public IndTestFisherZPercentIndependent(List<DataSet> dataSets, double alpha) {
this.dataSets = dataSets;
this.variables = dataSets.get(0).getVariables();
data = new ArrayList<TetradMatrix>();
for (DataSet dataSet : dataSets) {
dataSet = DataUtils.center(dataSet);
TetradMatrix _data = dataSet.getDoubleData();
data.add(_data);
}
ncov = new ArrayList<TetradMatrix>();
for (TetradMatrix d : this.data) ncov.add(d.transpose().times(d).scalarMult(1.0 / d.rows()));
setAlpha(alpha);
rows = new int[dataSets.get(0).getNumRows()];
for (int i = 0; i < getRows().length; i++) getRows()[i] = i;
variablesMap = new HashMap<Node, Integer>();
for (int i = 0; i < variables.size(); i++) {
variablesMap.put(variables.get(i), i);
}
this.recursivePartialCorrelation = new ArrayList<RecursivePartialCorrelation>();
for (TetradMatrix covMatrix : ncov) {
recursivePartialCorrelation.add(new RecursivePartialCorrelation(getVariables(), covMatrix));
}
}
public void insertSimple(int val, Node ptr, int i) {
// declare two lists to store keys and ptrs
List<Integer> tempKeys = new ArrayList<Integer>();
List<Node> tempPtrs = new ArrayList<Node>();
// store keys and ptrs into list
for (int j = i; j <= this.getLast(); j++) {
tempKeys.add(this.getKey(j));
tempPtrs.add(this.getPtr(j));
}
// set keys and ptrs at position i
this.keys[i] = val;
this.ptrs[i] = ptr;
// set parent reference
this.ptrs[i].setParent(new Reference(this, i, false));
int end = tempKeys.size();
// add keys and ptrs to current node from previous lists
for (int j = i + 1; j <= i + end; j++) {
this.keys[j] = tempKeys.get(j - i - 1);
this.ptrs[j] = tempPtrs.get(j - i - 1);
// set parent reference
this.ptrs[j].setParent(new Reference(this, j, false));
}
// increase lastindex because of insertion
this.lastindex++;
}
/*
* Method to that creates and returns and array list of the initial population of cells.
* The number of cells in the population is determined by the integer 'population_size'
*/
private static List<Cell> initiatePopulation(List<Cell> population, int population_size) {
int[][][] genome = new int[haploid_number][2][2]; // The genome of unlabelled chromosomes
for (int count_one = 0; count_one < genome.length; count_one++) {
for (int count_two = 0; count_two < genome[count_one].length; count_two++) {
for (int count_three = 0;
count_three < genome[count_one][count_two].length;
count_three++) {
genome[count_one][count_two][count_three] = 0; // Set each DNA strand to unlabelled
// printString("Chromosome " + Integer.toString(count_one+1) + "; Pair " +
// Integer.toString(count_two+1) + "; Strand " + Integer.toString(count_three+1));
}
}
}
// POPULATE GENOME WITH 0's
// Create the starting population of cells, all as generation 1
for (int counter = 0; counter < population_size; counter++) {
population.add(
new Cell(
counter,
newest_generation + 1,
-1,
true,
genome)); // Create a new Cell object with the following values.
id_of_last_created_cell = counter; // Track the id of the lastcreated cell
} // for
return population;
} // initiate_first_population()
public boolean isIndependent(Node x, Node y, List<Node> z) {
int[] all = new int[z.size() + 2];
all[0] = variablesMap.get(x);
all[1] = variablesMap.get(y);
for (int i = 0; i < z.size(); i++) {
all[i + 2] = variablesMap.get(z.get(i));
}
int sampleSize = data.get(0).rows();
List<Double> pValues = new ArrayList<Double>();
for (int m = 0; m < ncov.size(); m++) {
TetradMatrix _ncov = ncov.get(m).getSelection(all, all);
TetradMatrix inv = _ncov.inverse();
double r = -inv.get(0, 1) / sqrt(inv.get(0, 0) * inv.get(1, 1));
double fisherZ =
sqrt(sampleSize - z.size() - 3.0) * 0.5 * (Math.log(1.0 + r) - Math.log(1.0 - r));
double pValue;
if (Double.isInfinite(fisherZ)) {
pValue = 0;
} else {
pValue = 2.0 * (1.0 - RandomUtil.getInstance().normalCdf(0, 1, abs(fisherZ)));
}
pValues.add(pValue);
}
double _cutoff = alpha;
if (fdr) {
_cutoff = StatUtils.fdrCutoff(alpha, pValues, false);
}
Collections.sort(pValues);
int index = (int) round((1.0 - percent) * pValues.size());
this.pValue = pValues.get(index);
// if (this.pValue == 0) {
// System.out.println("Zero pvalue "+ SearchLogUtils.independenceFactMsg(x, y, z,
// getPValue()));
// }
boolean independent = this.pValue > _cutoff;
