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I have a multi-dimensional NumPy array, that is acting as input data to my neural network. I have 2115 different (6,100,60) samples. I want to shuffle my data - rearrange the order - of the 2115 (6,100,60) samples. I want to make sure the channels, columns, and rows of (6,100,60) all stay in place - i.e., I only want to shuffle the location (in the array) of these 2115 samples.

I am not sure how to do this - any help would be appreciated.

Thank you.

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You can shuffle the sample number (assuming first dimension) then reindex:

order = np.random.permutation(np.arange(2115))

data = data[order]
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Nevermind, I just realized it swaps the orders of the second dimension - the 6 channels. This is what I did not want to happen, do you know how I can keep these in place?
which is the dimension of 2115 samples? You need to shuffle that dimension.
its the first dimension, so would i do: data = data[order,:,:,:] ?
my data is of size (2115,6,100,60). I want everything to stay in place except for the dimension of 2115.
currently, its shuffling both the first and second dimension. - so my 6 channels are all switched up

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