public double distanciaEuclidiana(int x1, int x2, int y1, int y2) {
double a, b, c;
a = Math.pow(x2 - x1, 2);
b = Math.pow(y2 - y1, 2);
c = Math.sqrt(a + b);
return (c);
}
public int getWrongTwo() {
int wrongTwo = (int) (Math.random() * (Math.pow(2, bits)));
while (wrongTwo == answer || wrongTwo == wrongOne)
wrongOne = (int) (Math.random() * (Math.pow(2, bits)));
return wrongTwo;
}
public void generateCaverns(int count) {
for (int i = 0; i < count; i++) {
m_logger.debug("Generating underground erosion bubbles: " + i + "/" + count);
int x = m_random.nextInt(m_width);
int y = m_random.nextInt(m_height);
int z = m_random.nextInt(m_depth / 4);
int radius = m_random.nextInt(60) + 40;
radius = 6;
int type = m_random.nextInt(100);
if (type > 90) type = BlockConstants.LAVA;
else if (type > 45) type = BlockConstants.AIR;
else type = BlockConstants.WATER;
for (int m = 0; m < 2; m++) {
BUBBLE_GEN:
for (int j = x - radius; j < x + radius * 2; j++) {
if (j < 0) j = 0;
if (j >= m_width) break BUBBLE_GEN;
for (int k = y - radius; k < y + radius * 2; k++) {
if (k < 0) k = 0;
if (k >= m_height) break BUBBLE_GEN;
for (int l = z - radius; l < z + radius; l++) {
if (l < 0) l = 0;
if (l >= m_depth) break BUBBLE_GEN;
double distance =
Math.sqrt(Math.pow(j - x, 2) + Math.pow(k - y, 2) + Math.pow(l - z, 2));
if (Math.abs(distance / radius) <= Math.abs(m_random.nextGaussian())) {
m_blocks[j][k][l] = (byte) type;
}
}
}
}
x++;
}
}
}
public void plantTrees() {
ArrayList<Position> treeList = new ArrayList<Position>();
for (int x = 0; x < m_width; x++) {
for (int y = 0; y < m_height; y++) {
boolean tooClose = false;
for (Position p : treeList) {
double distance = Math.sqrt(Math.pow(p.getX() - x, 2) + Math.pow(p.getY() - y, 2));
if (distance < 30) tooClose = true;
}
if (!tooClose) {
if (m_random.nextInt(100) <= 5) {
for (int z = m_depth - 1; z > 0; z--) {
if ((m_blocks[x][y][z] == BlockConstants.DIRT
|| m_blocks[x][y][z] == BlockConstants.GRASS)
&& m_blocks[x][y][z + 1] == BlockConstants.AIR) {
plantTree(x, y, z);
treeList.add(new Position(x, y, z));
break;
} else if (z < m_depth - 1 && m_blocks[x][y][z + 1] != BlockConstants.AIR) {
break;
}
}
}
}
}
}
}
/**
* Perform the mutation operation
*
* @param probability Mutation probability
* @param solution The solution to mutate
* @throws JMException
*/
public void doMutation(double probability, Solution solution) throws JMException {
double rnd, delta1, delta2, mut_pow, deltaq;
double y, yl, yu, val, xy;
XReal x = new XReal(solution);
for (int var = 0; var < solution.numberOfVariables(); var++) {
if (PseudoRandom.randDouble() <= probability) {
y = x.getValue(var);
yl = x.getLowerBound(var);
yu = x.getUpperBound(var);
delta1 = (y - yl) / (yu - yl);
delta2 = (yu - y) / (yu - yl);
rnd = PseudoRandom.randDouble();
mut_pow = 1.0 / (eta_m_ + 1.0);
if (rnd <= 0.5) {
xy = 1.0 - delta1;
val = 2.0 * rnd + (1.0 - 2.0 * rnd) * (Math.pow(xy, (eta_m_ + 1.0)));
deltaq = java.lang.Math.pow(val, mut_pow) - 1.0;
} else {
xy = 1.0 - delta2;
val = 2.0 * (1.0 - rnd) + 2.0 * (rnd - 0.5) * (java.lang.Math.pow(xy, (eta_m_ + 1.0)));
deltaq = 1.0 - (java.lang.Math.pow(val, mut_pow));
}
