int main()
{
char t;
double a,b,c;
double root1,root2;
while(1)
{
cout<<"input q to quit, any other char to continue \n";
cin>>t;
if(t=='q')
break;
cout<<"input the coefficients a b c of the form ax^2+bx+c\n";
cin>>a>>b>>c;
double discriminant=compute_discriminant(a,b,c);
if(a==0&&b!=0)
{
linear_equation(b,c,root1);
cout<<"this is a linear equation with the root= "<<root1<<endl;
cout<<"the computational error is "<<compute_error(a,b,c,root1)<<endl;
}
if(a==0&&b==0)
{
cout<<"this equation has no real roots\n";
}
if(discriminant==0&&(a||b!=0))
{
double_real_root(a,b,c,root1);
cout<<"this is an equation with a double real root= "<<root1<<endl;
cout<<"the computational error is "<<compute_error(a,b,c,root1)<<endl;
}
if(discriminant>0&&a!=0)
{
two_real_roots(a,b,c,discriminant,root1,root2);
cout<<"this equation has two real roots = "<<root1<<" and "<<root2<<endl;
cout<<"the computational error for root 1 is "<<compute_error(a,b,c,root1)<<endl;
cout<<"the computational error for root 2 is "<<compute_error(a,b,c,root2)<<endl;
}
if(discriminant<0)
{
complex<double> com_root1;
complex<double> com_root2;
no_real_roots(a,b,c,discriminant,com_root1,com_root2);
cout<<"this equation has two imaginary roots = "<<com_root1<<" and "<<com_root2<<endl;
}
}
keep_window_open();
return 0;
}
void Test_lin_elem_exp_derivative(CuTest * tc){
printf("Testing function: lin_elem_exp_deriv on (a,b)\n");
struct Fwrap * fw = fwrap_create(1,"general-vec");
fwrap_set_fvec(fw,Sin3xTx2,NULL);
double lb = -2.0,ub = -1.0;
double delta = 1e-4, hmin = 1e-3;
struct LinElemExpAopts * opts = NULL;
opts = lin_elem_exp_aopts_alloc_adapt(0,NULL,lb,ub,delta,hmin);
le_t f1 = lin_elem_exp_approx(opts,fw);
le_t der = lin_elem_exp_deriv(f1);
// error
double abs_err;
double func_norm;
compute_error(lb,ub,1000,der,funcderiv,NULL,&abs_err,&func_norm);
double err = abs_err / func_norm;
CuAssertDblEquals(tc, 0.0, err, 1e-5);
LINELEM_FREE(f1);
LINELEM_FREE(der);
lin_elem_exp_aopts_free(opts);
fwrap_destroy(fw);
}
void ofxIcp::icp_step(const vector<cv::Point3d> & current, const vector<cv::Point3d> & target, vector<cv::Point3d> & output, cv::Mat & rotation, cv::Mat & translation, double & error){
vector<cv::Point3d> closest_current;
vector<cv::Point3d> closest_target;
find_closest_points(closest_points_count, current, target, closest_current, closest_target);
cv::Mat centroid_current;
cv::Mat centroid_target;
cv::reduce(cv::Mat(closest_current, false), centroid_current, 0, CV_REDUCE_AVG);
cv::reduce(cv::Mat(closest_target, false), centroid_target, 0, CV_REDUCE_AVG);
centroid_current = centroid_current.reshape(1);
centroid_target = centroid_target.reshape(1);
compute_rigid_transformation(closest_current, centroid_current, closest_target, centroid_target, rotation, translation);
vector<cv::Point3d> transformed_closest_current;
vector<cv::Point3d> transformed_current;
transform(closest_current, rotation, translation, transformed_closest_current);
transform(current, rotation, translation, transformed_current);
compute_error(transformed_closest_current, closest_target, error);
output = transformed_current;
}
void MainWindow::on_pushButton_3_clicked()
{
//Learning
//Target Input & Ouput Selection
QString test;
for(int k=0;k<n_training;k++)
{
for(int i=n_history;i>0;i--)
{
learning_rate=0.01;
setTarget(i,i-1);
forward();
backward();
}
}
long long error_rate = compute_error();
QString moneytext;
moneytext= QString("Amount Money : %1").arg(error_rate);
debug(moneytext);
}
void Test_pw_derivative(CuTest * tc){
printf("Testing function: piecewise_poly_deriv on (a,b)\n");
// function
struct Fwrap * fw = fwrap_create(1,"general-vec");
fwrap_set_fvec(fw,Sin3xTx2,NULL);
// approximation
double lb = -2.0, ub = -1.0;
struct PwPolyOpts * opts = pw_poly_opts_alloc(LEGENDRE,lb,ub);
opoly_t cpoly = piecewise_poly_approx1_adapt(opts,fw);
opoly_t der = piecewise_poly_deriv(cpoly);
// error
double abs_err;
double func_norm;
compute_error(lb,ub,1000,der,funcderiv,NULL,&abs_err,&func_norm);
double err = abs_err / func_norm;
CuAssertDblEquals(tc, 0.0, err, 1e-13);
POLY_FREE(cpoly);
POLY_FREE(der);
pw_poly_opts_free(opts);
fwrap_destroy(fw);
}
void rarray_compare(fftw_real *A, fftw_real *B, int n)
{
double d = compute_error(A, 1, B, 1, n);
if (d > TOLERANCE) {
fflush(stdout);
fprintf(stderr, "Found relative error %e\n", d);
fftw_die("failure in Ergun's verification procedure\n");
}
}
void Gauss_siedel(double *P, double *fn, double *a_x, double *a_y) {
long i, j, indx, indx_rght, indx_frnt, indx_lft, indx_bck, indx_ax, indx_ay;
double P_old;
double error;
double tol=1.0e-6;
int iter = 0;
for(;;) {
boundary_pressure();
for(i=1; i < pmesh-1; i++) {
for(j=1;j < pmesh-1;j++) {
indx = i*pmesh + j;
indx_rght = indx + 1;
indx_frnt = indx + pmesh;
indx_lft = indx - 1;
indx_bck = indx - pmesh;
indx_ax = (i-1)*(pmesh-1) +(j-1);
indx_ay = (i-1)*(pmesh-2) +(j-1);
if (((i+j)%2) == 0) {
//P[indx] =-1.0*(P[indx_lft] + P[indx_rght]
//+ P[indx_bck] + P[indx_frnt]) + deltax*deltax*fn[indx];
P[indx] = -1.0*(a_x[indx_ax]*P[indx_lft] + a_x[indx_ax+1]*P[indx_rght]
+ a_y[indx_ay]*P[indx_bck] + a_y[indx_ay+(pmesh-2)]*P[indx_frnt]) + deltax*deltax*fn[indx];
P[indx] /= -1.0*(a_x[indx_ax+1]+a_x[indx_ax]+a_y[indx_ay+(pmesh-2)]+a_y[indx_ay]);
}
}
}
for(i=1; i < pmesh-1; i++) {
for(j=1;j < pmesh-1;j++) {
indx = i*pmesh + j;
indx_rght = indx + 1;
indx_frnt = indx + pmesh;
indx_lft = indx - 1;
indx_bck = indx - pmesh;
indx_ax = (i-1)*(pmesh-1) + (j-1);
indx_ay = (i-1)*(pmesh-2) + (j-1);
if (((i+j)%2) != 0) {
//P[indx] =-1.0*(P[indx_lft] + P[indx_rght]
//+ P[indx_bck] + P[indx_frnt]) + deltax*deltax*fn[indx];
P[indx] =-1.0*(a_x[indx_ax]*P[indx_lft] + a_x[indx_ax+1]*P[indx_rght]
+ a_y[indx_ay]*P[indx_bck] + a_y[indx_ay+(pmesh-2)]*P[indx_frnt]) + deltax*deltax*fn[indx];
P[indx] /= -1.0*(a_x[indx_ax]+a_x[indx_ax+1]+a_y[indx_ay]+a_y[indx_ay+(pmesh-2)]);
}
}
}
iter++;
error = compute_error(a_x,a_y,P, fn);
printf("iter=%d\terror=%lf\n",iter,error);
if (fabs(error) < tol) {
break;
}
}
}
void processSpecialKeys(int key, int x, int y) {
/*
if (key == GLUT_KEY_F1) {
log_comp_designTriStrip_read(xs, ys);
vector_field_data->add_sketch(xs, ys);
}
else if (key == GLUT_KEY_F2) {
}
else if (key == GLUT_KEY_F3) {
}
else if (key == GLUT_KEY_F4) {
//save sketches
sketching_datas[current_sketch_data_idx].xsss.push_back(
sketching_datas[current_sketch_data_idx].xss);
sketching_datas[current_sketch_data_idx].ysss.push_back(
sketching_datas[current_sketch_data_idx].yss);
sketching_datas[current_sketch_data_idx].xss.clear();
sketching_datas[current_sketch_data_idx].yss.clear(); // xs.clear(); ys.clear();
vector_field_data->clear();
// vector_field_data->updated_vector_field();
}
else if (key == GLUT_KEY_F5) {
vector_field_data->add_sketch(xs, ys);
sketching_datas[current_sketch_data_idx].xss.push_back(xs);
sketching_datas[current_sketch_data_idx].yss.push_back(ys);
}*/
if (key == GLUT_KEY_F8) {
vector_field_data->interpolate();
void compute_error(VectorFieldDesignData<float> *vField);
compute_error(vector_field_data);
}
if (key == GLUT_KEY_F9) {
vector_field_data->show_design = !vector_field_data->show_design;
}
else if (key == GLUT_KEY_F10) {
vector_field_data->clone_push();
}
else if (key == GLUT_KEY_F11) {
selecting = !selecting;
vector_field_data->show_analysis(!selecting);
}
else if (key == GLUT_KEY_F12) {
vector_field_data->show_mesh = !vector_field_data->show_mesh;
}
