}
}
-template < class T >
-inline void ThreePointddt(T &df, const T &f1, const T &f2, const T &f3, int bias)
-{
- //a 3 point approximation pretends to have constant acceleration, so only one algorithm needed for left, middle, or right
- df = (f1 -f2*2 + f3)*(1/2.0f);
-}
-
-// WARNING -- totally broken
-template < class T >
-inline void FivePointddt(T &df, const T &f1, const T &f2, const T &f3, int bias)
-{
- if(bias == 0)
- {
- assert(0); // !?
- //middle
- //df = (- f1 + f2*16 - f3*30 + f4*16 - f5)*(1/12.0f);
- }/*else if(bias < 0)
- {
- //left
- df = (f1*7 - f2*26*4 + f3*19*6 - f4*14*4 + f5*11)*(1/12.0f);
- }else
- {
- //right
- df = (f1*3 - f2*16 + f3*36 - f4*48 + f5*25)*(1/12.0f);
- }*/
- //side ones don't work, use 3 point
-}
-
-//implement an arbitrary derivative
-//dumb algorithm
-template < class T >
-void DerivativeApprox(T &df, const T f[], const Real t[], int npoints, int indexval)
-{
- /*
- Lj(x) = PI_i!=j (x - xi) / PI_i!=j (xj - xi)
-
- so Lj'(x) = SUM_k PI_i!=j|k (x - xi) / PI_i!=j (xj - xi)
- */
-
- unsigned int i,j,k,i0,i1;
-
- Real Lpj,mult,div,tj;
- Real tval = t[indexval];
-
- //sum k
- for(j=0;j<npoints;++j)
- {
- Lpj = 0;
- div = 1;
- tj = t[j];
-
- for(k=0;k<npoints;++k)
- {
- if(k != j) //because there is no summand for k == j, since that term is missing from the original equation
- {
- //summation for k
- for(i=0;i<npoints;++i)
- {
- if(i != k)
- {
- mult *= tval - t[i];
- }
- }
-
- Lpj += mult; //add into the summation
-
- //since the ks follow the exact pattern we need for the divisor (use that too)
- div *= tj - t[k];
- }
- }
-
- //get the actual coefficient
- Lpj /= div;
-
- //add it in to the equation
- df += f[j]*Lpj;
- }
-}
+// template < class T >
+// inline void ThreePointddt(T &df, const T &f1, const T &f2, const T &f3, int bias)
+// {
+// // a 3 point approximation pretends to have constant acceleration,
+// // so only one algorithm needed for left, middle, or right
+// df = (f1 -f2*2 + f3)*(1/2.0f);
+// }
+//
+// // WARNING -- totally broken
+// template < class T >
+// inline void FivePointddt(T &df, const T &f1, const T &f2, const T &f3, int bias)
+// {
+// if(bias == 0)
+// {
+// assert(0); // !?
+// //middle
+// //df = (- f1 + f2*16 - f3*30 + f4*16 - f5)*(1/12.0f);
+// }/*else if(bias < 0)
+// {
+// //left
+// df = (f1*7 - f2*26*4 + f3*19*6 - f4*14*4 + f5*11)*(1/12.0f);
+// }else
+// {
+// //right
+// df = (f1*3 - f2*16 + f3*36 - f4*48 + f5*25)*(1/12.0f);
+// }*/
+// //side ones don't work, use 3 point
+// }
+//
+// //implement an arbitrary derivative
+// //dumb algorithm
+// template < class T >
+// void DerivativeApprox(T &df, const T f[], const Real t[], int npoints, int indexval)
+// {
+// /*
+// Lj(x) = PI_i!=j (x - xi) / PI_i!=j (xj - xi)
+//
+// so Lj'(x) = SUM_k PI_i!=j|k (x - xi) / PI_i!=j (xj - xi)
+// */
+//
+// unsigned int i,j,k,i0,i1;
+//
+// Real Lpj,mult,div,tj;
+// Real tval = t[indexval];
+//
+// //sum k
+// for(j=0;j<npoints;++j)
+// {
+// Lpj = 0;
+// div = 1;
+// tj = t[j];
+//
+// for(k=0;k<npoints;++k)
+// {
+// if(k != j) //because there is no summand for k == j, since that term is missing from the original equation
+// {
+// //summation for k
+// for(i=0;i<npoints;++i)
+// {
+// if(i != k)
+// {
+// mult *= tval - t[i];
+// }
+// }
+//
+// Lpj += mult; //add into the summation
+//
+// //since the ks follow the exact pattern we need for the divisor (use that too)
+// div *= tj - t[k];
+// }
+// }
+//
+// //get the actual coefficient
+// Lpj /= div;
+//
+// //add it in to the equation
+// df += f[j]*Lpj;
+// }
+// }
//END numerical derivatives
-template < class T >
-inline int sign(T f, T tol)
-{
- if(f < -tol) return -1;
- if(f > tol) return 1;
- return 0;
-}
+// template < class T >
+// inline int sign(T f, T tol)
+// {
+// if(f < -tol) return -1;
+// if(f > tol) return 1;
+// return 0;
+// }
void GetFirstDerivatives(const std::vector<synfig::Point> &f, unsigned int left, unsigned int right, char *out, unsigned int dfstride)
{
//build hermite curve, it's easier
curve.p1() = f[i0];
curve.p2() = f[i3];
- curve.t1() = df[i0]*(df[i0].mag_squared() > 1e-4 ? j2->tangentscale/df[i0].mag() : j2->tangentscale);
- curve.t2() = df[i3]*(df[i3].mag_squared() > 1e-4 ? j->tangentscale/df[i3].mag() : j->tangentscale);
+ curve.t1() = df[i0-ibase] * (df[i0-ibase].mag_squared() > 1e-4
+ ? j2->tangentscale/df[i0-ibase].mag()
+ : j2->tangentscale);
+ curve.t2() = df[i3-ibase] * (df[i3-ibase].mag_squared() > 1e-4
+ ? j->tangentscale/df[i3-ibase].mag()
+ : j->tangentscale);
curve.sync();
//MUST include the end point (since we are ignoring left one)
//preproceval += timer();
//numpre++;
- work.resize(size*2-1); //guarantee that all points will be tessellated correctly (one point inbetween every 2 adjacent points)
+ work.resize(size*2-1); //guarantee that all points will be tessellated correctly (one point in between every 2 adjacent points)
//if size of work is size*2-1, the step size should be 1/(size*2 - 2)
//Real step = 1/(Real)(size*2 - 1);
projects / synfig.git / blobdiff