// If it won't fit in a long, then we store off the intermediate product.
      if (normalizedBits + productBits >= Long.SIZE) {
        bignums.add(BigInteger.valueOf(product));
        product = 1;
        productBits = 0;
      }
      product *= normalizedNum;
      productBits = LongMath.log2(product, FLOOR) + 1;
    }
    // Check for leftovers.
    if (product > 1) {
      bignums.add(BigInteger.valueOf(product));
    }

   * }
   * }
   *
   * <p>Note that if any input list is empty, the Cartesian product will also be empty. If no lists
   * at all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of lists of size {@code m, n, p} is a

    // vol. 2, Knuth, 4.2.2, (16) to the two-variable case. We have two value series x_i and y_i.
    // We define the arithmetic means X_n = 1/n \sum_{i=1}^n x_i, and Y_n = 1/n \sum_{i=1}^n y_i.
    // We also define the sum of the products of the differences from the means
    //           C_n = \sum_{i=1}^n x_i y_i - n X_n Y_n
    // for all n >= 1. Then for all n > 1:
    //       C_{n-1} = \sum_{i=1}^{n-1} x_i y_i - (n-1) X_{n-1} Y_{n-1}

   * }
   * }
   *
   * <p>Note that if any input set is empty, the Cartesian product will also be empty. If no sets at
   * all are provided (an empty list), the resulting Cartesian product has one element, an empty
   * list (counter-intuitive, but mathematically consistent).
   *
   * <p><i>Performance notes:</i> while the cartesian product of sets of size {@code m, n, p} is a

*[Fess Site Search](https://github.com/codelibs/fess-site-search)* is a free alternative to [Google Site Search](https://enterprise.google.com/search/products/gss.html). For more details, see the [FSS JS Generator documentation](https://fss-generator.codelibs.org/docs/manual).

## Website

[fess.codelibs.org](https://fess.codelibs.org/)

## Issues/Questions

    checkState(count() > 1);
    return sumOfProductsOfDeltas / (count() - 1);
  }

  /**
   * Returns the <a href="http://mathworld.wolfram.com/CorrelationCoefficient.html">Pearson's or
   * product-moment correlation coefficient</a> of the values. The count must greater than one, and
   * the {@code x} and {@code y} values must both have non-zero population variance (i.e. {@code

        axesSizeProduct[i] = Math.multiplyExact(axesSizeProduct[i + 1], axes.get(i).size());
      }
    } catch (ArithmeticException e) {
      throw new IllegalArgumentException(
          "Cartesian product too large; must have size at most Integer.MAX_VALUE");
    }
    this.axesSizeProduct = axesSizeProduct;
  }

  private int getAxisIndexForProductIndex(int index, int axis) {

    assertThrows(IllegalArgumentException.class, () -> Sets.newSetFromMap(map));
  }

  /** The 0-ary cartesian product is a single empty list. */
  public void testCartesianProduct_zeroary() {
    assertThat(cartesianProduct()).containsExactly(list());
  }

  /** A unary cartesian product is one list of size 1 for each element in the input set. */
  public void testCartesianProduct_unary() {

     *
     * @return The minor version number.
     */
    public int getMinorVersion() {
        return minorVersion;
    }

    /**
     * Gets the product version string.
     *
     * @return The product version string.
     */
    public String getProductVersion() {
        return productVersion;
    }

    /**
     * Sets the interval for checking the system CPU load.

        // CSV with numbers and mixed data types - quoted fields keep quotes
        value = "123,\"Product Name\",45.67,\"Description with, comma\"";
        result = KuromojiCSVUtil.parse(value);
        assertEquals(4, result.length);
        assertEquals("123", result[0]);
        assertEquals("Product Name", result[1]);
        assertEquals("45.67", result[2]);
        assertEquals("\"Description with, comma\"", result[3]);