Am 12.12.14 09:30, schrieb KK Sasa:
Mark Lawrence於 2014年12月12日星期五UTC+8下午3時17分43秒寫道：
Hi Mark and Yotam, Thanks for kind reply. I think I didn't make my
problem clear enough. The slow part is "[d2(t[k]) for k in
xrange(1000)]". In addition, I don't need to construct a list of 1000
lists inside, but my aim is to get the sum of all "d2(t[k])". I
wonder if there is any method to sum up efficiently.
Not sure I understand what you need, but it seems that NumPy would be a
more efficient method. numpy.sum can sum elements along every dimensions
of a higher-dimensional matrix, and in general NumPy stores the elements
in native doubles instead of Python lists, which improves both
performance and memory usage
Christian
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