Merge branch 'dev'

README.md

@@ -14,8 +14,9 @@ The function has several examples and there are various visualization possibilit
 Although it's worked well for situations I've needed it, I will be happy to modify the function if users come up against problems.
 
 ## Features
+- Directly plot LinearModel objects from `fitlm` [NEW]
 - Easily mix a variety of plot styles on one figure
-- Easy post-hod modification of plot parameters via returned function handles
+- Easy post-hoc modification of plot parameters via returned function handles
 - Statistics (mean, SD, etc) optionally returned 
 - Optional plotting of median in addition to mean 
 - Option to plot either a 95% confidence interval for the mean or a 95% t-interval
@@ -34,3 +35,23 @@ A: Most modifications can be done using the function handles. See the function h
 
 ## Installation
 Add the ``code`` directory to your MATLAB path. Does not rely on any toolboxes. 
+
+
+## Changelog
+
+**v1.2 (28-08-16)**
+
+* Add median to plots
+* Select SEM or t-interval from command line
+* Return stats as second output
+* Move to parameter/value pairs by default and warn user if they aren't doing this. 
+* Add unit tests.
+
+**v1.3 (11-09-16)**
+
+* Remove legacy calls
+* Allow passing of a table, which automatically labels the axes
+* Pass a LinearModel, which automatically labels the axes and uses the model errors
+* Examples are now in separate files and doc text is neater
+* User can now optionally do `notBoxPlot(y,'jitter',0.5)` instead of `notBoxPlot(y,[],'jitter',0.5)` 
+

code/+NBP/SEM_calc.m

@@ -1,7 +1,7 @@
 function sem=SEM_calc(vect, CI)
 % SEM_calc - standard error of the mean, confidence interval
 %
-% function sem=SEM_calc(vect, CI) 
+% function sem = NBP.SEM_calc(vect, CI) 
 %
 % Purpose
 % Calculate the standard error the mean to a given confidence
@@ -31,8 +31,10 @@
 % plot([mean(r)-S,mean(r)+S], [mean(ylim),mean(ylim)],'r-')
 % hold off
 %
+%
 % Rob Campbell 
 %
+%
 % Also see - tInterval_Calc, norminv
 
 narginchk(1,2)
@@ -51,6 +53,3 @@
 
 sem = ( (nanstd(vect)) ./ sqrt(sum(~isnan(vect))) ) * stdCI ;    
 
-
-
-

code/+NBP/jitterExamples.m

@@ -0,0 +1,30 @@
+function jitterExamples
+
+% 
+% % Jitter examples 
+% % default jitter is 0.3
+%
+% clf
+%
+% R = randn(20,5);
+%
+% subplot(2,1,1)
+% notBoxPlot(R,'jitter',0.15)
+%
+% subplot(2,1,2)
+% notBoxPlot(R,'jitter',0.75);
+%
+
+help(['NBP.',mfilename])
+
+clf
+
+R = randn(20,5);
+
+subplot(2,1,1)
+notBoxPlot(R,'jitter',0.15)
+
+subplot(2,1,2)
+notBoxPlot(R,'jitter',0.75);
+
+

code/+NBP/lineExamples.m

@@ -0,0 +1,36 @@
+function lineExamples
+
+% % Mixing lines and areas [note that the way notBoxPlot
+% % sets the x axis limits can cause problems when combining plots
+% % this way]
+%
+% clf
+%
+% subplot(1,2,1)
+% h=notBoxPlot(randn(10,1)+4,5,'style','line');
+% set(h.data,'color','m')  
+% h=notBoxPlot(randn(50,10));
+% set(h(5).data,'color','m')
+%
+% subplot(1,2,2)
+% y=randn(50,1);
+% clf
+% notBoxPlot(y,1,'style','sdline')
+% notBoxPlot(y,2)   
+% xlim([0,3])
+
+help(['NBP.',mfilename])
+
+clf
+
+subplot(1,2,1)
+h=notBoxPlot(randn(10,1)+4,5,'style','line');
+set(h.data,'color','m')  
+h=notBoxPlot(randn(50,10));
+set(h(5).data,'color','m')
+
+subplot(1,2,2)
+y=randn(50,1);
+notBoxPlot(y,1,'style','sdline')
+notBoxPlot(y,2)   
+xlim([0,3])

