eva2/src/eva2/tools/math/Mathematics.java

1305 lines
31 KiB
Java

package eva2.tools.math;
import java.util.Arrays;
import java.util.List;
import eva2.server.go.tools.DoubleArrayComparator;
import eva2.tools.EVAERROR;
import eva2.tools.math.Jama.Matrix;
import eva2.tools.math.interpolation.BasicDataSet;
import eva2.tools.math.interpolation.InterpolationException;
import eva2.tools.math.interpolation.SplineInterpolation;
//created at June 27 2006
/**
* @author Andreas Dräger
*/
public class Mathematics {
/**
* Computes the full adjoint matrix.
*
* @param a
* @return
*/
public static double[][] adjoint(double[][] a) {
if (a == null)
return null;
if (a.length != a[0].length)
return null;
double[][] b = new double[a.length][a.length];
for (int i = 0; i < a.length; i++)
for (int j = 0; j < a.length; j++)
b[i][j] = adjoint(a, i, j);
return b;
}
/**
* Computes the adjoint of the matrix element at the position (k, l).
*
* @param a
* @param k
* @param l
* @return
*/
public static double adjoint(double[][] a, int k, int l) {
return Math.pow(-1, k + l + 2) * determinant(submatrix(a, k, l));
}
/**
* This computes the determinant of the given matrix
*
* @param matrix
* @return The determinant or null if there is no determinant (if the matrix
* is not square).
*/
public static double determinant(double[][] matrix) {
if (matrix == null)
return 0;
if (matrix.length != matrix[0].length)
return 0;
if (matrix.length == 1)
return matrix[0][0];
if (matrix.length == 2)
return matrix[0][0] * matrix[1][1] - matrix[0][1] * matrix[1][0];
if (matrix.length == 3)
return matrix[0][0] * matrix[1][1] * matrix[2][2] + matrix[0][1]
* matrix[1][2] * matrix[2][0] + matrix[0][2] * matrix[1][0]
* matrix[2][1] - matrix[2][0] * matrix[1][1] * matrix[0][2]
- matrix[2][1] * matrix[1][2] * matrix[0][0] - matrix[2][2]
* matrix[1][0] * matrix[0][1];
double det = 0;
for (int k = 0; k < matrix.length; k++) {
if (matrix[0][k] != 0)
det += matrix[0][k] * adjoint(matrix, 0, k);
}
return det;
}
/**
* Computes the root-Distance function. For example root = 2 gives the
* Euclidian Distance.
*
* @param x
* a vector
* @param y
* another vector
* @param root
* what kind of distance funktion
* @return the distance of x and y
* @throws Exception
* if x and y have different dimensions an exception is thrown.
*/
public static double dist(double[] x, double[] y, int root) {
if (x.length != y.length)
throw new RuntimeException(
"The vectors x and y must have the same dimension");
if (root == 0)
throw new RuntimeException("There is no 0-root!");
double d = 0;
for (int i = 0; i < x.length; i++)
d += Math.pow(Math.abs(x[i] - y[i]), root);
return Math.pow(d, (double) 1 / root);
}
/**
* Computes the euclidian distance function.
*
* @param x
* a vector
* @param y
* another vector
* @param root
* what kind of distance funktion
* @return the distance of x and y
* @throws Exception
* if x and y have different dimensions an exception is thrown.
*/
public static double euclidianDist(double[] x, double[] y) {
if (x.length != y.length)
throw new RuntimeException(
"The vectors x and y must have the same dimension");
double d = 0;
for (int i = 0; i < x.length; i++)
d += Math.pow(Math.abs(x[i] - y[i]), 2);
return Math.sqrt(d);
}
/**
* Expand a vector to a higher dimension (len) by filling it up with a
* constant value.
*
* @param x
* @param len
* @param v
* @return
*/
public static double[] expandVector(double[] x, int len, double v) {
if (len <= x.length) {// not really an error, just perform identity
// System.err.println("Error, invalid length in expandVector, expecting l>"
// + x.length);
return x;
} else {
double[] expanded = new double[len];
System.arraycopy(x, 0, expanded, 0, x.length);
for (int i = x.length; i < expanded.length; i++)
expanded[i] = v;
return expanded;
}
}
/**
* Fill the front of an array with data from a given source array.
