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rINSTCONTROL/Fit classes/@MyDoubleLorentzianFit/MyDoubleLorentzianFit.m
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MyDoubleLorentzianFit.m
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classdef MyDoubleLorentzianFit < MyFit
properties (Access=public)
tot_spacing;
end
%Public methods
methods (Access=public)
%Constructor function
function this=MyDoubleLorentzianFit(varargin)
this@MyFit(...
'fit_name','DoubleLorentzian',...
'fit_function','1/pi*b/2*a/((x-c)^2+(b/2)^2)+1/pi*e/2*d/((x-f)^2+(e/2)^2)+g',...
'fit_tex','$$\frac{a}{\pi}\frac{b/2}{(x-c)^2+(b/2)^2}+\frac{d}{\pi}\frac{e/2}{(x-f)^2+(e/2)^2}+g$$',...
'fit_params', {'a','b','c','d','e','f','g'},...
'fit_param_names',{'Amplitude 1','Width 1','Center 1','Amplitude 2',...
'Width 2','Center 2','Offset'},...
varargin{:});
end
end
methods (Access=protected)
function [p_in,lim_lower,lim_upper]=calcInitParams(this)
x = this.Data.x;
y = this.Data.y;
%Assumes form a/pi*b/2/((x-c)^2+(b/2)^2)+d/pi*e/2/((x-f)^2+(e/2)^2))+g
lim_upper=[Inf,Inf,Inf,Inf,Inf,Inf,Inf];
lim_lower=[-Inf,0,-Inf,-Inf,0,-Inf,-Inf];
%Finds peaks on the positive signal (max 2 peaks)
[~,locs{1},widths{1},proms{1}]=findpeaks(y,x,...
'MinPeakDistance',0.01*range(x),'SortStr','descend','NPeaks',2);
%Finds peaks on the negative signal (max 2 peaks)
[~,locs{2},widths{2},proms{2}]=findpeaks(-y,x,...
'MinPeakDistance',0.001*range(x),'SortStr','descend','NPeaks',2);
%If the prominence of the peak in the positive signal is greater, we adapt
%our limits and parameters accordingly, if negative signal has a greater
%prominence, we use this for fitting.
if isempty(proms{2}) || proms{1}(1)>proms{2}(1)
ind=1;
lim_lower(1)=0;
lim_lower(4)=0;
p_in(7)=min(y);
else
lim_upper(1)=0;
lim_upper(4)=0;
ind=2;
p_in(7)=max(y);
proms{2}=-proms{2};
end
p_in(2)=widths{ind}(1);
%Calculates the amplitude, as when x=c, the amplitude is 2a/(pi*b)
p_in(1)=proms{ind}(1)*pi*p_in(2)/2;
p_in(3)=locs{ind}(1);
if length(locs{ind})==2
p_in(5)=widths{ind}(2);
p_in(4)=proms{ind}(2)*pi*p_in(5)/2;
p_in(6)=locs{ind}(2);
else
p_in(5)=widths{ind}(1);
p_in(4)=proms{ind}(1)*pi*p_in(5)/2;
p_in(6)=locs{ind}(1);
end
%If one of the lorentzians is found to be much smaller than the other, we
%instead fit using only the greater lorentzian's parameters. This is an
%adaption for very closely spaced lorentzians.
if abs(p_in(1))>abs(10*p_in(4))
p_in(1)=p_in(1)/2;
p_in(5)=p_in(2);
p_in(6)=p_in(3);
p_in(4)=p_in(1);
end
lim_lower(2)=0.01*p_in(2);
lim_upper(2)=100*p_in(2);
lim_lower(5)=0.01*p_in(5);
lim_upper(5)=100*p_in(5);
end
%Calculates user-defined parameters
function calcUserParams(this)
this.opt_lw1=convOptFreq(this,this.coeffs(2));
this.opt_lw2=convOptFreq(this,this.coeffs(5));
splitting=abs(this.coeffs(6)-this.coeffs(3));
this.mode_split=convOptFreq(this,splitting);
end
%This function is used to convert the x-axis to frequency.
function real_freq=convOptFreq(this,freq)
real_freq=freq*this.line_spacing*this.line_no/this.tot_spacing;
end
function createUserGuiStruct(this)
createUserGuiStruct@MyFit(this);
this.UserGui.Tabs.Opt.tab_title='Optical';
this.UserGui.Tabs.Opt.Children={};
addUserField(this,'Opt','line_spacing',...
'Line Spacing (MHz)',1e6,'conv_factor',1e6,...
'Callback', @(~,~) calcUserParams(this));
addUserField(this,'Opt','line_no','Number of lines',10,...
'Callback', @(~,~) calcUserParams(this));
addUserField(this,'Opt','opt_lw1','Linewidth 1 (MHz)',1e6,...
'enable_flag','off','conv_factor',1e6);
addUserField(this,'Opt','opt_lw2','Linewidth 2 (MHz)',1e6,...
'enable_flag','off','conv_factor',1e6);
addUserField(this,'Opt','mode_split',...
'Modal splitting (MHz)',1e6,...
'enable_flag','off','conv_factor',1e6);
end
function genSliderVecs(this)
genSliderVecs@MyFit(this);
if validateData(this)
%We choose to have the slider go over the range of
%the x-values of the plot for the center of the
%Lorentzian.
this.slider_vecs{3}=...
linspace(this.x_vec(1),this.x_vec(end),101);
%Find the index closest to the init parameter
[~,ind]=...
min(abs(this.init_params(3)-this.slider_vecs{3}));
%Set to ind-1 as the slider goes from 0 to 100
set(this.Gui.(sprintf('Slider_%s',...
this.fit_params{3})),'Value',ind-1);
%Same for the other center
this.slider_vecs{6}=...
linspace(this.x_vec(1),this.x_vec(end),101);
%Find the index closest to the init parameter
[~,ind]=...
min(abs(this.init_params(6)-this.slider_vecs{6}));
%Set to ind-1 as the slider goes from 0 to 100
set(this.Gui.(sprintf('Slider_%s',...
this.fit_params{6})),'Value',ind-1);
end
end
end
end
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