C# Double.Select方法代码示例

        /// <summary>
        /// Gets an array of coefficients that can be used to weight a numerical sequence of the specified length.
        /// The value of an element in the array represents the weighting coefficient for the item at the corresponding index in the sequence.
        /// </summary>
        /// <param name="rateOfChange">The rate at which the ratios change.</param>
        /// <param name="length">The length of the sequence for which weighting coefficients will be returned.</param>
        /// <returns>An array of <paramref name="length"/> length, that contains the weighting coefficients.</returns>
        /// <remarks>
        /// The sum of the array's elements should always equal 1.
        /// When a low value is provided for <paramref name="length"/>, the sum of the array elements is measurably smaller than 1.
        /// Consequently, after all elements in the sequence have been calculated, the remainder is divided equally between all elements such that their sum approaches 1.
        /// </remarks>
        public Double[] GetRatios(Int32 length, Double rateOfChange = 0.5)
        {
            Double[] ratios = new Double[length];
            Double currentAmount = 1;
            for (Int32 i = 0; i < ratios.Length; i++)
            {
                Double currentVal = currentAmount * rateOfChange;
                Double remaining = currentAmount - currentVal;
                currentAmount = remaining;
                ratios[i] = currentVal;
            }

            // As the number of buckets increases, the sum of the buckets approaches 1.
            // When the number of buckets is very small, a significant portion is not represented in the output.
            // To account for this, we split the remaining portion and apply it evenly among every bucket.
            currentAmount /= length;

            // Sometimes Resharper is a little dumb.
            // ReSharper disable once RedundantAssignment
            ratios = ratios.Select(bucket => bucket += currentAmount).ToArray();
            return ratios;
        }

        private static Double[] CalculateNormalizeVector(Double[,] matrix)
        {
            Int32 n = matrix.GetLength(0);

            Double[] notNormalizeVector = new Double[n];

            for (Int32 i = 0; i < n; i++)
            {
                Double tmp = 1;
                for (Int32 j = 0; j < n; j++)
                {
                    tmp *= matrix[i, j];
                }

                notNormalizeVector[i] = Math.Pow(tmp, (Double)1/n);
            }

            Double sumOfVector = notNormalizeVector.Sum();

            Double[] normalizeVector = notNormalizeVector.Select(v => v / sumOfVector).ToArray();

            return normalizeVector;
        }