*
* @param dest
* @param src
*/
public static void fillFront(double[] dest, double[] src) {
System.arraycopy(src, 0, dest, 0, Math.min(dest.length, src.length));
}
/**
* Return first multiple of interval which is larger than len.
*
* @param len
* @param interval
* @return
*/
public static double firstMultipleAbove(double len, double interval) {
double startVal, dn = (len / interval);
startVal = Math.round(dn - 0.5) * interval;
if (startVal < len || (len == 0)) {
startVal += interval;
}
return startVal;
}
/**
* Return the vector of interval length values in any dimension.
* ret[i]=range[i][1]-range[i][0];
*
* @param range
* @return
*/
public static double[] getAbsRange(double[][] range) {
double[] ret = new double[range.length];
for (int i = 0; i < ret.length; i++) {
ret[i] = range[i][1] - range[i][0];
}
return ret;
}
/**
* Calculate the average length of the range intervals over all dimensions.
*
* @param range
* @return the average length of the range intervals
*/
public static double getAvgRange(double[][] range) {
double sum = 0.;
for (int i = 0; i < range.length; i++)
sum += (range[i][1] - range[i][0]);
return sum / range.length;
}
/**
* Calculates the norm of the given vector relative to the problem range.
*
* @param vector
* a double vector within the range
* @param range
* the range in each dimension
* @return measure of the length relative to the problem range
*/
public static double getRelativeLength(double[] vector, double[][] range) {
double sumV = 0;
double sumR = 0;
for (int i = 0; i < range.length; i++) {
sumV += Math.pow(vector[i], 2);
sumR += Math.pow(range[i][1] - range[i][0], 2);
}
sumV = Math.sqrt(sumV);
sumR = Math.sqrt(sumR);
return sumV / sumR;
}
/**
* Set rotation matrix entries along i/j axis. w is expected in radians.
*
* @param tmp
* @param i
* @param j
* @param w
*/
public static void getRotationEntriesSingleAxis(Matrix tmp, int i, int j,
double w) {
double cosw = Math.cos(w);
double sinw = Math.sin(w);
tmp.set(i, i, cosw);
tmp.set(i, j, sinw);
tmp.set(j, i, -sinw);
tmp.set(j, j, cosw);
}
public static Matrix getRotationMatrix(double w, int dim) {
Matrix A = Matrix.identity(dim, dim);
Matrix tmp = Matrix.identity(dim, dim);
for (int i = 1; i < dim; i++) {
// System.out.println("deg: "+(w/Math.PI)*180);
// make partial rotation matrix
getRotationEntriesSingleAxis(tmp, i - 1, i, w);
A = tmp.times(A); // add to resulting rotation
// reset tmp matrix to unity
resetRotationEntriesSingleAxis(tmp, i - 1, i);
}
// Matrix vec = new Matrix(dim, 1);
// for (int i=0; i<dim; i++) vec.set(i,0, 1);
// vec = A.times(vec);
// vec = A.times(vec);
return A;
}
/**
* Return a matrix A which performs the rotation of vec to (1,0,0,...0) if
* forward is true, else return a matrix B which performs the reverted
* rotation, where B=A' (transposition).
