From 2832b7a8c9998c5d8bf4e6cce42a629bcb801b71 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 09:44:52 +0100
Subject: [PATCH 1/9] Tidy code, improve comments, fix a typo.

---
 README.md         |   2 +-
 code/notBoxPlot.m | 192 ++++++++++++++++++++++++----------------------
 2 files changed, 101 insertions(+), 93 deletions(-)

diff --git a/README.md b/README.md
index 6a8bbc2..84e7809 100644
--- a/README.md
+++ b/README.md
@@ -15,7 +15,7 @@ Although it's worked well for situations I've needed it, I will be happy to modi
 
 ## Features
 - 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
diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index bcf940c..c37c3d1 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -129,7 +129,7 @@
 % notBoxPlot(y,[],'interval','tInterval'), title('95% t-interval (n=8)')
 %
 %
-% Example 8 - Add the median (dotted line) to plots
+% Example 9 - Add the median (dotted line) to plots
 % clf
 % n=[5,10,20,40];
 % for ii=1:4, rng(555), notBoxPlot(rand(1,n(ii)),ii,'markMedian',true), end
@@ -142,7 +142,7 @@
 
 
     
-    
+
 % Check input arguments
 if nargin==0
     help(mfilename)
@@ -150,14 +150,19 @@
 end
 
 
-if isvector(y), y=y(:); end
+if isvector(y)
+    y=y(:); 
+end
+
 
+%Generate an monotonically increasing X variable if the user didn't supply anything
 if nargin<2 || isempty(x)
     x=1:size(y,2);
 end
 
 
 if ~isempty(varargin)
+    %Check if these look like legacy input arguments
     if isnumeric(varargin{1})
         jitter=varargin{1};
         legacyCall=true;
@@ -179,6 +184,8 @@
     error('notBoxPlot:legacyError','You have mixed legacy with new-style calls. See function help')
 end
 
+
+%If the user fed in legacy arguments, we generate new-style arguments that can be fed to the inputParser 
 if legacyCall
     if nargin<4
         style='patch'; %Can also be 'line' or 'sdline'
@@ -196,9 +203,9 @@
 
 
 
-    
+
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    
-% Parse input arguments if new-style args were provided
+% Parse input arguments (including converted legacy arguments)
 if ~legacyCall
 
     params = inputParser;
@@ -211,9 +218,9 @@
     params.parse(varargin{:});
 
     %Extract values from the inputParser
-    jitter =  params.Results.jitter;
-    style =  params.Results.style;
-    interval = params.Results.interval;
+    jitter     = params.Results.jitter;
+    style      = params.Results.style;
+    interval   = params.Results.interval;
     markMedian = params.Results.markMedian;
 
     %Set interval function
@@ -225,7 +232,6 @@
         otherwise
             error('Interval %s is unknown',interval)
     end
-
 end
 
 
@@ -246,7 +252,7 @@
     
     u=unique(x);
     for ii=1:length(u)
-        f=x==u(ii);
+        f = x==u(ii);
         h(ii)=notBoxPlot(y(f),u(ii),varargin{:}); %recursive call
     end
 
@@ -265,8 +271,6 @@
     
 end
 
-
-
  
 if length(x) ~= size(y,2)
     error('length of x doesn''t match the number of columns in y')
@@ -274,9 +278,6 @@
 
 
 
-    
-    
-
 
 %We're going to render points with the same x value in different
 %colors so we loop through all unique x values and do the plotting
@@ -304,6 +305,7 @@
 end
 
 
+%handle the output arguments
 if nargout>0
     varargout{1}=H;
 end
@@ -324,100 +326,106 @@
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 function [h,statsOut]=myPlotter(X,Y)
 
- SEM=intervalFun(Y); %Supplied external function
- SD=std(Y,'omitnan');  %Requires the stats toolbox 
- mu=mean(Y,'omitnan'); %Requires the stats toolbox 
- if markMedian
-    med = median(Y,'omitnan');
- end
+    SEM=intervalFun(Y); %Supplied external function
+    SD=std(Y,'omitnan');  %Requires the stats toolbox 
+    mu=mean(Y,'omitnan'); %Requires the stats toolbox 
+    if markMedian
+       med = median(Y,'omitnan');
+    end
 
 
 
- %The plot colors to use for multiple sets of points on the same x
- %location
- cols=hsv(length(X)+1)*0.5;
- cols(1,:)=0;
- jitScale=jitter*0.55; %To scale the patch by the width of the jitter
+    %The plot colors to use for multiple sets of points on the same x
+    %location
+    cols=hsv(length(X)+1)*0.5;
+    cols(1,:)=0;
+    jitScale=jitter*0.55; %To scale the patch by the width of the jitter
 
- for k=1:length(X)
-     thisY=Y(:,k);
-     thisY=thisY(~isnan(thisY));    
-     thisX=repmat(X(k),1,length(thisY));
+    for k=1:length(X)
+        thisY=Y(:,k);
+        thisY=thisY(~isnan(thisY));    
+        thisX=repmat(X(k),1,length(thisY));
 
-     if strcmp(style,'patch') 
-       h(k).sdPtch=patchMaker(SD(k),[0.6,0.6,1]);
-     end
+        %Assemble stats for optional command line output
+        statsOut(k).mu = mu(k);
+        statsOut(k).interval = SEM(k);
+        statsOut(k).sd = SD(k);
 
-     %For optional command line output
-     statsOut(k).mu = mu(k);
-     statsOut(k).interval = SEM(k);
-     statsOut(k).sd = SD(k);
 
+        %Add the SD as a patch if the user asked for this
+        if strcmp(style,'patch') 
+            h(k).sdPtch=patchMaker(SD(k),[0.6,0.6,1]);
+        end
 
