code stringlengths 73 34.1k | label stringclasses 1
value |
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public void growMaxLength( int arrayLength , boolean preserveValue ) {
if( arrayLength < 0 )
throw new IllegalArgumentException("Negative array length. Overflow?");
// see if multiplying numRows*numCols will cause an overflow. If it won't then pick the smaller of the two
if( numRows ... | java |
public void growMaxColumns( int desiredColumns , boolean preserveValue ) {
if( col_idx.length < desiredColumns+1 ) {
int[] c = new int[ desiredColumns+1 ];
if( preserveValue )
System.arraycopy(col_idx,0,c,0,col_idx.length);
col_idx = c;
}
} | java |
public void histogramToStructure(int histogram[] ) {
col_idx[0] = 0;
int index = 0;
for (int i = 1; i <= numCols; i++) {
col_idx[i] = index += histogram[i-1];
}
nz_length = index;
growMaxLength( nz_length , false);
if( col_idx[numCols] != nz_length )
... | java |
public void sortIndices(SortCoupledArray_F64 sorter ) {
if( sorter == null )
sorter = new SortCoupledArray_F64();
sorter.quick(col_idx,numCols+1,nz_rows,nz_values);
indicesSorted = true;
} | java |
public void copyStructure( DMatrixSparseCSC orig ) {
reshape(orig.numRows, orig.numCols, orig.nz_length);
this.nz_length = orig.nz_length;
System.arraycopy(orig.col_idx,0,col_idx,0,orig.numCols+1);
System.arraycopy(orig.nz_rows,0,nz_rows,0,orig.nz_length);
} | java |
public static boolean bidiagOuterBlocks( final int blockLength ,
final DSubmatrixD1 A ,
final double gammasU[],
final double gammasV[])
{
// System.out.println("---------- Or... | java |
@Override
public boolean setA(DMatrixRBlock A) {
// Extract a lower triangular solution
if( !decomposer.decompose(A) )
return false;
blockLength = A.blockLength;
return true;
} | java |
@Override
public void solve(DMatrixRBlock B, DMatrixRBlock X) {
if( B.blockLength != blockLength )
throw new IllegalArgumentException("Unexpected blocklength in B.");
DSubmatrixD1 L = new DSubmatrixD1(decomposer.getT(null));
if( X != null ) {
if( X.blockLength != bl... | java |
public void growInternal(int amount ) {
int tmp[] = new int[ data.length + amount ];
System.arraycopy(data,0,tmp,0,data.length);
this.data = tmp;
} | java |
public static boolean lower( double[]T , int indexT , int n ) {
double el_ii;
double div_el_ii=0;
for( int i = 0; i < n; i++ ) {
for( int j = i; j < n; j++ ) {
double sum = T[ indexT + j*n+i];
// todo optimize
for( int k = 0; k < i; k... | java |
public static LinearSolverDense<DMatrixRMaj> general(int numRows , int numCols ) {
if( numRows == numCols )
return linear(numRows);
else
return leastSquares(numRows,numCols);
} | java |
public static LinearSolverDense<DMatrixRMaj> symmPosDef(int matrixWidth ) {
if(matrixWidth < EjmlParameters.SWITCH_BLOCK64_CHOLESKY ) {
CholeskyDecompositionCommon_DDRM decomp = new CholeskyDecompositionInner_DDRM(true);
return new LinearSolverChol_DDRM(decomp);
} else {
... | java |
public void setConvergence( int maxIterations , double ftol , double gtol ) {
this.maxIterations = maxIterations;
this.ftol = ftol;
this.gtol = gtol;
} | java |
private void computeGradientAndHessian(DMatrixRMaj param )
{
// residuals = f(x) - y
function.compute(param, residuals);
computeNumericalJacobian(param,jacobian);
CommonOps_DDRM.multTransA(jacobian, residuals, g);
CommonOps_DDRM.multTransA(jacobian, jacobian, H);
... | java |
public static DMatrixRMaj wrap(int numRows , int numCols , double []data ) {
DMatrixRMaj s = new DMatrixRMaj();
s.data = data;
s.numRows = numRows;
s.numCols = numCols;
