[Libreoffice-commits] core.git: nlpsolver/ThirdParty
Todor Balabanov (via logerrit)
logerrit at kemper.freedesktop.org
Fri May 17 06:46:38 UTC 2019
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java | 10 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java | 11 ++
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java | 19 ++--
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java | 10 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/ACRComparator.java | 7 +
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/BCHComparator.java | 4 -
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/IGoodnessCompareEngine.java | 12 ++-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/Library.java | 1
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/SearchPoint.java | 6 -
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java | 8 +-
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java | 39 +++++-----
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignDim.java | 1
nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java | 1
13 files changed, 74 insertions(+), 55 deletions(-)
New commits:
commit 5ee453818c88f0a73ca2863a80c6b901feed1837
Author: Todor Balabanov <todor.balabanov at gmail.com>
AuthorDate: Mon May 13 14:29:17 2019 +0300
Commit: Samuel Mehrbrodt <Samuel.Mehrbrodt at cib.de>
CommitDate: Fri May 17 08:45:46 2019 +0200
Some additional manual formatting.
Change-Id: Ie5590535d013aa2f747dd034fa2fcd2ae5c3956b
Reviewed-on: https://gerrit.libreoffice.org/72226
Tested-by: Jenkins
Reviewed-by: Samuel Mehrbrodt <Samuel.Mehrbrodt at cib.de>
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
index 0f1240df9a1b..b9784c8a2ab3 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/DEPSAgent.java
@@ -46,6 +46,7 @@ public class DEPSAgent implements ILibEngine {
// Describes the problem to be solved
private ProblemEncoder problemEncoder;
+
// Forms the goodness landscape
private IGoodnessCompareEngine qualityComparator;
@@ -57,8 +58,10 @@ public class DEPSAgent implements ILibEngine {
// the own memory: store the point that generated in old learning cycle
private BasicPoint pold_t;
+
// the own memory: store the point that generated in last learning cycle
private BasicPoint pcurrent_t;
+
// the own memory: store the personal best point
private SearchPoint pbest_t;
@@ -109,11 +112,12 @@ public class DEPSAgent implements ILibEngine {
}
public void generatePoint() {
-// generates a new point in the search space (S) based on
-// its memory and the library
+ // generates a new point in the search space (S) based on
+ // its memory and the library
selectGTBehavior = this.getGTBehavior();
selectGTBehavior.generateBehavior(trailPoint, problemEncoder);
-// evaluate into goodness information
+
+ // evaluate into goodness information
problemEncoder.evaluate(trailPoint);
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
index 40e570a77559..645318341108 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/DEGTBehavior.java
@@ -37,9 +37,14 @@ import net.adaptivebox.problem.ProblemEncoder;
import net.adaptivebox.space.BasicPoint;
public class DEGTBehavior extends AbsGTBehavior implements ILibEngine {
- private static final int DVNum = 2; // Number of differential vectors, normally be 1 or 2
- public double FACTOR = 0.5; // scale constant: (0, 1.2], normally be 0.5
- public double CR = 0.9; // crossover constant: [0, 1], normally be 0.1 or 0.9
+ //Number of differential vectors, normally be 1 or 2
+ private static final int DVNum = 2;
+
+ //scale constant: (0, 1.2], normally be 0.5
+ public double FACTOR = 0.5;
+
+ //crossover constant: [0, 1], normally be 0.1 or 0.9
+ public double CR = 0.9;
// the own memory: store the point that generated in last learning cycle
private SearchPoint pbest_t;
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
index afd18390e630..13c605b63780 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/deps/behavior/PSGTBehavior.java
@@ -64,20 +64,23 @@ import net.adaptivebox.space.DesignSpace;
public class PSGTBehavior extends AbsGTBehavior {
// Two normally choices for (c1, c2, weight), i.e., (2, 2, 0.4), or (1.494,
- // 1.494, 0.729)
- // The first is used in dissipative PSO (cf. [4]) as CL>0, and the second is
- // achieved by using
- // constriction factors (cf. [3])
+ // 1.494, 0.729) The first is used in dissipative PSO (cf. [4]) as CL>0, and
+ // the second is achieved by using constriction factors (cf. [3])
public double c1 = 2;
public double c2 = 2;
- public double weight = 0.4; // inertia weight
- public double CL = 0; // See ref[4], normally be 0.001~0.005
+ //inertia weight
+ public double weight = 0.4;
+
+ //See ref[4], normally be 0.001~0.005
+ public double CL = 0;
// the own memory: store the point that generated in old learning cycle
private BasicPoint pold_t;
+
// the own memory: store the point that generated in last learning cycle
private BasicPoint pcurrent_t;
+
// the own memory: store the personal best point
private SearchPoint pbest_t;
@@ -100,7 +103,8 @@ public class PSGTBehavior extends AbsGTBehavior {
deltaxb = weight * (pcurrent_t.getLocation()[b] - pold_t.getLocation()[b])
+ c1 * Math.random() * (pbest_t.getLocation()[b] - pcurrent_t.getLocation()[b])
