@operator(
value = {"clustering_simple_kmeans"},
content_type = IType.LIST,
category = {IOperatorCategory.STATISTICAL},
concept = {IConcept.STATISTIC})
@doc(
value =
"A list of agent groups clustered by K-Means Algorithm based on the given attributes. Some paremeters can be defined: "
+ "distance_f: The distance function to use. 4 possible distance functions: euclidean (by default) ; 'chebyshev', 'manhattan' or 'levenshtein'; "
+ "dont_replace_missing_values: if false, replace missing values globally with mean/mode; max_iterations: the maximum number of iterations to perform;"
+ "num_clusters: the number of clusters",
examples = {
@example(
value =
"clustering_simple_kmeans([ag1, ag2, ag3, ag4, ag5],[\"size\",\"age\", \"weight\"],[\"distance_f\"::\"manhattan\", \"num_clusters\"::3])",
equals = "for example, can return [[ag1, ag3], [ag2], [ag4, ag5]]",
isExecutable = false)
},
see = {
"clustering_xmeans",
"clustering_em",
"clustering_farthestFirst",
"clustering_DBScan",
"clustering_cobweb"
})
public static IList<IList<IAgent>> primClusteringSimpleKMeans(
final IScope scope,
final IAddressableContainer<Integer, IAgent, Integer, IAgent> agents,
final IList<String> attributes,
final GamaMap<String, Object> parameters) {
SimpleKMeans kmeans = new SimpleKMeans();
kmeans.setSeed(Cast.asInt(scope, scope.getRandom().getSeed()));
if (parameters != null) {
try {
if (parameters.containsKey("distance_f")) {
String distanceFct = Cast.asString(scope, parameters.get("distance_f"));
if (distanceFct.equals("chebyshev")) {
kmeans.setDistanceFunction(new ChebyshevDistance());
} else if (distanceFct.equals("manhattan")) {
kmeans.setDistanceFunction(new ManhattanDistance());
} else if (distanceFct.equals("levenshtein")) {
kmeans.setDistanceFunction(new EditDistance());
}
}
if (parameters.containsKey("dont_replace_missing_values")) {
kmeans.setDontReplaceMissingValues(
Cast.asBool(scope, parameters.get("dont_replace_missing_values")));
}
if (parameters.containsKey("max_iterations")) {
kmeans.setMaxIterations(Cast.asInt(scope, parameters.get("max_iterations")));
}
if (parameters.containsKey("num_clusters")) {
kmeans.setNumClusters(Cast.asInt(scope, parameters.get("num_clusters")));
}
} catch (Exception e) {
}
}
IList<IList<IAgent>> groupes = clusteringUsingWeka(scope, kmeans, attributes, agents);
return groupes;
}
public FsmStateStatement(final IDescription desc) {
super(desc);
setName(getLiteral(IKeyword.NAME)); // A VOIR
isInitial = Cast.asBool(null, getLiteral(FsmStateStatement.INITIAL));
isFinal = Cast.asBool(null, getLiteral(FsmStateStatement.FINAL));
}
@Override
protected Object privateExecuteIn(final IScope scope) throws GamaRuntimeException {
// IGraph data = createData(scope);
IGraph g = Cast.asGraph(scope, getFacetValue(scope, IKeyword.GRAPH));
int thread_number =
Cast.asInt(
scope,
getFacetValue(
scope, GraphForceAtlasLayoutStatement.THREAD_NUMBER, THREAD_NUMBER_DEFAULT));
boolean dissuade_hubs =
Cast.asBool(
scope,
getFacetValue(
scope, GraphForceAtlasLayoutStatement.DISSUADE_HUBS, DISSUADE_HUBS_DEFAULT));
boolean linlog_mode =
Cast.asBool(
scope,
