Fixed plotting, now adapted to object oriented.

ternary_frap.m

@@ -30,10 +30,14 @@ plot(T.x, Ternary_model.gamma0(T.x, T.a, T.b, T.e_g0, T.o_g0));
 axis([0, 3, 0, 1])
 figure;
 plot(Ternary_model.gamma0(T.x, T.a, T.b, T.e_g0, T.o_g0),...
-     Ternary_model.spacing(Ternary_model.gamma0(T.x, T.a, T.b, T.e_g0, T.o_g0), T.a, T.b, T.e_g0, T.o_g0));
+     Ternary_model.spacing(Ternary_model.gamma0(T.x, T.a, T.b, T.e_g0, T.o_g0),...
+     T.a, T.b, T.e_g0, T.o_g0));
 %% Fit with experimental BCs
-s = sol(1:end, 1:30)./max(sol(1:end, 1:30))/1.022;
-ts = t(1:end)';
+T = Ternary_model(2, 'FRAP', [], linspace(0.0, 400, 5000));
+T.solve_tern_frap();
+x_seed = 60;
+s = T.sol(1:end, 1:30)./max(T.sol(1:end, 1:30))/1.022;
+ts = T.t(1:end)';
 f_min = @(x) to_minimize(s, ts, x, 'simple_drop', s(:, end));
 opt = optimset('MaxFunEvals', 2000, 'PlotFcns',@optimplotfval);
 x_seed = fminsearch(f_min, x_seed, opt);
@@ -41,9 +45,9 @@ x_seed = fminsearch(f_min, x_seed, opt);
 [cost, v_fit, r_n, v_fit_end] = to_minimize(s, ts, x_seed, 'simple_drop', s(:, end));
 %% Plot for 
 figure; hold on;
-plot(s(1:2:100, :)', 'Color', [0.12156   0.4666666   0.7058823], 'LineWidth', 1.5);
-% plot(v_fit(1:2:100, :)', '--', 'Color', [1.   0.49803   0.0549], 'LineWidth', 1.5);
+plot(s(1:10:400, :)', 'Color', [0.12156   0.4666666   0.7058823], 'LineWidth', 1.5);
+plot(v_fit(1:10:400, :)', '--', 'Color', [1.   0.49803   0.0549], 'LineWidth', 1.5);
 make_graph_pretty('$x [\mu m]$', 'intensity [a.u.]', '');
-print('Timecourse_model_only.png','-dpng')
+print('Timecourse_model_only2.png','-dpng')