From ed19e41bc612246ff2a18faff529df24d66988a4 Mon Sep 17 00:00:00 2001
From: aliaksei-kudravets <frume28@gmail.com>
Date: Fri, 13 May 2022 08:31:40 +0200
Subject: [PATCH] add decision tree model to trashbins, which are generated on
 map

---
 .DS_Store                                    | Bin 0 -> 6148 bytes
 .ipynb_checkpoints/Untitled-checkpoint.ipynb | 109 ++++++++++++
 Untitled.ipynb                               | 126 ++++++++++++++
 decision_tree/decisionTree.py                |  21 +--
 decision_tree/tree_as_txt.txt                | 169 +++++++++----------
 decision_tree/tree_model                     | Bin 7076 -> 5545 bytes
 game_objects/trashbin.py                     |  34 ++--
 main.py                                      |  81 ++++++---
 map/map_utils.py                             |   5 +-
 9 files changed, 404 insertions(+), 141 deletions(-)
 create mode 100644 .DS_Store
 create mode 100644 .ipynb_checkpoints/Untitled-checkpoint.ipynb
 create mode 100644 Untitled.ipynb

diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..b920e7d38d3eadd1d146255d3fd7f08720c94faa
GIT binary patch
literal 6148
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diff --git a/.ipynb_checkpoints/Untitled-checkpoint.ipynb b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
new file mode 100644
index 0000000..d20f756
--- /dev/null
+++ b/.ipynb_checkpoints/Untitled-checkpoint.ipynb
@@ -0,0 +1,109 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fac14368",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = pandas.read_csv('/Users/mac/Desktop/tree_dataset.csv', sep=\";\")\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4d25d809",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "663eaf94",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f3c9b416",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bcfb233e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "11f0c1a2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b1a93eb4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "528f6ade",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "efb466fe",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5dbe234e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "language": "python",
+   "name": "env"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/Untitled.ipynb b/Untitled.ipynb
new file mode 100644
index 0000000..a339a94
--- /dev/null
+++ b/Untitled.ipynb
@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "fac14368",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[1]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from sklearn.tree import DecisionTreeClassifier, export_text, plot_tree\n",
+    "dataset = pandas.read_csv('/Users/mac/Desktop/tree_dataset.csv', sep=\";\")\n",
+    "decisions = [\"decision\"]\n",
+    "attributes = [\"season\", \"trash_type\", \"mass\", \"space\", \"trash_mass\"]\n",
+    "\n",
+    "x = dataset[attributes]\n",
+    "y = dataset[decisions]\n",
+    "decision_tree = DecisionTreeClassifier()\n",
+    "decision_tree.fit(x.values, y.values)\n",
+    "decision = decision_tree.predict(\n",
+    "        [[5, 3 , 3, 1, 2]])\n",
+    "print(decision)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "04bbec40",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9c1d0193",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8e40a924",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b430f8b8",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "58ce5faa",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a4b72d3d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b4e0aae9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "74fb263f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5dbe234e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "language": "python",
+   "name": "env"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/decision_tree/decisionTree.py b/decision_tree/decisionTree.py
index f15b77c..3986b0e 100644
--- a/decision_tree/decisionTree.py
+++ b/decision_tree/decisionTree.py
@@ -3,37 +3,26 @@ import matplotlib.pyplot as plt
 import pandas
 from sklearn.tree import DecisionTreeClassifier, export_text, plot_tree
 
-'''
-atrybuty w pliku csv muszą być integerami, wstępnie ustaliłem:
-season = {"wiosna": 1, "lato": 2, "jesien":3, "zima":4}
-enough_space_in_trashmaster = { "no": 1, "yes":2}
-time_since_flush = [1,2,3,4,5,6,7,8,9,10]
-type_of_trash = {"bio":1, "szklo":2, "plastik":3, "papier":4, "mieszane":5}
-access_to_bin = { "no":1, "yes":2}
-distance = [1,2,3,4,5,6,7,8,9,10]
-decision = [0,1] - decyzje zostaną zmienione z tych z wagami na zero jedynkowe ze względu na pewne trudności w dalszej pracy
-'''
 decisions = ["decision"]
-attributes = ["season", "enough_space_in_trashmaster", "time_since_flush", "type_of_trash", "access_to_bin", "distance"]
+attributes = ["season", "trash_type", "mass", "space", "trash_mass"]
 
