return (T) value;
            }
            return (T) Integer.valueOf(value.toString());
        }
        if (clazz.isAssignableFrom(Double.class)) {
            if (value instanceof Double) {
                return (T) value;
            }
            return (T) Double.valueOf(value.toString());
        }
        if (clazz.isAssignableFrom(Float.class)) {
            if (value instanceof Float) {

    public void setHitCount_PercentileRanks(double[] values) {
        setHitCount_PercentileRanks(values, null);
    }

    public void setHitCount_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setHitCount_PercentileRanks("hitCount", values, opLambda);
    }

   * #create(Funnel, int, double)}, or smaller. If it is significantly higher, it is usually the
   * case that too many elements (more than expected) have been put in the {@code BloomFilter},
   * degenerating it.
   *
   * @since 14.0 (since 11.0 as expectedFalsePositiveProbability())
   */
  public double expectedFpp() {
    return Math.pow((double) bits.bitCount() / bitSize(), numHashFunctions);
  }

    // seem to be a worthwhile tradeoff in a browser.
    return matcher;
  }

  static String formatCompact4Digits(double value) {
    return toPrecision(value, 4);
  }

  @JsMethod(name = "Number.prototype.toPrecision.call", namespace = JsPackage.GLOBAL)
  private static native String toPrecision(double value, int precision);

  @JsMethod
  static native boolean stringIsNullOrEmpty(@Nullable String string) /*-{

		{"a/b/c/", false},
		{"../../etc", false},
		{"../../", false},
		{"/../../etc", false},
		{" ../etc", false},
		{"./././", false},
		{"./etc", false},
		{`contains//double/forwardslash`, false},
		{`//contains/double-forwardslash-prefix`, false},
		{string([]byte{0xff, 0xfe, 0xfd}), false},
	}

	for i, testCase := range testCases {
		isValidObjectName := IsValidObjectName(testCase.objectName)

    public void setGidNumber_PercentileRanks(double[] values) {
        setGidNumber_PercentileRanks(values, null);
    }

    public void setGidNumber_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setGidNumber_PercentileRanks("gidNumber", values, opLambda);
    }

    public void setGidNumber_PercentileRanks(String name, double[] values,

          } else {
            diff[k] += 1;
          }
        }
      }
      // measure probability and assert it's within margin of error
      for (int j = 0; j < hashBits; j++) {
        double prob = (double) diff[j] / (double) (diff[j] + same[j]);
        assertThat(prob).isWithin(epsilon).of(0.50d);
      }
    }
  }

  /**

// Create 1 dimensional tensor with values from `values`
TF_Tensor* Int32Tensor(const std::vector<int32_t>& values);

TF_Tensor* Int32Tensor(int32_t v);

TF_Tensor* DoubleTensor(double v);

TF_Tensor* FloatTensor(float v);

TF_Operation* Placeholder(TF_Graph* graph, TF_Status* s,
                          const char* name = "feed",
                          TF_DataType dtype = TF_INT32,

            return ((Long) value).floatValue();
        }
        if (value instanceof Float) {
            return (Float) value;
        }
        if (value instanceof Double) {
            return ((Double) value).floatValue();
        }
        if (value != null) {
            return Float.parseFloat(value.toString());
        }

        return 0.0f;
    }

    public void setCreatedTime_PercentileRanks(double[] values) {
        setCreatedTime_PercentileRanks(values, null);
    }

    public void setCreatedTime_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setCreatedTime_PercentileRanks("createdTime", values, opLambda);
    }

    public void setCreatedTime_PercentileRanks(String name, double[] values,