Check if numpy array falls within bounds

Question

Looking for a more efficient way to check if items within a numpy array fall within any (or match at least once) of a set of min & max values. I toyed around with any() and np.any() and all() but these are newer concepts to me.

y_minmax_bounds = [[1.1, 2.0], [3.3, 6.21], [5.75, 10.0]]
y = np.array([1.5, 2.5, 2, 6, 8, 10])
withinbounds = [((y > min) & (y < max))for min, max in y_minmax_bounds]
print(withinbounds)

Returns:

[array([True, False, False, False, False, False]), 
array([False, False, False,  True, False, False]), 
array([False, False, False,  True,  True, False])]

After a array solution of:

[True False False True True False]

I can loop over y_minmax_bounds, but this seems inefficient given a very large np.array to check. The actual problem will also be enforcing this in multiple dimensions (x_minmax_bounds on x, z_minmax_bounds over z).

Apologies - I have edited a typo in y_minmax_bounds, which also sets 2.5 and 2 as False. — Steven T
– Steven T, Commented Aug 29, 2018 at 4:56

piRSquared · Accepted Answer · 2018-08-29 04:57:59Z

4

With Numpy broadcasting

mn, mx = np.array(y_minmax_bounds).T
x = y[:, None]

((x > mn) & (x < mx)).any(1)

array([ True, False, False,  True,  True, False])

edited Aug 29, 2018 at 4:57

answered Aug 29, 2018 at 4:48

piRSquared

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