Esempio n. 1
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        private static MathData GetMathData(string dataRoot, string gradientEoot)
        {
            var input        = ReadCsv(dataRoot);
            var inputMatrix  = DenseMatrix.OfColumnArrays(input);
            var output       = ReadCsv(gradientEoot);
            var outputMatrix = DenseMatrix.OfColumnArrays(output);
            var result       = new MathData(inputMatrix, outputMatrix);

            return(result);
        }
Esempio n. 2
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        public void AddingOperationBigInt()
        {
            //Arrange
            MathData mathData = new MathData(30000, 35000, "+");
            //Act
            var result = Calculations.DoMath(mathData);

            //Assert
            Assert.AreEqual(65000, result);
        }
Esempio n. 3
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        public void AddingOperationMaxInt()
        {
            //Arrange
            MathData mathData = new MathData(int.MaxValue, int.MinValue, "+");
            //Act
            var result = Calculations.DoMath(mathData);

            //Assert
            Assert.AreEqual(-1, result);
        }
Esempio n. 4
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        public void AddingOperationNegativeValues()
        {
            //Arrange
            MathData mathData = new MathData(-5, -4, "+");
            //Act
            var result = Calculations.DoMath(mathData);

            //Assert
            Assert.AreEqual(-9, result);
        }
Esempio n. 5
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        public void AddingOperationPositiveValues(int a, int b, int x)
        {
            //Arrange
            MathData mathData = new MathData(a, b, "+");
            //Act
            var result = Calculations.DoMath(mathData);

            //Assert
            Assert.AreEqual(x, result);
        }
Esempio n. 6
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    public override void OnInspectorGUI()
    {
        MathData myTarget = (MathData)target;

        DrawDefaultInspector();

        if (GUILayout.Button("Build Object"))
        {
            myTarget.CreateData();
        }
    }
Esempio n. 7
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        public void AddingOperation_Positive_Negative_Values()
        {
            // Arrange
            MathData mathData = new MathData(1, -1, "+");

            // Act
            var result = Calculations.DoMath(mathData);

            // Assert
            Assert.AreEqual(0, result);
        }
Esempio n. 8
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        public void AddingOperation_Positive_Values(int firstValue, int secondValue, int expectedResult)
        {
            // Arrange
            MathData mathData = new MathData(firstValue, secondValue, "+");

            // Act
            var result = Calculations.DoMath(mathData);

            // Assert
            Assert.AreEqual(expectedResult, result);
        }
Esempio n. 9
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 static void Main(string[] args)
 {
     using (TotalMathClient proxy = new TotalMathClient())
     {
         MathData data = proxy.Calculate(15, 3);
         Console.WriteLine($"Add {data.resAdd}");
         Console.WriteLine($"Sub {data.resSub}");
         Console.WriteLine($"Mult {data.resMult}");
         Console.WriteLine($"Div {data.resDiv}");
     }
 }
Esempio n. 10
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        public void AddingOperation_PositiveValue(int firstValue, int secondValue, int expectedResult)
        {
            //Arrange - przygotowujemy dane
            MathData mathData = new MathData(firstValue, secondValue, "+");

            //Act - to co testujemy
            var result = Calculations.GetResultValue(mathData);

            //Assert - robimy asercję
            Assert.AreEqual(expectedResult, result);
        }
Esempio n. 11
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        public double[] Test(MathData data)
        {
            Network.BatchSize = 1;
            Network.Mode      = Mode.Evaluation;
            var inputs      = data.Inputs;
            var outputs     = data.Outputs;
            int totalInputs = inputs.ColumnCount;
            int entrySize   = inputs.RowCount;
            var errors      = new double[totalInputs];

            for (int i = 0; i < totalInputs; i++)
            {
                var inputValues = inputs.SubMatrix(0, entrySize, i, 1);
                Network.Propagate(inputValues);
                var expectedOutput = outputs[0, i];
                var actualOutput   = Network.Output[0, 0];
                errors[i] = EvaluationFunction.EvaluateError(expectedOutput, actualOutput);
            }
            return(errors);
        }