I'm trying to implement Runga Kutta method for solving the Lorenz differential equation system.
At some point, the program always stops at a breakpoint which I can't see, and then throws an error about heap corruption.
Something must be wrong with the way I use the pointers, but I have no idea what's not working well.
Here's my code:// Runge_Kutta.cpp : This file contains the 'main' function. Program execution begins and ends there.
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <stdlib.h>
#include <iostream>
#include <stdio.h>
#include <fstream>
#include <vector>
#include <time.h>
#include <math.h>
#include <fstream>
#include <chrono>
using namespace std;
const int dimension=3;
double* F = new double(3);
double p1 = 10;
double p2 = 28;
double p3 = 8.0 / 3.0;
double* K1 = new double(3);
double* K2 = new double(3);
double* K3 = new double(3);
double* K4 = new double(3);
double* X = new double(3);
double* t = new double(3);
double a = 0;
double b = 100;
const int N = 1000;
//double * x=new double[N];
double dt = (b - a) / N;
void f(double *F,double *x, double *t)
{
double dx1 = p1 * (x[1] - x[0]);
double dx2 = x[0] * (p2 - x[2]) - x[1];
double dx3 = x[0] * x[1] - p3 * x[2];
//cout << "dx-ek: " << dx1 << " " << dx2 << " " << dx3 << "\n";
F[0] = dx1;
F[1] = dx2;
F[2] = dx3;
}
double* RK4(double* x, double *t, double dt)
{
f(K1, x, t);
//cout << "K1: " << K1[0] << " " << K1[1] << " " << K1[2] << "\n";
for (int i = 0; i < dimension; i++)
{
X[i] = x[i] + dt * K1[i] * 0.5;
}
f(K2, X, t);
//cout << "K2: " << K2[0] << " " << K2[1] << " " << K2[2] << "\n";
for (int i = 0; i < dimension; i++)
{
X[i] = x[i] + dt * K2[i] * 0.5;
}
f(K3, X, t);
//cout << "K3: " << K3[0] << " " << K3[1] << " " << K3[2] << "\n";
for (int i = 0; i < dimension; i++)
{
X[i] = x[i] + dt * K2[i] * 0.5;
}
f(K4, X, t);
//cout << "K4: " << K4[0] << " " << K4[1] << " " << K4[2] << "\n";
for (int i = 0; i < dimension; i++)
{
//cout << "Ennek nem kéne 0-nak lennie: " << K1[i] * 0.1666666 + K2[i] * 0.33333333 + K3[i] * 0.3333333 + K4[i] * 0.1666666 << '\n';
x[i] = x[i] + dt * (K1[i] * 0.1666666 + K2[i] * 0.33333333 + K3[i] * 0.3333333 + K4[i] * 0.1666666);
//cout << "Return előtt előtt: " << x[0] << " " << x[1] << " " << x[2] << "\n";
}
//cout << "Return előtt: " << x[0] << " " << x[1] << " " << x[2] << "\n";
return x;
}
int main()
{
cout << "Let's start!";
std::ofstream myfile;
myfile.open("solution.csv");
double* x = new double(3);
/*
for(int z=0;z<dimension;z++)
{
//cout << "WHat the heck?";
x[z]= 0;
}
*/
x[0] = -5.0;
x[1] = 0.0;
x[2] = 0.0;
auto start=std::chrono::high_resolution_clock::now();
for (int j = 0; j < N; j++)
{
RK4(x, t, dt);
//cout << j << "\n";
//cout << "Return után "<< x[0] << " " <<x[1]<<" "<<x[2]<<" it: "<<j << "\n";
//cout << "\n";
for (int u = 0; u < dimension; u++)
{
myfile << x[u];
if (u <= dimension - 2) myfile << ",";
else myfile << "\n";
}
}
auto elapsed = std::chrono::high_resolution_clock::now()-start;
long long microseconds = std::chrono::duration_cast<std::chrono::microseconds>(elapsed).count();
cout << "Simulation time: " << microseconds << " microsec" << endl << endl;
myfile.close();```
In the following snippet, when I print the posUVZ values, they are non-zero but after I pass them to ProjectDepthToCamera(wxhDepth, posUVZ, pos3D) all the pos3D values happen to be zero. Any though on why is this happening and how to fix it?
