Slicing a 2d array in python via another array in one line

Question

Apologies is the title is not correct. I didn't know how to describe exactly what I am looking for. So coming from Matlab I want to be able to do the following in Python in one line if possible

Say I have an index array:

index_array= np.array([0,1,1,0,0,0,1])

and a data array: data_array = np.zeros([len(index_array),2])

I want to place a value (e.g. 100) where index_array=0 to the data_array[:,0] and where index_array=1 to data_array[:,1]

I matlab you could do it with one line. Something like data_array(index_array)=100

The best I could figure out in python is this

data_array [index_array==0,0]=100

data_array [index_array==1,1]=100

Is it possible to do it more efficiently (w.r.t. lines of code). Also it would be nice to scale for additional dimensions in data_array (beyond 2d)

Alexander Korovin · Accepted Answer · 2021-04-05 12:45:07Z

1

If I understand your question correctly, please try this:

import numpy as np
index_array= np.array([0,1,1,0,0,0,1],dtype=bool)
data_array = np.zeros([len(index_array),2])
data_array[index_array,:]=100
print(data_array)

Here, index_array is instantiated as boolean. Or it can convert index_array to boolean using == (index_array==0).

Use data_array[index_array,...]=100 if there are additional dimensions.

------ CORRECTED VERSION ------

Hope I now understand your question. So try this:

import numpy as np
index_array= np.array([0,1,1,0,2,0,1,2])
data_array = np.zeros([len(index_array),3])

data_array[np.arange(len(index_array)), index_array] = 100

print(data_array)

edited Apr 5, 2021 at 12:45

answered Apr 4, 2021 at 12:57

Alexander Korovin

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4 Comments

vzografos Over a year ago

ok this works. I guess I omitted the boolean type thats why mine didnt work. However, I am not sure this naturally extends to more than 2 dimensions? Say, index_array= np.array([0,1,1,0,2,0,1,2],dtype=bool) and data_array = np.zeros([len(index_array),3]). Then using data_array[index_array,:]=100 produces the wrong result. Because when casting the index_array to boolean, anything nonzero becomes true.

Alexander Korovin Over a year ago

Please read the end of my answer "Use data_array[index_array,...]=100 if there are additional dimensions."

vzografos Over a year ago

I did. I used this data_array[index_array,...]= 100 verbatim but I got the same result as before. The problem comes from setting index_array= np.array([0,1,1,0,2,0,1,2],dtype=bool) because 1 and 2 are the same from the boolean point of view

Alexander Korovin Over a year ago

Ok, I understand that's a slightly different question. See corrected version in my answer.

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