user2290362 - 9 months ago 55

Python Question

I have a 3D array of binary data. I want to project this to 3 2D images - side on, head on, birds eye.

I have written the code:

`for x in range(data.shape[2]):`

for y in range(data.shape[0]):

val = 0

for z in range(data.shape[1]):

if data[y][z][x] > 0:

val = 255

break

side[y][x] = val

But this is horrifically slow (75s!) for a ~700x300x300 matrix.

What is the fastest way of achieving this task?

EDIT:

To save the image, I have used:

`sideImage = Image.fromarray(side)`

sideImage.convert('RGB').save("sideImage.png")

Answer Source

You can compute it as follows:

```
>>> data = np.random.random_sample((200, 300, 100)) > 0.5
>>> data.any(axis=-1).shape # show the result has the shape we want
(200, 300)
>>> data.any(axis=-1)
array([[ True, True, True, ..., True, True, True],
[ True, True, True, ..., True, True, True],
[ True, True, True, ..., True, True, True],
...,
[ True, True, True, ..., True, True, True],
[ True, True, True, ..., True, True, True],
[ True, True, True, ..., True, True, True]], dtype=bool)
>>>
```

You can scale values if you need

```
>>> data.any(axis=-1) * 255
array([[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255],
...,
[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255],
[255, 255, 255, ..., 255, 255, 255]])
>>>
```