a .NET library that can read/write Office formats without Microsoft Office installed. No COM+, no interop.
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/* * ==================================================================== * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for Additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0
* * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ==================================================================== */
namespace NPOI.SS.Formula.Functions{ using NPOI.SS.Formula; using NPOI.SS.Formula.Eval; using System;
/** * Base class for linear regression functions. * * Calculates the linear regression line that is used to predict y values from x values<br/> * (http://introcs.cs.princeton.edu/java/97data/LinearRegression.java.html)
* <b>Syntax</b>:<br/> * <b>INTERCEPT</b>(<b>arrayX</b>, <b>arrayY</b>)<p/> * or * <b>SLOPE</b>(<b>arrayX</b>, <b>arrayY</b>)<p/> * * * @author Johan Karlsteen */ public class LinearRegressionFunction : Fixed2ArgFunction {
private abstract class ValueArray : ValueVector { private readonly int _size; protected ValueArray(int size) { _size = size; }
public ValueEval GetItem(int index) { if (index < 0 || index > _size) { throw new ArgumentException("Specified index " + index + " is outside range (0.." + (_size - 1) + ")"); } return GetItemInternal(index); } protected abstract ValueEval GetItemInternal(int index);
public int Size { get { return _size; } } }
private sealed class SingleCellValueArray : ValueArray { private readonly ValueEval _value; public SingleCellValueArray(ValueEval value) : base(1) { _value = value; }
protected override ValueEval GetItemInternal(int index) { return _value; } }
private sealed class RefValueArray : ValueArray { private readonly RefEval _ref; private readonly int _width; public RefValueArray(RefEval ref1) : base(ref1.NumberOfSheets) { _ref = ref1; _width = ref1.NumberOfSheets; }
protected override ValueEval GetItemInternal(int index) { int sIx = (index % _width) + _ref.FirstSheetIndex; return _ref.GetInnerValueEval(sIx); } }
private sealed class AreaValueArray : ValueArray { private readonly TwoDEval _ae; private readonly int _width;
public AreaValueArray(TwoDEval ae) : base(ae.Width * ae.Height) { _ae = ae; _width = ae.Width; }
protected override 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 override ValueEval Evaluate(int srcRowIndex, int srcColumnIndex, ValueEval arg0, ValueEval arg1) { double result; try { ValueVector vvY = CreateValueVector(arg0); ValueVector vvX = CreateValueVector(arg1); int size = vvX.Size; if (size == 0 || vvY.Size != size) { return ErrorEval.NA; } result = EvaluateInternal(vvX, vvY, size); } catch (EvaluationException e) { return e.GetErrorEval(); } if (Double.IsNaN(result) || Double.IsInfinity(result)) { return ErrorEval.NUM_ERROR; } return new NumberEval(result); }
private double EvaluateInternal(ValueVector x, ValueVector y, int size) {
// error handling is as if the x is fully Evaluated before y
ErrorEval firstXerr = null; ErrorEval firstYerr = null; bool 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 is ErrorEval eval) { if (firstXerr == null) { firstXerr = eval; continue; } } if (vy is ErrorEval errorEval) { if (firstYerr == null) { firstYerr = errorEval; continue; } } // only count pairs if both elements are numbers
if (vx is NumberEval nx && vy is NumberEval ny) { accumlatedSome = true; sumx += nx.NumberValue; sumy += ny.NumberValue; } 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 is ErrorEval eval) { if (firstXerr == null) { firstXerr = eval; continue; } } if (vy is ErrorEval errorEval) { if (firstYerr == null) { firstYerr = errorEval; continue; } }
// only count pairs if both elements are numbers
if (vx is NumberEval nx && vy is NumberEval ny) { xxbar += (nx.NumberValue - xbar) * (nx.NumberValue - xbar); xybar += (nx.NumberValue - xbar) * (ny.NumberValue - 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) { if (arg is ErrorEval eval) { throw new EvaluationException(eval); } if (arg is TwoDEval dEval) { return new AreaValueArray(dEval); } if (arg is RefEval refEval) { return new RefValueArray(refEval); } return new SingleCellValueArray(arg); } }}
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