func cNodes(nodes []FeatureValue) *C.feature_node_t {
n := newNodes(C.size_t(len(nodes)))
for idx, val := range nodes {
C.nodes_put(n, C.size_t(idx), C.int(val.Index), C.double(val.Value))
}
return n
}
func (problem *Problem) Add(trainInst TrainingInstance) {
features := sortedFeatureVector(trainInst.Features)
nodes := C.nodes_new(C.size_t(len(features)))
for idx, val := range features {
C.nodes_put(nodes, C.size_t(idx), C.int(val.Index), C.double(val.Value))
}
C.problem_add_train_inst(problem.problem, nodes, C.double(trainInst.Label))
}
func (problem *Problem) AddManySorted(trainInsts []TrainingInstance) error {
for _, trainInst := range trainInsts {
if err := verifyFeatureIndices(trainInst.Features); err != nil {
return err
}
}
//nodesArr := make([][]C.feature_node_t, len(trainInsts))
nodesArr := make([]*C.feature_node_t, len(trainInsts))
for i, nodes := range trainInsts {
//nodesArr[i] = make([]C.feature_node_t, len(nodes.Features) + 1)
//nodesArr[i][len(nodesArr[i])-1].index = -1
//nodesArr[i][len(nodesArr[i])-1].value = 0.0
nodesArr[i] = newNodes(C.size_t(len(nodes.Features)))
//fmt.Printf("%v ", nodesArr[i][len(nodesArr[i])-1])
}
fmt.Println()
for _, nodes := range nodesArr {
problem.insts = append(problem.insts, nodes)
}
for i, inst := range trainInsts {
nodes := nodesArr[i]
for idx, val := range inst.Features {
//nodes[idx].index = C.int(val.Index)
//nodes[idx].value = C.double(val.Value)
C.nodes_put(nodes, C.size_t(idx), C.int(val.Index), C.double(val.Value))
}
}
labels := make([]C.double, len(trainInsts))
for i, inst := range trainInsts {
labels[i] = C.double(inst.Label)
}
/*
nodePtrs := make([]*C.feature_node_t, len(trainInsts))
for i, val := range nodesArr {
nodePtrs[i] = &val[0]
}
*/
C.problem_add_train_insts(problem.problem, &nodesArr[0], C.size_t(len(nodesArr)), &labels[0])
return nil
}
// Add adds a training instance to the problem.
func (problem *Problem) Add(trainInst TrainingInstance) error {
if err := verifyFeatureIndices(trainInst.Features); err != nil {
return err
}
features := sortedFeatureVector(trainInst.Features)
nodes := newNodes(C.size_t(len(features)))
problem.insts = append(problem.insts, nodes)
for idx, val := range features {
C.nodes_put(nodes, C.size_t(idx), C.int(val.Index), C.double(val.Value))
}
C.problem_add_train_inst(problem.problem, nodes, C.double(trainInst.Label))
return nil
}
