Numpy elementwise greater (for each element in another array)

Question

I struggle to write find the best "question" so please feel free to suggest another title.

Lets say I have a=np.array([5,3,2,4]) and b=np.array([1,2]) - I want to get a list of list (or np.arrays) with the value of a>b[i] i.e it can be written as a list comprehension

[a[i]>p for p in b] which returns

[np.array([True,True,True,True]), np.array([True,True,False,True])]. Since I have a rather large data set I hoped that there was a numpy function to do such, or is list comprehension the better way here?

If the array a is really large (close to your memory limit), you may want to process a > b[i] separately anyway and in that case I would look no further than a simple loop, which is slow but can have a small memory footprint. Otherwise, you can use broadcasting which is fast but has a large memory footprint. List-comprehension in this case has both disadvantages: slow and large memory footprint. — norok2
– norok2, Commented May 8, 2020 at 8:03

Blckknght · Accepted Answer · 2020-05-08 07:50:16Z

6

You can use numpy broadcasting for this, you just need to add an extra dimension into each of your arrays:

>>> a[None,:] > b[:,None]
array([[ True,  True,  True,  True],
       [ True,  True, False,  True]])

answered May 8, 2020 at 7:50

Blckknght

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