Diffusion Instrument Control (TekRSA-Freq-vs-Time) Browse

MyFit.m
a31264257c12TekRSA-Freq-vs-Time

MyFit.m
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			% Class that implements fitting routines with GUI capabilities.

			classdef MyFit < dynamicprops & MyAnalysisRoutine & ...
			matlab.mixin.CustomDisplay

			properties (Access = public)

			% MyTrace object contains the data to be fitted to
			Data MyTrace

			lim_lower % Lower limits for fit parameters
			lim_upper % Upper limits for fit parameters

			% If enabled, plots fit curve in the Axes every time the parameter
			% values are updated
			enable_plot

			fit_color = 'black' % Color of the fit line
			fit_length = 1e3 % Number of points in the fit trace
			end

			properties (GetAccess = public, SetAccess = protected)
			Axes % The handle which the fit is plotted in
			Fit % MyTrace object containing the fit
			Gui = struct() % Handles of GUI elements

			% Array of cursors with length=2 for the selection of fitting range
			RangeCursors MyCursor

			% Output structures from fit() function:
			FitResult cfit
			Gof struct
			FitInfo struct

			param_vals % Numeric values of fit parameters

			fit_name
			fit_tex % tex representation of the fit formula
			fit_function % fit formula as character string
			fit_params % character names of fit parameters in fit_function
			fit_param_names % long informative names of fit parameters
			anon_fit_fun % fit expression represented by anonimous function

			% Additional parameters that are calculated from the fit parameters
			% or inputed externally. Properties of user parameters including
			% long name and write attribute
			UserParamList = struct()
			end

			properties (Dependent = true, GetAccess = public)
			n_params

			% Indices of data points selected for fitting
			data_selection

			% Enable cursors for the selection of fit range
			enable_range_cursors
			end

			properties (Access = protected)
			enable_gui = 1

			% Vectors for varying the range of the sliders in GUI
			slider_vecs
			end

			% Events for communicating with outside entities
			events
			NewFit % Triggered any time fitting is performed
			end

			methods (Access = public)
			function this = MyFit(varargin)

			% Parse the arguments supplied to the constructor
			p = inputParser();
			addParameter(p, 'fit_name', '')
			addParameter(p, 'fit_function', 'x')
			addParameter(p, 'fit_tex', '')
			addParameter(p, 'fit_params', {})
			addParameter(p, 'fit_param_names', {})
			addParameter(p, 'Data', MyTrace());
			addParameter(p, 'x', []);
			addParameter(p, 'y', []);
			addParameter(p, 'Axes', [], @isaxes);
			addParameter(p, 'enable_gui', true);
			addParameter(p, 'enable_plot', true);
			addParameter(p, 'enable_range_cursors', false)

			% The parameters below are only active when GUI is enabled

			% If true, adds save trace panel to the fit gui
			addParameter(p,'save_panel',false,@islogical);

			addParameter(p,'base_dir', '');
			addParameter(p,'session_name','placeholder');
			addParameter(p,'file_name','placeholder');

			parse(p, varargin{:});

			for i=1:length(p.Parameters)

			% Takes the value from the inputParser to the appropriate
			% property.
			if isprop(this, p.Parameters{i})
			this.(p.Parameters{i}) = p.Results.(p.Parameters{i});
			end
			end

			this.Fit = MyTrace();

			%Generates the anonymous fit function from the input fit
			%function. This is used for fast plotting of the initial
			%values.
			args=['@(', strjoin([{'x'}, this.fit_params], ','),')'];
			this.anon_fit_fun=...
			str2func(vectorize([args,this.fit_function]));

			%Sets dummy values for the GUI
			this.param_vals=zeros(1,this.n_params);
			this.lim_lower=-Inf(1,this.n_params);
			this.lim_upper=Inf(1,this.n_params);

			%Allows us to load either x/y data or a MyTrace object directly
			if ismember('Data',p.UsingDefaults) &&...
			~ismember('x',p.UsingDefaults) &&...
			~ismember('y',p.UsingDefaults)

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

			%Creates the structure that contains variables for calibration
			%of fit results
			createUserParamList(this);

			%Creates the gui if the flag is enabled. This function is in a
			%separate file.
			if this.enable_gui
			createGui(this, 'save_panel', p.Results.save_panel)

