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From Ajo Fod <ajo....@gmail.com>
Subject Re: [MATH] What is the derivative of 0^x
Date Sun, 25 Aug 2013 23:19:16 GMT
```Are you saying patched the code? Can you provide the link?

-Ajo

On Sun, Aug 25, 2013 at 1:20 PM, Luc Maisonobe <luc@spaceroots.org> wrote:

> Le 24/08/2013 11:24, Luc Maisonobe a écrit :
> > Le 23/08/2013 19:20, Ajo Fod a écrit :
> >> Hello,
> >
> > Hi Ajo,
> >
> >>
> >> This shows one way of interpreting the derivative for strictly +ve
> numbers.
> >>
> >>     public static void main(final String[] args) {
> >>         final double x = 1d;
> >>         DerivativeStructure dsA = new DerivativeStructure(1, 1, 0, x);
> >>         System.out.println("Derivative of |a|^x wrt x");
> >>         for (int p = 10; p < 21; p++) {
> >>             double a;
> >>             if (p < 20) {
> >>                 a = 1d / Math.pow(2d, p);
> >>             } else {
> >>                 a = 0d;
> >>             }
> >>             final DerivativeStructure a_ds = new DerivativeStructure(1,
> 1,
> >> a);
> >>             final DerivativeStructure out = a_ds.pow(dsA);
> >>             final double calc = (Math.pow(a, x + EPS) - Math.pow(a, x))
> /
> >> EPS;
> >>             System.out.format("Derivative@%f=%f  %f\n", a, calc,
> >> out.getPartialDerivative(new int[]{1}));
> >>         }
> >>     }
> >>
> >> At this point I"m explicitly substituting the rule that
> derivative(|a|^x) =
> >> 0 for |a|=0.
> >
> > Yes, but this fails for x = 0, as the limit of the finite difference is
> > -infinity and not 0.
> >
> > You can build your own function which explicitly assumes a is constant
> > and takes care of special values as follows:
> >
> >  public static DerivativeStructure aToX(final double a,
> >                                         final DerivativeStructure x) {
> >      final double lnA = (a == 0 && x.getValue() == 0) ?
> >                   Double.NEGATIVE_INFINITY :
> >                   FastMath.log(a);
> >      final double[] function = new double[1 + x.getOrder()];
> >      function[0] = FastMath.pow(a, x.getValue());
> >      for (int i = 1; i < function.length; ++i) {
> >          function[i] = lnA * function[i - 1];
> >      }
> >      return x.compose(function);
> >  }
> >
> > This will work and provides derivatives to any order for almost any
> > values of a and x, including a=0, x=1 as in your exemple, but also
> > slightly better for a=0, x=0. However, it still has an important
> > drawback: it won't compute the n-th order derivative correctly for a=0,
> > x=0 and n > 1. It will provide NaN for these higher order derivatives
> > instead of +/-infinity according to parity of n.
>
> I have added a similar function to the DerivativeStructure class (with
> some errors above corrected). The main interesting property of this
> function is that it is more accurate that converting a to a
> DerivativeStructure and using the general x^y function. It does its best
> to handle the special case, but as written above, this does NOT work for
> general combination (i.e. more than one variable or more than one
> order). As soon as there is a combination, the derivative will involve
> something like df/dx * dg/dy and as infinities and zeros are everywheren
> NaN appears immediately for these partial derivatives. This cannot be
> avoided.
>
> If you stay away from the singularity, the function behaves correctly.
>
> best regards,
> Luc
>
> >
> > This is a known problem that we already encountered when dealing with
> > rootN. Here is an extract of a comment in the test case
> > testRootNSingularity, where similar NaN appears instead of +/- infinity.
> > The dsZero instance in the comment is simple the x parameter of the
> > function, as a derivativeStructure with value 0.0 and depending on
> > itself (dsZero = new DerivativeStructure(1, maxOrder, 0, 0.0)):
> >
> >
> > // the following checks shows a LIMITATION of the current implementation
> > // we have no way to tell dsZero is a pure linear variable x = 0
> > // we only say: "dsZero is a structure with value = 0.0,
> > // first derivative = 1.0, second and higher derivatives = 0.0".
