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/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.math.hadoop.stochasticsvd.qr;
import java.util.Arrays;
import java.util.Iterator;
import java.util.List;
import com.google.common.collect.Lists;
import org.apache.mahout.math.AbstractVector;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Matrix;
import org.apache.mahout.math.OrderedIntDoubleMapping;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.UpperTriangular;
/**
* Givens Thin solver. Standard Givens operations are reordered in a way that
* helps us to push them thru MapReduce operations in a block fashion.
*/
public class GivensThinSolver {
private double[] vARow;
private double[] vQtRow;
private final double[][] mQt;
private final double[][] mR;
private int qtStartRow;
private int rStartRow;
private int m;
private final int n; // m-row cnt, n- column count, m>=n
private int cnt;
private final double[] cs = new double[2];
public GivensThinSolver(int m, int n) {
if (!(m >= n)) {
throw new IllegalArgumentException("Givens thin QR: must be true: m>=n");
}
this.m = m;
this.n = n;
mQt = new double[n][];
mR = new double[n][];
vARow = new double[n];
vQtRow = new double[m];
for (int i = 0; i < n; i++) {
mQt[i] = new double[this.m];
mR[i] = new double[this.n];
}
cnt = 0;
}
public void reset() {
cnt = 0;
}
public void solve(Matrix a) {
assert a.rowSize() == m;
assert a.columnSize() == n;
double[] aRow = new double[n];
for (int i = 0; i < m; i++) {
Vector aRowV = a.viewRow(i);
for (int j = 0; j < n; j++) {
aRow[j] = aRowV.getQuick(j);
}
appendRow(aRow);
}
}
public boolean isFull() {
return cnt == m;
}
public int getM() {
return m;
}
public int getN() {
return n;
}
public int getCnt() {
return cnt;
}
public void adjust(int newM) {
if (newM == m) {
// no adjustment is required.
return;
}
if (newM < n) {
throw new IllegalArgumentException("new m can't be less than n");
}
if (newM < cnt) {
throw new IllegalArgumentException(
"new m can't be less than rows accumulated");
}
vQtRow = new double[newM];
// grow or shrink qt rows
if (newM > m) {
// grow qt rows
for (int i = 0; i < n; i++) {
mQt[i] = Arrays.copyOf(mQt[i], newM);
System.arraycopy(mQt[i], 0, mQt[i], newM - m, m);
Arrays.fill(mQt[i], 0, newM - m, 0);
}
} else {
// shrink qt rows
for (int i = 0; i < n; i++) {
mQt[i] = Arrays.copyOfRange(mQt[i], m - newM, m);
}
}
m = newM;
}
public void trim() {
adjust(cnt);
}
/**
* api for row-by-row addition
*
* @param aRow
*/
public void appendRow(double[] aRow) {
if (cnt >= m) {
throw new IllegalStateException("thin QR solver fed more rows than initialized for");
}
try {
/*
* moving pointers around is inefficient but for the sanity's sake i am
* keeping it this way so i don't have to guess how R-tilde index maps to
* actual block index
*/
Arrays.fill(vQtRow, 0);
vQtRow[m - cnt - 1] = 1;
int height = cnt > n ? n : cnt;
System.arraycopy(aRow, 0, vARow, 0, n);
if (height > 0) {
givens(vARow[0], getRRow(0)[0], cs);
applyGivensInPlace(cs[0], cs[1], vARow, getRRow(0), 0, n);
applyGivensInPlace(cs[0], cs[1], vQtRow, getQtRow(0), 0, m);
}
for (int i = 1; i < height; i++) {
givens(getRRow(i - 1)[i], getRRow(i)[i], cs);
applyGivensInPlace(cs[0], cs[1], getRRow(i - 1), getRRow(i), i,
n - i);
applyGivensInPlace(cs[0], cs[1], getQtRow(i - 1), getQtRow(i), 0,
m);
}
/*
* push qt and r-tilde 1 row down
*
* just swap the references to reduce GC churning
*/
pushQtDown();
double[] swap = getQtRow(0);
setQtRow(0, vQtRow);
vQtRow = swap;
pushRDown();
swap = getRRow(0);
setRRow(0, vARow);
vARow = swap;
} finally {
cnt++;
}
}
private double[] getQtRow(int row) {
return mQt[(row += qtStartRow) >= n ? row - n : row];
}
private void setQtRow(int row, double[] qtRow) {
mQt[(row += qtStartRow) >= n ? row - n : row] = qtRow;
}
private void pushQtDown() {
qtStartRow = qtStartRow == 0 ? n - 1 : qtStartRow - 1;
}
private double[] getRRow(int row) {
row += rStartRow;
return mR[row >= n ? row - n : row];
}
private void setRRow(int row, double[] rrow) {
mR[(row += rStartRow) >= n ? row - n : row] = rrow;
}
private void pushRDown() {
rStartRow = rStartRow == 0 ? n - 1 : rStartRow - 1;
}
/*
* warning: both of these return actually n+1 rows with the last one being //
* not interesting.
