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NumPy | divmod method

schedule Aug 11, 2023
Last updated
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Numpy's divmod(~) method returns the tuple (x//y, x%y) for each dividend x and divisor y in the input arrays. Here, // denotes integer division, while % denotes the standard Python modulo.

If you need both of these quantities, then use the divmod(~) method as it prevents redundant computations.

Parameters

1. x1 | array_like

The dividends.

2. x2 | array_like

The divisors.

3. out | Numpy array | optional

Instead of creating a new array, you can place the computed mean into the array specified by out.

4. where | array of boolean | optional

Values that are flagged as False will be ignored, that is, their original value will be uninitialized. If you specified the out parameter, the behavior is slightly different - the original value will be kept intact.

Return value

A tuple, (x//y, x%y), for each dividend x and divisor y in the input arrays

Examples

Common divisor

x = [3, 8.5, -7]
np.divmod(x, 3)
(array([ 1., 2., -3.]), array([0. , 2.5, 2. ]))

To clarify how the output was computed:

3 // 3 = 1
8.5 // 3 = 2
-7 // 3 = -3

3 % 3 = 0
8.5 % 3 = 2.5
-7 % 3 = 2

Multiple divisors

x = [3, 8.5, -7]
np.divmod(x, [1,2,3])
(array([ 3., 4., -3.]), array([0. , 0.5, 2. ]))
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Published by Isshin Inada
Edited by 0 others
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