if (verbose) {
if (independent) {
TetradLogger.getInstance()
.log("independencies", SearchLogUtils.independenceFactMsg(x, y, z, getPValue()));
// System.out.println(SearchLogUtils.independenceFactMsg(x, y, z, getPValue()));
} else {
TetradLogger.getInstance()
.log("dependencies", SearchLogUtils.dependenceFactMsg(x, y, z, getPValue()));
}
}
return independent;
}
/** @return the list of variable varNames. */
public List<String> getVariableNames() {
List<Node> variables = getVariables();
List<String> variableNames = new ArrayList<String>();
for (Node variable1 : variables) {
variableNames.add(variable1.getName());
}
return variableNames;
}
public ICovarianceMatrix getCov() {
List<DataSet> _dataSets = new ArrayList<DataSet>();
for (DataSet d : dataSets) {
_dataSets.add(DataUtils.standardizeData(d));
}
return new CovarianceMatrix(DataUtils.concatenateData(dataSets));
}
public int[] getContainedPositions(BoundingBox boundingBox) {
List<Integer> result = new ArrayList<>();
List<P> positions = getPositions();
for (int i = 0; i < positions.size(); i++) {
P position = positions.get(i);
if (position.hasCoordinates() && boundingBox.contains(position)) result.add(i);
}
return toArray(result);
}
@SuppressWarnings("UnusedDeclaration")
public ViaMichelinRoute asViaMichelinFormat() {
if (getFormat() instanceof ViaMichelinFormat) return (ViaMichelinRoute) this;
List<Wgs84Position> wgs84Positions = new ArrayList<>();
for (P position : getPositions()) {
wgs84Positions.add(position.asWgs84Position());
}
return new ViaMichelinRoute(getName(), wgs84Positions);
}
@SuppressWarnings("UnusedDeclaration")
public OvlRoute asOvlFormat() {
if (getFormat() instanceof OvlFormat) return (OvlRoute) this;
List<Wgs84Position> ovlPositions = new ArrayList<>();
for (P position : getPositions()) {
ovlPositions.add(position.asOvlPosition());
}
return new OvlRoute(getCharacteristics(), getName(), ovlPositions);
}
@SuppressWarnings("UnusedDeclaration")
public MagicMapsPthRoute asMagicMapsPthFormat() {
if (getFormat() instanceof MagicMapsPthFormat) return (MagicMapsPthRoute) this;
List<GkPosition> gkPositions = new ArrayList<>();
for (P position : getPositions()) {
gkPositions.add(position.asGkPosition());
}
return new MagicMapsPthRoute(getCharacteristics(), gkPositions);
}
@SuppressWarnings("UnusedDeclaration")
public MagicMapsIktRoute asMagicMapsIktFormat() {
if (getFormat() instanceof MagicMapsIktFormat) return (MagicMapsIktRoute) this;
List<Wgs84Position> wgs84Positions = new ArrayList<>();
for (P position : getPositions()) {
wgs84Positions.add(position.asWgs84Position());
}
return new MagicMapsIktRoute(getName(), getDescription(), wgs84Positions);
}
@SuppressWarnings("UnusedDeclaration")
public GarminFlightPlanRoute asGarminFlightPlanFormat() {
if (getFormat() instanceof GarminFlightPlanFormat) return (GarminFlightPlanRoute) this;
List<GarminFlightPlanPosition> flightPlanPositions = new ArrayList<>();
for (P position : getPositions()) {
flightPlanPositions.add(position.asGarminFlightPlanPosition());
}
return new GarminFlightPlanRoute(getName(), getDescription(), flightPlanPositions);
}
@SuppressWarnings("UnusedDeclaration")
public TourRoute asTourFormat() {
if (getFormat() instanceof TourFormat) return (TourRoute) this;
List<TourPosition> tourPositions = new ArrayList<>();
for (P position : getPositions()) {
tourPositions.add(position.asTourPosition());
}
return new TourRoute(getName(), tourPositions);
}
@SuppressWarnings("UnusedDeclaration")
public NokiaLandmarkExchangeRoute asNokiaLandmarkExchangeFormat() {
if (getFormat() instanceof NokiaLandmarkExchangeFormat)
return (NokiaLandmarkExchangeRoute) this;
List<Wgs84Position> wgs84Positions = new ArrayList<>();
for (P position : getPositions()) {
wgs84Positions.add(position.asWgs84Position());
}
return new NokiaLandmarkExchangeRoute(getName(), getDescription(), wgs84Positions);
}
public int[] getPositionsWithinDistanceToPredecessor(double distance) {
List<Integer> result = new ArrayList<>();
List<P> positions = getPositions();
if (positions.size() <= 2) return new int[0];
P previous = positions.get(0);
for (int i = 1; i < positions.size() - 1; i++) {
P next = positions.get(i);
if (!next.hasCoordinates() || next.calculateDistance(previous) <= distance) result.add(i);
