numpy.argmin()

numpy.argmin(a, axis=None, out=None) [source]

Returns the indices of the minimum values along an axis.

Parameters:

Parameters:	a : array_like Input array. axis : int, optional By default, the index is into the flattened array, otherwise along the specified axis. out : array, optional If provided, the result will be inserted into this array. It should be of the appropriate shape and dtype.
Returns:	index_array : ndarray of ints Array of indices into the array. It has the same shape as `a.shape` with the dimension along `axis` removed.

a : array_like

Input array.

axis : int, optional

By default, the index is into the flattened array, otherwise along the specified axis.

out : array, optional

If provided, the result will be inserted into this array. It should be of the appropriate shape and dtype.

Returns:

index_array : ndarray of ints

Array of indices into the array. It has the same shape as a.shape with the dimension along axis removed.

Notes

In case of multiple occurrences of the minimum values, the indices corresponding to the first occurrence are returned.

Examples

>>> a = np.arange(6).reshape(2,3)
>>> a
array([[0, 1, 2],
       [3, 4, 5]])
>>> np.argmin(a)
0
>>> np.argmin(a, axis=0)
array([0, 0, 0])
>>> np.argmin(a, axis=1)
array([0, 0])

>>> b = np.arange(6)
>>> b[4] = 0
>>> b
array([0, 1, 2, 3, 0, 5])
>>> np.argmin(b) # Only the first occurrence is returned.
0

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.argmin.html

doc_NumPy

2017-01-10 18:12:44

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