how to randomly sample in 2D matrix in numpy
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.
The alternative is to actually make it 2D:
Space_Position = np.array(Space_Position).reshape(-1, 2)
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.
If you want N
samples with replacement:
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
or without replacement:
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
user824624
Updated on June 12, 2022Comments
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user824624 almost 2 years
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 thenumpy.choice
but it is built for 1d array.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]] ]
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]
this indeed works to give me one sample, how about more than one sample like what
np.choice()
does?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], ..... ]
and at last use
np.choice()
, however I could not find the ways to do the transformation,np.flatten()
makes the array likeSpace_Position=[-62,29.23,-49.73,29.2, ....]
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user824624 almost 7 yearsThanks, is there any way to sample N (N>1) if not using for loop
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MSeifert almost 7 years@user824624 Sample with replacement or without?
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user824624 almost 7 yearswithout replacement
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MSeifert almost 7 years@user824624 I updated the answer, the last approach should be want to you need then :)
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user824624 almost 7 years,the last approach still give me a 3 dimension array, I hope to get a randomly 2 dimension array samples like [ [-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], ..... ]
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MSeifert almost 7 years@user824624 did you use the
Space_Position = np.array(Space_Position).reshape(-1, 2)
I mentioned? -
user824624 almost 7 yearsoh, yes, that is it. I missed it.