信息: if/else in a list comprehension 。
The last one will result in a list, not a numpy array, but other than that, all of these yield the same result.最后一个将产生一个列表,而不是 numpy 数组,但除此之外,所有这些都会产生相同的结果。
You could compare each item to the rest of the array to form a 2D matrix and sum each count.您可以将每个项目与数组的 rest 进行比较,以形成一个二维矩阵并对每个计数求和。 Then assign the items meeting the frequency condition with the desired value:
然后将满足频率条件的项目分配给期望的值:
import numpy as np
img = np.array([1 ,2 ,2, 3, 4, 4, 4, 4, 5, 6, 6 ,7 ,8 ,8 ,8 ,8])
img[np.sum(img==img[:,None],axis=1)<2] = 0
array([0, 2, 2, 0, 4, 4, 4, 4, 0, 6, 6, 0, 8, 8, 8, 8])
Probably not very efficient but it should work.可能效率不高,但应该可以。
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