fix error messages in R2019b. these error messages were warnings in t…

…he earlier versions.

OASIS_matlab/deconvolveCa.m

@@ -108,28 +108,32 @@
 %% run deconvolution
 c = y;
 s = y;
+b0 = options.b;
+
 switch lower(options.method)
     case 'foopsi'  %% use FOOPSI
         if strcmpi(options.type, 'ar1')  % AR 1
             if options.smin<0
                 options.smin = abs(options.smin)*options.sn;
             end
             gmax = exp(-1/options.max_tau); 
-            [c, s, options.b, options.pars] = foopsi_oasisAR1(y-options.b, options.pars, options.lambda, ...
+            [c, s, options.b, options.pars] = foopsi_oasisAR1(y-b0, options.pars, options.lambda, ...
                 options.smin, options.optimize_b, options.optimize_pars, [], options.maxIter, ...
                 options.tau_range, gmax);
+            options.b = options.b + b0; 
         elseif strcmpi(options.type, 'ar2') % AR 2
             if options.smin<0
                 options.smin = abs(options.smin)*options.sn/max_ht(options.pars);
             end
-            [c, s, options.b, options.pars] = foopsi_oasisAR2(y-options.b, options.pars, options.lambda, ...
+            [c, s, options.b, options.pars] = foopsi_oasisAR2(y-b0, options.pars, options.lambda, ...
                 options.smin);
+            options.b = options.b + b0;
         elseif strcmpi(options.type, 'exp2')   % difference of two exponential functions
             kernel = exp2kernel(options.pars, options.window);
-            [c, s] = onnls(y-options.b, kernel, options.lambda, ...
+            [c, s] = onnls(y-b0, kernel, options.lambda, ...
                 options.shift, options.window);
         elseif strcmpi(options.type, 'kernel') % convolution kernel itself
-            [c, s] = onnls(y-options.b, options.pars, options.lambda, ...
+            [c, s] = onnls(y-b0, options.pars, options.lambda, ...
                 options.shift, options.window);
         else
             disp('to be done');
@@ -158,7 +162,7 @@
             %                     options.pars, options.sn, options.optimize_b, options.optimize_pars, ...
             %                     [], options.maxIter, options.thresh_factor);
             %             else
-            %                 [c, s] = oasisAR1(y-options.b, options.pars, options.lambda, ...
+            %                 [c, s] = oasisAR1(y-b0, options.pars, options.lambda, ...
             %                     options.smin);
             %             end
         elseif strcmpi(options.type, 'ar2')
@@ -170,17 +174,17 @@
             %                     options.pars, options.sn, options.optimize_b, options.optimize_pars, ...
             %                     [], options.maxIter, options.thresh_factor);
             %             else
-            %                 [c, s] = oasisAR2(y-options.b, options.pars, options.lambda, ...
+            %                 [c, s] = oasisAR2(y-b0, options.pars, options.lambda, ...
             %                     options.smin);
             %             end
         elseif strcmpi(options.type, 'exp2')   % difference of two exponential functions
             d = options.pars(1);
             r = options.pars(2);
             options.pars = (exp(log(d)*(1:win)) - exp(log(r)*(1:win))) / (d-r); % convolution kernel
-            [c, s] = onnls(y-options.b, options.pars, options.lambda, ...
+            [c, s] = onnls(y-b0, options.pars, options.lambda, ...
                 options.shift, options.window, [], [], [], options.smin);
         elseif strcmpi(options.type, 'kernel') % convolution kernel itself
-            [c, s] = onnls(y-options.b, options.pars, options.lambda, ...
+            [c, s] = onnls(y-b0, options.pars, options.lambda, ...
                 options.shift, options.window, [], [], [], options.smin);
         else
             disp('to be done');
@@ -194,10 +198,12 @@
 
 % deal with large residual
 if options.remove_large_residuals && strcmpi(options.method, 'foopsi')
-    ind = (abs(smooth(y-c, 3))>options.smin);
+    ind = (abs(fastsmooth(y-c, 3))>options.smin) & (c>options.smin*5);
     c(ind) = max(0, y(ind));
 end
 
+% avoid nan output 
+c(isnan(c) | isinf(c)) = 0; 
 
 function options=parseinputs(varargin)
 %% parse input variables

OASIS_matlab/examples/Paper/fig3.m

@@ -31,7 +31,7 @@
 set(gca, 'ytick', 0:2);
 ylabel('Fluor.');
 box off;
-legend('Data', 'Truth', 'OASIS', 'CVX', 'location', 'northeast', 'orientation', 'horizental');
+legend('Data', 'Truth', 'OASIS', 'CVX', 'location', 'northeast', 'orientation', 'horizontal');
 % s
 axes('position', [.05, .18, .95, .37]);
 hold on;