y = y + deltaq * (yu - yl);
if (y < yl) y = yl;
if (y > yu) y = yu;
x.setValue(var, y);
}
} // for
} // doMutation
@Override
public double pNorm(double p) {
double norm = 0;
for (int i = 0; i < used; i++) norm += Math.pow(Math.abs(values[i]), p);
return Math.pow(norm, 1.0 / p);
}
/**
* Calculates word order similarity between the sentences, with weighted words
*
* @param s1 sentence 1
* @param s2 sentence 2
* @param weights1 of sentence 1
* @param weights2 of sentence 2
* @return Word order similarity value
*/
public double orderSimilarity(
List<double[]> s1,
List<double[]> s2,
List<double[]> weights1,
List<double[]> weights2,
String sent2,
String unique) {
double[] s1Dist = s1.get(0);
double[] s1Friend = s1.get(1);
double[] s2Dist = s2.get(0);
double[] s2Friend = s2.get(1);
double[] r1 = new double[s1Dist.length];
double[] r2 = new double[s2Dist.length];
String[] sent = sent2.split(" ");
String[] un = unique.split(" ");
String word;
// Specifies word order vectors for either sentence.
// Threshold specifies that words can be seen as the same if similar enough
// If same word not found in unique sentence, the order value is 0
for (int i = 0; i < r1.length; i++) {
if (s1Dist[i] == 1.0) {
r1[i] = i + 1;
} else if (s1Dist[i] >= threshold) {
r1[i] = s1Friend[i] + 1;
} else {
r1[i] = 0;
}
}
for (int i = 0; i < r2.length; i++) {
if (s2Dist[i] == 1.0) {
word = un[i];
r2[i] = Arrays.asList(sent).indexOf(word) + 1;
} else if (s2Dist[i] >= threshold) {
r2[i] = s2Friend[i] + 1;
} else {
r2[i] = 0.0;
}
}
double numerator = 0.0;
double denominator = 0.0;
// Calculate order similarity while avoiding division by 0
for (int i = 0; i < r1.length; i++) {
numerator = numerator + Math.pow((r1[i] - r2[i]) * weights1.get(0)[i], 2);
denominator = denominator + Math.pow((r1[i] + r2[i]) * weights1.get(0)[i], 2);
}
numerator = Math.sqrt(numerator);
denominator = Math.sqrt(denominator);
if (denominator == 0.0) {
numerator = 1;
denominator = 1;
}
return numerator / denominator;
}
@Override
public double integrate(final double dblBegin, final double dblEnd) throws java.lang.Exception {
if (!org.drip.quant.common.NumberUtil.IsValid(dblBegin)
|| !org.drip.quant.common.NumberUtil.IsValid(dblEnd))
throw new java.lang.Exception("NaturalLogSeriesElement::integrate => Invalid Inputs");
return (java.lang.Math.pow(dblEnd, _iExponent) - java.lang.Math.pow(dblBegin, _iExponent))
/ org.drip.quant.common.NumberUtil.Factorial(_iExponent + 1);
}
private double getDistanceTo(double x, double y, double z, Player player) {
double x2 = player.getX();
double y2 = player.getY();
double z2 = player.getZ();
double xResult = java.lang.Math.pow(java.lang.Math.max(x, x2) - java.lang.Math.min(x, x2), 2);
double yResult = java.lang.Math.pow(java.lang.Math.max(y, y2) - java.lang.Math.min(y, y2), 2);
double zResult = java.lang.Math.pow(java.lang.Math.max(z, z2) - java.lang.Math.min(z, z2), 2);
return java.lang.Math.sqrt(xResult + yResult + zResult);
}
/** Calculate how repusled the scanning robot is by a nearby object. */
public double calcObjRepulseSpeed(double robotX, double robotY, double obsX, double obsY) {
double speed = 0.0;
