protected override void Solve()
{
InitNeuronCell();
//if (SomaOn) { U.SetSubVector(0, myCell.vertCount, setSoma(U, myCell.somaID, vstart)); }
int nT; // Number of Time steps
List <bool> channels = new List <bool> {
false, false, false
}; // For adding/removing channels
// TODO: NEED TO DO THIS BETTER
if (HK_auto)
{
h = 0.1 * NeuronCell.edgeLengths.Average();
//if (h > 0.29) { h = 0.29; }
if (h <= 1)
{
k = h / 140;
}
if (h <= 0.5)
{
k = h / 70;
}
if (h <= 0.25)
{
k = h / 35;
}
if (h <= 0.12)
{
k = h / 18;
}
if (h <= 0.06)
{
k = h / 9;
}
if (h <= 0.03)
{
k = h / 5;
}
}
// Number of time steps
nT = (int)System.Math.Floor(endTime / k);
// set some constants for the HINES matrix
double diffConst = (1 / (2 * res * cap));
double cfl = diffConst * k / h;
// reaction vector
Vector R = Vector.Build.Dense(NeuronCell.vertCount);
List <double> reactConst = new List <double> {
gk, gna, gl, ek, ena, el
};
// temporary voltage vector
Vector tempV = Vector.Build.Dense(NeuronCell.vertCount);
// Construct sparse RHS and LHS in coordinate storage format, no zeros are stored
List <CoordinateStorage <double> > sparse_stencils = makeSparseStencils(NeuronCell, h, k, diffConst);
// Compress the sparse matrices
CompressedColumnStorage <double> r_csc = CompressedColumnStorage <double> .OfIndexed(sparse_stencils[0]); //null;
CompressedColumnStorage <double> l_csc = CompressedColumnStorage <double> .OfIndexed(sparse_stencils[1]); //null;
// Permutation matrix----------------------------------------------------------------------//
int[] p = new int[NeuronCell.vertCount];
p = Permutation.Create(NeuronCell.vertCount, 0);
CompressedColumnStorage <double> Id_csc = CompressedColumnStorage <double> .CreateDiagonal(NeuronCell.vertCount, 1);
Id_csc.PermuteRows(p);
//--------------------------------------------------------------------------------------------//
// for solving Ax = b problem
double[] b = new double[NeuronCell.vertCount];
// Apply column ordering to A to reduce fill-in.
//var order = ColumnOrdering.MinimumDegreeAtPlusA;
// Create Cholesky factorization setup
var chl = SparseCholesky.Create(l_csc, p);
//var chl = SparseCholesky.Create(l_csc, order);
try
{
for (i = 0; i < nT; i++)
{
if (SomaOn)
{
U.SetSubVector(0, NeuronCell.vertCount, setSoma(U, NeuronCell.somaID, vstart));
}
mutex.WaitOne();
r_csc.Multiply(U.ToArray(), b); // Peform b = rhs * U_curr
// Diffusion solver
chl.Solve(b, b);
// Set U_next = b
U.SetSubVector(0, NeuronCell.vertCount, Vector.Build.DenseOfArray(b));
// Save voltage from diffusion step for state probabilities
tempV.SetSubVector(0, NeuronCell.vertCount, U);
// Reaction
channels[0] = na_ONOFF;
channels[1] = k_ONOFF;
channels[2] = leak_ONOFF;
R.SetSubVector(0, NeuronCell.vertCount, reactF(reactConst, U, N, M, H, channels, NeuronCell.boundaryID));
R.Multiply(k / cap, R);
// This is the solution for the voltage after the reaction is included!
U.Add(R, U);
//Now update state variables using FE on M,N,H
N.Add(fN(tempV, N).Multiply(k), N);
M.Add(fM(tempV, M).Multiply(k), M);
H.Add(fH(tempV, H).Multiply(k), H);
//Always reset to IC conditions and boundary conditions (for now)
U.SetSubVector(0, NeuronCell.vertCount, boundaryConditions(U, NeuronCell.boundaryID));
if (SomaOn)
{
U.SetSubVector(0, NeuronCell.vertCount, setSoma(U, NeuronCell.somaID, vstart));
}
mutex.ReleaseMutex();
}
}
catch (Exception e)
{
GameManager.instance.DebugLogThreadSafe(e);
}
GameManager.instance.DebugLogSafe("Simulation Over.");
}
protected override void Solve()
{
InitNeuronCell();
for (int kSim = 0; kSim <= numRuns; kSim++)
{
//if (SomaOn) { U.SetSubVector(0, myCell.vertCount, setSoma(U, myCell.somaID, vstart)); }
int nT; // Number of Time steps
List <bool> channels = new List <bool> {
false, false, false
}; // For adding/removing channels
// TODO: NEED TO DO THIS BETTER
if (HK_auto)
{
h = 0.1 * NeuronCell.edgeLengths.Average();
//if (h > 0.29) { h = 0.29; }
if (h <= 1)
{
k = h / 130;
} // 0 refine
if (h <= 0.5)
{
k = h / 65;
} // 1 refine
if (h <= 0.25)
{
k = h / 32.5;
} // 2 refine
if (h <= 0.12)
{
k = h / 18;
} // 3 refine
if (h <= 0.06)
{
k = h / 9;
} // 4 refine
if (h <= 0.03)
{
k = h / 5;
}
}
// setup up paths for writing output
string strPath = Environment.GetFolderPath(System.Environment.SpecialFolder.DesktopDirectory);