else if (key == GLUT_KEY_F7) {
}
update();
}
static double acmp(COMPLEX *A, COMPLEX *B, int n) {
double tol = TOLERANCE;
double d = compute_error(A, B, n);
#ifdef EXIT_ON_FAIL
if (d > tol) {
printf("\n\nfailure in Ergun's verification procedure. Error: %e\n\n", d);
exit(1);
}
#endif
return d;
}
void ofxIcp::compute_transformation(const vector<cv::Point3d> & input, const vector<cv::Point3d> & target, cv::Mat & transformation){
vector<cv::Point3d> transformed;
cv::Mat rotation, translation;
double error;
vector<cv::Point3d> closest_current;
vector<cv::Point3d> closest_target;
int increment = input.size()/5;
for(int i = 0; i < input.size(); i += increment){
closest_current.push_back(input[i]);
closest_target.push_back(target[i]);
}
cv::Mat centroid_current;
cv::Mat centroid_target;
cv::reduce(cv::Mat(closest_current, false), centroid_current, 0, CV_REDUCE_AVG);
cv::reduce(cv::Mat(closest_target, false), centroid_target, 0, CV_REDUCE_AVG);
centroid_current = centroid_current.reshape(1);
centroid_target = centroid_target.reshape(1);
compute_rigid_transformation(closest_current, centroid_current, closest_target, centroid_target, rotation, translation);
vector<cv::Point3d> transformed_closest_current;
vector<cv::Point3d> transformed_current;
transform(closest_current, rotation, translation, transformed_closest_current);
compute_error(transformed_closest_current, closest_target, error);
transformation = (cv::Mat_<double>(4,4) << 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1);
cv::Mat rotation_tmp = transformation.colRange(0,3).rowRange(0,3);
cv::Mat translation_tmp = transformation.colRange(3,4).rowRange(0,3);
cv::Mat translation_t = translation.reshape(1).t();
rotation.copyTo(rotation_tmp);
translation_t.copyTo(translation_tmp);
}
template <typename PointSource, typename PointTarget, typename FeatureT> float
pcl::SampleConsensusInitialAlignment<PointSource, PointTarget, FeatureT>::computeErrorMetric (
const PointCloudSource &cloud, float)
{
std::vector<int> nn_index (1);
std::vector<float> nn_distance (1);
const ErrorFunctor & compute_error = *error_functor_;
float error = 0;
for (int i = 0; i < static_cast<int> (cloud.points.size ()); ++i)
{
// Find the distance between cloud.points[i] and its nearest neighbor in the target point cloud
tree_->nearestKSearch (cloud, i, 1, nn_index, nn_distance);
// Compute the error
error += compute_error (nn_distance[0]);
}
return (error);
}
void Test_pw_linear(CuTest * tc){
printf("Testing functions: piecewise_poly_linear \n");
double lb = -2.0;
double ub = 0.7;
struct PwPolyOpts * opts = pw_poly_opts_alloc(LEGENDRE,lb,ub);
struct PiecewisePoly * pw = piecewise_poly_linear(2.0,-0.2,opts);
// compute error
double abs_err;
double func_norm;
compute_error(lb,ub,1000,pw,pw_lin,NULL,&abs_err,&func_norm);
double err = abs_err / func_norm;
CuAssertDblEquals(tc, 0.0, err, 1e-13);
POLY_FREE(pw);
pw_poly_opts_free(opts);
}
int main(int argc, char ** argv) {
MPI_Init(&argc, &argv);
int P, rank;
MPI_Comm_size(MPI_COMM_WORLD, &P);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
if (isPowerOfTwo(P) == false) {
if (rank == 0) {
printf("The number of processes is not a power of two \n");
}
MPI_Finalize();
return 1;
}
if (argc > 1) {
if (rank == 0) {
printf("No argument needed\n");
}
MPI_Finalize ();
return 1;
}
int k;
int k_max = 15, k_min = 3;
double *err_vec, *S_vec;
err_vec = calloc( k_max - k_min, sizeof(double) );
S_vec = calloc( k_max - k_min, sizeof(double) );
for ( k = k_min; k < k_max; k++ ) {
int n = (int) pow(2, k);
int np = (int) (n - n%P)/P;
double *v, S = 0.0;
MPI_Status status;
int i;
if ( rank == 0 ) {
FILE *f;
f = fopen("Error_Ex03.txt", "w");
fprintf(f, "Error Ex03, P = %d\n", P);
v = calloc(n, sizeof(double));
compute_v(n, v);
for (i = 1; i < P; i++ ){
MPI_Send( &v[np*i], np, MPI_DOUBLE, i, 0, MPI_COMM_WORLD);
}
double S_n = compute_S(np, v);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
double err = compute_error(S);
S_vec[k - k_min] = S;
err_vec[k - k_min] = err;
if (k == k_max-1) {
print_vec(k_max-k_min, S_vec, err_vec);
for ( i = 0; i < k_max-k_min; i++ ) {
fprintf(f, "%1.16f\n", err_vec[i]);
}
}
free(v);
fclose(f);
}
else {
double *v_n;
if (rank == P-1) {
v_n = calloc(np + n%P, sizeof(double));
}
else {
v_n = calloc(np, sizeof(double));
}
MPI_Recv(v_n, np, MPI_DOUBLE, 0, 0, MPI_COMM_WORLD, &status);
double S_n = compute_S(np, v_n);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
}
}
MPI_Finalize();
return 0;
}
void _calculate_parameters(double h,my_point p[],double w[],int num) {
double H,I,J,K,L,A0, A1;
double x,y,d;
if (num > MAX_POINTS_NUM) {
fprintf(stderr,"Point number is larger than previous set!\n");
return;
}
is_set_ret = false;
compute_Aj(h,w,num);
H = compute_H(p,num);
I = compute_I(p,num);
J = compute_J(p,num);
K = compute_K(p,num);
L = compute_L(p,num);
A0 = H -h*h*J*J-K+h*h*L*L;
A1 = 2*(I-h*h*J*L);
// printf("H=%.3lf I=%.3lf J=%.3lf K=%.3lf L=%.3lf A0=%.3lf A1=%.3lf\n",
// H,I,J,K,L,A0,A1);
// printf("Calculated as follows:\n");
if (0 == A0) {
if (0 == A1) { // A0 A1 are0
// x,y could be any value
#if 1
printf("The distribution of the given points is a circle.\n");
x = y = sqrt(2.0) / 2;
d = -(h*h*(J*x+L*y));
compute_error(d,x,y,p,num);
#else
#endif
}
else { // A0 is 0 A1 is not 0，x2=1/2,x2+y2=1
double ar[2] = {sqrt(2.0)/2,-sqrt(2.0)/2};// possible values of x,y
int i,j;
for (i=0;i<2;i++) {
x = ar[i];
for (j=0;j<2;j++) {
y = ar[j];
d = -(h*h*(J*x+L*y));
compute_error(d,x,y,p,num);
}
}
}
}
else if (0 == A1) {
double x_ar[4] = {0,0,1,-1};
double y_ar[4] = {1,-1,0,0};//possible values of x,y
int i;
for (i=0;i<4;i++) {
x = x_ar[i];
y = y_ar[i];
d = -(h*h*(J*x+L*y));
compute_error(d,x,y,p,num);
}
}
else { // A0!=0 A1!=0
double t = A0 / sqrt (A1*A1+A0*A0); // 0 < t < 1
double x_ar[4] = {sqrt (0.5*(1+t)),sqrt (0.5*(1-t)),
-sqrt (0.5*(1+t)),-sqrt (0.5*(1-t))}; // possible values of x , x2 ≠ 0 or 1
int i;
for (i=0;i<4;i++) {
x = x_ar[i];
y = (A1/A0)* (x - 0.5/x);
d = -(h*h*(J*x+L*y));
compute_error(d,x,y,p,num);
}
}
}
int main(int argc,const char *argv[])
{
Net *net;
Group *input,*hidden,*output,*bias;
ExampleSet *examples;
Example *ex;
Connections *c1,*c2,*c3,*c4;
char * fileName = "input";
int i,count,j;
int inputCount = 0,outputCount = 0, hiddenCount = 200;
Real error, correct;
Real epsilon,range;
/* don't buffer output */
setbuf(stdout,NULL);
/* set seed to unique number */
mikenet_set_seed(0);
/* a default learning rate */
epsilon=0.1;
/* default weight range */
range=0.5;
default_errorRadius=0.0;
/* what are the command line arguments? */
for(i=1;i<argc;i++)
{
if (strcmp(argv[i],"-seed")==0)
{
mikenet_set_seed(atol(argv[i+1]));
i++;
}
else if (strncmp(argv[i],"-epsilon",5)==0)
{
epsilon=atof(argv[i+1]);
i++;
}
else if (strcmp(argv[i],"-range")==0)
{
range=atof(argv[i+1]);
i++;
}
else if (strcmp(argv[i],"-errorRadius")==0)
{
default_errorRadius=atof(argv[i+1]);
i++;
}
else if (strcmp(argv[i], "-f") == 0)
{
fileName = (char*)argv[i+1];
i++;
}
else if (strcmp(argv[i], "-i") == 0)
{
inputCount = atoi(argv[i+1]);
i++;
}
else if (strcmp(argv[i], "-o") == 0)
{
outputCount = atoi(argv[i+1]);
i++;
}
else if (strcmp(argv[i], "-h") == 0)
{
hiddenCount = atoi(argv[i+1]);
i++;
}
else
{
fprintf(stderr,"unknown argument: %s\n",argv[i]);
exit(-1);
}
}
/* build a network, with TIME number of time ticks */
net=create_net(TIME);
/* learning rate */
default_epsilon=epsilon;
/* create our groups.
