reorganized code into separate files

sensingModels/@sigmoidSensor/initialize.m

@@ -0,0 +1,21 @@
+function obj = initialize(obj, alphaDist, betaDist, alphaPan, betaPan, alphaTilt, betaTilt)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'sigmoidSensor')}
+        alphaDist (1, 1) double;
+        betaDist (1, 1) double;
+        alphaPan (1, 1) double;
+        betaPan (1, 1) double;
+        alphaTilt (1, 1) double;
+        betaTilt (1, 1) double;
+    end
+    arguments (Output)
+        obj (1, 1) {mustBeA(obj, 'sigmoidSensor')}
+    end
+
+    obj.alphaDist = alphaDist;
+    obj.betaDist = betaDist;
+    obj.alphaPan = alphaPan;
+    obj.betaPan = betaPan;
+    obj.alphaTilt = alphaTilt;
+    obj.betaTilt = betaTilt;
+end

sensingModels/@sigmoidSensor/sense.m

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+function [values, positions] = sense(obj, agent, sensingObjective, domain, partitioning)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'sigmoidSensor')};
+        agent (1, 1) {mustBeA(agent, 'agent')};
+        sensingObjective (1, 1) {mustBeA(sensingObjective, 'sensingObjective')};
+        domain (1, 1) {mustBeGeometry};
+        partitioning (:, :) double;
+    end
+    arguments (Output)
+        values (:, 1) double;
+        positions (:, 3) double;
+    end
+
+    % Find positions for this agent's assigned partition in the domain
+    idx = partitioning == agent.index;
+    positions = [sensingObjective.X(idx), sensingObjective.Y(idx), zeros(size(sensingObjective.X(idx)))];
+
+    % Evaluate objective function at every point in this agent's
+    % assigned partiton
+    values = sensingObjective.values(idx);
+end

sensingModels/@sigmoidSensor/sensorPerformance.m

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+function value = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos)
+    arguments (Input)
+        obj (1, 1) {mustBeA(obj, 'sigmoidSensor')};
+        agentPos (1, 3) double;
+        agentPan (1, 1) double;
+        agentTilt (1, 1) double;
+        targetPos (:, 3) double;
+    end
+    arguments (Output)
+        value (:, 1) double;
+    end
+
+    d = vecnorm(agentPos - targetPos, 2, 2); % distance from sensor to target
+    x = vecnorm(agentPos(1:2) - targetPos(:, 1:2), 2, 2); % distance from sensor nadir to target nadir (i.e. distance ignoring height difference)
+    tiltAngle = atan2(targetPos(:, 3) - agentPos(3), x) - agentTilt;
+
+    % Membership functions
+    mu_d = 1 - (1 ./ (1 + exp(-obj.betaDist .* (d - obj.alphaDist)))); % distance
+    mu_p = 1; % pan
+    mu_t = (1 ./ (1 + exp(-obj.betaPan .* (tiltAngle + obj.alphaPan)))) - (1 ./ (1 + exp(-obj.betaPan .* (tiltAngle - obj.alphaPan)))); % tilt
+
+    value = mu_d .* mu_p .* mu_t * 1e12;
+end

sensingModels/@sigmoidSensor/sigmoidSensor.m

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+classdef sigmoidSensor
+    properties (SetAccess = private, GetAccess = public)
+        % Sensor parameters
+        alphaDist = NaN;
+        betaDist = NaN;
+        alphaPan = NaN;
+        betaPan = NaN;
+        alphaTilt = NaN;
+        betaTilt = NaN;
+    end
+
+    methods (Access = public)
+        [obj]               = initialize(obj, alphaDist, betaDist, alphaPan, betaPan, alphaTilt, betaTilt);
+        [values, positions] = sense(obj, agent, sensingObjective, domain, partitioning);
+        [value]             = sensorPerformance(obj, agentPos, agentPan, agentTilt, targetPos);
+    end
+end