string subPath = strPath + @"\VR_Simulations";
bool exists = System.IO.Directory.Exists(subPath);
// check if directory exists
if (!exists)
{
System.IO.Directory.CreateDirectory(subPath);
}
// set the path for writing
strPath = subPath;
DirectoryInfo di = Directory.CreateDirectory(strPath + @"\SimulationRun" + "_" + kSim);
strPath = strPath + @"\SimulationRun" + "_" + kSim;
// Number of time steps
nT = (int)System.Math.Floor(endTime / k);
// set some constants for the HINES matrix
double diffConst = (1 / (2 * res * cap));
double cfl = diffConst * k / h;
// reaction vector
Vector R = Vector.Build.Dense(NeuronCell.vertCount);
List <double> reactConst = new List <double> {
gk, gna, gl, ek, ena, el
};
// temporary voltage vector
Vector tempV = Vector.Build.Dense(NeuronCell.vertCount);
// Construct sparse RHS and LHS in coordinate storage format, no zeros are stored
List <CoordinateStorage <double> > sparse_stencils = makeSparseStencils(NeuronCell, h, k, diffConst);
// Compress the sparse matrices
CompressedColumnStorage <double> r_csc = CompressedColumnStorage <double> .OfIndexed(sparse_stencils[0]); //null;
CompressedColumnStorage <double> l_csc = CompressedColumnStorage <double> .OfIndexed(sparse_stencils[1]); //null;
// Permutation matrix----------------------------------------------------------------------//
int[] p = new int[NeuronCell.vertCount];
if (randomPermute)
{
p = Permutation.Create(NeuronCell.vertCount, 1);
}
else
{
p = Permutation.Create(NeuronCell.vertCount, 0);
}
CompressedColumnStorage <double> Id_csc = CompressedColumnStorage <double> .CreateDiagonal(NeuronCell.vertCount, 1);
Id_csc.PermuteRows(p);
//--------------------------------------------------------------------------------------------//
// for solving Ax = b problem
double[] b = new double[NeuronCell.vertCount];
// Apply column ordering to A to reduce fill-in.
//var order = ColumnOrdering.MinimumDegreeAtPlusA;
// Create Cholesky factorization setup
Timer timer = new Timer();
timer.StartTimer();
var chl = SparseCholesky.Create(l_csc, p);
//var chl = SparseCholesky.Create(l_csc, order);
timer.StopTimer("Matrix Setup");
timer.ExportCSV_path(strPath + @"\chlSetup_" + kSim);
// Write permutation, rhsM, lhsM, and choleskyR matrix to file
if (printMatrices)
{
printMatrix(Id_csc, r_csc, l_csc, chl.L, strPath, kSim);
}
// Print cell info to a text file
if (printCellInfo)
{
printCell(NeuronCell, h, k, nT, endTime, cfl, strPath, kSim);
}
// For printing voltage data and time steps
var sw = new StreamWriter(strPath + @"\outputVoltage_" + kSim + ".txt", true);
var tw = new StreamWriter(strPath + @"\timesteps_" + kSim + ".txt", true);
timer = new Timer(nT);
try
{
for (i = 0; i < nT; i++)
{
if (SomaOn)
{
U.SetSubVector(0, NeuronCell.vertCount, setSoma(U, NeuronCell.somaID, vstart));
}
mutex.WaitOne();
r_csc.Multiply(U.ToArray(), b); // Peform b = rhs * U_curr
// Diffusion solver
timer.StartTimer();
chl.Solve(b, b);
timer.StopTimer(i.ToString());
// Set U_next = b
U.SetSubVector(0, NeuronCell.vertCount, Vector.Build.DenseOfArray(b));
// Save voltage from diffusion step for state probabilities
tempV.SetSubVector(0, NeuronCell.vertCount, U);
// Reaction
channels[0] = na_ONOFF;
channels[1] = k_ONOFF;
channels[2] = leak_ONOFF;
R.SetSubVector(0, NeuronCell.vertCount, reactF(reactConst, U, N, M, H, channels, NeuronCell.boundaryID));
R.Multiply(k / cap, R);
// This is the solution for the voltage after the reaction is included!
U.Add(R, U);
//Now update state variables using FE on M,N,H
N.Add(fN(tempV, N).Multiply(k), N);
M.Add(fM(tempV, M).Multiply(k), M);
H.Add(fH(tempV, H).Multiply(k), H);
//Always reset to IC conditions and boundary conditions (for now)
U.SetSubVector(0, NeuronCell.vertCount, boundaryConditions(U, NeuronCell.boundaryID));
if (SomaOn)
{
U.SetSubVector(0, NeuronCell.vertCount, setSoma(U, NeuronCell.somaID, vstart));
}
if (printVolt_time)
{
for (int j = 0; j < NeuronCell.vertCount; j++)
{
sw.Write(U[j] + " ");
}
sw.Write("\n");
tw.Write((k * (double)i) + " ");
tw.Write("\n");
}
mutex.ReleaseMutex();
}
sw.Close();
tw.Close();
}
catch (Exception e)
{
GameManager.instance.DebugLogThreadSafe(e);
}
finally
{
timer.ExportCSV_path(strPath + @"\diffusionTimes_" + kSim);
sw.Close();
tw.Close();
}
GameManager.instance.DebugLogSafe("Simulation Over.");
}
}