-     if strcmp(style,'patch') || strcmp(style,'sdline')
-       %Plot mean and SEM (and optionally the median)
-       h(k).semPtch=patchMaker(SEM(k),[1,0.6,0.6]);
-       h(k).mu=plot([X(k)-jitScale,X(k)+jitScale],[mu(k),mu(k)],'-r',...
-            'linewidth',2);
-       if markMedian
-          statsOut(k).median = med(k);
-          h(k).med=plot([X(k)-jitScale,X(k)+jitScale],[med(k),med(k)],':r',...
+        %Build patch surfaces for SEM, the means, and optionally the medians
+        if strcmp(style,'patch') || strcmp(style,'sdline')
+            h(k).semPtch=patchMaker(SEM(k),[1,0.6,0.6]);
+            h(k).mu=plot([X(k)-jitScale,X(k)+jitScale],[mu(k),mu(k)],'-r',...
                 'linewidth',2);
-       end
-     end
-    
-     %Plot jittered raw data
-     C=cols(k,:);
-     J=(rand(size(thisX))-0.5)*jitter;
-        
-     h(k).data=plot(thisX+J, thisY, 'o', 'color', C,...
-                   'markerfacecolor', C+(1-C)*0.65);
- end
-
- if strcmp(style,'line') || strcmp(style,'sdline')
-   for k=1:length(X)    
-     %Plot SD
-     h(k).sd=plot([X(k),X(k)],[mu(k)-SD(k),mu(k)+SD(k)],...
-                  '-','color',[0.2,0.2,1],'linewidth',2);
-     set(h(k).sd,'ZData',[1,1]*-1)
-   end
- end
-
- if strcmp(style,'line')
-     for k=1:length(X)     
-         %Plot mean and SEM (and optionally the median)
-         h(k).mu=plot(X(k),mu(k),'o','color','r',...
-             'markerfacecolor','r',...
-             'markersize',10);
+            if markMedian
+                statsOut(k).median = med(k);
+                h(k).med=plot([X(k)-jitScale,X(k)+jitScale],[med(k),med(k)],':r',...
+                    'linewidth',2);
+            end
+        end
         
-         h(k).sem=plot([X(k),X(k)],[mu(k)-SEM(k),mu(k)+SEM(k)],'-r',...
-             'linewidth',2);   
-        if markMedian
-            h(k).med=plot(X(k),med(k),'s','color',[0.8,0,0],...
-             'markerfacecolor','none',...
-             'lineWidth',2,...
-             'markersize',12);
+        %Overlay the jittered raw data
+        C=cols(k,:);
+        J=(rand(size(thisX))-0.5)*jitter;
+            
+        h(k).data=plot(thisX+J, thisY, 'o', 'color', C,...
+                       'markerfacecolor', C+(1-C)*0.65);
+    end  %for k=1:length(X)
+
+
+    %Plot SD as a line
+    if strcmp(style,'line') || strcmp(style,'sdline')
+        for k=1:length(X)    
+            h(k).sd=plot([X(k),X(k)],[mu(k)-SD(k),mu(k)+SD(k)],...
+                      '-','color',[0.2,0.2,1],'linewidth',2);
+            set(h(k).sd,'ZData',[1,1]*-1)
         end
+    end
 
-         h(k).xAxisLocation=x(k);
-     end
- end
- for ii=1:length(h)
-     h(ii).interval=interval;
- end
 
+    %Plot mean and SEM as a line, the means, and optionally the medians
+    if strcmp(style,'line')
+        for k=1:length(X)     
+            
+            h(k).mu=plot(X(k),mu(k),'o','color','r',...
+                'markerfacecolor','r',...
+                'markersize',10);
+
+            h(k).sem=plot([X(k),X(k)],[mu(k)-SEM(k),mu(k)+SEM(k)],'-r',...
+                'linewidth',2);   
+            if markMedian
+                h(k).med=plot(X(k),med(k),'s','color',[0.8,0,0],...
+                'markerfacecolor','none',...
+                'lineWidth',2,...
+                'markersize',12);
+            end
+
+             h(k).xAxisLocation=x(k);
+        end
+    end % if strcmp(style,'line')
 
+    for ii=1:length(h)
+        h(ii).interval=interval;
+    end
 
-     function ptch=patchMaker(thisInterval,color)
-         l=mu(k)-thisInterval;
-         u=mu(k)+thisInterval;
-         ptch=patch([X(k)-jitScale, X(k)+jitScale, X(k)+jitScale, X(k)-jitScale],...
+
+
+    function ptch=patchMaker(thisInterval,color)
+        %This nested function builds a patch for the SD or SEM
+        l=mu(k)-thisInterval;
+        u=mu(k)+thisInterval;
+        ptch=patch([X(k)-jitScale, X(k)+jitScale, X(k)+jitScale, X(k)-jitScale],...
                 [l,l,u,u], 0);
-         set(ptch,'edgecolor',color*0.8,'facecolor',color)
-     end %function patchMaker
+        set(ptch,'edgecolor',color*0.8,'facecolor',color)
+    end %function patchMaker
+
+
 
-        
-    
 end %function myPlotter
 
 

From 26483288678b2c10ced7426172a08f69ec66d7b9 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 10:02:03 +0100
Subject: [PATCH 2/9] MAJOR: remove handling of legacy notBoxPlot call

---
 code/notBoxPlot.m | 110 ++++++++++++++--------------------------------
 1 file changed, 32 insertions(+), 78 deletions(-)

diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index c37c3d1..0cd6f08 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -155,88 +155,45 @@
 end
 
 
-%Generate an monotonically increasing X variable if the user didn't supply anything
+% Generate an monotonically increasing X variable if the user didn't supply anything
+% for the grouping variable
 if nargin<2 || isempty(x)
     x=1:size(y,2);
 end
 
