Remove dependency to Statistics Toolbox

Removed the use of normrnd, poissrnd and prctile from the code for users without Statistical toolbox

Resolves: #6

Utilities/addCTnoise.m

@@ -91,7 +91,11 @@
 Im=I0*exp(-proj);
 
 % Photon noise + electronic noise
-Im=poissrnd(Im)+normrnd(m,sigma);
+if areTheseToolboxesInstalled({'MATLAB','Statistics Toolbox'})
+    Im=poissrnd(Im)+randn(size(Im)).*sigma + m;
+else
+    Im=poissonrandom(Im)+randn(size(Im)).*sigma + m; % this one is slower
+end
 Im(Im<0)=1e-6;
 proj=log(I0./Im);
 end

Utilities/areTheseToolboxesInstalled.m

@@ -0,0 +1,18 @@
+function tf = areTheseToolboxesInstalled(requiredToolboxes)
+%ARETHESETOOLBOXESINSTALLED takes a cell array of toolbox names and checks whether they are currently installed
+% SYNOPSIS tf = areTheseToolboxesInstalled(requiredToolboxes)
+%
+% INPUT requiredToolboxes: cell array with toolbox names to test for. Eg. 
+%        {'MATLAB','Image Processing Toolbox'}
+%
+% OUTPUT tf: true or false if the required toolboxes are installed or not
+%%%%%%%%%%%%%%%%%%%%%%%%%%
+% http://stackoverflow.com/a/2061075/1485872
+
+% get all installed toolbox names
+v = ver;
+% collect the names in a cell array
+[installedToolboxes{1:length(v)}] = deal(v.Name);
+
+% check 
+tf = all(ismember(requiredToolboxes,installedToolboxes));

Utilities/plotImg.m

@@ -145,7 +145,11 @@ function plotImg(img,varargin)
 % % % % % %         % Limits of the colors
         case 'Clims'
             if default
-                climits=prctile(double(img(:)),[1 99]);
+                if any(size(img)>512) || ~areTheseToolboxesInstalled({'MATLAB','Statistics Toolbox'})
+                   climits=[0, 0.95*max(img(:))];
+                else
+                   climits=prctile(double(img(:)),[1 99]);
+                end
             else
                 if min(size(val))==1 && max(size(val))==2
                     climits=val;

Utilities/poissonrandom.m

@@ -0,0 +1,20 @@
+function km=poissonrandom(lambda)
+
+% Donald Knuth's poisson random generator
+
+% This sucks bananas because its O(lambda) and we want lambda~=10000...
+
+km=zeros(size(lambda));
+for ii=1:numel(lambda)
+
+    L=exp(-lambda(ii));
+    k=1;
+    p=1*rand;
+
+    while p>L
+        k=k+1;
+        p=p*rand;
+    end
+    km(ii)=k-1;
+end
+end