format is: name, num of units, ticks */
input=init_group("Input",inputCount,TIME);
hidden=init_group("hidden",hiddenCount,TIME);
output=init_group("Output",outputCount,TIME);
/* bias is special. format is: value, ticks */
bias=init_bias(1.0,TIME);
/* now add our groups to the network object */
bind_group_to_net(net,input);
bind_group_to_net(net,hidden);
bind_group_to_net(net,output);
bind_group_to_net(net,bias);
/* now connect our groups, instantiating */
/* connection objects c1 through c4 */
c1=connect_groups(input,hidden);
c2=connect_groups(hidden,output);
c3=connect_groups(bias,hidden);
c4=connect_groups(bias,output);
/* add connections to our network */
bind_connection_to_net(net,c1);
bind_connection_to_net(net,c2);
bind_connection_to_net(net,c3);
bind_connection_to_net(net,c4);
/* randomize the weights in the connection objects.
2nd argument is weight range. */
randomize_connections(c1,range);
randomize_connections(c2,range);
randomize_connections(c3,range);
randomize_connections(c4,range);
/* how to load and save weights */
/* load_weights(net,"init.weights"); */
/* erase old initial weight file */
/* system("rm -f init.weights.Z"); */
/* save out our weights to file 'init.weights' */
/* save_weights(net,"init.weights"); */
/* load in our example set */
fprintf(stderr, "Reading %s\n",fileName);
examples=load_examples(fileName,TIME);
fprint(stderr, "Input: %d, Output: %d",);
error=0.0;
count=0;
/* loop for ITER number of times */
for(i=0;i<ITER;i++)
{
/* get j'th example from exampleset */
ex=get_random_example(examples);
/* do forward propagation */
bptt_forward(net,ex);
/* backward pass: compute gradients */
bptt_compute_gradients(net,ex);
/* sum up error for this example */
error+=compute_error(net,ex);
/* online learning: apply the deltas
from previous call to compute_gradients */
bptt_apply_deltas(net);
/* is it time to write status? */
if (count==REP)
{
/* average error over last 'count' iterations */
error = error/(float)count;
count=0;
/* print a message about average error so far */
fprintf(stderr, "%d\t%f\n",i,error);
if (error < 0.01)
{
break;
}
/* zero error; start counting again */
error=0.0;
}
count++;
}
/* done training. write out results for each example */
correct = 0;
for(i=0;i<examples->numExamples;i++)
{
ex=&examples->examples[i];
bptt_forward(net,ex);
int maxj = -1;
Real maxx = 0;
for(j=0 ; j < outputCount; j++){
if (output->outputs[TIME-1][j] > maxx){
maxj = j;
maxx = output->outputs[TIME-1][j];
}
/* printf("%d:%f ",j,output->outputs[TIME-1][j]); */
}
/* printf("max:%d\n",maxj); */
if (get_value(ex->targets,output->index,TIME-1,maxj) == 1)
correct += 1;
printf("i:%d g:%f cor:%f\n",i, get_value(ex->targets,output->index,TIME-1,maxj),correct / (i+1));
/* printf("example %d\tinputs %f\t%f\toutput %f\ttarget %f\n", */
/* i, */
/* get_value(ex->inputs,input->index,TIME-1,0), */
/* get_value(ex->inputs,input->index,TIME-1,1), */
/* output->outputs[TIME-1][0], */
/* get_value(ex->targets,output->index,TIME-1,0)); */
}
fprintf(stderr,"Acc:%f\n", correct / examples->numExamples);
return 0;
}
void testnd_in_place(int rank, int *n, fftwnd_plan validated_plan,
int alternate_api, int specific)
{
int istride, ostride, howmany;
int N, dim, i, j, k;
int nc, nhc, nr;
fftw_real *in1, *out3;
fftw_complex *in2, *out1, *out2;
fftwnd_plan p, ip;
int flags = measure_flag | wisdom_flag | FFTW_IN_PLACE;
if (coinflip())
flags |= FFTW_THREADSAFE;
N = nc = nr = nhc = 1;
for (dim = 0; dim < rank; ++dim)
N *= n[dim];
if (rank > 0) {
nr = n[rank - 1];
nc = N / nr;
nhc = nr / 2 + 1;
}
in1 = (fftw_real *) fftw_malloc(2 * nhc * nc * MAX_STRIDE * sizeof(fftw_real));
out3 = in1;
out1 = (fftw_complex *) in1;
in2 = (fftw_complex *) fftw_malloc(N * sizeof(fftw_complex));
out2 = (fftw_complex *) fftw_malloc(N * sizeof(fftw_complex));
if (alternate_api && specific && (rank == 2 || rank == 3)) {
if (rank == 2) {
p = rfftw2d_create_plan_specific(n[0], n[1],
FFTW_REAL_TO_COMPLEX, flags,
in1, MAX_STRIDE, 0, 0);
ip = rfftw2d_create_plan_specific(n[0], n[1],
FFTW_COMPLEX_TO_REAL, flags,
in1, MAX_STRIDE, 0, 0);
} else {
p = rfftw3d_create_plan_specific(n[0], n[1], n[2],
FFTW_REAL_TO_COMPLEX, flags,
in1, MAX_STRIDE, 0, 0);
ip = rfftw3d_create_plan_specific(n[0], n[1], n[2],
FFTW_COMPLEX_TO_REAL, flags,
in1, MAX_STRIDE, 0, 0);
}
} else if (specific) {
p = rfftwnd_create_plan_specific(rank, n, FFTW_REAL_TO_COMPLEX,
flags,
in1, MAX_STRIDE, in1, MAX_STRIDE);
ip = rfftwnd_create_plan_specific(rank, n, FFTW_COMPLEX_TO_REAL,
flags,
in1, MAX_STRIDE, in1, MAX_STRIDE);
} else if (alternate_api && (rank == 2 || rank == 3)) {
if (rank == 2) {
p = rfftw2d_create_plan(n[0], n[1], FFTW_REAL_TO_COMPLEX,
flags);
ip = rfftw2d_create_plan(n[0], n[1], FFTW_COMPLEX_TO_REAL,
flags);
} else {
p = rfftw3d_create_plan(n[0], n[1], n[2], FFTW_REAL_TO_COMPLEX,
flags);
ip = rfftw3d_create_plan(n[0], n[1], n[2], FFTW_COMPLEX_TO_REAL,
flags);
}
} else {
p = rfftwnd_create_plan(rank, n, FFTW_REAL_TO_COMPLEX, flags);
ip = rfftwnd_create_plan(rank, n, FFTW_COMPLEX_TO_REAL, flags);
}
CHECK(p != NULL && ip != NULL, "can't create plan");
for (i = 0; i < nc * nhc * 2 * MAX_STRIDE; ++i)
out3[i] = 0;
for (istride = 1; istride <= MAX_STRIDE; ++istride) {
/* generate random inputs */
for (i = 0; i < nc; ++i)
for (j = 0; j < nr; ++j) {
c_re(in2[i * nr + j]) = DRAND();
c_im(in2[i * nr + j]) = 0.0;
for (k = 0; k < istride; ++k)
in1[(i * nhc * 2 + j) * istride + k]
= c_re(in2[i * nr + j]);
}
fftwnd(validated_plan, 1, in2, 1, 1, out2, 1, 1);
howmany = ostride = istride;
WHEN_VERBOSE(2, printf("\n testing in-place stride %d...",
istride));