-
-if ~isempty(varargin)
-    %Check if these look like legacy input arguments
-    if isnumeric(varargin{1})
-        jitter=varargin{1};
-        legacyCall=true;
-        fprintf(['\n%s called with legacy input arguments. See function help for new call format.\n',...
-            'Legacy input arguments will be removed in the next release\n\n'],mfilename)
-    else
-        legacyCall=false;
-    end
-else
-    legacyCall=false;
-end
-
-if legacyCall && isempty(jitter)
-    jitter=0.3; %larger value means greater amplitude jitter
-end
-
-%Check for innapropriate mixed usage of new and old call types
-if (legacyCall && length(varargin)>2) || (~legacyCall && mod(length(varargin),2)>0)
-    error('notBoxPlot:legacyError','You have mixed legacy with new-style calls. See function help')
-end
-
-
-%If the user fed in legacy arguments, we generate new-style arguments that can be fed to the inputParser 
-if legacyCall
-    if nargin<4
-        style='patch'; %Can also be 'line' or 'sdline'
-    else
-        style=lower(varargin{2});
-    end
-
-    %TODO: the following will be removed, along with other references to legacy calling, in the next release
-    varargin={'jitter',jitter,'style',style,'interval','SEM'}; %define varargin so we feed the new-form inputs to the recursive call, below.
-    intervalFun = @NBP.SEM_calc; 
-    interval= 'SEM';
-    markMedian = false;
-end
-
-
-
+%If x is logical then the function fails. So let's make sure it's a double
+x=double(x);
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    
-% Parse input arguments (including converted legacy arguments)
-if ~legacyCall
-
-    params = inputParser;
-    params.CaseSensitive = false;
-    params.addParameter('jitter', 0.3, @(x) isnumeric(x) & isscalar(x));
-    params.addParameter('style','patch', @(x) ischar(x) && any(strncmp(x,{'patch','line','sdline'},inf)) ); 
-    params.addParameter('interval','SEM', @(x) ischar(x) && any(strncmp(x,{'SEM','tInterval'},inf)) ); 
-    params.addParameter('markMedian', false, @(x) islogical(x));
-
-    params.parse(varargin{:});
-
-    %Extract values from the inputParser
-    jitter     = params.Results.jitter;
-    style      = params.Results.style;
-    interval   = params.Results.interval;
-    markMedian = params.Results.markMedian;
-
-    %Set interval function
-    switch interval
-        case 'SEM'
-            intervalFun = @NBP.SEM_calc;
-        case 'tInterval'
-            intervalFun = @NBP.tInterval_calc;
-        otherwise
-            error('Interval %s is unknown',interval)
-    end
+% Parse input arguments
+params = inputParser;
+params.CaseSensitive = false;
+params.addParameter('jitter', 0.3, @(x) isnumeric(x) & isscalar(x));
+params.addParameter('style','patch', @(x) ischar(x) && any(strncmp(x,{'patch','line','sdline'},inf)) ); 
+params.addParameter('interval','SEM', @(x) ischar(x) && any(strncmp(x,{'SEM','tInterval'},inf)) ); 
+params.addParameter('markMedian', false, @(x) islogical(x));
+
+params.parse(varargin{:});
+
+%Extract values from the inputParser
+jitter     = params.Results.jitter;
+style      = params.Results.style;
+interval   = params.Results.interval;
+markMedian = params.Results.markMedian;
+
+%Set interval function
+switch interval
+    case 'SEM'
+        intervalFun = @NBP.SEM_calc;
+    case 'tInterval'
+        intervalFun = @NBP.tInterval_calc;
+    otherwise
+        error('Interval %s is unknown',interval)
 end
 
 
-%If x is logical then the function fails. So let's make sure it's a double
-x=double(x);
+
 
 if jitter==0 && strcmp(style,'patch') 
     warning('A zero value for jitter means no patch object visible')
@@ -249,7 +206,7 @@
     if length(x)~=length(y)
         error('length(x) should equal length(y)')
     end
-    
+
     u=unique(x);
     for ii=1:length(u)
         f = x==u(ii);
@@ -262,13 +219,13 @@
         xlim([min(u)-1,max(u)+1])
         set(gca,'XTick',u)
     end
-    
+
     if nargout==1
         varargout{1}=h;
     end
 
     return
-    
+
 end
 
  
@@ -314,9 +271,6 @@
     varargout{2}=stats;
 end
 
-if nargout>2
-    varargout{3}=legacyCall;
-end
 
 
 

From d0cbaeddf95afeacb9a4e45e93a6907c1237b7f7 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 10:17:34 +0100
Subject: [PATCH 3/9] Add a simple option to parse data in table format.

---
 code/notBoxPlot.m | 80 +++++++++++++++++++++++++++++++++++++----------
 1 file changed, 63 insertions(+), 17 deletions(-)

diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index 0cd6f08..1625e8d 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -17,13 +17,17 @@
 %
 %
 % Inputs
-% y - each column of y is one variable/group. If x is missing or empty
-%     then each column is plotted in a different x position. 
+% y - A vector, matrix, or table of the data to plot. 
+%      * vector and no x is provided: all data are grouped at one x position.
+%      * matrix and no x is provided: each column is plotted in a different x position. 
+%      * vector with x grouping variable provided: data grouped accordig to x
+%      * a table is treated such that the first column is y and the second x.
 %
 % x - [optional], the x axis points at which y columns should be
 %     plotted. This allows more than one set of y values to appear
 %     at one x location. Such instances are coloured differently. 
 %     Contrast the first two panels in Example 1 to see how this input behaves.
+%     x need not be provided if y is a table.
 %
 % Note that if x and y are both vectors of the same length this function
 % behaves like boxplot (see Example 5).
@@ -68,9 +72,9 @@
 % h=notBoxPlot(randn(10,40));
 % d=[h.data];
 % set(d(1:4:end),'markerfacecolor',[0.4,1,0.4],'color',[0,0.4,0])
-%  
+%
 % Example 2 - overlaying with areas
-% clf  
+% clf
 % x=[1,2,3,4,5,5];
 % y=randn(20,length(x));
 % y(:,end)=y(:,end)+3;
@@ -101,7 +105,7 @@
 % Note: an alternative to the style used in Example 5 is to call
 % notBoxPlot from a loop in an external function. In this case, the
 % user will have to take care of the x-ticks and axis limits. 
-%    
+%
 % Example 6 - replacing the SD with bars
 % clf
 % y=randn(50,1);
@@ -135,13 +139,27 @@
 % for ii=1:4, rng(555), notBoxPlot(rand(1,n(ii)),ii,'markMedian',true), end
 %
 %
+% Example 10 - Table call format
+% clf
+% albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
+% victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
+% M = table(victoria,albert); %place data in first column and groups in the second
+% notBoxPlot(M)
+%
+% Example 11 - Table call format with optional arguments
+% clf
+% albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
+% victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
+% M = table(victoria,albert); %place data in first column and groups in the second
+% notBoxPlot(M,'jitter',0.75)
+%
 %
 % Rob Campbell - August 2016
 %
-% Also see: boxplot, NBP.example
+% Also see: NBP.example, boxplot
+
 
 
-    
 
 % Check input arguments
 if nargin==0
@@ -150,21 +168,43 @@
 end
 
 
-if isvector(y)
-    y=y(:); 
-end
+%Handle table call 
+if istable(y)
+
+    tableCall=true;
+    if nargin>1 %so user doesn't need to specify a blank variable for x
+        if ~isempty(x)
+            varargin = [x,varargin];
+        end
+    end
+    thisTable=y;
+    varNames=thisTable.Properties.VariableNames;
+    if length(varNames) ~= 2
+        fprintf('% s can only handle tables with two variables\n',mfilename)
+        return
+    end
+    y = thisTable.(varNames{1});
+    x = thisTable.(varNames{2});
 
