updated documentation

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Krishna Vedala 2020-06-10 09:04:43 -04:00
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@ -24,11 +24,14 @@
* \n Steps:
* 1. `r1 = rand() % 100` gets a random number between 0 and 99
* 2. `r2 = r1 / 100` converts random number to be between 0 and 0.99
* 3. scale and offset the random number to given range of \f$[a,b]\f$
* 3. scale and offset the random number to given range of \f$[a,b)\f$
* \f[
* y = (b - a) \times \frac{\text{(random number between 0 and RAND_MAX)} \;
* \text{mod}\; 100}{100} + a \f]
*
* \param[in] a lower limit
* \param[in] b upper limit
* \returns random number in the range \f$[a,b]\f$
* \returns random number in the range \f$[a,b)\f$
*/
double _random(double a, double b)
{
@ -184,7 +187,12 @@ void kohonen_som_tracer(double **X, double *const *W, int num_samples,
/** Creates a random set of points distributed *near* the circumference
* of a circle and trains an SOM that finds that circular pattern. The
* generating function is
* \f{eqnarray*}{ \f}
* \f{eqnarray*}{
* r &\in& [1-\delta r, 1+\delta r)\\
* \theta &\in& [0, 2\pi)\\
* x &=& r\cos\theta\\
* y &=& r\sin\theta
* \f}
*
* \param[out] data matrix to store data in
* \param[in] N number of points required
@ -270,7 +278,16 @@ void test1()
/** 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
* that finds that circular pattern.
* \f{eqnarray*}{
* \delta r &=& 0.2\\
* \delta x &\in& [-\delta r, \delta r)\\
* \delta y &\in& [-\delta r, \delta r)\\
* \theta &\in& [0, \pi)\\
* x &=& \delta x + \cos\theta\\
* y &=& \delta y + \frac{\sin(2\theta)}{2}
* \f}
* \param[out] data matrix to store data in
* \param[in] N number of points required
*/
void test_lamniscate(double *const *data, int N)
@ -354,10 +371,14 @@ 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
/** creates a random set of points distributed in four clusters in
* 3D space with centroids at the points
* * \f$(0,5, 0.5, 0.5)\f$
* * \f$(0,5,-0.5, -0.5)\f$
* * \f$(-0,5, 0.5, 0.5)\f$
* * \f$(-0,5,-0.5, -0.5)\f$
*
* \param[out] data matrix to store data in
* \param[in] N number of points required
*/
void test_3d_classes(double *const *data, int N)