return s;
} | java |
public void add( int row , int col , double value ) {
if( col < 0 || col >= numCols || row < 0 || row >= numRows ) {
throw new IllegalArgumentException("Specified element is out of bounds");
}
data[ row * numCols + col ] += value;
} | java |
@Override
public double get( int row , int col ) {
if( col < 0 || col >= numCols || row < 0 || row >= numRows ) {
throw new IllegalArgumentException("Specified element is out of bounds: "+row+" "+col);
}
return data[ row * numCols + col ];
} | java |
public void set(int numRows, int numCols, boolean rowMajor, double ...data)
{
reshape(numRows,numCols);
int length = numRows*numCols;
if( length > this.data.length )
throw new IllegalArgumentException("The length of this matrix's data array is too small.");
if( rowMajor... | java |
@Override
public void solve(DMatrixRMaj B, DMatrixRMaj X) {
blockB.reshape(B.numRows,B.numCols,false);
MatrixOps_DDRB.convert(B,blockB);
// since overwrite B is true X does not need to be passed in
alg.solve(blockB,null);
MatrixOps_DDRB.convert(blockB,X);
} | java |
public List<Complex_F64> getEigenvalues() {
List<Complex_F64> ret = new ArrayList<Complex_F64>();
if( is64 ) {
EigenDecomposition_F64 d = (EigenDecomposition_F64)eig;
for (int i = 0; i < eig.getNumberOfEigenvalues(); i++) {
ret.add(d.getEigenvalue(i));
... | java |
public int getIndexMax() {
int indexMax = 0;
double max = getEigenvalue(0).getMagnitude2();
final int N = getNumberOfEigenvalues();
for( int i = 1; i < N; i++ ) {
double m = getEigenvalue(i).getMagnitude2();
if( m > max ) {
max = m;
... | java |
public int getIndexMin() {
int indexMin = 0;
double min = getEigenvalue(0).getMagnitude2();
final int N = getNumberOfEigenvalues();
for( int i = 1; i < N; i++ ) {
double m = getEigenvalue(i).getMagnitude2();
if( m < min ) {
min = m;
... | java |
public boolean process( DMatrixSparseCSC A ) {
init(A);
TriangularSolver_DSCC.eliminationTree(A,true,parent,gwork);
countNonZeroInR(parent);
countNonZeroInV(parent);
// if more columns than rows it's possible that Q*R != A. That's because a householder
// would need to... | java |
void init( DMatrixSparseCSC A ) {
this.A = A;
this.m = A.numRows;
this.n = A.numCols;
this.next = 0;
this.head = m;
this.tail = m + n;
this.nque = m + 2*n;
if( parent.length < n || leftmost.length < m) {
parent = new int[n];
post ... | java |
void countNonZeroInR( int[] parent ) {
TriangularSolver_DSCC.postorder(parent,n,post,gwork);
columnCounts.process(A,parent,post,countsR);
nz_in_R = 0;
for (int k = 0; k < n; k++) {
nz_in_R += countsR[k];
}
if( nz_in_R < 0)
throw new RuntimeExceptio... | java |
void countNonZeroInV( int []parent ) {
int []w = gwork.data;
findMinElementIndexInRows(leftmost);
createRowElementLinkedLists(leftmost,w);
countNonZeroUsingLinkedList(parent,w);
} | java |
void countNonZeroUsingLinkedList( int parent[] , int ll[] ) {
Arrays.fill(pinv,0,m,-1);
nz_in_V = 0;
m2 = m;
for (int k = 0; k < n; k++) {
int i = ll[head+k]; // remove row i from queue k
nz_in_V++; // count V(k,k) as nonzero
... | java |
public void alias(DMatrixRMaj variable , String name ) {
if( isReserved(name))
throw new RuntimeException("Reserved word or contains a reserved character");
VariableMatrix old = (VariableMatrix)variables.get(name);
if( old == null ) {
variables.put(name, new VariableMatri... | java |
public void alias( double value , String name ) {
if( isReserved(name))
throw new RuntimeException("Reserved word or contains a reserved character. '"+name+"'");
VariableDouble old = (VariableDouble)variables.get(name);