+else
+    tableCall=false;
 
-% Generate an monotonically increasing X variable if the user didn't supply anything
-% for the grouping variable
-if nargin<2 || isempty(x)
-    x=1:size(y,2);
+    if isvector(y)
+        y=y(:); 
+    end
+
+    % Generate an monotonically increasing X variable if the user didn't supply anything
+    % for the grouping variable
+    if nargin<2 || isempty(x)
+        x=1:size(y,2);
+    end
 end
 
 %If x is logical then the function fails. So let's make sure it's a double
 x=double(x);
 
 
+
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%    
 % Parse input arguments
 params = inputParser;
@@ -224,6 +264,12 @@
         varargout{1}=h;
     end
 
+    %If we had a table we can label the axes
+    if tableCall
+        ylabel(varNames{1})
+        xlabel(varNames{2})
+    end
+
     return
 
 end
@@ -334,7 +380,7 @@
 
     %Plot SD as a line
     if strcmp(style,'line') || strcmp(style,'sdline')
-        for k=1:length(X)    
+        for k=1:length(X)
             h(k).sd=plot([X(k),X(k)],[mu(k)-SD(k),mu(k)+SD(k)],...
                       '-','color',[0.2,0.2,1],'linewidth',2);
             set(h(k).sd,'ZData',[1,1]*-1)
@@ -344,8 +390,8 @@
 
     %Plot mean and SEM as a line, the means, and optionally the medians
     if strcmp(style,'line')
-        for k=1:length(X)     
-            
+        for k=1:length(X)
+
             h(k).mu=plot(X(k),mu(k),'o','color','r',...
                 'markerfacecolor','r',...
                 'markersize',10);

From 9db5c8322023dec906d71b56dcb40299ac9b57ea Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 11:40:28 +0100
Subject: [PATCH 4/9] Allow user to supply param/val pairs without needing to
 set x to empty if not supplying this argument.

---
 code/notBoxPlot.m | 7 +++++++
 1 file changed, 7 insertions(+)

diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index 1625e8d..1e82a02 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -193,6 +193,13 @@
         y=y(:); 
     end
 
+    % Handle case where user doesn't supply X, but have user param/val pairs. e.g.
+    % notBoxPlot(rand(20,5),'jitter',0.5)
+    if nargin>2 && ischar(x)
+        varargin = [x,varargin];
+        x=[];
+    end
+
     % Generate an monotonically increasing X variable if the user didn't supply anything
     % for the grouping variable
     if nargin<2 || isempty(x)

From 7e52362e019f15b85d1f6b0b66cde16f8682fe00 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 12:21:36 +0100
Subject: [PATCH 5/9] Organize the more detailed examples into separate
 functions under NBP

---
 code/+NBP/SEM_calc.m                |   7 +-
 code/+NBP/jitterExamples.m          |  30 ++++++++
 code/+NBP/lineExamples.m            |  36 +++++++++
 code/+NBP/{example.m => showCase.m} |  63 +++++++++------
 code/+NBP/simpleExamples.m          |  44 +++++++++++
 code/+NBP/statsOptionsExample.m     |  45 +++++++++++
 code/+NBP/tInterval_calc.m          |   9 ++-
 code/+NBP/tableExamples.m           |  32 ++++++++
 code/notBoxPlot.m                   | 115 +++++++---------------------
 9 files changed, 263 insertions(+), 118 deletions(-)
 create mode 100644 code/+NBP/jitterExamples.m
 create mode 100644 code/+NBP/lineExamples.m
 rename code/+NBP/{example.m => showCase.m} (63%)
 create mode 100644 code/+NBP/simpleExamples.m
 create mode 100644 code/+NBP/statsOptionsExample.m
 create mode 100644 code/+NBP/tableExamples.m

diff --git a/code/+NBP/SEM_calc.m b/code/+NBP/SEM_calc.m
index a5fdfa5..ce3e213 100644
--- a/code/+NBP/SEM_calc.m
+++ b/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 ;    
 
-
-
-
diff --git a/code/+NBP/jitterExamples.m b/code/+NBP/jitterExamples.m
new file mode 100644
index 0000000..9c8efc6
--- /dev/null
+++ b/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);
+
+
diff --git a/code/+NBP/lineExamples.m b/code/+NBP/lineExamples.m
new file mode 100644
index 0000000..4a1b8c5
--- /dev/null
+++ b/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])
\ No newline at end of file
diff --git a/code/+NBP/example.m b/code/+NBP/showCase.m
similarity index 63%
rename from code/+NBP/example.m
rename to code/+NBP/showCase.m
index dd4a292..31b4236 100644
--- a/code/+NBP/example.m
+++ b/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
@@ -38,16 +53,16 @@
 
 %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',[]) 
@@ -55,16 +70,16 @@
 
 %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));
diff --git a/code/+NBP/simpleExamples.m b/code/+NBP/simpleExamples.m
new file mode 100644
index 0000000..8b0485c
--- /dev/null
+++ b/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);
diff --git a/code/+NBP/statsOptionsExample.m b/code/+NBP/statsOptionsExample.m
new file mode 100644
index 0000000..26b8f96
--- /dev/null
+++ b/code/+NBP/statsOptionsExample.m
@@ -0,0 +1,45 @@
+function statsOptionsExamples
+
+% 
+% % Examples of different statistics options
+% 
+% % The 95% SEM vs the 95% t-interval
+% clf
+% y=randn(8,3);
+% subplot(2,2,1)
+% notBoxPlot(y)
+% title('95% SEM (n=8)')
+%
+% subplot(2,2,2)
+% notBoxPlot(y,'interval','tInterval')
+% title('95% t-interval (n=8)')
+%
+% % Adding medians
+% subplot(2,2,:3:4)
+% n=[5,10,20,40];
+% for ii=1:4
+%  rng(555), notBoxPlot(rand(1,n(ii)),ii,'markMedian',true)
+% end
+% title('median vs mean')
+
+
+help(['NBP.',mfilename])
+
+% The 95% SEM vs the 95% t-interval
+clf
+y=randn(8,3);
+subplot(2,2,1)
+notBoxPlot(y)
+title('95% SEM (n=8)')
+
+subplot(2,2,2)
+notBoxPlot(y,'interval','tInterval')
+title('95% t-interval (n=8)')
+
+% Adding medians
+subplot(2,2,3:4)
+n=[5,10,20,40];
+for ii=1:4
+ rng(555), notBoxPlot(rand(1,n(ii)),ii,'markMedian',true)
+end
+title('median vs mean')
\ No newline at end of file
diff --git a/code/+NBP/tInterval_calc.m b/code/+NBP/tInterval_calc.m
index e827ad6..5731e15 100644
--- a/code/+NBP/tInterval_calc.m
+++ b/code/+NBP/tInterval_calc.m
@@ -1,7 +1,8 @@
 function tint=tInterval_Calc(vect, CI)
 % tInterval_Calc - confidence interval based on the t-distribution
 %
-% function tint=tInterval_Calc(vect, CI)
+% function tint = NBP.tInterval_Calc(vect, CI)
+%
 %
 % Purpose
 % Calculate the t-interval about the mean to a given confidence
@@ -10,6 +11,7 @@
 % of this function has been checked against  known working code
 % written in R. 
 %
+%
 % Inputs
 % - vect: Calculates the two-tailed 95% t confidence limits for the mean.
 %
@@ -24,8 +26,11 @@
 % plot([mean(r)-T,mean(r)+T], [mean(ylim),mean(ylim)],'r-')
 % hold off
 %
+%
+%
 % Rob Campbell - 12/03/08
 %
+%
 % Also see - SEM_calc, tinv
 