if (howmany != 1 || istride != 1 || ostride != 1 || coinflip())
rfftwnd_real_to_complex(p, howmany, in1, istride, 1,
out1, ostride, 1);
else
rfftwnd_one_real_to_complex(p, in1, NULL);
for (i = 0; i < nc; ++i)
for (k = 0; k < howmany; ++k)
CHECK(compute_error_complex(out1 + i * nhc * ostride + k,
ostride,
out2 + i * nr, 1,
nhc) < TOLERANCE,
"in-place (r2c): wrong answer");
if (howmany != 1 || istride != 1 || ostride != 1 || coinflip())
rfftwnd_complex_to_real(ip, howmany, out1, ostride, 1,
out3, istride, 1);
else
rfftwnd_one_complex_to_real(ip, out1, NULL);
for (i = 0; i < nc * nhc * 2 * istride; ++i)
out3[i] *= 1.0 / N;
for (i = 0; i < nc; ++i)
for (k = 0; k < howmany; ++k)
CHECK(compute_error(out3 + i * nhc * 2 * istride + k,
istride,
(fftw_real *) (in2 + i * nr), 2,
nr) < TOLERANCE,
"in-place (c2r): wrong answer (check 2)");
}
rfftwnd_destroy_plan(p);
rfftwnd_destroy_plan(ip);
fftw_free(out2);
fftw_free(in2);
fftw_free(in1);
}
int main(int argc,char *argv[])
{
char cmd[255];
int hcount=0,scount=0;
float herr=0,serr=0,dice;
Example *ex;
int do_cg=0;
float epsilon;
int seed=1,first=1;
float e,e0,lr,lrPrev;
int start=1,i,j;
char loadFile[255],fn[255];
setbuf(stdout,NULL);
parallel_init(&argc,&argv);
if (myid==0)
{
announce_version();
system("hostname");
}
printf("pid %d\n",getpid());
loadFile[0]=0;
/* what are the command line arguments? */
for(i=1;i<argc;i++)
{
if (strcmp(argv[i],"-seed")==0)
{
seed=atoi(argv[i+1]);
i++;
}
else if (strcmp(argv[i],"-start")==0)
{
start=atoi(argv[i+1]);
i++;
}
else if (strncmp(argv[i],"-epsilon",5)==0)
{
epsilon=atof(argv[i+1]);
i++;
}
else if (strncmp(argv[i],"-load",5)==0)
{
strcpy(loadFile,argv[i+1]);
i++;
}
else
{
fprintf(stderr,"unknown argument: %s\n",argv[i]);
exit(1);
}
}
default_epsilon=0.05;
mikenet_set_seed(seed);
build_hearing_model(SAMPLES);
/* load in our example set */
phono_examples=load_examples("phono.pat",TICKS);
sem_examples=load_examples("sem.pat",TICKS);
hearing_examples=load_examples("ps.pat",TICKS);
speaking_examples=load_examples("sp.pat",TICKS);
phono_examples->numExamples=500;
sem_examples->numExamples=500;
hearing_examples->numExamples=500;
speaking_examples->numExamples=500;
myid=parallel_proc_id();
#ifdef DO_ONLINE_PRE_TRAIN
if (start==1)
{
for(i=1;i<=10000;i++)
{
dice = mikenet_random();
if (dice <=0.2)
{
ex=get_random_example(phono_examples);
crbp_forward(phono,ex);
crbp_compute_gradients(phono,ex);
crbp_apply_deltas(phono);
}
else if (dice <= 0.5)
{
ex=get_random_example(hearing_examples);
crbp_forward(ps,ex);
crbp_compute_gradients(ps,ex);
herr += compute_error(ps,ex);
crbp_apply_deltas(ps);
}
else if (dice <= 0.7)
{
ex=get_random_example(sem_examples);
crbp_forward(sem,ex);
crbp_compute_gradients(sem,ex);
crbp_apply_deltas(sem);
}
else
{
ex=get_random_example(speaking_examples);
crbp_forward(sp,ex);
crbp_compute_gradients(sp,ex);
serr+=compute_error(sp,ex);
crbp_apply_deltas(sp);
}
if (i % 100 == 0)
{
printf("%d hear %f speak %f\n",i,
herr/hcount,serr/scount);
herr=0.0;
serr=0.0;
hcount=0;
scount=0;
}
}
sprintf(fn,"s%d_online_weights",seed);
save_weights(hearing,fn);
}
#endif
parallel_broadcast_weights(hearing);
do_cg=1;
if (do_cg && myid==0)
printf("USING CG\n");
/* loop for ITER number of times */
for(i=1;i<5;i++)
{
parallel_sync();
store_all_weights(hearing);
e=parallel_g(ps,hearing_examples,0.8) +
parallel_g(sp,speaking_examples,0.8) +
parallel_g(sem,sem_examples,0.2) +
parallel_g(phono,phono_examples,0.2);
if(do_cg)
{
if (first)
init_cg(hearing);
else
cg(hearing);
first=0;
}
e0=e;
if (myid==0)
printf("%d e0: %f\n",i,e);
lr = 0.2/hearing_examples->numExamples;
lrPrev=lr/10;
for(j=1;j<10;j++)
{
e=sample(lr);
if (myid==0)
printf("\t\t%d %f %f\n",j,e,lr);
if (e>e0)
{
if (myid==0)
test_step(hearing,lrPrev);
parallel_broadcast_weights(hearing);
break;
}
e0=e;
lrPrev=lr;
lr *= 1.7;
}
zero_gradients(hearing);
if (i % 5==0 && myid==0)
{
sprintf(fn,"s%d_%d_weights",seed,i);
save_weights(hearing,fn);
}
}
parallel_finish();
return 0;
}
int main(int argc, char ** argv) {
MPI_Init(&argc, &argv);
int P, rank;
MPI_Comm_size(MPI_COMM_WORLD, &P); // size = number of processes nprocs
MPI_Comm_rank(MPI_COMM_WORLD, &rank); // Numbering of process
if (argc > 1) {
// Only one process needs to print usage output
if (rank == 0) {
printf("Argument k needed.\n");
}
MPI_Finalize ();
return 1;
}
double start = MPI_Wtime();
int k = 14;
int n = (int) pow(2, k);
int np = (int) (n - n%P)/P;
double *v, S = 0.0;
MPI_Status status;
int i;
if ( rank == 0 ) {
v = calloc(n, sizeof(double));
compute_v(n, v);
for (i = 1; i < P; i++ ){
MPI_Send( &v[np*i], np, MPI_DOUBLE, i, 0, MPI_COMM_WORLD);
}
double S_n = compute_S(np, v);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
double err = compute_error(S);
printf("Error = %1.16f\n", err);
free(v);
}
else {
double *v_n;
if (rank == P-1) {
v_n = calloc(np + n%P, sizeof(double));
}
else {
v_n = calloc(np, sizeof(double));
}
MPI_Recv(v_n, np, MPI_DOUBLE, 0, 0, MPI_COMM_WORLD, &status);
double S_n = compute_S(np, v_n);
free(v_n);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
}
double end = MPI_Wtime();
if (rank == 0)
printf("Elapsed time: %.16f seconds\n", end-start);
MPI_Finalize();
return 0;
}
/* Function kmeans.
* Run kmeans clustering on a set of input descriptors.
*
* Inputs:
* n : number of input descriptors
* dim : dimension of each input descriptor
* k : number of means to compute
* restarts : number of random restarts to perform
* v : array of pointers to dim-dimensional descriptors
*
* Output:
* means : array of output means. The means should be
* concatenated into one long array of length k*dim.