double distance = Math.sqrt(Math.pow(robotX - obsX, 2) + Math.pow(robotY - obsY, 2));
if (distance <= OBJ_DISTANCE) {
speed = ((OBJ_DISTANCE - distance) / OBJ_DISTANCE) * MAX_SPEED;
}
return speed;
}
@Override
public double[] populationMetricNorm() {
int iPNorm = outputMetricVectorSpace().pNorm();
if (java.lang.Integer.MAX_VALUE == iPNorm) return populationSupremumNorm();
org.drip.spaces.metric.R1Combinatorial r1CombinatorialInput =
(org.drip.spaces.metric.R1Combinatorial) inputMetricVectorSpace();
org.drip.measure.continuous.R1 distR1 = r1CombinatorialInput.borelSigmaMeasure();
java.util.List<java.lang.Double> lsElem = r1CombinatorialInput.elementSpace();
org.drip.function.definition.R1ToRd funcR1ToRd = function();
if (null == distR1 || null == funcR1ToRd) return null;
double dblProbabilityDensity = java.lang.Double.NaN;
double[] adblPopulationMetricNorm = null;
int iOutputDimension = -1;
double dblNormalizer = 0.;
for (double dblElement : lsElem) {
try {
dblProbabilityDensity = distR1.density(dblElement);
} catch (java.lang.Exception e) {
e.printStackTrace();
return null;
}
double[] adblValue = funcR1ToRd.evaluate(dblElement);
if (null == adblValue || 0 == (iOutputDimension = adblValue.length)) return null;
dblNormalizer += dblProbabilityDensity;
if (null == adblPopulationMetricNorm) {
adblPopulationMetricNorm = new double[iOutputDimension];
for (int i = 0; i < iOutputDimension; ++i) adblPopulationMetricNorm[i] = 0;
}
for (int i = 0; i < iOutputDimension; ++i)
adblPopulationMetricNorm[i] +=
dblProbabilityDensity * java.lang.Math.pow(java.lang.Math.abs(adblValue[i]), iPNorm);
}
for (int i = 0; i < iOutputDimension; ++i)
adblPopulationMetricNorm[i] +=
java.lang.Math.pow(adblPopulationMetricNorm[i] / dblNormalizer, 1. / iPNorm);
return adblPopulationMetricNorm;
}
public String outputBinary(int x, int bits) {
int val = x;
String temp = "";
for (int i = bits; i >= 0; i--) {
if ((val - Math.pow(2, i)) >= 0) {
temp = temp + "1";
val = val - (int) Math.pow(2, i);
} else temp = temp + "0";
}
return temp.substring(1);
}
/** Linearly decay the speed of the robot when it nears the goal. */
public double calcRobotSpeedLinear(double robotX, double robotY, double goalX, double goalY) {
double speed = 0;
double distance = Math.sqrt(Math.pow(robotX - goalX, 2) + Math.pow(robotY - goalY, 2));
if (distance >= GOAL_DISTANCE) {
speed = MAX_SPEED;
} else {
speed = (distance / GOAL_DISTANCE) * MAX_SPEED + 0.5;
}
return speed;
}
public void sculptHill(int centerX, int centerY, int height, int radius, boolean additive) {
// int maxHeight = 1;
if (additive) m_contour[centerX][centerY] += height;
else m_contour[centerX][centerY] = height;
for (int x = centerX - radius; x < centerX + radius; x++) {
for (int y = centerY - radius; y < centerY + radius; y++) {
double distance = Math.sqrt(Math.pow(x - centerX, 2) + Math.pow(y - centerY, 2));
if (Math.abs(radius - distance) <= 1) interpolateLine(x, y, centerX, centerY);
}
}
}
@Override
public double variance() {
if (varianceCache != null) return varianceCache;
double mu = mean();
double tmp = 0;
double N = length();
for (double x : values) tmp += Math.pow(x - mu, 2) / N;
