diff --git a/machine_learning/kohonen_som_topology.c b/machine_learning/kohonen_som_topology.c index e01f966a..a024ae04 100644 --- a/machine_learning/kohonen_som_topology.c +++ b/machine_learning/kohonen_som_topology.c @@ -28,12 +28,14 @@ #endif #ifndef max -#define max(a, b) (((a) > (b)) ? (a) : (b)) /**< shorthand for maximum value \ - */ +#define max(a, b) \ + (((a) > (b)) ? (a) : (b)) /**< shorthand for maximum value \ + */ #endif #ifndef min -#define min(a, b) (((a) < (b)) ? (a) : (b)) /**< shorthand for minimum value \ - */ +#define min(a, b) \ + (((a) < (b)) ? (a) : (b)) /**< shorthand for minimum value \ + */ #endif /** to store info regarding 3D arrays */ @@ -388,8 +390,8 @@ void test_2d_classes(double *const *data, int N) * The following [CSV](https://en.wikipedia.org/wiki/Comma-separated_values) * files are created to validate the execution: * * `test1.csv`: random test samples points with a circular pattern - * * `w11.csv`: initial random map - * * `w12.csv`: trained SOM map + * * `w11.csv`: initial random U-matrix + * * `w12.csv`: trained SOM U-matrix */ void test1() { @@ -487,9 +489,9 @@ void test_3d_classes1(double *const *data, int N) * 3D space and trains an SOM that finds the topological pattern. The following * [CSV](https://en.wikipedia.org/wiki/Comma-separated_values) files are created * to validate the execution: - * * `test2.csv`: random test samples points with a lamniscate pattern - * * `w21.csv`: initial random map - * * `w22.csv`: trained SOM map + * * `test2.csv`: random test samples points + * * `w21.csv`: initial random U-matrix + * * `w22.csv`: trained SOM U-matrix */ void test2() { @@ -590,9 +592,9 @@ void test_3d_classes2(double *const *data, int N) * 3D space and trains an SOM that finds the topological pattern. The following * [CSV](https://en.wikipedia.org/wiki/Comma-separated_values) files are created * to validate the execution: - * * `test3.csv`: random test samples points with a circular pattern - * * `w31.csv`: initial random map - * * `w32.csv`: trained SOM map + * * `test3.csv`: random test samples points + * * `w31.csv`: initial random U-matrix + * * `w32.csv`: trained SOM U-matrix */ void test3() {