values_t operator+(const values_t& a, const values_t& b)
{
#ifndef OPTIMIZED
if(a.size() != b.size())
throw "Vector addition error: wrong sizes!";
#endif
values_t result(a.size());
for(unsigned int i=0; i<a.size(); i++){
result[i] = a[i]+b[i];
}
return result;
}
void Neuron::feed(const values_t& input)
{
#ifndef OPTIMIZED
if(input.size() != connections.size()){
throw "Invalid fire sizes!";
}
#endif
value = bias;
for(int i=0; i<input.size(); i++){
value += input[i] * connections[i];
}
}
TYPE sum(const values_t& a)
{
TYPE sum = 0.0;
for(unsigned int i=0; i<a.size(); i++){
sum += a[i];
}
return sum;
}
TYPE abs(const values_t& a)
{
TYPE sum = 0.0;
for(unsigned int i=0; i<a.size(); i++){
sum += a[i]*a[i];
}
return sqrt(sum);
}
void on_bars(const datetime_t& datetime, const values_t& bars)
{
log_trace("StrategyTest::{}", __func__);
try
{
const value_t& bar = bars.at(symbol);
log_debug("StrategyTest::{} {}", __func__, bar);
}
catch (std::exception& e)
{
log_error("StrategyTest::{} {}", __func__, e.what());
}
}
void print(values_t& v)
{
for(unsigned int i=0; i<v.size(); i++)
printf("%.5f ", v[i]);
printf("\n");
}
template <typename T> Value const& operator[](T&& key) const
{ return values.at(std::forward<T>(key)); }
