// finds oscillation points in p0, p1 or p2 and p3 and returns status if oscillating points are found (1) or not (0)
int osc_points(double *p0, double *p1, double *p2, double *p3)
{
int i = 0, oscillate = 0;
double d1, d2;
void *tp;
g_w(1, p0, p1); // get n+1 th generation
//display_p(p0); display_p(p1);
while(oscillate !=1 && i<2000){ // restrict generations in case of no oscillation
g_w(1, p1, p2); // n+2 th generation
g_w(1, p2, p3); // n+3 th generation
// check if oscillation is reached
d1 = dist_p1p2(p0, p2); // distance between nth and n+2th generation
d2 = dist_p1p2(p1, p3); // distance between n+1th and n+3th generation
if(d1 < ERR && d2 < ERR){ // if oscillation is reached; ERR = error in distance to be considered equal
//display_p(p2); display_p(p3);
oscillate = 1;
}
else{ // move 2 gens forward
tp = p0; p0 = p2; p2 = tp;
tp = p1; p1 = p3; p3 = tp; i++; i++;
}
}
if(!oscillate){
printf("\n No oscillation after 2000 generations \n");
return 0;
}
return 1;
}
static mode_t g_rwx(void) { return (g_r() | g_w() | g_x()); }
int main(int argc, char** argv)
{
if(argc^7){
printf("Usage: ./osil bits seed N G Mu Chi\n");
exit(1);
}
if ((sizeof(int) < 4)|| (sizeof(long int) < 8)){
printf("Assumptions concerning bits are invalid: int has %d bits, unsigned long int has %d bits\n",
(int)(8*sizeof(int)), (int)(8*sizeof(unsigned long)));
return 1;
}
L = atol(argv[1]); // bit length
if (L > 32){
printf("Can't have more thqan 32 bits\n");
return 1;
}
int seed = atoi(argv[2]);
N = (unsigned long)atoi(argv[3]); // no. of individuals in finite population
G = (unsigned long)atol(argv[4]); // no. of generations
Mu_n = atof(argv[5]);
Chi_n = atof(argv[6]);
int i,j, n, m;
double *d1, *d2, dst1, dst2;
unsigned long *tmp_ptr;
char fname[200]; // file name
FILE *fp; // data file pointer
d1 = calloc(G, sizeof(double));
d2 = calloc(G, sizeof(double));
initrand(seed);
setup();
init(); // initializes memory for pop, M and Cr and also installs values for these
merge_sort(Pop[0], N);
// infinite population simulation
calc_px_from_finite_population(P0); // calculates haploids proportion using finite set
P1 = g_w(G, P0, P1);
display_p(P1);
// find oscillating points for infinite population
if( osc_points(P0, P1, P2, P3) ){ // if oscillation occurs
{ // compute distance between finite population to oscillating points
int a, b;
//finite population simulation
for(i = 0; i < G; i++){ // evolve through G generations
for(j = 0; j < N; j++){ // reproduce N offsprings
a = rnd(N); b = rnd(N);
reproduce(a, b, j); // randomly two parents chosen; will be proportional to proportion
}
merge_sort(Pop[0], N);
// calculate distance to oscillating points and write to file
dst1 = dist_n(P2); // distance to 1st oscillating point
dst2 = dist_n(P3); // distance to 2nd oscillating point
d1[i] = dst1;
d2[i] = dst2;
// set new generation as parent generation for next generation
tmp_ptr = Pop[0];
Pop[0] = Pop[1];
Pop[1] = tmp_ptr;
}
}
}
deinit();
cleanup();
sprintf(fname, "b%lug%lun%lu_osc.dat", L, G, N);
if(!(fp = fopen(fname, "w"))){
printf("%s could not be opened!! Error!!\n", fname);
exit(2);
}
// write distances to file
for(n = 0; n < G; n++){
fprintf(fp, "%d ", n);
fprintf(fp, "%" PREC "lf %" PREC "lf\n", d1[n], d2[n]);
}
fclose(fp);
free(d1); free(d2);
FILE *gp = popen ("gnuplot -persistent", "w"); // open gnuplot in persistent mode
plot(gp, 0, fname, 3, "oscillation", "G", "d", 0, "" );
fflush(gp);
pclose(gp);
return 0;
}
/*!
