			classdef MyFit < handle
			properties (Access=public)
			Data;
			init_params=[];
			scale_init=[];
			lim_lower;
			lim_upper;
			enable_plot;
			plot_handle;
			save_name;
			save_dir;
			end

			properties (GetAccess=public, SetAccess=private)
			Fit;
			Gui;
			Fitdata;
			FitStruct;
			coeffs;
			fit_name='Linear'
			end

			properties (Access=private)
			Parser;
			enable_gui=1;
			hline_init;
			end

			properties (Dependent=true)
			fit_function;
			fit_tex;
			fit_params;
			fit_param_names;
			valid_fit_names;
			n_params;
			scaled_params;
			init_param_fun;
			x_vec;
			end

			events
			NewFit;
			NewInitVal;
			end

			%%Public methods
			methods (Access=public)
			%Constructor function
			function this=MyFit(varargin)
			createFitStruct(this);
			createParser(this);
			parse(this.Parser,varargin{:});
			parseInputs(this);

			if ismember('Data',this.Parser.UsingDefaults) &&...
			~ismember('x',this.Parser.UsingDefaults) &&...
			~ismember('y',this.Parser.UsingDefaults)

			this.Data.x=this.Parser.Results.x;
			this.Data.y=this.Parser.Results.y;
			end

			%Sets the scale_init to 1, this is used for the GUI.
			this.scale_init=ones(1,this.n_params);
			this.init_params=ones(1,this.n_params);

			if this.enable_gui; createGui(this); end

			%If the data is appropriate, generates initial
			%parameters
			if validateData(this); genInitParams(this); end
			end

			%Deletion function of object
			function delete(this)
			if this.enable_gui
			%Avoids loops
			set(this.Gui.Window,'CloseRequestFcn','');
			%Deletes the figure
			delete(this.Gui.Window);
			%Removes the figure handle to prevent memory leaks
			this.Gui=[];
			end
			if ~isempty(this.hline_init); delete(this.hline_init); end
			if ~isempty(this.Fit.hlines); delete(this.Fit.hlines{:}); end
			end
			%Close figure callback simply calls delete function for class
			function closeFigure(this,~,~)
			delete(this);
			end

			%Fits the trace using currently set parameters, depending on the
			%model.
			function fitTrace(this)
			this.Fit.x=this.x_vec;
			switch this.fit_name
			case 'Linear'
			%Fits polynomial of order 1
			this.coeffs=polyfit(this.Data.x,this.Data.y,1);
			this.Fit.y=polyval(this.coeffs,this.Fit.x);
			case 'Quadratic'
			%Fits polynomial of order 2
			this.coeffs=polyfit(this.Data.x,this.Data.y,2);
			this.Fit.y=polyval(this.coeffs,this.Fit.x);
			case {'Exponential','Gaussian','Lorentzian',...
			'DoubleLorentzian'}
			doFit(this);
			otherwise
			error('Selected fit is invalid');
			end
			%Sets the new initial parameters to be the fitted parameters
			this.init_params=this.coeffs;
			%Resets the scale variables for the GUI
			this.scale_init=ones(1,this.n_params);
			%Updates the gui if it is enabled
			if this.enable_gui; updateGui(this); end
			%Plots the fit if the flag is on
			if this.enable_plot; plotFit(this); end
			%Triggers new fit event
			triggerNewFit(this);
			end