+ c2 * Math.random() * (gbest_t.getLocation()[b] - pcurrent_t.getLocation()[b]);
-// limitation for delta_x
+
+ // limitation for delta_x
deltaxbm = 0.5 * designSpace.getMagnitudeIn(b);
if (deltaxb < -deltaxbm) {
deltaxb = -deltaxbm;
@@ -118,5 +122,4 @@ public class PSGTBehavior extends AbsGTBehavior {
pold_t.importLocation(pcurrent_t);
pcurrent_t.importLocation(trailPoint);
}
-
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java
index 526257544091..db37ddb39f5b 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/encode/EvalStruct.java
@@ -42,13 +42,13 @@ public class EvalStruct {
evalRes[0] = evalRes[1] = 0;
for (int i = 0; i < evalElems.length; i++) {
if (evalElems[i].isOptType()) {
-// The objectives (OPTIM type)
-// The multi-objective will be translated into single-objective
+ // The objectives (OPTIM type)
+ // The multi-objective will be translated into single-objective
evalRes[1] += evalElems[i].evaluateOPTIM(targetValues[i]);
} else {
-// The constraints (CONS type)
-// If evalRes[0] equals to 0, then be a feasible point, i.e. satisfies
-// all the constraints
+ // The constraints (CONS type)
+ // If evalRes[0] equals to 0, then be a feasible point, i.e. satisfies
+ // all the constraints
evalRes[0] += evalElems[i].evaluateCONS(targetValues[i]);
}
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/ACRComparator.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/ACRComparator.java
index 22f4d4a32ba2..284549506ce1 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/ACRComparator.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/ACRComparator.java
@@ -51,8 +51,8 @@ public class ACRComparator implements IGoodnessCompareEngine, IUpdateCycleEngine
public ACRComparator(Library lib, int T) {
socialPool = lib;
this.T = T;
-// set the (epsilon_t|t=0) as the maximum CONS value among the SearchPoints in
-// the library
+
+ // set the (epsilon_t|t=0) as the maximum CONS value among the SearchPoints in the library
epsilon_t = lib.getExtremalVcon(true);
}
@@ -74,8 +74,9 @@ public class ACRComparator implements IGoodnessCompareEngine, IUpdateCycleEngine
}
public void updateCycle(int t) {
-// calculates the ratio
+ // calculates the ratio
double rn = (double) socialPool.getVconThanNum(epsilon_t) / (double) socialPool.getPopSize();
+
if (t > TthR * T && T != -1) { // Forcing sub-rule
epsilon_t *= BETAF;
} else { // Ratio-keeping sub-rules
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/BCHComparator.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/BCHComparator.java
index 74fd1b8481fe..8140650dd6e1 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/BCHComparator.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/BCHComparator.java
@@ -28,9 +28,7 @@ package net.adaptivebox.goodness;
public class BCHComparator implements IGoodnessCompareEngine {
- /*
- * check the magnitude of two array, the frontal is more important
- **/
+ /* check the magnitude of two array, the frontal is more important */
private static int compareArray(double[] fit1, double[] fit2) {
for (int i = 0; i < fit1.length; i++) {
if (fit1[i] > fit2[i]) {
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/IGoodnessCompareEngine.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/IGoodnessCompareEngine.java
index 70e227b5f610..17a85993d56f 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/IGoodnessCompareEngine.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/goodness/IGoodnessCompareEngine.java
@@ -29,9 +29,13 @@ public abstract interface IGoodnessCompareEngine {
int LESS_THAN = 0;
/**
- * check the magnitude of two IEncodeEngine LARGER_THAN: goodness1 is worse than
- * goodness2 LESS_THAN: goodness1 is better than goodness2 EQUAL_TO : goodness1
- * is equal to goodness2
- **/
+ * check the magnitude of two IEncodeEngine
+ *
+ * LARGER_THAN: goodness1 is worse than goodness2
+ *
+ * LESS_THAN: goodness1 is better than goodness2
+ *
+ * EQUAL_TO : goodness1 is equal to goodness2
+ */
int compare(double[] goodness1, double[] goodness2);
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/Library.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/Library.java
index 841e9102a1c0..247d4908c420 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/Library.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/Library.java
@@ -99,5 +99,4 @@ public class Library {
}
return num;
}
-
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/SearchPoint.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/SearchPoint.java
index eb0441648781..df13efc74d0a 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/SearchPoint.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/knowledge/SearchPoint.java
@@ -25,8 +25,7 @@ import net.adaptivebox.space.BasicPoint;
public class SearchPoint extends BasicPoint implements IEncodeEngine {
// store the encode information for goodness evaluation
- // encodeInfo[0]: the sum of constraints (if it equals to 0, then be a feasible
- // point)
+ // encodeInfo[0]: the sum of constraints (if it equals to 0, then be a feasible point)
// encodeInfo[1]: the value of objective function
private final double[] encodeInfo = new double[2];
