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Updating flocking analysis to save AIS/TE from all parameters tested in an autoembedding process

This commit is contained in:
Joseph Lizier 2020-09-03 22:20:03 +10:00
parent 4c95b4ee86
commit 8ecb512ce0
2 changed files with 21 additions and 5 deletions
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24
demos/octave/FlockingAnalysis/runAnalysis.m
View File

@ -60,6 +60,10 @@ else
end
% Step 1: Auto-embed if required:
% Set the lag to 1 as a dummy if we are optimising over that later as well:
if (~isfield(properties, 'lag'))
properties.lag = 1;
end
if (isfield(properties, 'kRange') || isfield(properties, 'tauRange'))
% If any one of these two ranges weren't supplied, set the range variables
% to the value of the corresponding non-range variable:
@ -69,20 +73,21 @@ if (isfield(properties, 'kRange') || isfield(properties, 'tauRange'))
if (~isfield(properties, 'tauRange'))
properties.tauRange = properties.tau;
end
% Also set the lag to 1 as a dummy if we are optimising over that later as well:
if (~isfield(properties, 'lag'))
properties.lag = 1;
end
% Ask generateObservations to only return the target samples for the AIS calculation
properties.destSamplesOnly = true;
% Optimise k and tau
maxAIS = -inf;
maxAISk = properties.kRange(1);
maxAIStau = properties.tauRange(1);
aisForKAndTau = zeros(length(properties.kRange), length(properties.tauRange));
kIndex = 0;
tauIndex = 0;
for k = properties.kRange
kIndex = kIndex + 1;
properties.k = k;
minTau = min(properties.tauRange);
for tau = properties.tauRange
tauIndex = tauIndex + 1;
if ((k == 1) && (tau > minTau))
% We only need compute k=1 for a single tau
continue;
@ -105,6 +110,7 @@ if (isfield(properties, 'kRange') || isfield(properties, 'tauRange'))
maxAISk = k;
maxAIStau = tau;
end
aisForKAndTau(kIndex, tauIndex) = ais;
end
end
% Optimisation is complete:
@ -142,7 +148,10 @@ if (isfield(properties, 'lagRange'))
% Caller asks us to maximise the TE over a given range:
maxTE = -inf;
maxTElag = properties.lagRange(1);
teForLag = zeros(length(properties.lagRange), 1);
lagIndex = 0;
for lag = properties.lagRange
lagIndex = lagIndex + 1;
properties.lag = lag;
% Generate the observations for k,tau,lag:
[D, Dpast, S, ~, safeDynamicCorrelationExclusionSamples] = generateObservations(properties);
@ -160,6 +169,7 @@ if (isfield(properties, 'lagRange'))
maxTE = te;
maxTElag = lag;
end
teForLag(lagIndex) = te;
end
% Optimisation is complete:
properties.lag = maxTElag;
@ -190,6 +200,12 @@ end
% Compute TE with no output arguments so that results are saved
computeTE(S, D, Dpast, properties);
save(properties.resultsFile, 'ais', '-append'); % Add the AIS into the results file as well
if (isfield(properties, 'kRange') || isfield(properties, 'tauRange'))
save(properties.resultsFile, 'aisForKAndTau', '-append'); % Add the AISs computed in auto-embedding
end
if (isfield(properties, 'lagRange'))
save(properties.resultsFile, 'teForLag', '-append'); % Add the TEs computed in optimising the source-target lag
end
end

2
demos/octave/FlockingAnalysis/watchRawMovement.m
View File

@ -53,11 +53,11 @@ if (~zoomIn)
axis([minX, maxX, minY, maxY]);
end
% Need to set this so that the axes don't keep updating
set(gca,'NextPlot','replacechildren') ;
end
fprintf('Loading data in %s (%d missing values)\n', dataFileName, numMissing);
for t = 1:size(x, 1)
set(gca,'NextPlot','replacechildren') ;
if (properties.data3d)
plot3(x(t,:), y(t,:), z(t,:), 'x')
else