int datasetSize;

  @Param QuantilesAlgorithm algorithm;

  private final double[][] datasets = new double[0x100][];

  @BeforeExperiment
  void setUp() {
    Random rng = new Random();
    for (int i = 0; i < 0x100; i++) {
      datasets[i] = new double[datasetSize];
      for (int j = 0; j < datasetSize; j++) {
        datasets[i][j] = rng.nextDouble();
      }
    }
  }

  private double[] dataset(int i) {

     * @return The data class.
     */
    public Class<?> getDataClass() {
        return dataClass;
    }

    /**
     * Sets the data class.
     * @param dataClass The data class to set.
     */
    public void setDataClass(final Class<?> dataClass) {
        this.dataClass = dataClass;
    }

    }

    /**
     * Returns the dataClass.
     *
     * @return the dataClass
     */
    public Class<?> getDataClass() {
        return dataClass;
    }

    /**
     * Sets the dataClass.
     *
     * @param dataClass the dataClass to set
     */
    public void setDataClass(final Class<?> dataClass) {
        this.dataClass = dataClass;
    }

    /**

You can also use `dataclasses` in the `response_model` parameter:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

     */
    private static byte[] createBuffer(int dataLen, byte[] dataBytes, String params) throws UnsupportedEncodingException {
        final byte[] paramBytes = params.getBytes(SmbConstants.DEFAULT_OEM_ENCODING);
        byte[] buffer = new byte[10 + paramBytes.length + dataLen];
        // copy params
        System.arraycopy(paramBytes, 0, buffer, 10, paramBytes.length);

                dstIndex += 4;
                SMBUtil.writeInt4(0, dst, dstIndex);
                dstIndex += 4; // Reserved
                final int dataLen = size8(nc.encode(dst, dstIndex));
                SMBUtil.writeInt2(dataLen, dst, lenOffset);
                dstIndex += dataLen;
            }
        }
        return dstIndex - start;
    }

    /**
     * {@inheritDoc}
     *

                final int dataLen = SMBUtil.readInt2(buffer, ncpos + 2);

                // Validate context data length
                if (dataLen < 0 || dataLen > 1024) { // 1KB max per context
                    throw new SMBProtocolDecodingException(
                            "Invalid negotiate context data length: " + dataLen + " at position " + i + " (must be 0-1024)");
                }

        // Test when data length exceeds outputBuffer size
        byte[] buffer = new byte[2000];
        int dataLen = outputBuffer.length + 100; // Exceeds outputBuffer size

        SMBProtocolDecodingException exception =
                assertThrows(SMBProtocolDecodingException.class, () -> response.readDataWireFormat(buffer, 0, dataLen));

        assertEquals("Payload exceeds buffer size", exception.getMessage());
    }

				int64(testCase.dataLen), testCase.chunkSize, bytes.NewReader(testCase.data),
				testCase.accessKey, testCase.secretKey)
		case testCase.contentEncoding == "":
			req, err = newTestStreamingSignedRequest(http.MethodPut,
				getPutObjectURL("", testCase.bucketName, testCase.objectName),
				int64(testCase.dataLen), testCase.chunkSize, bytes.NewReader(testCase.data),

  public static LinearTransformation horizontal(double y) {
    checkArgument(isFinite(y));
    double slope = 0.0;
    return new RegularLinearTransformation(slope, y);
  }

  /**
   * Builds an instance for datasets which contains {@link Double#NaN}. The {@link #isHorizontal}
   * and {@link #isVertical} methods return {@code false} and the {@link #slope}, and {@link