* discretizes 3d nonlinear anisotropic diffusion
* by finite volume method using a 27-point stencil
*/
int
FV_3d27::
discretize(DataCube &dc)
{
int code; // errorcode
int e,i,j,k,ewc,evc; // loop variables
NeuraDataType insert_diff; // help variable
NeuraDataType diff_x, diff_y, diff_z; // help variables
int n = a->Length(1);//=dc.GetSize()[1];
int m = a->Length(2);//=dc.GetSize()[2];
int l = a->Length(3);//=dc.GetSize()[3];
int number_of_elements = (n-1)*(m-1)*(l-1);
int number_of_nodes = n*m*l;
// eigenvalues and eigenvectors of inertian tensor
// within current integration point
Vector<NeuraDataType> ew(3);
Vector<NeuraDataType> ev(9);
Vector<NeuraDataType> tmp(3); // help vector
Vector<NeuraDataType> t(3); // coefficients of anisotropy
NeuraDataType cl, cp, ci; // characteristic structure coefficients
NeuraDataType sum_ew; // sum over eigenvalues of inertian tensor
NeuraDataType swap; // help variable
a->SetZero();
// prepare moment calculation
// for to use fastest method
if ( gt == CUBE ){
int warn = 0;
if ( integration_size_x % 2 == 1 ){ integration_size_x ++; warn = 1;}
if ( integration_size_y % 2 == 1 ){ integration_size_y ++; warn = 1;}
if ( integration_size_z % 2 == 1 ){ integration_size_z ++; warn = 1;}
if ( warn ) cout << "Warning: You should use even integration sizes in all directions at CUBE integration! Given values were adapted." << endl;
}
Volume vol(gt, 3, integration_size_x, integration_size_y, integration_size_z );
Moments mom(&dc);
Vector<NeuraDataType> *vals;
Vector<NeuraDataType> *vects;
time_t time1, time2, timediff;
// calculate moments
cout << "calculate moments..." << endl;
time1 = time(NULL);
if (
( integration_size_x > n ) ||
( integration_size_y > m ) ||
( integration_size_z > l )
)
{
return INTEGRATION_DOMAIN_TOO_BIG;
}
switch ( gt )
{
case CUBE: // fast moments calculation and elementwise kindOfMoments
kind_of_moments = ELEMENTWISE;
vals = new ( Vector<NeuraDataType>[number_of_elements])(3);
vects = new (Vector<NeuraDataType>[number_of_elements])(9);
code = mom.elemwise_fast2_all_inertian_values(vals,vects,vol);
if ( code ) return code;
break;
case BALL: // fourier moments calculation and nodewise kindOfMoments
kind_of_moments = NODEWISE;
vals = new ( Vector<NeuraDataType>[number_of_nodes])(3);
vects = new (Vector<NeuraDataType>[number_of_nodes])(9);
code = mom.fourier_all_inertian_values(vals,vects,vol,n,m,l);
code = mom.all_inertian_values(vals,vects,vol);
if ( code ) return code;
break;
default:
return UNKNOWN_GEOMETRY_TYPE;
}
if ( code ) return code;
time2 = time(NULL);
cout << "...moments calculated" << endl;
timediff = time2-time1;
cout << "calculation of moments took " << timediff << " seconds" << endl;
// discretise
for ( e = 0; e < number_of_elements; e++ ) // elements
{
elements_nodes(e,n,m,en);
for ( i = 0; i < 8; i++ ) // nodes
{
// determine moments
switch ( kind_of_moments )
{
case ELEMENTWISE:
// eigenvalues
for ( ewc = 1; ewc <= 3; ewc++ )
ew[ewc] = vals[e][ewc];
// eigenvectors
for ( evc = 1; evc <= 9; evc++ )
ev[evc] = vects[e][evc];
break;
case NODEWISE:
// eigenvalues
for ( ewc = 1; ewc <= 3; ewc++ )