private double objectiveValue;
@@ -68,5 +67,4 @@ public class SearchPoint extends BasicPoint implements IEncodeEngine {
public boolean isFeasible() {
return encodeInfo[0] == 0; // no constraint violations
}
-
-}
\ No newline at end of file
+}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
index c6a25e93c8f1..674d275420c3 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/problem/ProblemEncoder.java
@@ -85,11 +85,13 @@ public abstract class ProblemEncoder {
// evaluate the point into encoded information
public void evaluate(SearchPoint point) {
-// copy to temp point
+ // copy to temp point
System.arraycopy(point.getLocation(), 0, this.tempLocation, 0, tempLocation.length);
-// mapping the temp point to original search space S
+
+ // mapping the temp point to original search space S
designSpace.getMappingPoint(tempLocation);
-// calculate based on the temp point
+
+ // calculate based on the temp point
calcTargets(tempResponseSet, tempLocation);
evalStruct.evaluate(point.getEncodeInfo(), tempResponseSet);
point.setObjectiveValue(tempResponseSet[0]);
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java
index 7785069e86bc..a09d0dcfd6b2 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/sco/SCAgent.java
@@ -43,22 +43,24 @@ import net.adaptivebox.knowledge.SearchPoint;
public class SCAgent {
- // Describes the problem to be solved (encode the point into intermediate
- // information)
+ // Describes the problem to be solved (encode the point into intermediate information)
private ProblemEncoder problemEncoder;
+
// Forms the goodness landscape
private IGoodnessCompareEngine specComparator;
// the coefficients of SCAgent
private static final int TaoB = 2;
- // The early version set TaoW as the size of external library (NL), but 4 is
- // often enough
+
+ // The early version set TaoW as the size of external library (NL), but 4 is often enough
private static final int TaoW = 4;
// The referred external library
private Library externalLib;
+
// store the point that generated in current learning cycle
private SearchPoint trailPoint;
+
// the own memory: store the point that generated in last learning cycle
private SearchPoint pcurrent_t;
@@ -77,9 +79,10 @@ public class SCAgent {
}
public SearchPoint generatePoint() {
-// generate a new point
+ // generate a new point
generatePoint(trailPoint);
-// evaluate the generated point
+
+ // evaluate the generated point
problemEncoder.evaluate(trailPoint);
return trailPoint;
}
@@ -87,13 +90,14 @@ public class SCAgent {
private void generatePoint(ILocationEngine tempPoint) {
SearchPoint Xmodel, Xrefer, libBPoint;
-// choose Selects a better point (libBPoint) from externalLib (L) based
-// on tournament selection
+ // choose Selects a better point (libBPoint) from externalLib (L) based
+ // on tournament selection
int xb = externalLib.tournamentSelection(specComparator, TaoB, true);
libBPoint = externalLib.getSelectedPoint(xb);
-// Compares pcurrent_t with libBPoint
-// The better one becomes model point (Xmodel)
-// The worse one becomes refer point (Xrefer)
+
+ // Compares pcurrent_t with libBPoint
+ // The better one becomes model point (Xmodel)
+ // The worse one becomes refer point (Xrefer)
if (specComparator.compare(pcurrent_t.getEncodeInfo(),
libBPoint.getEncodeInfo()) == IGoodnessCompareEngine.LARGER_THAN) {
Xmodel = libBPoint;
@@ -102,19 +106,22 @@ public class SCAgent {
Xmodel = pcurrent_t;
Xrefer = libBPoint;
}
-// observational learning: generates a new point near the model point, which
-// the variation range is decided by the difference of Xmodel and Xrefer
+
+ // observational learning: generates a new point near the model point, which
+ // the variation range is decided by the difference of Xmodel and Xrefer
inferPoint(tempPoint, Xmodel, Xrefer, problemEncoder.getDesignSpace());
}
// 1. Update the current point into the external library
// 2. Replace the current point by the generated point
public void updateInfo() {
-// Selects a bad point kw from TaoW points in Library
+ // Selects a bad point kw from TaoW points in Library
int xw = externalLib.tournamentSelection(specComparator, TaoW, false);
-// Replaces kw with pcurrent_t
+
+ // Replaces kw with pcurrent_t
externalLib.getSelectedPoint(xw).importPoint(pcurrent_t);
-// Replaces pcurrent_t (x(t)) with trailPoint (x(t+1))
+
+ // Replaces pcurrent_t (x(t)) with trailPoint (x(t+1))
pcurrent_t.importPoint(trailPoint);
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignDim.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignDim.java
index 9fbe937e1dff..f8f283bf1929 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignDim.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignDim.java
@@ -42,5 +42,4 @@ public class DesignDim {
return paramBound.maxValue - Math.rint((paramBound.maxValue - value) / grain) * grain;
}
}
-
}
diff --git a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
index 0c28e0006e1b..7d9307936033 100644
--- a/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
+++ b/nlpsolver/ThirdParty/EvolutionarySolver/src/net/adaptivebox/space/DesignSpace.java
@@ -70,5 +70,4 @@ public class DesignSpace {
}
}
}
-
}
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