			%% Callbacks
			%Save function callback
			function saveCallback(this,~,~)
			assert(~isempty(this.save_dir),'Save directory is not specified');
			assert(ischar(this.save_dir),...
			['Save directory is not specified.',...
			' Should be of type char but is %s.'], ...
			class(this.save_dir))
			try
			this.Fit.save('name',this.save_name,...
			'save_dir',this.save_dir)
			catch
			error(['Attempted to save to directory %s',...
			' with file name %s, but failed'],this.save_dir,...
			this.save_name);
			end
			end
			%Callback functions for sliders in GUI. Uses param_ind to find out
			%which slider the call is coming from, this was implemented to
			%speed up the callback.
			function sliderCallback(this, param_ind, hObject, ~)
			%Gets the value from the slider
			scale=get(hObject,'Value');
			%Updates the scale with a new value
			this.scale_init(param_ind)=10^((scale-50)/50);
			%Updates the edit box with the new value from the slider
			set(this.Gui.(sprintf('Edit_%s',this.fit_params{param_ind})),...
			'String',sprintf('%3.3e',this.scaled_params(param_ind)));
			if this.enable_plot; plotInitFun(this); end
			end

			%Callback function for edit boxes in GUI
			function editCallback(this, hObject, ~)
			init_param=str2double(get(hObject,'String'));
			tag=get(hObject,'Tag');
			%Finds the index where the fit_param name begins (convention is
			%after the underscore)
			fit_param=tag((strfind(tag,'_')+1):end);
			param_ind=strcmp(fit_param,this.fit_params);
			%Updates the slider to be such that the scaling is 1
			set(this.Gui.(sprintf('Slider_%s',fit_param)),...
			'Value',50);
			%Updates the correct initial parameter
			this.init_params(param_ind)=init_param;
			if this.enable_plot; plotInitFun(this); end
			%Triggers event for new init values
			triggerNewInitVal(this);
			end

			%Callback function for analyze button in GUI. Checks if the data is
			%ready for fitting.
			function analyzeCallback(this, ~, ~)
			assert(validateData(this),...
			['The length of x is %d and the length of y is',...
			' %d. The lengths must be equal and greater than ',...
			'the number of fit parameters to perform a fit'],...
			length(this.Data.x),length(this.Data.y))
			fitTrace(this);
			end

			%Callback for clearing the fits on the axis.
			function clearFitCallback(this,~,~)
			clearFit(this);
			end

			%Callback function for generate init parameters button. Updates GUI
			%afterwards
			function initParamCallback(this,~,~)
			genInitParams(this);
			updateGui(this);
			end

			%Generates model-dependent initial parameters, lower and upper
			%boundaries.
			function genInitParams(this)
			assert(validateData(this), ['The data must be vectors of',...
			' equal length greater than the number of fit parameters.',...
			' Currently the number of fit parameters is %d, the',...
			' length of x is %d and the length of y is %d'],...
			this.n_params,length(this.Data.x),length(this.Data.y));
			%Cell for putting parameters in to be interpreted in the
			%parser. Element 1 contains the init params, Element 2 contains
			%the lower limits and Element 3 contains the upper limits.
			params={};

			switch this.fit_name
			case 'Exponential'
			[params{1},params{2},params{3}]=...
			initParamExponential(this.Data.x,this.Data.y);
			case 'Gaussian'
			[params{1},params{2},params{3}]=...
			initParamGaussian(this.Data.x,this.Data.y);
			case 'Lorentzian'
			[params{1},params{2},params{3}]=...
			initParamLorentzian(this.Data.x,this.Data.y);
			case 'DoubleLorentzian'
			[params{1},params{2},params{3}]=...
			initParamDblLorentzian(this.Data.x,this.Data.y);
			end

			%Validates the initial parameters
			p=createFitParser(this.n_params);
			parse(p,params{:});

			%Loads the parsed results into the class variables
			this.init_params=p.Results.init_params;
			this.lim_lower=p.Results.lower;
			this.lim_upper=p.Results.upper;

			%Plots the fit function with the new initial parameters
			if this.enable_gui; plotInitFun(this); end
			end

			%Plots the trace contained in the Fit MyTrace object.
			function plotFit(this,varargin)
			this.Fit.plotTrace(this.plot_handle,varargin{:});
			end

			%Clears the plots
			function clearFit(this)
			cellfun(@(x) delete(x), this.Fit.hlines);
			delete(this.hline_init);
			this.hline_init=[];
			this.Fit.hlines={};
			end

