Shifting one curve to a reference curve using error minimization (fmincon from the Minimization Toolbox)
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I need to shift the red curve ONLY horizontally to overlap with the black one. This should be possible using error minimization (e.g. fmincon in the Optimization Toolbox) but I have not managed to do this so far. How can I do this?
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/790224/image.png)
2 Comments
Accepted Answer
Mathieu NOE
on 5 Nov 2021
hello again
as we look at data plotted in log log scale, a x shift is in fact a multiplicative coefficient on the Y amplitude
see the code and results below
I removed in my computation the first X samples where the two curve are not really parallel so it matches better for x > 10
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/790704/image.png)
clc
clearvars
data = readtable('ShiftData.xlsx');
X1 = data.x1;
Y1 = data.y1;
X2 = data.x2;
Y2 = data.y2;
% avoid taking into account first samples where two curves are not parallel
a = (Y1./Y2);
b = abs(a./rms(a));
ind = find( b> 0.5 & b < 2 );
am = rms(a(ind));
loglog(X1,Y1,X2,Y2,X2,Y2.*am);
legend('curve 1','curve 2' ,'curve 2 shifted');
3 Comments
Mathieu NOE
on 5 Nov 2021
oops - you're right , I was a bit too quick
now this should be better
I look for some points at same Y values belonging to both data and compute the X ratio to shift the Y2 data
here is it :
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/790994/image.png)
code :
clc
clearvars
data = readtable('ShiftData.xlsx');
X1 = data.x1;
Y1 = data.y1;
X2 = data.x2;
Y2 = data.y2;
ll = max(min(Y1),min(Y2));
mm = min(max(Y1),max(Y2));
ind1 = find(Y1>ll & Y1<mm);
X11 = X1(ind1);
Y11 = Y1(ind1);
ind2 = find(Y2>ll & Y2<mm);
X22 = X2(ind2);
Y22 = Y2(ind2);
ll = max(min(Y11),min(Y22));
mm = min(max(Y11),max(Y22));
N = 25;
thr = logspace(log10(3*ll),log10(0.7*mm),N);
for ci = 1: N
[t0_pos1(ci),~,~,~]= crossing_V7(Y11,X11,thr(ci),'linear'); % positive (pos) and negative (neg) slope crossing points
[t0_pos2(ci),~,~,~]= crossing_V7(Y22,X22,thr(ci),'linear'); % positive (pos) and negative (neg) slope crossing points
dt(ci) = t0_pos2(ci)/t0_pos1(ci);
end
yy1 = interp1(X1,Y1,t0_pos1);
yy2 = interp1(X2,Y2,t0_pos2);
shift_X = 1./mean(dt);
loglog(X1,Y1,t0_pos1,yy1,'dr',X2,Y2,t0_pos2,yy2,'dc',X2.*shift_X,Y2);
legend('curve 1','curve 1 test points','curve 2' ,'curve 2 test points','curve 2 shifted');
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [t0_pos,s0_pos,t0_neg,s0_neg] = crossing_V7(S,t,level,imeth)
% [ind,t0,s0,t0close,s0close] = crossing_V6(S,t,level,imeth,slope_sign) % older format
% CROSSING find the crossings of a given level of a signal
% ind = CROSSING(S) returns an index vector ind, the signal
% S crosses zero at ind or at between ind and ind+1
% [ind,t0] = CROSSING(S,t) additionally returns a time
% vector t0 of the zero crossings of the signal S. The crossing
% times are linearly interpolated between the given times t
% [ind,t0] = CROSSING(S,t,level) returns the crossings of the
% given level instead of the zero crossings
% ind = CROSSING(S,[],level) as above but without time interpolation
% [ind,t0] = CROSSING(S,t,level,par) allows additional parameters
% par = {'none'|'linear'}.
% With interpolation turned off (par = 'none') this function always
% returns the value left of the zero (the data point thats nearest
% to the zero AND smaller than the zero crossing).
%
% check the number of input arguments
error(nargchk(1,4,nargin));
% check the time vector input for consistency
if nargin < 2 | isempty(t)
% if no time vector is given, use the index vector as time
t = 1:length(S);
elseif length(t) ~= length(S)
% if S and t are not of the same length, throw an error
error('t and S must be of identical length!');
end
% check the level input
if nargin < 3
% set standard value 0, if level is not given
level = 0;
end
% check interpolation method input
if nargin < 4
imeth = 'linear';
end
% make row vectors
t = t(:)';
S = S(:)';
% always search for zeros. So if we want the crossing of
% any other threshold value "level", we subtract it from
% the values and search for zeros.
S = S - level;
% first look for exact zeros
ind0 = find( S == 0 );
% then look for zero crossings between data points
S1 = S(1:end-1) .* S(2:end);
ind1 = find( S1 < 0 );
% bring exact zeros and "in-between" zeros together
ind = sort([ind0 ind1]);
% and pick the associated time values
t0 = t(ind);
s0 = S(ind);
if ~isempty(ind)
if strcmp(imeth,'linear')
% linear interpolation of crossing
for ii=1:length(t0)
%if abs(S(ind(ii))) >= eps(S(ind(ii))) % MATLAB V7 et +
if abs(S(ind(ii))) >= eps*abs(S(ind(ii))) % MATLAB V6 et - EPS * ABS(X)
% interpolate only when data point is not already zero
NUM = (t(ind(ii)+1) - t(ind(ii)));
DEN = (S(ind(ii)+1) - S(ind(ii)));
slope = NUM / DEN;
slope_sign(ii) = sign(slope);
t0(ii) = t0(ii) - S(ind(ii)) * slope;
s0(ii) = level;
end
end
end
% extract the positive slope crossing points
ind_pos = find(sign(slope_sign)>0);
t0_pos = t0(ind_pos);
s0_pos = s0(ind_pos);
% extract the negative slope crossing points
ind_neg = find(sign(slope_sign)<0);
t0_neg = t0(ind_neg);
s0_neg = s0(ind_neg);
else
% empty output
ind_pos = [];
t0_pos = [];
s0_pos = [];
% extract the negative slope crossing points
ind_neg = [];
t0_neg = [];
s0_neg = [];
end
end
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