Problem with a yyaxis plot

Question

Peng Yalun 2020-4-15

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/518051-problem-with-a-yyaxis-plot

编辑： Ameer Hamza 2020-5-21

everytime I execute the yyaxis function, following error message came up.

Error: File: union.m Line: 1 Column: 1
The input character is not valid in MATLAB statements or expressions.
Error in matlab.graphics.internal.YYAxisEventManager/addAxes
Error in matlab.graphics.internal.YYAxisEventManager
Error in matlab.graphics.internal.YYAxisEventManager.registerAxes
Error in yyaxis

The double yaxis figure is created, but the program stopped. If the figure is created and the yyaxis function is re-excuted, the error message does not show.

I am stuck here in desparation...please help

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Peng Yalun 2020-5-21

在 MATLAB Online 中打开

function [timewindows] = tuningPlot(session, cellname, juiceAB)
if 0
	clear all
	session = 'B140620a';	cellname = '11';
end
disp(['   ... plotting tuning results ',session,cellname])
readsession_autosort
[timewindows colrs] = get_timewindows_JC(session, cellname);
ntwins = length(timewindows);
filename = [dirroot, session, cellname, '_tuning']; eval(['load ',filename]) %generated by tuning.mat
verbose = 1;
if 0
	clear all
	tic
	session = 'B140620a';	cellname = '11';
    verbose = 1;
end
space = 'log';
dx = .005;			% for Riemann's integral
epsilon = 0.0001;	% for integration domain (how small the distr. before we ignore)
%load data
readsession_autosort
filename = [dirroot, session, cellname, '_data']; eval(['load ',filename])
filename = [dirroot, session, cellname, '_bhvParams']; eval(['load ',filename])
npairs = size(pairs,1);
%probability ratios
prob_ratios = zeros(npairs,1);
for ipair = 1:npairs
	prob_ratios(ipair) = sessionParams.goods(pairlist(ipair,1)).probability / sessionParams.goods(pairlist(ipair,2)).probability;
end
%alloffers_num
alloffers_num = [];
for ipair = 1:npairs
	table01 = table01_all.pooldir{ipair};
	alloffers_num = [alloffers_num; table01(:,1:2)];
end
alloffers_num = unique(abs(alloffers_num),'rows');
eps = 0.001;
aux = alloffers_num + eps;
[~, jnd] = sort(aux(:,2)./aux(:,1));
alloffers_num = alloffers_num(jnd,:);
%
psyphycell = -ones(npairs, 3);
for ipair = 1:npairs
	table01 = table01_all.pooldir{ipair};
	
	%separate non-forced choice trials and forced choices
	table1mod = table01(logical(table01(:,1) & table01(:,2)),:);
	forcedAtab = table01(logical(table01(:,1) & ~table01(:,2)),:);
	forcedBtab = table01(logical(~table01(:,1) & table01(:,2)),:);
	nfA = size(forcedAtab,1);
	nfB = size(forcedBtab,1);
	
	%tuningy
	xx = table1mod(:,2)./table1mod(:,1);
	if		isequal(space,'linear') 
	elseif	isequal(space,'log') 
		xx = log(xx);	
	end
	yy = table1mod(:,3);
	
	g = fittype('normcdf(x,x0,w)','coeff',{'x0','w'});	
	[fittedmodel,goodness] = fit(xx, yy, g, ...
        'startpoint',[0 1], 'lower',[-Inf 0], 'upper',[Inf Inf]);
	coefit = [fittedmodel.x0, fittedmodel.w];
    
	%find the end of integration domain, imposing value distr. < epsilon
	leftlim = min(xx);
	while normpdf(leftlim,coefit(1),coefit(2))>epsilon
		leftlim = leftlim-dx;
	end
	rightlim = max(xx);
	while normpdf(rightlim,coefit(1),coefit(2))>epsilon
		rightlim = rightlim+dx;
	end
	
	%compute relvalue (NB: in log space, it is not just the center of the value distrib.)
	if	isequal(space,'linear')
		relvalue = fittedmodel.x0; 
		width = fittedmodel.w;
	elseif	isequal(space,'log')
		relvalue = exp(fittedmodel.x0);
		width = exp(fittedmodel.w);
	end
	Rsq = goodness.adjrsquare;
	%extract tuning results
    
    tuningWindowInd = struct2cell(tuning.AB.neuract.byoffertype);
    tuningWindow = tuningWindowInd{:};
    %tuningX = find(tuningWindow(:,3) == 1 & tuningWindow(:,6)>10);
    tuningX = tuningWindow(:,3);
   % tuningY = find(tuningWindow(:,3) == -1 & tuningWindow(:,6)>10);
    tuningY = tuningWindow(:,4);
    
    tuner(1,:) = tuningX;
    tuner(2,:) = tuningY;
    
