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convert to shuffled P Vals into one whole flat list
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@vbcwonderland
vbcwonderland committed May 31, 2024
1 parent 18c244e commit e9441e7
Showing 1 changed file with 62 additions and 59 deletions.
121 changes: 62 additions & 59 deletions tetrad-lib/src/main/java/edu/cmu/tetrad/search/MarkovCheck.java
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.Future;
import java.util.stream.Collectors;

/**
* Checks whether a graph is Markov given a data set. First, a list of m-separation predictions are made for each pair
Expand Down Expand Up @@ -327,13 +328,15 @@ public List<List<Node>> getAndersonDarlingTestAcceptsRejectsNodesForAllNodes(Ind
List<IndependenceFact> localIndependenceFacts = getLocalIndependenceFacts(x);
// All local nodes' p-values for node x
List<List<Double>> shuffledlocalPValues = getLocalPValues(independenceTest, localIndependenceFacts, shuffleThreshold);
for (List<Double> localPValues: shuffledlocalPValues) {
Double ADTest = checkAgainstAndersonDarlingTest(localPValues); // P value obtained from AD test
if (ADTest <= threshold) {
rejects.add(x);
} else {
accepts.add(x);
}
// TODO VBC: what should we do for cases when ADTest is NaN and ∞ ?
List<Double> flatList = shuffledlocalPValues.stream()
.flatMap(List::stream)
.collect(Collectors.toList());
Double ADTestPValue = checkAgainstAndersonDarlingTest(flatList);
if (ADTestPValue <= threshold) {
rejects.add(x);
} else {
accepts.add(x);
}
}
accepts_rejects.add(accepts);
Expand Down Expand Up @@ -391,38 +394,38 @@ public List<List<Node>> getAndersonDarlingTestAcceptsRejectsNodesForAllNodesPlot
Double ahr = ap_ar_ahp_ahr.get(3);
// All local nodes' p-values for node x.
List<List<Double>> shuffledlocalPValues = getLocalPValues(independenceTest, localIndependenceFacts, shuffleThreshold); // shuffleThreshold default to be 0.5
for (List<Double> localPValues: shuffledlocalPValues) {
// P value obtained from AD test
Double ADTestPValue = checkAgainstAndersonDarlingTest(localPValues);
// TODO VBC: what should we do for cases when ADTest is NaN and ∞ ?
if (ADTestPValue <= threshold) {
rejects.add(x);
if (!Double.isNaN(ap)) {
rejects_AdjP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ar)) {
rejects_AdjR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahp)) {
rejects_AHP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahr)) {
rejects_AHR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
} else {
accepts.add(x);
if (!Double.isNaN(ap)) {
accepts_AdjP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ar)) {
accepts_AdjR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahp)) {
accepts_AHP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahr)) {
accepts_AHR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
List<Double> flatList = shuffledlocalPValues.stream()
.flatMap(List::stream)
.collect(Collectors.toList());
Double ADTestPValue = checkAgainstAndersonDarlingTest(flatList);
// TODO VBC: what should we do for cases when ADTest is NaN and ∞ ?
if (ADTestPValue <= threshold) {
rejects.add(x);
if (!Double.isNaN(ap)) {
rejects_AdjP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ar)) {
rejects_AdjR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahp)) {
rejects_AHP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahr)) {
rejects_AHR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
} else {
accepts.add(x);
if (!Double.isNaN(ap)) {
accepts_AdjP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ar)) {
accepts_AdjR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahp)) {
accepts_AHP_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
if (!Double.isNaN(ahr)) {
accepts_AHR_ADTestP.add(Arrays.asList(ap, ADTestPValue));
}
}
}
Expand Down Expand Up @@ -532,26 +535,26 @@ public List<List<Node>> getAndersonDarlingTestAcceptsRejectsNodesForAllNodesPlot
Double lgr = lgp_lgr.get(1);
// All local nodes' p-values for node x.
List<List<Double>> shuffledlocalPValues = getLocalPValues(independenceTest, localIndependenceFacts, shuffleThreshold); // shuffleThreshold default to be 0.5
for (List<Double> localPValues: shuffledlocalPValues) {
// P value obtained from AD test
Double ADTestPValue = checkAgainstAndersonDarlingTest(localPValues);
// TODO VBC: what should we do for cases when ADTest is NaN and ∞ ?
if (ADTestPValue <= threshold) {
rejects.add(x);
if (!Double.isNaN(lgp)) {
rejects_LGP_ADTestP.add(Arrays.asList(lgp, ADTestPValue));
}
if (!Double.isNaN(lgr)) {
rejects_LGR_ADTestP.add(Arrays.asList(lgr, ADTestPValue));
}
} else {
accepts.add(x);
if (!Double.isNaN(lgp)) {
accepts_LGP_ADTestP.add(Arrays.asList(lgp, ADTestPValue));
}
if (!Double.isNaN(lgr)) {
accepts_LGR_ADTestP.add(Arrays.asList(lgr, ADTestPValue));
}
List<Double> flatList = shuffledlocalPValues.stream()
.flatMap(List::stream)
.collect(Collectors.toList());
Double ADTestPValue = checkAgainstAndersonDarlingTest(flatList);
// TODO VBC: what should we do for cases when ADTest is NaN and ∞ ?
if (ADTestPValue <= threshold) {
rejects.add(x);
if (!Double.isNaN(lgp)) {
rejects_LGP_ADTestP.add(Arrays.asList(lgp, ADTestPValue));
}
if (!Double.isNaN(lgr)) {
rejects_LGR_ADTestP.add(Arrays.asList(lgr, ADTestPValue));
}
} else {
accepts.add(x);
if (!Double.isNaN(lgp)) {
accepts_LGP_ADTestP.add(Arrays.asList(lgp, ADTestPValue));
}
if (!Double.isNaN(lgr)) {
accepts_LGR_ADTestP.add(Arrays.asList(lgr, ADTestPValue));
}
}
}
Expand Down

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