getFacetValue(scope, GraphForceAtlasLayoutStatement.LINLOG_MODE, LINLOG_MODE_DEFAULT));
boolean prevent_overlap =
Cast.asBool(
scope,
getFacetValue(
scope, GraphForceAtlasLayoutStatement.PREVENT_OVERLAP, PREVENT_OVERLAP_DEFAULT));
double edge_weight_influence =
Cast.asFloat(
scope,
getFacetValue(
scope,
GraphForceAtlasLayoutStatement.EDGE_WEIGHT_INFLUENCE,
EDGE_WEIGHT_INFLUENCE_DEFAULT));
double scaling =
Cast.asFloat(
scope, getFacetValue(scope, GraphForceAtlasLayoutStatement.SCALING, SCALING_DEFAULT));
boolean stronger_gravity =
Cast.asBool(
scope,
getFacetValue(
scope, GraphForceAtlasLayoutStatement.STRONGER_GRAVITY, STRONGER_GRAVITY_DEFAULT));
double gravity =
Cast.asFloat(
scope, getFacetValue(scope, GraphForceAtlasLayoutStatement.GRAVITY, GRAVITY_DEFAULT));
double tolerance =
Cast.asFloat(
scope,
getFacetValue(scope, GraphForceAtlasLayoutStatement.TOLERANCE, TOLERANCE_DEFAULT));
boolean approximate_repulsion =
Cast.asBool(
scope,
getFacetValue(
scope,
GraphForceAtlasLayoutStatement.APPROXIMATE_REPULSION,
APPROXIMATE_REPULSION_DEFAULT));
double approximation =
Cast.asFloat(
scope,
getFacetValue(
scope, GraphForceAtlasLayoutStatement.APPROXIMATION, APPROXIMATION_DEFAULT));
int nb_steps =
Cast.asInt(
scope, getFacetValue(scope, GraphForceAtlasLayoutStatement.NB_STEPS, NB_STEPS_DEFAULT));
Object bp1 = getFacetValue(scope, GraphForceAtlasLayoutStatement.BOUNDED_P1, null);
Object bp2 = getFacetValue(scope, GraphForceAtlasLayoutStatement.BOUNDED_P2, null);
// public static IGraph YifanHuLayout_Step_Unlimited(final IGraph g, double optimal_distance,
// double initial_step, double step_ratio, double convergence_threshold, double
// barnes_hut_theta) {
initializing();
// System.out.println("ForceAtlas2 algorithm (by step), starting.");
// System.out.println("converting ...");
IGraph_to_GraphModel(g);
// System.out.println("initializing ...");
ForceAtlas2 fa2Layout = new ForceAtlas2(new ForceAtlas2Builder());
initializing_GraphModel(g);
fa2Layout.resetPropertiesValues();
fa2Layout.setGraphModel(graph_model);
fa2Layout.setOutboundAttractionDistribution(dissuade_hubs);
fa2Layout.setLinLogMode(linlog_mode);
fa2Layout.setAdjustSizes(prevent_overlap);
fa2Layout.setEdgeWeightInfluence(edge_weight_influence);
fa2Layout.setScalingRatio(scaling);
fa2Layout.setStrongGravityMode(stronger_gravity);
fa2Layout.setGravity(gravity);
fa2Layout.setJitterTolerance(tolerance);
fa2Layout.setBarnesHutOptimize(approximate_repulsion);
fa2Layout.setBarnesHutTheta(approximation);
// System.out.println("working ...");
fa2Layout.initAlgo();
// System.out.println("working ...");
// int nbsteps=1;
// for (int i = 0; i < nbsteps && fa2Layout.canAlgo(); i++){
for (int i = 0; i < nb_steps; i++) {
fa2Layout.goAlgo();
}
fa2Layout.endAlgo();
// fa2Layout.goAlgo();
// fa2Layout.endAlgo();
if (bp1 != null && bp2 != null) {
ILocation p1 = Cast.asPoint(scope, bp1);
ILocation p2 = Cast.asPoint(scope, bp2);
Update_locations(
g,
FastMath.min(p1.getX(), p2.getX()),
FastMath.min(p1.getY(), p2.getY()),
FastMath.max(p1.getX(), p2.getX()),
FastMath.max(p1.getY(), p2.getY()));
} else {
Update_locations(g);
}
// System.out.println("ended.");
return g;
}