 
 # return tree made from attributes
 def tree():
-    dataset = pandas.read_csv('./decision_tree/drzewo_decyzyjne.csv')
+    dataset = pandas.read_csv('/Users/mac/Desktop/tree_dataset.csv', sep=";")
 
     x = dataset[attributes]
     y = dataset[decisions]
     decision_tree = DecisionTreeClassifier()
-    decision_tree = decision_tree.fit(x, y)
+    decision_tree = decision_tree.fit(x.values, y.values)
 
     return decision_tree
 
 
 # return decision made from tree and attributes
-def decision(decision_tree, season, enough_space_in_trashmaster, time_since_flush, type_of_trash, access_to_bin,
-             distance):
+def decision(decision_tree, season, trash_type, mass, space, trash_mass):
     decision = decision_tree.predict(
-        [[season, enough_space_in_trashmaster, time_since_flush, type_of_trash, access_to_bin, distance]])
+        [[season, trash_type , mass, space, trash_mass]])
 
     return decision
 
diff --git a/decision_tree/tree_as_txt.txt b/decision_tree/tree_as_txt.txt
index 28a1fd5..af74d02 100644
--- a/decision_tree/tree_as_txt.txt
+++ b/decision_tree/tree_as_txt.txt
@@ -1,94 +1,91 @@
-|--- feature_4 <= 1.50
-|   |--- feature_5 <= 1.50
-|   |   |--- feature_2 <= 6.50
+|--- feature_2 <= 3.50
+|   |--- feature_4 <= 3.50
+|   |   |--- feature_0 <= 1.50
 |   |   |   |--- class: 0
-|   |   |--- feature_2 >  6.50
-|   |   |   |--- feature_0 <= 3.00
-|   |   |   |   |--- class: 1
-|   |   |   |--- feature_0 >  3.00
-|   |   |   |   |--- class: 0
-|   |--- feature_5 >  1.50
-|   |   |--- class: 0
-|--- feature_4 >  1.50
-|   |--- feature_1 <= 1.50
-|   |   |--- feature_0 <= 3.50
-|   |   |   |--- class: 0
-|   |   |--- feature_0 >  3.50
-|   |   |   |--- class: 1
-|   |--- feature_1 >  1.50
-|   |   |--- feature_0 <= 3.50
-|   |   |   |--- feature_0 <= 1.50
-|   |   |   |   |--- feature_3 <= 2.50
+|   |   |--- feature_0 >  1.50
+|   |   |   |--- feature_3 <= 3.50
+|   |   |   |   |--- feature_2 <= 2.50
 |   |   |   |   |   |--- class: 1
-|   |   |   |   |--- feature_3 >  2.50
-|   |   |   |   |   |--- feature_3 <= 3.50
-|   |   |   |   |   |   |--- feature_5 <= 7.50
-|   |   |   |   |   |   |   |--- feature_2 <= 5.50
-|   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |--- feature_2 >  5.50
-|   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |--- feature_5 >  7.50
-|   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |--- feature_3 >  3.50
+|   |   |   |   |--- feature_2 >  2.50
+|   |   |   |   |   |--- feature_4 <= 2.50
 |   |   |   |   |   |   |--- class: 1
-|   |   |   |--- feature_0 >  1.50
-|   |   |   |   |--- feature_3 <= 1.50
-|   |   |   |   |   |--- feature_5 <= 2.50
-|   |   |   |   |   |   |--- feature_5 <= 1.50
-|   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |--- feature_5 >  1.50
+|   |   |   |   |   |--- feature_4 >  2.50
+|   |   |   |   |   |   |--- class: 0
+|   |   |   |--- feature_3 >  3.50
+|   |   |   |   |--- feature_3 <= 4.50
+|   |   |   |   |   |--- feature_1 <= 2.50
+|   |   |   |   |   |   |--- feature_0 <= 2.50
+|   |   |   |   |   |   |   |--- feature_1 <= 1.50
+|   |   |   |   |   |   |   |   |--- feature_4 <= 2.50
+|   |   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |   |--- feature_4 >  2.50
+|   |   |   |   |   |   |   |   |   |--- feature_2 <= 2.00
+|   |   |   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |   |   |--- feature_2 >  2.00
+|   |   |   |   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |   |   |--- feature_1 >  1.50
+|   |   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |   |--- feature_0 >  2.50
+|   |   |   |   |   |   |   |--- feature_4 <= 2.50
+|   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |--- feature_4 >  2.50
