gum::ChiSquare Class Reference

<agrum/FMDP/learning/core/testPolicy/chiSquare.h> More...

#include <chiSquare.h>

Collaboration diagram for gum::ChiSquare:

Static Public Member Functions
static double	probaChi2 (double x, Size df)
	computes the probability of chi2 value (used by the cache) More...

Detailed Description

<agrum/FMDP/learning/core/testPolicy/chiSquare.h>

Definition at line 48 of file chiSquare.h.

Member Function Documentation

exp__()

static double gum::ChiSquare::exp__ ( double  x )

inlinestaticprivate

Required constant to compute the cdf.

Definition at line 80 of file chiSquare.h.

{ return (((x) < -BIGX__) ? 0.0 : exp(x)); }

probaChi2()

double gum::ChiSquare::probaChi2 ( double  x, Size  df  )

static

computes the probability of chi2 value (used by the cache)

Definition at line 117 of file chiSquare.cpp.

References gum::Set< Key, Alloc >::emplace().

                                               {
    double retVal = 0.0;
    //      ++nbChit;

    //      std::pair<double, unsigned long> conty(x, df);
    //      if( !chi2Cache__.exists(conty) ){

    double a, y = 0, s;
    double e, c, z;
    int    even; /* true if df is an even number */

    if ((x <= 0.0) || (df < 1)) {
      //          chi2Cache__.insert(conty,1.0);
      retVal = 1.0;
    } else {
      a = 0.5 * x;

      even = (2 * (df / 2)) == df;

      if (df > 1) y = exp__(-a);

      s = (even ? y : (2.0 * probaZValue__(-sqrt(x))));

      if (df > 2) {
        x = 0.5 * (df - 1.0);
        z = (even ? 1.0 : 0.5);

        if (a > BIGX__) {
          e = (even ? 0.0 : LOG_SQRT_PI__);
          c = log(a);

          while (z <= x) {
            e = log(z) + e;
            s += exp__(c * z - a - e);
            z += 1.0;
          }

          //              chi2Cache__.insert(conty,s);
          retVal = s;

        } else {
          e = (even ? 1.0 : (I_SQRT_PI__ / sqrt(a)));
          c = 0.0;

          while (z <= x) {
            e = e * (a / z);
            c = c + e;
            z += 1.0;
          }

          //              chi2Cache__.insert(conty,( c * y + s ));
          retVal = (c * y + s);
        }
      } else {
        //            chi2Cache__.insert(conty,s);
        retVal = s;
      }
    }
    //      } else {
    //          ++nbChi;
    //        }
    //      std::cout << "Z avoid : " << nbZ << " / " << nbZt << ". Chi avoid :
    //      " << nbChi << " / " << nbChit << "." << std::endl;
    //      return chi2Cache__[conty];
    return retVal;
  }

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probaZValue__()

double gum::ChiSquare::probaZValue__ ( double  z )

staticprivate

computes the probability of normal z value (used by the cache)

Definition at line 42 of file chiSquare.cpp.

References gum::Set< Key, Alloc >::emplace().

                                          {
    //      ++nbZt;

    //      z = std::round(z * std::pow(10, 3)) / std::pow(10, 3);
    //      if( !ZCache__.exists(z) ){

    double y, x, w;

    if (z == 0.0)
      x = 0.0;
    else {
      y = 0.5 * fabs(z);

      if (y >= (Z_MAX__ * 0.5))
        x = 1.0;
      else if (y < 1.0) {
        w = y * y;
        x = ((((((((0.000124818987 * w - 0.001075204047) * w + 0.005198775019) * w
                  - 0.019198292004)
                    * w
                 + 0.059054035642)
                   * w
                - 0.151968751364)
                  * w
               + 0.319152932694)
                 * w
              - 0.531923007300)
                * w
             + 0.797884560593)
          * y * 2.0;
      } else {
        y -= 2.0;
        x = (((((((((((((-0.000045255659 * y + 0.000152529290) * y
                        - 0.000019538132)
                          * y
                       - 0.000676904986)
                         * y
                      + 0.001390604284)
                        * y
                     - 0.000794620820)
                       * y
                    - 0.002034254874)
                      * y
                   + 0.006549791214)
                     * y
                  - 0.010557625006)
                    * y
                 + 0.011630447319)
                   * y
                - 0.009279453341)
                  * y
               + 0.005353579108)
                 * y
              - 0.002141268741)
                * y
             + 0.000535310849)
             * y
          + 0.999936657524;
      }
    }

    //        ZCache__.insert(z, ( z > 0.0 ? (( x + 1.0 ) * 0.5 ) : (( 1.0 - x )
    //        * 0.5 ) ) );
    //      } else {
    //          ++nbZ;
    //        }

    //      return ZCache__[z];
    return (z > 0.0 ? ((x + 1.0) * 0.5) : ((1.0 - x) * 0.5));
  }

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Member Data Documentation

BIGX__

constexpr double gum::ChiSquare::BIGX__ = 20.0

staticprivate

max value to represent exp (x)

Definition at line 72 of file chiSquare.h.

CHI_EPSILON__

constexpr double gum::ChiSquare::CHI_EPSILON__ = 0.000001

staticprivate

accuracy of critchi approximation

Definition at line 60 of file chiSquare.h.

CHI_MAX__

constexpr double gum::ChiSquare::CHI_MAX__ = 99999.0

staticprivate

maximum chi square value

Definition at line 63 of file chiSquare.h.

I_SQRT_PI__

constexpr double gum::ChiSquare::I_SQRT_PI__ = 0.5641895835477562869480795

staticprivate

1 / sqrt (pi)

Definition at line 69 of file chiSquare.h.

LOG_SQRT_PI__

constexpr double gum::ChiSquare::LOG_SQRT_PI__ = 0.5723649429247000870717135

staticprivate

log (sqrt (pi))

Definition at line 66 of file chiSquare.h.

Z_MAX__

constexpr double gum::ChiSquare::Z_MAX__ = 6.0

staticprivate

Required constant to compute the cdf.

maximum meaningful z value

Definition at line 57 of file chiSquare.h.

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The documentation for this class was generated from the following files:

• agrum/FMDP/learning/core/chiSquare.h
• agrum/FMDP/learning/core/chiSquare.cpp