void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
int dim;
LWPR_Model model;
const double *xn;
double yn;
double yp;
double max_w;
if (nrhs<4) mexErrMsgTxt("Too few arguments.");
create_model_from_matlab(&model,prhs[0]);
dim = (int) mxGetScalar(prhs[1])-1;
if (dim<0 || dim>=model.nOut) mexErrMsgTxt("2nd parameter (dim) exceeds model size.\n");
xn = mxGetPr(prhs[2]);
if (mxGetM(prhs[2])!=model.nIn || mxGetN(prhs[2])!=1) {
lwpr_free_model(&model);
mexErrMsgTxt("3rd parameter (center) does not match model dimensions.\n");
}
yn = mxGetScalar(prhs[3]);
lwpr_aux_update_one(&model, dim, xn, yn, &yp, &max_w);
plhs[0] = mxCreateStructMatrix(1,1, SUB_FIELDS, SUB_FIELD_NAMES);
fill_matlab_from_sub(&model.sub[dim], plhs[0], 0);
plhs[1] = mxCreateDoubleScalar(yp);
plhs[2] = mxCreateDoubleScalar(max_w);
lwpr_free_model(&model);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
LWPR_Model model, model2;
create_model_from_matlab(&model, prhs[0]);
if (!lwpr_duplicate_model(&model2, &model)) mexErrMsgTxt("Cannot copy internally!");
plhs[0] = create_matlab_from_model(&model);
plhs[1] = create_matlab_from_model(&model2);
lwpr_free_model(&model);
lwpr_free_model(&model2);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
LWPR_Model model;
char filename[MAX_PATH];
int numErrors, numWarnings;
if (nrhs!=1 || !mxIsChar(prhs[0])) mexErrMsgTxt("Second argument must be a filename (string).\n");
mxGetString(prhs[0],filename,MAX_PATH);
numErrors = lwpr_read_xml(&model, filename, &numWarnings);
if (numErrors==-2) {
mexErrMsgTxt("LWPR library has been compiled without support for reading XML files (depends on EXPAT)\n");
} else if (numErrors==-1) {
mexErrMsgTxt("Could not read XML file. Please check filename and access permissions.\n");
} else if (numErrors>0) {
mexErrMsgTxt("XML file seems to be invalid, error(s) occured.\n");
}
if (numWarnings>0) {
printf("Parsing XML file '%s' produced %d warnings.\n",filename,numWarnings);
}
plhs[0] = create_matlab_from_model(&model);
lwpr_free_model(&model);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
int ok;
LWPR_ReceptiveField RF,RFT;
LWPR_Model model;
const double *xc;
double y;
if (nrhs<4) mexErrMsgTxt("Too few arguments.");
create_model_from_matlab(&model,prhs[0]);
xc = mxGetPr(prhs[2]);
if (mxGetM(prhs[2])!=model.nIn || mxGetN(prhs[2])!=1) {
lwpr_free_model(&model);
mexErrMsgTxt("3rd parameter (center) does not match model dimensions.\n");
}
y = mxGetScalar(prhs[3]);
if (mxIsEmpty(prhs[1])) {
ok = lwpr_aux_init_rf(&RF,&model,NULL,xc,y);
} else {
create_RF_from_matlab(&RFT,&model, prhs[1], 0);
ok = lwpr_aux_init_rf(&RF,&model,&RFT,xc,y);
lwpr_mem_free_rf(&RFT);
}
lwpr_free_model(&model);
if (!ok) mexErrMsgTxt("Couldn't allocate storage for RF.\n");
plhs[0] = mxCreateStructMatrix(1,1, RF_FIELDS, RF_FIELD_NAMES);
fill_matlab_from_RF(&RF,plhs[0],0);
lwpr_mem_free_rf(&RF);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
LWPR_Model model;
FILE *fp;
char filename[MAX_PATH];
int ok;
if (nrhs!=1 || !mxIsChar(prhs[0])) mexErrMsgTxt("Second argument must be a filename (string).\n");
