numpy - opposite of array.sum (subtraction?)

Question

I was wondering if there a method that can subtract values? Something similar to sum

for Examples

> np.array([[10, 2], [1, 2]]).sum() 
15
" imaginary method "
> np.array([[10, 2], [1, 2]]).sub() 
6

# axis = 1
> np.array([[10, 2], [1, 2]]).sum(axis=1)
array([12,  3])
" imaginary method "
> np.array([[10, 2], [1, 2]]).sum(axis=1)
array([8,  -1])

# axis = 0
> np.array([[10, 2], [1, 2]]).sum(axis=0)
array([11,  4])
"imaginary"
> np.array([[10, 2], [1, 2]]).sub(axis=0)
array([9,  0])

I am frustrated I cann't find anything in docs (somehow numpy docs are not easy to use if you don't know what you looking for).

thank you.

What do you expect to happen if the axis has length greater than (or less than!) two? — user2357112
– user2357112, Commented Mar 22, 2019 at 21:25
Normally, you wouldn't have a single array and try to call some sort of sum-like method. You'd have two arrays and do a - b. — user2357112
– user2357112, Commented Mar 22, 2019 at 21:26
Multiply the appropriate rows/columns with -1 and then call sum. — Ahmed Fasih
– Ahmed Fasih, Commented Mar 22, 2019 at 21:26
There's also np.diff that's kind of related and that I occasionally use to do subtraction, but it's probably obfuscating to use that when actually want to do row/col subtraction and not doing finite-differences. — Ahmed Fasih
– Ahmed Fasih, Commented Mar 22, 2019 at 21:28

G. Anderson · Accepted Answer · 2019-03-22 21:46:28Z

4

The difference equivalent of np.sum() is np.diff()

Docs

answered Mar 22, 2019 at 21:46

G. Anderson

5,9652 gold badges16 silver badges22 bronze badges

Sign up to request clarification or add additional context in comments.

Comments

hpaulj · Accepted Answer · 2019-03-22 23:53:42Z

np.sum is np.add.reduce:

In [87]: np.add.reduce(arr, axis=0)                                             
Out[87]: array([11,  4])
In [88]: np.add.reduce(arr, axis=1)                                             
Out[88]: array([12,  3])

There is a subtract ufunc too:

In [93]: np.subtract.reduce(arr, axis=0)                                        
Out[93]: array([9, 0])
In [94]: np.subtract.reduce(arr, axis=1)                                        
Out[94]: array([ 8, -1])

np.diff does sliced subtraction:

In [97]: np.subtract(arr[:-1,:], arr[1:,:])                                     
Out[97]: array([[9, 0]])
In [98]: np.subtract(arr[:,:-1], arr[:,1:])                                     
Out[98]: 
array([[ 8],
       [-1]])

For two elements diff and subtract.reduce do the same thing. What's supposed to happen when you have more than 2 rows or columns?

In [109]: arr = np.array([[10, 2, 3], [1, 2, 4], [0, 1, 2]])                    
In [110]: arr                                                                   
Out[110]: 
array([[10,  2,  3],
       [ 1,  2,  4],
       [ 0,  1,  2]])

diff does pair wise subtraction, row 0 from 1, row 1 from 2:

In [111]: np.diff(arr, axis=0)                                                  
Out[111]: 
array([[-9,  0,  1],
       [-1, -1, -2]])

subtract.reduce does a cumulative, which might be easier to follow with the accumulate alternative:

In [112]: np.subtract.reduce(arr, axis=0)                                       
Out[112]: array([ 9, -1, -3])
In [113]: np.subtract.accumulate(arr, axis=0)                                   
Out[113]: 
array([[10,  2,  3],
       [ 9,  0, -1],
       [ 9, -1, -3]])

Collectives™ on Stack Overflow

numpy - opposite of array.sum (subtraction?)

2 Answers 2

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

2 Answers 2

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related