本文整理匯總了Java中org.apache.commons.math3.linear.MatrixUtils.createRealVector方法的典型用法代碼示例。如果您正苦於以下問題:Java MatrixUtils.createRealVector方法的具體用法?Java MatrixUtils.createRealVector怎麽用?Java MatrixUtils.createRealVector使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類org.apache.commons.math3.linear.MatrixUtils
的用法示例。
在下文中一共展示了MatrixUtils.createRealVector方法的15個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Java代碼示例。
示例1: makeDataMatrix
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
private RealMatrix makeDataMatrix(List<double[]> X, double[] meanX) {
if (meanX == null) {
return makeDataMatrix(X);
}
final int m = X.size();
final int n = X.get(0).length;
RealMatrix M = MatrixUtils.createRealMatrix(n, m);
RealVector mean = MatrixUtils.createRealVector(meanX);
int i = 0;
for (double[] x : X) {
RealVector xi = MatrixUtils.createRealVector(x).subtract(mean);
M.setColumnVector(i, xi);
i++;
}
return M;
}
示例2: getVectorVarByName
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public List<RealVector> getVectorVarByName(String name) {
String varName = "V_" + name;
JsonNode obj = redisService.getValue(spaceIdentifier, varName);
int size = obj.get("size").asInt();
int dim = obj.get("dim").asInt();
double initial = obj.get("initial").asDouble();
boolean randomize = obj.get("randomize").asBoolean();
boolean normalize = obj.get("normalize").asBoolean();
List<RealVector> vars = new ArrayList<>(size);
for (int i=0; i<size; i++) {
RealVector var = MatrixUtils.createRealVector(new double[dim]);
initializeVector(var, initial, randomize, normalize);
vars.add(var);
}
String varIdxName = "IDX_V_" + name + "_";
List<String> keys = redisService.keysWithPrefixPattern(spaceIdentifier, varIdxName);
List<JsonNode> values = redisService.bulkGet(keys);
for (JsonNode one : values) {
setValue(vars, one, dim);
}
return vars;
}
示例3: ensureVectorVar
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
final public void ensureVectorVar(String name, int size, int dim, double initial,
boolean randomize, boolean normalize) {
writeLock.lock();
try {
int curSize = vectorVars.get(name).size();
if (curSize < size) {
for (int i=curSize; i<size; i++) {
RealVector vec = MatrixUtils.createRealVector(new double[dim]);
initializeVector(vec, initial, randomize, normalize);
vectorVars.get(name).add(vec);
}
}
curSize = readLocks.size();
SpaceUtilities.fillReadWriteLocks(readLocks, writeLocks, curSize, size);
} finally {
writeLock.unlock();
}
}
示例4: getStochasticOracle
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public List<StochasticOracle> getStochasticOracle(List<LearningInstance> instances) {
List<StochasticOracle> oracles = new ArrayList<>(instances.size());
for (LearningInstance inIns : instances) {
SVDFeatureInstance ins = (SVDFeatureInstance) inIns;
StochasticOracle orc = new StochasticOracle();
RealVector ufactSum = MatrixUtils.createRealVector(new double[factDim]);
RealVector ifactSum = MatrixUtils.createRealVector(new double[factDim]);
double pred = predict(ins, orc, ufactSum, ifactSum);
RealVector leftGrad = ifactSum;
RealVector rightGrad = ufactSum;
for (int i = 0; i < ins.ufeas.size(); i++) {
orc.addVectorOracle(SVDFeatureKey.FACTORS.get(),
ins.ufeas.get(i).getIndex(),
leftGrad.mapMultiply(ins.ufeas.get(i).getValue()));
}
for (int i = 0; i < ins.ifeas.size(); i++) {
orc.addVectorOracle(SVDFeatureKey.FACTORS.get(),
ins.ifeas.get(i).getIndex(),
rightGrad.mapMultiply(ins.ifeas.get(i).getValue()));
}
orc.setValues(pred, ins.label, ins.weight);
oracles.add(orc);
}
return oracles;
}
示例5: realmat2vector
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public static RealVector realmat2vector(RealMatrix inMatrix, int dimWalk){
RealVector retVector = null;
int ncols = inMatrix.getColumnDimension();
int nrows = inMatrix.getRowDimension();
switch (dimWalk){
case 1:
{
retVector = MatrixUtils.createRealVector(inMatrix.getRow(0));
for(int i=1;i<nrows;i++){
retVector = retVector.append(inMatrix.getRowVector(i));
}
}
default:
{
retVector = MatrixUtils.createRealVector(inMatrix.getColumn(0));
for(int i=1;i<ncols;i++){
retVector = retVector.append(inMatrix.getColumnVector(i));
}
}
}
return(retVector);
}
示例6: realmatSelectVector
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public static RealVector realmatSelectVector(RealMatrix inMatrix,RealMatrix selectMatrix, double valueSelect){
RealVector retVector = MatrixUtils.createRealVector(new double[0]);
int ncols = inMatrix.getColumnDimension();
int nrows = inMatrix.getRowDimension();
for(int j=0;j<ncols;j++){
for(int i=0;i<nrows;i++){
if(inMatrix.getEntry(i,j)==valueSelect) {
retVector = retVector.append(selectMatrix.getEntry(i,j));
}
}
}
return(retVector);
}
示例7: initStepEnergyOpt
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public void initStepEnergyOpt(){
foregroundPixelVal = MatrixUtils.createRealVector(new double[1]);
Boolean vecInitialised = Boolean.FALSE;
for(int i=0;i<edgeflag2.getRowDimension();i++){
for(int j=0;j<edgeflag2.getColumnDimension();j++){
if(edgeflag2.getEntry(i,j)>0){
if(!vecInitialised){
foregroundPixelVal.setEntry(0,idmax.getEntry(i,j));
vecInitialised = Boolean.TRUE;
}else {
foregroundPixelVal = foregroundPixelVal.append(idmax.getEntry(i, j));
}
}
}
}
KE= foregroundPixelVal.getMaxValue()-foregroundPixelVal.getMinValue()+1;
step=KE/100;
//step = sme_pluginGetManifold.getStack1().getSize()/(double)stepNumber;
}
示例8: ProjectiveMapping
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
/**
* Constructor for more than 4 point pairs, finds a least-squares solution
* for the homography parameters.
