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I have a numpy array being generated from a function as follows

 circles = [[ 56, 152, 26],
 [288, 300, 25],
 [288, 362,  25],
 [288, 238,  24],
 [318, 298,  45],
 [220, 366, 29]]

I want to check if all the values in the first element of each subarray are consistent (mathematically close, not differing by a large amount i.e. > 5) and remove the subarrays that don't conform to this condition. So in this case, i want to remove any subarray that is greater than 288 + 5 or less than 288 - 5. Any thoughts?

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  • what's your desired output in this case? Commented Sep 7, 2018 at 6:08
  • [[288, 300, 25], [288, 362, 25], [288, 238, 24]] Commented Sep 7, 2018 at 13:17

1 Answer 1

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A possible solution using mode: 

>>> from scipy.stats import mode
>>> eps = 5
>>> most_freq = mode(circles[:, 0])[0][0]
>>> mask = np.abs(circles[:, 0] - most_freq) <= eps
>>> circles[mask]
array([[288, 300,  25],
   [288, 362,  25],
   [288, 238,  24]])

Edit: if your circles array is limited to to non-negative integers, you can use the following expression for most_freq:

most_freq = np.bincount(circles[:, 0]).argmax()
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3 Comments

When i try that it gives me this error TypeError: list indices must be integers or slices, not tuple
@HarshVedant, Looks, your circles is a list if lists. Try circles = np.array(circles) before processing it.
Never mind, i was messing around in the python terminal and not my actual code, where it wasn't a numpy array. This is brilliant, thanks!

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