*
* @param vec
* @return
*/
public static Matrix getRotationMatrix(Matrix vec) {
Matrix A = Matrix
.identity(vec.getRowDimension(), vec.getRowDimension());
Matrix tmp = Matrix.identity(vec.getRowDimension(), vec
.getRowDimension());
Matrix z = (Matrix) vec.clone();
z.multi(1. / z.norm2()); // normalize
for (int i = 1; i < vec.getRowDimension(); i++) {
double w = Math.atan2(z.get(i, 0), z.get(0, 0));// calc angle
// between the
// projection of x
// and x0 in
// x0-xi-plane
// System.out.println("deg: "+(w/Math.PI)*180);
// make partial rotation matrix
getRotationEntriesSingleAxis(tmp, 0, i, w);
A = tmp.times(A); // add to resulting rotation
z = tmp.times(z); // z is now 0 in i-th component
// reset tmp matrix to unity
resetRotationEntriesSingleAxis(tmp, 0, i);
}
return A;
}
/**
* This method return a vector from a to b
*
* @param a
* first vector
* @param b
* second vectors
* @return the vector from a to b
*/
public static double[] getVectorFromTo(double[] a, double[] b) {
return vvSub(b, a);
}
/**
* Computes a hyperbolic interpolation of the two point (x0,f0) and (x1,f1).
*
* @param x
* @param x0
* @param x1
* @param f0
* @param f1
* @return
*/
public static double hyperbolicInterpolation(double x, double x0,
double x1, double f0, double f1) {
if (x1 == 0)
return lerp(f0, f1, (x - x0) / (-x0));
double l = lerp(x0 / x1, 1, x);
if (l == 0)
return linearInterpolation(x, x0, x1, f0, f1);
return lerp(f0, f1, x / l);
}
/**
* Intersect two ranges resulting in the maximum range contained in both.
*
* @param modRange
* @param makeRange
* @param destRange
*/
public static void intersectRange(double[][] r1, double[][] r2,
double[][] destRange) {
for (int i = 0; i < r1.length && i < r2.length; i++) {
destRange[i][0] = Math.max(r1[i][0], r2[i][0]);
destRange[i][1] = Math.min(r1[i][1], r2[i][1]);
}
}
/**
* Computes the inverse of the given matrix or returns null if there is no
* inverse (if the determinant is 0).
*
* @param a
* @return
*/
public static double[][] inverse(double[][] a) {
if (a == null)
return null;
if (a.length != a[0].length)
return null;
double det = determinant(a);
if (det == 0)
return null;
double[][] b = adjoint(a);
for (int i = 0; i < a.length; i++)
for (int j = 0; j < a.length; j++)
b[i][j] /= det;
return b;
}
/**
* Check whether the given value lies within the interval in every
* dimension.
*
* @param x
* @param range
* @return true if the vector lies within the range, else false
*/
public static boolean isInRange(double v, double lower, double upper) {
if (v < lower || (v > upper))
return false;
return true;
}
/**
* Check whether the given vector lies within the range in every dimension.
*
* @param x
* @param range
* @return true if the vector lies within the range, else false
*/
public static boolean isInRange(double[] x, double[][] range) {
for (int i = 0; i < x.length; i++) {
if (x[i] < range[i][0] || (x[i] > range[i][1]))
return false;
}
return true;
}
/**
* Returns false if a vector contains NaN, its squared sum is NaN or the
* absolute sum is smaller than 10^-18.
*
* @param d
* @return
*/
public static boolean isValidVec(double[] d) {
double sum = 0;
for (int i = 0; i < d.length; i++) {
if (Double.isNaN(d[i]))
return false;
sum += Math.pow(d[i], 2);
}
if (Double.isNaN(sum))
return false;
if (Math.abs(sum) < 0.000000000000000001)
return false;
return true;
}
/**
* @param f0
* @param f1
* @param t
* @return
*/
private static double lerp(double f0, double f1, double t) {
return f0 + (f1 - f0) * t;
}
/**
* This method gives a linear interpolation of the function values of the
* given argument/function value pairs.
*
* @param x
* The argument at the point with unknown function value
* @param x0
* The argument at the last position with a function value
* @param x1
* The argument at the next known fuction value
* @param f0
* The function value at the position x0
* @param f1
* The function value at the position x1
* @return The function value at position x given by linear interpolation.
*/
public static double linearInterpolation(double x, double x0, double x1,
double f0, double f1) {
if (x1 == x0)
return f0;
return lerp(f0, f1, (x - x0) / (x1 - x0));
}
public static double max(double[] vals) {
double maxVal = vals[0];
for (int i = 1; i < vals.length; i++)
maxVal = Math.max(maxVal, vals[i]);
return maxVal;
}
/**
* Computes the mean for an array of doubles.