mxGetString(prhs[0],filename,MAX_PATH);
fp = fopen(filename, "rb");
if (fp==NULL) {
mexErrMsgTxt("Could not open the file. Please check filename and access permissions.\n");
}
ok = lwpr_read_binary_fp(&model, fp);
if (!ok) mexErrMsgTxt("LWPR file seems to be invalid, error(s) occured.\n");
fclose(fp);
plhs[0] = create_matlab_from_model(&model);
lwpr_free_model(&model);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
LWPR_Model model;
char filename[MAX_PATH];
FILE *fp;
int ok;
if (nrhs<2 || !mxIsChar(prhs[1])) mexErrMsgTxt("Second argument must be a filename (string).\n");
create_model_from_matlab(&model, prhs[0]);
mxGetString(prhs[1],filename,MAX_PATH);
fp = fopen(filename, "wb");
if (fp==NULL) {
mexErrMsgTxt("Could not open the file. Please check filename and access permissions.\n");
}
ok = lwpr_write_binary_fp(&model, fp);
fclose(fp);
plhs[0] = mxCreateDoubleScalar(ok);
lwpr_free_model(&model);
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,const mxArray *prhs[]) {
int i;
double *nrfs;
LWPR_Model model;
LWPR_Model *pmodel;
if (nrhs<1) mexErrMsgTxt("Too few arguments.");
pmodel = get_pointer_from_array(prhs[0]);
if (pmodel == NULL) {
create_model_from_matlab(&model,prhs[0]);
pmodel = &model;
}
plhs[0] = mxCreateDoubleMatrix(pmodel->nOut,1,mxREAL);
nrfs = mxGetPr(plhs[0]);
for (i=0;i<pmodel->nOut;i++) {
nrfs[i] = pmodel->sub[i].numRFS;
}
if (pmodel == &model) lwpr_free_model(&model);
}
int lwpr_read_binary_fp(LWPR_Model *model, FILE *fp) {
char str[5];
int ok;
int nIn,nInS,nOut;
int i,dim;
int version;
ok = (int) fread(str, sizeof(char), 4, fp);
if (ok!=4) return 0;
str[4]=0;
if (strcmp(str,"LWPR")!=0) return 0;
if (!lwpr_io_read_int(fp, &version)) return 0;
if (version!=LWPR_BINIO_VERSION) {
fprintf(stderr,"Sorry, version of binary LWPR file does not match this implementation.\n");
return 0;
}
if (!lwpr_io_read_int(fp, &nIn) || !lwpr_io_read_int(fp, &nOut)) return 0;
if (nIn<=0) return 0;
if (nOut<=0) return 0;
if (!lwpr_init_model(model, nIn, nOut, NULL)) return 0;
ok = lwpr_io_read_int(fp, &i);
model->kernel = (LWPR_Kernel) i;
ok &= lwpr_io_read_int(fp, &i);
if (i>0) {
size_t len = (size_t) i;
model->name = (char *) LWPR_MALLOC((len+1)*sizeof(char));
if (model->name == NULL) return 0;
ok &= (fread(model->name, sizeof(char), len, fp) == len)?1:0;
model->name[i] = 0;
}
nInS = model->nInStore;
ok &= lwpr_io_read_int(fp, &model->n_data);
ok &= lwpr_io_read_vector(fp, nIn, model->mean_x);
ok &= lwpr_io_read_vector(fp, nIn, model->var_x);
ok &= lwpr_io_read_int(fp, &model->diag_only);
ok &= lwpr_io_read_int(fp, &model->update_D);
ok &= lwpr_io_read_int(fp, &model->meta);
ok &= lwpr_io_read_scalar(fp, &model->meta_rate);
ok &= lwpr_io_read_scalar(fp, &model->penalty);
ok &= lwpr_io_read_matrix(fp, nIn, nInS, nIn, model->init_alpha);
ok &= lwpr_io_read_vector(fp, nIn, model->norm_in);
ok &= lwpr_io_read_vector(fp, nOut, model->norm_out);
ok &= lwpr_io_read_matrix(fp, nIn, nInS, nIn, model->init_D);
ok &= lwpr_io_read_matrix(fp, nIn, nInS, nIn, model->init_M);
ok &= lwpr_io_read_scalar(fp, &model->w_gen);
