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package org.apache.poi.ss.formula.functions;

import org.apache.poi.ss.formula.TwoDEval;
import org.apache.poi.ss.formula.eval.ErrorEval;
import org.apache.poi.ss.formula.eval.EvaluationException;
import org.apache.poi.ss.formula.eval.NumberEval;
import org.apache.poi.ss.formula.eval.RefEval;
import org.apache.poi.ss.formula.eval.ValueEval;
import org.apache.poi.ss.formula.functions.LookupUtils.ValueVector;

/**
 * Base class for linear regression functions.
 *
 * Calculates the linear regression line that is used to predict y values from x values
* (http://introcs.cs.princeton.edu/java/97data/LinearRegression.java.html) * Syntax:
* INTERCEPT(arrayX, arrayY)

* or * SLOPE(arrayX, arrayY)

* * * @author Johan Karlsteen */ public final class LinearRegressionFunction extends Fixed2ArgFunction { private static abstract class ValueArray implements ValueVector { private final int _size; protected ValueArray(int size) { _size = size; } public ValueEval getItem(int index) { if (index < 0 || index > _size) { throw new IllegalArgumentException("Specified index " + index + " is outside range (0.." + (_size - 1) + ")"); } return getItemInternal(index); } protected abstract ValueEval getItemInternal(int index); public final int getSize() { return _size; } } private static final class SingleCellValueArray extends ValueArray { private final ValueEval _value; public SingleCellValueArray(ValueEval value) { super(1); _value = value; } protected ValueEval getItemInternal(int index) { return _value; } } private static final class RefValueArray extends ValueArray { private final RefEval _ref; private final int _width; public RefValueArray(RefEval ref) { super(ref.getNumberOfSheets()); _ref = ref; _width = ref.getNumberOfSheets(); } protected ValueEval getItemInternal(int index) { int sIx = (index % _width) + _ref.getFirstSheetIndex(); return _ref.getInnerValueEval(sIx); } } private static final class AreaValueArray extends ValueArray { private final TwoDEval _ae; private final int _width; public AreaValueArray(TwoDEval ae) { super(ae.getWidth() * ae.getHeight()); _ae = ae; _width = ae.getWidth(); } protected ValueEval getItemInternal(int index) { int rowIx = index / _width; int colIx = index % _width; return _ae.getValue(rowIx, colIx); } } public enum FUNCTION {INTERCEPT, SLOPE} public FUNCTION function; public LinearRegressionFunction(FUNCTION function) { this.function = function; } public ValueEval evaluate(int srcRowIndex, int srcColumnIndex, ValueEval arg0, ValueEval arg1) { double result; try { ValueVector vvY = createValueVector(arg0); ValueVector vvX = createValueVector(arg1); int size = vvX.getSize(); if (size == 0 || vvY.getSize() != size) { return ErrorEval.NA; } result = evaluateInternal(vvX, vvY, size); } catch (EvaluationException e) { return e.getErrorEval(); } if (Double.isNaN(result) || Double.isInfinite(result)) { return ErrorEval.NUM_ERROR; } return new NumberEval(result); } private double evaluateInternal(ValueVector x, ValueVector y, int size) throws EvaluationException { // error handling is as if the x is fully evaluated before y ErrorEval firstXerr = null; ErrorEval firstYerr = null; boolean accumlatedSome = false; // first pass: read in data, compute xbar and ybar double sumx = 0.0, sumy = 0.0; for (int i = 0; i < size; i++) { ValueEval vx = x.getItem(i); ValueEval vy = y.getItem(i); if (vx instanceof ErrorEval) { if (firstXerr == null) { firstXerr = (ErrorEval) vx; continue; } } if (vy instanceof ErrorEval) { if (firstYerr == null) { firstYerr = (ErrorEval) vy; continue; } } // only count pairs if both elements are numbers if (vx instanceof NumberEval && vy instanceof NumberEval) { accumlatedSome = true; NumberEval nx = (NumberEval) vx; NumberEval ny = (NumberEval) vy; sumx += nx.getNumberValue(); sumy += ny.getNumberValue(); } else { // all other combinations of value types are silently ignored } } double xbar = sumx / size; double ybar = sumy / size; // second pass: compute summary statistics double xxbar = 0.0, xybar = 0.0; for (int i = 0; i < size; i++) { ValueEval vx = x.getItem(i); ValueEval vy = y.getItem(i); if (vx instanceof ErrorEval) { if (firstXerr == null) { firstXerr = (ErrorEval) vx; continue; } } if (vy instanceof ErrorEval) { if (firstYerr == null) { firstYerr = (ErrorEval) vy; continue; } } // only count pairs if both elements are numbers if (vx instanceof NumberEval && vy instanceof NumberEval) { NumberEval nx = (NumberEval) vx; NumberEval ny = (NumberEval) vy; xxbar += (nx.getNumberValue() - xbar) * (nx.getNumberValue() - xbar); xybar += (nx.getNumberValue() - xbar) * (ny.getNumberValue() - ybar); } else { // all other combinations of value types are silently ignored } } double beta1 = xybar / xxbar; double beta0 = ybar - beta1 * xbar; if (firstXerr != null) { throw new EvaluationException(firstXerr); } if (firstYerr != null) { throw new EvaluationException(firstYerr); } if (!accumlatedSome) { throw new EvaluationException(ErrorEval.DIV_ZERO); } if(function == FUNCTION.INTERCEPT) { return beta0; } else { return beta1; } } private static ValueVector createValueVector(ValueEval arg) throws EvaluationException { if (arg instanceof ErrorEval) { throw new EvaluationException((ErrorEval) arg); } if (arg instanceof TwoDEval) { return new AreaValueArray((TwoDEval) arg); } if (arg instanceof RefEval) { return new RefValueArray((RefEval) arg); } return new SingleCellValueArray(arg); } }





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