if( old == null ) {
variables.put(name, new Variabl... | java |
public void alias( Object ...args ) {
if( args.length % 2 == 1 )
throw new RuntimeException("Even number of arguments expected");
for (int i = 0; i < args.length; i += 2) {
aliasGeneric( args[i], (String)args[i+1]);
}
} | java |
protected void aliasGeneric( Object variable , String name ) {
if( variable.getClass() == Integer.class ) {
alias(((Integer)variable).intValue(),name);
} else if( variable.getClass() == Double.class ) {
alias(((Double)variable).doubleValue(),name);
} else if( variable.get... | java |
public Sequence compile( String equation , boolean assignment, boolean debug ) {
functions.setManagerTemp(managerTemp);
Sequence sequence = new Sequence();
TokenList tokens = extractTokens(equation,managerTemp);
if( tokens.size() < 3 )
throw new RuntimeException("Too few t... | java |
private void parseMacro( TokenList tokens , Sequence sequence ) {
Macro macro = new Macro();
TokenList.Token t = tokens.getFirst().next;
if( t.word == null ) {
throw new ParseError("Expected the macro's name after "+tokens.getFirst().word);
}
List<TokenList.Token> v... | java |
private void checkForUnknownVariables(TokenList tokens) {
TokenList.Token t = tokens.getFirst();
while( t != null ) {
if( t.getType() == Type.WORD )
throw new ParseError("Unknown variable on right side. "+t.getWord());
t = t.next;
}
} | java |
private Variable createVariableInferred(TokenList.Token t0, Variable variableRight) {
Variable result;
if( t0.getType() == Type.WORD ) {
switch( variableRight.getType()) {
case MATRIX:
alias(new DMatrixRMaj(1,1),t0.getWord());
break;
... | java |
private List<Variable> parseAssignRange(Sequence sequence, TokenList tokens, TokenList.Token t0) {
// find assignment symbol
TokenList.Token tokenAssign = t0.next;
while( tokenAssign != null && tokenAssign.symbol != Symbol.ASSIGN ) {
tokenAssign = tokenAssign.next;
}
... | java |
protected void handleParentheses( TokenList tokens, Sequence sequence ) {
// have a list to handle embedded parentheses, e.g. (((((a)))))
List<TokenList.Token> left = new ArrayList<TokenList.Token>();
// find all of them
TokenList.Token t = tokens.first;
while( t != null ) {
... | java |
protected List<TokenList.Token> parseParameterCommaBlock( TokenList tokens, Sequence sequence ) {
// find all the comma tokens
List<TokenList.Token> commas = new ArrayList<TokenList.Token>();
TokenList.Token token = tokens.first;
int numBracket = 0;
while( token != null ) {
... | java |
protected TokenList.Token parseSubmatrixToExtract(TokenList.Token variableTarget,
TokenList tokens, Sequence sequence) {
List<TokenList.Token> inputs = parseParameterCommaBlock(tokens, sequence);
List<Variable> variables = new ArrayList<Variable>(... | java |
private void addSubMatrixVariables(List<TokenList.Token> inputs, List<Variable> variables) {
for (int i = 0; i < inputs.size(); i++) {
TokenList.Token t = inputs.get(i);
if( t.getType() != Type.VARIABLE )
throw new ParseError("Expected variables only in sub-matrix input, ... | java |
protected TokenList.Token parseBlockNoParentheses(TokenList tokens, Sequence sequence, boolean insideMatrixConstructor) {
// search for matrix bracket operations
if( !insideMatrixConstructor ) {
parseBracketCreateMatrix(tokens, sequence);
}
// First create sequences from an... | java |
private void stripCommas(TokenList tokens) {
TokenList.Token t = tokens.getFirst();
while( t != null ) {
TokenList.Token next = t.next;
if( t.getSymbol() == Symbol.COMMA ) {
tokens.remove(t);
