refactored sensing objective into domain, random inits

@sensingObjective/initialize.m

@@ -1,22 +1,21 @@
-function obj = initialize(obj, objectiveFunction, footprint, groundAlt, discretizationStep)
+function obj = initialize(obj, objectiveFunction, domain, discretizationStep)
     arguments (Input)
         obj (1,1) {mustBeA(obj, 'sensingObjective')};
         objectiveFunction (1, 1) {mustBeA(objectiveFunction, 'function_handle')};
-        footprint (:, 2) double;
-        groundAlt (1, 1) double = 0;
+        domain (1, 1) {mustBeGeometry};
         discretizationStep (1, 1) double = 1;
     end
     arguments (Output)
         obj (1,1) {mustBeA(obj, 'sensingObjective')};
     end
 
-    obj.groundAlt = groundAlt;
+    obj.groundAlt = domain.minCorner(3);
 
     % Extract footprint limits
-    xMin = min(footprint(:, 1));
-    xMax = max(footprint(:, 1));
-    yMin = min(footprint(:, 2));
-    yMax = max(footprint(:, 2));
+    xMin = min(domain.footprint(:, 1));
+    xMax = max(domain.footprint(:, 1));
+    yMin = min(domain.footprint(:, 2));
+    yMax = max(domain.footprint(:, 2));
 
     xGrid = unique([xMin:discretizationStep:xMax, xMax]);
     yGrid = unique([yMin:discretizationStep:yMax, yMax]);

@sensingObjective/initializeRandomMvnpdf.m

@@ -0,0 +1,27 @@
+function obj = initializeRandomMvnpdf(obj, domain, protectedRange, discretizationStep)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'sensingObjective')};
+        domain (1, 1) {mustBeGeometry};
+        protectedRange (1, 1) double = 1;
+        discretizationStep (1, 1) double = 1;
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'sensingObjective')};
+    end
+
+    % Set random objective position
+    mu = domain.minCorner;
+    while domain.distance(mu) < protectedRange
+        mu = domain.random();
+    end
+    mu = mu(1:2);
+
+    % Set random distribution parameters
+    sig = [2 + rand * 2, 1; 1, 2 + rand * 2];
+
+    % Set up random bivariate normal distribution function
+    objectiveFunction = @(x, y) mvnpdf([x(:), y(:)], mu, sig);
+
+    % Regular initialization
+    obj = obj.initialize(objectiveFunction, domain, discretizationStep);
+end

@sensingObjective/plot.m

@@ -18,7 +18,6 @@ function f = plot(obj, ind, f)
         o.HitTest = 'off';
         o.PickableParts = 'none';
         hold(f.CurrentAxes, "off");
-
     else
         hold(f.Children(1).Children(ind(1)), "on");
         o = surf(f.Children(1).Children(ind(1)), obj.X, obj.Y, repmat(obj.groundAlt, size(obj.X)), obj.values ./ max(obj.values, [], "all"), 'EdgeColor', 'none');

@sensingObjective/sensingObjective.m

@@ -12,7 +12,8 @@ classdef sensingObjective
     end
 
     methods (Access = public)
-        [obj] = initialize(obj, objectiveFunction, footprint, groundAlt, discretizationStep);
+        [obj] = initialize(obj, objectiveFunction, domain, discretizationStep);
+        [obj] = initializeRandomMvnpdf(obj, domain, protectedRange, discretizationStep);
         [f  ] = plot(obj, ind, f);
     end
 end