/***
Reads the depth data from the sensor and fills in the matrix
***/
void SR300Camera::fillInZCoords()
{
PXCImage::ImageData depthImage;
PXCImage *depthMap = sample->depth;
depthMap->AcquireAccess(PXCImage::ACCESS_READ, &depthImage);
PXCImage::ImageInfo imgInfo = depthMap->QueryInfo();
int depth_stride = depthImage.pitches[0] / sizeof(pxcU16);
Projection * projection = device->CreateProjection();
unsigned int wxhDepth = depth_width * depth_height;
// create the array of depth coordinates + depth value (posUVZ) within the defined ROI
PXCPoint3DF32* posUVZ = new PXCPoint3DF32[wxhDepth];
pxcU16 *dpixels = (pxcU16*)depthImage.planes[0];
unsigned int dpitch = depthImage.pitches[0] / sizeof(pxcU16); /* aligned width */
for (unsigned int yy = 0, k = 0; yy < depth_height; yy++)
{
for (unsigned int xx = 0; xx < depth_width; xx++, k++)
{
posUVZ[k].x = (pxcF32)xx;
posUVZ[k].y = (pxcF32)yy;
posUVZ[k].z = (pxcF32)dpixels[yy * dpitch + xx];
// cout << "xx is " << posUVZ[k].x << endl;
// cout << "yy is " << posUVZ[k].y << endl;
// cout << "zz is " << posUVZ[k].z<< endl;
}
}
// convert the array of depth coordinates + depth value (posUVZ) into the world coordinates (pos3D) in mm
PXCPoint3DF32* pos3D = new PXCPoint3DF32[wxhDepth];
projection->ProjectDepthToCamera(wxhDepth, posUVZ, pos3D);
/*
if (projection->ProjectDepthToCamera(wxhDepth, posUVZ, pos3D) < PXC_STATUS_NO_ERROR)
{
delete[] posUVZ;
delete[] pos3D;
cout << "projection unsucessful";
return;
}
*/
for (unsigned int yy = 0, k = 0; yy < depth_height; yy++)
{
for (unsigned int xx = 0; xx < depth_width; xx++, k++)
{
cout << "xx is " << pos3D[k].x*1000.0 << endl;
cout << "yy is " << pos3D[k].y*1000.0 << endl;
cout << "zz is " << pos3D[k].z*1000.0 << endl;
xyzBuffer.push_back(cv::Point3f(pos3D[k].x, pos3D[k].y, pos3D[k].z));
}
}
/*
for (int idx = 0; idx < wxhDepth; idx++) {
cout << "x is " << pos3D[idx].x*1000.0 << endl;
cout << "y is " << pos3D[idx].y*1000.0 << endl;
cout << "z is " << pos3D[idx].z*1000.0 << endl;
xyzBuffer.push_back(cv::Point3f(pos3D[idx].x, pos3D[idx].y, pos3D[idx].z));
}
*/
//xyzMap = cv::Mat(xyzMap.size(), xyzMap.type, &pos3D);
xyzMap = cv::Mat(xyzBuffer);
cout << "xyzMap = " << endl << " " << xyzMap << endl << endl;
projection->Release();
delete[] posUVZ;
delete[] pos3D;
};
Here's the correct answer to get the xyzMap from the Depth image UVmap:
PXCImage::ImageData depthImage;
depthMap->AcquireAccess(PXCImage::ACCESS_READ, &depthImage);
PXCImage::ImageInfo imgInfo = depthMap->QueryInfo();
depth_width = imgInfo.width;
depth_height = imgInfo.height;
num_pixels = depth_width * depth_height;
PXCProjection * projection = device->CreateProjection();
PXCPoint3DF32 *pos3D = new PXCPoint3DF32[num_pixels];
sts = projection->QueryVertices(depthMap, &pos3D[0]);
if (sts < Status::STATUS_NO_ERROR) {
wprintf_s(L"Projection was unsuccessful! \n");
sm->Close();
}
I have a simple main code that gives me segmentation fault when calling a function. In the following code, I have two functions, the first one works correctly but the program doesn't enter the second one and gives me segmentation fault error. Is there any reason for that? I have made sure about the following:
The variables o and c are not out of bound.
