Skip to content

Commit 46a08cf

Browse files
RuedigerLundeRuedigerLunde
committed
Code cleaned up.
1 parent ef18bb8 commit 46a08cf

File tree

10 files changed

+1337
-1355
lines changed

10 files changed

+1337
-1355
lines changed

‎aima-gui/src/main/java/aima/gui/fx/demo/search/games/EightPuzzleApp.java‎

Lines changed: 5 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -1,45 +1,36 @@
11
package aima.gui.fx.demo.search.games;
22

3+
import java.util.ArrayList;
4+
import java.util.List;
5+
import java.util.Random;
6+
37
import aima.core.agent.Action;
48
import aima.core.environment.eightpuzzle.BidirectionalEightPuzzleProblem;
59
import aima.core.environment.eightpuzzle.EightPuzzleBoard;
610
import aima.core.environment.eightpuzzle.ManhattanHeuristicFunction;
711
import aima.core.environment.eightpuzzle.MisplacedTilleHeuristicFunction;
8-
import aima.core.environment.nqueens.AttackingPairsHeuristic;
9-
import aima.core.environment.nqueens.NQueensBoard;
10-
import aima.core.environment.nqueens.NQueensBoard.Config;
1112
import aima.core.search.framework.Metrics;
12-
import aima.core.search.framework.Search;
1313
import aima.core.search.framework.SearchForActions;
1414
import aima.core.search.framework.problem.Problem;
1515
import aima.core.search.framework.qsearch.BidirectionalSearch;
1616
import aima.core.search.framework.qsearch.GraphSearch;
17-
import aima.core.search.framework.qsearch.TreeSearch;
1817
import aima.core.search.informed.AStarSearch;
1918
import aima.core.search.informed.GreedyBestFirstSearch;
2019
import aima.core.search.local.SimulatedAnnealingSearch;
2120
import aima.core.search.uninformed.BreadthFirstSearch;
22-
import aima.core.search.uninformed.DepthFirstSearch;
2321
import aima.core.search.uninformed.DepthLimitedSearch;
2422
import aima.core.search.uninformed.IterativeDeepeningSearch;
2523
import aima.core.util.CancelableThread;
26-
import aima.gui.fx.demo.search.NQueensSearchProg;
2724
import aima.gui.fx.framework.IntegrableApplication;
2825
import aima.gui.fx.framework.Parameter;
2926
import aima.gui.fx.framework.SimulationPaneBuilder;
3027
import aima.gui.fx.framework.SimulationPaneCtrl;
3128
import aima.gui.fx.views.EightPuzzleViewCtrl;
32-
import aima.gui.fx.views.NQueensViewCtrl;
3329
import javafx.application.Platform;
3430
import javafx.scene.layout.BorderPane;
3531
import javafx.scene.layout.Pane;
3632
import javafx.scene.layout.StackPane;
3733

38-
import java.util.ArrayList;
39-
import java.util.Arrays;
40-
import java.util.List;
41-
import java.util.Random;
42-
4334

4435
/**
4536
* Integrable application which demonstrates how different search strategies
@@ -125,7 +116,7 @@ public Pane createRootPane() {
125116

126117
protected Parameter[] createParameters() {
127118
Parameter p1 = new Parameter(PARAM_INIT_CONF, "Three Moves", "Medium", "Extreme", "Random");
128-
Parameter p2 = new Parameter(PARAM_STRATEGY, (String[]) SEARCH_NAMES.toArray(new String[] {}));
119+
Parameter p2 = new Parameter(PARAM_STRATEGY, (Object[]) SEARCH_NAMES.toArray(new String[] {}));
129120
return new Parameter[] {p1, p2};
130121
}
131122

‎aima-gui/src/main/java/aima/gui/fx/demo/search/local/GeneticMaximumFinderApp.java‎