			%Function for plotting fit model with current initial parameters.
			function plotInitFun(this)
			%Substantially faster than any alternative - generating
			%anonymous functions is very cpu intensive.

			input_cell=num2cell(this.scaled_params);
			y_vec=feval(this.FitStruct.(this.fit_name).anon_fit_fun,...
			this.x_vec,input_cell{:});
			if isempty(this.hline_init)
			this.hline_init=plot(this.plot_handle,this.x_vec,y_vec);
			else
			set(this.hline_init,'XData',this.x_vec,'YData',y_vec);
			end
			end
			end

			methods(Access=private)
			%Creates the GUI of MyFit, in separate file.
			createGui(this);

			%Creates parser for constructor
			function createParser(this)
			p=inputParser;
			addParameter(p,'fit_name','Linear',@ischar)
			addParameter(p,'Data',MyTrace());
			addParameter(p,'Fit',MyTrace());
			addParameter(p,'x',[]);
			addParameter(p,'y',[]);
			addParameter(p,'enable_gui',1);
			addParameter(p,'enable_plot',0);
			addParameter(p,'plot_handle',[]);
			addParameter(p,'save_dir',[]);
			addParameter(p,'save_name',[]);
			this.Parser=p;
			end

			%Sets the class variables to the inputs from the inputParser.
			function parseInputs(this)
			for i=1:length(this.Parser.Parameters)
			%Takes the value from the inputParser to the appropriate
			%property.
			if isprop(this,this.Parser.Parameters{i})
			this.(this.Parser.Parameters{i})=...
			this.Parser.Results.(this.Parser.Parameters{i});
			end
			end
			end

			%Does the fit with the currently set parameters
			function doFit(this)
			%Fits with the below properties. Chosen for maximum accuracy.
			this.Fitdata=fit(this.Data.x,this.Data.y,this.fit_function,...
			'Lower',this.lim_lower,'Upper',this.lim_upper,...
			'StartPoint',this.init_params, ....
			'MaxFunEvals',2000,'MaxIter',2000,'TolFun',1e-9);
			%Puts the y values of the fit into the struct.
			this.Fit.y=this.Fitdata(this.Fit.x);
			%Puts the coeffs into the class variable.
			this.coeffs=coeffvalues(this.Fitdata);
			end

			%Triggers the NewFit event such that other objects can use this to
			%e.g. plot new fits
			function triggerNewFit(this)
			notify(this,'NewFit');
			end

			function triggerNewInitVal(this)
			notify(this,'NewInitVal');
			end

			%Creates the struct used to get all things relevant to the fit
			%model
			function createFitStruct(this)
			%Adds fits
			addFit(this,'Linear','a*x+b','$$ax+b$$',{'a','b'},...
			{'Gradient','Offset'})
			addFit(this,'Quadratic','ax^2+bx+c','$$ax^2+bx+c$$',...
			{'a','b','c'},{'Quadratic coeff.','Linear coeff.','Offset'});
			addFit(this,'Gaussian','a*exp(-((x-c)/b)^2/2)+d',...
			'$$ae^{-\frac{(x-c)^2}{2b^2}}+d$$',{'a','b','c','d'},...
			{'Amplitude','Width','Center','Offset'});
			addFit(this,'Lorentzian','1/piab/2/((x-c)^2+(b/2)^2)+d',...
			'$$\frac{a}{\pi}\frac{b/2}{(x-c)^2+(b/2)^2}+d$$',{'a','b','c','d'},...
			{'Amplitude','Width','Center','Offset'});
			addFit(this,'Exponential','aexp(bx)+c',...
			'$$ae^{bx}+c$$',{'a','b','c'},...
			{'Amplitude','Rate','Offset'});
			addFit(this,'DoubleLorentzian',...
			'1/pib/2a/((x-c)^2+(b/2)^2)+1/pie/2d/((x-f)^2+(e/2)^2)+g',...
			'$$\frac{a}{(x-c)^2+(b/2)^2}+\frac{d}{(x-f)^2+(e/2)^2}+g$$',...
			{'a','b','c','d','e','f','g'},...
			{'Amplitude 1','Width 1','Center 1','Amplitude 2',...
			'Width 2','Center 2','Offset'});
			end