}
t = next;
}
} | java |
protected void parseSequencesWithColons(TokenList tokens , Sequence sequence ) {
TokenList.Token t = tokens.getFirst();
if( t == null )
return;
int state = 0;
TokenList.Token start = null;
TokenList.Token middle = null;
TokenList.Token prev = t;
bo... | java |
protected void parseIntegerLists(TokenList tokens) {
TokenList.Token t = tokens.getFirst();
if( t == null || t.next == null )
return;
int state = 0;
TokenList.Token start = null;
TokenList.Token prev = t;
boolean last = false;
while( true ) {
... | java |
protected void parseCombineIntegerLists(TokenList tokens) {
TokenList.Token t = tokens.getFirst();
if( t == null || t.next == null )
return;
int numFound = 0;
TokenList.Token start = null;
TokenList.Token end = null;
while( t != null ) {
if( t.g... | java |
private static boolean isVariableInteger(TokenList.Token t) {
if( t == null )
return false;
return t.getScalarType() == VariableScalar.Type.INTEGER;
} | java |
protected void parseBracketCreateMatrix(TokenList tokens, Sequence sequence) {
List<TokenList.Token> left = new ArrayList<TokenList.Token>();
TokenList.Token t = tokens.getFirst();
while( t != null ) {
TokenList.Token next = t.next;
if( t.getSymbol() == Symbol.BRACKET_L... | java |
protected void parseNegOp(TokenList tokens, Sequence sequence) {
if( tokens.size == 0 )
return;
TokenList.Token token = tokens.first;
while( token != null ) {
TokenList.Token next = token.next;
escape:
if( token.getSymbol() == Symbol.MINUS ) {
... | java |
protected void parseOperationsL(TokenList tokens, Sequence sequence) {
if( tokens.size == 0 )
return;
TokenList.Token token = tokens.first;
if( token.getType() != Type.VARIABLE )
throw new ParseError("The first token in an equation needs to be a variable and not "+toke... | java |
protected void parseOperationsLR(Symbol ops[], TokenList tokens, Sequence sequence) {
if( tokens.size == 0 )
return;
TokenList.Token token = tokens.first;
if( token.getType() != Type.VARIABLE )
throw new ParseError("The first token in an equation needs to be a variable... | java |
public <T extends Variable> T lookupVariable(String token) {
Variable result = variables.get(token);
return (T)result;
} | java |
void insertMacros(TokenList tokens ) {
TokenList.Token t = tokens.getFirst();
while( t != null ) {
if( t.getType() == Type.WORD ) {
Macro v = lookupMacro(t.word);
if (v != null) {
TokenList.Token before = t.previous;
Lis... | java |
protected static boolean isTargetOp( TokenList.Token token , Symbol[] ops ) {
Symbol c = token.symbol;
for (int i = 0; i < ops.length; i++) {
if( c == ops[i])
return true;
}
return false;
} | java |
protected static boolean isOperatorLR( Symbol s ) {
if( s == null )
return false;
switch( s ) {
case ELEMENT_DIVIDE:
case ELEMENT_TIMES:
case ELEMENT_POWER:
case RDIVIDE:
case LDIVIDE:
case TIMES:
case POWER... | java |
protected boolean isReserved( String name ) {
if( functions.isFunctionName(name))
return true;
for (int i = 0; i < name.length(); i++) {
if( !isLetter(name.charAt(i)) )
return true;
}
return false;
} | java |
public Equation process( String equation , boolean debug ) {
compile(equation,true,debug).perform();
return this;
} | java |
public void print( String equation ) {
// first assume it's just a variable
Variable v = lookupVariable(equation);
if( v == null ) {
Sequence sequence = compile(equation,false,false);
sequence.perform();
v = sequence.output;
}
if( v instanceof... | java |
public static double computeTauAndDivide(final int j, final int numRows ,