* clustering : assignment of descriptors to means (should
* range between 0 and k-1), stored as an array of
* length n. clustering[i] contains the
* cluster ID for point i
*/
double kmeans(int n, int dim, int k, int restarts, unsigned char **v,
double *means, unsigned int *clustering)
{
int i;
double min_error = DBL_MAX;
double *means_curr, *means_new, *work;
int *starts;
unsigned int *clustering_curr;
double changed_pct_threshold = 0.05; // 0.005;
if (n <= k) {
printf("[kmeans] Error: n <= k\n");
return -1;
}
means_curr = (double *) malloc(sizeof(double) * dim * k);
means_new = (double *) malloc(sizeof(double) * dim * k);
clustering_curr = (unsigned int *) malloc(sizeof(unsigned int) * n);
starts = (int *) malloc(sizeof(int) * k);
work = (double *) malloc(sizeof(double) * dim);
if (means_curr == NULL) {
printf("[kmeans] Error allocating means_curr\n");
exit(-1);
}
if (means_new == NULL) {
printf("[kmeans] Error allocating means_new\n");
exit(-1);
}
if (clustering_curr == NULL) {
printf("[kmeans] Error allocating clustering_curr\n");
exit(-1);
}
if (starts == NULL) {
printf("[kmeans] Error allocating starts\n");
exit(-1);
}
if (work == NULL) {
printf("[kmeans] Error allocating work\n");
exit(-1);
}
for (i = 0; i < restarts; i++) {
int j;
double max_change = 0.0;
double error = 0.0;
int round = 0;
choose(n, k, starts);
for (j = 0; j < k; j++) {
fill_vector(means_curr + j * dim, v[starts[j]], dim);
}
/* Compute new assignments */
timeval start, stop;
gettimeofday(&start, NULL);
int changed = 0;
changed = compute_clustering_kd_tree(n, dim, k, v, means_curr,
clustering_curr, error);
double changed_pct = (double) changed / n;
do {
gettimeofday(&stop, NULL);
long seconds = stop.tv_sec - start.tv_sec;
long useconds = stop.tv_usec - start.tv_usec;
double etime = seconds + useconds * 0.000001;
printf("Round %d: changed: %d\n", i, changed);
printf("Round took %0.3lfs\n", etime);
fflush(stdout);
gettimeofday(&start, NULL);
/* Recompute means */
max_change = compute_means(n, dim, k, v,
clustering_curr, means_new);
memcpy(means_curr, means_new, sizeof(double) * dim * k);
/* Compute new assignments */
changed = compute_clustering_kd_tree(n, dim, k, v, means_curr,
clustering_curr, error);
changed_pct = (double) changed / n;
round++;
} while (changed_pct > changed_pct_threshold);
max_change = compute_means(n, dim, k, v, clustering_curr, means_new);
memcpy(means_curr, means_new, sizeof(double) * dim * k);
if (error < min_error) {
min_error = error;
memcpy(means, means_curr, sizeof(double) * k * dim);
memcpy(clustering, clustering_curr, sizeof(unsigned int) * n);
}
}
free(means_curr);
free(means_new);
free(clustering_curr);
free(starts);
free(work);
return compute_error(n, dim, k, v, means, clustering);
}
// Computes the Euler spiral for the given params
//if the global lookup table is available, it looks up the ES params first and then optimizes them
//this should dramatically cut down in the time to optimize
void EulerSpiral::compute_es_params ()
{
//compute scaling distance
double d = euc_distance(params.start_pt, params.end_pt);
params.psi = angle0To2Pi(atan2(params.end_pt.y()-params.start_pt.y(),params.end_pt.x()-params.start_pt.x()));
//degeneracy check
if (d<eError)
return;
//first compute a biarc estimate
_bi_arc_estimate.set_start_params(params.start_pt, params.start_angle);
_bi_arc_estimate.set_end_params(params.end_pt, params.end_angle);
_bi_arc_estimate.compute_biarc_params();
//get the total turning angle::This is an important parameter because
//it defines the one solution out of many possible solutions
params.turningAngle = _bi_arc_estimate.params.K1*_bi_arc_estimate.params.L1 +
_bi_arc_estimate.params.K2*_bi_arc_estimate.params.L2;
//From here on, normlize the parameters and use these to perform the optimization
double k0_init_est = _bi_arc_estimate.params.K1*d;
double L_init_est = _bi_arc_estimate.params.L()/d;
double dstep = 0.1;
//Alternately, we can get the initial values from the lookup table and perform
//the optimization from there
//double k0_init_est = globalEulerSpiralLookupTable->get_globalEulerSpiralLookupTable()->k0(CCW(params.psi, params.start_angle), CCW(params.psi, params.end_angle));
//double L_init_est = globalEulerSpiralLookupTable->get_globalEulerSpiralLookupTable()->L(CCW(params.psi, params.start_angle), CCW(params.psi, params.end_angle));
//double dstep = globalEulerSpiralLookupTable->get_globalEulerSpiralLookupTable()->dt()/4;
//then perform a simple gradient descent to find the real solution
double error = compute_error(k0_init_est, L_init_est);
double prev_error = error;
double k0 = k0_init_est;
double L = L_init_est;
double e1, e2, e3, e4 = 0;
for (int i=0; i<MAX_NUM_ITERATIONS; i++)
{
if (error<eError)
break;
e1 = compute_error(k0 + dstep, L);
e2 = compute_error(k0 - dstep, L);
e3 = compute_error(k0, L + dstep);
if (L>dstep) e4 = compute_error(k0, L - dstep);
error = MIN2(MIN2(e1,e2),MIN2(e3,e4));
if (error>prev_error)
{
dstep = dstep/2;
continue;
}
if (error==e1) k0 = k0 + dstep;
else if (error==e2) k0 = k0 - dstep;
else if (error==e3) L = L + dstep;
else if (error==e4) L = L - dstep;
prev_error = error;
}
//store the parameters
params.K0 = k0/d;
params.L = L*d;
params.gamma = 2*(params.turningAngle - k0*L)/(L*L)/(d*d);
params.K2 = (k0 + params.gamma*L)/d;
params.error = error;
}
int main(int argc, char ** argv) {
MPI_Init(&argc, &argv);
int P, rank;
MPI_Comm_size(MPI_COMM_WORLD, &P); // P = number of processes
MPI_Comm_rank(MPI_COMM_WORLD, &rank); // Rank = numbering of each process
if (isPowerOfTwo(P) == false) {
if (rank == 0) {
printf("The number of processes is not a power of two \n");
}
MPI_Finalize();
return 1;
}
if (argc < 2) {
if (rank == 0) {
printf("Usage: ex3 k, n=pow(2,k)\n");
printf("n = vector/matrix size\n");
}
MPI_Finalize ();
return 1;
}
int k = atoi(argv[1]);
int n = (int) pow(2, k);
int np = (int) (n - n%P)/P;
double *v, S = 0.0;
MPI_Status status;
int i;
if ( rank == 0 ) {
v = calloc(n, sizeof(double));
compute_v(n, v);
for (i = 1; i < P; i++ ){
MPI_Send(&v[np*i], np, MPI_DOUBLE, i, 0, MPI_COMM_WORLD);
}
double S_n = compute_S(np, v);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
printf("S = %1.16f\n", S);
double err = compute_error(S);
printf("Error = %1.16f\n", err);
free(v);
}
else {
double *v_n;
if (rank == P-1) {
v_n = calloc(np + n%P, sizeof(double));
}
else {
v_n = calloc(np, sizeof(double));
}
MPI_Recv(v_n, np, MPI_DOUBLE, 0, 0, MPI_COMM_WORLD, &status);
double S_n = compute_S(np, v_n);
free(v_n);
MPI_Reduce(&S_n, &S, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
}
MPI_Finalize();
return 0;
}
void array_compare(fftw_real * A, fftw_real * B, int n)
{
CHECK(compute_error(A, 1, B, 1, n) < TOLERANCE,
"failure in RFFTW verification");
}
int main()
{
DDRB |= _BV(PB0);
DDRD = 0x00;
setup_motors();
int change_pwm = 0;
int prev_error = 0;
int error = 0;
int p = 0,i = 0,d = 0;
while(1) {
prev_error = error;
error = compute_error();
if(check_all()) {
for(int x = 0; x < 4; x++) {
errors[x] = errors[x+1];
}
errors[4] = error;
}
toggle_led();
if(!check_all()) {
int r_count = 0, l_count = 0;
for(int i = 0; i < 5; i++) {
if(errors[i] < 0)
l_count++;
if(errors[i] > 0)
r_count++;
}
if(l_count > r_count)
motors_left();
else
motors_right();
OCR1A = 255;
OCR1B = 255;
}
else {
p = error;
change_pwm = kp*p;
int right = tp + change_pwm;
int left = tp - change_pwm;
if(right > 255) right = 255;
if(left > 255) left = 255;
motors_straight();
OCR1A = right;
OCR1B = left;
}
_delay_ms(5);
}
}
void test_in_place(int n, int istride,
int howmany, fftw_direction dir,
fftw_plan validated_plan, int specific)
{
fftw_complex *in2, *out2;
fftw_real *in1, *out1, *out3;
fftw_plan plan;
int i, j;
int ostride = istride;
int flags = measure_flag | wisdom_flag | FFTW_IN_PLACE;
if (coinflip())
flags |= FFTW_THREADSAFE;
in1 = (fftw_real *) fftw_malloc(istride * n * sizeof(fftw_real) * howmany);
in2 = (fftw_complex *) fftw_malloc(n * sizeof(fftw_complex));
out1 = in1;
out2 = (fftw_complex *) fftw_malloc(n * sizeof(fftw_complex));
out3 = (fftw_real *) fftw_malloc(n * sizeof(fftw_real));
if (!specific)
plan = rfftw_create_plan(n, dir, flags);
else
plan = rfftw_create_plan_specific(n, dir, flags,
in1, istride, out1, ostride);
CHECK(plan != NULL, "can't create plan");
/* generate random inputs */
fill_random(in1, n, istride);
for (j = 1; j < howmany; ++j)
for (i = 0; i < n; ++i)
