I have a list that looks like this:
[['3'], ['9', '1'], ['5'], ['4'], ['2', '5', '8']]
how can I get all the combinations thereof that looks like as follows:
3,9,5,4,2
3,1,5,4,2
3,9,5,4,5
3,1,5,4,5
etc.
Thank You,
Gerdus
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> But I'm afraid with the Swing-like interface, i.e : did you use the same
> widget positionning ?
Not sure what you mean, but each parent widget is responsible for
rendering and positioning the children. Can use layout managers, two
currently absolute and simple flow. ( In the screenshot, the
Hi
I am halfway to a first release of a new GUI library for python. It
will be cross platform and follows the Swing philosophy of user
experience and interface fidelity above "but it doesn't look like
windows!" (aside: neither does office 2007 or windowsmediaplayer).
The library is built on top o
van Zyl
Seperated Gaussian blur:
def blurB(self):
pixels = self.array
temp1 = copy.copy(pixels)
#temp2 = copy.copy(pixels)
stride = self.width * 4
clr = array.array('B',[255,255,255,255])
w = self.width
h = self.height
Does anyone have a relatively fast gaussian blur implemented in pure
python? Below is my attempt but it takes 2.9 seconds for a 320x240
image. Image comes from byte string: self.array =
array.array('B',srcstring). Would some sort of matrix multiplication
be faster? I don't have experience in that.
I have the following, that is used to convert pixel data and thus
should be as fast as possible:
b = numpy.ndarray (shape=(w,h,4), dtype=numpy.uint8)
a = numpy.frombuffer(buf, numpy.uint8)
a.shape = (w, h, 3)
b[:,:,0] = a[:,:,2]
b[:,:,1] = a[:,:,1]
b[:,:,2] = a[:,:,0]
b[:,:,3] = 255
Can anyone
