필터 지우기
필터 지우기

How to differentiate vectors

조회 수: 3 (최근 30일)
Ikechi Ndamati
Ikechi Ndamati 2022년 2월 15일
댓글: Star Strider 2022년 2월 17일
Hello, please I have a code with lambda and n given below. Please how do I obtain d(n)/d(lambda) and d^2(n)/d(lambda)^2 i.e. the first and second deriviative of n wrt lambda?
lambda = linspace(0.5,2.5);
n = [1.55155531233953 1.54949576778463 1.54767969992980 1.54606941077293 1.54463432037936 1.54334939304258 1.54219395936135 1.54115082328366 1.54020557725122 1.53934607132757 1.53856199764777 1.53784456219577 1.53718622338909 1.53658048225698 1.53602171281363 1.53550502400216 1.53502614662547 1.53458134019413 1.53416731575664 1.53378117163556 1.53342033964695 1.53308253988297 1.53276574252631 1.53246813546774 1.53218809673566 1.53192417093373 1.53167504903131 1.53143955097005 1.53121661064518 1.53100526289637 1.53080463220578 1.53061392285076 1.53043241030050 1.53025943367952 1.53009438914900 1.52993672407995 1.52978593191141 1.52964154760293 1.52950314360382 1.52937032627300 1.52924273269261 1.52912002782641 1.52900190198108 1.52888806853379 1.52877826189461 1.52867223567629 1.52856976104774 1.52847062525013 1.52837463025771 1.52828159156731 1.52819133710247 1.52810370622009 1.52801854880867 1.52793572446860 1.52785510176605 1.52777655755305 1.52769997634709 1.52762524976427 1.52755227600092 1.52748095935889 1.52741120981038 1.52734294259859 1.52727607787089 1.52721054034140 1.52714625898047 1.52708316672849 1.52702120023196 1.52696029959983 1.52690040817834 1.52684147234282 1.52678344130489 1.52672626693392 1.52666990359143 1.52661430797744 1.52655943898778 1.52650525758144 1.52645172665720 1.52639881093877 1.52634647686784 1.52629469250434 1.52624342743341 1.52619265267854 1.52614234062043 1.52609246492120 1.52604300045342 1.52599392323372 1.52594521036064 1.52589683995631 1.52584879111185 1.52580104383610 1.52575357900747 1.52570637832878 1.52565942428470 1.52561270010188 1.52556618971130 1.52551987771288 1.52547374934221 1.52542779043906 1.52538198741785 1.52533632723963];
plot(n,lambda)
ylabel('n','FontWeight','bold','FontSize',14)
xlabel('lambda','FontWeight','bold','FontSize',14)

채택된 답변

Star Strider
Star Strider 2022년 2월 15일
Use the gradient function —
lambda = linspace(0.5,2.5);
n = [1.55155531233953 1.54949576778463 1.54767969992980 1.54606941077293 1.54463432037936 1.54334939304258 1.54219395936135 1.54115082328366 1.54020557725122 1.53934607132757 1.53856199764777 1.53784456219577 1.53718622338909 1.53658048225698 1.53602171281363 1.53550502400216 1.53502614662547 1.53458134019413 1.53416731575664 1.53378117163556 1.53342033964695 1.53308253988297 1.53276574252631 1.53246813546774 1.53218809673566 1.53192417093373 1.53167504903131 1.53143955097005 1.53121661064518 1.53100526289637 1.53080463220578 1.53061392285076 1.53043241030050 1.53025943367952 1.53009438914900 1.52993672407995 1.52978593191141 1.52964154760293 1.52950314360382 1.52937032627300 1.52924273269261 1.52912002782641 1.52900190198108 1.52888806853379 1.52877826189461 1.52867223567629 1.52856976104774 1.52847062525013 1.52837463025771 1.52828159156731 1.52819133710247 1.52810370622009 1.52801854880867 1.52793572446860 1.52785510176605 1.52777655755305 1.52769997634709 1.52762524976427 1.52755227600092 1.52748095935889 1.52741120981038 1.52734294259859 1.52727607787089 1.52721054034140 1.52714625898047 1.52708316672849 1.52702120023196 1.52696029959983 1.52690040817834 1.52684147234282 1.52678344130489 1.52672626693392 1.52666990359143 1.52661430797744 1.52655943898778 1.52650525758144 1.52645172665720 1.52639881093877 1.52634647686784 1.52629469250434 1.52624342743341 1.52619265267854 1.52614234062043 1.52609246492120 1.52604300045342 1.52599392323372 1.52594521036064 1.52589683995631 1.52584879111185 1.52580104383610 1.52575357900747 1.52570637832878 1.52565942428470 1.52561270010188 1.52556618971130 1.52551987771288 1.52547374934221 1.52542779043906 1.52538198741785 1.52533632723963];
plot(n,lambda)
ylabel('\lambda','FontWeight','bold','FontSize',14)
xlabel('n','FontWeight','bold','FontSize',14)
dndlambda = gradient(n) ./ gradient(lambda); % First Numerical Derivative
d2ndlambda2 = gradient(dndlambda) ./ gradient(lambda); % Second NMumerical Derivative
figure
yyaxis left
plot(lambda, n, 'DisplayName','Original Data')
yyaxis right
plot(lambda, dndlambda, 'DisplayName','First Derivative')
hold on
plot(lambda, d2ndlambda2, 'DisplayName','Second Derivative')
hold off
grid
xlabel('\lambda','FontWeight','bold','FontSize',14)
legend('Location','best')
Note that the first asrgument to plot is the independent variable and the second argument is the dependent variable. I corrected the axis labels in the firsst plot to reflect this.
I used yyaxis because the magnitudes between the original data and the derivatives are significantly different.
.
  댓글 수: 2
Ikechi Ndamati
Ikechi Ndamati 2022년 2월 17일
Thanks so much @Star Strider
Star Strider
Star Strider 2022년 2월 17일
As always, my pleasure!

댓글을 달려면 로그인하십시오.

추가 답변 (0개)

카테고리

Help CenterFile Exchange에서 Smoothing and Denoising에 대해 자세히 알아보기

제품

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by