 narginchk(1,2)
@@ -48,5 +53,5 @@
 end
   
 
-tint =  ( (nanstd(vect)) ./ sqrt(sum(~isnan(vect))) ) * stdCI ;    
+tint = ( (nanstd(vect)) ./ sqrt(sum(~isnan(vect))) ) * stdCI ;    
 
diff --git a/code/+NBP/tableExamples.m b/code/+NBP/tableExamples.m
new file mode 100644
index 0000000..725c180
--- /dev/null
+++ b/code/+NBP/tableExamples.m
@@ -0,0 +1,32 @@
+function tableExamples
+
+% % Table call format
+%
+% clf
+%
+% albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
+% victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
+% M = table(victoria,albert); %place data in first column and groups in the second
+%
+% subplot(1,2,1)
+% notBoxPlot(M)
+%
+% subplot(1,2,2)
+% notBoxPlot(M,'jitter',0.5)
+
+
+help(['NBP.',mfilename])
+
+
+clf
+
+albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
+victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
+
+M = table(victoria,albert); %place data in first column and groups in the second
+
+subplot(1,2,1)
+notBoxPlot(M)
+
+subplot(1,2,2)
+notBoxPlot(M,'jitter',0.75)
\ No newline at end of file
diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index 1e82a02..d09e6dc 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -61,102 +61,41 @@
 % 
 %
 % 
-%
-% Example 1 - simple example
-% clf 
-% subplot(2,2,1)  
-% notBoxPlot(randn(20,5));
-% subplot(2,2,2)  
-% notBoxPlot(randn(20,5),[1:4,7]);
-% subplot(2,2,3:4)
-% h=notBoxPlot(randn(10,40));
-% d=[h.data];
-% set(d(1:4:end),'markerfacecolor',[0.4,1,0.4],'color',[0,0.4,0])
-%
-% Example 2 - overlaying with areas
-% clf
-% 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);
-%
-% Example 3 - lines
-% clf
-% H=notBoxPlot(randn(20,5),[],'style','line');
-% set([H.data],'markersize',10)
-%
-% Example 4 - mix lines and areas [note that the way this function
-% sets the x axis limits can cause problems when combining plots
-% this way]
-%
-% clf
-% 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')
-%  
-% Example 5 - x and y are vectors
-% clf
-% x=[1,1,1,3,2,1,3,3,3,2,2,3,3];
-% y=[7,8,6,1,5,7,2,1,3,4,5,2,4];
-% notBoxPlot(y,x);
+% -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  - 
+% Examples (run clf between examples):
 % 
-% Note: an alternative to the style used in Example 5 is to call
-% notBoxPlot from a loop in an external function. In this case, the
-% user will have to take care of the x-ticks and axis limits. 
-%
-% Example 6 - replacing the SD with bars
-% clf
-% y=randn(50,1);
-% clf
-% notBoxPlot(y,1,'style','sdline')
-% notBoxPlot(y,2)   
-% xlim([0,3])
-%
-%
-% Example 7 - the effect of jitter (default jitter is 0.3)
-% clf
-% subplot(2,1,1)
-% notBoxPlot(randn(20,5),[],'jitter',0.15)
-% subplot(2,1,2)
-% notBoxPlot(randn(20,5),[],'jitter',0.75);
-%
+% 1 - Basic usage:
+%  >> notBoxPlot([7,8,6,1,5,7,2,1,3,4,5,2,4])
+%  >> notBoxPlot([7,8,6,1,5,7,2,1,3,4,5,2,4], [1,1,1,3,2,1,3,3,3,2,2,3,3])
+%  >> notBoxPlot(rand(1,100))
+%  >> notBoxPlot(randn(20,5))
+%  >> notBoxPlot(randn(20,5),[1:4,7]);
+%  >> notBoxPlot(MY_TABLE)
+%
+%  For more run:
+%   NBP.simpleExamples
+%   NBP.tableExample
 % 
-% Example 8 - The 95% SEM vs the 95% t-interval
-% clf
-% y=randn(8,3);
-% subplot(1,2,1)
-% notBoxPlot(y), title('95% SEM (n=8)')
-%
-% subplot(1,2,2)
-% notBoxPlot(y,[],'interval','tInterval'), title('95% t-interval (n=8)')
-%
-%
-% Example 9 - Add the median (dotted line) to plots
-% clf
-% n=[5,10,20,40];
-% for ii=1:4, rng(555), notBoxPlot(rand(1,n(ii)),ii,'markMedian',true), end
-%
+% 2 - Changing plot style
+%  >> notBoxPlot(randn(20,5),[],'interval','tinterval'); 
+%  >> notBoxPlot(randn(20,5),'style','line'); %also valid: no need for x
+%  >> notBoxPlot(MY_TABLE,'jitter',0.5)
 %
-% Example 10 - Table call format
-% clf
-% albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
-% victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
-% M = table(victoria,albert); %place data in first column and groups in the second
-% notBoxPlot(M)
+%  For more run:
+%   NBP.lineExamples
+%   NBP.jitterExamples
+%   NBP.showCase
 %
-% Example 11 - Table call format with optional arguments
-% clf
-% albert=[1,1,1,3,2,1,3,3,3,2,2,3,3]';
-% victoria=[7,8,6,1,5,7,2,1,3,4,5,2,4]';
-% M = table(victoria,albert); %place data in first column and groups in the second
-% notBoxPlot(M,'jitter',0.75)
+% 3 - Showing different statistics
+%  >> notBoxPlot(randn(8,3),'interval','tInterval')
+%  >> notBoxPlot(randn(8,3),'markMedian',true)
 %
+%  For more run:
+%   NBP.statsOptionsExamples
 %
 % Rob Campbell - August 2016
 %
-% Also see: NBP.example, boxplot
+% Also see: boxplot
 
 
 

From ea0ad26c5926b37d59f99de5d7d79b6aa3326acc Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 13:38:51 +0100
Subject: [PATCH 6/9] Accepts a LinearModel and uses the confidence intervals
 derived from it.

