Timeline for Increasing the speed of sparse array
Current License: CC BY-SA 4.0
8 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 21, 2018 at 19:01 | vote | accept | jsid | ||
| Sep 21, 2018 at 19:01 | comment | added | jsid | Ya, thanks that's a really fast code. But its is required to be a fat matrix since I need to carryout SVD on the complete matrix. | |
| Sep 21, 2018 at 18:23 | comment | added | Henrik Schumacher | @jsid, my friend: It is not my fault that you want to assemble such a fat matrix. ^^ | |
| Sep 21, 2018 at 18:12 | comment | added | jsid | Your code is really fast in computing the SparseMat . But, after the computation my Mathematica slows down a little, maybe on a powerful computer with more RAM it wouldn't and operations on SparseMat wouldn't hang. Btw, with ByteCount, SparseMat takes 1.07813 Gb of space. | |
| Sep 21, 2018 at 14:45 | history | edited | Henrik Schumacher | CC BY-SA 4.0 | edited body |
| Sep 21, 2018 at 14:33 | comment | added | Carl Woll | Since col2 is randomly generated, the OP may wish to do this procedure multiple times with different randomly generated values for col2. In that case, it makes sense to define nf = Nearest[Col -> Automatic] once, and then use Flatten @ nf[col2] for each invocation of col2. | |
| Sep 21, 2018 at 14:22 | history | edited | Henrik Schumacher | CC BY-SA 4.0 | deleted 51 characters in body |
| Sep 21, 2018 at 14:11 | history | answered | Henrik Schumacher | CC BY-SA 4.0 |