final double[] u , final double max) {
double tau = 0;
// double div_max = 1.0/max;
// if( Double.isInfinite(div_max)) {
for( int i = j; i < numRows; i++ ) {
... | java |
public static boolean isSameStructure(DMatrixSparseCSC a , DMatrixSparseCSC b) {
if( a.numRows == b.numRows && a.numCols == b.numCols && a.nz_length == b.nz_length) {
for (int i = 0; i <= a.numCols; i++) {
if( a.col_idx[i] != b.col_idx[i] )
return false;
... | java |
public static boolean isVector(DMatrixSparseCSC a) {
return (a.numCols == 1 && a.numRows > 1) || (a.numRows == 1 && a.numCols>1);
} | java |
public static boolean isSymmetric( DMatrixSparseCSC A , double tol ) {
if( A.numRows != A.numCols )
return false;
int N = A.numCols;
for (int i = 0; i < N; i++) {
int idx0 = A.col_idx[i];
int idx1 = A.col_idx[i+1];
for (int index = idx0; index <... | java |
public void implicitDoubleStep( int x1 , int x2 ) {
if( printHumps )
System.out.println("Performing implicit double step");
// compute the wilkinson shift
double z11 = A.get(x2 - 1, x2 - 1);
double z12 = A.get(x2 - 1, x2);
double z21 = A.get(x2, x2 - 1);
dou... | java |
public void performImplicitDoubleStep(int x1, int x2 , double real , double img ) {
double a11 = A.get(x1,x1);
double a21 = A.get(x1+1,x1);
double a12 = A.get(x1,x1+1);
double a22 = A.get(x1+1,x1+1);
double a32 = A.get(x1+2,x1+1);
double p_plus_t = 2.0*real;
dou... | java |
public boolean process(DMatrixRMaj A , int numSingularValues, DMatrixRMaj nullspace ) {
decomposition.decompose(A);
if( A.numRows > A.numCols ) {
Q.reshape(A.numCols,Math.min(A.numRows,A.numCols));
decomposition.getQ(Q, true);
} else {
Q.reshape(A.numCols, A.... | java |
public static boolean isInverse(DMatrixRMaj a , DMatrixRMaj b , double tol ) {
if( a.numRows != b.numRows || a.numCols != b.numCols ) {
return false;
}
int numRows = a.numRows;
int numCols = a.numCols;
for( int i = 0; i < numRows; i++ ) {
for( int j = 0;... | java |
public static boolean isRowsLinearIndependent( DMatrixRMaj A )
{
// LU decomposition
LUDecomposition<DMatrixRMaj> lu = DecompositionFactory_DDRM.lu(A.numRows,A.numCols);
if( lu.inputModified() )
A = A.copy();
if( !lu.decompose(A))
throw new RuntimeException("... | java |
public static boolean isConstantVal(DMatrixRMaj mat , double val , double tol )
{
// see if the result is an identity matrix
int index = 0;
for( int i = 0; i < mat.numRows; i++ ) {
for( int j = 0; j < mat.numCols; j++ ) {
if( !(Math.abs(mat.get(index++)-val) <= to... | java |
public static boolean isDiagonalPositive( DMatrixRMaj a ) {
for( int i = 0; i < a.numRows; i++ ) {
if( !(a.get(i,i) >= 0) )
return false;
}
return true;
} | java |
public static int rank(DMatrixRMaj A , double threshold ) {
SingularValueDecomposition_F64<DMatrixRMaj> svd = DecompositionFactory_DDRM.svd(A.numRows,A.numCols,false,false,true);
if( svd.inputModified() )
A = A.copy();
if( !svd.decompose(A) )
throw new RuntimeException(... | java |
public static int countNonZero(DMatrixRMaj A){
int total = 0;
for (int row = 0, index=0; row < A.numRows; row++) {
for (int col = 0; col < A.numCols; col++,index++) {
if( A.data[index] != 0 ) {
total++;
}
}
}
ret... | java |
public static boolean invertSPD(DMatrixRMaj mat, DMatrixRMaj result ) {
if( mat.numRows != mat.numCols )
throw new IllegalArgumentException("Must be a square matrix");
result.reshape(mat.numRows,mat.numRows);
if( mat.numRows <= UnrolledCholesky_DDRM.MAX ) {
// L*L' = A
... | java |
public static DMatrixRMaj identity(int numRows , int numCols )
{
DMatrixRMaj ret = new DMatrixRMaj(numRows,numCols);