			%Generates the slider lookup table
			genSliderVecs(this);

			if isempty(p.Results.base_dir)
			try
			bd = getLocalSettings('measurement_base_dir');
			catch ME
			warning(ME.message)
			bd = '';
			end
			else
			bd = '';
			end

			this.Gui.BaseDir.String = bd;
			this.Gui.SessionName.String = p.Results.session_name;
			this.Gui.FileName.String = p.Results.file_name;
			end

			if ~isempty(this.Axes)

			% Add two vertical cursors to the axes
			xlim = this.Axes.XLim;
			x1 = xlim(1)+0.1*(xlim(2)-xlim(1));
			x2 = xlim(2)-0.1*(xlim(2)-xlim(1));

			this.RangeCursors = ...
			[MyCursor(this.Axes, x1, 'orientation', 'vertical', ...
			'Label','Fit range 1', 'Color', [0.6, 0, 0]),...
			MyCursor(this.Axes, x2, 'orientation', 'vertical', ...
			'Label','Fit range 2', 'Color', [0.6, 0, 0])];

			% Enabling/disabling of the cursors by setting the class
			% property can be done only after the cursors are
			% initialized
			this.enable_range_cursors = p.Results.enable_range_cursors;
			end

			%If data was supplied, generates initial fit parameters
			if ~isDataEmpty(this.Data)
			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 ismethod(this.Fit, 'delete')

			% Delete the fit trace, in particular, in order to remove
			% the fit curve from the axes
			delete(this.Fit);
			end

			if ~isempty(this.RangeCursors)
			delete(this.RangeCursors);
			end
			end

			%Saves the metadata
			function saveParams(this,varargin)
			p=inputParser;
			addParameter(p,'save_user_params',true);
			addParameter(p,'save_gof',true);
			parse(p,varargin{:});
			%Flags for saving the user parameters or goodness of fit
			save_user_params=p.Results.save_user_params;
			save_gof=p.Results.save_gof;

			assert(~isempty(this.param_vals) && ...
			length(this.param_vals)==this.n_params,...
			['The number of calculated coefficients (%i) is not',...
			' equal to the number of parameters (%i).', ...
			' Perform a fit before trying to save parameters.'],...
			length(this.param_vals),this.n_params);

			%Creates combined strings of form: Linewidth (b), where
			%Linewidth is the parameter name and b is the parameter tag
			headers=cellfun(@(x,y) sprintf('%s (%s)',x,y),...
			this.fit_param_names, this.fit_params,'UniformOutput',0);
			save_data=this.param_vals;

			if save_user_params
			%Creates headers for the user fields
			user_field_headers=cellfun(@(x,y) ...
			sprintf('%s. %s',this.UserGui.Fields.(x).parent,y),...
			this.user_field_tags,this.user_field_names,...
			'UniformOutput',0)';
			%Appends the user headers and data to the save data
			headers=[headers, user_field_headers];
			save_data=[save_data,this.user_field_vals']
			end

			if save_gof
			%Appends GOF headers and data to the save data
			headers=[headers,fieldnames(this.Gof)'];
			save_data=[save_data,struct2array(this.Gof)];
			end

			%Find out at the end how many columns we have
			n_columns=length(headers);

			%Sets the column width. Pads 2 for legibility.
			col_width=cellfun(@(x) length(x), headers)+2;
			%Min column width of 24
			col_width(col_width<24)=24;

			%Create the right directories
			if ~exist(this.base_dir,'dir')
			mkdir(this.base_dir)
			end

			if ~exist(this.save_path,'dir')
			mkdir(this.save_path)
			end

			fullpath=[this.save_path,this.filename,'.txt'];

			%We automatically append to the file if it already exists,
			%otherwise create a new file
			if exist(fullpath,'file')
			fileID=fopen(fullpath,'a');
			fprintf('Appending data to %s \n',fullpath);
			else
			fileID=fopen(fullpath,'w');
			pre_fmt_str=repmat('%%%is\\t',1,n_columns);
			fmt_str=sprintf([pre_fmt_str,'\r\n'],col_width);
			fprintf(fileID,fmt_str,headers{:});
			end

			pre_fmt_str_nmb=repmat('%%%i.15e\\t',1,n_columns);
			nmb_fmt_str=sprintf([pre_fmt_str_nmb,'\r\n'],col_width);
			fprintf(fileID,nmb_fmt_str,save_data);

			fclose(fileID);
			end

			%We can load a fit from a file with appropriately formatted columns
			%We simply load the coefficients from the file into the fit.
			function loadFit(this,fullfilename,varargin)
			p=inputParser
			addParameter(p,'line_no',1);
			parse(p,varargin{:})
			n=p.Results.line_no;

			load_table=readtable(fullfilename);
			load_names=fieldnames(load_table);
			for i=1:this.n_params
			this.param_vals(i)=load_table.(load_names{i})(n);
			end
			end

