I am trying to sum a function and then attempting to find the root of said function. That is, for example, take:
Consider that I have a matrix,X, and vector,t, of values: X(2*n+1,n+1), t(n+1)
for j = 1:n+1
sum = 0;
for i = 1:2*j+1
f = #(g)exp[-exp[X(i,j)+g]*(t(j+1)-t(j))];
sum = sum + f;
end
fzero(sum,0)
end
That is,
I want to evaluate at
j = 1
f = #(g)exp[-exp[X(1,1)+g]*(t(j+1)-t(j))]
fzero(f,0)
j = 2
f = #(g)exp[-exp[X(1,2)+g]*(t(j+1)-t(j))] + exp[-exp[X(2,2)+g]*(t(j+1)-t(j))] + exp[-exp[X(3,2)+g]*(t(j+1)-t(j))]
fzero(f,0)
j = 3
etc...
However, I have no idea how to actually implement this in practice.
Any help is appreciated!
PS - I do not have the symbolic toolbox in Matlab.
I suggest making use of matlab's array operations:
zerovec = zeros(1,n+1); %preallocate
for k = 1:n+1
f = #(y) sum(exp(-exp(X(1:2*k+1,k)+y)*(t(k+1)-t(k))));
zerovec(k) = fzero(f,0);
end
However, note that the sum of exponentials will never be zero, unless the exponent is complex. Which fzero will never find, so the question is a bit of a moot point.
Another solution is to write a function:
function [ sum ] = func(j,g,t,X)
sum = 0;
for i = 0:2*j
f = exp(-exp(X(i+1,j+1)+g)*(t(j+3)-t(j+2)));
sum = sum + f;
end
end
Then loop your solver
for j=0:n
fun = #(g)func(j,g,t,X);
fzero(fun,0)
end
Related
I am using MATLAB to calculate the numerical integral of a complex function including natural exponent.
I get a warning:
Infinite or Not-a-Number value encountered
if I use the function integral, while another error is thrown:
Output of the function must be the same size as the input
if I use the function quadgk.
I think the reason could be that the integrand is infinite when the variable ep is near zero.
Code shown below. Hope you guys can help me figure it out.
close all
clear
clc
%%
N = 10^5;
edot = 10^8;
yita = N/edot;
kB = 8.6173324*10^(-5);
T = 300;
gamainf = 0.115;
dTol = 3;
K0 = 180;
K = K0/160.21766208;
nu = 3*10^12;
i = 1;
data = [];
%% lambda = ec/ef < 1
for ef = 0.01:0.01:0.1
for lambda = 0.01:0.01:0.08
ec = lambda*ef;
f = #(ep) exp(-((32/3)*pi*gamainf^3*(0.5+0.5*sqrt(1+2*dTol*K*(ep-ec)/gamainf)-dTol*K*(ep-ec)/gamainf).^3/(K*(ep-ec)).^2-16*pi*gamainf^3*(0.5+0.5*sqrt(1+2*dTol*K*(ep-ec)/gamainf)-dTol*K*(ep-ec)/gamainf).^2/((1+dTol*K*(ep-ec)/(gamainf*(0.5+0.5*sqrt(1+2*dTol*K*(ep-ec)/gamainf)-dTol*K*(ep-ec)/gamainf)))*(K*(ep-ec)).^2))/(kB*T));
q = integral(f,0,ef,'ArrayValued',true);
% q = quadgk(f,0,ef);
prob = 1-exp(-yita*nu*q);
data(i,1) = ef;
data(i,2) = lambda;
data(i,3) = q;
i = i+1;
end
end
I've rewritten your equations so that a human can actually understand it:
function integration
N = 1e5;
edot = 1e8;
yita = N/edot;
kB = 8.6173324e-5;
T = 300;
gamainf = 0.115;
dTol = 3;
K0 = 180;
K = K0/160.21766208;
nu = 3e12;
i = 1;
data = [];
%% lambda = ec/ef < 1
for ef = 0.01:0.01:0.1
for lambda = 0.01:0.01:0.08
ec = lambda*ef;
q = integral(#f,0,ef,'ArrayValued',true);
% q = quadgk(f,0,ef);
prob = 1 - exp(-yita*nu*q);
data(i,:) = [ef lambda q];
i = i+1;
end
end
function y = f(ep)
G = K*(ep - ec);
r = dTol*G/gamainf;
S = sqrt(1 + 2*r);
x = (1 + S)/2 - r;
Z = 16*pi*gamainf^3;
y = exp( -Z*x.^2.*( 2*x/(3*G.^2) - 1/(G.^2*(1 + r/x))) ) /...
(kB*T));
end
end
Now, for the first iteration, ep = 0.01, the value of the argument of the exp() function inside f is huge. In fact, if I rework the function to return the argument to the exponent (not the value):
function y = f(ep)
% ... all of the above
% NOTE: removed the exp() to return the argument
y = -Z*x.^2.*( 2*x/(3*G.^2) - 1/(G.^2*(1 + r/x))) ) /...
