numpy--PIL int type issue

Question

So I've got the x and y values of a curve that I want to plot held as float values in numpy arrays. Now, I want to round them to the nearest int, and plot them as pixel values in an empty PIL image. Leaving out how I actually fill my x and y vectors, here is what we're working with: ``` # create blank image new_img = Image.new('L', (500,500)) pix = new_img.load() # round to int and convert to int xx = np.rint(x).astype(int) yy = np.rint(y).astype(int) ordered_pairs = set(zip(xx, yy)) for i in ordered_pairs: pix[i[0], i[1]] = 255 ``` This gives me an error message: ``` File "makeCurves.py", line 105, in makeCurve pix[i[0], i[1]] = 255 TypeError: an integer is required ``` However, this makes no sense to me since the `.astype(int)` should have cast these puppies to an integer. If I use `pix[int(i[0]], int(i[1])]` it works, but that's gross. Why isn't my `.astype(int)` being recognized as int by PIL?

Accepted Answer

I think the problem is that your numpy arrays have type `numpy.int64` or something similar, which PIL does not understand as an `int` that it can use to index into the image.

Try this, which converts all the `numpy.int64`s to Python `int`s:

```
# round to int and convert to int    
xx = map(int, np.rint(x).astype(int)) 
yy = map(int, np.rint(y).astype(int))
```

In case you're wondering how I figured this out, I used the `type` function on a value from a numpy array:

```
>>> a = np.array([[1.3, 403.2], [1.0, 0.3]])
>>> b = np.rint(a).astype(int)
>>> b.dtype
 dtype('int64')
>>> type(b[0, 0])
 numpy.int64
>>> type(int(b[0, 0]))
 int
```

numpy-->PIL int type issue

Solution

Problem