In [1]:

    

import numpy as np


    

In [2]:

    

a = np.array([0, 1, 2])
b = np.array([2, 0, 6])


    

In [3]:

    

print(np.maximum(a, b))


    

    




[2 1 6]

In [4]:

    

print(np.fmax(a, b))


    

    




[2 1 6]

In [5]:

    

l_a = [0, 1, 2]
l_b = [2, 0, 6]


    

In [6]:

    

print(np.maximum(l_a, l_b))


    

    




[2 1 6]

In [7]:

    

print(np.fmax(l_a, l_b))


    

    




[2 1 6]

In [8]:

    

print(np.maximum(0, 2))


    

    




2

In [9]:

    

print(np.fmax(0, 2))


    

    




2

In [10]:

    

print(max(0, 2))


    

    




2

In [11]:

    

a_2d = np.arange(6).reshape(2, 3)
print(a_2d)


    

    




[[0 1 2]
 [3 4 5]]

In [12]:

    

print(b)


    

    




[2 0 6]

In [13]:

    

print(a_2d + b)


    

    




[[ 2  1  8]
 [ 5  4 11]]

In [14]:

    

print(np.maximum(a_2d, b))


    

    




[[2 1 6]
 [3 4 6]]

In [15]:

    

print(np.fmax(a_2d, b))


    

    




[[2 1 6]
 [3 4 6]]

In [16]:

    

a_mismatch = np.array([0, 1, 2, 3])


    

In [17]:

    

# print(np.maximum(a_mismatch, b))
# ValueError: operands could not be broadcast together with shapes (4,) (3,)


    

In [18]:

    

# print(np.fmax(a_mismatch, b))
# ValueError: operands could not be broadcast together with shapes (4,) (3,)


    

In [19]:

    

print(np.maximum(a_2d, 2))


    

    




[[2 2 2]
 [3 4 5]]

In [20]:

    

print(np.fmax(a_2d, 2))


    

    




[[2 2 2]
 [3 4 5]]

In [21]:

    

print(np.maximum(2, a_2d))


    

    




[[2 2 2]
 [3 4 5]]

In [22]:

    

print(np.fmax(2, a_2d))


    

    




[[2 2 2]
 [3 4 5]]

In [23]:

    

print(np.maximum([np.nan, np.nan], [np.inf, 0]))


    

    




[nan nan]

In [24]:

    

print(np.fmax([np.nan, np.nan], [np.inf, 0]))


    

    




[inf  0.]