ok &= lwpr_io_read_scalar(fp, &model->w_prune);
ok &= lwpr_io_read_scalar(fp, &model->init_lambda);
ok &= lwpr_io_read_scalar(fp, &model->final_lambda);
ok &= lwpr_io_read_scalar(fp, &model->tau_lambda);
ok &= lwpr_io_read_scalar(fp, &model->init_S2);
ok &= lwpr_io_read_scalar(fp, &model->add_threshold);
for (dim=0;dim<model->nOut;dim++) {
int numRFS;
LWPR_SubModel *sub = &model->sub[dim];
ok &= (fread(str, sizeof(char), 4, fp)==4)?1:0;
str[4]=0;
if (!ok || strcmp(str,"SUBM")!=0) {
lwpr_free_model(model);
return 0;
}
ok &= lwpr_io_read_int(fp, &i);
ok &= (i==dim);
ok &= lwpr_io_read_int(fp, &numRFS);
ok &= lwpr_io_read_int(fp, &sub->n_pruned);
for (i=0;i<numRFS;i++) {
ok &= lwpr_io_read_rf(fp, sub);
}
ok &= (numRFS == sub->numRFS);
}
ok &= (fread(str, sizeof(char), 4, fp) == 4)?1:0;
str[4] = 0;
if (!ok || strcmp(str,"RPWL")!=0) {
lwpr_free_model(model);
return 0;
}
return 1;
}
int main(int argc, char** argv)
{
// Instantiate a ModelManager:
ModelManager manager("Test LWPR");
// Parse command-line:
if (manager.parseCommandLine((const int)argc, (const char**)argv, "", 0, 0) == false)
return(1);
manager.start();
double x[2];
double y,yp;
double mse;
FILE *fp;
LWPR_Model model;
int i,j;
/* This allocates some memory and sets initial values
** Note that the model structure itself already exists (on the stack)
*/
lwpr_init_model(&model,2,1,"2D_Cross");
/* Set initial distance metric to 50*(identity matrix) */
lwpr_set_init_D_spherical(&model,50);
/* Set init_alpha to 250 in all elements */
lwpr_set_init_alpha(&model,250);
/* Set w_gen to 0.2 */
model.w_gen = 0.2;
/* See above definition, we either use srand() on Windows or srand48 everywhere else */
SEED_RAND();
for (j=0;j<20;j++) {
mse = 0.0;
for (i=0;i<1000;i++) {
x[0] = 2.0*URAND()-1.0;
x[1] = 2.0*URAND()-1.0;
y = cross(x[0],x[1]) + 0.1*URAND()-0.05;
/* Update the model with one sample
**
** x points to (x[0],x[1]) (input vector)
** &y points to y (output "vector")
** &yp points to yp (prediction "vector")
**
** If you are interested in maximum activation, call
** lwpr_update(&model, x, &y, &yp, &max_w);
*/
lwpr_update(&model, x, &y, &yp, NULL);
mse+=(y-yp)*(y-yp);
}
mse/=500;
printf("#Data = %d #RFS = %d MSE = %f\n",model.n_data, model.sub[0].numRFS, mse);
}
fp = fopen("output.txt","w");
mse = 0.0;
i=0;
for (x[1]=-1.0; x[1]<=1.01; x[1]+=0.05) {
for (x[0]=-1.0; x[0]<=1.01; x[0]+=0.05) {
y = cross(x[0],x[1]);
/* Use the model for predicting an output
**
** x points to (x[0],x[1]) (input vector)
** 0.001 is the cutoff value (clip Gaussian kernel)
** &yp points to yp (prediction "vector")
**
** If you are interested in confidence bounds or
** maximum activation, call
** lwpr_predict(&model, x, 0.001, &yp, &conf, &max_w);
*/
lwpr_predict(&model, x, 0.001, &yp, NULL, NULL);
mse += (y-yp)*(y-yp);
i++;
fprintf(fp,"%8.5f %8.5f %8.5f\n",x[0],x[1],yp);
}
fprintf(fp,"\n\n");
}
fclose(fp);
printf("MSE on test data (%d) = %f\n",i,mse/(double) i);
printf("\nTo view the output, start gnuplot, and type:\n");
printf(" splot \"output.txt\"\n\n");
/* Free the memory that was allocated for receptive fields etc.
