Add Doxygen Documentation for Environment

Add Doxygen Doc. for Environment

**Self evaluation:**
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Signed-off-by: jijoong.moon <jijoong.moon@samsung.com>

diff --git a/Environment/CartPole/cartpole.cpp b/Environment/CartPole/cartpole.cpp
index 0f31d09..2ef1d8c 100644 (file)
--- a/Environment/CartPole/cartpole.cpp
+++ b/Environment/CartPole/cartpole.cpp
@@ -1,12 +1,27 @@
+/**
+ * @file       cartpole.cpp
+ * @date       04 December 2019
+ * @brief      This is environment class for cartpole example
+ * @see                https://github.sec.samsung.net/jijoong-moon/Transfer-Learning.git
+ * @author     Jijoong Moon <jijoong.moon@samsung.com>
+ * @bug                No known bugs except for NYI items
+ *
+ */
 #include "cartpole.h"
 #include <stdlib.h>
 
 #define M_PI 3.14159265358979323846
 
-static double RandomDouble(double min, double max) {
-  return min + ((double)rand() / (RAND_MAX / (max - min)));
-}
+/**
+ * @brief     Generate Random Double value between min to max
+ * @retval    random value
+ */
+static double RandomDouble(double min, double max) { return min + ((double)rand() / (RAND_MAX / (max - min))); }
 
+/**
+ * @brief     Generate Random integer 0 or 1
+ * @retval    random value
+ */
 static int random0to1() { return rand() % 2; }
 
 namespace Env {
@@ -30,8 +45,7 @@ void CartPole::init() {
     S.observation.push_back(0.0);
 }
 
-void CartPole::step(const std::vector<float> &action, bool rendering,
-                    State *s) {
+void CartPole::step(const std::vector<float> &action, bool rendering, State *s) {
   double x = S.observation[0];
   double x_dot = S.observation[1];
   double theta = S.observation[2];
@@ -40,11 +54,9 @@ void CartPole::step(const std::vector<float> &action, bool rendering,
 
   double costheta = cos(theta);
   double sintheta = sin(theta);
-  double temp =
-      (force + polemass_length * theta_dot * theta_dot * sintheta) / total_mass;
+  double temp = (force + polemass_length * theta_dot * theta_dot * sintheta) / total_mass;
   double thetaacc =
-      (gravity * sintheta - costheta * temp) /
-      (length * (4.0 / 3.0 - masspole * costheta * costheta / total_mass));
+      (gravity * sintheta - costheta * temp) / (length * (4.0 / 3.0 - masspole * costheta * costheta / total_mass));
   double xacc = temp - polemass_length * thetaacc * costheta / total_mass;
 
   x = x + tau * x_dot;
@@ -62,8 +74,7 @@ void CartPole::step(const std::vector<float> &action, bool rendering,
   s->observation.push_back(theta);
   s->observation.push_back(theta_dot);
 
-  S.done = (bool)(x < x_threshold * -1.0 || x > x_threshold ||
-                  theta < theta_threshold_radians * -1.0 ||
+  S.done = (bool)(x < x_threshold * -1.0 || x > x_threshold || theta < theta_threshold_radians * -1.0 ||
                   theta > theta_threshold_radians);
   // theta > theta_threshold_radians || count >= 200);
   count++;

diff --git a/Environment/CartPole/cartpole.h b/Environment/CartPole/cartpole.h
index ed7581b..16cf7b9 100644 (file)
--- a/Environment/CartPole/cartpole.h
+++ b/Environment/CartPole/cartpole.h
@@ -1,3 +1,12 @@
+/**
+ * @file       cartpole.h
+ * @date       04 December 2019
+ * @brief      This is environment class for cartpole example
+ * @see                https://github.sec.samsung.net/jijoong-moon/Transfer-Learning.git
+ * @author     Jijoong Moon <jijoong.moon@samsung.com>
+ * @bug                No known bugs except for NYI items
+ *
+ */
 #ifndef __CARTPOLE_H__
 #define __CARTPOLE_H__
 
