On 08/29/2013 01:48 PM, Ralf Gommers wrote:
Thanks. I had read that quite differently, and I'm sure I'm not the only one. Some context would have helped....
My apologies--that was a rather obtuse reference. In my oddly-wired brain it struck me as a fairly similar, suboptimally-posed question: all data structures sit in memory at the same speed, it's a question of the operations. And as you pointed out, most of the time for non-trivial datasets the numpy operations will be faster. (I'm daunted by the notion of trying to do linear algebra on lists of tuples, assuming that's the relevant set of operations given the comparison to the matrix class.) -- Jonathan Niehof ISR-3 Space Data Systems Los Alamos National Laboratory MS-D466 Los Alamos, NM 87545 Phone: 505-667-9595 email: jniehof@lanl.gov Correspondence / Technical data or Software Publicly Available