			%Updates the GUI if the edit or slider boxes are changed from
			%elsewhere.
			function updateGui(this)
			%Converts the scale variable to the value between 0 and 100
			%necessary for the slider
			slider_vals=50*log10(this.scale_init)+50;
			for i=1:this.n_params
			set(this.Gui.(sprintf('Edit_%s',this.fit_params{i})),...
			'String',sprintf('%3.3e',this.scaled_params(i)));
			set(this.Gui.(sprintf('Slider_%s',this.fit_params{i})),...
			'Value',slider_vals(i));
			end
			end

			%Adds a fit to the list of fits
			function addFit(this,fit_name,fit_function,fit_tex,fit_params,...
			fit_param_names)
			this.FitStruct.(fit_name).fit_function=fit_function;
			this.FitStruct.(fit_name).fit_tex=fit_tex;
			this.FitStruct.(fit_name).fit_params=fit_params;
			this.FitStruct.(fit_name).fit_param_names=fit_param_names;
			%Generates the anonymous fit function from the above
			args=['@(x,', strjoin(fit_params,','),')'];
			anon_fit_fun=str2func(vectorize([args,fit_function]));
			this.FitStruct.(fit_name).anon_fit_fun=anon_fit_fun;
			end

			%Checks if the class is ready to perform a fit
			function bool=validateData(this)
			bool=~isempty(this.Data.x) && ~isempty(this.Data.y) && ...
			length(this.Data.x)==length(this.Data.y) && ...
			length(this.Data.x)>=this.n_params;
			end
			end

			%% Get and set functions
			methods
			%% Set functions

			%Set function for fit_name.
			function set.fit_name(this,fit_name)
			assert(ischar(fit_name),'The fit name must be a string');
			%Capitalizes the first letter
			fit_name=[upper(fit_name(1)),lower(fit_name(2:end))];
			%Checks it is a valid fit name
			ind=strcmpi(fit_name,this.valid_fit_names);%#ok<MCSUP>
			assert(any(ind),'%s is not a supported fit name',fit_name);

			this.fit_name=this.valid_fit_names{ind}; %#ok<MCSUP>
			end

			%% Get functions for dependent variables

			%Generates the valid fit names
			function valid_fit_names=get.valid_fit_names(this)
			valid_fit_names=fieldnames(this.FitStruct);
			end

			%Grabs the correct fit function from FitStruct
			function fit_function=get.fit_function(this)
			fit_function=this.FitStruct.(this.fit_name).fit_function;
			end

			%Grabs the correct tex string from FitStruct
			function fit_tex=get.fit_tex(this)
			fit_tex=this.FitStruct.(this.fit_name).fit_tex;
			end

			%Grabs the correct fit parameters from FitStruct
			function fit_params=get.fit_params(this)
			fit_params=this.FitStruct.(this.fit_name).fit_params;
			end

			%Grabs the correct fit parameter names from FitStruct
			function fit_param_names=get.fit_param_names(this)
			fit_param_names=this.FitStruct.(this.fit_name).fit_param_names;
			end

			%Calculates the scaled initial parameters
			function scaled_params=get.scaled_params(this)
			scaled_params=this.scale_init.*this.init_params;
			end

			%Calculates the number of parameters in the fit function
			function n_params=get.n_params(this)
			n_params=length(this.fit_params);
			end

			%Generates a vector of x values for plotting
			function x_vec=get.x_vec(this)
			x_vec=linspace(min(this.Data.x),max(this.Data.x),1000);
			end
			end
			end

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