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NumPy | amin method

schedule Aug 10, 2023
Last updated
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Numpy's amin(~) method returns the smallest value in the Numpy array. The minimums can also be computed row-wise and column-wise.

Parameters

1. a | array_like

The input array.

2. axis | None or int | optional

The allowed values are as follows:

Parameter value

Meaning

axis=0

Minimum computed column-wise

axis=1

Minimum computed row-wise

None

Minimum computed from entire array

By default, axis=None.

3. initial | int | optional

If the computed minimum is larger than initial, then initial will be returned instead.

4. where | array-like of booleans | optional

Instead of considering all the values, we can choose which values to consider by providing this parameter. Only values corresponding to True in the mask will be considered.

Return value

A scalar is returned if the axis parameter is not supplied. Otherwise, a Numpy array is returned.

Examples

Minimum of the entire array

np.amin([[2,5],[1,3]])
1

Minimum of each column

np.amin([[2,5],[1,3]], axis=0)
array([1, 3])

Minimum of each row

np.amin([[2,5],[1,3]], axis=1)
array([2, 1])

Handling missing values

When your array contains missing values (e.g. NaNs), then NaN is returned:

np.amin([2,np.NaN,1,3])
nan

If you want to ignore missing values, then use np.nanmin(~) method instead.

Passing in initial parameter

np.amin([[2,5],[1,3]], initial=-4)
-4

Here, the computed minimum is 1, yet it is larger than the provided value of initial (i.e. -4), so -4 is returned instead.

Passing in a boolean mask

Instead of considering all the values, we can choose which values to compute the minimum of by providing a mask:

np.amin([2,5,3,4], where=[False,False,True,True], initial=8)
3

Here, although 2 is technically the smallest value, it is ignored since its corresponding value in the mask is False. Note that we need to supply the parameter initial here, which will be the returned value if the minimum cannot be computed (e.g. when the mask is all False).

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Published by Isshin Inada
Edited by 0 others
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