cn is initialized correctly.
I have a read-only access to cm and argv. Plus it does not even enter the function evaluate
Here is the code:
void print_cm(vector<vector<int> > *cm, char* gtf);
void evaluate(vector<vector<int> > *cm, char* gtf);
int main(int argc, char** argv)
{
int o = 2; // It is initialized
int c = 4; // It is initialized
vector<vector<int> > cm; // It is initialized
if (argc>4)
print_cm(&cm, argv[o]);
if (argc>4)
{
cout << argv[c] << endl; // Works
// The following also works
for (int i=0; i<cm.size(); i++)
for (int j=0; j<cm[i].size(); j++)
cout << cm[i][j] << " ";
// The following causes segmentation fault;
evaluate(&cm, argv[c]);
}
return 0;
}
void evaluate(vector<vector<int> > *cm, char* gtf)
{
// Read-only access to cm and gtf
}
void print_cm(vector<vector<int> > *cm, char* gtf)
{
// Read-only access to cm and gtf
}
Here is the complete code:
#include "includes/Utility.h"
#include "includes/Graph.h"
void print_cm(vector<vector<int> > *cores, char* output);
void evaluate(vector<vector<int> > const *cm, char* gtf);
int main(int argc, char** argv)
{
int g = -1, c = -1, o = -1;
for (int i=1; i<argc-1; i++)
if (argv[i][0]=='-')
{
if (argv[i][1]=='g')
g = i + 1;
else if (argv[i][1]=='c')
c = i + 1;
else if (argv[i][1]=='k')
ki = i + 1;
else if (argv[i][1]=='s')
si = i + 1;
else if (argv[i][1]=='o')
o = i + 1;
}
Graph G;
if (c>0) G.read_input(argv[g], argv[c]);
else G.read_input(argv[g]);
if (ki > 0)
{
int k = atoi(argv[ki]);
cout << k << endl;
}
if (si > 0)
{
int s = atoi(argv[si]);
cout << s << endl;
}
// Find communities
vector<vector<int> > cores;
G.partitioning(&cores);
if (o>0)
print_cm(&cores, argv[o]);
if (c>0)
{
cout << "here" << endl;
for (size_t i=0; i<cores.size(); i++)
for (size_t j=0; j<cores[i].size(); j++)
if (cores.at(i).at(j)<0) cout << "here";
cout << "here" << endl;
evaluate(&cores, argv[c]);
}
}
return 0;
}
void print_cm(vector<vector<int> > *cores, char* output)
{
ofstream out;
out.open(output);
for(size_t i=0; i<(*cores).size(); i++)
{
for(size_t j=0; j<(*cores)[i].size(); j++)
out << (*cores)[i][j] << " ";
out << endl;
}
out.close();
return ;
}
void evaluate(vector<vector<int> > const *cm, char* gtf)
{
// we evaluate precision, recall, F1 and F2
vector<vector<int> > gt;
ifstream in;
char str[100000000];
in.open(gtf);
while(in.getline(str, 100000000))
{
stringstream s;
s << str;
int a;
gt.resize(gt.size()+1);
while (s >> a) gt[gt.size()-1].push_back(a);
}
in.close();
cout << "==================== Evaluation Results ====================" << endl;
int imax = 0;
for(size_t i=0; i<(*cm).size(); i++)
imax = max(imax, *max_element((*cm)[i].begin(), (*cm)[i].end()));
for(size_t i=0; i<gt.size(); i++)
imax = max(imax, *max_element(gt[i].begin(), gt[i].end()));
vector<bool> flag(imax, false);
vector<double> recall((*cm).size(), 0), precision((*cm).size(), 0), f1((*cm).size(), 0), f2((*cm).size(), 0);
int overlap;
double size = 0;
for(size_t i=0; i<(*cm).size(); i++)
{
// evaluate
size += (double) (*cm)[i].size();
for(size_t j=0; j<(*cm)[i].size(); j++)
flag[(*cm)[i][j]] = true;
double p, r, ff1, ff2;
for(size_t j=0; j<gt.size(); j++)
{
overlap = 0;
for(size_t k=0; k<gt[j].size(); k++)
if (flag[gt[j][k]]) overlap++;