in1[(j * n + i) * istride] = in1[i * istride];
/* copy random inputs to complex array for comparison with fftw: */
if (dir == FFTW_REAL_TO_COMPLEX)
for (i = 0; i < n; ++i) {
c_re(in2[i]) = in1[i * istride];
c_im(in2[i]) = 0.0;
} else {
int n2 = (n + 1) / 2;
c_re(in2[0]) = in1[0];
c_im(in2[0]) = 0.0;
for (i = 1; i < n2; ++i) {
c_re(in2[i]) = in1[i * istride];
c_im(in2[i]) = in1[(n - i) * istride];
}
if (n2 * 2 == n) {
c_re(in2[n2]) = in1[n2 * istride];
c_im(in2[n2]) = 0.0;
++i;
}
for (; i < n; ++i) {
c_re(in2[i]) = c_re(in2[n - i]);
c_im(in2[i]) = -c_im(in2[n - i]);
}
}
/*
* fill in other positions of the array, to make sure that
* rfftw doesn't overwrite them
*/
for (j = 1; j < istride; ++j)
for (i = 0; i < n * howmany; ++i)
in1[i * istride + j] = i * istride + j;
WHEN_VERBOSE(2, rfftw_print_plan(plan));
/* fft-ize */
if (howmany != 1 || istride != 1 || coinflip())
rfftw(plan, howmany, in1, istride, n * istride, 0, 0, 0);
else
rfftw_one(plan, in1, NULL);
rfftw_destroy_plan(plan);
/* check for overwriting */
for (j = 1; j < ostride; ++j)
for (i = 0; i < n * howmany; ++i)
CHECK(out1[i * ostride + j] == i * ostride + j,
"output has been overwritten");
fftw(validated_plan, 1, in2, 1, n, out2, 1, n);
if (dir == FFTW_REAL_TO_COMPLEX) {
int n2 = (n + 1) / 2;
out3[0] = c_re(out2[0]);
for (i = 1; i < n2; ++i) {
out3[i] = c_re(out2[i]);
out3[n - i] = c_im(out2[i]);
}
if (n2 * 2 == n)
out3[n2] = c_re(out2[n2]);
} else {
for (i = 0; i < n; ++i)
out3[i] = c_re(out2[i]);
}
for (j = 0; j < howmany; ++j)
CHECK(compute_error(out1 + j * n * ostride, ostride, out3, 1, n)
< TOLERANCE,
"test_in_place: wrong answer");
WHEN_VERBOSE(2, printf("OK\n"));
fftw_free(in1);
fftw_free(in2);
fftw_free(out2);
fftw_free(out3);
}
int CybCamCalibration::calibration(CvSeq* image_points_seq, CvSize img_size, CvSize board_size,
float square_size, float aspect_ratio, int flags, CvMat* camera_matrix,
CvMat* dist_coeffs, CvMat** extr_params, CvMat** reproj_errs,
double* avg_reproj_err) {
int code;
int image_count = image_points_seq->total;
int point_count = board_size.width*board_size.height;
CvMat* image_points = cvCreateMat( 1, image_count*point_count, CV_32FC2);
CvMat* object_points = cvCreateMat( 1, image_count*point_count, CV_32FC3);
CvMat* point_counts = cvCreateMat( 1, image_count, CV_32SC1);
CvMat rot_vects, trans_vects;
int i, j, k;
CvSeqReader reader;
cvStartReadSeq(image_points_seq, &reader);
// initialize arrays of points
for (i = 0; i < image_count; i++) {
CvPoint2D32f* src_img_pt = (CvPoint2D32f*)reader.ptr;
CvPoint2D32f* dst_img_pt = ((CvPoint2D32f*)image_points->data.fl) + i
*point_count;
CvPoint3D32f* obj_pt = ((CvPoint3D32f*)object_points->data.fl) + i
*point_count;
for (j = 0; j < board_size.height; j++)
for (k = 0; k < board_size.width; k++) {
*obj_pt++ = cvPoint3D32f(j*square_size, k*square_size, 0);
*dst_img_pt++ = *src_img_pt++;
}
CV_NEXT_SEQ_ELEM( image_points_seq->elem_size, reader );
}
cvSet(point_counts, cvScalar(point_count) );
*extr_params = cvCreateMat(image_count, 6, CV_32FC1);
cvGetCols( *extr_params, &rot_vects, 0, 3);
cvGetCols( *extr_params, &trans_vects, 3, 6);
cvZero( camera_matrix );
cvZero( dist_coeffs );
if (flags & CV_CALIB_FIX_ASPECT_RATIO) {
camera_matrix->data.db[0] = aspect_ratio;
camera_matrix->data.db[4] = 1.;
}
cvCalibrateCamera2(object_points, image_points, point_counts, img_size,
camera_matrix, dist_coeffs, &rot_vects, &trans_vects, flags);
code = cvCheckArr(camera_matrix, CV_CHECK_QUIET) && cvCheckArr(dist_coeffs,
CV_CHECK_QUIET) && cvCheckArr( *extr_params, CV_CHECK_QUIET);
*reproj_errs = cvCreateMat( 1, image_count, CV_64FC1);
*avg_reproj_err = compute_error(object_points, &rot_vects,
&trans_vects, camera_matrix, dist_coeffs, image_points,
point_counts, *reproj_errs);
cvReleaseMat( &object_points);
cvReleaseMat( &image_points);
cvReleaseMat( &point_counts);
return code;
}
// level_refine {{{
int level_refine(int level,parameter &par,boost::shared_ptr<std::vector<id_type> > &result_data, double time)
{
int rc;
int ghostwidth = par->ghostwidth;
double ethreshold = par->ethreshold;
double minx0 = par->minx0;
double maxx0 = par->maxx0;
double h = par->h;
int refine_factor = 2;
// local vars
std::vector<int> b_minx,b_maxx;
std::vector<int> ddminx,ddmaxx;
int maxlevel = par->allowedl;
if ( level == maxlevel ) {
return 0;
}
double minx,maxx;
double hl;
int gi;
if ( level == -1 ) {
// we're creating the coarse grid
minx = minx0;
maxx = maxx0;
gi = -1;
hl = h;
} else {
// find the bounds of the level
rc = level_find_bounds(level,minx,maxx,par);
// find the grid index of the beginning of the level
gi = level_return_start(level,par);
// grid spacing for the level
hl = par->gr_h[gi];
}
int nxl = (int) ((maxx-minx)/hl+0.5);
nxl++;
std::vector<double> error,localerror;
std::vector<int> flag;
error.resize(nxl);
flag.resize(nxl);
if ( level == -1 ) {
int numbox = nxl/par->grain_size;
b_minx.resize(numbox);
b_maxx.resize(numbox);
std::size_t grain_size;
grain_size = par->grain_size;
for (int i=0;i<numbox;i++) {
b_minx[i] = i*grain_size;
if ( i == numbox-1 ) {
grain_size = nxl - (numbox-1)*par->grain_size;
}
b_maxx[i] = b_minx[i] + grain_size;
if (i == numbox-1 ) {
// indicate the last of the level -- no more siblings
par->gr_sibling.push_back(-1);
} else {
par->gr_sibling.push_back(i+1);
}
int nx = (b_maxx[i] - b_minx[i]);
double lminx = minx + b_minx[i]*hl;
double lmaxx = lminx + hl*(grain_size-1);
par->gr_minx.push_back(lminx);
par->gr_maxx.push_back(lmaxx);
par->gr_h.push_back(hl);
par->gr_lbox.push_back(false);
par->gr_rbox.push_back(false);
par->gr_left_neighbor.push_back(-1);
par->gr_right_neighbor.push_back(-1);
par->gr_nx.push_back(nx);
}
return 0;
} else {
// loop over all grids in level and get its error data
gi = level_return_start(level,par);
while ( grid_return_existence(gi,par) ) {
int nx = par->gr_nx[gi];
localerror.resize(nx);
double lminx = par->gr_minx[gi];
double lmaxx = par->gr_maxx[gi];
rc = compute_error(localerror,nx,
lminx, lmaxx,
par->gr_h[gi],time,gi,result_data,par);
int mini = (int) ((lminx - minx)/hl+0.5);
// sanity check
if ( floatcmp(lminx-(minx + mini*hl),0.0) == 0 ||
floatcmp(lmaxx-(minx + (mini+nx-1)*hl),0.0) == 0 ) {
std::cerr << " Index problem " << std::endl;
std::cerr << " lminx " << lminx << " " << minx + mini*hl << std::endl;
std::cerr << " lmaxx " << lminx << " " << minx + (mini+nx-1)*hl << std::endl;
exit(0);
}
rc = level_combine(error,localerror,
mini,nxl,nx);
gi = par->gr_sibling[gi];
}
}
level_makeflag_simple(flag,error,nxl,ethreshold);
// level_cluster
int hgw = (ghostwidth+1)/2;
int maxfind = 0;
for (std::size_t i=0;i<flag.size();i++) {
if ( flag[i] == 1 && maxfind == 0 ) {
b_minx.push_back(i);
maxfind = 1;
}
if ( flag[i] == 0 && maxfind == 1 ) {
b_maxx.push_back(i-1);
maxfind = 0;
}
}
// add in ghostzones
for (std::size_t i=0;i<b_maxx.size();i++) {
b_minx[i] -= hgw;
b_maxx[i] += hgw;
}
// Determine the domain decomposition
for (std::size_t i=0;i<b_maxx.size();i++) {
std::size_t grain_size;
grain_size = par->grain_size;
BOOST_ASSERT(b_maxx[i] > b_minx[i]);
std::size_t nx = (b_maxx[i] - b_minx[i])*refine_factor+1;
if ( par->grain_size > nx ) {
ddminx.push_back(b_minx[i]);
ddmaxx.push_back(b_maxx[i]);
} else {
int numddbox = nx/par->grain_size;
// break up b_minx/b_maxx in numddbox portions
int tnx = b_maxx[i] - b_minx[i];
int grain_size = tnx/numddbox;
for (int j=0;j<numddbox;j++) {
ddminx.push_back(j*grain_size + b_minx[i]);
if ( j == numddbox-1 ) {
grain_size = tnx - (numddbox-1)*grain_size;
}
ddmaxx.push_back(ddminx[ddminx.size()-1] + grain_size-1);
}
}
}
BOOST_ASSERT(ddmaxx.size() == ddminx.size());
int prev_tgi = 0;
int tgi = 0;
for (std::size_t i=0;i<ddmaxx.size();i++) {
int nx = (ddmaxx[i] - ddminx[i])*refine_factor+1;
double lminx = minx + ddminx[i]*hl;
double lmaxx = minx + ddmaxx[i]*hl;
if ( i != 0 ) {
prev_tgi = tgi;
}
// look for matching grid on level
tgi = increment_gi(level,nx,lminx,lmaxx,hl,refine_factor,par);
if ( i == 0 ) {
par->levelp[level+1] = tgi;
}
if (i == ddmaxx.size()-1) {
par->gr_sibling[prev_tgi] = tgi;
par->gr_sibling[tgi] = -1;
} else if (i != 0 ) {
par->gr_sibling[prev_tgi] = tgi;
}
}
return 0;
}
int main(int argc,const char *argv[])
{
Net *net;
Group *input,*hidden,*output,*bias;
ExampleSet *examples, *test;
Example *ex;
Connections *c1,*c2,*c3,*c4;
char * fileName = "input";
int i,count,j, dataCount =0, testCount = 0;
int dataCountArray[6] = {0};
