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rename save function to nd and added missing time diff computation function

This commit is contained in:
Krishna Vedala 2020-06-03 13:39:26 -04:00
parent 60a768b2a1
commit 46a3707ac8
1 changed files with 28 additions and 14 deletions
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42
machine_learning/kohonen_som.c
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@ -34,16 +34,27 @@ double _random(double a, double b)
}
/**
* Save a given data martix to file.
* Save a given n-dimensional data martix to file.
*
* \param[in] fname filename to save in (gets overwriten without confirmation)
* \param[in] X matrix to save
* \param[in] num_points number of rows in the matrix
* \param[in] num_features number of columns in the matrix
* \param[in] num_points rows in the matrix = number of points
* \param[in] num_features columns in the matrix = dimensions of points
* \returns 0 if all ok
* \returns -1 if file creation failed
*/
void save_2d_data(const char *fname, const double *const *X, int num_points,
int num_features)
int save_nd_data(const char *fname, const double *const *X, int num_points,
int num_features)
{
FILE *fp = fopen(fname, "wt");
if (!fp) // error with fopen
{
char msg[120];
sprintf(msg, "File error (%s): ", fname);
perror(msg);
return -1;
}
for (int i = 0; i < num_points; i++) // for each point in the array
{
for (int j = 0; j < num_features; j++) // for each feature in the array
@ -56,6 +67,7 @@ void save_2d_data(const char *fname, const double *const *X, int num_points,
fprintf(fp, "\n"); // start a new line
}
fclose(fp);
return 0;
}
/**
@ -237,10 +249,11 @@ void test1()
}
test_circle(X, N); // create test data around circumference of a circle
save_2d_data("test1.csv", X, N, 2); // save test data points
save_2d_data("w11.csv", W, num_out, 2); // save initial random weights
kohonen_som_tracer(X, W, N, 2, num_out, 0.1); // train the SOM
save_2d_data("w12.csv", W, num_out, 2); // save the resultant weights
save_nd_data("test1.csv", X, N, features); // save test data points
save_nd_data("w11.csv", W, num_out,
features); // save initial random weights
kohonen_som_tracer(X, W, N, features, num_out, 0.1); // train the SOM
save_nd_data("w12.csv", W, num_out, features); // save the resultant weights
for (int i = 0; i < (num_out > N ? num_out : N); i++)
{
@ -281,7 +294,7 @@ void test_lamniscate(double *const *data, int N)
* that finds that circular 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 circular pattern
* * `test2.csv`: random test samples points with a lamniscate pattern
* * `w21.csv`: initial random map
* * `w22.csv`: trained SOM map
*
@ -319,10 +332,11 @@ void test2()
}
test_lamniscate(X, N); // create test data around the lamniscate
save_2d_data("test2.csv", X, N, 2); // save test data points
save_2d_data("w21.csv", W, num_out, 2); // save initial random weights
kohonen_som_tracer(X, W, N, 2, num_out, 0.01); // train the SOM
save_2d_data("w22.csv", W, num_out, 2); // save the resultant weights
save_nd_data("test2.csv", X, N, features); // save test data points
save_nd_data("w21.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("w22.csv", W, num_out, features); // save the resultant weights
for (int i = 0; i < (num_out > N ? num_out : N); i++)
{