p = (double) overlap / (double) (*cm)[i].size();
if (p > precision[i])
precision[i] = p;
r = (double) overlap / (double) gt[j].size();
if (r > recall[i])
recall[i] = r;
ff1 = (double) 2*(p*r)/(p+r);
if (ff1 > f1[i])
f1[i] = ff1;
ff2 = (double) 5*(p*r)/(4*p + r);
if (ff2 > f2[i])
f2[i] = ff2;
}
for(size_t j=0; j<(*cm)[i].size(); j++)
flag[(*cm)[i][j]] = false;
}
double Recall = 0, Precision = 0, F1 = 0, F2 = 0;
for(size_t i=0; i<(*cm).size(); i++)
{
Recall += recall[i];
Precision += precision[i];
F1 += f1[i];
F2 += f2[i];
}
cout << "+--------------+--------------+--------------+--------------+" << endl;
cout << "| " << setiosflags( ios::left ) << setw(10) << "Precision";
cout << " | " << setiosflags( ios::left ) << setw(10) << "Recall";
cout << " | " << setiosflags( ios::left ) << setw(10) << "F1-measure";
cout << " | " << setiosflags( ios::left ) << setw(10) << "F2-measure";
cout << " |" << endl;
cout << "| " << setiosflags( ios::left ) << setw(10) << Precision/(*cm).size() ;
cout << " | " << setiosflags( ios::left ) << setw(10) << Recall/(*cm).size();
cout << " | " << setiosflags( ios::left ) << setw(10) << F1/(*cm).size();
cout << " | " << setiosflags( ios::left ) << setw(10) << F2/(*cm).size();
cout << " |" << endl;
cout << "+--------------+--------------+--------------+--------------+" << endl;
cout << "Number of communities: " << (*cm).size() << endl;
cout << "Average community size: " << size/(*cm).size() << endl;
return ;
}
char str[100000000];
This is in your evaluate function. This are 100 million bytes, or about 95 MB that you're allocating on the stack.
Typical stack sizes are far less than that, around 1 MB.
So apart from possible other problems this is most likely causing a stack overflow.
When entering the function, the stack frame gets extended to be large enough to hold the local variables. As soon as the stack is used then (to write a default value) you're accessing invalid (non stack, thankfully protected) memory.
I'm attempting to test a mathematical class I've created using random numbers from the full range of representable positivefloats, but I find that I seem to be having a problem with my use of std::random. This program
#include <random>
#include <iostream>
#include <functional>
template <typename T>
class Rand {
public:
Rand(T lo=std::numeric_limits<T>::min(),
T hi=std::numeric_limits<T>::max()) :
r(bind(std::uniform_real_distribution<>(lo, hi),std::mt19937_64{})) {}
T operator()() const { return r(); }
private:
std::function<T()> r;
};
int main()
{
Rand<float> f{};
const int samples = 1000000;
float min = std::numeric_limits<float>::max();
float max = std::numeric_limits<float>::min();
std::cout << "range min = " << max
<< ", max = " << min << '\n';
for (int i=0; i < samples; ++i) {
float r = f();
if (r < min) min = r;
if (r > max) max = r;
}
std::cout << "for n = " << samples
<< "\nsample min = " << min
<< ", max = " << max << std::endl;
}
produces this output
range min = 1.17549e-38, max = 3.40282e+38
for n = 1000000
sample min = 8.14884e+31, max = 3.40281e+38
Clearly the range is extremely skewed toward larger numbers. How do I generate the desired range of floats with a uniform distribution?