	%take care of outliers
	if (isequal('space','log') && confinterval(2)>5) || (isequal('space','linear') && confinterval(2)>100) 
		confinterval(2) = NaN; 
		disp(['manually corrected confinterval']); 
	end
	psyphycell(ipair,:) = [fittedmodel.x0, fittedmodel.w, Rsq];
	
	%this should be made part of the function plot_sigmoid
	if verbose
		colrs = [0 0 0; ones(npairs,1)*[0 0 1]];
		%initialize figures
		
        %if ipair==1
	%		hf = figure; set(gcf, 'position',[650 620 425 350], 'PaperPositionMode','auto')
    %      end
        
        orient landscape
        set(gcf,'position',[200 200 960 720]);
        hold on        
        
        warning off;
        
        axis square;
        yyaxis left;
       %% %plot choice pattern + forced choices
		plot(xx,yy,'o','color',colrs(1,:),'markersize',8,'markerfacecolor',colrs(1,:))
        hold on
		xx_forcedA = min(xx)-log(2)*[1:nfA];	xx_forcedA = sort(xx_forcedA)';
		xx_forcedB = max(xx)+log(2)*[1:nfB];	xx_forcedB = sort(xx_forcedB)';
		plot(xx_forcedA,zeros(1,nfA),'o','color',colrs(1,:),'markersize',8,'markerfacecolor',colrs(1,:))
		plot(xx_forcedB, ones(1,nfB),'o','color',colrs(1,:),'markersize',8,'markerfacecolor',colrs(1,:))
		ylabel('Percent choosing A')
        set(gca,'ytick',[0:.25:1],'yticklabel',[0:25:100])
        
        %
        yyaxis right
        %plot tuning curve
        plot(xx(1:length(tuner(juiceAB,2:(end-1)))),tuner(juiceAB,2:end-1),'bo-')
        hold on
        %plot(xx((end+1-length(tuningY(1:end-1))):end),tuningY(1:end-1),'bd-')
        plot(xx_forcedA,tuner(juiceAB,1),'bo')
        plot(xx_forcedB,tuner(juiceAB,end),'bo')
		%cosmetics
		set(gca,'xlim',[min(xx)-1.5*log(2) max(xx)+1.5*log(2)])
        set(gca,'ylim',[min(tuner(juiceAB,:))-1.5*log(2) max(tuner(juiceAB,:))+1.5*log(2)])
        ylabel('Firing Rate');
        
		[~,ind,~] = unique(xx);	%remove doubles in xx
		xxx = xx(ind);
		%
		xlab = [];		%xlabels
		for ifA = 1:nfA
			xlab{ifA} = [num2str(forcedAtab(nfA-ifA+1,2)),':',num2str(forcedAtab(nfA-ifA+1,1))];
		end
		for i = 1:size(xxx,1)
			xlab{nfA+i} = [num2str(table1mod(ind(i),2)),':',num2str(table1mod(ind(i),1))];
		end
		for ifB = 1:nfB
			xlab{nfA+i+ifB} = [num2str(forcedBtab(nfB-ifB+1,2)),':',num2str(forcedBtab(nfB-ifB+1,1))];
		end
		%
		%add forced choices
		xxx = [xx_forcedA;xxx;xx_forcedB];
		set(gca,'xtick',xxx,'xticklabel',xlab)
        %xticklabel_rotate([],90,[]);
		
% 		%
% 		text(min(x)-.5,.925,['\mu = ',	sprintf('%1.3g',relvalue)],'fontsize',9)
% 		text(min(x)-.5,.855,['\sigma = ',sprintf('%1.3g',width)],	'fontsize',9)
		%
		%mark cellname
		if ipair == npairs
			axes('position',[.1 .925 .5 .015])
			text(0,3,['  session: ',session,' sigmoid fit (',space,' space)'], ...
				'fontname','timesnewroman','fontsize', 8)
			axis off
			set(gcf,'PaperPositionMode','auto')
		end
		if (ipair==3) 
            set(gcf,'position',[200 600 1200 350]); 
        end
        
	end %if verbose
    
end
        

Peng Yalun 2020-5-21

I only called clear all when verbose = 0, but as you see the "clear all" code is never executed.

However I still delete these and the error persists....

Thank you though

Ameer Hamza 2020-5-21

编辑：Ameer Hamza 2020-5-21

在 MATLAB Online 中打开

Can you show the output of following statement after running in command window?

which union

It seems that the MATLAB files somehow got messed up. You may need to uninstall and reinstall MATLAB completely. Can you tell which MATLAB release are you using?

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Problem with a yyaxis plot

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Problem with a yyaxis plot

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