** Note again that this does not free the LWPR_Model structure
** itself (but it exists on the stack, so it's automatically free'd) */
lwpr_free_model(&model);
// stop all our ModelComponents
manager.stop();
// all done!
return 0;
}
static void PyLWPR_dealloc(PyLWPR* self) {
lwpr_free_model(&self->model);
free(self->extra_in);
self->ob_type->tp_free((PyObject*)self);
}
int main() {
double x[2],y[2],yp[2];
double mseTr[2];
double testErr[2],wTestErr[2];
double binErr[2], wBinErr[2];
double xmlErr[2], wXmlErr[2];
double sumErr;
LWPR_Model model;
int i,j;
int numRFS;
/* This allocates some memory and sets initial values
** Note that the model structure itself already exists (on the stack)
*/
lwpr_init_model(&model,2,2,"2D_Cross");
/* Set initial distance metric to 50*(identity matrix) */
lwpr_set_init_D_spherical(&model,50);
/* Set init_alpha to 250 in all elements */
lwpr_set_init_alpha(&model,250);
/* Set w_gen to 0.2 */
model.w_gen = 0.2;
/* See above definition, we either use srand() on Windows or srand48 everywhere else */
SEED_RAND();
for (j=0;j<20;j++) {
mseTr[0] = mseTr[1] = 0.0;
for (i=0;i<1000;i++) {
x[0] = 2.0*URAND()-1.0;
x[1] = 2.0*URAND()-1.0;
y[0] = cross(x[0],x[1]) + 0.1*URAND()-0.05;
y[1] = y[0] + 10; /* sanity check */
/* Update the model with one sample
**
** x points to (x[0],x[1]) (input vector)
** &y points to y (output "vector")
** &yp points to yp (prediction "vector")
**
** If you are interested in maximum activation, call
** lwpr_update(&model, x, &y, &yp, &max_w);
*/
lwpr_update(&model, x, y, yp, NULL);
mseTr[0]+=(y[0]-yp[0])*(y[0]-yp[0]);
mseTr[1]+=(y[1]-yp[1])*(y[1]-yp[1]);
}
mseTr[0]/=500;
mseTr[1]/=500;
printf("#Data = %d #RFS = %d / %d MSE = %f / %f\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS, mseTr[0], mseTr[1]);
}
if (model.n_data != 20000) {
fprintf(stderr,"model.n_data should have been 20*1000 = 20000. Something is very wrong!\n");
exit(1);
}
if (model.sub[0].numRFS != model.sub[1].numRFS) {
fprintf(stderr,"There should have been an equal number of receptive fields for both outputs :-(\n");
exit(1);
}
numRFS = model.sub[0].numRFS;
testErrors(&model, testErr, wTestErr);
printf("MSE on test data: %f / %f\n",testErr[0], testErr[1]);
if (fabs(testErr[0]-testErr[1]) > 1e-4) {
fprintf(stderr,"MSE should be equal for both outputs, but the difference is > 1e-4\n");
exit(1);
}
printf("Weighted MSE....: %f / %f\n",wTestErr[0], wTestErr[1]);
if (fabs(wTestErr[0]-wTestErr[1]) > 1e-4) {
fprintf(stderr,"Weighted MSE should be equal for both outputs, but the difference is > 1e-4\n");
exit(1);
}
printf("Writing the model to a binary file\n");
/* Write the model to an XML file */
lwpr_write_binary(&model,"lwpr_cross_2d.dat");
/* Free the memory that was allocated for receptive fields etc. */
lwpr_free_model(&model);
