classdef sensingObjective % Sensing objective definition parent class properties (SetAccess = private, GetAccess = public) label = ""; groundAlt = 0; groundPos = [0, 0]; discretizationStep = 1; objectiveFunction = @(x, y) 0; % define objective functions over a grid in this manner X = []; Y = []; values = []; end methods (Access = public) function obj = initialize(obj, objectiveFunction, footprint, groundAlt, discretizationStep) arguments (Input) obj (1,1) {mustBeA(obj, 'sensingObjective')}; objectiveFunction (1, 1) {mustBeA(objectiveFunction, 'function_handle')}; footprint (2, :) double; groundAlt (1, 1) double = 0; discretizationStep (1, 1) double = 1; end arguments (Output) obj (1,1) {mustBeA(obj, 'sensingObjective')}; end obj.groundAlt = groundAlt; % Extract footprint limits xMin = min(footprint(1, :)); xMax = max(footprint(1, :)); yMin = min(footprint(2, :)); yMax = max(footprint(2, :)); xGrid = unique([xMin:discretizationStep:xMax, xMax]); yGrid = unique([yMin:discretizationStep:yMax, yMax]); % Store grid points for plotting later [obj.X, obj.Y] = meshgrid(xGrid, yGrid); % Evaluate function over grid points obj.objectiveFunction = objectiveFunction; obj.values = reshape(obj.objectiveFunction(obj.X, obj.Y), size(obj.X)); % store ground position idx = obj.values == max(obj.values, [], "all"); obj.groundPos = [obj.X(idx), obj.Y(idx)]; end function f = plot(obj, f) arguments (Input) obj (1,1) {mustBeA(obj, 'sensingObjective')}; f (1,1) {mustBeA(f, 'matlab.ui.Figure')} = figure; end arguments (Output) f (1,1) {mustBeA(f, 'matlab.ui.Figure')}; end % Create axes if they don't already exist f = firstPlotSetup(f); % Plot gradient on the "floor" of the domain hold(f.CurrentAxes, "on"); s = surf(obj.X, obj.Y, repmat(obj.groundAlt, size(obj.X)), obj.values ./ max(obj.values, [], "all"), 'EdgeColor', 'none'); s.HitTest = 'off'; s.PickableParts = 'none'; hold(f.CurrentAxes, "off"); end end end