From 218c2876cf80a11b65c4fde4e2ed391e3cf11948 Mon Sep 17 00:00:00 2001
From: Philipp Horstenkamp <philipp@horstenkamp.de>
Date: Sun, 12 Feb 2023 14:32:24 +0100
Subject: [PATCH] Added a section abot imports and dependencies and some
 initial design decisions for the game.

---
 main.ipynb | 55 ++++++++++++++++++++++++++++++++++++++++++++++--------
 1 file changed, 47 insertions(+), 8 deletions(-)

diff --git a/main.ipynb b/main.ipynb
index 6af3342..ad5161d 100644
--- a/main.ipynb
+++ b/main.ipynb
@@ -21,7 +21,9 @@
     "## Content\n",
     "\n",
     "* [The game rules](#the-game-rules) A short overview over the rules of the game.\n",
-    "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations."
+    "* [Some common Otello strategies](#some-common-otello-strategies) introduces some easy approaches to a classic Otello AI and defines some behavioral expectations.\n",
+    "* [Initial design decisions](#initial-design-decisions) an explanation about some initial design decision and assumptions\n",
+    "* [Imports and dependencies](#imports-and-dependencies) explains what libraries where used"
    ],
    "metadata": {
     "collapsed": false
@@ -67,6 +69,23 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Initial design decisions\n",
+    "\n",
+    "At the beginning of this project I made some design decisions.\n",
+    "The first onw was that I do not want to use a gym library because it limits the data formats accessible.\n",
+    "I choose to implement the hole game as entry in a stack in numpy arrays to be able to accommodate interfacing with a neural network easier and to use scipy pattern recognition tools to implement some game mechanics for a fast simulation cycle.\n",
+    "I chose to ignore player colors as far as I could instead a player perspective was used. Which allowed to change the perspective with a flipping of the sign. (multiplying with -1).\n",
+    "The array format should also allow for data multiplication or the breaking of strikt sequences by flipping the game along one the for axis, (horizontal, vertical, transpose along both diagonals).\n",
+    "\n",
+    "I wanted to implement different agents as classes that act on those game stacks."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -80,12 +99,32 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Imports"
+    "## Imports and dependencies\n",
+    "\n",
+    "The following direct dependencies where used for this project:\n",
+    "```toml\n",
+    "jupyter = \"^1.0.0\"\n",
+    "matplotlib = \"^3.6.3\"\n",
+    "numpy = \"^1.24.1\"\n",
+    "pytest = \"^7.2.1\"\n",
+    "python = \"3.10.*\"\n",
+    "scipy = \"^1.10.0\"\n",
+    "tqdm = \"^4.64.1\"\n",
+    "jupyterlab = \"^3.6.1\"\n",
+    "torchvision = \"^0.14.1\"\n",
+    "torchaudio = \"^0.13.1\"\n",
+    "```\n",
+    "* `Jupyter` and `jupyterlab` on pycharm was used as a IDE / Ipython was used to implement this code.\n",
+    "* `matplotlib` was used for visualisation and statistics.\n",
+    "* `numpy` was used for array support and mathematical functions\n",
+    "* `tqdm` was used for progress bars\n",
+    "* `scipy` contains fast pattern recognition tools for images. It was used to make an initial estimation about where possible turns should be.\n",
+    "* `torch` supplied the ANN functionalities."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,7 +140,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Constants"
+    "## Constants\n",
+    "\n",
+    "Some general constants needed to be defined. Such as board game size and Player and Enemy representations. Also, directional offsets and the initial placement of blocks."
    ]
   },
   {
@@ -112,7 +153,7 @@
    "source": [
     "BOARD_SIZE: Final[int] = 8  # defines the board side length as 8\n",
     "PLAYER: Final[int] = 1  # defines the number symbolising the player as 1\n",
-    "ENEMY: Final[int] = -1  # defines the number symbolising the enenemy as 1"
+    "ENEMY: Final[int] = -1  # defines the number symbolising the enemy as -1"
    ]
   },
   {
@@ -284,7 +325,7 @@
     }
    ],
    "source": [
-    "def plot_othello_board(board, ax=None):\n",
+    "def plot_othello_board(board, ax=None) -> None:\n",
     "    \"\"\"Plots a single otello board.\n",
     "\n",
     "    If a matplot axis object is given the board will be plotted into that axis. If not an axis object will be generated.\n",
@@ -293,8 +334,6 @@
     "        board: The bord that should be plotted. Only a single games is allowed. A numpy array of the form 8x8 is expected.\n",
     "        ax: If needed the\n",
     "\n",
-    "    Returns:\n",
-    "\n",
     "    \"\"\"\n",
     "    plot_all = False\n",
     "    if ax is None:\n",