/**
* Create DMatrix from Sparse matrix in CSR/CSC format.
*
* @param headers The row index of the matrix.
* @param indices The indices of presenting entries.
* @param data The data content.
* @param st Type of sparsity.
* @throws XGBoostError
*/
public DMatrix(long[] headers, int[] indices, float[] data, SparseType st) throws XGBoostError {
long[] out = new long[1];
if (st == SparseType.CSR) {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromCSR(headers, indices, data, out));
} else if (st == SparseType.CSC) {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromCSC(headers, indices, data, out));
} else {
throw new UnknownError("unknow sparsetype");
}
handle = out[0];
}
/**
* Slice the DMatrix and return a new DMatrix that only contains `rowIndex`.
*
* @param rowIndex row index
* @return sliced new DMatrix
* @throws XGBoostError native error
*/
public DMatrix slice(int[] rowIndex) throws XGBoostError {
long[] out = new long[1];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixSliceDMatrix(handle, rowIndex, out));
long sHandle = out[0];
DMatrix sMatrix = new DMatrix(sHandle);
return sMatrix;
}
/**
* Create DMatrix by loading libsvm file from dataPath
*
* @param dataPath The path to the data.
* @throws XGBoostError
*/
public DMatrix(String dataPath) throws XGBoostError {
if (dataPath == null) {
throw new NullPointerException("dataPath: null");
}
long[] out = new long[1];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromFile(dataPath, 1, out));
handle = out[0];
}
/**
* Create DMatrix from iterator.
*
* @param iter The data iterator of mini batch to provide the data.
* @param cacheInfo Cache path information, used for external memory setting, can be null.
* @throws XGBoostError
*/
public DMatrix(Iterator<LabeledPoint> iter, String cacheInfo) throws XGBoostError {
if (iter == null) {
throw new NullPointerException("iter: null");
}
// 32k as batch size
int batchSize = 32 << 10;
Iterator<DataBatch> batchIter = new DataBatch.BatchIterator(iter, batchSize);
long[] out = new long[1];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromDataIter(batchIter, cacheInfo, out));
handle = out[0];
}
public synchronized void dispose() {
if (handle != 0) {
XGBoostJNI.XGDMatrixFree(handle);
handle = 0;
}
}
/** save DMatrix to filePath */
public void saveBinary(String filePath) {
XGBoostJNI.XGDMatrixSaveBinary(handle, filePath, 1);
}
/**
* get the row number of DMatrix
*
* @return number of rows
* @throws XGBoostError native error
*/
public long rowNum() throws XGBoostError {
long[] rowNum = new long[1];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixNumRow(handle, rowNum));
return rowNum[0];
}
/**
* Set group sizes of DMatrix (used for ranking)
*
* @param group group size as array
* @throws XGBoostError native error
*/
public void setGroup(int[] group) throws XGBoostError {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixSetGroup(handle, group));
}
private int[] getIntInfo(String field) throws XGBoostError {
int[][] infos = new int[1][];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixGetUIntInfo(handle, field, infos));
return infos[0];
}
/**
* if specified, xgboost will start from this init margin can be used to specify initial
* prediction to boost from
*
* @param baseMargin base margin
* @throws XGBoostError native error
*/
public void setBaseMargin(float[] baseMargin) throws XGBoostError {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixSetFloatInfo(handle, "base_margin", baseMargin));
}
/**
* set weight of each instance
*
* @param weights weights
* @throws XGBoostError native error
*/
public void setWeight(float[] weights) throws XGBoostError {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixSetFloatInfo(handle, "weight", weights));
}
/**
* set label of dmatrix
*
* @param labels labels
* @throws XGBoostError native error
*/
public void setLabel(float[] labels) throws XGBoostError {
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixSetFloatInfo(handle, "label", labels));
}
/**
* create DMatrix from dense matrix
*
* @param data data values
* @param nrow number of rows
* @param ncol number of columns
* @throws XGBoostError native error
*/
public DMatrix(float[] data, int nrow, int ncol) throws XGBoostError {
long[] out = new long[1];
JNIErrorHandle.checkCall(XGBoostJNI.XGDMatrixCreateFromMat(data, nrow, ncol, 0.0f, out));
handle = out[0];
}
/**
* Check the return value of C API.
*
* @param ret return valud of xgboostJNI C API call
* @throws XGBoostError native error
*/
static void checkCall(int ret) throws XGBoostError {
if (ret != 0) {
throw new XGBoostError(XGBoostJNI.XGBGetLastError());
}
}