code/+NBP/linearModelExamples.m

@@ -0,0 +1,105 @@
+function linearModelExamples
+
+% % Linear model call format
+%
+%
+% % Build data
+% rng(555), 
+% n=10;
+% R=rand(n,5);
+% R(:,3)=R(:,3)+1;
+% 
+% X=repmat(1:5,size(R,1),1);
+% lemmings=R(:);
+% group=X(:);
+%
+% clf
+%
+% % We can call notBoxPlot with just X and Y
+% subplot(2,2,1)
+% notBoxPlot(lemmings,group,'jitter',0.75)
+% grid on, box on
+% ylim([-0.5,2.2])
+% title('two vectors')
+%
+% % We can create a table and get the same plot plus the variable names on the axes
+% subplot(2,2,2)
+% T = table(lemmings,group);
+% notBoxPlot(T,'jitter',0.75)
+% grid on, box on
+% ylim([-0.5,2.2])
+% title('table')
+%
+% % We can fit a linear model do the data and plot this
+% subplot(2,2,3)
+% group = categorical(group);
+% T = table(lemmings,group);
+% M = fitlm(T,'lemmings ~ group');
+% notBoxPlot(M,'jitter',0.75)
+% grid on, box on
+% ylim([-0.5,2.2])
+% title('model')
+%
+% % Increase variance of one group
+% subplot(2,2,4)
+% lemmings(end-n+1:end) = lemmings(end-n+1:end)*1.75;
+% T = table(lemmings,group);
+% M = fitlm(T,'lemmings ~ group');
+% notBoxPlot(M,'jitter',0.75)
+% grid on, box on
+% ylim([-0.5,2.2])
+% title('increased variance in group 5')
+
+help(['NBP.',mfilename])
+
+
+
+
+% Build data
+rng(555), 
+n=10;
+R=rand(n,5);
+R(:,3)=R(:,3)+1;
+
+X=repmat(1:5,size(R,1),1);
+lemmings=R(:);
+group=X(:);
+
+
+clf
+
+% We can call notBoxPlot with just X and Y
+subplot(2,2,1)
+notBoxPlot(lemmings,group,'jitter',0.75)
+grid on, box on
+ylim([-0.5,2.2])
+title('two vectors')
+
+% We can create a table and get the same plot plus the variable names on the axes
+subplot(2,2,2)
+T = table(lemmings,group);
+notBoxPlot(T,'jitter',0.75)
+grid on, box on
+ylim([-0.5,2.2])
+title('table')
+
+% We can fit a linear model do the data and plot this
+subplot(2,2,3)
+group = categorical(group);
+T = table(lemmings,group);
+M = fitlm(T,'lemmings ~ group');
+notBoxPlot(M,'jitter',0.75)
+grid on, box on
+ylim([-0.5,2.2])
+title('model')
+
+
+% Increase variance of one group
+subplot(2,2,4)
+lemmings(end-n+1:end) = lemmings(end-n+1:end)*1.75;
+T = table(lemmings,group);
+M = fitlm(T,'lemmings ~ group');
+notBoxPlot(M,'jitter',0.75)
+grid on, box on
+ylim([-0.5,2.2])
+title('increased variance in group 5')

code/+NBP/example.m → code/+NBP/showCase.m

@@ -1,13 +1,28 @@
-function example
-% Pretty example use of notBoxPlot
-
-disp('Running example')
+function showCase
+% Example showing a variety of effects possible with notBoxPlot
+%
+% function NBP.showCase
+%
+% 
+% Purpose
+% Showcase notBoxPlot
+%
+%
+% No inputs or outputs
+%
+% 
+% Rob Campbell
+
+
+
+W=which(['NBP.',mfilename]);
+fprintf('Running example located at %s\n',W)
 
 hFig=figure(1984);
 
 set(hFig,...
-	'Name','notBoxPlot example',...
-	'PaperPosition',[0,0,12,9]) %Just to make save to disk consistent)
+    'Name','notBoxPlot example',...
+    'PaperPosition',[0,0,12,9]) %Just to make save to disk consistent)
 clf
 
