List of usage examples for org.apache.commons.math.util FastMath ceil
public static double ceil(double x)
From source file:com.polytech4A.cuttingstock.core.method.Result.java
public Result(double[] printings, int sheetCost, int patternCost) { int[] buf = new int[printings.length]; this.cost = 0; for (int i = 0; i < printings.length; ++i) { buf[i] = (int) FastMath.ceil(printings[i]); this.cost += buf[i] * sheetCost; }//from w w w .ja v a 2s .c om this.cost += patternCost * printings.length; this.printings = buf; }
From source file:afest.datastructures.tree.decision.erts.grower.AERTGrower.java
/** * Return an extra tree created from the set of points. * @param <T> Type of ITrainingPoints used by the Extra Trees. * @param set set of points to create the tree from. * @return an extra tree created from the set of points. *///w w w . j a v a 2s .c o m public <T extends ITrainingPoint<R, O>> DecisionTree<R, C> growERT(Collection<T> set) { // get the attributes present in the points. T aElement = set.iterator().next(); ArrayList<R> attributeList = new ArrayList<R>(); for (R attribute : aElement.getAttributes()) { attributeList.add(attribute); } // set k to sqrt(number of attributes) if unset if (fK == null) { fK = (int) FastMath.ceil(FastMath.sqrt(attributeList.size())); } // Train the tree ArrayList<R> constantAttributes = new ArrayList<R>(); DTNode<R, C> root = buildAnExtraTree(set, constantAttributes, attributeList); DecisionTree<R, C> tree = new DecisionTree<R, C>(root); return tree; }
From source file:com.polytech4A.cuttingstock.core.method.LinearResolutionMetodTest.java
@Test public void testMinimize() { LinearResolutionMethod method = new LinearResolutionMethod(context); Result result = method.minimize(solution); int[] printings = { 123, 443, 200 }; for (int i = 0; i < printings.length; ++i) { assertEquals(printings[i], result.getPrintings()[i]); }/*from w w w . j a va 2s . c o m*/ assertEquals(826, (int) FastMath.ceil(result.getCost())); }