如何在numpy中以二维矩阵随机采样 [英] how to randomly sample in 2D matrix in numpy
问题描述
我有一个像这样的2d数组/矩阵,我如何从这个2D矩阵中随机选择值,例如获取像[-62, 29.23]
这样的值.我看了numpy.choice
,但它是为一维数组构建的.
I have a 2d array/matrix like this, how would I randomly pick the value from this 2D matrix, for example getting value like [-62, 29.23]
. I looked at the numpy.choice
but it is built for 1d array.
以下是我的示例,其中包含4行8列
The following is my example with 4 rows and 8 columns
Space_Position=[
[[-62,29.23],[-49.73,29.23],[-31.82,29.23],[-14.2,29.23],[3.51,29.23],[21.21,29.23],[39.04,29.23],[57.1,29.23]],
[[-62,11.28],[-49.73,11.28],[-31.82,11.28],[-14.2,11.28],[3.51,11.28],[21.21,11.28] ,[39.04,11.28],[57.1,11.8]],
[[-62,-5.54],[-49.73,-5.54],[-31.82,-5.54] ,[-14.2,-5.54],[3.51,-5.54],[21.21,-5.54],[39.04,-5.54],[57.1,-5.54]],
[[-62,-23.1],[-49.73,-23.1],[-31.82,-23.1],[-14.2,-23.1],[3.51,-23.1],[21.21,-23.1],[39.04,-23.1] ,[57.1,-23.1]]
]
在回答中给出了以下解决方案:
In the answers the following solution was given:
random_index1 = np.random.randint(0, Space_Position.shape[0])
random_index2 = np.random.randint(0, Space_Position.shape[1])
Space_Position[random_index1][random_index2]
这确实可以给我一个示例,像np.choice()
一样有多个示例呢?
this indeed works to give me one sample, how about more than one sample like what np.choice()
does?
我在想的另一种方法是将矩阵转换成数组,而不是像
Another way I am thinking is to tranform the matrix into a array instead of matrix like,
Space_Position=[
[-62,29.23],[-49.73,29.23],[-31.82,29.23],[-14.2,29.23],[3.51,29.23],[21.21,29.23],[39.04,29.23],[57.1,29.23], ..... ]
,最后使用np.choice()
,但是我找不到进行转换的方法,np.flatten()
使数组类似
and at last use np.choice()
, however I could not find the ways to do the transformation, np.flatten()
makes the array like
Space_Position=[-62,29.23,-49.73,29.2, ....]
推荐答案
只需使用随机索引(在您的情况下为2,因为您有3个维度):
Just use a random index (in your case 2 because you have 3 dimensions):
import numpy as np
Space_Position = np.array(Space_Position)
random_index1 = np.random.randint(0, Space_Position.shape[0])
random_index2 = np.random.randint(0, Space_Position.shape[1])
Space_Position[random_index1, random_index2] # get the random element.
替代方法是将其实际制成2D:
The alternative is to actually make it 2D:
Space_Position = np.array(Space_Position).reshape(-1, 2)
,然后使用一个随机索引:
and then use one random index:
Space_Position = np.array(Space_Position).reshape(-1, 2) # make it 2D
random_index = np.random.randint(0, Space_Position.shape[0]) # generate a random index
Space_Position[random_index] # get the random element.
如果要替换N
个样品:
N = 5
Space_Position = np.array(Space_Position).reshape(-1, 2) # make it 2D
random_indices = np.random.randint(0, Space_Position.shape[0], size=N) # generate N random indices
Space_Position[random_indices] # get N samples with replacement
或不进行替换:
Space_Position = np.array(Space_Position).reshape(-1, 2) # make it 2D
random_indices = np.arange(0, Space_Position.shape[0]) # array of all indices
np.random.shuffle(random_indices) # shuffle the array
Space_Position[random_indices[:N]] # get N samples without replacement
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