How to remove nan and inf values from a numpy matrix?

Question

Here is my code

import numpy as np
cv = [[1,3,4,56,0,345],[2,3,2,56,87,255],[234,45,35,76,12,87]]
cv2 = [[1,6,4,56,0,345],[2,3,4,56,187,255],[234,45,35,0,12,87]]

output = np.true_divide(cv,cv2,where=(cv!=0) | (cv2!=0))
print(output)`

I am getting Nan and inf values.i tried to remove differently means once i removed Nan and then i removed Inf values and replace them with 0.But i need to replace them together!Is there any way to replace them together ?

"But i need to replace them together!I" Why?

roganjosh
– roganjosh

2018-09-22 16:05:48 +00:00
Commented Sep 22, 2018 at 16:05 — roganjosh
– roganjosh, Commented Sep 22, 2018 at 16:05

sacuL · Accepted Answer · 2018-09-22 19:47:26Z

12

You can just replace NaN and infinite values with the following mask:

output[~np.isfinite(output)] = 0

>>> output
array([[1.        , 0.5       , 1.        , 1.        , 0.        ,
        1.        ],
       [1.        , 1.        , 0.5       , 1.        , 0.46524064,
        1.        ],
       [1.        , 1.        , 1.        , 0.        , 1.        ,
        1.        ]])

edited Sep 22, 2018 at 19:47

answered Sep 22, 2018 at 16:07

sacuL

51.6k9 gold badges88 silver badges115 bronze badges

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

1 Comment

user3483203 Over a year ago

You don't need the isnan, isfinite checks for both: "Test element-wise for finiteness (not infinity or not Not a Number)."

apatsekin · Accepted Answer · 2020-11-17 08:55:32Z

6

There is a special function just for that:

numpy.nan_to_num(x_arr, copy=False, nan=0.0, posinf=0.0, neginf=0.0)

answered Nov 17, 2020 at 8:55

apatsekin

1,62413 silver badges12 bronze badges

Comments

user3483203 · Accepted Answer · 2018-09-22 21:19:20Z

3

If you don't want to modify the array in place, you can make use of the np.ma library, and create a masked array:

np.ma.masked_array(output, ~np.isfinite(output)).filled(0)

array([[1.        , 0.5       , 1.        , 1.        , 0.        ,
        1.        ],
       [1.        , 1.        , 0.5       , 1.        , 0.46524064,
        1.        ],
       [1.        , 1.        , 1.        , 0.        , 1.        ,
        1.        ]])

answered Sep 22, 2018 at 21:19

user3483203

51.3k10 gold badges72 silver badges104 bronze badges

Collectives™ on Stack Overflow

How to remove nan and inf values from a numpy matrix?

3 Answers 3

1 Comment

Comments

Comments

Your Answer

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

1 Comment

Comments

Comments

Your Answer

Sign up or log in

Post as a guest

Related