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fixed weirdness

This commit is contained in:
David Shorten 2019-02-01 15:35:26 +11:00
parent ea8a322b61
commit 4985def021
1 changed files with 18 additions and 13 deletions
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31
java/source/infodynamics/measures/spiking/integration/TransferEntropyCalculatorSpikingIntegration.java
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@ -30,7 +30,7 @@ public class TransferEntropyCalculatorSpikingIntegration implements
protected final static boolean USE_POINT_ITSELF = false;
protected final static boolean TRIM_RADII = false;
protected final static boolean USE_SAME_RADII = true;
protected final static boolean USE_SAME_RADII = false;
/**
* Number of past destination spikes to consider (akin to embedding length)
@ -565,15 +565,17 @@ public class TransferEntropyCalculatorSpikingIntegration implements
// Find the Knns nearest neighbour matches to this event,
// with the same previous spiker and the next.
// TODO Add dynamic exclusion time later
/*int num_after_event = 0;
int extra_to_search = -1;
boolean leave_out = false;
if(timeToNextSpikeSincePreviousDestSpike < 0.01 || timeToNextSpikeSincePreviousDestSpike > 0.5) {
continue;
}
while(num_after_event < Knns) {
extra_to_search++;
num_after_event = 0;
PriorityQueue<NeighbourNodeData> nnPQ =
kdTreesJoint[NEXT_DEST].findKNearestNeighbours(Knns + extra_to_search,
kdTreesJoint[NEXT_DEST].findKNearestNeighbours(Knns + extra_to_search,
eventIndexWithinType);
for (int j = 0; j < Knns + extra_to_search; j++) {
@ -596,7 +598,7 @@ public class TransferEntropyCalculatorSpikingIntegration implements
PriorityQueue<NeighbourNodeData> nnPQ =
kdTreesJoint[NEXT_DEST].findKNearestNeighbours(Knns,
eventIndexWithinType);
eventIndexWithinType);
// Find eps_{x,y,z} as the maximum x, y and z norms amongst this set:
double radius_sourcePast = 0.0;
@ -606,16 +608,19 @@ public class TransferEntropyCalculatorSpikingIntegration implements
for (int j = 0; j < Knns; j++) {
// Take the furthest remaining of the nearest neighbours from the PQ:
NeighbourNodeData nnData = nnPQ.poll();
if (nnData.norms[0] > radius_sourcePast) {
//if(eventTimings[NEXT_DEST].elementAt(nnData.sampleIndex)[2][0] >
// timeToNextSpikeSincePreviousDestSpike) {
if (nnData.norms[0] > radius_sourcePast) {
radius_sourcePast = nnData.norms[0];
}
if (nnData.norms[1] > radius_destPast) {
}
if (nnData.norms[1] > radius_destPast) {
radius_destPast = nnData.norms[1];
}
if (nnData.norms[2] > radius_destNext) {
}
if (nnData.norms[2] > radius_destNext) {
radius_destNext = nnData.norms[2];
radius_destNext_sampleIndex = nnData.sampleIndex;
}
}
//}
}
if (!TRIM_RADII) {
double radius_max = Math.max(Math.max(radius_sourcePast, radius_destPast), radius_destNext);
@ -743,7 +748,7 @@ public class TransferEntropyCalculatorSpikingIntegration implements
// and that the previous source spike did not occur after the window
// (this is possible since our neighbour match hasn't checked for the next spike time)
if ((matchingHistoryTimeToNextSpike >= timeToNextSpikeSincePreviousDestSpike - radius_destNext) &&
(matchingHistoryTimeToPrevSourceSpike <= timeToNextSpikeSincePreviousDestSpike + radius_destNext)) {
(matchingHistoryTimeToPrevSourceSpike <= timeToNextSpikeSincePreviousDestSpike + radius_destNext)) {
/*// Real start of window cannot be before previous destination spike:
double realStartOfWindow = Math.max(timeToNextSpikeSincePreviousDestSpike, 0);
@ -918,9 +923,9 @@ public class TransferEntropyCalculatorSpikingIntegration implements
// estimates the log rates.
// Inferred rates raw:
double rawRateGivenSourceAndDest = ((double) (Knns)) / timeInWindowWithMatchingJointHistories;
if(rawRateGivenSourceAndDest > 50) {
/*if(rawRateGivenSourceAndDest > 50) {
System.out.println("SUPER HIGGHHG");
}
}*/
double rawRateGivenDest = ((double) (countOfDestNextMatched)) / timeInWindowWithMatchingDestHistory;
// Attempt at bias correction:
// Using digamma of neighbour_count - 1, since the neighbour count now includes our search point and it's really k waiting times