*/
public UpperTriangular getRTilde() {
UpperTriangular packedR = new UpperTriangular(n);
for (int i = 0; i < n; i++) {
packedR.assignNonZeroElementsInRow(i, getRRow(i));
}
return packedR;
}
public double[][] getThinQtTilde() {
if (qtStartRow != 0) {
/*
* rotate qt rows into place
*
* double[~500][], once per block, not a big deal.
*/
double[][] qt = new double[n][];
System.arraycopy(mQt, qtStartRow, qt, 0, n - qtStartRow);
System.arraycopy(mQt, 0, qt, n - qtStartRow, qtStartRow);
return qt;
}
return mQt;
}
public static void applyGivensInPlace(double c, double s, double[] row1,
double[] row2, int offset, int len) {
int n = offset + len;
for (int j = offset; j < n; j++) {
double tau1 = row1[j];
double tau2 = row2[j];
row1[j] = c * tau1 - s * tau2;
row2[j] = s * tau1 + c * tau2;
}
}
public static void applyGivensInPlace(double c, double s, Vector row1,
Vector row2, int offset, int len) {
int n = offset + len;
for (int j = offset; j < n; j++) {
double tau1 = row1.getQuick(j);
double tau2 = row2.getQuick(j);
row1.setQuick(j, c * tau1 - s * tau2);
row2.setQuick(j, s * tau1 + c * tau2);
}
}
public static void applyGivensInPlace(double c, double s, int i, int k,
Matrix mx) {
int n = mx.columnSize();
for (int j = 0; j < n; j++) {
double tau1 = mx.get(i, j);
double tau2 = mx.get(k, j);
mx.set(i, j, c * tau1 - s * tau2);
mx.set(k, j, s * tau1 + c * tau2);
}
}
public static void fromRho(double rho, double[] csOut) {
if (rho == 1) {
csOut[0] = 0;
csOut[1] = 1;
return;
}
if (Math.abs(rho) < 1) {
csOut[1] = 2 * rho;
csOut[0] = Math.sqrt(1 - csOut[1] * csOut[1]);
return;
}
csOut[0] = 2 / rho;
csOut[1] = Math.sqrt(1 - csOut[0] * csOut[0]);
}
public static void givens(double a, double b, double[] csOut) {
if (b == 0) {
csOut[0] = 1;
csOut[1] = 0;
return;
}
if (Math.abs(b) > Math.abs(a)) {
double tau = -a / b;
csOut[1] = 1 / Math.sqrt(1 + tau * tau);
csOut[0] = csOut[1] * tau;
} else {
double tau = -b / a;
csOut[0] = 1 / Math.sqrt(1 + tau * tau);
csOut[1] = csOut[0] * tau;
}
}
public static double toRho(double c, double s) {
if (c == 0) {
return 1;
}
if (Math.abs(s) < Math.abs(c)) {
return Math.signum(c) * s / 2;
} else {
return Math.signum(s) * 2 / c;
}
}
public static void mergeR(UpperTriangular r1, UpperTriangular r2) {
TriangularRowView r1Row = new TriangularRowView(r1);
TriangularRowView r2Row = new TriangularRowView(r2);
int kp = r1Row.size();
assert kp == r2Row.size();
double[] cs = new double[2];
for (int v = 0; v < kp; v++) {
for (int u = v; u < kp; u++) {
givens(r1Row.setViewedRow(u).get(u), r2Row.setViewedRow(u - v).get(u),
cs);
applyGivensInPlace(cs[0], cs[1], r1Row, r2Row, u, kp - u);
}
}
}
public static void mergeR(double[][] r1, double[][] r2) {
int kp = r1[0].length;
assert kp == r2[0].length;
double[] cs = new double[2];
for (int v = 0; v < kp; v++) {
for (int u = v; u < kp; u++) {
givens(r1[u][u], r2[u - v][u], cs);
applyGivensInPlace(cs[0], cs[1], r1[u], r2[u - v], u, kp - u);
}
}
}
public static void mergeRonQ(UpperTriangular r1, UpperTriangular r2,
double[][] qt1, double[][] qt2) {
