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rINSTCONTROL/@MyBeta/MyBeta.m
1b4ca1d7070aTekRSA-Freq-vs-Time

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MyBeta.m
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classdef MyBeta < handle
properties (Access=public)
name;
%Trace
Data
end
properties (GetAccess=public, SetAccess=private)
%Struct containing GUI handles
Gui;
beta;
enable_gui;
end
properties (Access=private)
%Input parser
Parser;
end
methods (Access=public)
function this=MyBeta(varargin)
%Parses inputs to the constructor
createParser(this);
parse(this.Parser,varargin{:});
this.Data=this.Parser.Results.Data;
this.enable_gui=this.Parser.Results.enable_gui;
%Default enables gui
if this.enable_gui
this.Gui=guihandles(eval('GuiBeta'));
initGui(this);
end
end
%Deletion function for cleanup
function delete(this)
if this.enable_gui
set(this.Gui.figure1,'CloseRequestFcn','');
%Deletes the figure
delete(this.Gui.figure1);
%Removes the figure handle to prevent memory leaks
this.Gui=[];
end
end
%Callback for analyze button
function analyzeCallback(this)
calcBeta(this);
end
%Calculates beta, updates the gui with the value and stores it in
%the class.
function calcBeta(this)
%Number of points next to peak we will use to find the area
%under each peak
n=10;
% Finding the index of the the centeral maximum and the side bands
min_pk_dist=200;
[peaks,pk_inds] = findpeaks(this.Data.y,...
'minpeakdistance',min_pk_dist);
%First we sort by height of the peaks
amp_sort=sortrows([peaks, pk_inds]);
%Then we sort the five highest peaks by location
sort_mat=sortrows(amp_sort((end-4):end,:),2);
%The sorted indices of the peaks
ind_sort=sort_mat(:,2);
% Finds indices for the data in the neighborhood of each peak
%Peak 1 is the leftmost (2nd order peak), Peak 2 is the left
%1st order peak, Peak 3 is the central peak etc.
ind_pks=cell(5,1);
for i=1:5
ind_pks{i}=(ind_sort(i)-n):(ind_sort(i)+n);
end
%Here we integrate the data surrounding the peaks and take the
%square root of the areas.
v_rms_pks=cellfun(@(x) sqrt(integrate(this.Data,x)),ind_pks);
% Then we can calculate the FM beta by using:
sdratio_01 = 0.5*(v_rms_pks(4)+v_rms_pks(2))/v_rms_pks(3);
sdratio_02 = 0.5*(v_rms_pks(5)+v_rms_pks(1))/v_rms_pks(3);
syms b;
%Then find the beta by numerically solution of the bessel
%functions
beta_01 = double(vpasolve(besselj(1,b) == ...
sdratio_01 * besselj(0,b), b, 2*sdratio_01));
beta_02 = double(vpasolve(besselj(2,b) == ...
sdratio_02 * besselj(0,b), b, 2*sdratio_02));
%We use beta_02 as it is less affected by residual intensity
%noise.
this.beta=beta_02;
%Sets the values on the GUI
set(this.Gui.Beta02,'String',num2str(beta_02,5));
set(this.Gui.Beta01,'String',num2str(beta_01,5));
end
end
methods (Access=private)
%Initializes the GUI with correct callbacks
function initGui(this)
this.Gui.AnalyzeButton.Callback=@(~,~) analyzeCallback(this);
this.Gui.figure1.CloseRequestFcn=@(~,~) closeFigure(this);
end
%The close figure function calls the deletion method.
function closeFigure(this)
delete(this);
end
%Creates input parser for constructor
function createParser(this)
p=inputParser;
addParameter(p,'Data',MyTrace())
addParameter(p,'enable_gui',true);
this.Parser=p;
end
end
end
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