In addition to the statistics you have printed out, I've computed both the theoretical and actual mean, variance, skew and kurtosis of this distribution. Here is my code, and the results:
#include <random>
#include <iostream>
#include <functional>
#include <vector>
#include <numeric>
#include <cmath>
template <typename T>
class Rand {
public:
Rand(T lo=std::numeric_limits<T>::min(),
T hi=std::numeric_limits<T>::max()) :
r(bind(std::uniform_real_distribution<>(lo, hi),std::mt19937_64{})) {}
T operator()() const { return r(); }
private:
std::function<T()> r;
};
template <class T>
inline
T
sqr(T x)
{
return x * x;
}
int main()
{
Rand<float> f{};
const int samples = 1000000;
float min = std::numeric_limits<float>::max();
float max = std::numeric_limits<float>::min();
std::vector<float> u;
std::cout << "range min = " << max
<< ", max = " << min << '\n';
for (int i=0; i < samples; ++i) {
float r = f();
if (r < min) min = r;
if (r > max) max = r;
u.push_back(r);
}
std::cout << "for n = " << samples
<< "\nsample min = " << min
<< ", max = " << max << std::endl;
double mean = std::accumulate(u.begin(), u.end(),
double(0)) / u.size();
double var = 0;
double skew = 0;
double kurtosis = 0;
for (int i = 0; i < u.size(); ++i)
{
double d = (u[i] - mean);
double d2 = sqr(d);
var += d2;
skew += d * d2;
kurtosis += d2 * d2;
}
var /= u.size();
double dev = std::sqrt(var);
skew /= u.size() * dev * var;
kurtosis /= u.size() * var * var;
kurtosis -= 3;
double x_mean = ((double)min + max) / 2;
double x_var = sqr((double)max - min) / 12;
double x_skew = 0;
double x_kurtosis = -6./5;
std::cout << std::scientific << '\n';
std::cout << " expected actual\n";
std::cout << "mean " << x_mean << " " << mean << "\n";
std::cout << "variance " << x_var << " " << var << "\n";
std::cout << "skew " << x_skew << " " << skew << "\n";
std::cout << "kurtosis " << x_kurtosis << " " << kurtosis << "\n";
}
And here are the results:
range min = 1.17549e-38, max = 3.40282e+38
for n = 1000000
sample min = 8.14884e+31, max = 3.40281e+38
expected actual
mean 1.701407e+38 1.700724e+38
variance 9.649275e+75 9.645774e+75
skew 0.000000e+00 7.401975e-04
kurtosis -1.200000e+00 -1.199432e+00
Everything is looking pretty good to me.
The biggest point you are missing is that you are not generating numbers between (-max_value,max_value) , but between ( 0 ,max_value).
There are about pow(10,32) numbers between 0 and 8.14884e+31, but there are about pow(10,37) numbers between 8.14884e+31 and 3.40281e+38. Hence the result is obvious.
I'm trying to get some old C++ code up and running. I've gotten it to compile without error, but it immediately segfaults when I run, without entering main. When I use gdb to find out where things are going wrong, I find the following:
(gdb) run
Starting program: /Users/dreens/Documents/OH/extrabuncher2/ParaOHSB
Reading symbols for shared libraries +++. done
Program received signal EXC_BAD_ACCESS, Could not access memory.
Reason: KERN_INVALID_ADDRESS at address: 0x00007fff5636581c
0x000000010000151e in main (argc=1, argv=0x100000ad0) at ParaMainOHSlowerBuncher.cc:13
13 int main(int argc, char *argv[]){
(gdb) backtrace
#0 0x000000010000151e in main (argc=1, argv=0x100000ad0) at ParaMainOHSlowerBuncher.cc:13
(gdb)
Does anyone know what could cause a memory access issue right at the start of the main method?
