Timeline for Calculating derivative of experimental data (with noise) using tangent method
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
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| Oct 7, 2022 at 20:51 | comment | added | MarcoB | @atapaka Thank you for the link. On this second data set the linfit approach took 7 minutes and did not run out of memory on my relatively limited laptop (screenshot). | |
| Oct 7, 2022 at 19:58 | comment | added | atapaka | I used it for most of the analyses but the issue is that I need to do some analysis with the derivative that is not available in the software. The link is wolframcloud.com/obj/f487156f-b8ae-4d07-a728-56f528ce1bd6 I dont know why the slash appeared there. It is an interesting problem though, I just wrote the code in matlab, hoping it would be faster than MA, but it is almost the same performance... The S-G method you mentioned is really more and more intriguing but how do you deal with the memory issue (when i run S-G implemented from the link in the post, i run out of mem.? | |
| Oct 7, 2022 at 19:07 | comment | added | MarcoB | @atapaka I can't get the link to the cloud object in the comment above to work. In any case, if you already have a solution through the other software, then I guess your best bet would be to use that. | |
| Oct 7, 2022 at 19:03 | comment | added | atapaka | I noticed that Fit uses all cores on my machine (4 cores). When I use this dataset CloudObject["https://www.wolframcloud.com/obj/f487156f-b8ae-4d07-a728-\ 56f528ce1bd6"] the Fit take 2-3 minutes with 1201 point window, linfit does not end before my patience does. This exact dataset with this smoothing takes less than 3 sec in the software which runs in a virtual environment (only 2 cpus). Unless there is some obvious way to speed it up by 2 om (i need this type of derivative anyway to keep consistent with all analyses that were done in that software), i am giving up on optimization. | |
| Oct 7, 2022 at 14:15 | history | answered | MarcoB | CC BY-SA 4.0 |