OASIS_matlab/examples/Paper/fig5.m

@@ -32,7 +32,7 @@
 plot(trueC(1, :), 'color', col{3}/255, 'linewidth', 3); 
 plot(c, 'color', col{1}/255); 
 plot(c_t, 'color', col{2}/255); 
-legend('Data', 'Truth', 'Thresh', 'L1', 'orientation', 'horizental'); 
+legend('Data', 'Truth', 'Thresh', 'L1', 'orientation', 'horizontal'); 
 ylim([ymin, ymax]); 
 xlim([0, 452]); 
 set(gca, 'xtick', 0:150:500); 
@@ -116,7 +116,7 @@
 plot(trueC(1, :), 'color', col{3}/255, 'linewidth', 3); 
 plot(c, 'color', col{1}/255); 
 plot(c_t, 'color', col{2}/255); 
-legend('Data', 'Truth', 'Thresh', 'L1', 'orientation', 'horizental'); 
+legend('Data', 'Truth', 'Thresh', 'L1', 'orientation', 'horizontal'); 
 ylim([ymin, ymax]); 
 xlim([0, 452]); 
 set(gca, 'xtick', 0:150:500); 

OASIS_matlab/examples/Paper/test_all.m

@@ -1,3 +1,6 @@
+if ~exist('fig', 'dir')
+    mkdir('fig'); 
+end
 fig1; 
 fig2; 
 fig3; 

OASIS_matlab/examples/show_results.m

@@ -18,9 +18,9 @@
 ylabel('Fluor.');
 box off;
 if plot_cvx
-    legend('Data', 'Truth', 'OASIS', 'CVX', 'location', 'northeast', 'orientation', 'horizental');
+    legend('Data', 'Truth', 'OASIS', 'CVX', 'location', 'northeast', 'orientation', 'horizontal');
 else
-    legend('Data', 'Truth', 'OASIS', 'location', 'northeast', 'orientation', 'horizental');
+    legend('Data', 'Truth', 'OASIS', 'location', 'northeast', 'orientation', 'horizontal');
 end
 % s
 axes('position', [.05, .18, .95, .37]);

OASIS_matlab/packages/oasis/constrained_oasisAR1.m

@@ -82,6 +82,8 @@
 
 %% optimize parameters
 tol = 1e-4;
+dphi = 0; 
+
 % flag_lam = true;
 if ~optimize_b   %% don't optimize the baseline b
     %% initialization
@@ -227,6 +229,7 @@ function update_lam_b() % estimate lambda  & b
    g_range = [0, 1];  
 end
 %% find the optimal g and get the warm started active_set
+h = []; 
 g = fminbnd(@rss_g, g_range(1), g_range(2));
 yp = y - lam*(1-g);
 for m=1:len_active_set

OASIS_matlab/packages/oasis/foopsi_oasisAR1.m

@@ -148,6 +148,7 @@
 c = zeros(size(y));     % the optimal denoised trace
 
 %% find the optimal g and get the warm started active_set
+h = []; 
 g = fminbnd(@rss_g, g_range(1), g_range(2));
 yp = y - lam*(1-g);
 for m=1:len_active_set

OASIS_matlab/packages/oasis/oasisAR1.m

@@ -81,7 +81,7 @@
 
     %% backtrack until violations fixed
     while (~isnan(ii_prev)) && (active_set(ii,1)/active_set(ii,2)<...
-            active_set(ii_prev,1)/active_set(ii_prev,2)*g^(active_set(ii_prev,4))+smin)
+            max(0, active_set(ii_prev,1)/active_set(ii_prev,2)*g^(active_set(ii_prev,4)))+smin)
         ii_next = ii;
         ii = ii_prev;
         active_set(ii,1) = active_set(ii,1) + active_set(ii_next,1)* (g^(active_set(ii,4)));

OASIS_matlab/packages/oasis/thresholded_oasisAR1.m

@@ -245,6 +245,7 @@
    g_range = [0, 1];  
 end
 %% find the optimal g and get the warm started active_set
+h = []; 
 g = fminbnd(@rss_g, g_range(1), g_range(2));
 yp = y;
 for m=1:len_active_set

OASIS_matlab/packages/oasis/thresholded_oasisAR2.m

@@ -138,7 +138,7 @@
             break;
         end
         % update g
-        if and(optimize_g, ~g_converged);
+        if and(optimize_g, ~g_converged)
             g0 = g;
             g = update_g(y-b, g, spks);
             smin = choose_smin(g, sn, 0.9999);