How to find the values of jump in an array?
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I am trying to find the displacement jump from an array where I want to get the values at the locations highlighted in the attached image.
Following the array that I currently have for now:
v = [0 0.128669530153275 0.130120709538460 0.134193837642670 0.106409639120102 0.0963872149586678 0.0900304913520813 0.0918694287538528 0.0891467630863190 0.0845631361007690 0.0796448960900307 0.0774808377027512 0.0832534655928612 0.0903223231434822 0.0791355073451996 0.0867500454187393 0.0822556465864182 0.0834708511829376 0.0809724852442741 0.0769125446677208 0.0762052312493324 0.0814182013273239 0.0824952796101570 0.0871148481965065 0.0828126743435860 0.0934268161654472 0.100223250687122 0.105054035782814 0.101684793829918 0.0938292965292931 0.0913284420967102 0.0830449163913727 0.0823436081409454 0.0801921039819717 0.0739008858799934 0.0733054578304291 0.0756217613816261 0.0752388313412666 0.0852720662951469 0.0937606021761894 0.102765440940857 0.113776959478855 0.114458248019218 0.119862981140614 0.126136168837547 0.130058258771896 0.134705126285553 0.135741069912910 0.143991172313690 0.141014173626900 0.149323135614395 0.139213815331459 0.116455316543579 0.0450247861444950 -0.0422766618430615 -0.133420765399933 -0.196351751685143 -0.255337893962860 -0.268517315387726 -0.271409779787064 -0.272508561611176 -0.272525668144226 -0.270379871129990 -0.270709663629532 -0.271532326936722 -0.269337981939316 -0.277245104312897 -0.275981307029724 -0.279530405998230 -0.281473547220230 -0.279926627874374 -0.279666334390640 -0.288220971822739 -0.280666559934616 0];
There are in total more than 3000 files in total with same trend that I want to observe and it is quite possible that maxima or minima is not always just at the start of or end of prominent jump as shown in figure. Any help regarding this is highly appreciated.
Cheers,
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Réponse acceptée
Rik
le 22 Juin 2019
There are several ways to solve this. Below you find a way to look over a few samples where there is a big jump. Another option would be to do a movmean on the diff and then find the biggest jump.
v = [0 0.128669530153275 0.130120709538460 0.134193837642670 0.106409639120102 0.0963872149586678 0.0900304913520813 0.0918694287538528 0.0891467630863190 0.0845631361007690 0.0796448960900307 0.0774808377027512 0.0832534655928612 0.0903223231434822 0.0791355073451996 0.0867500454187393 0.0822556465864182 0.0834708511829376 0.0809724852442741 0.0769125446677208 0.0762052312493324 0.0814182013273239 0.0824952796101570 0.0871148481965065 0.0828126743435860 0.0934268161654472 0.100223250687122 0.105054035782814 0.101684793829918 0.0938292965292931 0.0913284420967102 0.0830449163913727 0.0823436081409454 0.0801921039819717 0.0739008858799934 0.0733054578304291 0.0756217613816261 0.0752388313412666 0.0852720662951469 0.0937606021761894 0.102765440940857 0.113776959478855 0.114458248019218 0.119862981140614 0.126136168837547 0.130058258771896 0.134705126285553 0.135741069912910 0.143991172313690 0.141014173626900 0.149323135614395 0.139213815331459 0.116455316543579 0.0450247861444950 -0.0422766618430615 -0.133420765399933 -0.196351751685143 -0.255337893962860 -0.268517315387726 -0.271409779787064 -0.272508561611176 -0.272525668144226 -0.270379871129990 -0.270709663629532 -0.271532326936722 -0.269337981939316 -0.277245104312897 -0.275981307029724 -0.279530405998230 -0.281473547220230 -0.279926627874374 -0.279666334390640 -0.288220971822739 -0.280666559934616 0];
long_diff=@(x,k) x((1+k):end)-x(1:(end-k));
k=5;%define window size
a=long_diff(v,k);
[~,b]=max(abs(a));
v2=v(b+(-k:k));
jump_size=max(v2)-min(v2);
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