Is your cloud always on? With an Always On cloud you won't have to worry about downtime for maintenance or software application code updates, ensuring that your bottom line isn't affected.
??? Error using ==> sphere Too many input arguments.
Error in ==>sphereplotting at 89
Z = sphere(X1,X2);
function ph = sphere(x)
ph = sum(x.*x, 2);
end
??? Error using ==> contour at 73
Z must be size 2x2 or greater.
cmin = -25;
cmax = 25;
ngrid = 25;
cvals = linspace(cmin, cmax, ngrid); % Create the mesh
[X1, X2] = meshgrid(cvals, cvals); % Create the grid
% k=1,l=2;
Z = sphere(X1,X2);
figure;
contour(X1, X2, Z);
M = 100; % population size
n = 2;
pop = 0 + 1.*randn(M,n);
[popSize d] = size(pop);
G = 25; % number of generations for the fitness evaluation function
Max_F = 1000; % maximal number of FEs
options.optmType = 'max';
y = zeros(1,G);
for i =1:G
eval = sphere(pop); % fitness evaluation of the initial population.
% Setting Criteria for selecting N(<=M)
if ~isfield(options, 'optmType')
error('Please provide optimisation type {min, max}');
end
% define best population size
if isfield(options, 'topSize')
topSize = options.topSize;
if topSize > popSize
disp('Warning: topSize is larger than popSize, will use, popSize/10');
topSize = 0.25 * popSize;
options.topSize = topSize;
end
else
topSize = 0.25 * popSize;
options.topSize = topSize;
end
% all initial pop are top_x
top_x = pop;
% Criteria for selecting top 'topSize' individuals based on fitness
% values(eval)
if strcmp(options.optmType, 'min')
[void, b] = sort(eval, 'descend'); % maximising
else
[void, b] = sort(eval, 'ascend'); % minimising
end
top_x = pop(b(1:options.topSize),:); % select top individuals
optm_x = pop(b(1),:); % save optimal parameter
fv = eval(b(1)); % save optimal func. value
mu = mean(top_x); % mean vector calculation
Sigma = cov(top_x); % Covariance calculation
pop = mvnrnd(mu,Sigma,M); % Calculate joint probability distribution of selected individuals(sampling)
dstring = [num2str(M), ' samples are generated.'];
subplot(1,2,1);
y(i) = sphere(optm_x);
plot(y(1:i));
xlabel('Generations')
ylabel(' Best Individuals')
title(sprintf('At the some Generations'))
%axis('equal');
cmin = -25;
cmax = 25;
ngrid = 25;
cvals = linspace(cmin, cmax, ngrid); % Create the mesh
[X1, X2] = meshgrid(cvals, cvals); % Create the grid
Z = sphere(X1);
subplot(1,2,2);
contour(X1, X2, Z);
end
eval = sphere(pop); % fitness evaluation of the initial population.
Z = arrayfun(@sphere, X1);
The surf & Plot3 plots show a parabola, but the contour plot shows only vertical lines, not contours. I don't know why? contour(X1, X2, Z);
shows the vertical lines not contours, why?surf(X1, X2, Z); and Plot3(X1, X2, Z);
show parabola which is reasonable.arrayfun
?
function ph = sphere(x)
ph = sum(x.*x,2);
end
Z = arrayfun(@sphere, X1);
eval = sphere(pop);
contour(X1, X2, Z);
Is showing vertical line, not contour line. This is not how it should be. How can i fix this?
K= 4
for l = 1 : K
contour(X,Y,ph);
hold on
plot(bestId, 'rx');
end
Which line of your code is at 89? Which is at 73?
What is Z?