*
* @param vector
* the array
* @return the mean
*/
public static double mean(double[] vector) {
if (vector.length == 0) {
return 0;
}
return sum(vector) / (double) vector.length;
}
/**
* This method returns a mean vector from a whole array of vectors.
*
* @param d
* d[i] the vectors, d[i][j] the jth coordinate of the ith vector
* @return The mean vector.
*/
public static double[] meanVect(double[][] d) {
double[] result = new double[d[0].length];
for (int i = 0; i < d.length; i++) {
for (int j = 0; j < d[i].length; j++) {
result[j] += d[i][j];
}
}
for (int i = 0; i < result.length; i++) {
result[i] = result[i] / ((double) d.length);
}
return result;
}
/**
* Computes the median of a given double vector by sorting x.
*
* @param x
* a vector of doubles
* @param cloneX
* flag whether x should be cloned before sorting.
* @return the median
*/
public static double median(double[] x, boolean cloneX) {
double[] in;
if (cloneX)
in = (double[]) x.clone();
else
in = x;
if (in.length == 1)
return in[0];
else if (in.length == 2)
return (in[0] + in[1]) / 2.;
else {
Arrays.sort(in);
if (in.length % 2 != 0)
return in[(in.length - 1) / 2];
else
return (in[in.length / 2] + in[(in.length / 2) + 1]) / 2.;
}
}
/**
* Computes the median of a given list of double vectors by sorting it. If
* the size is even, no direct median is defined - in that case it may be
* interpolated by the two closest elements or one of them may be selected
* (always the smaller one depending on the comparator.
*
* @see #DoubleArrayComparator
* @param dblArrList
* a list of double vectors
* @param interpolate
* flag whether, for even size, the median is interpolated
* @return the median
*/
public static double[] median(List<double[]> dblArrList, boolean interpolate) {
java.util.Collections.sort(dblArrList, new DoubleArrayComparator()); // by
// default,
// the
// comparator
// uses
// pareto
// dominance
int len = dblArrList.size();
if (len % 2 != 0)
return dblArrList.get((len - 1) / 2);
else {
double[] med = dblArrList.get(len / 2).clone();
if (interpolate) {
vvAdd(med, dblArrList.get((len / 2) + 1), med);
svDiv(2, med, med);
}
return med;
}
}
public static double min(double[] vals) {
double minVal = vals[0];
for (int i = 1; i < vals.length; i++)
minVal = Math.min(minVal, vals[i]);
return minVal;
}
/**
* Computes the 2-norm of an array of doubles.
*
* @param doubles
* the array of double
* @return the 2-norm of the elements
*/
public static double norm(double[] d) {
double sqSum = 0;
for (int i = 0; i < d.length; i++) {
sqSum += d[i] * d[i];
}
return Math.sqrt(sqSum);
}
/**
* Normalizes the doubles in the array by their sum, so that they add up to
* one.
*
* @param doubles
* the array of double
* @exception IllegalArgumentException
* if sum is Zero or NaN
*/
public static double[] normalizeSum(double[] v) {
double[] res = new double[v.length];
svMult(1. / sum(v), v, res);
return res;
}
/**
* Normalizes the doubles in the array by their sum, so that they add up to
* one.
*
* @param doubles
* the array of double
* @exception IllegalArgumentException
* if sum is Zero or NaN
*/
public static void normalizeSum(double[] v, double[] res) {
svMult(1. / sum(v), v, res);
}
/**
* Normalize the given vector to an euclidian length of 1.
*
* @param v
* @return
*/
public static double[] normVect(double[] v) {
return svDiv(norm(v), v);
}
/**
* Normalize the given vector to an euclidian length of 1.
*
* @param v
* @return
*/
public static void normVect(double[] v, double[] res) {
svDiv(norm(v), v, res);
}
/**
* Return the product over a double vector.