@@ -5,8 +14,17 @@
 #include <iostream>
 #include <vector>
 
+/**
+ * @Namespace   Namespace Env
+ * @brief       Namespace Env
+ */
 namespace Env {
-
+/**
+ * @brief     State Data Type
+ *            ovservation : state variables
+ *            reward : reward
+ *            done : boolean for end of episode
+ */
 typedef struct {
   std::vector<float> observation;
   float reward;
@@ -14,18 +32,61 @@ typedef struct {
   std::string ginfo;
 } State;
 
+/**
+ * @class   CartPole Class
+ * @brief   CartPole-v0 example for Reinforcement Learning
+ */
 class CartPole {
-public:
+ public:
+  /**
+   * @brief     Constructor of CartPole
+   */
   CartPole(){};
+
+  /**
+   * @brief     Destructor of CartPole
+   */
   ~CartPole(){};
+
+  /**
+   * @brief     Initialization fo CarPole variables
+   *            Set hyper parameters & set observation zero
+   */
   void init();
+
+  /**
+   * @brief     Run Env with action
+   * @param[in] action input action
+   * @param[in] rendering boolean variable to redering. (It is not used)
+   * @param[out]s State Output calculated by Env
+   */
   void step(const std::vector<float> &action, bool rendering, State *s);
-  void reset(State *initiali_s);
+
+  /**
+   * @brief     reset Env
+   * @param[out] initial_s copy inialize State from this->S
+   */
+  void reset(State *initial_s);
+
+  /**
+   * @brief     get InputSize : 4 (CartPole-v0 example)
+   * @retval    inputsize
+   */
   int getInputSize();
+
+  /**
+   * @brief     get OutputSize : 2 (CartPole-v0 example)
+   * @retval    outputSize
+   */
   int getOutputSize();
+
+  /**
+   * @brief     generate random action value
+   * @retval    random action values as vector<float>
+   */
   std::vector<float> sample();
 
-private:
+ private:
   double gravity;
   double masscart;
   double masspole;

diff --git a/Environment/CartPole/main.cpp b/Environment/CartPole/main.cpp
index f82e77e..706471f 100644 (file)
--- a/Environment/CartPole/main.cpp
+++ b/Environment/CartPole/main.cpp
@@ -1,3 +1,13 @@
+/**
+ * @file       main.cpp
+ * @date       04 December 2019
+ * @brief      This is simple example to use Env CartPole-v0
+ * @see                https://github.sec.samsung.net/jijoong-moon/Transfer-Learning.git
+ * @author     Jijoong Moon <jijoong.moon@samsung.com>
+ * @bug                No known bugs except for NYI items
+ *
+ */
+
 #include "cartpole.h"
 #include <iostream>
 #include <stdio.h>
@@ -7,7 +17,7 @@ int main() {
   Env::CartPole cartpole;
   srand(time(NULL));
   std::vector<float> action;
-  action=cartpole.sample();
+  action = cartpole.sample();
   cartpole.init();
   for (int episode = 0; episode < 100; episode++) {
     cartpole.reset(&state);
@@ -15,16 +25,14 @@ int main() {
     int total_steps = 0;
     while (1) {
       action = cartpole.sample();
-      cartpole.step(action,false, &state);
+      cartpole.step(action, false, &state);
       total_reward += state.reward;
       total_steps += 1;
-      printf("action : %f --> state : %f %f %f %f\n", action[0],
-             state.observation[0], state.observation[1], state.observation[2],
-             state.observation[3]);
+      printf("action : %f --> state : %f %f %f %f\n", action[0], state.observation[0], state.observation[1],
+             state.observation[2], state.observation[3]);
       if (state.done)
         break;
     }
-    printf("episode %i finished in %i steps with reward %02f\n", episode,
-           total_steps, total_reward);
+    printf("episode %i finished in %i steps with reward %02f\n", episode, total_steps, total_reward);
   }
 }