char * testFileArray[6] = {NULL};
int inputCount = 0,outputCount = 0, hiddenCount = 200;
int batchFlag = 0;
Real error, correct;
Real epsilon,range, hiddenRatio = 0;
unsigned long seed = 0;
/* don't buffer output */
setbuf(stdout,NULL);
/* set seed to unique number */
mikenet_set_seed(seed);
/* a default learning rate */
epsilon=0.1;
/* default weight range */
range=0.5;
default_errorRadius=0.0;
const char *usage = "mike_childes [options]\n"
"-seed\t\tRandom seed (default to 0)\n"
"-i\t\tNumer of input units (default to 0)\n"
"-h\t\tNumer of hidden units (default to 200)\n"
"-o\t\tNumer of output units (default to 0)\n"
"-r\t\tRatio of input units / hidden units.(default to 200)\n"
"-b\t\tEnables batch learning (default online learning)\n"
"-epsilon\tBack probagation epsilon (Default 0.1)\n"
"-help\t\tprints this help\n";
/* what are the command line arguments? */
if (argc == 1) {
fprintf(stderr, "%s", usage);
exit(1);
}
for(i=1;i<argc;i++) {
if (strcmp(argv[i],"-seed")==0) {
seed = atol(argv[i+1]);
mikenet_set_seed(seed);
i++;
} else if (strncmp(argv[i],"-epsilon",5)==0) {
epsilon=atof(argv[i+1]);
i++;
} else if (strcmp(argv[i],"-range")==0) {
range=atof(argv[i+1]);
i++;
} else if (strcmp(argv[i],"-errorRadius")==0) {
default_errorRadius=atof(argv[i+1]);
i++;
} else if (strcmp(argv[i],"-t")==0){
testFileArray[testCount] = (char *)argv[i+1];
testCount++;
i++;
} else if (strcmp(argv[i],"-d")==0){
dataCountArray[dataCount]= atoi(argv[i+1]);
dataCount++;
i++;
} else if (strcmp(argv[i], "-iter")==0) {
ITER = atoi(argv[i+1]);
i++;
} else if (strcmp(argv[i], "-f") == 0) {
fileName = (char*)argv[i+1];
i++;
} else if (strcmp(argv[i], "-v") == 0) {
VERBOSE = 1;
} else if (strcmp(argv[i], "-i") == 0) {
inputCount = atoi(argv[i+1]);
i++;
} else if (strcmp(argv[i], "-o") == 0) {
outputCount = atoi(argv[i+1]);
i++;
} else if (strcmp(argv[i], "-h") == 0) {
hiddenCount = atoi(argv[i+1]);
i++;
} else if (strcmp(argv[i], "-r") == 0) {
hiddenRatio = atof(argv[i+1]);
i++;
} else if (strcmp(argv[i], "-b") == 0) {
batchFlag = 1;
} else {
fprintf(stderr,"unknown argument: %s\n%s\n",argv[i],usage);
exit(-1);
}
}
/* build a network, with TIME number of time ticks */
net=create_net(TIME);
/* learning rate */
default_epsilon=epsilon;
/* hidden ratio */
if (hiddenRatio > 0 && hiddenRatio <= 1) {
hiddenCount = (int)inputCount * hiddenRatio;
if(VERBOSE) fprintf(stderr, "number of hidden units is set to %d\n",hiddenCount);
} else if(hiddenRatio > 1) {
fprintf(stderr, "%s", usage);
exit(1);
}
/* First stdout of this code is nummber of hidden units*/
printf("%d\t",hiddenCount);
/* create our groups.
format is: name, num of units, ticks */
input=init_group("Input",inputCount,TIME);
hidden=init_group("hidden",hiddenCount,TIME);
output=init_group("Output",outputCount,TIME);
/* bias is special. format is: value, ticks */
bias=init_bias(1.0,TIME);
/* now add our groups to the network object */
bind_group_to_net(net,input);
bind_group_to_net(net,hidden);
bind_group_to_net(net,output);
bind_group_to_net(net,bias);
/* now connect our groups, instantiating */
/* connection objects c1 through c4 */
c1=connect_groups(input,hidden);
c2=connect_groups(hidden,output);
c3=connect_groups(bias,hidden);
c4=connect_groups(bias,output);
/* add connections to our network */
bind_connection_to_net(net,c1);
bind_connection_to_net(net,c2);
bind_connection_to_net(net,c3);
bind_connection_to_net(net,c4);
/* randomize the weights in the connection objects.
2nd argument is weight range. */
randomize_connections(c1,range);
randomize_connections(c2,range);
randomize_connections(c3,range);
randomize_connections(c4,range);
/* how to load and save weights */
/* load_weights(net,"init.weights"); */
/* erase old initial weight file */
/* system("rm -f init.weights.Z"); */
/* save out our weights to file 'init.weights' */
/* load in our example set */
if (VERBOSE){
fprintf(stderr, "Reading %s Iter:%d ",fileName, ITER);
for(i=0; i < 6; i++){
if (testFileArray[i] == NULL) break;
fprintf(stderr, "TestSet:%s\n", testFileArray[i]);
}
}
examples=load_examples(fileName,TIME);
if (VERBOSE){
fprintf(stderr, "size:%d\n", examples->numExamples);
for(i=0; i < dataCount; i++){
if (i == 0){
fprintf(stderr, "DataCounts[%d] start:0 end:%d size:%d\n", \
i,dataCountArray[i],dataCountArray[i]);
}else{
fprintf(stderr, "DataCounts[%d] start:%d end:%d size:%d\n", \
i,dataCountArray[i - 1], dataCountArray[i], dataCountArray[i] - dataCountArray[i - 1]);
}
}
}
error=0.0;
count=0;
/* loop for ITER number of times */
/* Reset the seed to get same training set*/
fprintf(stderr, "Training: %s size:%d\n", fileName, examples->numExamples);
mikenet_set_seed(seed);
for(i=0;i<ITER;i++) {
/* get j'th example from exampleset */
int ridx = (int) (mikenet_random() * (Real)examples->numExamples);
ex = &examples->examples[ridx];
/*Original one*/
// ex = get_random_example(examples);
/* do forward propagation */
bptt_forward(net,ex);
/* backward pass: compute gradients */
bptt_compute_gradients(net,ex);
/* sum up error for this example */
error+=compute_error(net,ex);
/* online learning: apply the deltas
from previous call to compute_gradients */
if(batchFlag == 0)
bptt_apply_deltas(net);
/* is it time to write status? */
if (count==REP) {
/* average error over last 'count' iterations */
error = error/(float)count;
count=0;
/* print a message about average error so far */
if (VERBOSE) fprintf(stderr, "%d\t%f\n",i,error);
if (error < 0.1) {
break;
}
/* zero error; start counting again */
error=0.0;
}
count++;
}
if(batchFlag == 1)
bptt_apply_deltas(net);
/* done training. write out results for each example */
if (testCount == 0){
correct = 0;
dataCount = 0;
for(i=0;i<examples->numExamples;i++)
{
if (VERBOSE && i % 1000 == 0) fprintf(stderr,".");
if (dataCount && i == dataCountArray[dataCount]){
if (dataCount ==0){
printf("%f\t", correct / dataCountArray[dataCount]);
}else{
printf("%f\t", correct / (dataCountArray[dataCount] - dataCountArray[dataCount - 1]));
}
correct = 0;
dataCount++;
}
ex=&examples->examples[i];
bptt_forward(net,ex);
int maxj = -1;
Real maxx = 0;
for(j=0 ; j < outputCount; j++){
if (output->outputs[TIME-1][j] > maxx){
maxj = j;
maxx = output->outputs[TIME-1][j];
}
/* printf("%d:%f ",j,output->outputs[TIME-1][j]); */
}
if (get_value(ex->targets,output->index,TIME-1,maxj) == 1)
correct += 1;
}
printf("%f\n", correct / (dataCountArray[dataCount] - dataCountArray[dataCount - 1]));
}
else{
int tt = 0, dc = 0;
correct = 0;
for(tt = 0; tt < testCount; tt++){
test = load_examples(testFileArray[tt],TIME);
if (VERBOSE)
fprintf(stderr,"Testing:%s size:%d\n",testFileArray[tt],test->numExamples);
correct = 0;
for(i=0;i<test->numExamples;i++){
if (dataCount && i == dataCountArray[dc]){
if (dc == 0)
printf("%f\t", correct / dataCountArray[dc]);
else
printf("%f\t", correct / (dataCountArray[dc] - dataCountArray[dc - 1]));
correct = 0;
dc++;
}
if (VERBOSE && i % 1000 == 0) fprintf(stderr,".");
ex=&test->examples[i];
bptt_forward(net,ex);
int maxj = -1;
Real maxx = 0;
int goldIdx = -1;
for(j=0 ; j < outputCount; j++){
if (output->outputs[TIME-1][j] > maxx){
maxj = j;
maxx = output->outputs[TIME-1][j];
}
if (get_value(ex->targets,output->index,TIME-1,j) == 1) {
if(goldIdx != -1) {
fprintf(stderr,\
"Multiple active output unit: Instance:%d unit:%d in test set!"\
,i,j);
}
goldIdx = j;
}
/* printf("%d:%f ",j,output->outputs[TIME-1][j]); */
}
if (goldIdx != -1 || maxj != -1) {
// prints the goldtag and answer tag
fprintf(stderr, "%d %d\n", goldIdx, maxj);
} else{
fprintf(stderr, "No active output units in test set");
exit(-1);
}
if (get_value(ex->targets,output->index,TIME-1,maxj) == 1) {
correct += 1;
}
}
if (dataCount == 0)
printf("%f %d %d\t", correct / test->numExamples, (int)correct, test->numExamples);
else
printf("%f\n", correct / (dataCountArray[dc] - dataCountArray[dc - 1]));
}
}
return 0;
}
static uint64_t compress_latc_block(uint8_t block[16]) {
// Just do a simple min/max but choose which of the
// two palettes is better
uint8_t maxVal = 0;
uint8_t minVal = 255;
for (int i = 0; i < 16; ++i) {
maxVal = SkMax32(maxVal, block[i]);
minVal = SkMin32(minVal, block[i]);
}
// Generate palettes
uint8_t palettes[2][8];
// Straight linear ramp
palettes[0][0] = maxVal;
palettes[0][1] = minVal;
for (int i = 1; i < 7; ++i) {
palettes[0][i+1] = ((7-i)*maxVal + i*minVal) / 7;
}
// Smaller linear ramp with min and max byte values at the end.