*
* @param vals
* @return
*/
public static double product(double[] vals) {
double prod = 1.;
for (int i = 0; i < vals.length; i++) {
prod *= vals[i];
}
return prod;
}
// /**
// * Normalizes the doubles in the array using the given value so that they
// sum up to 1.
// *
// * @param doubles the array of double
// * @param sum the value by which the doubles are to be normalized
// * @exception IllegalArgumentException if sum is zero or NaN
// */
// public static void normalize(double[] v, double sum, double[] res) {
// if (Double.isNaN(sum)) {
// throw new IllegalArgumentException("Can't normalize array. Sum is NaN.");
// }
// if (sum == 0) {
// // Maybe this should just be a return.
// throw new
// IllegalArgumentException("Can't normalize array. Sum is zero.");
// }
// svMult(1/sum, v, res);
// }
/**
* Project the values in x to the range given. The range must be an vector
* of 2d-arrays each of which containing lower and upper bound in the i-th
* dimension. x must not be longer than the available ranges. Values
* exceeding the bounds are set on the bound. The number of bound violations
* is returned.
*
* @param x
* @param range
* @return
*/
public static int projectToRange(double[] x, double[][] range) {
int viols = 0;
if (x.length > range.length)
System.err
.println("Invalid vector length, x is longer than range! (Mathematics.projectToRange)");
for (int i = 0; i < x.length; i++) {
if (x[i] < range[i][0]) {
viols++;
x[i] = range[i][0];
} else if (x[i] > range[i][1]) {
viols++;
x[i] = range[i][1];
}
}
return viols;
}
/**
* Project the value to the range given.
*
* @param v
* @param min
* @param max
* @return the closest value to v within [min,max]
*/
public static double projectValue(double v, double min, double max) {
if (v < min) {
return min;
} else if (v > max) {
return max;
} else
return v;
}
/**
* Create a random vector, the components will be set to gaussian
* distributed values with mean zero and the given standard deviation.
*
* @param dim
* the desired dimension
* @param stdDev
* the gaussian standard deviation
* @return random vector
*/
public static double[] randomVector(int dim, double stdDev) {
double[] vect = new double[dim];
for (int j = 0; j < vect.length; j++) {
vect[j] = RNG.gaussianDouble(stdDev);
}
return vect;
}
/**
* Reflect the entries of x which violate the bounds to within the range.
* Return the number of violating dimensions.
*
* @param x
* @param range
* @return the number of violating dimensions
*/
public static int reflectBounds(double[] x, double[][] range) {
int viols = 0;
double d = 0.;
for (int i = 0; i < x.length; i++) {
double dimLen = range[i][1] - range[i][0];
if (dimLen <= 0.) {
EVAERROR
.errorMsgOnce("Error in reflectBounds: empty range! (possibly multiple errors)");
} else {
if (x[i] < range[i][0]) {
viols++;
d = range[i][0] - x[i];
while (d > dimLen)
d -= dimLen; // avoid violating the other bound
// immediately
x[i] = range[i][0] + d;
} else if (x[i] > range[i][1]) {
viols++;
d = x[i] - range[i][1];
while (d > dimLen)
d -= dimLen; // avoid violating the other bound
// immediately
x[i] = range[i][1] - d;
}
}
}
return viols;
}
/**
* Simple version of reflection of a value moving by a step and bouncing of
* min and max values like a pool ball. Precondition is min <= val <= max,
* post condition is min <= retVal <= max.
*
* @param val
* @param step
* @param min
* @param max
* @return
*/
public static double reflectValue(double val, double step, double min,
double max) {
while (step > (max - min))
step -= (max - min);
if ((val + step) > max)
return (2 * max - val - step);
if ((val + step) < min)
return (2 * min - val - step);
return (val += step);
}
/**
* Computes the relative distance of vector x to vector y. Therefore the
* difference of x[i] and y[i] is divided by y[i] for every i. If y[i] is
* zero, the default value def is used instead. The sum of these differences
* gives the distance function.