Lines changed: 136 additions & 134 deletions
Original file line numberDiff line numberDiff line change
@@ -1,134 +1,136 @@
1-
package aima.gui.fx.demo.search.local;
2-
3-
import java.util.Collection;
4-
import java.util.Optional;
5-
import java.util.function.Function;
6-
7-
import aima.core.search.local.Individual;
8-
import aima.gui.fx.framework.IntegrableApplication;
9-
import aima.gui.fx.framework.Parameter;
10-
import aima.gui.fx.framework.SimulationPaneBuilder;
11-
import aima.gui.fx.framework.SimulationPaneCtrl;
12-
import aima.gui.fx.views.FunctionPlotterCtrl;
13-
import javafx.application.Platform;
14-
import javafx.scene.canvas.Canvas;
15-
import javafx.scene.layout.BorderPane;
16-
import javafx.scene.layout.Pane;
17-
import javafx.scene.paint.Color;
18-
import javafx.scene.paint.Paint;
19-
20-
21-
/**
22-
* Demonstrates, how the genetic algorithm can be used, to find maximums in
23-
* mathematical functions. Different parameter settings can be tried out and
24-
* progress shown for each iteration.
25-
*
26-
* @author Ruediger Lunde
27-
*/
28-
public class GeneticMaximumFinderApp extends IntegrableApplication {
29-
30-
public static void main(String[] args) {
31-
launch(args);
32-
}
33-
34-
public final static String PARAM_FUNC_SELECT = "funcSelect";
35-
public final static String PARAM_MUT_PROB = "mutProb";
36-
public final static String PARAM_POPULATION = "population";
37-
public final static String PARAM_MAX_ITER = "maxIter";
38-
39-
protected FunctionPlotterCtrl funcPlotterCtrl;
40-
private SimulationPaneCtrl simPaneCtrl;
41-
private GeneticMaximumFinderProg experiment;
42-
43-
@Override
44-
public String getTitle() {
45-
return "Genetic Maxium Finder App";
46-
}
47-
48-
/**
49-
* Defines state view, parameters, and call-back functions and calls the
50-
* simulation pane builder to create layout and controller objects.
51-
*/
52-
@Override
53-
public Pane createRootPane() {
54-
BorderPane root = new BorderPane();
55-
56-
Canvas canvas = new Canvas();
57-
funcPlotterCtrl = new FunctionPlotterCtrl(canvas);
58-
funcPlotterCtrl.setLimits(Functions.minX, Functions.maxX, Functions.minY, Functions.maxY);
59-
Parameter[] params = createParameters();
60-
61-
SimulationPaneBuilder builder = new SimulationPaneBuilder();
62-
builder.defineParameters(params);
63-
builder.defineStateView(canvas);
64-
builder.defineInitMethod(this::initialize);
65-
builder.defineSimMethod(this::simulate);
66-
simPaneCtrl = builder.getResultFor(root);
67-
68-
return root;
69-
}
70-
71-
protected Parameter[] createParameters() {
72-
Parameter p1 = new Parameter(PARAM_FUNC_SELECT);
73-
p1.setValues(Functions.f1, Functions.f2, Functions.f3);
74-
p1.setValueNames("f1", "f2", "f3");
75-
Parameter p2 = new Parameter(PARAM_MUT_PROB, 0.0, 0.2, 0.5, 1.0);
76-
p2.setDefaultValueIndex(1);
77-
Parameter p3 = new Parameter(PARAM_POPULATION, 2, 10, 20, 100);
78-
p3.setDefaultValueIndex(2);
79-
Parameter p4 = new Parameter(PARAM_MAX_ITER, 100, 200, 400);
80-
p4.setDefaultValueIndex(0);
81-
return new Parameter[] {p1, p2, p3, p4};
82-
}
83-
84-
/** Displays the selected function on the state view. */
85-
@Override
86-
public void initialize() {
87-
funcPlotterCtrl.setFunction((Function<Double, Double>) simPaneCtrl.getParamValue(PARAM_FUNC_SELECT));
88-
}
89-