The code is rather large, but here is the file containing the main method. Could the included .hh and .cc files be a part of the problem? Should I attach them?
Thanks!
David
#include <iostream>
#include <stdlib.h>
#include <math.h>
#include <time.h>
#include "MoleculeEnsemble.hh"
#include "SlowerForceLoadOH32.cc"
#include "SlowerForceLoadOH12.cc"
//#include "SlowerForceLoad3mmBuncher.cc"
#include "SlowerForceLoad4mmBuncher.cc"
using namespace std;
int main(int argc, char *argv[]){
//int main(){
cout << "Ahhhh!" << endl;
/******Parallel Crap********/
/*
int totalnodes = 0;
int mynode = 0;
MPI_Status status;
MPI_Init(&argv,&argc);
MPI_Comm_size(MPI_COMM_WORLD,&totalnodes);
MPI_Comm_rank(MPI_COMM_WORLD,&mynode);
srand(time(NULL)*mynode);
*/
/******Distribution Parameters *******/
long MoleculeNumber = long(5e4);
double Xcenter = 0;
double Ycenter = 0;
double Zcenter = 0;
double DeltaX = 0.0015;
double DeltaY = 0.0015;
double DeltaZ = 0.01;
int FlatX = 1;
int FlatY = 1;
int FlatZ = 1;
double vXcenter = 0;
double vYcenter = 0;
double vZcenter = 406;
double Vcalc = 406;
double vZfinal = 0;
double DeltavX = 2;
double DeltavY = DeltavX;
double DeltavZ = 40;
int FlatvX = 0;
int FlatvY = 0;
int FlatvZ = 0;
int TimeArrayOnly = 0; //Outputs only Time Array
double TimeOffset = 0; //Adds valve-skimmer flight time to ToF array
/*******Overtone Parameters********/
int S = 1; //parameter S=Vz/Vswitch as defined by VDM et al.
int JILAOT = 0; //JILAOT is either 0 or 1, denoting whether or not to use special switching
/*******Hexapole Parameters********/
double VSD = 0.06;
double Voltage = 2000;
double HexRadius = .00268;
double HexStart = .0238;
double HexEnd = .083170;//0.089103;
double HexOn = 1e-6;
double HexOff = 203e-6;//224e-6; 212 for current data; Good = 243e-6 for 408m/s
double DeltaT = 1e-6;
double DeltaTSeqGen = 1e-9; //Need to use smaller time steps for finding the time sequence
double DetectionTime = HexOff; //Use to fake out hex code
double TriggerLatency = 0;//170e-9;
/*******Detection Parameters*******/
double DetectionPosition = double(0.9319);//0.257480; <- for viewing at 31.5 ||||| 0.9428; <-Mag trap(4stages), .9319 <-MagTrap(3Stages)
double IrisWidth = 0.008;//31.5 0.0023 //PostSlower.015;
double LaserRadius = .001;
/*****Bunching Paramaters******/
int BunchNumber = 0;
int NumberUsed = 0;
/*****Timing Variables*********/
time_t start, finish;
time( &start);
/*****Molecule Parameters******/
double mass =double(17*1.672e-27);
/******ToF Detection Arrays and Slowing Parameters *********/
double Phi = double(34.2);
double PhiEB = double(0);
int NumberOfStages = int(142/S); //Use 142 for Big machine
int EBStages = 3; //Larger Add-on stages at end of slower
double BuncherScale = 1;
double Time[int(1e7)];
int ToFSignal32[int(1e7)];
int ToFSignal12[int(1e7)];