---
 code/+NBP/linearModelExamples.m | 105 ++++++++++++++++++++++++++++++
 code/notBoxPlot.m               | 112 +++++++++++++++++++++++++-------
 2 files changed, 193 insertions(+), 24 deletions(-)
 create mode 100644 code/+NBP/linearModelExamples.m

diff --git a/code/+NBP/linearModelExamples.m b/code/+NBP/linearModelExamples.m
new file mode 100644
index 0000000..7846291
--- /dev/null
+++ b/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])
+% titl
+
+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')
diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index d09e6dc..32586fa 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -21,7 +21,8 @@
 %      * vector and no x is provided: all data are grouped at one x position.
 %      * matrix and no x is provided: each column is plotted in a different x position. 
 %      * vector with x grouping variable provided: data grouped accordig to x
-%      * a table is treated such that the first column is y and the second x.
+%      * a Table is treated such that the first column is y and the second x.
+%      * a LinearModel produced by fitlm
 %
 % x - [optional], the x axis points at which y columns should be
 %     plotted. This allows more than one set of y values to appear
@@ -49,6 +50,8 @@
 %
 % 'interval' - 'SEM' [default] Plots a 95% confidence interval for the mean
 %            - 'tInterval' Plots a 95% t-interval for the mean
+%            - If a LinearModel from fitlm is provided, interval is always
+%              the tInterval and the confidence interval comes from the model.
 %
 % 'markMedian' - false [default] if true the median value is highlighted
 %                The median is highlighted as a dotted line or an open square 
@@ -106,14 +109,24 @@
     return
 end
 
+% Check if Y is of a suitable class 
+if ~isnumeric(y) && ~istable(y) && ~isa(y,'LinearModel')
+    fprintf('Variable y is a %s. This is not an allowed input type. see help %s\n',...
+        class(y), mfilename)
+    return
+end
+
+% Parse the different call types
+modelCIs=[]; 
+tableOrModelCall=false;
 
-%Handle table call 
-if istable(y)
+switch lower(class(y))
 
-    tableCall=true;
+case 'table'
+    tableOrModelCall=true;
     if nargin>1 %so user doesn't need to specify a blank variable for x
         if ~isempty(x)
-            varargin = [x,varargin];
+            varargin=[x,varargin];
         end
     end
     thisTable=y;
@@ -125,8 +138,31 @@
     y = thisTable.(varNames{1});
     x = thisTable.(varNames{2});
 
-else
-    tableCall=false;
+case 'linearmodel'
+    tableOrModelCall=true;
+    if nargin>1 %so user doesn't need to specify a blank variable for x
+        if ~isempty(x)
+            varargin=[x,varargin];
+        end
+    end
+
+    thisModel=y;
+
+    if length(thisModel.PredictorNames) >1
+        fprintf('% s can only handle linear models with one predictor\n',mfilename)
+        return
+    end
+    y = thisModel.Variables.(thisModel.ResponseName);
+    x = thisModel.Variables.(thisModel.PredictorNames{1});
+    varNames = {thisModel.ResponseName,thisModel.PredictorNames{1}}; %for the axis labels
+
+   % Set the SD bar to have 1.96 standard deviations
+    varargin = [varargin,'numSDs',1.96];
+
+    % Get the the confidence intervals from the model
+    modelCIs = coefCI(thisModel,0.05);
+
+otherwise %Otherwise Y is a vector or a matrix
 
     if isvector(y)
         y=y(:); 
@@ -135,7 +171,7 @@
     % Handle case where user doesn't supply X, but have user param/val pairs. e.g.
     % notBoxPlot(rand(20,5),'jitter',0.5)
     if nargin>2 && ischar(x)
-        varargin = [x,varargin];
+        varargin=[x,varargin];
         x=[];
     end
 
@@ -144,7 +180,9 @@
     if nargin<2 || isempty(x)
         x=1:size(y,2);
     end
-end
+
+end %switch class(y)
+
 
 %If x is logical then the function fails. So let's make sure it's a double
 x=double(x);
@@ -155,11 +193,17 @@
 % Parse input arguments
 params = inputParser;
 params.CaseSensitive = false;
-params.addParameter('jitter', 0.3, @(x) isnumeric(x) & isscalar(x));
+
+%User-visible options
+params.addParameter('jitter', 0.3, @(x) isnumeric(x) && isscalar(x));
 params.addParameter('style','patch', @(x) ischar(x) && any(strncmp(x,{'patch','line','sdline'},inf)) ); 
 params.addParameter('interval','SEM', @(x) ischar(x) && any(strncmp(x,{'SEM','tInterval'},inf)) ); 
 params.addParameter('markMedian', false, @(x) islogical(x));
 
+%Options hidden from the user
+params.addParameter('numSDs',1, @(x) isnumeric(x) && isscalar(x) && x>=0) 
+params.addParameter('manualCI',[], @(x) (isnumeric(x) && isscalar(x)) || isempty(x) )
+
 params.parse(varargin{:});
 
 %Extract values from the inputParser
@@ -168,6 +212,10 @@
 interval   = params.Results.interval;
 markMedian = params.Results.markMedian;
 
+%The multiplier for the SD patch. e.g. for 1.96 SDs this value should be 1.96
+numSDs = params.Results.numSDs;
+manualCI = params.Results.manualCI; %Is used by the recursive call to over-ride the CI when y is a LinearModel
+
 %Set interval function
 switch interval
     case 'SEM'
@@ -178,14 +226,15 @@
         error('Interval %s is unknown',interval)
 end
 
-
-
-
 if jitter==0 && strcmp(style,'patch') 
     warning('A zero value for jitter means no patch object visible')
 end
 