(kB*T);
end
and print its value at some example nodes like so:
for ef = 0.01 : 0.01 : 0.1
for lambda = 0.01 : 0.01 : 0.08
ec = lambda*ef;
zzz(i,:) = [f(0) f(ef/4) f(ef)];
i = i+1;
end
end
zzz
I get this:
% f(0) f(ef/4) f(ef)
zzz =
7.878426438111721e+07 1.093627454284284e+05 3.091140080273912e+03
1.986962280947140e+07 1.201698288371587e+05 3.187767404903769e+03
8.908646053687230e+06 1.325435523124976e+05 3.288027743119838e+03
5.055141696747510e+06 1.467952125661714e+05 3.392088351112798e+03
...
3.601790797707676e+04 2.897200140791236e+02 2.577170427480841e+01
2.869829209254144e+04 3.673888685004256e+02 2.404148067956737e+01
2.381082059148755e+04 4.671147785149462e+02 2.238181495716831e+01
So, integral() has to deal with things like exp(10^7). This may not be a problem per se if the argument would fall off quickly enough, but as shown above, it doesn't.
So basically you're asking for the integral of a function that ranges in value between exp(~10^7) and exp(~10^3). Needless to say, The d(ef) in the order of 0.01 isn't going to compensate for that, and it'll be non-finite in floating point arithmetic.
I suspect you have a scaling problem. Judging from the names of your variables as well as the equations, I would think that this has something to do with thermodynamics; a reworked form of Planck's law? In that case, I'd check if you're working in nanometers; a few factors of 10^(-9) will creep in, rescaling your integrand to the compfortably computable range.
In any case, it'll be wise to check all your units, because it's something like that that's messing up the numbers.
NB: the maximum exp() you can compute is around exp(709.7827128933840)
I'm trying to call a numerical integration function (namely one that uses the trapazoidal method) to compute a definite integral. However, I want to pass more than one value of 'n' to the following function,
function I = traprule(f, a, b, n)
if ~isa(f, 'function_handle')
error('Your first argument was not a function handle')
end
h = (b-a)./ n;
x = a:h:b;
S = 0;
for j = 2:n
S = S + f(x(j));
end
I = (h/2)*(f(a) + 2*S + f(b)); %computes indefinite integral
end
I'm using; f = #(x) 1/x, a = 1 and b = 2. I'm trying to pass n = 10.^(1:10) too, however, I get the following output for I when I do so,
I =
Columns 1 through 3
0.693771403175428 0.069377140317543 0.006937714031754
Columns 4 through 6
0.000693771403175 0.000069377140318 0.000006937714032
Columns 7 through 9
0.000000693771403 0.000000069377140 0.000000006937714
Column 10
0.000000000693771
Any ideas on how to get the function to take n = 10.^(1:10) so I get an output something like,
I = 0.693771403175428, 0.693153430481824, 0.693147243059937 ... and so on for increasing powers of 10?
In the script where you are calling this from, simply iterate over n
k = 3;
f = #(x)1./x;
a = 1; b = 2;
I = zeros(k,1);
for n = 1:k
I(n) = traprule(f, a, b, 10^n);
end
% output: I = 0.693771403175428
% 0.693153430481824
% 0.693147243059937
Then I will contain all of the outputs. Alternatively you can adapt your function to use the same logic to loop over the elements of n if it is passed
as a vector.
Note, you can improve the efficiency of your traprule code by removing the for loop:
% This loop operates on every element of x individually, and is inefficient
S = 0;
for j = 2:n
S = S + f(x(j));
end
% If you ensure you use element-wise equations like f=#(x)1./x instead of f=#(x)1/x
% Then you can use this alternative:
S = sum(f(x(2:n)));
I want to calculate the limit of log(CR(r))/log(r) as r tends to 0.
MATLAB code is written below.
function cd = CD(data)
syms r
cd = limit(log(CR(r,data))/log(r),r,0) ;
end
function val = hf(xi,xj,r)
dis = abs(xi-xj);
if(dis <= r)
val = 1;
else
val = 0 ;
end
end
function cr = CR(r,data)
N = length(data);
sum = 0;
for i = 1 : N
for j = i+1 : N
sum = sum + hf(data(i),data(j),r);
end
end
cr = sum/(N*(N-1));
end
Error:-
Well, the error message says it all really:
You can't use a symbolic variable in an equality check. How can you know if dis <= r when r doesn't have a value?
I'm obligated to say this:
Don't use sum as a variable name! It's a very important and useful builtin function. You're making it useless when doing that.
i and j are bad variable names in MATLAB, since they denote the imaginary unit (sqrt(-1)).
Also, did I remember to say: Dont use sum as a variable name!
PS! Your hf-function is equivalent to:
function val = hf(xi,xj,r)
var = abs(xi-xj) <= r; % Still doesn't work since r is symbolic
end
I'm running a script calling a function and within the function it takes a value from the matrix. Matlab seems to be thinking that the value is still a matrix and is asking for a . when its squared. I should be getting a single value out of my matrix. Any help would be appreciated!
Output
Error using ^
Inputs must be a scalar and a square matrix.
