C++ ColumnVector::resize方法代码示例

void RealFFT(const ColumnVector& U, ColumnVector& X, ColumnVector& Y)
{
   // Fourier transform of a real series
   Tracer trace("RealFFT");
   REPORT
   const int n = U.Nrows();                     // length of arrays
   const int n2 = n / 2;
   if (n != 2 * n2)
      Throw(ProgramException("Vector length not multiple of 2", U));
   ColumnVector A(n2), B(n2);
   Real* a = A.Store(); Real* b = B.Store(); Real* u = U.Store(); int i = n2;
   while (i--) { *a++ = *u++; *b++ = *u++; }
   FFT(A,B,A,B);
   int n21 = n2 + 1;
   X.resize(n21); Y.resize(n21);
   i = n2 - 1;
   a = A.Store(); b = B.Store();              // first els of A and B
   Real* an = a + i; Real* bn = b + i;        // last els of A and B
   Real* x = X.Store(); Real* y = Y.Store();  // first els of X and Y
   Real* xn = x + n2; Real* yn = y + n2;      // last els of X and Y

   *x++ = *a + *b; *y++ = 0.0;                // first complex element
   *xn-- = *a++ - *b++; *yn-- = 0.0;          // last complex element

   int j = -1; i = n2/2;
   while (i--)
   {
      Real c,s; cossin(j--,n,c,s);
      Real am = *a - *an; Real ap = *a++ + *an--;
      Real bm = *b - *bn; Real bp = *b++ + *bn--;
      Real samcbp = s * am + c * bp; Real sbpcam = s * bp - c * am;
      *x++  =  0.5 * ( ap + samcbp); *y++  =  0.5 * ( bm + sbpcam);
      *xn-- =  0.5 * ( ap - samcbp); *yn-- =  0.5 * (-bm + sbpcam);
   }
}

// Multiply X by n-1 x n matrix to give n-1 contrasts
// Return a ColumnVector
ReturnMatrix Helmert(const ColumnVector& X, bool full)
{
   REPORT
   Tracer et("Helmert * CV");
   int n = X.nrows();
   if (n == 0) Throw(ProgramException("X Vector of length 0", X));
   Real sum = 0.0; ColumnVector Y;
   if (full) Y.resize(n); else Y.resize(n-1);
   for (int i = 1; i < n; ++i)
      { sum += X(i); Y(i) = (i * X(i+1) - sum) / sqrt((Real)i * (i+1)); }
   if (full) { sum += X(n); Y(n) = sum / sqrt((Real)n); }
   Y.release(); return Y.for_return();
} 

void RealFFTI(const ColumnVector& A, const ColumnVector& B, ColumnVector& U)
{
   // inverse of a Fourier transform of a real series
   Tracer trace("RealFFTI");
   REPORT
   const int n21 = A.Nrows();                     // length of arrays
   if (n21 != B.Nrows() || n21 == 0)
      Throw(ProgramException("Vector lengths unequal or zero", A, B));
   const int n2 = n21 - 1;  const int n = 2 * n2;  int i = n2 - 1;

   ColumnVector X(n2), Y(n2);
   Real* a = A.Store(); Real* b = B.Store();  // first els of A and B
   Real* an = a + n2;   Real* bn = b + n2;    // last els of A and B
   Real* x = X.Store(); Real* y = Y.Store();  // first els of X and Y
   Real* xn = x + i;    Real* yn = y + i;     // last els of X and Y

   Real hn = 0.5 / n2;
   *x++  = hn * (*a + *an);  *y++  = - hn * (*a - *an);
   a++; an--; b++; bn--;
   int j = -1;  i = n2/2;
   while (i--)
   {
      Real c,s; cossin(j--,n,c,s);
      Real am = *a - *an; Real ap = *a++ + *an--;
      Real bm = *b - *bn; Real bp = *b++ + *bn--;
      Real samcbp = s * am - c * bp; Real sbpcam = s * bp + c * am;
      *x++  =  hn * ( ap + samcbp); *y++  =  - hn * ( bm + sbpcam);
      *xn-- =  hn * ( ap - samcbp); *yn-- =  - hn * (-bm + sbpcam);
   }
   FFT(X,Y,X,Y);             // have done inverting elsewhere
   U.resize(n); i = n2;
   x = X.Store(); y = Y.Store(); Real* u = U.Store();
   while (i--) { *u++ = *x++; *u++ = - *y++; }
}

 /*
 * helper function to allocate all the memory necessary to respresent the responsabilities.
 * @param N_meas number of points
 * @param N_comp number of clusters
 */
 void allocate(int N_meas, int N_comp)
 {
     R.assign(N_meas,ColumnVector(N_comp));
     responsibleCluster.assign(N_meas,-1);
     sumR.resize(N_meas);
     N.resize(N_comp);   
 }

void FFT(const ColumnVector& U, const ColumnVector& V,
   ColumnVector& X, ColumnVector& Y)
{
   // from Carl de Boor (1980), Siam J Sci Stat Comput, 1 173-8
   // but first try Sande and Gentleman
   Tracer trace("FFT");
   REPORT
   const int n = U.Nrows();                     // length of arrays
   if (n != V.Nrows() || n == 0)
      Throw(ProgramException("Vector lengths unequal or zero", U, V));
   if (n == 1) { REPORT X = U; Y = V; return; }

   // see if we can use the newfft routine
   if (!FFT_Controller::OnlyOldFFT && FFT_Controller::CanFactor(n))
   {
      REPORT
      X = U; Y = V;
      if ( FFT_Controller::ar_1d_ft(n,X.Store(),Y.Store()) ) return;
   }

   ColumnVector B = V;
   ColumnVector A = U;
   X.resize(n); Y.resize(n);
   const int nextmx = 8;
   int prime[8] = { 2,3,5,7,11,13,17,19 };
   int after = 1; int before = n; int next = 0; bool inzee = true;
   int now = 0; int b1;             // initialised to keep gnu happy

   do
   {
      for (;;)
      {
	 if (next < nextmx) { REPORT now = prime[next]; }
	 b1 = before / now;  if (b1 * now == before) { REPORT break; }
	 next++; now += 2;
      }
      before = b1;

      if (inzee) { REPORT fftstep(A, B, X, Y, after, now, before); }
      else { REPORT fftstep(X, Y, A, B, after, now, before); }

      inzee = !inzee; after *= now;
   }

LinearAnalyticConditionalGaussian::LinearAnalyticConditionalGaussian(const vector<Matrix> & ratio,
        const Gaussian& additiveNoise)
    : AnalyticConditionalGaussianAdditiveNoise(additiveNoise,ratio.size())
    , _ratio(ratio)
    , _mean_temp(DimensionGet())
    , _arg(DimensionGet())
{
    // Initialise ConditionalArguments to 0
    ColumnVector arg;
    for (unsigned int i=0; i < NumConditionalArgumentsGet() ; i++)
    {
        arg.resize(_ratio[i].columns());
        arg = 0.0;
        ConditionalArgumentSet(i,arg);
    }
}

ColumnVector
MLP<Model, Tuple>::predict(
        const model_type                    &model,
        const independent_variables_type    &x,
        const bool                          get_class) {
    std::vector<ColumnVector> net, o;

    feedForward(model, x, net, o);
    ColumnVector output = o.back();

    if(get_class){ // Return a length 1 array with the predicted index
        int max_idx;
        output.maxCoeff(&max_idx);
        output.resize(1);
        output[0] = (double) max_idx;
    }
    return output;
}