// Now add all the zeros into it
tmp += (length() - used) * Math.pow(0 - mu, 2) / N;
return (varianceCache = tmp);
}
public ArrayList<Node> RegionQuery(Node P, ArrayList<Node> points, int eps) {
int x2 = P.getX();
int y2 = P.getY();
ArrayList<Node> neighbors = new ArrayList<>();
for (int i = 0; i < points.size(); i++) {
Node temp = points.get(i);
int x1 = temp.getX();
int y1 = temp.getY();
if ((Math.pow((x1 - x2), 2) + Math.pow((y1 - y2), 2)) < Math.pow(eps, 2)) {
neighbors.add(temp);
}
}
return neighbors;
}
public void dataReceived(int ch1, int ch2) {
// This application processes the computed features on the server side to summarize Physical
// Activity and Estimate
// Energy Expenditure
double EE_minute = 0;
// Process the KCAL features
// KCAL computes a vertical activity count (ch 2) and two horizontal activity counts (ch 1 and
// 3)
accum_minute_V +=
(((double) ch1) / 30.0)
/ 1024.0; // rescale the sensor data by 1024. // note, divide by 30 because of 30
// samples within a sec.
accum_minute_H += (((double) ch2) / 30.0) / 1024.0;
// accum_minute_V = (((double)ch1)/30.0)/1024.0;
// accum_minute_H = (((double)ch2)/30.0)/1024.0;
counter++;
// EEact(k) = a*H^p1 + b*V^p2
//
// assume: mass(kg) = 80 kg
// gender = 1 (male)
//
// a = (12.81 * mass(kg) + 843.22) / 1000 = 1.87
// b = (38.90 * mass(kg) - 682.44 * gender(1=male,2=female) + 692.50)/1000 = 3.12
// p1 = (2.66 * mass(kg) + 146.72)/1000 = 0.36
// p2 = (-3.85 * mass(kg) + 968.28)/1000 = 0.66
if (counter >= 60) {
EE_minute =
1.87 * java.lang.Math.pow(accum_minute_H, 0.36)
+ 3.12 * java.lang.Math.pow(accum_minute_V, 0.66);
// System.out.println("Activity count per minute: " + accum_minute_V);
accum_minute_V = 0;
accum_minute_H = 0;
counter = 0;
// System.out.println("*************************************");
// System.out.println("EE in units kcal/minute: " + EE_minute/4.184); // the 4.184 is to
// convert from KJ to kilocalories
results.addElement(new Double(EE_minute / 4.184));
// System.out.println("*************************************");
}
}
/**
* -=========================================/ generateOutput() -- Fill R.id.numberBox with bases
* and squares and cubes. Note that this method simply assumes that start >= end. This should
* always be the case, as setLimits() does this error checking.
* /==========================================-
*/
private void generateOutput(int start, int end) {
ViewGroup.LayoutParams widthHeightSettings =
new ViewGroup.LayoutParams(
ViewGroup.LayoutParams.WRAP_CONTENT, ViewGroup.LayoutParams.WRAP_CONTENT);
// I will later pass this object to TableRows (as they are created) to define their width and
// height.
TableLayout numberContainer = (TableLayout) findViewById(R.id.numberBox);
numberContainer.removeAllViews();
int row, column;
Context appContext = getApplicationContext();
for (row = 0; row <= (end - start); row++) {
// Create a TableRow row.
TableRow aRow = new TableRow(appContext);
aRow.setId(row);
aRow.setLayoutParams(widthHeightSettings);
numberContainer.addView(aRow);
for (column = 0; column < 3; column++) {
// Create a TextView column, and place it in the just-created TableRow row.
