Python中的np.argmin()和np.argmax()函数用法

numpy.argmin(a, axis=None, out=None)
numpy.argmax(a, axis=None, out=None)

import numpy as np
a = np.arange(6).reshape(2, 3)
a
array([[0, 1, 2],
       [3, 4, 5]])

# 此时自动展平了
np.argmin(a)
0
np.argmax(a)
5
# 在axis方向上找最小的值并返回坐标
np.argmin(a, axis=1)
array([0, 0], dtype=int64)

# 在axis方向上找最大的值并返回坐标
np.argmax(a, axis=1)
array([2, 2], dtype=int64)

a = np.arange(6)
a[4] = 0
a

array([0, 1, 2, 3, 0, 5])

np.argmin(a)
0

min(iterable, key=func)->value
np.argmin(a, axis=None)

>>> l = ['1', '100', '111', '2']
>>> max(l)
'2'
# 下面我们指定比较内容
>>> max(l, key=lambda x: int(x)
'111'
>>> max(l, key=lambda x: len(x))
'100'
>>> max(l, key=lambda x: len(x) and int(x))
'111'

>>> ll = [(1, 'a'), (3, 'c'), (4, 'e'), (-1, 'z')]
>>> max(ll)

>>> l = [(1, 2, 5), (2, 3, 5), (3, 2, 5), (4, 4, 5), (5, 1, 5)]
>>> max(l, key=lambda x: x[1])
(4, 4, 5)
>>> l.index(max(l, key=lambda x: x[1]))
3

>>> max(ll, key=lambda x: x[1])
(-1, 'z')

>>> ll = [(1, 'a'), (3, 'c'), (4, 'e'), (-1, 'z')]
>>> val = max(ll, lambda x: x[1])
>>> ll.index(val)
3

def max(items, key=lambda x: x):
    current = items[0]
    for item in items:
        if key(item) > key(current):
            current = item
    return current