 
+
+% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
+% We now loop through the unique x values, plotting each notBox in turn
+% using recursive calls to notBoxPlot.
 if isvector(y) && isvector(x) && length(x)>1
     x=x(:);
    
@@ -195,8 +244,16 @@
 
     u=unique(x);
     for ii=1:length(u)
-        f = x==u(ii);
-        h(ii)=notBoxPlot(y(f),u(ii),varargin{:}); %recursive call
+        f = find(x==u(ii));
+
+        %If a model was used, we use the 95% t-intervals it produces
+        if ~isempty(modelCIs)
+            thisCI = range(modelCIs(ii,:))/2; %the interval is symmetric and we need just this. 
+        else
+            thisCI =[];
+        end
+
+        h(ii)=notBoxPlot(y(f),u(ii),varargin{:},'manualCI',thisCI); %recursive call
     end
 
 
@@ -211,16 +268,17 @@
     end
 
     %If we had a table we can label the axes
-    if tableCall
+    if tableOrModelCall
         ylabel(varNames{1})
         xlabel(varNames{2})
     end
 
-    return
-
+    return % User's call to notBoxPlot never goes beyond here
 end
+% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
+
+
 
- 
 if length(x) ~= size(y,2)
     error('length of x doesn''t match the number of columns in y')
 end
@@ -271,10 +329,16 @@
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 function [h,statsOut]=myPlotter(X,Y)
+    %This is a nested function that shares the caller's namespace
 
-    SEM=intervalFun(Y); %Supplied external function
-    SD=std(Y,'omitnan');  %Requires the stats toolbox 
-    mu=mean(Y,'omitnan'); %Requires the stats toolbox 
+    if isempty(manualCI)
+        SEM=intervalFun(Y); %A function handle to a supplied external function
+    else
+        SEM=manualCI;
+    end
+
+    SD=std(Y,'omitnan')*numSDs; 
+    mu=mean(Y,'omitnan');
     if markMedian
        med = median(Y,'omitnan');
     end
@@ -314,11 +378,11 @@
                     'linewidth',2);
             end
         end
-        
+
         %Overlay the jittered raw data
         C=cols(k,:);
         J=(rand(size(thisX))-0.5)*jitter;
-            
+
         h(k).data=plot(thisX+J, thisY, 'o', 'color', C,...
                        'markerfacecolor', C+(1-C)*0.65);
     end  %for k=1:length(X)

From 0876812413c3b5fb7bf88d9db0d216d559b6f5c5 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Sat, 11 Mar 2017 15:51:36 +0100
Subject: [PATCH 7/9] Update readme and unit tests

---
 README.md                       |  20 ++++
 code/+NBP/linearModelExamples.m |   2 +-
 tests/core_tests.m              | 162 +++++++++-----------------------
 tests/readme.txt                |  10 ++
 tests/run_tests.m               |  21 -----
 5 files changed, 78 insertions(+), 137 deletions(-)
 create mode 100644 tests/readme.txt
 delete mode 100644 tests/run_tests.m

diff --git a/README.md b/README.md
index 84e7809..e48dbf5 100644
--- a/README.md
+++ b/README.md
@@ -34,3 +34,23 @@ 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)` 
+
diff --git a/code/+NBP/linearModelExamples.m b/code/+NBP/linearModelExamples.m
index 7846291..96268d7 100644
--- a/code/+NBP/linearModelExamples.m
+++ b/code/+NBP/linearModelExamples.m
@@ -48,7 +48,7 @@
 % notBoxPlot(M,'jitter',0.75)
 % grid on, box on
 % ylim([-0.5,2.2])
-% titl
+% title('increased variance in group 5')
 
 help(['NBP.',mfilename])
 
diff --git a/tests/core_tests.m b/tests/core_tests.m
index a73052c..ec5b81f 100644
--- a/tests/core_tests.m
+++ b/tests/core_tests.m
@@ -1,138 +1,70 @@
 classdef core_tests < matlab.unittest.TestCase
-	% Unit tests for notBoxPlot
+    % Unit tests for notBoxPlot
 
-	properties
+    properties
 
-	end %properties
+    end %properties
 
 
-	methods (Test)
+    methods (Test)
 
-		function checkForNonLegacyCall(testCase)
-			% Legacy function calls take the form: notBoxPlot(y,x,jitter,style)
-			% From release v1.2 the form is  notBoxPlot(y,x,'param','val',...)
-			% Here we test that NBP is correctly able to find non-legacy usage
-			y=rand(10,2);
-			x=1:2;
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y);
- 			testCase.verifyTrue(legacyCall == false);
+        function checkInputParameters(testCase)
+            %Check that no gross errors are produced for all param/val pairs not already tested above
+            y=rand(10,3);
+            x=[1,2,2]; %To place to boxes on the same x location and one on its own
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,x);
- 			testCase.verifyTrue(legacyCall == false);
+            clf
+            H=notBoxPlot(y,x,'jitter',0.6,'style','sdline');
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,x,'jitter',0.3);
- 			testCase.verifyTrue(legacyCall == false);
+            clf
+            notBoxPlot(y,[],'style','patch','interval','SEM');     
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,x,'style','patch');
- 			testCase.verifyTrue(legacyCall == false);
+            clf
+            notBoxPlot(y,x,'interval','tInterval');  
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,x,'style','line','jitter',0.2);
- 			testCase.verifyTrue(legacyCall == false);
+            clf
+            h=notBoxPlot(y,x,'interval','tInterval','markMedian',false);  
+            testCase.verifyFalse(isfield(h,'med'))
 
- 			close(gcf)
-		end
+            clf
+            h=notBoxPlot(y,x,'interval','tInterval','markMedian',true);
+            testCase.verifyTrue(isfield(h,'med'))
 
-		function checkForLegacyCall(testCase)
-			% Legacy function calls take the form: notBoxPlot(y,x,jitter,style)
-			% From release v1.2 the form is  notBoxPlot(y,x,'param','val',...)
-			% Here we test that NBP is correctly able to find legacy usage
-			y=rand(10,2);
-			x=1:2;
+            clf
+            h=notBoxPlot(y,x,'style','line','markMedian',false);  
+            testCase.verifyFalse(isfield(h,'med'))
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,[],0.3);
- 			testCase.verifyTrue(legacyCall == true);
+            clf
+            h=notBoxPlot(y,x,'style','line','markMedian',true);
+            testCase.verifyTrue(isfield(h,'med'))
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,[],[],'line');
- 			testCase.verifyTrue(legacyCall == true);
+            %Check that the showCase example runs
+            NBP.showCase
+            
+            close(gcf)
+        end
 
