Select cells randomly from NumPy array - without replacement

robintw_1912 0
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I'm writing some modelling routines in NumPy that need to select cells randomly from a NumPy array and do some processing on them. All cells must be selected without replacement (as in, once a cell has been selected it can't be selected again, but all cells must be selected by the end).

I'm transitioning from IDL where I can find a nice way to do this, but I assume that NumPy has a nice way to do this too. What would you suggest?

Update: I should have stated that I'm trying to do this on 2D arrays, and therefore get a set of 2D indices back.

sampling shuffle random numpy python
6 Answers

Let's say you have an array of data points of size 8x3

data = np.arange(50,74).reshape(8,-1)

If you truly want to sample, as you say, all the indices as 2d pairs, the most compact way to do this that i can think of, is:

#generate a permutation of data's size, coerced to data's shape
idxs = divmod(np.random.permutation(data.size),data.shape[1])

#iterate over it
for x,y in zip(*idxs): 
    #do something to data[x,y] here
    pass

Moe generally, though, one often does not need to access 2d arrays as 2d array simply to shuffle 'em, in which case one can be yet more compact. just make a 1d view onto the array and save yourself some index-wrangling.

flat_data = data.ravel()
flat_idxs = np.random.permutation(flat_data.size)
for i in flat_idxs:
    #do something to flat_data[i] here
    pass

This will still permute the 2d "original" array as you'd like. To see this, try:

 flat_data[12] = 1000000
 print data[4,0]
 #returns 1000000
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