			%This function is used to set the coefficients, to avoid setting it
			%to a number not equal to the number of parameters
			function setFitParams(this,param_vals)
			assert(length(param_vals)==this.n_params,...
			['The length of the coefficient vector (currently %i) ',...
			'must be equal to the number of parameters (%i)'],...
			length(this.param_vals),this.n_params)
			this.param_vals=param_vals;
			end

			%Fits the trace using currently set parameters, depending on the
			%model.
			function fitTrace(this)

			%Check the validity of data
			validateData(this);

			%Check for valid limits
			lim_check=this.lim_upper>this.lim_lower;
			assert(all(lim_check),...
			sprintf(['All upper limits must exceed lower limits. ',...
			'Check limit %i, fit parameter %s'],find(~lim_check,1),...
			this.fit_params{find(~lim_check,1)}));

			%Check the consistency of initial parameters
			assert(isnumeric(this.param_vals) && isvector(this.param_vals) && ...
			length(this.param_vals)==this.n_params, ['Starting points must be given as ' ...
			'a vector of size %d'],this.n_params);
			assert(isnumeric(this.lim_lower) && isvector(this.lim_lower) && ...
			length(this.lim_lower)==this.n_params, ['Lower limits must be given as ' ...
			'a vector of size %d'], this.n_params);
			assert(isnumeric(this.lim_upper) && isvector(this.lim_upper) && ...
			length(this.lim_upper)==this.n_params, ['Upper limits must be given as ' ...
			'a vector of size %d'], this.n_params);

			%Perform the fit with current parameters as a starting point
			ind = this.data_selection;
			this.param_vals = doFit(this, ...
			this.Data.x(ind), this.Data.y(ind), this.param_vals, ...
			this.lim_lower, this.lim_upper);

			%Calculate the fit curve
			calcFit(this);

			%Calculate user parameters that depend on the fit parameters
			calcUserParams(this);

			%Update fit metadata
			this.Fit.UserMetadata = createMetadata(this);

			%Updates the gui if it is enabled
			if this.enable_gui
			genSliderVecs(this);
			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

			%Clears the plots
			function clearFit(this)
			cellfun(@(x) delete(x), this.Fit.PlotLines);
			end

			%Plots the trace contained in the Fit MyTrace object
			function plotFit(this, varargin)
			plot(this.Fit, this.Axes, 'Color', this.fit_color, varargin{:});
			end

			%Generates model-dependent initial parameters, lower and upper
			%boundaries.
			function genInitParams(this)
			validateData(this);

			calcInitParams(this);
			calcFit(this);
			calcUserParams(this);

			%Plots the fit function with the new initial parameters
			if this.enable_plot
			plotFit(this)
			end

			%Updates the GUI and creates new lookup tables for the init
			%param sliders
			if this.enable_gui
			genSliderVecs(this);
			updateGui(this);
			end
			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

			%Triggered for transferring of the fit trace to DAQ
			function triggerNewAnalysisTrace(this)
			EventData = MyNewAnalysisTraceEvent('Trace', copy(this.Fit));
			notify(this, 'NewAnalysisTrace', EventData);
			end

			% Create metadata with all the fitting and user-defined parameters
			function Mdt = createMetadata(this)

			% Field for the fit parameters
			InfoMdt = MyMetadata('title', 'FitInfo');

			addObjProp(InfoMdt, this, 'fit_name');
			addObjProp(InfoMdt, this, 'fit_function');

			% Indicate if the parameter values were obtained manually or
			% from performing a fit
			if isempty(this.Gof)
			param_val_mode = 'manual';
			else
			param_val_mode = 'fit';
			end

			addParam(InfoMdt, 'param_val_mode', param_val_mode, ...
			'comment', ['If the parameter values were set manually '...
			'or obtained from fit']);

			% Field for the fit parameters
			ParValMdt = MyMetadata('title', 'FittingParameters');

			if ~isempty(this.Gof)

			% Add fit parameters with confidence intervals
			ci = confint(this.FitResult, 0.95);

			for i=1:length(this.fit_params)
			str = sprintf('%8.4g (%.4g, %.4g)', ...
			this.param_vals(i), ci(1,i), ci(2,i));

			addParam(ParValMdt, this.fit_params{i}, str, ...
			'comment', [this.fit_param_names{i} ...
			' (95% confidence interval)']);
			end
			else

