Dear Julian Taylor Thank you very much, I really appreciated your codes.
On Sat, Oct 18, 2014 at 9:28 PM, Julian Taylor < jtaylor.deb...@googlemail.com> wrote: > On 18.10.2014 14:14, Artur Bercik wrote: > > > > > > On Sat, Oct 18, 2014 at 9:00 PM, Artur Bercik <vbubbl...@gmail.com > > <mailto:vbubbl...@gmail.com>> wrote: > > > > > > > > On Sat, Oct 18, 2014 at 8:28 PM, Julian Taylor > > <jtaylor.deb...@googlemail.com > > <mailto:jtaylor.deb...@googlemail.com>> wrote: > > > > On 18.10.2014 07:58, Artur Bercik wrote: > > > Dear Python and Numpy Users: > > > > > > My data are in the form of '32-bit unsigned integer' as > follows: > > > > > > myData = np.array([1073741824, 1073741877, 1073742657, > 1073742709, > > > 1073742723, 1073755137, 1073755189,1073755969],dtype=np.int32) > > > > > > I want to get the index of my data where the following occurs: > > > > > > Bit No. 0–1 > > > Bit Combination: 00 > > > > > > How can I do it? I heard this type of problem first time, > please help me. > > > > > > Artur > > > > > > > not sure I understand the problem, maybe this? > > > > np.where((myData & 0x3) == 0) > > > > > > yes, it works greatly for the following case: > > > > myData = np.array([1073741824, 1073741877, 1073742657, 1073742709, > > 1073742723, 1073755137, 1073755189,1073755969],dtype=np.uint32) > > Bit No. 0–1 > > Bit Combination: 00 > > > > Can you make such automation for the following case as well? > > > > Bit No. 2–5 > > Bit Combination: 1101 > > > > sure, you can do any of these with the right masks: > np.where((myData & 0x3c) == 0x34) > > you can use bin(number) to check if your numbers are correct. > > > > > > Also wondering why np.where((myData & 0x3) == 0) instead of > > just np.where((myData & 3) == 0) > > > > its the same, 0x means the number is in hexadecimal representation, for > 3 they happen to be equal (as 3 < 10) > It is often easier to work in the hexadecimal representation when > dealing with binary data as its base is a power of two. So two digits in > hexadecimal represent one byte. > In the case above: 0x3c > c is 12 -> 1100 > 3 is 3 -> 11 > together you get 111100, mask for bits 2-5 > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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