On Tue, Oct 6, 2009 at 4:39 PM, Christopher Barker
josef.pktd@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
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