Examples with JSONObject org.apache.wink.json4j.JSONObject used on opensource projects

Example 6 with JSONObject

use of org.apache.wink.json4j.JSONObject in project incubator-systemml by apache.

the class ScalingTest method generateSpecFile.

// ----------------------------
private void generateSpecFile(int cols, String specFile) throws IOException, Exception {
    final String NAME = "name";
    final String METHOD = "method";
    final String SCALE_METHOD_Z = "z-score";
    final String SCALE_METHOD_M = "mean-subtraction";
    JSONObject outputSpec = new JSONObject();
    JSONArray scaleSpec = new JSONArray();
    for (int colID = 1; colID <= cols; colID++) {
        JSONObject obj = new JSONObject();
        obj.put(NAME, "V" + colID);
        if (colID <= cols / 2)
            obj.put(METHOD, SCALE_METHOD_M);
        else
            obj.put(METHOD, SCALE_METHOD_Z);
        scaleSpec.add(obj);
    }
    outputSpec.put(TfUtils.TXMETHOD_SCALE, scaleSpec);
    FileSystem fs = IOUtilFunctions.getFileSystem(specFile);
    try (BufferedWriter out = new BufferedWriter(new OutputStreamWriter(fs.create(new Path(specFile), true)))) {
        out.write(outputSpec.toString());
    }
}

Example 7 with JSONObject

use of org.apache.wink.json4j.JSONObject in project incubator-systemml by apache.

the class Connection method readDoubleMatrix.

// //////////////////////////////////////////
// Read matrices
// //////////////////////////////////////////
/**
 * Reads an input matrix in arbitrary format from HDFS into a dense double array.
 * NOTE: this call currently only supports default configurations for CSV.
 *
 * @param fname the filename of the input matrix
 * @return matrix as a two-dimensional double array
 * @throws IOException if IOException occurs
 */
public double[][] readDoubleMatrix(String fname) throws IOException {
    try {
        // read json meta data
        String fnamemtd = DataExpression.getMTDFileName(fname);
        JSONObject jmtd = new DataExpression().readMetadataFile(fnamemtd, false);
        // parse json meta data
        long rows = jmtd.getLong(DataExpression.READROWPARAM);
        long cols = jmtd.getLong(DataExpression.READCOLPARAM);
        int brlen = jmtd.containsKey(DataExpression.ROWBLOCKCOUNTPARAM) ? jmtd.getInt(DataExpression.ROWBLOCKCOUNTPARAM) : -1;
        int bclen = jmtd.containsKey(DataExpression.COLUMNBLOCKCOUNTPARAM) ? jmtd.getInt(DataExpression.COLUMNBLOCKCOUNTPARAM) : -1;
        long nnz = jmtd.containsKey(DataExpression.READNUMNONZEROPARAM) ? jmtd.getLong(DataExpression.READNUMNONZEROPARAM) : -1;
        String format = jmtd.getString(DataExpression.FORMAT_TYPE);
        InputInfo iinfo = InputInfo.stringExternalToInputInfo(format);
        // read matrix file
        return readDoubleMatrix(fname, iinfo, rows, cols, brlen, bclen, nnz);
    } catch (Exception ex) {
        throw new IOException(ex);
    }
}

Example 8 with JSONObject

use of org.apache.wink.json4j.JSONObject in project incubator-systemml by apache.

the class Connection method readStringFrame.

// //////////////////////////////////////////
// Read frames
// //////////////////////////////////////////
/**
 * Reads an input frame in arbitrary format from HDFS into a dense string array.
 * NOTE: this call currently only supports default configurations for CSV.
 *
 * @param fname the filename of the input frame
 * @return frame as a two-dimensional string array
 * @throws IOException if IOException occurs
 */
public String[][] readStringFrame(String fname) throws IOException {
    try {
        // read json meta data
        String fnamemtd = DataExpression.getMTDFileName(fname);
        JSONObject jmtd = new DataExpression().readMetadataFile(fnamemtd, false);
        // parse json meta data
        long rows = jmtd.getLong(DataExpression.READROWPARAM);
        long cols = jmtd.getLong(DataExpression.READCOLPARAM);
        String format = jmtd.getString(DataExpression.FORMAT_TYPE);
        InputInfo iinfo = InputInfo.stringExternalToInputInfo(format);
        // read frame file
        return readStringFrame(fname, iinfo, rows, cols);
    } catch (Exception ex) {
        throw new IOException(ex);
    }
}

Example 9 with JSONObject

use of org.apache.wink.json4j.JSONObject in project incubator-systemml by apache.

the class Connection method convertToMatrix.

/**
 * Converts an input stream of a string matrix in csv or textcell format
 * into a matrix block. The meta data string is the SystemML generated
 * .mtd file including the number of rows and columns.
 *
 * @param input InputStream to a string matrix in csv or textcell format
 * @param meta string representing SystemML matrix metadata in JSON format
 * @return matrix as a matrix block
 * @throws IOException if IOException occurs
 */
public MatrixBlock convertToMatrix(InputStream input, String meta) throws IOException {
    try {
        // parse json meta data
        JSONObject jmtd = new JSONObject(meta);
        int rows = jmtd.getInt(DataExpression.READROWPARAM);
        int cols = jmtd.getInt(DataExpression.READCOLPARAM);
        String format = jmtd.getString(DataExpression.FORMAT_TYPE);
        // parse the input matrix
        return convertToMatrix(input, rows, cols, format);
    } catch (Exception ex) {
        throw new IOException(ex);
    }
}

Example 10 with JSONObject

use of org.apache.wink.json4j.JSONObject in project incubator-systemml by apache.

the class Connection method convertToFrame.

/**
 * Converts an input stream of a string frame in csv or textcell format
 * into a frame block. The meta data string is the SystemML generated
 * .mtd file including the number of rows and columns.
 *
 * @param input InputStream to a string frame in csv or textcell format
 * @param meta string representing SystemML frame metadata in JSON format
 * @return frame as a frame block
 * @throws IOException if IOException occurs
 */
public FrameBlock convertToFrame(InputStream input, String meta) throws IOException {
    try {
        // parse json meta data
        JSONObject jmtd = new JSONObject(meta);
        int rows = jmtd.getInt(DataExpression.READROWPARAM);
        int cols = jmtd.getInt(DataExpression.READCOLPARAM);
        String format = jmtd.getString(DataExpression.FORMAT_TYPE);
        // parse the input frame
        return convertToFrame(input, rows, cols, format);
    } catch (Exception ex) {
        throw new IOException(ex);
    }
}