Record arrays allow you to access fields as elements of an array using
arr.a and arr.b
numpy.recarray.clip () strong> returns an array limited to
[min, max] . One of max or min must be specified.
numpy.recarray.clip (min = None, max = None, out = None)
min: Minimum value.
- & gt; If None, clipping is not performed on lower interval edge. Not more than one of a_min and a_max may be None.
max: Maximum value.
- & gt; If None, clipping is not performed on upper interval edge. Not more than one of a_min and a_max may be None.
- & gt; If a_min or a_max are array_like, then the three arrays will be broadcasted to match their shapes.
out: Results will be placed in this array. It may be the input array for in-place clipping. out must be of the right shape to hold the output. Its type is preserved.
Return: [clipped_array, ndarray] An array where values less than minimum are replaced with min, and values greater then maximum with max.
Code # 1:
Input array : [[(5.0, 2) (3.0, -4) (6.0, 9)] [(9.0, 1) (5.0, 4) (-12.0, -7)]] Record array of int: [[2 -4 9] [1 4 -7]] Record array of float: [[5. 3. 6.] [9. 5. -12.]] Output clipped array: [[5. 3. 5.] [5. 5 . -1.]] Record array of int: [[2 -4 9] [1 4 -7]] Output clipped array: [[2 2 6] [2 4 2]]
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