			% Add only fit parameters
			for i=1:length(this.fit_params)
			addParam(ParValMdt, this.fit_params{i}, ...
			this.param_vals(i), 'comment', ...
			this.fit_param_names{i});
			end
			end

			user_params = fieldnames(this.UserParamList);
			if ~isempty(user_params)

			% Add a field with the user parameters
			UserParMdt = MyMetadata('title', 'UserParameters');
			for i=1:length(user_params)
			tag = user_params{i};
			addParam(UserParMdt, tag, this.(tag), ...
			'comment', this.UserParamList.(tag).title);
			end
			else
			UserParMdt = MyMetadata.empty();
			end

			if ~isempty(this.Gof)

			% Field for the goodness of fit which copies the fields of
			% corresponding structure
			GofMdt = MyMetadata('title', 'GoodnessOfFit');

			addParam(GofMdt, 'sse', this.Gof.sse, 'comment', ...
			'Sum of squares due to error');
			addParam(GofMdt, 'rsquare', this.Gof.rsquare, 'comment',...
			'R-squared (coefficient of determination)');
			addParam(GofMdt, 'dfe', this.Gof.dfe, 'comment', ...
			'Degrees of freedom in the error');
			addParam(GofMdt, 'adjrsquare', this.Gof.adjrsquare, ...
			'comment', ['Degree-of-freedom adjusted ' ...
			'coefficient of determination']);
			addParam(GofMdt, 'rmse', this.Gof.rmse, 'comment', ...
			'Root mean squared error (standard error)');
			else
			GofMdt = MyMetadata.empty();
			end

			Mdt = [InfoMdt, ParValMdt, UserParMdt, GofMdt];
			end
			end

			methods (Access = protected)

			%Creates the GUI of MyFit, in separate file.
			createGui(this, varargin);

			%Does the fit with the currently set parameters. This method is
			%often overloaded in subclasses to improve performance.
			function fitted_vals = doFit(this, x, y, init_vals, lim_lower, ...
			lim_upper)

			%Fits with the below properties. Chosen for maximum accuracy.
			Ft = fittype(this.fit_function,'coefficients',this.fit_params);
			Opts = fitoptions('Method','NonLinearLeastSquares',...
			'Lower', lim_lower,...
			'Upper', lim_upper,...
			'StartPoint', init_vals,...
			'MaxFunEvals', 2000,...
			'MaxIter', 2000,...
			'TolFun', 1e-10,...
			'TolX', 1e-10);

			[this.FitResult, this.Gof, this.FitInfo] = fit(x, y, Ft, Opts);

			%Return the coefficients
			fitted_vals = coeffvalues(this.FitResult);
			end

			%Low level function that generates initial parameters.
			%The default version of this function is not meaningful, it
			%should be overloaded in subclasses.
			function calcInitParams(this)
			this.param_vals=ones(1,this.n_params);
			this.lim_lower=-Inf(1,this.n_params);
			this.lim_upper=Inf(1,this.n_params);
			end

			% Calculate user parameters from fit parameters.
			% Dummy method that needs to be overloaded in subclasses.
			function calcUserParams(this) %#ok<MANU>
			end

			function addUserParam(this, name, varargin)

			% Process inputs
			p = inputParser();
			addRequired(p, 'name', @ischar);
			addParameter(p, 'title', '');
			addParameter(p, 'editable', @(x)assert(isequal(x, 'on') \|\| ...
			isequal(x, 'off'), ['''editable'' property must be ' ...
			'''on'' or ''off''']));
			addParameter(p, 'default', []);

			parse(p, name, varargin{:});

			% Store the information about the user parameter
			this.UserParamList.(name).title = p.Results.title;
			this.UserParamList.(name).editable = p.Results.editable;

			% Create a dynamic property for easy access
			Mp = addprop(this, name);
			this.UserParamList.(name).Metaprop = Mp;

			Mp.GetAccess = 'public';

			if ~isempty(p.Results.default)
			this.(name) = p.Results.default;
			end

			if this.UserParamList.(name).editable
			Mp.SetAccess = 'public';
			else
			Mp.SetAccess = 'private';
			end
			end