To compute elementwise POWER, use POWER (.^) instead.
Error in ls_error (line 11)
partialSum = (vi - yi)^2;
This is the script i'm running
Exp1H1 = 35.6;
Exp1H2 = 24.7;
Exp2H1 = 46.8;
Exp2H2 = 37.8;
Exp3H1 = 45.7;
Exp3H2 = 36.4;
Exp4H1 = 47.7;
Exp4H2 = 39.2;
Radius = 3.75;
L = 10;
ArrayOfHeightDiff = [(Exp1H1-Exp1H2),(Exp2H1-Exp2H2),(Exp3H1-Exp3H2), (Exp4H1-Exp4H2)];
dhdl = ArrayOfHeightDiff./L
ArrayOfDarcys = [0.29,0.25,0.26,0.23];
v_meas = ((ArrayOfDarcys.*1000)./60)./(pi*Radius^2)
K = [-0.3 : 0.1 : 0.5];
for ii = 1 : 1 : length(K)
ExportSum = ls_error(dhdl, v_meas, K)
ExportSum(1,ii) = ExportSum
end
This is the function
function [ExportSum] = ls_error(dhdl, v_meas, K)
total = 0;
L = length(dhdl);
for ii = 1 : 1 : L
dhdl1 = dhdl(1,ii);
vi = v_meas(1,ii);
yi = 1*K* dhdl1;
partialSum = (vi - yi)^2;
total = total + partialSum;
end
ExportSum = total;
end
In the following code, you create a 1xN vector K, and pass it into ls_error:
K = [-0.3 : 0.1 : 0.5];
for ii = 1 : 1 : length(K)
ExportSum = ls_error(dhdl, v_meas, K)
ExportSum(1,ii) = ExportSum
end
You then use this vector Kand multiply it by two scalars, which will produce a 1xN vector:
yi = 1*K* dhdl1;
partialSum = (vi - yi)^2;
The partialSum calculation is then giving you the error, as you can't perform a scalar square on a vector.
From your code, what I think you meant to do was this:
for ii = 1 : 1 : length(K)
ExportSum = ls_error(dhdl, v_meas, K(ii))
ExportSum(1,ii) = ExportSum
end
Where instead of passing in the entire vector K, you just want to pass in the iith element to use within the calculation of ExportSum which you return.
As a further note, once this bug is solved, it may be worth looking at vectorising your Matlab function (i.e. deliberately passing it the entire vector of K and computing all of the ExportSums at once using vector arithmetic instead of inside a loop), which will hugely speed up your code. It can be complicated, but will likely give you a huge decrease in execution time.
In the calling script you define K as a vector. Therefore, in the function yi is a vector too. Hence the error in (vi - yi)^2.
I'm trying to optimize the performance (e.g. speed) of my code. I 'm new to vectorization and tried myself to vectorize, but unsucessful ( also try bxsfun, parfor, some kind of vectorization, etc ). Can anyone help me optimize this code, and a short description of how to do this?
% for simplify, create dummy data
Z = rand(250,1)
z1 = rand(100,100)
z2 = rand(100,100)
%update missing param on the last updated, thanks #Bas Swinckels and #Daniel R
j = 2;
n = length(Z);
h = 0.4;
tic
[K1, K2] = size(z1);
result = zeros(K1,K2);
for l = 1 : K1
for m = 1: K2
result(l,m) = sum(K_h(h, z1(l,m), Z(j+1:n)).*K_h(h, z2(l,m), Z(1:n-j)));
end
end
result = result ./ (n-j);
toc
The K_h.m function is the boundary kernel and defined as (x is scalar and y can be vector)
function res = K_h(h, x,y)
res = 0;
if ( x >= 0 & x < h)
denominator = integral(#kernelFunc,-x./h,1);
res = 1./h.*kernelFunc((x-y)/h)/denominator;
elseif (x>=h & x <= 1-h)
res = 1./h*kernelFunc((x-y)/h);
elseif (x > 1 - h & x <= 1)
denominator = integral(#kernelFunc,-1,(1-x)./h);
res = 1./h.*kernelFunc((x-y)/h)/denominator;
else
fprintf('x is out of [0,1]');
return;
end
end
It takes a long time to obtain the results: \Elapsed time is 13.616413 seconds.
Thank you. Any comments are welcome.
P/S: Sorry for my lack of English
Some observations: it seems that Z(j+1:n)) and Z(1:n-j) are constant inside the loop, so do the indexing operation before the loop. Next, it seems that the loop is really simple, every result(l, m) depends on z1(l, m) and z2(l, m). This is an ideal case for the use of arrayfun. A solution might look something like this (untested):
tic
% do constant stuff outside of the loop
Zhigh = Z(j+1:n);
Zlow = Z(1:n-j);
result = arrayfun(#(zz1, zz2) sum(K_h(h, zz1, Zhigh).*K_h(h, zz2, Zlow)), z1, z2)
result = result ./ (n-j);
toc
I am not sure if this will be a lot faster, since I guess the running time will not be dominated by the for-loops, but by all the work done inside the K_h function.