else previous = next;
}
return toArray(result);
}
private static void runSimulationExecutive(
int sim_duration,
int simulation_time_interval,
List<Cell> cell_population,
int cell_doubling_rate) {
int population_size = cell_population.size();
int next_div_time = cell_doubling_rate;
int[][][] diploid_genome =
new int[haploid_number][2]
[2]; // The genome, chromosome->homologous pair->complementary DNA strands
// Progress through time at selected intervals for a specified duration
for (int current_time = 0;
current_time < sim_duration;
current_time += simulation_time_interval) {
Random rand = new Random();
// Perform division of all cells that can divide as determined by a random number generator
// and the set division threshhold
// As new cells are being added to the list, only go through the cells in the population
// before new cells are added i.e use the previous population size as max number of iterations
for (int counter = 0; counter < population_size; counter++) {
if (cell_population.get(counter).getDivisionStatus()) {
// Random number generator, 0 = divide, 1 = don't divide
double coin_flip = rand.nextDouble();
// printString(Double.toString(coin_flip));
if (coin_flip >= 0.5) {
// Remove one cell from the current generation and add two to the next
// by changing the generation of the dividing cell to current_gen + 1 and
// create a new cell object for the next generation
cell_population.get(counter).setGen(cell_population.get(counter).getGen() + 1);
cell_population.add(
new Cell(
id_of_last_created_cell + 1, newest_generation + 1, -1, true, diploid_genome));
id_of_last_created_cell++;
}
} // if the cell can divide
} // for all items in main population array
population_size =
cell_population.size(); // Update the population size after the round of division
newest_generation++; // Update the value of the most recent generation after the division
// round
next_div_time +=
cell_doubling_rate; // Set the next time of division by adding the doubling rate to the
// current time
printString(current_time + " " + population_size);
} // for
} // runSimulationExecutive
public void revert() {
List<P> positions = getPositions();
List<P> reverted = new ArrayList<>();
for (P position : positions) {
reverted.add(0, position);
}
order(reverted);
String routeName = getName();
if (!routeName.endsWith(REVERSE_ROUTE_NAME_POSTFIX))
routeName = routeName + REVERSE_ROUTE_NAME_POSTFIX;
else
routeName = routeName.substring(0, routeName.length() - REVERSE_ROUTE_NAME_POSTFIX.length());
setName(routeName);
}
public void add(Tp obj, int maxDepth) {
if (!in(0, 0, 0, 2, obj)) throw new RuntimeException("Object is out of octree");
if (maxDepth != 0) {
for (int i = 0; i < 2; ++i)
for (int j = 0; j < 2; ++j)
for (int k = 0; k < 2; ++k)
if (in(i, j, k, 1, obj)) {
if (subtree[i][j][k] == null)
subtree[i][j][k] = new Octree(xc[i], xc[i + 1], yc[j], yc[j + 1], zc[k], zc[k + 1]);
subtree[i][j][k].add(obj, maxDepth - 1);
return;
}
}
// Gstate.counter++;
container.add(obj);
// System.out.println("gstate counter:" + Gstate.counter);
}
private List<Chessboard> getPossibleMutations(Chessboard chessboard) {
List<Chessboard> result = new ArrayList<Chessboard>();
for (int i = 0; i < chessboard.board.length; ++i) {
for (int j = i + 1; j < chessboard.board.length; ++j) {
int rook1Col = chessboard.board[i];
int rook2Col = chessboard.board[j];
if (rook1Col > rook2Col) {
Chessboard newChessboard =
new Chessboard(Arrays.copyOf(chessboard.board, chessboard.board.length));
newChessboard.board[j] = rook1Col;
newChessboard.board[i] = rook2Col;
result.add(newChessboard);
}
}
}
return result;
}
public void solve() throws Exception {
P[] ps = new P[N];
Map<Integer, Set<Integer>> map = new HashMap<Integer, Set<Integer>>();
for (int i = 0; i < N; i++) {
P p = new P();
p.x = sc.nextInt();
p.y = sc.nextInt();
ps[i] = p;
if (!map.containsKey(p.x)) {
Set<Integer> set = new HashSet<Integer>();
map.put(p.x, set);
}
map.get(p.x).add(p.y);
}
Arrays.sort(
ps,
new Comparator<P>() {
@Override
public int compare(P p1, P p2) {
if (p1.x != p2.x) {
return p1.x - p2.x;
}
return p1.y - p2.y;
}
});
List<Pair> yp = new ArrayList<Pair>();
for (int i = 0; i < ps.length - 1; i++) {
