indicators.cpp

神经网络是序列预测,C++实现

#include "tseries.h"
#include "sunhack.h"

template<class DateT>
tseries<DateT> tseries<DateT>::true_high() const {

  double *high = getCol("high");
  double *close = getCol("close");

  if(high==NULL||close==NULL)
    return tseries();

  double *ans_data = new double[rows];
  DateT *ans_dates = new DateT[rows];

  if(ans_data==NULL || ans_dates==NULL) {
    cerr << "ERROR: tseries tseries::true_high() out of memory." << endl;
    return tseries();
  }

  // create dates of new tseries
  memcpy(ans_dates,getDates(),sizeof(double)*rows);

  ans_data[0] = NAN;

  for(unsigned int i = 1; i < rows; i++)
    ans_data[i] = (high[i] > close[i-1]) ? high[i] : close[i-1];

  return tseries(ans_data,ans_dates,rows,1,true);
}

template<class DateT>
tseries<DateT> tseries<DateT>::true_low() const {

  double *low = getCol("low");
  double *close = getCol("close");

  if(low==NULL||close==NULL)
    return tseries();

  double *ans_data = new double[rows];
  DateT *ans_dates = new DateT[rows];

  if(ans_data==NULL || ans_dates==NULL) {
    cerr << "ERROR: tseries tseries::true_low() out of memory." << endl;
    return tseries();
  }

  // create dates of new tseries
  memcpy(ans_dates,getDates(),sizeof(double)*rows);

  ans_data[0] = NAN;

  for(unsigned int i = 1; i < rows; i++)
    ans_data[i] = (low[i] < close[i-1]) ? low[i] : close[i-1];

  return tseries(ans_data,ans_dates,rows,1,true);
}