Anton - 5 months ago 14

Python Question

I'm facing very strange problem with arrays in python and numpy. First of all what Im trying to archive is :

1) Get an MxN matrix from KxTxN matrix

2) Transpose this matrix and calculate product of this transposed matrix and the original one

What I get is some what strange, here comes the code :

First of all, I have read an image with help of cv2, and got K by T by 3 matrix (a field of RGB points), then I'm cutting a small window form it and reshaping this window to M by N matrix :

`def clipSubwindowFromImage(img, i, j, winSize):`

winI = img[i - winSize: i + winSize + 1, j - winSize : j + winSize + 1, : ]

res = np.vstack((winI[:,::3,:].reshape(winI.shape[1],3), winI[:,1::3,:].reshape(winI.shape[1],3), winI[:,2::3,:].reshape(winI.shape[1],3)))

return res

so far so god, say we had

`winSize = 1, i = 1, j = 1`

`>> subWin = clipSubwindowFromImage(background12x12b, 1, 1, 1)`

>> [[201 199 187]

[216 219 198]

[226 228 207]

[243 241 228]

[240 244 221]

[233 235 213]

[239 238 220]

[238 240 216]

[233 235 211]]

Then I just want to get the product in question, like this :

`>>r1 = subWin.T.dot(subWin)`

>>[[197 234 89]

[234 65 163]

[ 89 163 105]]

Well, it's not right, the right result should be :

`>>[[477125 479466 438361]`

[479466 481857 440483]

[438361 440483 402793]]

But if I initialize

`subWin`

`>>subWin = np.array([[201, 199, 187], [216, 219, 198], [226, 228, 207], [243, 241, 228], [240, 244, 221], [233, 235, 213],[239, 238, 220], [238, 240, 216],[233, 235, 211]])`

I get right result.

I can't get it,

`subWin`

Answer

As @Aguy said, your problem comes from the data-type of your array. The dot product of a uint8 array with an other uint8 array gives an array that is also uint8 hence the data-type is overflowed in your case. Here's an example that shows the effect of overflow on your values:

```
import numpy as np
a = np.array([[201, 199, 187], [216, 219, 198], [226, 228, 207], [243, 241, 228], [240, 244, 221], [233, 235, 213],[239, 238, 220], [238, 240, 216],[233, 235, 211]])
b = a.T.dot(a)
print b.dtype
print b
print "overflowed uint8 :"
print b.astype(np.uint8)
```

Gives:

```
>>> int64
>>> [[477125 479466 438361]
>>> [479466 481857 440483]
>>> [438361 440483 402793]]
>>> overflowed uint8 :
>>> [[197 234 89]
>>> [234 65 163]
>>> [ 89 163 105]]
```

Just change the data-type of one array to something more suitable in your dot product and you're good to go :

```
r1 = subWin.T.dot(subWin.astype(np.uint32))
```