if (ps[i].x != ps[i + 1].x) continue;
int lidx = i + 1;
while (lidx + 1 < ps.length && ps[i].x == ps[lidx + 1].x) {
lidx++;
}
Pair pair = new Pair();
pair.s = ps[i].y;
pair.l = ps[lidx].y;
pair.base = ps[i].x;
yp.add(pair);
i = lidx;
}
Arrays.sort(
ps,
new Comparator<P>() {
@Override
public int compare(P p1, P p2) {
if (p1.y != p2.y) {
return p1.y - p2.y;
}
return p1.x - p2.x;
}
});
List<Pair> xp = new ArrayList<Pair>();
for (int i = 0; i < ps.length - 1; i++) {
if (ps[i].y != ps[i + 1].y) continue;
int lidx = i + 1;
while (lidx + 1 < ps.length && ps[i].y == ps[lidx + 1].y) {
lidx++;
}
Pair pair = new Pair();
pair.s = ps[i].x;
pair.l = ps[lidx].x;
pair.base = ps[i].y;
xp.add(pair);
i = lidx;
}
int ans = 0;
for (int i = 0; i < yp.size(); i++) {
int xnow = yp.get(i).base;
int sy = yp.get(i).s;
int ly = yp.get(i).l;
for (int j = 0; j < xp.size(); j++) {
int y = xp.get(j).base;
if (y < sy || ly < y) continue;
if (xp.get(j).s > xnow || xp.get(j).l < xnow) continue;
try {
if (!map.get(xnow).contains(y)) {
ans++;
map.get(xnow).add(y);
}
} catch (Exception ex) {
}
}
}
ans += ps.length;
out.println(ans);
}
private static List<String> importGenomeData(
File genome_text_file, String target_organism, int sex) throws IOException {
List<String> temp_genome_data =
new ArrayList<String>(); // The genome data array that contains the sizes of each chromosome
// int haploid_number; // Used to determine the size of the first dimension in the
// temp_genome_data array
boolean found_target_organism =
false; // Used to determine what action to take when a new header line in the file is found;
// close if true, keep reading if false
boolean end_of_genome = false; // True when the Y chromosome has been dealt with
// Construct BufferedReader from FileReader; search for header line of target organism and
// obtain the haploid number then create a two dimensional array, size of the first dimension
// equals the haploid number, size of second dimension equals two (two chromosomes to form
// deploid organism)
// At this point, the next lines correspond to the size of each chromosome so populate the newly
// created array
// with this information. Stop reading when no more new lines or when a new header line is found
BufferedReader genome_file_reader = new BufferedReader(new FileReader(genome_text_file));
String line = null;
StringBuilder organism_name;
while ((line = genome_file_reader.readLine()) != null) {
String[] split_line = line.split(" ");
if (split_line[0].equals(">")) // If this is a first header line
{
organism_name =
new StringBuilder()
.append(split_line[1])
.append(" ")
.append(
split_line[
2]); // Recreate the genus and species of the organism from the strings that
// were separated during the splitting of the line
if (organism_name
.toString()
.equals(target_organism)) // If this line refers to the organism of interest
{
found_target_organism = true;
haploid_number =
Integer.parseInt(split_line[4]); // Get the haploid number stored in the header line
} else {
found_target_organism = false;
continue; // This is a header line but it is not the organism of interest
}
} else if (found_target_organism
&& !end_of_genome) // This is not a header line and we probably want to import this line
{
// boolean autosome = true;
switch (sex) {
case 1: // Female
{
if (split_line[0].equals("chrX")) {
temp_genome_data.add(split_line[1] + "," + split_line[1]);
} else if (split_line[0].equals("chrY")) {
end_of_genome = true;
} // Ignore the Y chromosome
else
temp_genome_data.add(
split_line[1] + "," + split_line[1]); // The current line is an autosome
}
break;
case 2: // Male
{
if (split_line[0].equals("chrX")) {
temp_genome_data.add(split_line[1] + ",");
} else if (split_line[0].equals("chrY")) {
String temp =
temp_genome_data.get(
temp_genome_data.size() - 1); // Store the value already there
temp_genome_data.remove(temp_genome_data.size() - 1);
temp = temp + split_line[1];
temp_genome_data.add(temp);
end_of_genome = true;
} else
temp_genome_data.add(
split_line[1] + "," + split_line[1]); // The current line is an autosome
}
break;
}
}
} // while ((line = genome_file_reader.readLine()) != null)
genome_file_reader.close();
return temp_genome_data;
} // importGenomeData