palettes[1][0] = minVal;
palettes[1][1] = maxVal;
for (int i = 1; i < 5; ++i) {
palettes[1][i+1] = ((5-i)*maxVal + i*minVal) / 5;
}
palettes[1][6] = 0;
palettes[1][7] = 255;
// Figure out which of the two is better:
// - accumError holds the accumulated error for each pixel from
// the associated palette
// - indices holds the best indices for each palette in the
// bottom 48 (16*3) bits.
uint32_t accumError[2] = { 0, 0 };
uint64_t indices[2] = { 0, 0 };
for (int i = 15; i >= 0; --i) {
// For each palette:
// 1. Retreive the result of this pixel
// 2. Store the error in accumError
// 3. Store the minimum palette index in indices.
for (int p = 0; p < 2; ++p) {
uint32_t result = compute_error(block[i], palettes[p]);
accumError[p] += (result >> 8);
indices[p] <<= 3;
indices[p] |= result & 7;
}
}
SkASSERT(indices[0] < (static_cast<uint64_t>(1) << 48));
SkASSERT(indices[1] < (static_cast<uint64_t>(1) << 48));
uint8_t paletteIdx = (accumError[0] > accumError[1]) ? 0 : 1;
// Assemble the compressed block.
uint64_t result = 0;
// Jam the first two palette entries into the bottom 16 bits of
// a 64 bit integer. Based on the palette that we chose, one will
// be larger than the other and it will select the proper palette.
result |= static_cast<uint64_t>(palettes[paletteIdx][0]);
result |= static_cast<uint64_t>(palettes[paletteIdx][1]) << 8;
// Jam the indices into the top 48 bits.
result |= indices[paletteIdx] << 16;
// We assume everything is little endian, if it's not then make it so.
return SkEndian_SwapLE64(result);
}
void Gauss_siedel(double *phi, double *mu, double *V) {
long i, j, index, index_right, index_front, index_left, index_back;
double V_old,A[MESHX*MESHY],B[MESHX*MESHY],C[MESHX*MESHY],E[MESHX*MESHY],F[MESHX*MESHY];
double error;
double tol=1.0e-6;
for(i=1; i < MESHX-1; i++) {
for(j=1; j< MESHY-1; j++) {
indx = i*MESHY + j;
indx_rght = indx + 1;
indx_frnt = indx + MESHY;
indx_lft = indx - 1;
indx_bck = indx - MESHY;
A[index] = (zeta(phi[index_left]) + zeta(phi[index])); //left
B[index] = (zeta(phi[index_right]) + zeta(phi[index])); //right
C[index] = (zeta(phi[index_back]) + zeta(phi[index])); //back
E[index] = (zeta(phi[index_front]) + zeta(phi[index])); //front
F[index] = -(A[index] + B[index] + C[index] + E[index]);
}
}
for(;;) {
for(i=1; i < MESHX-1; i++) {
for(j=1;j < MESHY-1;j++) {
index = i*MESHY + j;
index_right = index + 1;
index_front = index + MESHY;
index_left = index - 1;
index_back = index - MESHY;
if (((i+j)%2) == 0) {
V_old = V[index];
V[index] = A[index]*V[index_left] + B[index]*V[index_right]
+ C[index]*V[index_back] + E[index]*V[index_front];
V[index] /= (-F[index]);
}
}
}
for(i=1; i < MESHX-1; i++) {
for(j=1;j < MESHY-1; j++) {
index = i*MESHY + j;
index_right = index + 1;
index_front = index + MESHY;
index_left = index - 1;
index_back = index - MESHY;
if (((i+j)%2) != 0) {
V_old = V[index];
V[index] = A[index]*V[index_left] + B[index]*V[index_right]
+ C[index]*V[index_back] + E[index]*V[index_front];
V[index] /= (-F[index]);
}
}
}
error = compute_error(A, B, C, E, F, V);
if (fabs(error) < tol) {
break;
}
}
}
void testnd_out_of_place(int rank, int *n, fftwnd_plan validated_plan)
{
int istride, ostride;
int N, dim, i, j, k;
int nc, nhc, nr;
fftw_real *in1, *out3;
fftw_complex *in2, *out1, *out2;
fftwnd_plan p, ip;
int flags = measure_flag | wisdom_flag;
if (coinflip())
flags |= FFTW_THREADSAFE;
N = nc = nr = nhc = 1;
for (dim = 0; dim < rank; ++dim)
N *= n[dim];
if (rank > 0) {
nr = n[rank - 1];
nc = N / nr;
nhc = nr / 2 + 1;
}
in1 = (fftw_real *) fftw_malloc(N * MAX_STRIDE * sizeof(fftw_real));
out3 = (fftw_real *) fftw_malloc(N * MAX_STRIDE * sizeof(fftw_real));
out1 = (fftw_complex *) fftw_malloc(nhc * nc * MAX_STRIDE
* sizeof(fftw_complex));
in2 = (fftw_complex *) fftw_malloc(N * sizeof(fftw_complex));
out2 = (fftw_complex *) fftw_malloc(N * sizeof(fftw_complex));
p = rfftwnd_create_plan(rank, n, FFTW_REAL_TO_COMPLEX, flags);
ip = rfftwnd_create_plan(rank, n, FFTW_COMPLEX_TO_REAL, flags);
CHECK(p != NULL && ip != NULL, "can't create plan");
for (istride = 1; istride <= MAX_STRIDE; ++istride) {
/* generate random inputs */
for (i = 0; i < nc; ++i)
for (j = 0; j < nr; ++j) {
c_re(in2[i * nr + j]) = DRAND();
c_im(in2[i * nr + j]) = 0.0;
for (k = 0; k < istride; ++k)
in1[(i * nr + j) * istride + k]
= c_re(in2[i * nr + j]);
}
for (i = 0; i < N * istride; ++i)
out3[i] = 0.0;
fftwnd(validated_plan, 1, in2, 1, 1, out2, 1, 1);
for (ostride = 1; ostride <= MAX_STRIDE; ++ostride) {
int howmany = (istride < ostride) ? istride : ostride;
WHEN_VERBOSE(2, printf("\n testing stride %d/%d...",
istride, ostride));
if (howmany != 1 || istride != 1 || ostride != 1 || coinflip())
rfftwnd_real_to_complex(p, howmany, in1, istride, 1,
out1, ostride, 1);
else
rfftwnd_one_real_to_complex(p, in1, out1);
for (i = 0; i < nc; ++i)
for (k = 0; k < howmany; ++k)
CHECK(compute_error_complex(out1 + i * nhc * ostride + k,
ostride,
out2 + i * nr, 1,
nhc) < TOLERANCE,
"out-of-place (r2c): wrong answer");
if (howmany != 1 || istride != 1 || ostride != 1 || coinflip())
rfftwnd_complex_to_real(ip, howmany, out1, ostride, 1,
out3, istride, 1);
else
rfftwnd_one_complex_to_real(ip, out1, out3);
for (i = 0; i < N * istride; ++i)
out3[i] *= 1.0 / N;
if (istride == howmany)
CHECK(compute_error(out3, 1, in1, 1, N * istride)
< TOLERANCE, "out-of-place (c2r): wrong answer");
for (i = 0; i < nc; ++i)
for (k = 0; k < howmany; ++k)
CHECK(compute_error(out3 + i * nr * istride + k,
istride,
(fftw_real *) (in2 + i * nr), 2,
nr) < TOLERANCE,
"out-of-place (c2r): wrong answer (check 2)");
}
}
rfftwnd_destroy_plan(p);
rfftwnd_destroy_plan(ip);
fftw_free(out3);
fftw_free(out2);
fftw_free(in2);
fftw_free(out1);
fftw_free(in1);
}
