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From "Gilles (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (MATH-866) New method to compute relative deviation between two floating numbers
Date Fri, 21 Sep 2012 11:07:07 GMT

     [ https://issues.apache.org/jira/browse/MATH-866?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gilles updated MATH-866:
------------------------

    Description: 
A new method to compute a relative deviation would be very useful.

In order to handle properly odd values (O+,0-,NaN,Infinity), we suggest to call first the
classical equals() method (strict equality, using one ulp as a threshold) and then the relative
tolerance.

Here is the code we use : 
{noformat}
  public static boolean equalsWithRelativeTolerance(final double x, final double y, final
double eps) {

        // Initialisation
        boolean isEqual = false;

        // very close (including both equals 0.0) case
        if (equals(x, y)) {
            isEqual = true;
        }
        // common case
        else {
            // Relative difference computation
            final double absoluteMax = FastMath.max(FastMath.abs(x), FastMath.abs(y));
            final double relativeDifference = FastMath.abs((x - y) / absoluteMax);

            //test
            if (relativeDifference < eps) {
                isEqual = true;
            }
        }
        return isEqual;
    }
{noformat}

  was:
A new method to compute a relative deviation would be very useful.

In order to handle properly odd values (O+,0-,NaN,Infinity), we suggest to call first the
classical equals() method (strict equality, using one ulp as a threshold) and then the relative
tolerance.

Here is the code we use : 

  public static boolean equalsWithRelativeTolerance(final double x, final double y, final
double eps) {

        // Initialisation
        boolean isEqual = false;

        // very close (including both equals 0.0) case
        if (equals(x, y)) {
            isEqual = true;
        }
        // common case
        else {
            // Relative difference computation
            final double absoluteMax = FastMath.max(FastMath.abs(x), FastMath.abs(y));
            final double relativeDifference = FastMath.abs((x - y) / absoluteMax);

            //test
            if (relativeDifference < eps) {
                isEqual = true;
            }
        }
        return isEqual;
    }


    
> New method to compute relative deviation between two floating numbers
> ---------------------------------------------------------------------
>
>                 Key: MATH-866
>                 URL: https://issues.apache.org/jira/browse/MATH-866
>             Project: Commons Math
>          Issue Type: Improvement
>    Affects Versions: 3.1
>            Reporter: Yannick TANGUY
>             Fix For: 3.1
>
>
> A new method to compute a relative deviation would be very useful.
> In order to handle properly odd values (O+,0-,NaN,Infinity), we suggest to call first
the classical equals() method (strict equality, using one ulp as a threshold) and then the
relative tolerance.
> Here is the code we use : 
> {noformat}
>   public static boolean equalsWithRelativeTolerance(final double x, final double y, final
double eps) {
>         // Initialisation
>         boolean isEqual = false;
>         // very close (including both equals 0.0) case
>         if (equals(x, y)) {
>             isEqual = true;
>         }
>         // common case
>         else {
>             // Relative difference computation
>             final double absoluteMax = FastMath.max(FastMath.abs(x), FastMath.abs(y));
>             final double relativeDifference = FastMath.abs((x - y) / absoluteMax);
>             //test
>             if (relativeDifference < eps) {
>                 isEqual = true;
>             }
>         }
>         return isEqual;
>     }
> {noformat}

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