* NOTE: this is UNFINISHED code!
* @param P sequence of points (source)
* @param Q sequence of points (target)
* @param dummy unused (only to avoid duplicate signature)
*/
public ProjectiveMapping(Point2D[] P, Point2D[] Q, boolean dummy) {
final int n = P.length;
double[] ba = new double[2 * n];
double[][] Ma = new double[2 * n][];
for (int i = 0; i < n; i++) {
double x = P[i].getX();
double y = P[i].getY();
double u = Q[i].getX();
double v = Q[i].getY();
ba[2 * i + 0] = u;
ba[2 * i + 1] = v;
Ma[2 * i + 0] = new double[] { x, y, 1, 0, 0, 0, -u * x, -u * y };
Ma[2 * i + 1] = new double[] { 0, 0, 0, x, y, 1, -v * x, -v * y };
}
RealMatrix M = MatrixUtils.createRealMatrix(Ma);
RealVector b = MatrixUtils.createRealVector(ba);
DecompositionSolver solver = new SingularValueDecomposition(M).getSolver();
RealVector h = solver.solve(b);
a00 = h.getEntry(0);
a01 = h.getEntry(1);
a02 = h.getEntry(2);
a10 = h.getEntry(3);
a11 = h.getEntry(4);
a12 = h.getEntry(5);
a20 = h.getEntry(6);
a21 = h.getEntry(7);
a22 = 1;
}
示例9: solve
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public static double[] solve(final double[][] A, double[] b) {
RealMatrix AA = MatrixUtils.createRealMatrix(A);
RealVector bb = MatrixUtils.createRealVector(b);
DecompositionSolver solver = new LUDecomposition(AA).getSolver();
double[] x = null;
try {
x = solver.solve(bb).toArray();
} catch (SingularMatrixException e) {}
return x;
}
示例10: getScalarVarByName
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
public RealVector getScalarVarByName(String name) {
String varName = "S_" + name;
JsonNode obj = redisService.getValue(spaceIdentifier, varName);
String varIdxName = "IDX_S_" + name + "_";
List<String> keys = redisService.keysWithPrefixPattern(spaceIdentifier, varIdxName);
int size = obj.get("size").asInt();
RealVector vars = MatrixUtils.createRealVector(new double[size]);
initializeVector(vars, obj.get("initial").asDouble(), obj.get("randomize").asBoolean(), false);
List<JsonNode> values = redisService.bulkGet(keys);
for (JsonNode one : values) {
vars.setEntry(one.get(0).asInt(), one.get(1).asDouble());
}
return vars;
}
示例11: getState
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
private RealVector getState(IndexedVectorModel stateModel, ObjectNode state) {
String stateKey = getStateKey(state);
RealVector curVal;
if (stateModel.hasKey(stateKey)) {
curVal = stateModel.getKeyVector(stateKey);
} else {
curVal = MatrixUtils.createRealVector(new double[actionAttrs.size() + 1]);
}
return curVal;
}
示例12: getActionStateValue
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
private RealVector getActionStateValue(ObjectNode action) {
RealVector vec = MatrixUtils.createRealVector(new double[actionAttrs.size()]);
for (int i=0; i< actionAttrs.size(); i++) {
vec.setEntry(i, action.get(actionAttrs.get(i)).asDouble());
}
return vec;
}
示例13: getStateValue
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
private RealVector getStateValue(ObjectNode state) {
RealVector vec = MatrixUtils.createRealVector(new double[actionAttrs.size() + 1]);
double cnt = state.get(modelName + "-state-cnt").asDouble();
vec.setEntry(0, cnt);
for (int i=0; i< actionAttrs.size(); i++) {
vec.setEntry(i + 1, state.get("state-" + actionAttrs.get(i)).asDouble() * cnt);
}
return vec;
}
示例14: requestVectorVar
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
final public void requestVectorVar(String name, int size, int dim, double initial,
boolean randomize, boolean normalize) {
List<RealVector> var = new ArrayList<>(size);
for (int i=0; i<size; i++) {
RealVector vec = MatrixUtils.createRealVector(new double[dim]);
initializeVector(vec, initial, randomize, normalize);
var.add(vec);
}
writeLock.lock();
try {
vectorVars.put(name, var);
} finally {
writeLock.unlock();
}
}
示例15: getScalarVarByName
import org.apache.commons.math3.linear.MatrixUtils; //導入方法依賴的package包/類
final public RealVector getScalarVarByName(String name) {
readLock.lock();
try {
DoubleList var = scalarVars.get(name);
double[] newVar = new double[var.size()];
setDoubleList(newVar, var);
return MatrixUtils.createRealVector(newVar);
} finally {
readLock.unlock();
}
}