* or implied. See the License for the specific language governing permissions and limitations under
 * the License.
 */

/*
 * SipHash-c-d was designed by Jean-Philippe Aumasson and Daniel J. Bernstein and is described in
 * "SipHash: a fast short-input PRF" (available at https://131002.net/siphash/siphash.pdf).
 */

package com.google.common.hash;

/**
 * A request to configure a bean from some configuration in the POM or similar.
 *
 */
public interface BeanConfigurationRequest {

    /**
     * Gets the bean to configure. Eventually, a valid request must have a bean set.
     *
     * @return The bean to configure, or {@code null} if none.
     */
    Object getBean();

    /**

        MySingletonBean bean = container.lookup(MySingletonBean.class);
        assertNotNull(bean);
        assertNotNull(bean.anotherBean);
        assertSame(bean.anotherBean.getClass(), AnotherBean.class);
        assertNotNull(bean.myBean);
        assertNotSame(bean.myBean.getClass(), MySessionScopedBean.class);

        assertThrows(OutOfScopeException.class, () -> bean.myBean.getSession());

        SomeBean bean = new SomeBean();

        Xpp3Dom config = toConfig("<file>test</file>");

        DefaultBeanConfigurationRequest request = new DefaultBeanConfigurationRequest();
        request.setBean(bean).setConfiguration(config);

        configurator.configureBean(request);

        assertEquals(Paths.get("test"), bean.file);
    }

    @Test

        twoValuesAccumulator.xStats().mean(),
        twoValuesAccumulator.yStats().mean(),
        twoValuesAccumulator.xStats().populationVariance(),
        twoValuesAccumulator.populationCovariance());
    assertDiagonalLinearTransformation(
        twoValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean(),

        twoValuesAccumulator.xStats().mean(),
        twoValuesAccumulator.yStats().mean(),
        twoValuesAccumulator.xStats().populationVariance(),
        twoValuesAccumulator.populationCovariance());
    assertDiagonalLinearTransformation(
        twoValuesAccumulatorByAddAllPartitionedPairedStats.leastSquaresFit(),
        twoValuesAccumulatorByAddAllPartitionedPairedStats.xStats().mean(),

      }
    }
    assertThat(MANY_VALUES_STATS_ITERABLE.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(MANY_VALUES_STATS_ITERATOR.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(MANY_VALUES_STATS_SNAPSHOT.mean()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MEAN);
    assertThat(LARGE_VALUES_STATS.mean())
        .isWithin(ALLOWED_ERROR * Double.MAX_VALUE)
        .of(LARGE_VALUES_MEAN);

    assertThat(twoValuesAccumulatorByAddAllStats.mean())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_MEAN);
    assertThat(manyValuesAccumulatorByAddAllIterable.mean())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    assertThat(manyValuesAccumulatorByAddAllIterator.mean())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);

        return LinearTransformation.mapping(xStats.mean(), yStats.mean())
            .withSlope(sumOfProductsOfDeltas / xSumOfSquaresOfDeltas);
      } else {
        return LinearTransformation.horizontal(yStats.mean());
      }
    } else {
      checkState(yStats.sumOfSquaresOfDeltas() > 0.0);
      return LinearTransformation.vertical(xStats.mean());
    }
  }

  /**
   * {@inheritDoc}
   *

            dest.put(destPropertyName, convertedValue);
        }
    }

    /**
     * コピー元のBeanを新しいBeanのインスタンスにコピーして返します。
     *
     * @param <T> コピー先となるBeanの型
     * @param src コピー元のBean。{@literal null}であってはいけません
     * @param destClass コピー先となるBeanの型。{@literal null}であってはいけません
     * @return コピーされた新しいBean
     */
    public static <T> T copyBeanToNewBean(final Object src, final Class<T> destClass) {