 W=0.45; %image width
@@ -38,33 +53,33 @@
 
 %higher means as green
 set([H(find(IND)).data],'MarkerSize',4,...
-	'markerFaceColor',[1,1,1]*0.25,...
-	'markerEdgeColor', 'none')
+    'markerFaceColor',[1,1,1]*0.25,...
+    'markerEdgeColor', 'none')
 set([H(find(IND)).semPtch],...
-	'FaceColor',[0,0.75,0],...
-	'EdgeColor','none')
+    'FaceColor',[0,0.75,0],...
+    'EdgeColor','none')
 set([H(find(IND)).sdPtch],...
-	'FaceColor',[0.6,1,0.6],...
-	'EdgeColor','none')
+    'FaceColor',[0.6,1,0.6],...
+    'EdgeColor','none')
 set([H(find(IND)).mu],...
-	'Color',[0,0.4,0])
+    'Color',[0,0.4,0])
 
 
 set(gca,'XTick',[]) 
 
 
 %lower means as gray
 set([H(find(~IND)).data],'MarkerSize',4,...
-	'markerFaceColor',[1,1,1]*0.5,...
-	'markerEdgeColor', 'none')
+    'markerFaceColor',[1,1,1]*0.5,...
+    'markerEdgeColor', 'none')
 set([H(find(~IND)).semPtch],...
-	'FaceColor',[1,1,1]*0.25,...
-	'EdgeColor','none')
+    'FaceColor',[1,1,1]*0.25,...
+    'EdgeColor','none')
 set([H(find(~IND)).sdPtch],...
-	'FaceColor',[1,1,1]*0.75,...
-	'EdgeColor','none')
+    'FaceColor',[1,1,1]*0.75,...
+    'EdgeColor','none')
 set([H(find(~IND)).mu],...
-	'Color','b')
+    'Color','b')
 
 box on
 
@@ -79,7 +94,7 @@
 
 H=notBoxPlot(y,x,'jitter',0.6,'style','sdline');
 set(H(end).data,'Marker','^',...
-	'MarkerSize',5)
+    'MarkerSize',5)
 set([H.sd],'LineWidth',4)
 box on
 grid on
@@ -97,9 +112,9 @@
 
 H=notBoxPlot(r,[],'jitter',0.5);
 set([H.data],...
-	'MarkerFaceColor',[1,1,1]*0.35,....
-	'markerEdgeColor',[1,1,1]*0.35,...
-	'MarkerSize',3)
+    'MarkerFaceColor',[1,1,1]*0.35,...
+    'markerEdgeColor',[1,1,1]*0.35,...
+    'MarkerSize',3)
 
 set([H.mu],'color','w')
 J=jet(length(H));

code/+NBP/simpleExamples.m

@@ -0,0 +1,44 @@
+function simpleExamples
+%
+% clf 
+%
+% subplot(2,2,1)  
+% notBoxPlot(randn(20,5));
+%
+% subplot(2,2,2)  
+% notBoxPlot(randn(20,5),[1:4,7]);
+%
+% subplot(2,2,3)
+% h=notBoxPlot(randn(10,20));
+% d=[h.data];
+% set(d(1:4:end),'markerfacecolor',[0.4,1,0.4],'color',[0,0.4,0])
+%
+% subplot(2,2,4)
+% x=[1,2,3,4,5,5];
+% y=randn(20,length(x));
+% y(:,end)=y(:,end)+3;
+% y(:,end-1)=y(:,end-1)-1;
+% notBoxPlot(y,x);
+
+help(['NBP.',mfilename])
+
+clf 
+
+subplot(2,2,1)  
+notBoxPlot(randn(20,5));
+
+subplot(2,2,2)  
+notBoxPlot(randn(20,5),[1:4,7]);
+
+subplot(2,2,3)
+h=notBoxPlot(randn(10,20));
+d=[h.data];
+set(d(1:4:end),'markerfacecolor',[0.4,1,0.4],'color',[0,0.4,0])
+
+
+subplot(2,2,4)
+x=[1,2,3,4,5,5];
+y=randn(20,length(x));
+y(:,end)=y(:,end)+3;
+y(:,end-1)=y(:,end-1)-1;
+notBoxPlot(y,x);