Esempio n. 1
0
        /// <summary>Update the buffer <c>Buffer</c>.</summary>
        /// <param name="Buffer">Buffer <c>Buffer</c>.</param>
        /// <param name="list">Incoming message from <c>list</c>.</param>
        /// <param name="IndexOfMaximumDouble">Constant value for <c>indexOfMaximumDouble</c>.</param>
        /// <returns>New value of buffer <c>Buffer</c>.</returns>
        /// <remarks>
        ///   <para />
        /// </remarks>
        /// <typeparam name="GaussianList">The type of an incoming message from <c>list</c>.</typeparam>
        public static IndexOfMaximumBuffer Buffer <GaussianList>(
            IndexOfMaximumBuffer Buffer, GaussianList list, int IndexOfMaximumDouble) // redundant parameters required for correct dependency graph
            where GaussianList : IList <Gaussian>
        {
            var      max_marginal = Buffer.to_list[IndexOfMaximumDouble] * list[IndexOfMaximumDouble];
            Gaussian product      = Gaussian.Uniform();

            //var order = Rand.Perm(list.Count);
            for (int i = 0; i < list.Count; i++)
            {
                //int c = order[i];
                int c = i;
                if (c != IndexOfMaximumDouble)
                {
                    var msg_to_sum = max_marginal / Buffer.MessagesToMax[c];

                    var msg_to_positiveop = DoublePlusOp.AAverageConditional(Sum: msg_to_sum, b: list[c]);
                    var msgFromPositiveOp = IsPositiveOp.XAverageConditional(true, msg_to_positiveop);
                    Buffer.MessagesToMax[c] = DoublePlusOp.SumAverageConditional(list[c], msgFromPositiveOp);
                    Buffer.to_list[c]       = DoublePlusOp.AAverageConditional(Sum: msg_to_sum, b: msgFromPositiveOp);
                    max_marginal            = msg_to_sum * Buffer.MessagesToMax[c];
                    product.SetToProduct(product, Buffer.MessagesToMax[c]);
                }
            }
            //Buffer.to_list[IndexOfMaximumDouble] = max_marginal / list[IndexOfMaximumDouble];
            Buffer.to_list[IndexOfMaximumDouble] = product;
            return(Buffer);
        }
        // redundant parameters required for correct dependency graph
        public static IndexOfMaximumBuffer Buffer <GaussianList>(IndexOfMaximumBuffer Buffer, GaussianList list, int IndexOfMaximumDouble)
            where GaussianList : IList <Gaussian>
        {
            var max_marginal = Buffer.to_list[IndexOfMaximumDouble] * list[IndexOfMaximumDouble];

            //var order = Rand.Perm(list.Count);
            for (int i = 0; i < list.Count; i++)
            {
                //int c = order[i];
                int c = i;
                if (c != IndexOfMaximumDouble)
                {
                    var msg_to_sum = max_marginal / Buffer.MessagesToMax[c];

                    var msg_to_positiveop = DoublePlusOp.AAverageConditional(Sum: msg_to_sum, b: list[c]);
                    var msgFromPositiveOp = IsPositiveOp.XAverageConditional(true, msg_to_positiveop);
                    Buffer.MessagesToMax[c] = DoublePlusOp.SumAverageConditional(list[c], msgFromPositiveOp);
                    Buffer.to_list[c]       = DoublePlusOp.AAverageConditional(Sum: msg_to_sum, b: msgFromPositiveOp);
                    max_marginal            = msg_to_sum * Buffer.MessagesToMax[c];
                }
            }
            Buffer.to_list[IndexOfMaximumDouble] = max_marginal / list[IndexOfMaximumDouble];
            return(Buffer);
        }