*
* @param x
* A vector
* @param y
* The reference vector
* @param def
* The default value to be use to avoid division by zero.
* @return The relative distance of x to y.
* @throws Exception
*/
public static double relDist(double[] x, double[] y, double def)
throws Exception {
if (x.length != y.length)
throw new Exception(
"The vectors x and y must have the same dimension");
double d = 0;
for (int i = 0; i < x.length; i++)
if (y[i] != 0)
d += Math.pow(((x[i] - y[i]) / y[i]), 2);
else
d += def;
return d;
}
/**
* Reset single axis rotation matrix to unity.
*/
public static void resetRotationEntriesSingleAxis(Matrix tmp, int i, int j) {
tmp.set(i, i, 1);
tmp.set(i, j, 0);
tmp.set(j, i, 0);
tmp.set(j, j, 1);
}
public static void revertArray(Object[] src, Object[] dst) {
if (dst.length >= src.length) {
for (int i = 0; i < src.length; i++) {
dst[src.length - i - 1] = src[i];
}
} else
System.err.println("Mismatching array lengths!");
}
/**
* Rotate the vector by angle alpha around axis i/j
*
* @param vect
* @param alpha
* @param i
* @param j
*/
public static void rotate(double[] vect, double alpha, int i, int j) {
double xi = vect[i];
double xj = vect[j];
vect[i] = (xi * Math.cos(alpha)) - (xj * Math.sin(alpha));
vect[j] = (xi * Math.sin(alpha)) + (xj * Math.cos(alpha));
}
/**
* Rotate a given double vector using a rotation matrix. If the matrix is
* null, x will be returned unchanged. Matrix dimensions must fit.
*
* @param x
* @param rotMatrix
* @return the rotated vector
*/
public static double[] rotate(double[] x, Matrix rotMatrix) {
if (rotMatrix != null) {
Matrix resVec = rotMatrix.times(new Matrix(x, x.length));
x = resVec.getColumnPackedCopy();
return x;
} else
return x;
}
/**
* Rotate the vector along all axes by angle alpha or a uniform random value
* in [-alpha, alpha] if randomize is true.
*
* @param vect
* @param alpha
* @param randomize
*/
public static void rotateAllAxes(double[] vect, double alpha,
boolean randomize) {
for (int i = 0; i < vect.length - 1; i++) {
for (int j = i + 1; j < vect.length; j++) {
if (randomize)
rotate(vect, RNG.randomDouble(-alpha, alpha), i, j);
else
rotate(vect, alpha, i, j);
}
}
}
/**
* Rotate the vector along all axes i/j by angle alphas[i][j].
*
* @param vect
* @param alphas
*/
public static void rotateAllAxes(double[] vect, double[][] alphas) {
for (int i = 0; i < vect.length - 1; i++) {
for (int j = i + 1; j < vect.length; j++) {
rotate(vect, alphas[i][j], i, j);
}
}
}
/**
* Scale a range by the given factor, meaning that the interval in each
* dimension is extended (fact>1) or reduced (fact<1) by the defined ratio
* around the center.
*
* @param rangeScaleFact
* @param range
*/
public static void scaleRange(double rangeScaleFact, double[][] range) {
double[] intervalLengths = Mathematics.getAbsRange(range);
double[] tmpInts = Mathematics.svMult(rangeScaleFact, intervalLengths);
Mathematics.vvSub(tmpInts, intervalLengths, tmpInts); // this is what
// must be added
// to range
// interval
for (int i = 0; i < range.length; i++) {
range[i][0] -= tmpInts[i] / 2;
range[i][1] += tmpInts[i] / 2;
}
}
/**
* Shift bounds by a constant value in every dimension.
*
* @param range
* @return
*/
public static void shiftRange(double[][] range, double dist) {
for (int i = 0; i < range.length; i++) {
svAdd(dist, range[i]);
}
}
/**
* Shift bounds by a constant value in every dimension. The dists must be of
* dimensions as the range.
