matrix.c

@@ -131,17 +131,4 @@ Matrix multiply(const Matrix matrix1, const Matrix matrix2)
             }
     }
     return result;
-}
-void writeMatrix(Matrix matrix, FILE *file)//Added for neuralNetworkTests
-{
-	//fprintf(file, "%d%d", matrix.rows, matrix.cols);
-	for(int i = 0; i < matrix.rows; i++)
-	{
-		for(int j = 0; j < matrix.cols; j++)
-		{
-			putw(*(matrix.buffer + (j+i)*sizeof(MatrixType)), file);
-			//fprintf(file, "%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
-			printf("%f", *(matrix.buffer + (j+i)*sizeof(MatrixType)));
-		}
-	}
 }

matrix.h

@@ -21,7 +21,6 @@ void setMatrixAt(MatrixType value, Matrix matrix, unsigned int rowIdx, unsigned
 MatrixType getMatrixAt(const Matrix matrix, unsigned int rowIdx, unsigned int colIdx);
 Matrix add(const Matrix matrix1, const Matrix matrix2);
 Matrix multiply(const Matrix matrix1, const Matrix matrix2);
-void writeMatrix(Matrix matrix, FILE *file);//Added for neuralNetworkTests
 
 
 #endif

neuralNetworkTests.c

@@ -4,23 +4,11 @@
 #include <math.h>
 #include "unity.h"
 #include "neuralNetwork.h"
-#include "matrix.h"
 
 
 static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 {
-	FILE *testDatei = fopen(path, "w");
+    // TODO
-	fprintf(testDatei, "__info2_neural_network_file_format__");
-	fprintf(testDatei, "%d%d", nn.layers->weights.rows, nn.layers->weights.cols);
-	// fprintf(testDatei, (char*) nn.numberOfLayers);
-	for(int i = 0; i < nn.numberOfLayers; i++)
-	{
-		//fprintf(testDatei, "\n");
-		//putw((nn.layers + sizeof(Layer) * i), testDatei);
-		writeMatrix(nn.layers[i].weights, testDatei);
-		writeMatrix(nn.layers[i].biases, testDatei);
-	}
-	fclose(testDatei);
 }
 
 void test_loadModelReturnsCorrectNumberOfLayers(void)
@@ -43,7 +31,7 @@ void test_loadModelReturnsCorrectNumberOfLayers(void)
 
     netUnderTest = loadModel(path);
     remove(path);
-	printf("\n%d\n%d\n", netUnderTest.numberOfLayers, expectedNet.numberOfLayers);
+
     TEST_ASSERT_EQUAL_INT(expectedNet.numberOfLayers, netUnderTest.numberOfLayers);
     clearModel(&netUnderTest);
 }