int small = numRows < numCols ? numRows : numCols;
for( int i = 0; i < small; i++ ) {
ret.set(i,i,1.0);
}
return ret;
} | java |
public static void extract( DMatrix src,
int srcY0, int srcY1,
int srcX0, int srcX1,
DMatrix dst ) {
((ReshapeMatrix)dst).reshape(srcY1-srcY0,srcX1-srcX0);
extract(src,srcY0,srcY1,srcX0,srcX1,dst,0,0);
} | java |
public static void extract( DMatrixRMaj src,
int rows[] , int rowsSize ,
int cols[] , int colsSize , DMatrixRMaj dst ) {
if( rowsSize != dst.numRows || colsSize != dst.numCols )
throw new MatrixDimensionException("Unexpected number of r... | java |
public static void extract(DMatrixRMaj src, int indexes[] , int length , DMatrixRMaj dst ) {
if( !MatrixFeatures_DDRM.isVector(dst))
throw new MatrixDimensionException("Dst must be a vector");
if( length != dst.getNumElements())
throw new MatrixDimensionException("Unexpected numb... | java |
public static DMatrixRMaj extractRow(DMatrixRMaj a , int row , DMatrixRMaj out ) {
if( out == null)
out = new DMatrixRMaj(1,a.numCols);
else if( !MatrixFeatures_DDRM.isVector(out) || out.getNumElements() != a.numCols )
throw new MatrixDimensionException("Output must be a vector o... | java |
public static DMatrixRMaj extractColumn(DMatrixRMaj a , int column , DMatrixRMaj out ) {
if( out == null)
out = new DMatrixRMaj(a.numRows,1);
else if( !MatrixFeatures_DDRM.isVector(out) || out.getNumElements() != a.numRows )
throw new MatrixDimensionException("Output must be a ve... | java |
public static void removeColumns( DMatrixRMaj A , int col0 , int col1 )
{
if( col1 < col0 ) {
throw new IllegalArgumentException("col1 must be >= col0");
} else if( col0 >= A.numCols || col1 >= A.numCols ) {
throw new IllegalArgumentException("Columns which are to be removed ... | java |
public static void scaleRow( double alpha , DMatrixRMaj A , int row ) {
int idx = row*A.numCols;
for (int col = 0; col < A.numCols; col++) {
A.data[idx++] *= alpha;
}
} | java |
public static void scaleCol( double alpha , DMatrixRMaj A , int col ) {
int idx = col;
for (int row = 0; row < A.numRows; row++, idx += A.numCols) {
A.data[idx] *= alpha;
}
} | java |
public static BMatrixRMaj elementLessThan(DMatrixRMaj A , double value , BMatrixRMaj output )
{
if( output == null ) {
output = new BMatrixRMaj(A.numRows,A.numCols);
}
output.reshape(A.numRows, A.numCols);
int N = A.getNumElements();
for (int i = 0; i < N; i++)... | java |
public static DMatrixRMaj elements(DMatrixRMaj A , BMatrixRMaj marked , DMatrixRMaj output ) {
if( A.numRows != marked.numRows || A.numCols != marked.numCols )
throw new MatrixDimensionException("Input matrices must have the same shape");
if( output == null )
output = new DMatrix... | java |
public static int countTrue(BMatrixRMaj A) {
int total = 0;
int N = A.getNumElements();
for (int i = 0; i < N; i++) {
if( A.data[i] )
total++;
}
return total;
} | java |
public static void symmLowerToFull( DMatrixRMaj A )
{
if( A.numRows != A.numCols )
throw new MatrixDimensionException("Must be a square matrix");
final int cols = A.numCols;
for (int row = 0; row < A.numRows; row++) {
for (int col = row+1; col < cols; col++) {
... | java |
public void init( DMatrixRMaj A ) {
if( A.numRows != A.numCols)
throw new IllegalArgumentException("Must be square");
if( A.numCols != N ) {
N = A.numCols;
QT.reshape(N,N, false);
if( w.length < N ) {
w = new double[ N ];
... | java |
public static void inner_reorder_lower(DMatrix1Row A , DMatrix1Row B )
{
final int cols = A.numCols;
B.reshape(cols,cols);
Arrays.fill(B.data,0);
