On Tue, Oct 6, 2009 at 4:39 PM, Christopher Barker <chris.bar...@noaa.gov> wrote: > josef.p...@gmail.com wrote: >> If I have a structured or a regular array, is the use of strides in >> the following always correct for the length of the row memory? >> >> I would like to do tostring() but on each row, by creating a string >> view of the memory in a 1d array. > > Maybe I'm missing what you want, but why not just: > > In [15]: tmp > Out[15]: > array([[ 1.07810097, -1.74157351, 0.29740878], > [-0.16786436, 0.45752272, -0.8038045 ], > [-0.17195028, -1.16753882, 0.04329128], > [ 0.45460137, -0.44584955, -0.77140505]]) > > In [16]: rows = [] > > In [17]: for r in range(tmp.shape[0]): > rows.append(tmp[r,:].tostring()) > ....: > > In [19]: rows > Out[19]: > ['?\xf1?\xe6\xce\x1f9\xce\xbf\xfb\xdd|.\xc85Z?\xd3\x08\xbe\xd6\xb7\xb6\xe8', > '\xbf\xc5|\x94Sx\x92\x18?\xddH\r\\T\xfbT\xbf\xe9\xb8\xc45\xff\x92\xdf', > '\xbf\xc6\x02w\x82\x18i\xaf\xbf\xf2\xae=/\xfe\xff\x0b?\xa6*FD\xae\xd1F', > > '?\xdd\x180Z\xcet\xa5\xbf\xdc\x88\xcc\x8a\x8c\x8b\xe7\xbf\xe8\xafY\xa2\xf8\xac > '] > > > in general, you can let numpy worry about the strides, etc.
I wanted to avoid the python loop and thought creating the view will be faster with large arrays. But for this I need to know the memory length of a row of arbitrary types for the conversion to strings, strides was the only thing I could think of. > > -Chris > > -- > Christopher Barker, Ph.D. > Oceanographer > > Emergency Response Division > NOAA/NOS/OR&R (206) 526-6959 voice > 7600 Sand Point Way NE (206) 526-6329 fax > Seattle, WA 98115 (206) 526-6317 main reception > > chris.bar...@noaa.gov > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
