VlKDForest *
kdtreebuild(int verbose,
vl_size dimension,
vl_size numTrees,
int thresholdingMethod,
vl_size numData, float *data)
{
vl_type dataType = VL_TYPE_FLOAT;
VlKDForest * forest;
forest = vl_kdforest_new (dataType, dimension, numTrees) ;
vl_kdforest_set_thresholding_method (forest, thresholdingMethod) ;
if (verbose) {
char const * str = 0 ;
printf("vl_kdforestbuild: data %s [%d x %d]\n",
vl_get_type_name (dataType), dimension, numData) ;
switch (vl_kdforest_get_thresholding_method(forest)) {
case VL_KDTREE_MEAN : str = "mean" ; break ;
case VL_KDTREE_MEDIAN : str = "median" ; break ;
default: abort() ;
}
printf("vl_kdforestbuild: threshold selection method: %s\n", str) ;
printf("vl_kdforestbuild: number of trees: %d\n",
vl_kdforest_get_num_trees(forest)) ;
}
/* -----------------------------------------------------------------
* Do job
* -------------------------------------------------------------- */
vl_kdforest_build (forest, numData, data) ;
if (verbose) {
vl_uindex ti ;
for (ti = 0 ; ti < vl_kdforest_get_num_trees(forest) ; ++ ti) {
printf("vl_kdforestbuild: tree %d: depth %d, num nodes %d\n",
ti,
vl_kdforest_get_depth_of_tree(forest, ti),
vl_kdforest_get_num_nodes_of_tree(forest, ti)) ;
}
}
return(forest);
}
void
mexFunction(int nout, mxArray *out[],
int nin, const mxArray *in[])
{
enum {IN_DATA = 0, IN_END} ;
enum {OUT_TREE = 0} ;
int verbose = 0 ;
int opt ;
int next = IN_END ;
mxArray const *optarg ;
VlKDForest * forest ;
void * data ;
vl_size numData ;
vl_size dimension ;
mxClassID dataClass ;
vl_type dataType ;
int thresholdingMethod = VL_KDTREE_MEDIAN ;
vl_size numTrees = 1 ;
VL_USE_MATLAB_ENV ;
/* -----------------------------------------------------------------
* Check the arguments
* -------------------------------------------------------------- */
if (nin < 1) {
vlmxError(vlmxErrInvalidArgument,
"At least one argument required") ;
} else if (nout > 2) {
vlmxError(vlmxErrInvalidArgument,
"Too many output arguments");
}
dataClass = mxGetClassID(IN(DATA)) ;
if (! vlmxIsMatrix (IN(DATA), -1, -1) ||
! vlmxIsReal (IN(DATA))) {
vlmxError(vlmxErrInvalidArgument,
"DATA must be a real matrix ") ;
}
switch (dataClass) {
case mxSINGLE_CLASS : dataType = VL_TYPE_FLOAT ; break ;
case mxDOUBLE_CLASS : dataType = VL_TYPE_DOUBLE ; break ;
default:
vlmxError(vlmxErrInvalidArgument,
"DATA must be either SINGLE or DOUBLE") ;
}
while ((opt = vlmxNextOption (in, nin, options, &next, &optarg)) >= 0) {
char buffer [1024] ;
switch (opt) {
case opt_threshold_method :
mxGetString (optarg, buffer, sizeof(buffer)/sizeof(buffer[0])) ;
if (! vlmxIsString(optarg, -1)) {
vlmxError(vlmxErrInvalidOption,
"THRESHOLDMETHOD must be a string") ;
}
if (vl_string_casei_cmp(buffer, "median") == 0) {
thresholdingMethod = VL_KDTREE_MEDIAN ;
} else if (vl_string_casei_cmp(buffer, "mean") == 0) {
thresholdingMethod = VL_KDTREE_MEAN ;
} else {
vlmxError(vlmxErrInvalidOption,
"Unknown thresholding method %s", buffer) ;
}
break ;
case opt_num_trees :
if (! vlmxIsScalar(optarg) ||
(numTrees = mxGetScalar(optarg)) < 1) {
vlmxError(vlmxErrInvalidOption,
"NUMTREES must be not smaller than one") ;
}
break ;
case opt_verbose :
++ verbose ;
break ;
}
}
data = mxGetData (IN(DATA)) ;
numData = mxGetN (IN(DATA)) ;
dimension = mxGetM (IN(DATA)) ;
forest = vl_kdforest_new (dataType, dimension, numTrees) ;
vl_kdforest_set_thresholding_method (forest, thresholdingMethod) ;
if (verbose) {
char const * str = 0 ;
mexPrintf("vl_kdforestbuild: data %s [%d x %d]\n",
vl_get_type_name (dataType), dimension, numData) ;
switch (vl_kdforest_get_thresholding_method(forest)) {
case VL_KDTREE_MEAN : str = "mean" ; break ;
case VL_KDTREE_MEDIAN : str = "median" ; break ;
default: abort() ;
}
mexPrintf("vl_kdforestbuild: threshold selection method: %s\n", str) ;
mexPrintf("vl_kdforestbuild: number of trees: %d\n",
vl_kdforest_get_num_trees(forest)) ;
}
/* -----------------------------------------------------------------
* Do job
* -------------------------------------------------------------- */
vl_kdforest_build (forest, numData, data) ;
if (verbose) {
vl_uindex ti ;
for (ti = 0 ; ti < vl_kdforest_get_num_trees(forest) ; ++ ti) {
mexPrintf("vl_kdforestbuild: tree %d: depth %d, num nodes %d\n",
ti,
vl_kdforest_get_depth_of_tree(forest, ti),
vl_kdforest_get_num_nodes_of_tree(forest, ti)) ;
}
}
out[OUT_TREE] = new_array_from_kdforest (forest) ;
vl_kdforest_delete (forest) ;
}
