public LUDecomposition(Matrix A, boolean autoPivot) {
LU = A.copy();
int m = LU.m, n = LU.n;
pivsign = 1;
piv = new int[m];
for (int i = 0; i < m; i++) piv[i] = i;
// Outer loop.
for (int j = 0; j < n; j++) {
if (n > 1000) System.out.printf("%d / %d\r", j, n);
// Make a copy of the j-th column to localize references.
Vec LUcolj = LU.getColumn(j);
// Apply previous transformations.
for (int i = 0; i < m; i++) {
Vec LUrowi = LU.getRow(i);
// Most of the time is spent in the following dot product.
int kmax = Math.min(i, j);
double s = LUrowi.dotProduct(LUcolj, 0, kmax - 1);
LUcolj.plusEquals(i, -s);
LUrowi.plusEquals(j, -s);
}
// Find pivot and exchange if necessary.
int p = j;
if (autoPivot) {
for (int i = j + 1; i < m; i++) {
if (Math.abs(LUcolj.get(i)) > Math.abs(LUcolj.get(p))) {
p = i;
}
}
}
if (p != j) {
LU.swapRows(p, j);
int k = piv[p];
piv[p] = piv[j];
piv[j] = k;
pivsign = -pivsign;
}
// Compute multipliers.
if (j < n && j < m && LU.get(j, j) != 0.0) {
double LUjj = LU.get(j, j);
for (int i = j + 1; i < m; i++) {
LU.timesEquals(i, j, 1.0 / LUjj);
}
}
}
}
@Override
public void mutablePairwiseDivide(Vec b) {
if (this.length() != b.length())
throw new ArithmeticException("Vectors must have the same length");
clearCaches();
for (int i = 0; i < used; i++) values[i] /= b.get(indexes[i]); // zeros stay zero
}
public Tensor3 setRow(final int i, final int j, final Vec val) {
if (val.dim() != dim3)
throw new IllegalArgumentException(
"val.dim() != dim3, val.dim() = " + val.dim() + ", dim3 = " + dim3);
final int index = index(i, j, 0);
for (int l = 0; l < dim3; l++) vec.set(index + l, val.get(l));
return this;
}
@Override
public boolean equals(Object obj) {
if (!(obj instanceof Vec)) return false;
Vec otherVec = (Vec) obj;
if (this.length() != otherVec.length()) return false;
int z = 0;
for (int i = 0; i < length(); i++) {
// Move through until we hit the next null element, comparing the other vec to zero
while (z < used && indexes[z] > i) if (otherVec.get(i++) != 0) return false;
// We made it! (or are at the end). Is our non zero value the same?
if (z < used && indexes[z] == i) if (values[z++] != otherVec.get(i)) return false;
}
return true;
}
@Override
public double pNormDist(double p, Vec y) {
if (this.length() != y.length())
throw new ArithmeticException("Vectors must be of the same length");
double norm = 0;
if (y instanceof SparseVector) {
int p1 = 0, p2 = 0;
SparseVector b = (SparseVector) y;
while (p1 < this.used && p2 < b.used) {
int a1 = indexes[p1], a2 = b.indexes[p2];
if (a1 == a2) {
norm += Math.pow(Math.abs(this.values[p1] - b.values[p2]), p);
p1++;
p2++;
} else if (a1 > a2) norm += Math.pow(Math.abs(b.values[p2++]), p);
else // a1 < a2, this vec has a value, other does not
norm += Math.pow(Math.abs(this.values[p1++]), p);
}
// One of them is now empty.
// So just sum up the rest of the elements
while (p1 < this.used) norm += Math.pow(Math.abs(this.values[p1++]), p);
while (p2 < b.used) norm += Math.pow(Math.abs(b.values[p2++]), p);
} else {
int z = 0;
for (int i = 0; i < length(); i++) {
// Move through until we hit the next null element, comparing the other vec to zero
while (z < used && indexes[z] > i) norm += Math.pow(Math.abs(-y.get(i++)), p);
// We made it! (or are at the end). Is our non zero value the same?
if (z < used && indexes[z] == i) norm += Math.pow(Math.abs(values[z] - y.get(i)), p);
}
}
return Math.pow(norm, 1.0 / p);
}
@Override
public double dot(Vec v) {
double dot = 0;
if (v instanceof SparseVector) {
SparseVector b = (SparseVector) v;
int p1 = 0, p2 = 0;
while (p1 < used && p2 < b.used) {
int a1 = indexes[p1], a2 = b.indexes[p2];
if (a1 == a2) dot += values[p1++] * b.values[p2++];
else if (a1 > a2) p2++;
else p1++;
}
} else // it is dense
for (int i = 0; i < used; i++) dot += values[i] * v.get(indexes[i]);
return dot;
}
@Override
public void mutableAdd(double c, Vec v) {
clearCaches();
if (c == 0.0) return;
if (v instanceof SparseVector) {
SparseVector b = (SparseVector) v;
int p1 = 0, p2 = 0;
while (p1 < used && p2 < b.used) {
int a1 = indexes[p1], a2 = b.indexes[p2];
if (a1 == a2) {
values[p1] += c * b.values[p2];
p1++;
p2++;
} else if (a1 > a2) {
// 0 + some value is that value, set it
this.set(a2, c * b.values[p2]);
/*
* p2 must be increment becase were moving to the next value
*
* p1 must be be incremented becase a2 was less thenn the current index.
* So the inseration occured before p1, so for indexes[p1] to == a1,
* p1 must be incremented
*
*/
p1++;
p2++;
} else // a1 < a2, thats adding 0 to this vector, nothing to do.
{
p1++;
}
}
// One of them is now empty.
// If b is not empty, we must add b to this. If b is empty, we would be adding zeros to this
// [so we do nothing]
while (p2 < b.used)
this.set(b.indexes[p2], c * b.values[p2++]); // TODO Can be done more efficently
} else if (v.isSparse()) {
if (v.nnz() == 0) return;
int p1 = 0;
Iterator<IndexValue> iter = v.getNonZeroIterator();
IndexValue iv = iter.next();
while (p1 < used && iv != null) {
int a1 = indexes[p1];
int a2 = iv.getIndex();
if (a1 == a2) {
values[p1++] += c * iv.getValue();
if (iter.hasNext()) iv = iter.next();
else break;
} else if (a1 > a2) {
this.set(a2, c * iv.getValue());
p1++;
if (iter.hasNext()) iv = iter.next();
else break;
} else p1++;
}
} else {
// Else it is dense
for (int i = 0; i < length(); i++) this.set(i, this.get(i) + c * v.get(i));
}
}
