full simulation with RF sensors

@agent/agent.m

@@ -50,8 +50,8 @@ classdef agent
             obj.commsGeometry = spherical;
         end
         [obj] = initialize(obj, pos, pan, tilt, collisionGeometry, sensorModel, guidanceModel, comRange, index, label);
-        [obj] = run(obj, domain, partitioning, t, index, agents);
-        [partitioning] = partition(obj, agents, objective)
+        [obj] = run(obj, domain, partitioning, t, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents);
+        [partitioning, agents] = partition(obj, agents, objective)
         [obj, f] = plot(obj, ind, f);
         updatePlots(obj);
     end

@agent/partition.m

@@ -1,4 +1,4 @@
-function [partitioning] = partition(obj, agents, objective)
+function [partitioning, agents] = partition(obj, agents, objective)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         agents (:, 1) {mustBeA(agents, "cell")};
@@ -6,6 +6,7 @@ function [partitioning] = partition(obj, agents, objective)
     end
     arguments (Output)
         partitioning (:, :) double;
+        agents (:, 1) cell;
     end
 
     nAgents = size(agents, 1);
@@ -18,8 +19,22 @@ function [partitioning] = partition(obj, agents, objective)
     % minimum threshold that must be exceeded for any assignment.
     agentPerf = zeros(nPoints, nAgents + 1);
     for aa = 1:nAgents
-        p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
-            [objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
+        if isa(agents{aa}.sensorModel, "sigmoidSensor")
+            p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
+                [objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
+        elseif isa(agents{aa}.sensorModel, "rfSensor")
+            otherSensorsIdx = [1:(aa - 1), (aa + 1):size(agents, 1)];
+            otherSensors = agents(otherSensorsIdx);
+            otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherSensors, "UniformOutput", false));
+            otherSensors = cellfun(@(x) x.sensorModel, otherSensors, "UniformOutput", false);
+            [p, ~, agents{aa}.sensorModel, otherSensors] = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
+                [objective.X(:), objective.Y(:), zeros(nPoints, 1)], otherSensorsPos, otherSensors);
+            for k = 1:numel(otherSensorsIdx)
+                agents{otherSensorsIdx(k)}.sensorModel = otherSensors{k};
+            end
+        else
+            error("?");
+        end
         agentPerf(:, aa) = p(:);
     end
     agentPerf(:, nAgents + 1) = objective.sensorPerformanceMinimum;

@agent/run.m

@@ -1,4 +1,4 @@
-function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing)
+function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleIntegrator, dampingCoeff, dt, optimizeSensorPointing, otherAgents)
     arguments (Input)
         obj (1, 1) {mustBeA(obj, "agent")};
         domain (1, 1) {mustBeGeometry};
@@ -9,6 +9,7 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
         dampingCoeff (1, 1) double = 2.0;
         dt (1, 1) double = 1.0;
         optimizeSensorPointing (1, 1) logical = false;
+        otherAgents (:, 1) cell = cell();
     end
     arguments (Output)
         obj (1, 1) {mustBeA(obj, "agent")};
@@ -33,6 +34,26 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
     maskedX = domain.objective.X(partitionMask);
     maskedY = domain.objective.Y(partitionMask);
 
+    if isa(obj.sensorModel, "rfSensor")
+        % Extract other agents' sensor models and positions once, outside the delta loop.
+        % Mask the full-grid RSS caches (filled by partition()) down to this agent's
+        % partition subset so sensorPerformance can reuse them for all perturbations.
+        otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherAgents, "UniformOutput", false));
+        otherSensors    = cellfun(@(x) x.sensorModel, otherAgents, "UniformOutput", false);
+        partitionIndices = find(partitionMask);
+        for kk = 1:numel(otherSensors)
+            if ~isempty(otherSensors{kk}.rssCache)
+                otherSensors{kk}.rssCache = otherSensors{kk}.rssCache(partitionIndices);
+            end
+        end
+        % Pre-mask this agent's own full-grid cache to the partition subset.
+        % Used for ii==1 (current position, no perturbation) to avoid recomputing.
+        baseSensorModel = obj.sensorModel;
+        if ~isempty(obj.sensorModel.rssCache)
+            baseSensorModel.rssCache = obj.sensorModel.rssCache(partitionIndices);
+        end
+    end
+
     if optimizeSensorPointing
         % Stash actual current sensor model tilt/azimuth before messing with it
         % in these following hypotheticals
@@ -58,7 +79,18 @@ function obj = run(obj, domain, partitioning, timestepIndex, index, useDoubleInt
         end
         
         % Compute performance values on partition
-        sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
+        if isa(obj.sensorModel, "sigmoidSensor")
+            sensorValues = obj.sensorModel.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))]); % S_n(omega, P_n) on W_n
+        elseif isa(obj.sensorModel, "rfSensor")
+            if ii == 1
+                sensorModelForDelta = baseSensorModel; % reuse partition-step cache; no recompute needed
+            else
+                sensorModelForDelta = obj.sensorModel.clearRssCache;
+            end
+            [sensorValues, ~, ~, ~] = sensorModelForDelta.sensorPerformance(pos, [maskedX, maskedY, zeros(size(maskedX))], otherSensorsPos, otherSensors);
+        else
+            error("?");
+        end
 
         % Rearrange data into image arrays
         F = NaN(size(partitionMask));