added 3D test case

This commit is contained in:
Krishna Vedala 2020-06-03 13:39:41 -04:00
parent 46a3707ac8
commit fcf1b5ab91
1 changed files with 114 additions and 0 deletions

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@ -349,6 +349,115 @@ void test2()
free(W);
}
/** Creates a random set of points distributed *near* the locus
* of the [Lamniscate of
* Gerono](https://en.wikipedia.org/wiki/Lemniscate_of_Gerono) and trains an SOM
* that finds that circular pattern. \param[out] data matrix to store data in
* \param[in] N number of points required
*/
void test_3d_classes(double *const *data, int N)
{
const double R = 0.1; // radius of cluster
int i;
const int num_classes = 4;
const double centres[][3] = {
// centres of each class cluster
{.5, .5, .5}, // centre of class 1
{.5, -.5, -.5}, // centre of class 2
{-.5, .5, .5}, // centre of class 3
{-.5, -.5 - .5} // centre of class 4
};
#ifdef _OPENMP
#pragma omp for
#endif
for (i = 0; i < N; i++)
{
int class = rand() % num_classes; // select a random class for the point
// create random coordinates (x,y,z) around the centre of the class
data[i][0] = _random(centres[class][0] - R, centres[class][0] + R);
data[i][1] = _random(centres[class][1] - R, centres[class][1] + R);
data[i][2] = _random(centres[class][2] - R, centres[class][2] + R);
/* The follosing can also be used
for (int j = 0; j < 3; j++)
data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);
*/
}
}
/** Test that creates a random set of points distributed in six clusters in
* 3D space. 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
*
* The outputs can be readily plotted in [gnuplot](https:://gnuplot.info) using
* the following snippet
* ```gnuplot
* set datafile separator ','
* plot "test3.csv" title "original", \
* "w31.csv" title "w1", \
* "w32.csv" title "w2"
* ```
*/
void test3()
{
int j, N = 200;
int features = 3;
int num_out = 20;
double **X = (double **)malloc(N * sizeof(double *));
double **W = (double **)malloc(num_out * sizeof(double *));
for (int i = 0; i < (num_out > N ? num_out : N); i++)
{
if (i < N) // only add new arrays if i < N
X[i] = (double *)malloc(features * sizeof(double));
if (i < num_out) // only add new arrays if i < num_out
{
W[i] = (double *)malloc(features * sizeof(double));
#ifdef _OPENMP
#pragma omp for
#endif
// preallocate with random initial weights
for (j = 0; j < features; j++)
W[i][j] = _random(-1, 1);
}
}
test_3d_classes(X, N); // create test data around the lamniscate
save_nd_data("test3.csv", X, N, features); // save test data points
save_nd_data("w31.csv", W, num_out,
features); // save initial random weights
kohonen_som_tracer(X, W, N, features, num_out, 0.01); // train the SOM
save_nd_data("w32.csv", W, num_out, features); // save the resultant weights
for (int i = 0; i < (num_out > N ? num_out : N); i++)
{
if (i < N)
free(X[i]);
if (i < num_out)
free(W[i]);
}
free(X);
free(W);
}
/**
* Convert clock cycle difference to time in seconds
*
* \param[in] start_t start clock
* \param[in] start_t end clock
* \returns time difference in seconds
*/
inline double get_clock_diff(clock_t start_t, clock_t end_t)
{
return (double)(end_t - start_t) / (double)CLOCKS_PER_SEC;
}
/** Main function */
int main(int argc, char **argv)
{
@ -367,6 +476,11 @@ int main(int argc, char **argv)
end_clk = clock();
printf("Test 2 completed in %.4g sec\n",
get_clock_diff(start_clk, end_clk));
start_clk = clock();
test3();
end_clk = clock();
printf("Test 3 completed in %.4g sec\n",
get_clock_diff(start_clk, end_clk));
printf("(Note: Calculated times include: creating test sets, training "
"model and writing files to disk.)\n\n");
return 0;