for (int i = 0; i <cols; i++) {
for (int j = 0; j <=i; j++) {
B.data[i*cols+j] += A.data[i]*A.data[j];
... | java |
public static void pow(ComplexPolar_F64 a , int N , ComplexPolar_F64 result )
{
result.r = Math.pow(a.r,N);
result.theta = N*a.theta;
} | java |
public static void sqrt(Complex_F64 input, Complex_F64 root)
{
double r = input.getMagnitude();
double a = input.real;
root.real = Math.sqrt((r+a)/2.0);
root.imaginary = Math.sqrt((r-a)/2.0);
if( input.imaginary < 0 )
root.imaginary = -root.imaginary;
} | java |
public boolean computeDirect( DMatrixRMaj A ) {
initPower(A);
boolean converged = false;
for( int i = 0; i < maxIterations && !converged; i++ ) {
// q0.print();
CommonOps_DDRM.mult(A,q0,q1);
double s = NormOps_DDRM.normPInf(q1);
Comm... | java |
private boolean checkConverged(DMatrixRMaj A) {
double worst = 0;
double worst2 = 0;
for( int j = 0; j < A.numRows; j++ ) {
double val = Math.abs(q2.data[j] - q0.data[j]);
if( val > worst ) worst = val;
val = Math.abs(q2.data[j] + q0.data[j]);
if( ... | java |
public void setup( int numSamples , int sampleSize ) {
mean = new double[ sampleSize ];
A.reshape(numSamples,sampleSize,false);
sampleIndex = 0;
numComponents = -1;
} | java |
public double[] getBasisVector( int which ) {
if( which < 0 || which >= numComponents )
throw new IllegalArgumentException("Invalid component");
DMatrixRMaj v = new DMatrixRMaj(1,A.numCols);
CommonOps_DDRM.extract(V_t,which,which+1,0,A.numCols,v,0,0);
return v.data;
} | java |
public double[] sampleToEigenSpace( double[] sampleData ) {
if( sampleData.length != A.getNumCols() )
throw new IllegalArgumentException("Unexpected sample length");
DMatrixRMaj mean = DMatrixRMaj.wrap(A.getNumCols(),1,this.mean);
DMatrixRMaj s = new DMatrixRMaj(A.getNumCols(),1,tru... | java |
public double[] eigenToSampleSpace( double[] eigenData ) {
if( eigenData.length != numComponents )
throw new IllegalArgumentException("Unexpected sample length");
DMatrixRMaj s = new DMatrixRMaj(A.getNumCols(),1);
DMatrixRMaj r = DMatrixRMaj.wrap(numComponents,1,eigenData);
... | java |
public double response( double[] sample ) {
if( sample.length != A.numCols )
throw new IllegalArgumentException("Expected input vector to be in sample space");
DMatrixRMaj dots = new DMatrixRMaj(numComponents,1);
DMatrixRMaj s = DMatrixRMaj.wrap(A.numCols,1,sample);
CommonO... | java |
public static <T extends DMatrix> boolean decomposeSafe(DecompositionInterface<T> decomp, T M ) {
if( decomp.inputModified() ) {
return decomp.decompose(M.<T>copy());
} else {
return decomp.decompose(M);
}
} | java |
public static DMatrix2 extractColumn( DMatrix2x2 a , int column , DMatrix2 out ) {
if( out == null) out = new DMatrix2();
switch( column ) {
case 0:
out.a1 = a.a11;
out.a2 = a.a21;
break;
case 1:
out.a1 = a.a12;
... | java |
public static boolean decomposeSafe(DecompositionInterface<ZMatrixRMaj> decomposition, ZMatrixRMaj a) {
if( decomposition.inputModified() ) {
a = a.copy();
}
return decomposition.decompose(a);
} | java |
public static void invert( final int blockLength ,
final boolean upper ,
final DSubmatrixD1 T ,
final DSubmatrixD1 T_inv ,
final double temp[] )
{
if( upper )
throw new Ill... | java |
public static DMatrixRMaj[] span(int dimen, int numVectors , Random rand ) {
if( dimen < numVectors )
throw new IllegalArgumentException("The number of vectors must be less than or equal to the dimension");
DMatrixRMaj u[] = new DMatrixRMaj[numVectors];
u[0] = RandomMatrices_DDRM.r... | java |
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