List of usage examples for java.lang Double hashCode
@Override public int hashCode()
From source file:Main.java
public static void main(String[] args) { Double d = new Double("3.0001"); int retval = d.hashCode(); System.out.println("Value = " + retval); }
From source file:com.itemanalysis.psychometrics.reliability.AbstractScoreReliability.java
public int hashCode() { Double v = new Double(value()); return v.hashCode(); }
From source file:com.itemanalysis.psychometrics.polycor.PearsonCorrelation.java
@Override public int hashCode() { Double v = new Double(this.value()); return v.hashCode(); }
From source file:org.bibsonomy.rest.utils.HeaderUtils.java
/** * // w ww. jav a 2s . c o m * @param acceptHeader * the HTML ACCEPT Header * <br/>example: * <code>ACCEPT: text/xml,text/html;q=0.9,text/plain;q=0.8,image/png</code> * would be interpreted in the following precedence: * <ol> * <li>text/xml</li> * <li>image/png</li> * <li>text/html</li> * <li>text/plain</li> * </ol> * ) * @return a sorted map with the precedences */ public static SortedMap<Double, Vector<String>> getPreferredTypes(final String acceptHeader) { // maps the q-value to output format (reverse order) final SortedMap<Double, Vector<String>> preferredTypes = new TreeMap<Double, Vector<String>>( new Comparator<Double>() { @Override public int compare(Double o1, Double o2) { if (o1.doubleValue() > o2.doubleValue()) return -1; else if (o1.doubleValue() < o2.doubleValue()) return 1; else return o1.hashCode() - o2.hashCode(); } }); if (!present(acceptHeader)) { return preferredTypes; } // fill map with q-values and formats final Scanner scanner = new Scanner(acceptHeader.toLowerCase()); scanner.useDelimiter(","); while (scanner.hasNext()) { final String[] types = scanner.next().split(";"); final String type = types[0]; double qValue = 1; if (types.length != 1) { /* * FIXME: we get * java.lang.NumberFormatException: For input string: "screen" * in the error log because the format we assume seems to be * different by some clients. Until we find out, what is really * wrong (our parsing or the client), we are more careful with * parsing external data. */ try { qValue = Double.parseDouble(types[1].split("=")[1]); } catch (NumberFormatException e) { qValue = 0; log.error("Couldn't parse accept header '" + acceptHeader + "'"); } } Vector<String> v = preferredTypes.get(qValue); if (!preferredTypes.containsKey(qValue)) { v = new Vector<String>(); preferredTypes.put(qValue, v); } v.add(type); } return preferredTypes; }
From source file:ubic.gemma.analysis.preprocess.svd.ExpressionDataSVD.java
/** * Implements method described in Skillicorn et al., "Strategies for winnowing microarray data" (also section 3.5.5 * of his book)//from w ww. j a v a 2 s .co m * * @param thresholdQuantile Enter 0.5 for median. Value must be > 0 and < 1. * @return a filtered matrix */ public ExpressionDataDoubleMatrix winnow(double thresholdQuantile) { if (thresholdQuantile <= 0 || thresholdQuantile >= 1) { throw new IllegalArgumentException("Threshold quantile should be a value between 0 and 1 exclusive"); } class NormCmp implements Comparable<NormCmp> { Double norm; int rowIndex; public NormCmp(int rowIndex, Double norm) { super(); this.rowIndex = rowIndex; this.norm = norm; } @Override public int compareTo(NormCmp o) { return this.norm.compareTo(o.norm); } /* * (non-Javadoc) * * @see java.lang.Object#equals(java.lang.Object) */ @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (getClass() != obj.getClass()) return false; NormCmp other = (NormCmp) obj; if (norm == null) { if (other.norm != null) return false; } else if (!norm.equals(other.norm)) return false; return true; } public int getRowIndex() { return rowIndex; } /* * (non-Javadoc) * * @see java.lang.Object#hashCode() */ @Override public int hashCode() { final int prime = 31; int result = 1; result = prime * result + ((norm == null) ? 0 : norm.hashCode()); return result; } } // order rows by distance from the origin. This is proportional to the 1-norm. Algebra a = new Algebra(); List<NormCmp> os = new ArrayList<NormCmp>(); for (int i = 0; i < this.expressionData.rows(); i++) { double[] row = this.getU().getRow(i); DoubleMatrix1D rom = new DenseDoubleMatrix1D(row); norm1 = a.norm1(rom); os.add(new NormCmp(i, norm1)); } Collections.sort(os); int quantileLimit = (int) Math.floor(this.expressionData.rows() * thresholdQuantile); quantileLimit = Math.max(0, quantileLimit); List<CompositeSequence> keepers = new ArrayList<CompositeSequence>(); for (int i = 0; i < quantileLimit; i++) { NormCmp x = os.get(i); CompositeSequence d = this.expressionData.getDesignElementForRow(x.getRowIndex()); keepers.add(d); } // / remove genes which are near the origin in SVD space. FIXME: make sure the missing values are still masked. return new ExpressionDataDoubleMatrix(this.expressionData, keepers); }
From source file:ubic.gemma.core.analysis.preprocess.svd.ExpressionDataSVD.java
/** * Implements method described in Skillicorn et al., "Strategies for winnowing microarray data" (also section 3.5.5 * of his book)/*from w ww.j av a2s .c o m*/ * * @param thresholdQuantile Enter 0.5 for median. Value must be > 0 and < 1. * @return a filtered matrix */ public ExpressionDataDoubleMatrix winnow(double thresholdQuantile) { if (thresholdQuantile <= 0 || thresholdQuantile >= 1) { throw new IllegalArgumentException("Threshold quantile should be a value between 0 and 1 exclusive"); } class NormCmp implements Comparable<NormCmp> { private Double norm; private int rowIndex; private NormCmp(int rowIndex, Double norm) { super(); this.rowIndex = rowIndex; this.norm = norm; } @Override public int compareTo(NormCmp o) { return this.norm.compareTo(o.norm); } public int getRowIndex() { return rowIndex; } @Override public int hashCode() { final int prime = 31; int result = 1; result = prime * result + ((norm == null) ? 0 : norm.hashCode()); return result; } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (this.getClass() != obj.getClass()) return false; NormCmp other = (NormCmp) obj; if (norm == null) { return other.norm == null; } return norm.equals(other.norm); } } // order rows by distance from the origin. This is proportional to the 1-norm. Algebra a = new Algebra(); List<NormCmp> os = new ArrayList<>(); for (int i = 0; i < this.expressionData.rows(); i++) { double[] row = this.getU().getRow(i); DoubleMatrix1D rom = new DenseDoubleMatrix1D(row); double norm1 = a.norm1(rom); os.add(new NormCmp(i, norm1)); } Collections.sort(os); int quantileLimit = (int) Math.floor(this.expressionData.rows() * thresholdQuantile); quantileLimit = Math.max(0, quantileLimit); List<CompositeSequence> keepers = new ArrayList<>(); for (int i = 0; i < quantileLimit; i++) { NormCmp x = os.get(i); CompositeSequence d = this.expressionData.getDesignElementForRow(x.getRowIndex()); keepers.add(d); } // remove genes which are near the origin in SVD space. FIXME: make sure the missing values are still masked. return new ExpressionDataDoubleMatrix(this.expressionData, keepers); }