*
* @param range
* @return
*/
public static void shiftRange(double[][] range, double[] dists) {
for (int i = 0; i < range.length; i++) {
svAdd(dists[i], range[i]);
}
}
// <<<<<<< .working
// /**
// * Computes a spline interpolation of the two point (x0,f0) and (x1,f1).
// *
// * @param x
// * @param x0
// * @param x1
// * @param f0
// * @param f1
// * @return If an error with the spline occurs, a linear interpolation will
// be
// * returned.
// */
// /* public static double splineInterpolation(double x, double x0, double
// x1,
// double f0, double f1) {
// try {
// double[] t = { x0, x1 }, f = { f0, f1 };
// SplineInterpolation spline = new SplineInterpolation(new BasicDataSet(t,
// f, 1));
// return spline.getY(x);
// } catch (InterpolationException e) {
// e.printStackTrace();
// }
// return linearInterpolation(x, x0, x1, f0, f1);
// }*/
// =======
/**
* Computes a spline interpolation of the two point (x0,f0) and (x1,f1).
*
* @param x
* @param x0
* @param x1
* @param f0
* @param f1
* @return If an error with the spline occurs, a linear interpolation will
* be returned.
*/
public static double splineInterpolation(double x, double x0, double x1,
double f0, double f1) {
try {
double[] t = { x0, x1 }, f = { f0, f1 };
SplineInterpolation spline = new SplineInterpolation(
new BasicDataSet(t, f, 1));
return spline.getY(x);
} catch (InterpolationException e) {
e.printStackTrace();
}
return linearInterpolation(x, x0, x1, f0, f1);
}
/**
* This computes the submatrix of the given matrix as a result by scraching
* out the row k and the column l.
*
* @param a
* @param k
* @param l
* @return
*/
public static double[][] submatrix(double[][] a, int k, int l) {
double b[][] = new double[a.length - 1][a[0].length - 1];
int i, j, m = 0, n = 0;
for (i = 0; i < a.length; i++) {
if (i == k)
continue;
for (j = 0; j < a[0].length; j++) {
if (j == l)
continue;
b[m][n++] = a[i][j];
}
m++;
n = 0;
}
return b;
}
/**
* Computes the sum of the elements of an array of doubles.
*
* @param doubles
* the array of double
* @return the sum of the elements
*/
public static double sum(double[] doubles) {
double sum = 0;
for (int i = 0; i < doubles.length; i++) {
sum += doubles[i];
}
return sum;
}
/**
* Computes the sum of the elements of an array of integers.
*
* @param ints
* the array of integers
* @return the sum of the elements
*/
public static int sum(int[] ints) {
int sum = 0;
for (int i = 0; i < ints.length; i++) {
sum += ints[i];
}
return sum;
}
/**
* Add each entry of a vector with a scalar in a new vector.
*
* @param s
* @param v
* @return
*/
public static double[] svAdd(double s, double[] v) {
double[] res = new double[v.length];
svAdd(s, v, res);
return res;
}
/**
* Add each entry of a vector with a scalar in a result vector.
*
* @param s
* @param v
* @return
*/
public static void svAdd(double s, double[] v, double[] res) {
for (int i = 0; i < v.length; i++) {
res[i] = v[i] + s;
}
}
/**
* Return a new vector which is c = (v_i/s).
*
* @param s
* @param v
* @return
*/
public static double[] svDiv(double s, double[] v) {
double[] res = new double[v.length];
for (int i = 0; i < v.length; i++) {
res[i] = v[i] / s;
}
return res;
}
/**
* Divide by scalar in place, res_i = v_i/s.
*
* @param s
* @param v
* @return
*/
public static void svDiv(double s, double[] v, double[] res) {
for (int i = 0; i < v.length; i++) {
res[i] = v[i] / s;
}
}
/**
* Multiplies (scales) every element of the array v with s returning a new
* vector.
*
* @param s
* a scalar
* @param v
* an array to be multiplied with s.
* @return a scaled array.
*/
public static double[] svMult(double s, double[] v) {
double[] res = new double[v.length];
for (int i = 0; i < v.length; i++) {
res[i] = v[i] * s;
}
return res;
}
/**
* Multiplies (scales) every element of the array v with s in place.
