//Computes the updated state of the system. Is called from the process function.
//This performs state space interpolation to calculate the state of the
//channel.
//When a value of Vm_ and ligandConc_ is provided, we find the 4 matrix
//exponentials that are closest to these values, and then calculate the
//states at each of these 4 points. We then interpolate between these
//states to calculate the final one.
//In case all rates are 1D, then, the above-mentioned interpolation is
//only one-dimensional in nature.
void MarkovSolverBase::computeState( )
{
Vector* newState;
bool useBilinear = false, useLinear = false;
if ( rateTable_->areAnyRates2d() ||
( rateTable_->areAllRates1d() &&
rateTable_->areAnyRatesVoltageDep() &&
rateTable_->areAnyRatesLigandDep()
) )
{
useBilinear = true;
}
else if ( rateTable_->areAllRatesVoltageDep() ||
rateTable_->areAllRatesLigandDep() )
{
useLinear = true;
}
//Heavily borrows from the Interpol2D::interpolate function.
if ( useBilinear )
newState = bilinearInterpolate();
else
newState = linearInterpolate();
state_ = *newState;
delete newState;
}
double smooth_noiseBilinear(Vector2D p,int seed){
double x;
double y;
double fractional_x;
double fractional_y;
int integer_x;
int integer_y;
if(p.x()>=0){
x=p.x();
integer_x = (int)x;
fractional_x = x - integer_x;
}
else{
integer_x=((int)p.x())-1;
fractional_x=p.x()-integer_x;
}
if(p.y()>=0){
y=p.y();
integer_y = (int)y;
fractional_y = y - integer_y;
}
else{
integer_y=((int)p.y())-1;
fractional_y=p.y()-integer_y;
}
Vector2D pf(fractional_x,fractional_y);
double xy = noise(integer_x,integer_y,seed);
double x1y = noise(integer_x+1,integer_y,seed);
double xy1 = noise(integer_x,integer_y+1,seed);
double x1y1 = noise(integer_x+1,integer_y+1,seed);
return bilinearInterpolate(xy,x1y,xy1,x1y1,pf);
}