ew[ewc] = vals[en[i]-1][ewc];
// eigenvectors
for ( evc = 1; evc <= 9; evc++ )
ev[evc] = vects[en[i]-1][evc];
break;
default:
cout << "FV_3d27::RunTimeError: Unknown kindOfMoments! \n Abort " << endl;
exit(1);
}
k = 0;
while ( ( ip[i][k][0] != -1 ) && ( k < 2 ) ) // ips
{
for ( j = 0; j < 8; j++ ) // ansatzfunctions
{
diff_x = grad_phi_x(j,ip[i][k][0],ip[i][k][1],ip[i][k][2]);
diff_y = grad_phi_y(j,ip[i][k][0],ip[i][k][1],ip[i][k][2]);
diff_z = grad_phi_z(j,ip[i][k][0],ip[i][k][1],ip[i][k][2]);
// sort eigenvalues
if ( ew[1] < ew[2] ){
swap = ew[1]; ew[1] = ew[2]; ew[2] = swap;
swap = ev[1]; ev[1] = ev[4]; ev[4] = swap;
swap = ev[2]; ev[2] = ev[5]; ev[5] = swap;
swap = ev[3]; ev[3] = ev[6]; ev[6] = swap;
}
if ( ew[1] < ew[3] ){
swap = ew[1]; ew[1] = ew[3]; ew[3] = swap;
swap = ev[1]; ev[1] = ev[7]; ev[7] = swap;
swap = ev[2]; ev[2] = ev[8]; ev[8] = swap;
swap = ev[3]; ev[3] = ev[9]; ev[9] = swap;
}
if ( ew[2] < ew[3] ){
swap = ew[2]; ew[2] = ew[3]; ew[3] = swap;
swap = ev[4]; ev[4] = ev[7]; ev[7] = swap;
swap = ev[5]; ev[5] = ev[8]; ev[8] = swap;
swap = ev[6]; ev[6] = ev[9]; ev[9] = swap;
}
// determine coefficients of anisotropy
if ( fixed_coeffs )
{
t[1] = anicoeff1;
t[2] = anicoeff2;
t[3] = anicoeff3;
}
else
{
sum_ew = ew[1]+ew[2]+ew[3];
if ( fabs(sum_ew) <= 0.000001 )
{ cl = 0; cp = 0; ci = 1; }
else {
cl = (ew[1]-ew[2])/sum_ew;
cp = 2*(ew[2]-ew[3])/sum_ew;
ci = 3*ew[3]/sum_ew;
}
t[1] = 1.0;
switch (dependence_type)
{
case PERONA_MALIK:
t[2] = g_pm(cl);
t[3] = g_pm(1-ci);
break;
case WEIKERT:
t[2] = g_w(cl);
t[3] = g_w(1-ci);
break;
case BLACK_SAPIRO:
t[2] = g_bs(cl);
t[3] = g_bs(1-ci);
break;
default:
cout << "Unknown nonlinear function specified!\n Abort" << endl;
exit(1);
}
}
// multiplication with the anisotropy tensor
tmp[1] = ev[1]*diff_x + ev[2]*diff_y + ev[3]*diff_z;
tmp[2] = ev[4]*diff_x + ev[5]*diff_y + ev[6]*diff_z;
tmp[3] = ev[7]*diff_x + ev[8]*diff_y + ev[9]*diff_z;
tmp[1] *= t[1]; tmp[2] *= t[2]; tmp[3] *= t[3];
diff_x = ev[1]*tmp[1] + ev[4]*tmp[2] + ev[7]*tmp[3];
diff_y = ev[2]*tmp[1] + ev[5]*tmp[2] + ev[8]*tmp[3];
diff_z = ev[3]*tmp[1] + ev[6]*tmp[2] + ev[9]*tmp[3];
// multiplication with normal
insert_diff = diff_x * nip[i][k][0] +
diff_y * nip[i][k][1] +
diff_z * nip[i][k][2];
insert_diff *= 0.25; // surface of subcontrolvolume
a->Add(en[i], en[j], insert_diff);
a->Add( en[intact[i][k]], en[j], -insert_diff);
}//for j
k++;
}// while
}// for i
}// for e
delete [] vals;
delete [] vects;
// treatment of boundary
int position;
// lower and upper boundary
for ( i = 0; i < n; i++ )
{
for ( j = 0; j < m; j++ )
{
k = 0;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
k = l-1;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
}
}
//left and right boundary
for ( j = 0; j < m; j++ )
{
for ( k = 0; k < l; k++ )
{
i = 0;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
i = n-1;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
}
}
// front and back boundary
for ( i = 0; i < n; i++ )
{
for ( k = 0; k < l; k++ )
{
j = 0;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
j = m-1;
position = 1 + i + j*n + k*n*m;
a->MultiplyRow(position,2);
}
}
return OK;
}