TextView aNumber = new TextView(appContext);
// aNumber.setLayoutParams(widthHeightSettings);
// Fails. I don't know why.
aNumber.setText(Double.toString(Math.pow(start + row, 1 + column)));
((TableRow) numberContainer.findViewById(row)).addView(aNumber);
}
}
}
public double lockKorn() {
double diff = _machCurrent - calculateMachCr.korn();
if (diff > 0) _cdw = 20 * Math.pow((diff), 4);
return _cdw;
}
/**
* Returns the power set from the given set by using a binary counter Example: S = {a,b,c} P(S) =
* {[], [c], [b], [b, c], [a], [a, c], [a, b], [a, b, c]}
*
* @param set String[]
* @return LinkedHashSet
*/
private <T> ArrayList<ArrayList<T>> powerSet(T[] set) {
// create the empty power set
ArrayList<ArrayList<T>> power = new ArrayList<ArrayList<T>>();
// get the number of elements in the set
int elements = set.length;
// the number of members of a power set is 2^n
int powerElements = (int) Math.pow(2, elements);
// run a binary counter for the number of power elements
for (int i = 0; i < powerElements; i++) {
// convert the binary number to a string containing n digits
String binary = intToBinary(i, elements);
// create a new set
ArrayList<T> innerSet = new ArrayList<T>();
// convert each digit in the current binary number to the corresponding element
// in the given set
for (int j = 0; j < binary.length(); j++) {
if (binary.charAt(j) == '1') innerSet.add(set[j]);
}
// add the new set to the power set
power.add(innerSet);
}
return power;
}
@Override
public void evaluate(Solution solution) {
double[] theta = new double[numberOfObjectives - 1];
double[] f = new double[numberOfObjectives];
double[] x = EncodingUtils.getReal(solution);
int k = numberOfVariables - numberOfObjectives + 1;
double g = 0.0;
for (int i = numberOfVariables - k; i < numberOfVariables; i++) {
g += java.lang.Math.pow(x[i], 0.1);
}
double t = java.lang.Math.PI / (4.0 * (1.0 + g));
theta[0] = x[0] * java.lang.Math.PI / 2;
for (int i = 1; i < (numberOfObjectives - 1); i++) {
theta[i] = t * (1.0 + 2.0 * g * x[i]);
}
for (int i = 0; i < numberOfObjectives; i++) {
f[i] = 1.0 + g;
for (int j = 0; j < numberOfObjectives - (i + 1); j++) {
f[i] *= java.lang.Math.cos(theta[j]);
}
if (i != 0) {
int aux = numberOfObjectives - (i + 1);
f[i] *= java.lang.Math.sin(theta[aux]);
}
solution.setObjective(i, f[i]);
}
}
public static List<Double> root(List<Double> data, double root) {
List<Double> t_list = new ArrayList<Double>(data.size());
for (double i : data) {
t_list.add(Math.pow(i, 1.0 / root));
}
return t_list;
}
/**
* Evaluates a solution
*
* @param solution The solution to evaluate
* @throws JMException
*/
public void evaluate(Solution solution) throws JMException {
DecisionVariables gen = solution.getDecisionVariables();
double[] x = new double[numberOfVariables_];
double[] f = new double[numberOfObjectives_];
double[] theta = new double[numberOfObjectives_ - 1];
int k = numberOfVariables_ - numberOfObjectives_ + 1;
for (int i = 0; i < numberOfVariables_; i++) x[i] = gen.variables_[i].getValue();
double g = 0.0;
for (int i = numberOfVariables_ - k; i < numberOfVariables_; i++)
g += java.lang.Math.pow(x[i], 0.1);
double t = java.lang.Math.PI / (4.0 * (1.0 + g));
theta[0] = x[0] * java.lang.Math.PI / 2;