printf("Re-read the model from the binary file\n");
/* Read a model from an XML file, memory allocation is done automatically,
** but later lwpr_free_model has to be called again */
j=lwpr_read_binary(&model,"lwpr_cross_2d.dat");
remove("lwpr_cross_2d.dat");
if (j==0) {
fprintf(stderr,"File could not be read, aborting\n");
exit(1);
}
printf("#Data = %d #RFS = %d / %d\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS);
if (model.n_data != 20000 || model.sub[0].numRFS!=numRFS || model.sub[1].numRFS!=numRFS) {
fprintf(stderr,"Model (from binary file) seems to be broken :-(\n");
exit(1);
}
testErrors(&model, binErr, wBinErr);
printf("MSE on test data: %f / %f\n",binErr[0], binErr[1]);
printf("Weighted MSE....: %f / %f\n",wBinErr[0], wBinErr[1]);
sumErr = fabs(binErr[0] - testErr[0]) + fabs(binErr[1] - testErr[1]);
sumErr+= fabs(wBinErr[0] - wTestErr[0]) + fabs(wBinErr[1] - wTestErr[1]);
if (sumErr>1e-8) {
fprintf(stderr,"Error statistics from the binary-IO LWPR model are not the same :-(\n");
exit(1);
}
#if HAVE_LIBEXPAT
printf("Writing the model to an XML file\n");
/* Write the model to an XML file */
lwpr_write_xml(&model,"lwpr_cross_2d.xml");
/* Free the memory that was allocated for receptive fields etc. */
lwpr_free_model(&model);
/* Read a model from an XML file, memory allocation is done automatically,
** but later lwpr_free_model has to be called again */
j=lwpr_read_xml(&model,"lwpr_cross_2d.xml",&i);
remove("lwpr_cross_2d.xml");
printf("Re-read the model from the XML file\n");
printf("%d errors %d warnings\n",j,i);
if (j!=0) {
printf("Errors detected, aborting\n");
exit(1);
}
printf("#Data = %d #RFS = %d / %d\n",model.n_data, model.sub[0].numRFS, model.sub[1].numRFS);
if (model.n_data != 20000 || model.sub[0].numRFS!=numRFS || model.sub[1].numRFS!=numRFS) {
fprintf(stderr,"Model (from XML file) seems to be broken :-(\n");
exit(1);
}
testErrors(&model, xmlErr, wXmlErr);
printf("MSE on test data: %f / %f\n",xmlErr[0], xmlErr[1]);
printf("Weighted MSE....: %f / %f\n",wXmlErr[0], wXmlErr[1]);
sumErr = fabs(xmlErr[0] - testErr[0]) + fabs(xmlErr[1] - testErr[1]);
sumErr+= fabs(wXmlErr[0] - wTestErr[0]) + fabs(wXmlErr[1] - wTestErr[1]);
sumErr/=fabs(testErr[0]) + fabs(testErr[1]) + fabs(wTestErr[0]) + fabs(wTestErr[1]);
printf("Relative difference to the original model: %f\n",sumErr);
if (sumErr>0.0001) {
fprintf(stderr,"Error statistics from the XML-IO LWPR model differ too much :-(\n");
exit(1);
}
#else
printf("LWPR library has been compiled without EXPAT support, XML IO will not be tested.\n");
#endif
/* Free the memory that was allocated for receptive fields etc.
** Note again that this does not free the LWPR_Model structure
** itself (but it exists on the stack, so it's automatically free'd) */
lwpr_free_model(&model);
exit(0);
}