			% addUserParam statements must be contained in this function
			% overloaded in subclasses.
			function createUserParamList(this) %#ok<MANU>
			end

			function genSliderVecs(this)
			%Return values of the slider
			slider_vals=1:101;
			%Default scaling vector
			def_vec=10.^((slider_vals-51)/50);
			%Sets the cell to the default value
			for i=1:this.n_params
			this.slider_vecs{i}=def_vec*this.param_vals(i);
			set(this.Gui.(sprintf('Slider_%s', this.fit_params{i})),...
			'Value',50);
			end
			end

			%Checks if the class is ready to perform a fit
			function validateData(this)
			assert(~isempty(this.Data.x) && ~isempty(this.Data.y) && ...
			length(this.Data.x)==length(this.Data.y) && ...
			length(this.Data.x)>=this.n_params, ...
			['The data must be vectors of equal length greater ' ...
			'than the number of fit parameters.', ...
			' Currently the number of fit parameters is %i, the', ...
			' length of x is %i and the length of y is %i'], ...
			this.n_params, length(this.Data.x), length(this.Data.y));
			end

			%Calculates the trace object that represents the fitted curve
			function calcFit(this)
			xmin = this.Data.x(1);
			xmax = this.Data.x(end);

			if this.enable_range_cursors

			% If range cursors are active, restrict to the selected
			% range
			xmin = max(xmin, min(this.RangeCursors.value));
			xmax = min(xmax, max(this.RangeCursors.value));
			end

			this.Fit.x=linspace(xmin, xmax, this.fit_length);
			input_coeffs=num2cell(this.param_vals);
			this.Fit.y=this.anon_fit_fun(this.Fit.x, input_coeffs{:});
			end

			%Overload a method of matlab.mixin.CustomDisplay in order to
			%separate the display of user properties from the others.
			function PrGroups = getPropertyGroups(this)
			user_params = fieldnames(this.UserParamList);
			static_props = setdiff(properties(this), user_params);

			PrGroups = [matlab.mixin.util.PropertyGroup(static_props), ...
			matlab.mixin.util.PropertyGroup(user_params)];
			end
			end

			%Callbacks
			methods (Access = protected)

			%Callback for saving the fit trace
			function saveFitCallback(this,~,~)
			base_dir=this.Gui.BaseDir.String;
			session_name=this.Gui.SessionName.String;
			file_name=this.Gui.FileName.String;

			% Add extension to the file name if missing
			[~,~,ext]=fileparts(file_name);
			if isempty(ext) \|\| (length(ext) > 5) \|\| any(isspace(ext))
			file_name=[file_name, '.txt'];
			end

			assert(~isempty(base_dir),'Save directory is not specified');
			save_path=createSessionPath(base_dir, session_name);
			save(this.Fit, fullfile(save_path, file_name));
			end

			%Creates callback functions for sliders in GUI. Uses ind to find
			%out which slider the call is coming from. Note that this gets
			%triggered whenever the value of the slider is changed.
			function f = createSliderStateChangedCallback(this, ind)
			edit_field_name = sprintf('Edit_%s',this.fit_params{ind});

			function sliderStateChangedCallback(hObject, ~)
			%Gets the value from the slider
			val=hObject.Value;

			%Find out if the current slider value is correct for the
			%current init param value. If so, do not change anything.
			%This is required as the callback also gets called when
			%the slider values are changed programmatically
			[~, slider_ind]=...
			min(abs(this.param_vals(ind)-this.slider_vecs{ind}));

			if slider_ind~=(val+1)
			%Updates the scale with a new value from the lookup
			%table
			this.param_vals(ind)=...
			this.slider_vecs{ind}(val+1);
			%Updates the edit box with the new value from the
			%slider
			set(this.Gui.(edit_field_name),...
			'String', sprintf('%3.3e',this.param_vals(ind)));

			%Re-calculate the fit curve.
			calcFit(this);

			if this.enable_plot
			plotFit(this);
			end
			end
			end

			f = @sliderStateChangedCallback;
			end

			function f = createParamFieldEditedCallback(this, ind)
			function paramEditFieldCallback(hObject, ~)
			val=str2double(hObject.String);
			manSetParamVal(this, ind, val);
			end

			f = @paramEditFieldCallback;
			end

			function f = createSliderMouseReleasedCallback(this, ind)
			function sliderMouseReleasedCallback(hObject, ~)
			slider_ind=hObject.Value;
			val = this.slider_vecs{ind}(slider_ind+1);
			manSetParamVal(this, ind, val);
			end

			f = @sliderMouseReleasedCallback;
			end

			%Callback function for the manual update of the values of fit
			%parameters in GUI. Triggered when values in the boxes are editted
			%and when pulling a slider is over.
			function manSetParamVal(this, ind, new_val)

