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Warning fixes continued

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This commit is contained in:
Andrey Kamaev
2012-06-09 15:00:04 +00:00
parent f6b451c607
commit f2d3b9b4a1
127 changed files with 6298 additions and 6277 deletions
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56
modules/ml/src/boost.cpp
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@@ -129,7 +129,7 @@ CvBoostTree::train( CvDTreeTrainData*, const CvMat* )
void
CvBoostTree::scale( double scale )
CvBoostTree::scale( double _scale )
{
CvDTreeNode* node = root;
@@ -139,7 +139,7 @@ CvBoostTree::scale( double scale )
CvDTreeNode* parent;
for(;;)
{
node->value *= scale;
node->value *= _scale;
if( !node->left )
break;
node = node->left;
@@ -501,7 +501,7 @@ CvBoostTree::find_split_ord_reg( CvDTreeNode* node, int vi, float init_quality,
int i, best_i = -1;
double L = 0, R = weights[n];
double best_val = init_quality, lsum = 0, rsum = node->value*R;
// compensate for missing values
for( i = n1; i < n; i++ )
{
@@ -590,7 +590,7 @@ CvBoostTree::find_split_cat_reg( CvDTreeNode* node, int vi, float init_quality,
{
R += counts[i];
rsum += sum[i];
sum[i] = fabs(counts[i]) > DBL_EPSILON ? sum[i]/counts[i] : 0;
sum[i] = fabs(counts[i]) > DBL_EPSILON ? sum[i]/counts[i] : 0;
sum_ptr[i] = sum + i;
}
@@ -1030,7 +1030,7 @@ CvBoost::train( const CvMat* _train_data, int _tflag,
__BEGIN__;
int i;
set_params( _params );
cvReleaseMat( &active_vars );
@@ -1057,7 +1057,7 @@ CvBoost::train( const CvMat* _train_data, int _tflag,
if ( (_params.boost_type == LOGIT) || (_params.boost_type == GENTLE) )
data->do_responses_copy();
update_weights( 0 );
for( i = 0; i < params.weak_count; i++ )
@@ -1088,7 +1088,7 @@ CvBoost::train( const CvMat* _train_data, int _tflag,
}
bool CvBoost::train( CvMLData* _data,
CvBoostParams params,
CvBoostParams _params,
bool update )
{
bool result = false;
@@ -1105,7 +1105,7 @@ bool CvBoost::train( CvMLData* _data,
const CvMat* var_idx = _data->get_var_idx();
CV_CALL( result = train( values, CV_ROW_SAMPLE, response, var_idx,
train_sidx, var_types, missing, params, update ) );
train_sidx, var_types, missing, _params, update ) );
__END__;
@@ -1258,7 +1258,7 @@ CvBoost::update_weights( CvBoostTree* tree )
// invert the subsample mask
cvXorS( subsample_mask, cvScalar(1.), subsample_mask );
data->get_vectors( subsample_mask, values, missing, 0 );
_sample = cvMat( 1, data->var_count, CV_32F );
_mask = cvMat( 1, data->var_count, CV_8U );
@@ -1458,17 +1458,17 @@ CvBoost::trim_weights()
}
const CvMat*
const CvMat*
CvBoost::get_active_vars( bool absolute_idx )
{
CvMat* mask = 0;
CvMat* inv_map = 0;
CvMat* result = 0;
CV_FUNCNAME( "CvBoost::get_active_vars" );
__BEGIN__;
if( !weak )
CV_ERROR( CV_StsError, "The boosted tree ensemble has not been trained yet" );
@@ -1478,7 +1478,7 @@ CvBoost::get_active_vars( bool absolute_idx )
int i, j, nactive_vars;
CvBoostTree* wtree;
const CvDTreeNode* node;
assert(!active_vars && !active_vars_abs);
mask = cvCreateMat( 1, data->var_count, CV_8U );
inv_map = cvCreateMat( 1, data->var_count, CV_32S );
@@ -1518,7 +1518,7 @@ CvBoost::get_active_vars( bool absolute_idx )
}
nactive_vars = cvCountNonZero(mask);
//if ( nactive_vars > 0 )
{
active_vars = cvCreateMat( 1, nactive_vars, CV_32S );
@@ -1538,7 +1538,7 @@ CvBoost::get_active_vars( bool absolute_idx )
j++;
}
}
// second pass: now compute the condensed indices
cvStartReadSeq( weak, &reader );
@@ -1638,7 +1638,7 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
"floating-point vector of the same number of components as the length of input slice" );
wstep = CV_IS_MAT_CONT(weak_responses->type) ? 1 : weak_responses->step/sizeof(float);
}
int var_count = active_vars->cols;
const int* vtype = data->var_type->data.i;
const int* cmap = data->cat_map->data.i;
@@ -1738,7 +1738,7 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
CvBoostTree* wtree;
const CvDTreeNode* node;
CV_READ_SEQ_ELEM( wtree, reader );
node = wtree->get_root();
while( node->left )
{
@@ -1757,14 +1757,14 @@ CvBoost::predict( const CvMat* _sample, const CvMat* _missing,
{
const int* avars = active_vars->data.i;
const uchar* m = _missing ? _missing->data.ptr : 0;
// full-featured version
for( i = 0; i < weak_count; i++ )
{
CvBoostTree* wtree;
const CvDTreeNode* node;
CV_READ_SEQ_ELEM( wtree, reader );
node = wtree->get_root();
while( node->left )
{
@@ -1841,9 +1841,9 @@ float CvBoost::calc_error( CvMLData* _data, int type, std::vector<float> *resp )
{
CvMat sample, miss;
int si = sidx ? sidx[i] : i;
cvGetRow( values, &sample, si );
if( missing )
cvGetRow( missing, &miss, si );
cvGetRow( values, &sample, si );
if( missing )
cvGetRow( missing, &miss, si );
float r = (float)predict( &sample, missing ? &miss : 0 );
if( pred_resp )
pred_resp[i] = r;
@@ -1859,15 +1859,15 @@ float CvBoost::calc_error( CvMLData* _data, int type, std::vector<float> *resp )
CvMat sample, miss;
int si = sidx ? sidx[i] : i;
cvGetRow( values, &sample, si );
if( missing )
cvGetRow( missing, &miss, si );
if( missing )
cvGetRow( missing, &miss, si );
float r = (float)predict( &sample, missing ? &miss : 0 );
if( pred_resp )
pred_resp[i] = r;
float d = r - response->data.fl[si*r_step];
err += d*d;
}
err = sample_count ? err / (float)sample_count : -FLT_MAX;
err = sample_count ? err / (float)sample_count : -FLT_MAX;
}
return err;
}
@@ -2097,10 +2097,10 @@ CvBoost::CvBoost( const Mat& _train_data, int _tflag,
default_model_name = "my_boost_tree";
active_vars = active_vars_abs = orig_response = sum_response = weak_eval =
subsample_mask = weights = subtree_weights = 0;
train( _train_data, _tflag, _responses, _var_idx, _sample_idx,
_var_type, _missing_mask, _params );
}
}
bool
@@ -2130,7 +2130,7 @@ CvBoost::predict( const Mat& _sample, const Mat& _missing,
weak_count = weak->total;
slice.start_index = 0;
}
if( !(weak_responses->data && weak_responses->type() == CV_32FC1 &&
(weak_responses->cols == 1 || weak_responses->rows == 1) &&
weak_responses->cols + weak_responses->rows - 1 == weak_count) )