*
* @param s
* a scalar
* @param v
* an array to be multiplied with s.
* @return a scaled array.
*/
public static void svMult(double s, double[] v, double[] res) {
for (int i = 0; i < v.length; i++) {
res[i] = v[i] * s;
}
}
/**
* Add vectors scaled: res[i] = s*v[i] + w[i]
*
* @param s
* @param v
* @param w
* @return
*/
public static void svvAddScaled(double s, double[] v, double[] w,
double[] res) {
for (int i = 0; i < v.length; i++) {
res[i] = s * v[i] + w[i];
}
}
/**
* Add vectors returning a new vector c = a + b;
*
* @param a
* @param b
* @return a new vector c = a + b
*/
public static double[] vvAdd(double[] a, double[] b) {
double[] result = new double[a.length];
for (int i = 0; i < a.length; i++) {
result[i] = a[i] + b[i];
}
return result;
}
/**
* Add vectors in place setting res = v1 + v2.
*
* @param v1
* @param v2
* @return vector addition
*/
public static void vvAdd(double[] v1, double[] v2, double[] res) {
vvAddOffs(v1, 0, v2, 0, res, 0, v1.length);
}
/**
* Calculate r=1/2 * sqrt(sum(sqr(upperBound_i - lowerBound_i))).
*
* @param range
* @return the average length of the range intervals
*/
public static double getAvgRangeL2(double[][] range) {
double sum = 0.;
for (int i = 0; i < range.length; i++) {
double d = (range[i][1] - range[i][0]);
sum += (d * d);
}
return Math.sqrt(sum) / 2.;
}
/**
* Add vectors in place setting with an offset within the target vector,
* meaning that res[resOffs+i]=v1[v1Offs+i]+v2[v2Offs+i] for i in length.
*
* @param v1
* @param v2
* @return vector addition
*/
public static void vvAddOffs(double[] v1, int v1Offs, double[] v2,
int v2Offs, double[] res, int resOffs, int len) {
for (int i = 0; i < len; i++) {
res[resOffs + i] = v1[v1Offs + i] + v2[v2Offs + i];
}
}
/**
* Scalar product of two vectors returning sum_i (a_i * b_i).
*
* @param a
* @param b
* @return
*/
public static double vvMult(double[] a, double[] b) {
double result = 0;
for (int i = 0; i < a.length; i++) {
result += a[i] * b[i];
}
return result;
}
/**
* Component wise multiplication of vectors: res[i]=u[i]*v[i]
*
* @param s
* @param v
* @return
*/
public static void vvMultCw(double[] u, double[] v, double[] res) {
for (int i = 0; i < res.length; i++) {
res[i] = u[i] * v[i];
}
}
/**
* Subtract vectors returning a new vector c = a - b.
*
* @param a
* @param b
* @return a new vector c = a - b
*/
public static double[] vvSub(double[] a, double[] b) {
double[] result = new double[a.length];
vvSub(a, b, result);
return result;
}
/**
* Subtract vectors returning a new vector c = a - b.
*
* @param a
* @param b
* @return a new vector c = a - b
*/
public static void vvSub(double[] a, double[] b, double[] res) {
for (int i = 0; i < a.length; i++) {
res[i] = a[i] - b[i];
}
}
/**
* Return a vector of given length containing zeroes.
*
* @param n
* @return
*/
public static double[] zeroes(int n) {
return makeVector(0, n);
}
/**
* Create a double vector of length dim filled with value d.
*
* @param d
* @param dim
* @return a double vector of length dim filled with value d
*/
public static double[] makeVector(double d, int dim) {
double[] ret = new double[dim];
Arrays.fill(ret, d);
return ret;
}
/**
* Scales a vector with the given scalar.
*
* @param scale
* @param vec
*/
public static void scale(double scale, double[] vec) {
for (int i=0; i<vec.length; i++) {
vec[i] *= scale;
}
}
}