double TimeArray[800];
double VExit[800];
double Average32[7];
double Average12[7];
int LOST[200];
/*************Finished ToF Detection Arrays and Slowing Parameters ********/
/******Force Arrays********/
int Xnumber = 111;
int Ynumber = 21;
int Znumber = 21;
int FLength = Xnumber*Ynumber*Znumber;
double AXxDT[FLength];
double AYxDT[FLength];
double AZxDT[FLength];
double AZxDTSeqGen[FLength];
SlowerForceLoadOH32(AZxDT, AYxDT, AXxDT); //Note how Z and X are placed in this function. My matlab code calls the longitudnal dimension X, here it is Z
double DTovermass = DeltaT/mass;
for(int j = 0; j <FLength; j++){
AXxDT[j] = DTovermass*AXxDT[j];
AYxDT[j] = DTovermass*AYxDT[j];
AZxDT[j] = DTovermass*AZxDT[j];
AZxDTSeqGen[j] = DeltaTSeqGen*AZxDT[j]/DeltaT;
}
double AXxDT12[FLength];
double AYxDT12[FLength];
double AZxDT12[FLength];
SlowerForceLoadOH12(AZxDT12, AYxDT12, AXxDT12); //Note how Z and X are placed in this function. My matlab code calls the longitudnal dimension X, here it is Z
for(int j = 0; j <FLength; j++){
AXxDT12[j] = DTovermass*AXxDT12[j];
AYxDT12[j] = DTovermass*AYxDT12[j];
AZxDT12[j] = DTovermass*AZxDT12[j];
}
/********Load Extra Buncher Forces*********/
int XnumberEB = 251;
int YnumberEB = 41;
int ZnumberEB = 41;
int FLengthEB = XnumberEB*YnumberEB*ZnumberEB;
double AXxDTEB[FLengthEB], AYxDTEB[FLengthEB], AZxDTEB[FLengthEB], AZxDTSeqGenEB[FLengthEB];
SlowerForceLoad4mmBuncher(AZxDTEB, AYxDTEB, AXxDTEB);
for(int j = 0; j <FLengthEB; j++)
{
AXxDTEB[j] = DTovermass*AXxDTEB[j]/BuncherScale;
AYxDTEB[j] = DTovermass*AYxDTEB[j]/BuncherScale;
AZxDTEB[j] = DTovermass*AZxDTEB[j]/BuncherScale;
AZxDTSeqGenEB[j] = DeltaTSeqGen*AZxDTEB[j]/(DeltaT*BuncherScale);
}
/********* End All initiliazation ***************************/
/************Beginning Calculation *************************/
//Create Molecule Ensemble
MoleculeEnsemble Alice(MoleculeNumber,Xcenter,Ycenter,Zcenter,DeltaX,DeltaY,DeltaZ,FlatX,FlatY,FlatZ,vXcenter,vYcenter,vZcenter,DeltavX,DeltavY,DeltavZ,FlatvX,FlatvY,FlatvZ);
//MoleculeEnsemble Bob(MoleculeNumber,Xcenter,Ycenter,Zcenter,DeltaX,DeltaY,DeltaZ,FlatX,FlatY,FlatZ,vXcenter,vYcenter,vZcenter,DeltavX,DeltavY,DeltavZ,FlatvX,FlatvY,FlatvZ);
//Generate the Timing Sequence
Alice.TimeArrayGeneratorWithBuncher(Vcalc,Phi,PhiEB,TimeArray,VExit,AZxDTSeqGen,AZxDTSeqGenEB,HexOff,DeltaTSeqGen,BunchNumber,vZfinal,NumberUsed,NumberOfStages,S,EBStages);
/*if(mynode == 0){
cout << "Slowing utilized " << NumberUsed << " stages, yielding a final velocity of " << VExit[NumberUsed] << " m/s." << endl;
cout << endl;
for(int kk = 0; kk < NumberOfStages; kk++){cout << kk << " , " << TimeArray[kk] << " , " << VExit[kk] << endl;}
}*/
/*Alice.MoleculeEnsemble_Averager(Average32);
Bob.MoleculeEnsemble_Averager(Average12);
