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update documentation

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Signed-off-by: Krishna Vedala <7001608+kvedala@users.noreply.github.com>
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Krishna Vedala 2020-06-13 18:25:55 -04:00
parent e8cebc36b2
commit 8d2ca00459
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1 changed files with 14 additions and 11 deletions
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machine_learning/kohonen_som_image.c
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@ -15,7 +15,7 @@
* src="https://raw.githubusercontent.com/kvedala/C/docs/images/machine_learning/kohonen/2D_Kohonen_SOM.svg" * src="https://raw.githubusercontent.com/kvedala/C/docs/images/machine_learning/kohonen/2D_Kohonen_SOM.svg"
* /> * />
*/ */
#define _USE_MATH_DEFINES // required for MS Visual C #define _USE_MATH_DEFINES /**< required for MS Visual C */
#include <math.h> #include <math.h>
#include <stdio.h> #include <stdio.h>
#include <stdlib.h> #include <stdlib.h>
@ -24,14 +24,16 @@
#include <omp.h> #include <omp.h>
#endif #endif
#define max(a, b) (a > b ? a : b) // shorthand for maximum value #define max(a, b) (a > b ? a : b) /**< shorthand for maximum value */
#define min(a, b) (a < b ? a : b) // shorthand for minimum value #define min(a, b) (a < b ? a : b) /**< shorthand for minimum value */
/** to store info regarding 3D arrays */ /** to store info regarding 3D arrays */
struct array_3d struct array_3d
{ {
int dim1, dim2, dim3; /**< lengths of each dimension */ int dim1; /**< lengths of first dimension */
double *data; /**< pointer to data */ int dim2; /**< lengths of second dimension */
int dim3; /**< lengths of thirddimension */
double *data; /**< pointer to data */
}; };
/** Function that returns the pointer to (x, y, z) ^th location in the /** Function that returns the pointer to (x, y, z) ^th location in the
@ -145,9 +147,9 @@ int save_u_matrix(const char *fname, struct array_3d *W)
#ifdef _OPENMP #ifdef _OPENMP
#pragma omp parallel for reduction(+ : distance) #pragma omp parallel for reduction(+ : distance)
#endif #endif
for (l = from_x; l < to_x; l++) for (l = from_x; l < to_x; l++) // scan neighborhoor in x
{ {
for (int m = from_y; m < to_y; m++) for (int m = from_y; m < to_y; m++) // scan neighborhood in y
{ {
double d = 0.f; double d = 0.f;
for (k = 0; k < W->dim3; k++) // for each feature for (k = 0; k < W->dim3; k++) // for each feature
@ -179,7 +181,8 @@ int save_u_matrix(const char *fname, struct array_3d *W)
* \param[in] X matrix to search * \param[in] X matrix to search
* \param[in] N number of points in the vector * \param[in] N number of points in the vector
* \param[out] val minimum value found * \param[out] val minimum value found
* \param[out] idx index where minimum value was found * \param[out] idx_x x-index where minimum value was found
* \param[out] idx_y y-index where minimum value was found
*/ */
void get_min_2d(double **X, int N, double *val, int *x_idx, int *y_idx) void get_min_2d(double **X, int N, double *val, int *x_idx, int *y_idx)
{ {
@ -296,8 +299,8 @@ void kohonen_som(double **X, struct array_3d *W, int num_samples,
double dmin = 1.f; double dmin = 1.f;
// Loop alpha from 1 to slpha_min // Loop alpha from 1 to slpha_min
for (double alpha = 1.f; alpha > alpha_min && dmin > 1e-9; for (double alpha = 1.f; alpha > alpha_min && dmin > 1e-10;
alpha -= 0.005, iter++) alpha -= 0.001, iter++)
{ {
dmin = 0.f; dmin = 0.f;
// Loop for each sample pattern in the data set // Loop for each sample pattern in the data set
@ -309,7 +312,7 @@ void kohonen_som(double **X, struct array_3d *W, int num_samples,
} }
// every 20th iteration, reduce the neighborhood range // every 20th iteration, reduce the neighborhood range
if (iter % 20 == 0 && R > 0) if (iter % 50 == 0 && R > 1)
R--; R--;
dmin /= num_samples; dmin /= num_samples;