- Added a SampleStatistic class (from the old deprecated libg++) library. - Make time statistics and printing conditionable - Added an interface function to switch time stamp collection and printing on and off from the application (defaults to off).
153 lines
3.3 KiB
C++
153 lines
3.3 KiB
C++
// This may look like C code, but it is really -*- C++ -*-
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/*
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Copyright (C) 1988 Free Software Foundation
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written by Dirk Grunwald (grunwald@cs.uiuc.edu)
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This file is part of the GNU C++ Library. This library is free
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software; you can redistribute it and/or modify it under the terms of
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the GNU Library General Public License as published by the Free
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Software Foundation; either version 2 of the License, or (at your
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option) any later version. This library is distributed in the hope
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that it will be useful, but WITHOUT ANY WARRANTY; without even the
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implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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PURPOSE. See the GNU Library General Public License for more details.
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You should have received a copy of the GNU Library General Public
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License along with this library; if not, write to the Free Software
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Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
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*/
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#ifdef __GNUG__
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#pragma implementation
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#endif
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#include <math.h>
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#ifndef HUGE_VAL
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#ifdef HUGE
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#define HUGE_VAL HUGE
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#else
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#include <float.h>
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#define HUGE_VAL DBL_MAX
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#endif
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#endif
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#include <iostream>
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#include <fstream>
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#include <simgear/debug/logstream.hxx>
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#include "SGSmplstat.hxx"
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void SampleStatistic::error (const char *msg)
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{
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SG_LOG(SG_GENERAL, SG_ALERT, msg);
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}
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// t-distribution: given p-value and degrees of freedom, return t-value
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// adapted from Peizer & Pratt JASA, vol63, p1416
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double tval (double p, int df)
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{
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double t;
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int positive = p >= 0.5;
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p = (positive) ? 1.0 - p : p;
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if (p <= 0.0 || df <= 0)
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t = HUGE_VAL;
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else if (p == 0.5)
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t = 0.0;
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else if (df == 1)
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t = 1.0 / tan ((p + p) * 1.57079633);
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else if (df == 2)
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t = sqrt (1.0 / ((p + p) * (1.0 - p)) - 2.0);
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else
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{
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double ddf = df;
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double a = sqrt (log (1.0 / (p * p)));
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double aa = a * a;
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a = a - ((2.515517 + (0.802853 * a) + (0.010328 * aa)) /
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(1.0 + (1.432788 * a) + (0.189269 * aa) +
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(0.001308 * aa * a)));
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t = ddf - 0.666666667 + 1.0 / (10.0 * ddf);
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t = sqrt (ddf * (exp (a * a * (ddf - 0.833333333) / (t * t)) - 1.0));
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}
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return (positive) ? t : -t;
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}
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void SampleStatistic::reset ()
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{
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n = 0;
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x = x2 = 0.0;
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maxValue = -HUGE_VAL;
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minValue = HUGE_VAL;
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}
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void SampleStatistic::operator += (double value)
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{
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n += 1;
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x += value;
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x2 += (value * value);
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if (minValue > value)
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minValue = value;
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if (maxValue < value)
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maxValue = value;
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}
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double SampleStatistic::mean () const
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{
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if (n > 0)
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{
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return (x / n);
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}
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else
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{
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return (0.0);
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}
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}
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double SampleStatistic::var () const
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{
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if (n > 1)
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{
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return ((x2 - ((x * x) / n)) / (n - 1));
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}
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else
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{
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return (0.0);
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}
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}
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double SampleStatistic::stdDev () const
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{
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if (n <= 0 || this->var () <= 0)
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{
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return (0);
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}
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else
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{
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return ((double) sqrt (var ()));
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}
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}
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double SampleStatistic::confidence (int interval) const
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{
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int df = n - 1;
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if (df <= 0)
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return HUGE_VAL;
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double t = tval (double (100 + interval) * 0.005, df);
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if (t == HUGE_VAL)
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return t;
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else
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return (t * stdDev ()) / sqrt (double (n));
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}
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double SampleStatistic::confidence (double p_value) const
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{
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int df = n - 1;
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if (df <= 0)
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return HUGE_VAL;
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double t = tval ((1.0 + p_value) * 0.5, df);
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if (t == HUGE_VAL)
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return t;
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else
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return (t * stdDev ()) / sqrt (double (n));
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}
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