cout << "Processor: " << mynode << "\t" << sqrt(pow(Average32[3],2)+pow(Average32[4],2)) << ", " << sqrt(pow(Average12[3],2)+pow(Average12[4],2));
cout << " Mean = " << Average32[6] << ", " << Average12[6] << endl << endl << endl;
*/
if(TimeArrayOnly!=1)
{
//Fly the Ensemble through the hexapole
Alice.HexapoleFlightOH(Voltage, HexRadius, HexStart, HexEnd, HexOn, HexOff, DeltaT, double(3/2), DetectionTime);
//Bob.HexapoleFlightOH(Voltage, HexRadius, HexStart, HexEnd, HexOn, HexOff, DeltaT, double(1/2), DetectionTime);
/*
Alice.MoleculeEnsemble_Averager(Average32);
Bob.MoleculeEnsemble_Averager(Average12);
cout << "Processor: " << mynode << "\t" << sqrt(pow(Average32[3],2)+pow(Average32[4],2)) << ", " << sqrt(pow(Average12[3],2)+pow(Average12[4],2));
cout << " Mean = " << Average32[6] << ", " << Average12[6] << endl << endl << endl;
*/
//Fly the Ensemble through the slower
Alice.SlowerFlight(LOST, Time, ToFSignal32, Phi, TimeArray, DeltaT, AXxDT, AYxDT, AZxDT, AXxDTEB, AYxDTEB, AZxDTEB, Xnumber, Ynumber, Znumber, DetectionPosition, IrisWidth, LaserRadius, NumberOfStages, EBStages,S, TriggerLatency);
//Bob.SlowerFlight(LOST, Time, ToFSignal12, Phi, TimeArray, DeltaT, AXxDT12, AYxDT12, AZxDT12, Xnumber, Ynumber, Znumber, DetectionPosition, IrisWidth, LaserRadius, NumberOfStages, EBStages, S, TriggerLatency);
}
/**********Ending Calculation **********************/
//Alice.MoleculeEnsemble_Drawer();
/*
Alice.MoleculeEnsemble_Averager(Average32);
Bob.MoleculeEnsemble_Averager(Average12);
cout << "Processor: " << mynode << "\t" << sqrt(pow(Average32[3],2)+pow(Average32[4],2)) << ", " << sqrt(pow(Average12[3],2)+pow(Average12[4],2));
cout << " Mean = " << Average32[6] << ", " << Average12[6] << endl << endl;
*/
//Output ToF signal
if(TimeArrayOnly!=1)
{
for(int ii = 0; ii < int(1e7); ii++)
{
if(ToFSignal32[ii] > 0 && Time[ii] > 3e-3)
{
cout << Time[ii]+TimeOffset << "," << ToFSignal32[ii] << endl;
//+double(VSD/vZcenter)+38e-6 << "," << ToFSignal32[ii] << endl;
}
if(ToFSignal12[ii] > 0 && Time[ii] > 3e-3)
{
cout << Time[ii]+TimeOffset << "," << ToFSignal12[ii] << endl;
//+double(VSD/vZcenter)+38e-6 << "," << ToFSignal12[ii] << endl;
}
}
}
if(TimeArrayOnly==1)
{
for(int ii = 0; ii < NumberOfStages+EBStages+1; ii++)
{
cout << ii << "\t" << TimeArray[ii] << "\t" << VExit[ii] << endl;
//+double(VSD/vZcenter)+double(265e-6) << "\t" << VExit[ii] << endl;
}
}
/*for(int ii = 0; ii < NumberOfStages; ii++)
{
cout << ii << "\t" << LOST[ii] << endl;
}
*/
/*
MPI_Finalize();
*/
}
You're out of stack space.
You declare very large arrays in your code (over 10 million elements), which are all allocated on the stack. Instead of declaring the arrays statically, use dynamic memory allocation. So, instead of
double Time[int(1e7)];
write
double* Time;
Time = new double[int(1e7)];
and hope to have enough RAM in your computer :)