for (int i = 1; i < (numberOfObjectives_ - 1); i++) theta[i] = t * (1.0 + 2.0 * g * x[i]);
for (int i = 0; i < numberOfObjectives_; i++) f[i] = 1.0 + g;
for (int i = 0; i < numberOfObjectives_; i++) {
for (int j = 0; j < numberOfObjectives_ - (i + 1); j++) f[i] *= java.lang.Math.cos(theta[j]);
if (i != 0) {
int aux = numberOfObjectives_ - (i + 1);
f[i] *= java.lang.Math.sin(theta[aux]);
} // if
} // for
for (int i = 0; i < numberOfObjectives_; i++) solution.setObjective(i, f[i]);
} // evaluate
public Complex powi(float p) {
float magnew = (float) Math.pow((double) abs(), (double) p);
float phasenew = arg() * p;
re = magnew * (float) Math.cos(phasenew);
im = magnew * (float) Math.sin(phasenew);
return this;
}
@Override
public double empiricalLoss(
final org.drip.function.definition.RdToR1 funcLearnerRdToR1,
final org.drip.spaces.instance.GeneralizedValidatedVector gvviX,
final org.drip.spaces.instance.GeneralizedValidatedVector gvviY)
throws java.lang.Exception {
if (null == funcLearnerRdToR1
|| null == gvviX
|| !(gvviX instanceof org.drip.spaces.instance.ValidatedRd)
|| null == gvviY
|| !(gvviY instanceof org.drip.spaces.instance.ValidatedR1))
throw new java.lang.Exception("LpLossLearner::empiricalLoss => Invalid Inputs");
double[][] aadblX = ((org.drip.spaces.instance.ValidatedRd) gvviX).instance();
double[] adblY = ((org.drip.spaces.instance.ValidatedR1) gvviY).instance();
double dblEmpiricalLoss = 0.;
int iNumSample = aadblX.length;
if (iNumSample != adblY.length)
throw new java.lang.Exception("LpLossLearner::empiricalLoss => Invalid Inputs");
for (int i = 0; i < iNumSample; ++i)
dblEmpiricalLoss +=
java.lang.Math.pow(
java.lang.Math.abs(funcLearnerRdToR1.evaluate(aadblX[i]) - adblY[i]),
_dblLossExponent);
return dblEmpiricalLoss / _dblLossExponent;
}
/**
* Calculates a standardized normal distributed value (using the polar method).
*
* @return The value
*/
public double standNormalDistrDouble() {
double q = Double.MAX_VALUE;
double u1 = 0;
double u2;
while (q >= 1d || q == 0) {
u1 = randomDouble();
u2 = randomDouble();
q = java.lang.Math.pow(u1, 2) + java.lang.Math.pow(u2, 2);
}
double p = java.lang.Math.sqrt((-2d * (java.lang.Math.log(q))) / q);
return u1 * p; // or u2 * p
}
public void grav() {
double maga = 10 / Math.pow(distPts2D(x, y, xcp, ycp), 2);
xa = (xcp - x) * maga;
ya = (ycp - y) * maga;
find();
}
/**
* The page table constructor. Must call
*
* <p>super(ownerTask)
*
* <p>as its first statement. @OSPProject Memory
*/
public PageTable(TaskCB ownerTask) {
super(ownerTask);
size = (int) Math.pow(2, MMU.getPageAddressBits());
pages = new PageTableEntry[size];
for (int i = 0; i < size; i++) {
pages[i] = new PageTableEntry(this, i);
}
}
public double perkinsAndHage() {
// Difference between current mach number and critical mach number
double diff = _machCurrent - calculateMachCr.perkinsAndHage();
if (diff > 0) _cdw = 9.5 * Math.pow((diff), 2.8) + 0.00193;
return _cdw;
}
@Override
public double calcDerivative(final double dblVariate, final int iOrder)
throws java.lang.Exception {
return iOrder > _iExponent
? 0.
: java.lang.Math.pow(dblVariate, _iExponent - iOrder)
/ org.drip.quant.common.NumberUtil.Factorial(_iExponent - iOrder);
}