Adrian - 9 months ago 33

Python Question

I am looking for the optimal (fastest) way to find the exact overlap between two arrays in numpy. Given two arrays x and y

`x = array([1,0,3,0,5,0,7,4],dtype=int)`

y = array([1,4,0,0,5,0,6,4],dtype=int)

What I want to get is, an array of the same length that contains only the numbers from both vectors that are equal:

`array([1,0,0,0,5,0,0,4])`

First I tried

`x&y`

array([1,0,0,0,5,0,6,4])

Then I realised that this is always true for two numbers if they are > 0.

Answer

```
result = numpy.where(x == y, x, 0)
```

Have a look at `numpy.where`

documentation for explanation. Basically, `numpy.where(a, b, c)`

, for a condition `a`

returns an array of shape `a`

, and with values from `b`

or `c`

, depending upon whether the corresponding element of `a`

is true or not. `b`

or `c`

can be scalars.

By the way, `x & y`

is not necessarily "always true" for two positive numbers. It does bitwise-and for elements in `x`

and `y`

:

```
x = numpy.array([2**p for p in xrange(10)])
# x is [ 1 2 4 8 16 32 64 128 256 512]
y = x - 1
# y is [ 0 1 3 7 15 31 63 127 255 511]
x & y
# result: [0 0 0 0 0 0 0 0 0 0]
```

This is because the bitwise representation of each element in `x`

is of the form `1`

followed by `n`

zeros, and the corresponding element in `y`

is `n`

1s. In general, for two non-zero numbers `a`

and `b`

, `a & b`

may equal zero, or non-zero but not necessarily equal to either `a`

or `b`

.

Source (Stackoverflow)