Example #1
0
        public VectorParameterExpression GetParameter <T>(NArray <T> array)
        {
            var local = array as ILocalNArray;

            if (local != null)
            {
                return(_localParameters[local.Index] as VectorParameterExpression);
            }
            else
            {
                // if the array is a scalar and not an independent variable of any derivative calculation, we do not care where it came from; do not
                // add to argument list
                if (array.IsScalar && !IsIndependentVariable(array))
                {
                    return(new ConstantExpression <T>(array.First()));
                }
                VectorParameterExpression argument;
                // is this fast enough?
                if (!_argumentLookup.TryGetValue(array, out argument))
                {
                    argument = array.IsScalar ? new ReferencingVectorParameterExpression <T>(array.First(), ParameterType.Argument, _argumentLookup.Count)
                        : new ReferencingVectorParameterExpression <T>(array, ParameterType.Argument, _argumentLookup.Count);
                    _argumentLookup.Add(array, argument);
                }
                return(argument);
            }
        }
        public NArray BinaryExpression(NArray operand1, NArray operand2, 
            Func<Expression, Expression, BinaryExpression> operation)
        {
            CheckNArrays(operand1, operand2);
            NArray result;
            ParameterExpression parameterExpression;
            NewLocal(out result, out parameterExpression);

            Expression arg1, arg2;
            arg1 = (operand1.IsScalar) ? (Expression)GetConstant(operand1.First()) : (Expression)GetNArray(operand1);
            arg2 = (operand2.IsScalar) ? (Expression)GetConstant(operand2.First()) : (Expression)GetNArray(operand2);

            _expressions.Add(
                Expression.Assign(parameterExpression,
                operation(arg1, arg2)
            ));

            return result;
        }
Example #3
0
        public NArray BinaryExpression(NArray operand1, NArray operand2,
                                       Func <Expression, Expression, BinaryExpression> operation)
        {
            CheckNArrays(operand1, operand2);
            NArray result;
            ParameterExpression parameterExpression;

            NewLocal(out result, out parameterExpression);

            Expression arg1, arg2;

            arg1 = (operand1.IsScalar) ? (Expression)GetConstant(operand1.First()) : (Expression)GetNArray(operand1);
            arg2 = (operand2.IsScalar) ? (Expression)GetConstant(operand2.First()) : (Expression)GetNArray(operand2);

            _expressions.Add(
                Expression.Assign(parameterExpression,
                                  operation(arg1, arg2)
                                  ));

            return(result);
        }
        /// <summary>
        /// Test of efficiency for a large number of simple vector operations.
        /// In particular, tests enhanced recycling of locals.
        /// </summary>
        public void SimpleTest()
        {
            // create 500 random vectors
            var vectorLength = 5000;
            var vectors      = new NArray[500];

            using (var randomStream = new RandomNumberStream(StorageLocation.Host, RandomNumberGeneratorType.MRG32K3A, 111))
            {
                var normalDistribution = new Normal(randomStream, 0, 1);

                for (int i = 0; i < vectors.Length; ++i)
                {
                    vectors[i] = NArray.CreateRandom(vectorLength, normalDistribution);
                }
            }
            var watch  = new System.Diagnostics.Stopwatch(); watch.Start();
            var result = NArray.CreateLike(vectors.First());

            for (int i = 0; i < vectors.Length; ++i)
            {
                for (int j = 0; j < vectors.Length; ++j)
                {
                    result.Add(vectors[i] * vectors[j] * 123);
                    //result = result + vectors[i] * vectors[j] * 123;
                }
            }
            watch.Stop();
            Console.WriteLine(watch.ElapsedMilliseconds);

            var arrays = vectors.Select(v => (v.Storage as ManagedStorage <double>).Array).ToArray();

            watch.Restart();
            var arrayResult = new double[vectors.First().Length];

            for (int i = 0; i < vectors.Length; ++i)
            {
                for (int j = 0; j < vectors.Length; ++j)
                {
                    for (int k = 0; k < arrayResult.Length; ++k)
                    {
                        arrayResult[k] += arrays[i][k] * arrays[j][k] * 123;
                    }
                }
            }
            watch.Stop();
            Console.WriteLine(watch.ElapsedMilliseconds);

            watch.Restart();
            result = NArray.CreateLike(vectors.First());
            for (int i = 0; i < vectors.Length; ++i)
            {
                var batch = NArray.Evaluate(() =>
                {
                    NArray res = NArray.CreateScalar(0);
                    for (int j = 0; j < vectors.Length; ++j)
                    {
                        res = res + vectors[i] * vectors[j] * 123;
                    }
                    return(res);
                });
                result += batch;
            }
            watch.Stop();
            Console.WriteLine(watch.ElapsedMilliseconds);
        }