90-
@Override
91-
public void finalize() {
92-
simPaneCtrl.cancelSimulation();
93-
}
94-
95-
/** Starts the experiment. */
96-
public void simulate() {
97-
experiment = new GeneticMaximumFinderProg();
98-
experiment.setFunction((Function<Double, Double>) simPaneCtrl.getParamValue(PARAM_FUNC_SELECT));
99-
experiment.setMutationProb(simPaneCtrl.getParamAsDouble(PARAM_MUT_PROB));
100-
experiment.setPopulationSize(simPaneCtrl.getParamAsInt(PARAM_POPULATION));
101-
experiment.setMaxIterations(simPaneCtrl.getParamAsInt(PARAM_MAX_ITER));
102-
experiment.startExperiment(this::updateStateView);
103-
}
104-
105-
/**
106-
* Caution: While the background thread should be slowed down, updates of
107-
* the GUI have to be done in the GUI thread!
108-
*/
109-
private void updateStateView(int itCount, Collection<Individual<Double>> gen) {
110-
Platform.runLater(() -> updateStateViewLater(itCount, gen));
111-
simPaneCtrl.waitAfterStep();
112-
}
113-
114-
/**
115-
* Must be called by the GUI thread!
116-
*/
117-
private void updateStateViewLater(int itCount, Collection<Individual<Double>> gen) {
118-
funcPlotterCtrl.update();
119-
if (gen != null) {
120-
for (Individual<Double> ind : gen) {
121-
Optional<Paint> fill = Optional.empty();
122-
if (ind.getDescendants() > 0)
123-
fill = Optional.of(Color.rgb(Math.max(255 - ind.getDescendants() * 20, 0), 0, 0));
124-
else
125-
fill = Optional.of(Color.RED.brighter());
126-
double x = ind.getRepresentation().get(0);
127-
funcPlotterCtrl.setMarker(x, fill);
128-
}
129-
simPaneCtrl.setStatus(experiment.getIterationInfo(itCount, gen));
130-
} else {
131-
simPaneCtrl.setStatus("");
132-
}
133-
}
134-
}
1+
package aima.gui.fx.demo.search.local;
2+
3+
import java.util.Collection;
4+
import java.util.Optional;
5+
import java.util.function.Function;
6+
7+
import aima.core.search.local.Individual;
8+
import aima.gui.fx.framework.IntegrableApplication;
9+
import aima.gui.fx.framework.Parameter;
10+
import aima.gui.fx.framework.SimulationPaneBuilder;
11+
import aima.gui.fx.framework.SimulationPaneCtrl;
12+
import aima.gui.fx.views.FunctionPlotterCtrl;
13+
import javafx.application.Platform;
14+
import javafx.scene.canvas.Canvas;
15+
import javafx.scene.layout.BorderPane;
16+
import javafx.scene.layout.Pane;
17+
import javafx.scene.paint.Color;
18+
import javafx.scene.paint.Paint;
19+
20+
21+
/**
22+
* Demonstrates, how the genetic algorithm can be used, to find maximums in
23+
* mathematical functions. Different parameter settings can be tried out and
24+
* progress shown for each iteration.
25+
*
26+
* @author Ruediger Lunde
27+
*/
28+
public class GeneticMaximumFinderApp extends IntegrableApplication {
29+
30+
public static void main(String[] args) {
31+
launch(args);
32+
}
33+
34+
public final static String PARAM_FUNC_SELECT = "funcSelect";
35+
public final static String PARAM_MUT_PROB = "mutProb";
36+
public final static String PARAM_POPULATION = "population";
37+
public final static String PARAM_MAX_ITER = "maxIter";
38+
39+
protected FunctionPlotterCtrl funcPlotterCtrl;
40+
private SimulationPaneCtrl simPaneCtrl;
41+
private GeneticMaximumFinderProg experiment;
42+
43+
@Override
44+
public String getTitle() {
45+
return "Genetic Maxium Finder App";
46+
}
47+
48+
/**
49+