			%Updates the correct initial parameter
			this.param_vals(ind)=new_val;

			%Re-calculate the fit curve.
			calcFit(this);

			if this.enable_plot
			plotFit(this)
			end

			%Centers the slider
			set(this.Gui.(sprintf('Slider_%s',this.fit_params{ind})),...
			'Value',50);

			%Generate the new slider vectors
			genSliderVecs(this);

			%Reset fit structures to indicate that the current parameters
			%were set manually
			this.FitResult=cfit.empty();
			this.Gof=struct.empty();
			this.FitInfo=struct.empty();

			%Calculate user parameters
			calcUserParams(this);

			%Update fit metadata
			this.Fit.UserMetadata=createMetadata(this);
			end

			function f = createLowerLimEditCallback(this, ind)
			function lowerLimEditCallback(hObject, ~)
			this.lim_lower(ind)=str2double(hObject.String);
			end

			f = @lowerLimEditCallback;
			end

			function f = createUpperLimEditCallback(this, ind)
			function upperLimEditCallback(hObject, ~)
			this.lim_upper(ind)=str2double(hObject.String);
			end

			f = @upperLimEditCallback;
			end

			%Create a callback that is executed when an editable user parameter
			%is set in the GUI
			function f = createUserParamCallback(this, param_name)
			function userParamCallback(hObject, ~)
			this.(param_name) = str2double(hObject.String);
			calcUserParams(this);
			end

			f = @userParamCallback;
			end

			%Callback function for analyze button in GUI. Checks if the data is
			%ready for fitting.
			function analyzeCallback(this, ~, ~)
			fitTrace(this);
			end

			function acceptFitCallback(this, ~, ~)
			triggerNewAnalysisTrace(this);
			end

			function enableCursorsCallback(this, hObject, ~)
			this.enable_range_cursors = hObject.Value;
			end

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

			%Callback function for the button that generates init parameters.
			function initParamCallback(this, ~, ~)
			genInitParams(this);
			end

			%Close figure callback simply calls delete function for class
			function closeFigureCallback(this,~,~)
			delete(this);
			end
			end

			%Private methods
			methods(Access = private)

			%Creates a panel for the GUI, in separate file
			createUserControls(this, varargin);

			%Updates the GUI if the edit or slider boxes are changed from
			%elsewhere.
			function updateGui(this)
			for i=1:this.n_params
			str=this.fit_params{i};
			set(this.Gui.(sprintf('Edit_%s',str)),...
			'String',sprintf('%3.3e',this.param_vals(i)));
			set(this.Gui.(sprintf('Lim_%s_upper',str)),...
			'String',sprintf('%3.3e',this.lim_upper(i)));
			set(this.Gui.(sprintf('Lim_%s_lower',str)),...
			'String',sprintf('%3.3e',this.lim_lower(i)));
			end
			end
			end

			methods

			% Can set enable_plot to true only if Axes are present
			function set.enable_plot(this, val)
			val = logical(val);
			this.enable_plot = val & ~isempty(this.Axes); %#ok<MCSUP>
			end

			function set.enable_range_cursors(this, val)
			if ~isempty(this.RangeCursors)
			for i=1:length(this.RangeCursors)
			this.RangeCursors(i).Line.Visible = val;
			end
			end

			try
			if this.enable_gui && ...
			this.Gui.CursorsCheckbox.Value ~= val
			this.Gui.CursorsCheckbox.Value = val;
			end
			catch
			end
			end

			% Visibility of the range cursors is the reference if they are
			% enabled or not
			function val = get.enable_range_cursors(this)
			if ~isempty(this.RangeCursors)
			val = strcmpi(this.RangeCursors(1).Line.Visible, 'on');
			else
			val = false;
			end
			end

			function ind = get.data_selection(this)
			if this.enable_range_cursors
			xmin = min(this.RangeCursors.value);
			xmax = max(this.RangeCursors.value);
			ind = (this.Data.x>xmin & this.Data.x<=xmax);
			else
			ind = true(1, length(this.Data.x));
			end
			end

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

rINSTCONTROL/@MyFit/MyFit.ma31264257c12TekRSA-Freq-vs-Time

MyFit.mView Options

rINSTCONTROL/@MyFit/MyFit.m
a31264257c12TekRSA-Freq-vs-Time

MyFit.m
View Options