Suppose you have an array:

```
a =
[ 0,1,0]
[-1,2,1]
[3,-4,2]
```

And lets say you add 20 to everything

```
b =
[ 20, 21, 20]
[ 19, 22, 21]
[ 23, 16, 22]
```

Now lets say I want to add the resulting `b`

to the original array `a`

but only in cases where `a < 0`

i.e at the index `[0,1]`

and `[1,2]`

where `a = -1, -4`

respectively *getting the value 0 otherwise*. Ultimately leading to a matrix as such:

```
c =
[ 0, 0, 0]
[ 18, 0, 0]
[ 0, 12, 0]
```

```
18 = 19 (from b) + -1 (from a)
12 = 16 (from b) + -4 (from a)
```

And assume that I want to be able to extend this to any operation (not just add 20), so that you can’t just filter all values < 20 from matrix `c`

. So I want to use matrix `a`

as a mask toward matrix c, zeroing the `i, j`

where `a[i,j] < 0`

.

I’m having a tough time finding a concise example of how to do this in numpy with python. I was hoping you may be able to direct me to the correct implementation of such a method.

What I am struggling to get is this into a mask and only performing operations on the retained values, finally resulting in `c`

.

Thanks for the help in advance.

Probably something like:

(a + b)*(a<0)

should work unless you have very strong requirements concerning the number of intermediate arrays.

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