55 lines
2.2 KiB
Matlab
55 lines
2.2 KiB
Matlab
function [partitioning, agents] = partition(obj, agents, objective)
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arguments (Input)
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obj (1, 1) {mustBeA(obj, "agent")};
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agents (:, 1) {mustBeA(agents, "cell")};
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objective (1, 1) {mustBeA(objective, "sensingObjective")};
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end
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arguments (Output)
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partitioning (:, :) double;
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agents (:, 1) cell;
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end
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nAgents = size(agents, 1);
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gridM = size(objective.X, 1);
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gridN = size(objective.X, 2);
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nPoints = gridM * gridN;
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% Assess sensing performance of each agent at each sample point.
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% agentPerf is (nPoints x nAgents+1): the extra column is the
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% minimum threshold that must be exceeded for any assignment.
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agentPerf = zeros(nPoints, nAgents + 1);
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for aa = 1:nAgents
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if isa(agents{aa}.sensorModel, "sigmoidSensor")
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p = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
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[objective.X(:), objective.Y(:), zeros(nPoints, 1)]);
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elseif isa(agents{aa}.sensorModel, "rfSensor")
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otherSensorsIdx = [1:(aa - 1), (aa + 1):size(agents, 1)];
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otherSensors = agents(otherSensorsIdx);
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otherSensorsPos = cell2mat(cellfun(@(x) x.pos, otherSensors, "UniformOutput", false));
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otherSensors = cellfun(@(x) x.sensorModel, otherSensors, "UniformOutput", false);
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[p, ~, agents{aa}.sensorModel, otherSensors] = agents{aa}.sensorModel.sensorPerformance(agents{aa}.pos, ...
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[objective.X(:), objective.Y(:), zeros(nPoints, 1)], otherSensorsPos, otherSensors);
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for k = 1:numel(otherSensorsIdx)
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agents{otherSensorsIdx(k)}.sensorModel = otherSensors{k};
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end
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else
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error("?");
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end
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agentPerf(:, aa) = p(:);
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end
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agentPerf(:, nAgents + 1) = objective.sensorPerformanceMinimum;
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% Find which agent has highest performance at each point.
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% If the threshold column wins (idx == nAgents+1) the point is unassigned (0).
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[~, idx] = max(agentPerf, [], 2);
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assignedAgent = zeros(nPoints, 1);
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for pp = 1:nPoints
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if idx(pp) <= nAgents
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assignedAgent(pp) = idx(pp);
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end
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end
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partitioning = reshape(assignedAgent, gridM, gridN);
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end
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