-			clf
- 			[~,~,legacyCall] = notBoxPlot(y,x,0.2,'line');
- 			testCase.verifyTrue(legacyCall == true);
 
- 			close(gcf)
-		end
+        function checkOutputs(testCase)
+            %Check output args
+            y=rand(10,3);
+            x=[1,2,2]; %To place to boxes on the same x location and one on its own
 
-		function checkForMixedCalls(testCase)
-			% Legacy function calls take the form: notBoxPlot(y,x,jitter,style)
-			% From release v1.2 the form is  notBoxPlot(y,x,'param','val',...)
-			% Here we test that NBP is correctly able to catch erroneous mixed usage
-			y=rand(10,2);
-			x=1:2;
+            clf
+            [H,stats]=notBoxPlot(y,x,'jitter',0.6,'style','sdline');
+            testCase.verifyTrue(isstruct(H))
+            testCase.verifyTrue(isstruct(stats))
+            testCase.verifyTrue(length(H)==length(stats))
 
-			clf
- 			testCase.verifyError(@() notBoxPlot(y,x,0.3,'style','line'),'notBoxPlot:legacyError')
+            clf
+            [H,stats]=notBoxPlot(y,x,'jitter',0.6,'markMedian',true);
 
-			clf
- 			testCase.verifyError(@() notBoxPlot(y,x,'style','line',0.3),'notBoxPlot:legacyError')
+            testCase.verifyTrue(isfield(stats,'median'))
 
- 			close(gcf)
-		end
-
-
-		function checkInputParameters(testCase)
-			%Check that no gross errors are produced for all param/val pairs not already tested above
-			y=rand(10,3);
-			x=[1,2,2]; %To place to boxes on the same x location and one on its own
-
-			clf
-			H=notBoxPlot(y,x,'jitter',0.6,'style','sdline');
-
-			clf
-			notBoxPlot(y,[],'style','patch','interval','SEM');     
-
-			clf
-			notBoxPlot(y,x,'interval','tInterval');  
-
-			clf
-			h=notBoxPlot(y,x,'interval','tInterval','markMedian',false);  
-			testCase.verifyFalse(isfield(h,'med'))
-
-			clf
-			h=notBoxPlot(y,x,'interval','tInterval','markMedian',true);
-			testCase.verifyTrue(isfield(h,'med'))
-
-			clf
-			h=notBoxPlot(y,x,'style','line','markMedian',false);  
-			testCase.verifyFalse(isfield(h,'med'))
-
-			clf
-			h=notBoxPlot(y,x,'style','line','markMedian',true);
-			testCase.verifyTrue(isfield(h,'med'))
-
-			%Check that the example runs
-			NBP.example
-			
- 			close(gcf)
-		end
-
-
-		function checkOutputs(testCase)
-			%Check output args
-			y=rand(10,3);
-			x=[1,2,2]; %To place to boxes on the same x location and one on its own
-
-			clf
-			[H,stats]=notBoxPlot(y,x,'jitter',0.6,'style','sdline');
-			testCase.verifyTrue(isstruct(H))
-			testCase.verifyTrue(isstruct(stats))
-			testCase.verifyTrue(length(H)==length(stats))
-
-			clf
-			[H,stats]=notBoxPlot(y,x,'jitter',0.6,'markMedian',true);
-
-			testCase.verifyTrue(isfield(stats,'median'))
-
-			
-			close(gcf)
-		end
-	end %methods (Test)
+            
+            close(gcf)
+        end
+    end %methods (Test)
 
 end %classdef core_tests < matlab.unittest.TestCase
\ No newline at end of file
diff --git a/tests/readme.txt b/tests/readme.txt
new file mode 100644
index 0000000..9809e7c
--- /dev/null
+++ b/tests/readme.txt
@@ -0,0 +1,10 @@
+This directory contains code for unit testing settings_handler. 
+You do not need to add this directory to your path. 
+
+To run the unit tests:
+
+>> runtests
+
+or 
+
+>> table(runtests)
\ No newline at end of file
diff --git a/tests/run_tests.m b/tests/run_tests.m
deleted file mode 100644
index 56f0c25..0000000
--- a/tests/run_tests.m
+++ /dev/null
@@ -1,21 +0,0 @@
-function varargout = run_tests
-% run all unit tests for settings handler
-%
-% function results = run_tests	
-%
-% No input arguments. Results printed to screen and optionally 
-% returned to the workspace. 
-
-
-testCase = core_tests;
-results = run(testCase);
-out{1}=results;
-
-
-fprintf('\n------------------------  RESULTS  ------------------------\n')
-for ii=1:length(out)
-	disp(out{ii});
-end
-if nargout>0
-	varargout{1}=out;
-end

From d10661fdfe9239493bfbcc2b15fdac6a2a340c47 Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Tue, 14 Mar 2017 08:56:05 +0100
Subject: [PATCH 8/9] Do not attempt to plot model if the predictor is numeric.
 Coerce cell arrays to categorical.

---
 code/notBoxPlot.m | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/code/notBoxPlot.m b/code/notBoxPlot.m
index 32586fa..96f067f 100644
--- a/code/notBoxPlot.m
+++ b/code/notBoxPlot.m
@@ -154,6 +154,17 @@
     end
     y = thisModel.Variables.(thisModel.ResponseName);
     x = thisModel.Variables.(thisModel.PredictorNames{1});
+
+    %Check that x is of a suitable type
+    if isnumeric(x)
+        fprintf('The model predictor variable should not be continuous\n')
+        return
+    end
+    if iscell(x)
+        fprintf('Coercing predictor variable from a cell array to a categorical variable\n')
+        x=categorical(x);
+    end
+
     varNames = {thisModel.ResponseName,thisModel.PredictorNames{1}}; %for the axis labels
 
    % Set the SD bar to have 1.96 standard deviations

From 35b01d65bfadacdc1d001403eb4ea7630ec793ca Mon Sep 17 00:00:00 2001
From: Rob Campbell <git@raacampbell.com>
Date: Tue, 14 Mar 2017 09:01:17 +0100
Subject: [PATCH 9/9] update readme to reflect new feature

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index e48dbf5..b8ff212 100644
--- a/README.md
+++ b/README.md
@@ -14,6 +14,7 @@ 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-hoc modification of plot parameters via returned function handles
 - Statistics (mean, SD, etc) optionally returned