* Defines state view, parameters, and call-back functions and calls the
50+
* simulation pane builder to create layout and controller objects.
51+
*/
52+
@Override
53+
public Pane createRootPane() {
54+
BorderPane root = new BorderPane();
55+
56+
Canvas canvas = new Canvas();
57+
funcPlotterCtrl = new FunctionPlotterCtrl(canvas);
58+
funcPlotterCtrl.setLimits(Functions.minX, Functions.maxX, Functions.minY, Functions.maxY);
59+
Parameter[] params = createParameters();
60+
61+
SimulationPaneBuilder builder = new SimulationPaneBuilder();
62+
builder.defineParameters(params);
63+
builder.defineStateView(canvas);
64+
builder.defineInitMethod(this::initialize);
65+
builder.defineSimMethod(this::simulate);
66+
simPaneCtrl = builder.getResultFor(root);
67+
68+
return root;
69+
}
70+
71+
protected Parameter[] createParameters() {
72+
Parameter p1 = new Parameter(PARAM_FUNC_SELECT);
73+
p1.setValues(Functions.f1, Functions.f2, Functions.f3);
74+
p1.setValueNames("f1", "f2", "f3");
75+
Parameter p2 = new Parameter(PARAM_MUT_PROB, 0.0, 0.2, 0.5, 1.0);
76+
p2.setDefaultValueIndex(1);
77+
Parameter p3 = new Parameter(PARAM_POPULATION, 2, 10, 20, 100);
78+
p3.setDefaultValueIndex(2);
79+
Parameter p4 = new Parameter(PARAM_MAX_ITER, 100, 200, 400);
80+
p4.setDefaultValueIndex(0);
81+
return new Parameter[] {p1, p2, p3, p4};
82+
}
83+
84+
/** Displays the selected function on the state view. */
85+
@SuppressWarnings("unchecked")
86+
@Override
87+
public void initialize() {
88+
funcPlotterCtrl.setFunction((Function<Double, Double>) simPaneCtrl.getParamValue(PARAM_FUNC_SELECT));
89+
}
90+
91+
@Override
92+
public void finalize() {
93+
simPaneCtrl.cancelSimulation();
94+
}
95+
96+
/** Starts the experiment. */
97+
@SuppressWarnings("unchecked")
98+
public void simulate() {
99+
experiment = new GeneticMaximumFinderProg();
100+
experiment.setFunction((Function<Double, Double>) simPaneCtrl.getParamValue(PARAM_FUNC_SELECT));
101+
experiment.setMutationProb(simPaneCtrl.getParamAsDouble(PARAM_MUT_PROB));
102+
experiment.setPopulationSize(simPaneCtrl.getParamAsInt(PARAM_POPULATION));
103+
experiment.setMaxIterations(simPaneCtrl.getParamAsInt(PARAM_MAX_ITER));
104+
experiment.startExperiment(this::updateStateView);
105+
}
106+
107+
/**
108+
* Caution: While the background thread should be slowed down, updates of
109+
* the GUI have to be done in the GUI thread!
110+
*/
111+
private void updateStateView(int itCount, Collection<Individual<Double>> gen) {
112+
Platform.runLater(() -> updateStateViewLater(itCount, gen));
113+
simPaneCtrl.waitAfterStep();
114+
}
115+
116+
/**
117+
* Must be called by the GUI thread!
118+
*/
119+
private void updateStateViewLater(int itCount, Collection<Individual<Double>> gen) {
120+
funcPlotterCtrl.update();
121+
if (gen != null) {
122+
for (Individual<Double> ind : gen) {
123+
Optional<Paint> fill = Optional.empty();
124+
if (ind.getDescendants() > 0)
125+
fill = Optional.of(Color.rgb(Math.max(255 - ind.getDescendants() * 20, 0), 0, 0));
126+
else
127+
fill = Optional.of(Color.RED.brighter());
128+
double x = ind.getRepresentation().get(0);
129+
funcPlotterCtrl.setMarker(x, fill);
130+
}
131+
simPaneCtrl.setStatus(experiment.getIterationInfo(itCount, gen));
132+
} else {
133+
simPaneCtrl.setStatus("");
134+
}
135+
}
136+
}

0 commit comments

Comments
 (0)