Пример #1
0
        /// <summary>
        /// Calculates the weighted sum on the columns of data.
        /// </summary>
        /// <param name="data">The data columns to calculate on.</param>
        /// <param name="weight">The weights to use on the data columns (must be length data.Rows).</param>
        /// <returns>The sum vectorT.</returns>
        public static vectorT Sum(matrix data, vector weight)
        {
            var r = new vectorT(data.Cols);

            ThrowHelper.Check(Vsl.SumWeighted(data.Rows, data.Cols, data.Array, weight.Array, r.Array));
            return(r);
        }
Пример #2
0
        /// <summary>
        /// Calculates the median on the columns of data.
        /// </summary>
        /// <param name="data">The data columns to calculate on.</param>
        /// <returns>The median vectorT.</returns>
        public static vectorT Median(matrix data)
        {
            var r = new vectorT(data.Cols);

            ThrowHelper.Check(Vsl.Median(data.Rows, data.Cols, data.Array, r.Array));
            return(r);
        }
Пример #3
0
        /// <summary>
        /// Calculates the weighted correlation on the columns of data.
        /// </summary>
        /// <param name="data">The data columns to calculate on.</param>
        /// <param name="weight">The weights to use on the data columns (must be length data.Rows).</param>
        /// <param name="mean">The calculated mean.</param>
        /// <returns>data.Cols x data.Cols matrix.</returns>
        public static matrix Correlation(matrix data, vector weight, out vectorT mean)
        {
            mean = new vectorT(data.Cols);
            var cor = new matrix(data.Cols, data.Cols);

            ThrowHelper.Check(Vsl.CorrelationWeighted(data.Rows, data.Cols, data.Array, weight.Array, mean.Array, cor.Array));
            return(cor);
        }
Пример #4
0
        /// <summary>
        /// Calculates the weighted covariance on the columns of data.
        /// </summary>
        /// <param name="data">The data columns to calculate on.</param>
        /// <param name="weight">The weights to use on the data columns (must be length data.Rows).</param>
        /// <param name="mean">The calculated mean.</param>
        /// <returns>data.Cols x data.Cols matrix.</returns>
        public static matrix Covariance(matrix data, vector weight, out vectorT mean)
        {
            mean = new vectorT(data.Cols);
            var cov = new matrix(data.Cols, data.Cols);

            ThrowHelper.Check(Vsl.CovarianceWeighted(data.Rows, data.Cols, data.Array, weight.Array, mean.Array, cov.Array));
            return(cov);
        }
Пример #5
0
        /// <summary>
        /// Calculates the weighted median and MAD on the columns of data.
        /// </summary>
        /// <param name="data">The data columns to calculate on.</param>
        /// <param name="weight">The weights to use on the data columns (must be length data.Rows).</param>
        /// <param name="mad">The calculated MAD.</param>
        /// <returns>The median vectorT.</returns>
        public static vectorT MedianMAD(matrix data, vector weight, out vectorT mad)
        {
            var median = new vectorT(data.Cols);

            mad = new vectorT(data.Cols);
            ThrowHelper.Check(Vsl.MedianMADWeighted(data.Rows, data.Cols, data.Array, weight.Array, median.Array, mad.Array));
            return(median);
        }
Пример #6
0
 public VectorTReuse(vectorT a) => V = a;
Пример #7
0
 public VectorTInput(vectorT a) => V = a;