> > // Function composition rule for second derivatives is:
> > // d2[f(g(x))]/dx2 = f''(g(x)) * [g'(x)]^2 + f'(g(x)) * g''(x)
> > // when function f is the nth root and x = 0 we have:
> > // f(0) = 0, f'(0) = +infinity, f''(0) = -infinity (and higher
> > // derivatives keep switching between +infinity and -infinity)
> > // so given that in our case dsZero represents g, we have g(x) = 0,
> > // g'(x) = 1 and g''(x) = 0
> > // applying the composition rules gives:
> > // d2[f(g(x))]/dx2 = f''(g(x)) * [g'(x)]^2 + f'(g(x)) * g''(x)
> > //                 = -infinity * 1^2 + +infinity * 0
> > //                 = -infinity + NaN
> > //                 = NaN
> > // if we knew dsZero is really the x variable and not the identity
> > // function applied to x, we would not have computed f'(g(x)) * g''(x)
> > // and we would have found that the result was -infinity and not NaN
> >
> > Hope this helps
> > Luc
> >
> >>
> >> Thanks,
> >> Ajo.
> >>
> >>
> >>
> >> On Fri, Aug 23, 2013 at 9:39 AM, Luc Maisonobe <Luc.Maisonobe@free.fr
> >wrote:
> >>
> >>> Hi Ajo,
> >>>
> >>> Le 23/08/2013 17:48, Ajo Fod a écrit :
> >>>> Try this and I'm happy to explain if necessary:
> >>>>
> >>>> public class Derivative {
> >>>>
> >>>>     public static void main(final String[] args) {
> >>>>         DerivativeStructure dsA = new DerivativeStructure(1, 1, 0,
> 1d);
> >>>>         System.out.println("Derivative of constant^x wrt x");
> >>>>         for (int a = -3; a < 3; a++) {
> >>>
> >>> We have chosen the classical definition which implies c^x is not
> defined
> >>> for real r and negative c.
> >>>
> >>> Our implementation is based on the decomposition c^r = exp(r * ln(c)),
> >>> so the NaN comes from the logarithm when c <= 0.
> >>>
> >>> Noe also that as explained in the documentation here:
> >>> <
> >>>
> http://commons.apache.org/proper/commons-math/userguide/analysis.html#a4.7_Differentiation
> >>>> ,
> >>> there are no concepts of "constants" and "variables" in this framework,
> >>> so we cannot draw a line between c^r as seen as a univariate function
> of
> >>> r, or as a univariate function of c, or as a bivariate function of c
> and
> >>> r, or even as a pentavariate function of p1, p2, p3, p4, p5 with both c
> >>> and r being computed elsewhere from p1...p5. So we don't make special
> >>> cases for the case c = 0 for example.
> >>>
> >>> Does this explanation make sense to you?
> >>>
> >>> best regards,
> >>> Luc
> >>>
> >>>
> >>>>             final DerivativeStructure a_ds = new
> DerivativeStructure(1,
> >>> 1,
> >>>> a);
> >>>>             final DerivativeStructure out = a_ds.pow(dsA);
> >>>>             System.out.format("Derivative@%d=%f\n", a,
> >>>> out.getPartialDerivative(new int[]{1}));
> >>>>         }
> >>>>     }
> >>>> }
> >>>>
> >>>>
> >>>>
> >>>> On Fri, Aug 23, 2013 at 7:59 AM, Gilles <gilles@harfang.homelinux.org
> >>>> wrote:
> >>>>
> >>>>> On Fri, 23 Aug 2013 07:17:35 -0700, Ajo Fod wrote:
> >>>>>
> >>>>>> Seems like the DerivativeCompiler returns NaN.
> >>>>>>
> >>>>>> IMHO it should return 0.
> >>>>>>
> >>>>>
> >>>>> What should be 0?  And Why?
> >>>>>
> >>>>>
> >>>>>
> >>>>>> Is this worthy of an issue?
> >>>>>>
> >>>>>
> >>>>> As is, no.
> >>>>>
> >>>>> Gilles
> >>>>>
> >>>>>
> >>>>>> Thanks,
> >>>>>> -Ajo
> >>>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>
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> >>>>>
> >>>>>
> >>>>
> >>>
> >>>
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> >>>
> >>>
> >>
> >
> >
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> >
> >
>
>
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>

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