public static RealMatrix stochasticSubmatrix(RealMatrix data, int batch_size, Random rng) {
// assume all data has the size number_samples by number_features
int num_samples = data.getRowDimension();
int num_features = data.getColumnDimension();
int batch_num = num_samples / batch_size + 1;
// randomly generate a batch index
int batch_index = rng.nextInt(batch_num);
List<Integer> rowIndex_tmp = new ArrayList<Integer>();
for (int i = 0; i < batch_size; i++) {
if (batch_size * batch_index + i >= num_samples) {
break;
} else {
rowIndex_tmp.add(batch_size * batch_index + i);
}
}
int[] rowIndex = TypeConvert.ArrayTointv(rowIndex_tmp);
// System.out.println(rowIndex_tmp);
int[] columnIndex = new int[num_features];
for (int j = 0; j < num_features; j++) {
columnIndex[j] = j;
}
// System.out.println(batch_index);
// return null;
return data.getSubMatrix(rowIndex, columnIndex);
}
protected void writeEventStream(Payload payload) throws IOException {
PrintStream printStream = new PrintStream(response.outputStream());
try (Stream<?> stream = (Stream<?>) payload.rawContent()) {
stream.forEach(
item -> {
String jsonOrPlainString =
(item instanceof String) ? (String) item : TypeConvert.toJson(item);
printStream
.append("data: ")
.append(jsonOrPlainString.replaceAll("[\n]", "\ndata: "))
.append("\n\n")
.flush();
});
}
}