Hi there,
I have the piece of code that you see at the bottom. In short,
I have a function whose form I don’t know but I know it is smooth and I can interpolated it.
I create a function function that accepts a cell as an input and has 2 variables.
I create a new function to three variables, the previous 2 + 1, so that I can minimise it useing fzero
I would like to use arrayfun or cellfun (or any other trick) to evaluate fzero over several pairs of inputs all at once to avoid looping.
I would appreciate if someone could put me on the right track.
miny = setting.Y.miny;
maxy = y(end);
xrep = reshape(repmat(x’, [y_sz 1]),[x_sz*y_sz 1]);
yrep = repmat(y, [x_sz 1]);
xy = mat2cell(num2cell([xrep yrep]), ones([x_sz*y_sz 1]), 2);
Fmin_bar = MW_mw.Fmin_bar;
Smin = griddedInterpolant({x,y},MW_mw.S_xy_min,"linear","spline");
dSdy =@(c) (Smin({c{1},c{2}+1e-9})-Smin(c))./1e-9.*MS_tilde_f(c{:});
t_thres =@(t,c) dSdy(c) – c{1}./(r+delta+s.*lamb_min.*Fmin_bar(t));d
tr = fzero(@(t) t_thres(t,c),[miny maxy*10]);
tr = zeros(4000,1);
tic
for i = 1:4000
z = xy{i,:};
try
tr(i) = fzero(@(t) t_thres(t,z),[miny maxy*10]);
catch
tr(i) = NaN;
end
end
Best,
RubenHi there,
I have the piece of code that you see at the bottom. In short,
I have a function whose form I don’t know but I know it is smooth and I can interpolated it.
I create a function function that accepts a cell as an input and has 2 variables.
I create a new function to three variables, the previous 2 + 1, so that I can minimise it useing fzero
I would like to use arrayfun or cellfun (or any other trick) to evaluate fzero over several pairs of inputs all at once to avoid looping.
I would appreciate if someone could put me on the right track.
miny = setting.Y.miny;
maxy = y(end);
xrep = reshape(repmat(x’, [y_sz 1]),[x_sz*y_sz 1]);
yrep = repmat(y, [x_sz 1]);
xy = mat2cell(num2cell([xrep yrep]), ones([x_sz*y_sz 1]), 2);
Fmin_bar = MW_mw.Fmin_bar;
Smin = griddedInterpolant({x,y},MW_mw.S_xy_min,"linear","spline");
dSdy =@(c) (Smin({c{1},c{2}+1e-9})-Smin(c))./1e-9.*MS_tilde_f(c{:});
t_thres =@(t,c) dSdy(c) – c{1}./(r+delta+s.*lamb_min.*Fmin_bar(t));d
tr = fzero(@(t) t_thres(t,c),[miny maxy*10]);
tr = zeros(4000,1);
tic
for i = 1:4000
z = xy{i,:};
try
tr(i) = fzero(@(t) t_thres(t,z),[miny maxy*10]);
catch
tr(i) = NaN;
end
end
Best,
Ruben Hi there,
I have the piece of code that you see at the bottom. In short,
I have a function whose form I don’t know but I know it is smooth and I can interpolated it.
I create a function function that accepts a cell as an input and has 2 variables.
I create a new function to three variables, the previous 2 + 1, so that I can minimise it useing fzero
I would like to use arrayfun or cellfun (or any other trick) to evaluate fzero over several pairs of inputs all at once to avoid looping.
I would appreciate if someone could put me on the right track.
miny = setting.Y.miny;
maxy = y(end);
xrep = reshape(repmat(x’, [y_sz 1]),[x_sz*y_sz 1]);
yrep = repmat(y, [x_sz 1]);
xy = mat2cell(num2cell([xrep yrep]), ones([x_sz*y_sz 1]), 2);
Fmin_bar = MW_mw.Fmin_bar;
Smin = griddedInterpolant({x,y},MW_mw.S_xy_min,"linear","spline");
dSdy =@(c) (Smin({c{1},c{2}+1e-9})-Smin(c))./1e-9.*MS_tilde_f(c{:});
t_thres =@(t,c) dSdy(c) – c{1}./(r+delta+s.*lamb_min.*Fmin_bar(t));d
tr = fzero(@(t) t_thres(t,c),[miny maxy*10]);
tr = zeros(4000,1);
tic
for i = 1:4000
z = xy{i,:};
try
tr(i) = fzero(@(t) t_thres(t,z),[miny maxy*10]);
catch
tr(i) = NaN;
end
end
Best,
Ruben arrayfun, cellfun, fzero MATLAB Answers — New Questions

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