Merge branch 'abhinab' of https://github.com/ComputationalScienceLaboratory/DATools into abhinab

Merged the remote branch

Author: Abhinab Bhattacharjee

.gitignore

@@ -1,2 +1,5 @@
 
 *.asv
+*.mat
+*.png
+*.fig

README.md

@@ -1 +1,3 @@
-Nothing here but the wind.
+A set of Data assimilation tools. Filter smoothers, ensemble and variational methods, localization, etc.
+
+An active work in progress.

src/+datools/+error/Error.m

@@ -1,11 +1,11 @@
 classdef Error < handle
-    
+
     methods
-        
+
         function xp = adderr(~, ~, x)
             xp = x;
         end
-        
+
     end
-    
+
 end

src/+datools/+error/Gaussian.m

@@ -1,29 +1,29 @@
 classdef Gaussian < datools.error.Error
-    
+
     properties
         CovarianceSqrt
         Bias
     end
-    
+
     methods
-        
+
         function obj = Gaussian(varargin)
             p = inputParser;
             addOptional(p, 'CovarianceSqrt', 1);
             addOptional(p, 'Bias', 0);
             parse(p, varargin{:});
-            
+
             s = p.Results;
-            
+
             obj.CovarianceSqrt = s.CovarianceSqrt;
             obj.Bias = s.Bias;
         end
-        
+
         function xp = adderr(obj, ~, x)
-            A = obj.CovarianceSqrt*randn(size(x, 1), size(x, 2));
+            A = obj.CovarianceSqrt * randn(size(x, 1), size(x, 2));
             xp = x + A + obj.Bias;
         end
-        
+
     end
-    
+
 end

src/+datools/+error/Laplace.m

@@ -1,31 +1,31 @@
 classdef Laplace < datools.error.Error
-    
+
     properties
         CovarianceSqrt
         Bias
     end
-    
+
     methods
-        
+
         function obj = Laplace(varargin)
             p = inputParser;
             addOptional(p, 'CovarianceSqrt', 1);
             addOptional(p, 'Bias', 0);
             parse(p, varargin{:});
-            
+
             s = p.Results;
-            
+
             obj.CovarianceSqrt = s.CovarianceSqrt;
             obj.Bias = s.Bias;
         end
-        
+
         function xp = adderr(obj, ~, x)
-            X = obj.CovarianceSqrt*randn(size(x, 1), size(x, 2));
+            X = obj.CovarianceSqrt * randn(size(x, 1), size(x, 2));
             Z = exprnd(1, 1, size(x, 2));
-            Y = sqrt(Z).*X;
+            Y = sqrt(Z) .* X;
             xp = x + Y + obj.Bias;
         end
-        
+
     end
-    
+
 end

src/+datools/+error/Logistic.m

@@ -1,52 +1,52 @@
 classdef Logistic < datools.error.Error
-    
+
     properties
         State
         Scale
         R
     end
-    
+
     methods
-        
+
         function obj = Logistic(varargin)
-          p = inputParser;
+            p = inputParser;
             p.KeepUnmatched = true;
             addParameter(p, 'NumVars', 1);
             addParameter(p, 'Scale', 2*sqrt(3));
             addParameter(p, 'R', 3.99999);
             parse(p, varargin{:});
-            
+
             s = p.Results;
-            
+
             obj.Scale = s.Scale;
-            obj.R    = s.R;
-            
+            obj.R = s.R;
+
             kept = p.Unmatched;
-            
+
             p = inputParser;
             addParameter(p, 'InitialState', rand(s.NumVars, 1));
             parse(p, kept);
-            
+
             s = p.Results;
-            
+
             obj.State = s.InitialState;
-            
+
         end
-        
+
         function xp = adderr(obj, ~, x)
             r = obj.R;
-            
+
             z = obj.State;
-            
-            z = r*z.*(1 - z);
-            
+
+            z = r * z .* (1 - z);
+
             obj.State = z;
-            
-            err = obj.Scale*(z - 0.5);
-            
+
+            err = obj.Scale * (z - 0.5);
+
             xp = x + err;
         end
-        
+
     end
-    
+
 end