TriangularRowView r1Row = new TriangularRowView(r1);
TriangularRowView r2Row = new TriangularRowView(r2);
int kp = r1Row.size();
assert kp == r2Row.size();
assert kp == qt1.length;
assert kp == qt2.length;
int r = qt1[0].length;
assert qt2[0].length == r;
double[] cs = new double[2];
for (int v = 0; v < kp; v++) {
for (int u = v; u < kp; u++) {
givens(r1Row.setViewedRow(u).get(u), r2Row.setViewedRow(u - v).get(u),
cs);
applyGivensInPlace(cs[0], cs[1], r1Row, r2Row, u, kp - u);
applyGivensInPlace(cs[0], cs[1], qt1[u], qt2[u - v], 0, r);
}
}
}
public static void mergeRonQ(double[][] r1, double[][] r2, double[][] qt1,
double[][] qt2) {
int kp = r1[0].length;
assert kp == r2[0].length;
assert kp == qt1.length;
assert kp == qt2.length;
int r = qt1[0].length;
assert qt2[0].length == r;
double[] cs = new double[2];
/*
* pairwise givens(a,b) so that a come off main diagonal in r1 and bs come
* off u-th upper subdiagonal in r2.
*/
for (int v = 0; v < kp; v++) {
for (int u = v; u < kp; u++) {
givens(r1[u][u], r2[u - v][u], cs);
applyGivensInPlace(cs[0], cs[1], r1[u], r2[u - v], u, kp - u);
applyGivensInPlace(cs[0], cs[1], qt1[u], qt2[u - v], 0, r);
}
}
}
// returns merged Q (which in this case is the qt1)
public static double[][] mergeQrUp(double[][] qt1, double[][] r1,
double[][] r2) {
int kp = qt1.length;
int r = qt1[0].length;
double[][] qTilde = new double[kp][];
for (int i = 0; i < kp; i++) {
qTilde[i] = new double[r];
}
mergeRonQ(r1, r2, qt1, qTilde);
return qt1;
}
// returns merged Q (which in this case is the qt1)
public static double[][] mergeQrUp(double[][] qt1, UpperTriangular r1, UpperTriangular r2) {
int kp = qt1.length;
int r = qt1[0].length;
double[][] qTilde = new double[kp][];
for (int i = 0; i < kp; i++) {
qTilde[i] = new double[r];
}
mergeRonQ(r1, r2, qt1, qTilde);
return qt1;
}
public static double[][] mergeQrDown(double[][] r1, double[][] qt2, double[][] r2) {
int kp = qt2.length;
int r = qt2[0].length;
double[][] qTilde = new double[kp][];
for (int i = 0; i < kp; i++) {
qTilde[i] = new double[r];
}
mergeRonQ(r1, r2, qTilde, qt2);
return qTilde;
}
public static double[][] mergeQrDown(UpperTriangular r1, double[][] qt2, UpperTriangular r2) {
int kp = qt2.length;
int r = qt2[0].length;
double[][] qTilde = new double[kp][];
for (int i = 0; i < kp; i++) {
qTilde[i] = new double[r];
}
mergeRonQ(r1, r2, qTilde, qt2);
return qTilde;
}
public static double[][] computeQtHat(double[][] qt, int i,
Iterator rIter) {
UpperTriangular rTilde = rIter.next();
for (int j = 1; j < i; j++) {
mergeR(rTilde, rIter.next());
}
if (i > 0) {
qt = mergeQrDown(rTilde, qt, rIter.next());
}
while (rIter.hasNext()) {
qt = mergeQrUp(qt, rTilde, rIter.next());
}
return qt;
}
// test helpers
public static boolean isOrthonormal(double[][] qt, boolean insufficientRank, double epsilon) {
int n = qt.length;
int rank = 0;
for (int i = 0; i < n; i++) {
Vector ei = new DenseVector(qt[i], true);
double norm = ei.norm(2);
if (Math.abs(1.0 - norm) < epsilon) {
rank++;
} else if (Math.abs(norm) > epsilon) {
return false; // not a rank deficiency, either
