}

  /** Returns a new bias. */
  private fun adapt(
    delta: Int,
    numpoints: Int,
    first: Boolean,
  ): Int {
    var delta =
      when {
        first -> delta / DAMP
        else -> delta / 2
      }
    delta += (delta / numpoints)
    var k = 0
    while (delta > ((BASE - TMIN) * TMAX) / 2) {
      delta /= (BASE - TMIN)
      k += BASE
    }

        double mean = meanAlgorithm.mean(values);
        double sumOfSquaresOfDeltas = 0.0;
        for (double value : values) {
          double delta = value - mean;
          sumOfSquaresOfDeltas += delta * delta;
        }
        return new MeanAndVariance(mean, sumOfSquaresOfDeltas / values.length);
      }
    },
    KAHAN {
      @Override

    if not verify_password(password, user.hashed_password):
        return False
    return user


def create_access_token(data: dict, expires_delta: Union[timedelta, None] = None):
    to_encode = data.copy()
    if expires_delta:
        expire = datetime.now(timezone.utc) + expires_delta
    else:
        expire = datetime.now(timezone.utc) + timedelta(minutes=15)
    to_encode.update({"exp": expire})

    if not verify_password(password, user.hashed_password):
        return False
    return user


def create_access_token(data: dict, expires_delta: Union[timedelta, None] = None):
    to_encode = data.copy()
    if expires_delta:
        expire = datetime.now(timezone.utc) + expires_delta
    else:
        expire = datetime.now(timezone.utc) + timedelta(minutes=15)
    to_encode.update({"exp": expire})

                        break;
                      case 5:
                        map.getAndAdd(key, delta);
                        threadSum += delta;
                        break;
                      case 6:
                        long oldValue = map.put(key, delta);
                        threadSum += delta - oldValue;
                        break;
                      case 7:

        double mean = meanAlgorithm.mean(values);
        double sumOfSquaresOfDeltas = 0.0;
        for (double value : values) {
          double delta = value - mean;
          sumOfSquaresOfDeltas += delta * delta;
        }
        return new MeanAndVariance(mean, sumOfSquaresOfDeltas / values.length);
      }
    },
    KAHAN {
      @Override

    if not verify_password(password, user.hashed_password):
        return False
    return user


def create_access_token(data: dict, expires_delta: Union[timedelta, None] = None):
    to_encode = data.copy()
    if expires_delta:
        expire = datetime.now(timezone.utc) + expires_delta
    else:
        expire = datetime.now(timezone.utc) + timedelta(minutes=15)
    to_encode.update({"exp": expire})

            Long.MIN_VALUE,
            Long.MAX_VALUE)) {
      for (double delta : Doubles.asList(0.0, 1.0, 2.0)) {
        integralBuilder.addAll(Doubles.asList(d + delta, d - delta, -d - delta, -d + delta));
      }
      for (double delta : Doubles.asList(0.01, 0.1, 0.25, 0.499, 0.5, 0.501, 0.7, 0.8)) {
        double x = d + delta;
        if (x != Math.round(x)) {
          fractionalBuilder.add(x);
        }
      }

                        break;
                      case 5:
                        map.getAndAdd(key, delta);
                        threadSum += delta;
                        break;
                      case 6:
                        long oldValue = map.put(key, delta);
                        threadSum += delta - oldValue;
                        break;
                      case 7:

      // This range is [-5, 4] - slight negative bias so we often hit zero, which brings the
      // auto-removal of zeroes into play.
      int delta = random.nextInt(10) - 5;
      blah += delta;
      if (delta >= 0) {
        multiset.add(key, delta);
      } else {
        multiset.remove(key, -delta);
      }
    }
    return blah;
  }

  private enum MultisetSupplier {
    CONCURRENT_HASH_MULTISET() {