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fixed performance plot after 50th timestep

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This commit is contained in:
Kevin Dee
2025-12-01 22:58:38 -08:00
parent f296fd2803
commit f9aa2eb9d4
2 changed files with 15 additions and 17 deletions
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25
@agent/run.m
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@@ -29,17 +29,17 @@ function obj = run(obj, domain, partitioning, t)
obj.performance = [obj.performance, sum(C(~isnan(C)))]; obj.performance = [obj.performance, sum(C(~isnan(C)))];
% Compute gradient on agent's performance % Compute gradient on agent's performance
[gradSensorPerformanceX, gradSensorPerformanceY] = gradient(S, domain.objective.discretizationStep); % grad S_n
[gradObjectiveX, gradObjectiveY] = gradient(F, domain.objective.discretizationStep); % grad f
gradS = cat(3, gradSensorPerformanceX, gradSensorPerformanceY, zeros(size(gradSensorPerformanceX))); % grad S_n
gradF = cat(3, gradObjectiveX, gradObjectiveY, zeros(size(gradObjectiveX))); % grad f
[gradCX, gradCY] = gradient(C, domain.objective.discretizationStep); % grad C; [gradCX, gradCY] = gradient(C, domain.objective.discretizationStep); % grad C;
gradC = cat(3, gradCX, gradCY, zeros(size(gradCX))); % temp zeros for gradCZ gradC = cat(3, gradCX, gradCY, zeros(size(gradCX))); % temp zeros for gradCZ
nGradC = vecnorm(gradC, 2, 3); nGradC = vecnorm(gradC, 2, 3);
if obj.debug if obj.debug
% Compute additional component-level values for diagnosing issues
[gradSensorPerformanceX, gradSensorPerformanceY] = gradient(S, domain.objective.discretizationStep); % grad S_n
[gradObjectiveX, gradObjectiveY] = gradient(F, domain.objective.discretizationStep); % grad f
gradS = cat(3, gradSensorPerformanceX, gradSensorPerformanceY, zeros(size(gradSensorPerformanceX))); % grad S_n
gradF = cat(3, gradObjectiveX, gradObjectiveY, zeros(size(gradObjectiveX))); % grad f
ii = 8; ii = 8;
hold(obj.debugFig.Children(1).Children(ii), "on"); hold(obj.debugFig.Children(1).Children(ii), "on");
imagesc(obj.debugFig.Children(1).Children(ii), F./max(F, [], 'all')); imagesc(obj.debugFig.Children(1).Children(ii), F./max(F, [], 'all'));
@@ -96,26 +96,21 @@ function obj = run(obj, domain, partitioning, t)
end end
end end
% grad(s*f) = grad(f) * s + f * grad(s) - product rule (f scalar field, s vector field) % Use largest grad(C) value to find the direction of the next position
% gradC = S .* abs(gradF) + F .* abs(gradS); % second term provides altitude [xNextIdx, yNextIdx] = find(nGradC == max(nGradC, [], 'all'));
% normalize in x3 dimension and find the direction which maximizes ascent
% nGradC = vecnorm(gradC, 2, 3);
[xNextIdx, yNextIdx] = find(nGradC == max(nGradC, [], 'all')); % find direction of steepest increase
roundingScale = 10^-log10(domain.objective.discretizationStep); roundingScale = 10^-log10(domain.objective.discretizationStep);
pNext = [floor(roundingScale .* mean(unique(domain.objective.X(:, xNextIdx))))./roundingScale, floor(roundingScale .* mean(unique(domain.objective.Y(yNextIdx, :))))./roundingScale, obj.pos(3)]; % have to do some unfortunate rounding here soemtimes pNext = [floor(roundingScale .* mean(unique(domain.objective.X(:, xNextIdx))))./roundingScale, floor(roundingScale .* mean(unique(domain.objective.Y(yNextIdx, :))))./roundingScale, obj.pos(3)]; % have to do some unfortunate rounding here soemtimes
% Determine next position
vDir = (pNext - obj.pos)./norm(pNext - obj.pos, 2); vDir = (pNext - obj.pos)./norm(pNext - obj.pos, 2);
rate = 0.2 - 0.004 * t; rate = 0.2 - 0.004 * t;
nextPos = obj.pos + vDir * rate; nextPos = obj.pos + vDir * rate;
% Move to next position % Move to next position
% (dynamics not modeled at this time)
obj.lastPos = obj.pos; obj.lastPos = obj.pos;
obj.pos = nextPos; obj.pos = nextPos;
% Calculate movement
d = obj.pos - obj.collisionGeometry.center;
% Reinitialize collision geometry in the new position % Reinitialize collision geometry in the new position
d = obj.pos - obj.collisionGeometry.center;
obj.collisionGeometry = obj.collisionGeometry.initialize([obj.collisionGeometry.minCorner; obj.collisionGeometry.maxCorner] + d, obj.collisionGeometry.tag, obj.collisionGeometry.label); obj.collisionGeometry = obj.collisionGeometry.initialize([obj.collisionGeometry.minCorner; obj.collisionGeometry.maxCorner] + d, obj.collisionGeometry.tag, obj.collisionGeometry.label);
end end

7
@miSim/plotPerformance.m
View File

@@ -15,14 +15,17 @@ function obj = plotPerformance(obj)
% Plot current cumulative performance % Plot current cumulative performance
hold(obj.fPerf.Children(1), 'on'); hold(obj.fPerf.Children(1), 'on');
o = plot(obj.fPerf.Children(1), obj.perf(end, :)); o = plot(obj.fPerf.Children(1), obj.perf(end, :));
o.XData = NaN(size(o.XData)); % correct time will be set at runtime warning('off', 'MATLAB:gui:array:InvalidArrayShape'); % suppress this warning to avoid polluting output
o.XData = NaN(1, obj.maxIter); % correct time will be set at runtime
o.YData = [0, NaN(1, obj.maxIter - 1)];
hold(obj.fPerf.Children(1), 'off'); hold(obj.fPerf.Children(1), 'off');
% Plot current agent performance % Plot current agent performance
for ii = 1:(size(obj.perf, 1) - 1) for ii = 1:(size(obj.perf, 1) - 1)
hold(obj.fPerf.Children(1), 'on'); hold(obj.fPerf.Children(1), 'on');
o = [o; plot(obj.fPerf.Children(1), obj.perf(ii, :))]; o = [o; plot(obj.fPerf.Children(1), obj.perf(ii, :))];
o(end).XData = NaN(size(o(end).XData)); % correct time will be set at runtime o(end).XData = NaN(1, obj.maxIter); % correct time will be set at runtime
o(end).YData = [0, NaN(1, obj.maxIter - 1)];
hold(obj.fPerf.Children(1), 'off'); hold(obj.fPerf.Children(1), 'off');
end end