}
for (int j = 0; j <= i; j++) {
Vector ej = new DenseVector(qt[j], true);
double dot = ei.dot(ej);
if (!(Math.abs((i == j && rank > j ? 1.0 : 0.0) - dot) < epsilon)) {
return false;
}
}
}
return insufficientRank ? rank < n : rank == n;
}
public static boolean isOrthonormalBlocked(Iterable qtHats,
boolean insufficientRank, double epsilon) {
int n = qtHats.iterator().next().length;
int rank = 0;
for (int i = 0; i < n; i++) {
List ei = Lists.newArrayList();
// Vector e_i=new DenseVector (qt[i],true);
for (double[][] qtHat : qtHats) {
ei.add(new DenseVector(qtHat[i], true));
}
double norm = 0;
for (Vector v : ei) {
norm += v.dot(v);
}
norm = Math.sqrt(norm);
if (Math.abs(1 - norm) < epsilon) {
rank++;
} else if (Math.abs(norm) > epsilon) {
return false; // not a rank deficiency, either
}
for (int j = 0; j <= i; j++) {
List ej = Lists.newArrayList();
for (double[][] qtHat : qtHats) {
ej.add(new DenseVector(qtHat[j], true));
}
// Vector e_j = new DenseVector ( qt[j], true);
double dot = 0;
for (int k = 0; k < ei.size(); k++) {
dot += ei.get(k).dot(ej.get(k));
}
if (!(Math.abs((i == j && rank > j ? 1 : 0) - dot) < epsilon)) {
return false;
}
}
}
return insufficientRank ? rank < n : rank == n;
}
private static final class TriangularRowView extends AbstractVector {
private final UpperTriangular viewed;
private int rowNum;
private TriangularRowView(UpperTriangular viewed) {
super(viewed.columnSize());
this.viewed = viewed;
}
TriangularRowView setViewedRow(int row) {
rowNum = row;
return this;
}
@Override
public boolean isDense() {
return true;
}
@Override
public boolean isSequentialAccess() {
return false;
}
@Override
public Iterator iterator() {
throw new UnsupportedOperationException();
}
@Override
public Iterator iterateNonZero() {
throw new UnsupportedOperationException();
}
@Override
public double getQuick(int index) {
return viewed.getQuick(rowNum, index);
}
@Override
public Vector like() {
throw new UnsupportedOperationException();
}
@Override
public void setQuick(int index, double value) {
viewed.setQuick(rowNum, index, value);
}
@Override
public int getNumNondefaultElements() {
throw new UnsupportedOperationException();
}
@Override
public double getLookupCost() {
return 1;
}
@Override
public double getIteratorAdvanceCost() {
return 1;
}
@Override
public boolean isAddConstantTime() {
return true;
}
@Override
public Matrix matrixLike(int rows, int columns) {
throw new UnsupportedOperationException();
}
/**
* Used internally by assign() to update multiple indices and values at once.
* Only really useful for sparse vectors (especially SequentialAccessSparseVector).
*
* If someone ever adds a new type of sparse vectors, this method must merge (index, value) pairs into the vector.
*
* @param updates a mapping of indices to values to merge in the vector.
*/
@Override
public void mergeUpdates(OrderedIntDoubleMapping updates) {
int[] indices = updates.getIndices();
double[] values = updates.getValues();
for (int i = 0; i < updates.getNumMappings(); ++i) {
viewed.setQuick(rowNum, indices[i], values[i]);
}
}
}
}
