			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

rINSTCONTROL/@MyBeta/MyBeta.m
a4a7f284022cconfint-fix

MyBeta.m
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rINSTCONTROL/@MyBeta/MyBeta.ma4a7f284022cconfint-fix

MyBeta.mView Options

rINSTCONTROL/@MyBeta/MyBeta.m
a4a7f284022cconfint-fix

MyBeta.m
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