Thanks Jamie, Indeed those objects were very helpful at this stage.
Now I need to do something a little more complex which may need to perform better than unpacking to a list for calcs... I need to calculate the sum of the differences between two tables (768 elements each). I suppose the fastest way would be to do it in the signal domain? Really what I got used to is the amazing and fast vector operations in R. Seems to me the best thing would be a numpy py external that accesses the tables directly. I hunger for a unified datatype in PD not tied to data-structures. I mean things like tables of symbols, tables of lists and tables of tables. And, of course, higher math functions on those tables. Thanks all, B. Jamie Bullock wrote: > On Sat, 2008-10-25 at 00:21 +0200, Frank Barknecht wrote: >> Hallo, >> B. Bogart hat gesagt: // B. Bogart wrote: >> >>> What is the best (least cpu usage) way to get some basic stats on the >>> content of a table? >> Are externals allowed? Then either vasp or the iem_tab externals may be >> worth a look, i.e.: >> >> iem_tab is written by Thomas Musil from IEM Graz Austria and it is >> compatible to miller puckette's pd-0.37-3 to pd-0.39-2. see also >> LICENCE.txt, GnuGPL.txt. >> >> The objects of iem_tab manipulate tables or arrays; you can set >> constant, copy, fft, ifft, reverse, find minimum or maximum, compare, >> add, subtract, mul tiplicate, divide arrays. > > There is of course the mighty zexy also. In there you have: > > tabminmax: get the minimum and maximum of a table (I think this is what > Ben wants to do) > tabdump: dump the contents of the table to a list > unpack~/pack~ : convert between list and signal > > If you want to do complex things, you could unpack~ the table contents > into a signal, then get your stats from the signal vector. For example > you could use something like xtract~ (from libXtract) to get a whole > bunch of different stats from the audio vector if you wanted. > > Jamie > _______________________________________________ [email protected] mailing list UNSUBSCRIBE and account-management -> http://lists.puredata.info/listinfo/pd-list