src/+datools/+error/Tent.m

@@ -1,51 +1,51 @@
 classdef Tent < datools.error.Error
-    
+
     properties
         State
         Scale
         Mu
     end
-    
+
     methods
-        
+
         function obj = Tent(varargin)
             p = inputParser;
             p.KeepUnmatched = true;
             addParameter(p, 'NumVars', 1);
             addParameter(p, 'Scale', 2*sqrt(3));
             addParameter(p, 'Mu', 1.99999);
             parse(p, varargin{:});
-            
+
             s = p.Results;
-            
+
             obj.Scale = s.Scale;
-            obj.Mu    = s.Mu;
-            
+            obj.Mu = s.Mu;
+
             kept = p.Unmatched;
-            
+
             p = inputParser;
             addParameter(p, 'InitialState', rand(s.NumVars, 1));
             parse(p, kept);
-            
+
             s = p.Results;
-            
+
             obj.State = s.InitialState;
         end
-        
+
         function xp = adderr(obj, ~, x)
             mu = obj.Mu;
-            
+
             z = obj.State;
-            
-            z = mu*min(z, 1 - z);
-            
+
+            z = mu * min(z, 1-z);
+
             obj.State = z;
-            
-            err = obj.Scale*(z - 0.5);
-            
+
+            err = obj.Scale * (z - 0.5);
+
             xp = x + err;
         end
-        
+
     end
-    
+
 end

src/+datools/+error/Triangle.m

@@ -0,0 +1,35 @@
+classdef Triangle < datools.error.Error
+
+    properties
+        Lower
+        Middle
+        Upper
+    end
+
+    methods
+
+        function obj = Triangle(varargin)
+            p = inputParser;
+            addOptional(p, 'Lower', -1);
+            addOptional(p, 'Middle', 0);
+            addOptional(p, 'Upper', 1);
+
+            parse(p, varargin{:});
+
+            s = p.Results;
+
+            obj.Lower = s.Lower;
+            obj.Middle = s.Middle;
+            obj.Upper = s.Upper;
+        end
+
+        function xp = adderr(obj, ~, x)
+            td = makedist('Triangular', obj.Lower, obj.Middle, obj.Upper);
+
+            A = td.random([size(x, 1), size(x, 2)]);
+            xp = x + A;
+        end
+
+    end
+
+end

src/+datools/+examples/+error/logisticmapbifurcation.m

@@ -8,23 +8,23 @@
 ys = zeros(nr, addpoints);
 
 for mui = 1:nr
-    
+
     r = rs(mui);
-    
+
     tenterror = datools.error.Logistic('R', r, 'Scale', 1);
-    
+
     % initial evolve
     for i = 1:initialevolve
         tenterror.adderr(0, 0);
     end
-    
+
     % add points
     for i = 1:addpoints
         y = tenterror.adderr(0, 0.5);
         xs(mui, i) = r;
         ys(mui, i) = y;
     end
-    
+
 end
 
 p = scatter(xs(:), ys(:), 1, '.k');

src/+datools/+examples/+error/lorenz63bifurcation.m

@@ -11,39 +11,39 @@
 zs = zeros(nrho, addpoints);
 
 for rhoi = 1:nrho
-    
+
     rho = rhos(rhoi);
-    
+
     model = otp.lorenz63.presets.Canonical;
     model.Parameters.rho = rho;
-    
+
     model.TimeSpan = [0, initialevolve] + model.TimeSpan(1);
-    
-    [~, yi] = ode45(model.Rhs.F, [0 initialevolve], model.Y0);
-    
+
+    [~, yi] = ode45(model.Rhs.F, [0, initialevolve], model.Y0);
+
     model.TimeSpan = model.TimeSpan + tspandt;
     model.Y0 = yi(end, :).';
-    
+
     rhoplot(rhoi, :) = rho;
     [~, y] = ode45(model.Rhs.F, ...
         linspace(model.TimeSpan(1), model.TimeSpan(end), addpoints), ...
         model.Y0);
-    
+
     xs(rhoi, :) = y(:, 1).';
     ys(rhoi, :) = y(:, 2).';
     zs(rhoi, :) = y(:, 3).';
-    
+
 end
 
 xmin = min(xs(:));
 xmax = max(zs(:));
 zmin = min(zs(:));
 zmax = max(zs(:));
 
-xs = (xs(:) + xmin)/diff([xmax, xmin]);
-zs = (zs(:) + xmin)/diff([zmax, zmin]);
+xs = (xs(:) + xmin) / diff([xmax, xmin]);
+zs = (zs(:) + xmin) / diff([zmax, zmin]);
 
-ds = sqrt(xs.^2 + zs.^2);
+ds = sqrt(xs.^2+zs.^2);
 
 [~, si] = sort(ds);
 
@@ -56,8 +56,8 @@
 
 cax = gca;
 
-set(cax, 'box','off','XTickLabel',[],'XTick',[],'YTickLabel',[],'YTick',[])
-set(gca,'LooseInset',get(gca,'TightInset'));
-set(gca,'XColor','none')
-set(gca,'YColor','none')
-set(gcf,'color','white')
+set(cax, 'box', 'off', 'XTickLabel', [], 'XTick', [], 'YTickLabel', [], 'YTick', [])
+set(gca, 'LooseInset', get(gca, 'TightInset'));
+set(gca, 'XColor', 'none')
+set(gca, 'YColor', 'none')
+set(gcf, 'color', 'white')