+|   |   |   |   |   |   |   |   |--- feature_2 <= 2.50
+|   |   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |   |--- feature_2 >  2.50
+|   |   |   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |--- feature_1 >  2.50
+|   |   |   |   |   |   |--- feature_0 <= 3.50
+|   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |   |--- feature_0 >  3.50
+|   |   |   |   |   |   |   |--- feature_1 <= 3.50
+|   |   |   |   |   |   |   |   |--- feature_2 <= 2.50
+|   |   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |   |--- feature_2 >  2.50
+|   |   |   |   |   |   |   |   |   |--- feature_4 <= 2.00
+|   |   |   |   |   |   |   |   |   |   |--- class: 1
+|   |   |   |   |   |   |   |   |   |--- feature_4 >  2.00
+|   |   |   |   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |   |   |--- feature_1 >  3.50
+|   |   |   |   |   |   |   |   |--- class: 0
+|   |   |   |   |--- feature_3 >  4.50
+|   |   |   |   |   |--- class: 0
+|   |--- feature_4 >  3.50
+|   |   |--- feature_2 <= 1.50
+|   |   |   |--- feature_4 <= 4.50
+|   |   |   |   |--- feature_3 <= 3.50
+|   |   |   |   |   |--- feature_0 <= 1.50
+|   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |--- feature_0 >  1.50
+|   |   |   |   |   |   |--- class: 1
+|   |   |   |   |--- feature_3 >  3.50
+|   |   |   |   |   |--- feature_1 <= 2.50
+|   |   |   |   |   |   |--- feature_3 <= 4.50
 |   |   |   |   |   |   |   |--- feature_0 <= 2.50
 |   |   |   |   |   |   |   |   |--- class: 0
 |   |   |   |   |   |   |   |--- feature_0 >  2.50
 |   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |--- feature_5 >  2.50
-|   |   |   |   |   |   |--- class: 1
-|   |   |   |   |--- feature_3 >  1.50
-|   |   |   |   |   |--- feature_2 <= 3.50
-|   |   |   |   |   |   |--- feature_0 <= 2.50
-|   |   |   |   |   |   |   |--- feature_5 <= 2.00
-|   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |   |--- feature_5 >  2.00
-|   |   |   |   |   |   |   |   |--- feature_5 <= 4.00
-|   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |   |--- feature_5 >  4.00
-|   |   |   |   |   |   |   |   |   |--- feature_3 <= 2.50
-|   |   |   |   |   |   |   |   |   |   |--- feature_5 <= 7.00
-|   |   |   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |   |   |   |--- feature_5 >  7.00
-|   |   |   |   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |   |   |   |--- feature_3 >  2.50
-|   |   |   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |--- feature_0 >  2.50
-|   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |--- feature_2 >  3.50
-|   |   |   |   |   |   |--- feature_5 <= 1.50
+|   |   |   |   |   |   |--- feature_3 >  4.50
 |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |--- feature_5 >  1.50
-|   |   |   |   |   |   |   |--- feature_3 <= 2.50
-|   |   |   |   |   |   |   |   |--- feature_5 <= 5.00
-|   |   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |   |   |--- feature_5 >  5.00
-|   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |--- feature_3 >  2.50
-|   |   |   |   |   |   |   |   |--- feature_5 <= 5.50
-|   |   |   |   |   |   |   |   |   |--- feature_0 <= 2.50
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 <= 4.50
-|   |   |   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 >  4.50
-|   |   |   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |   |   |--- feature_0 >  2.50
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 <= 4.50
-|   |   |   |   |   |   |   |   |   |   |   |--- class: 0
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 >  4.50
-|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2
-|   |   |   |   |   |   |   |   |--- feature_5 >  5.50
-|   |   |   |   |   |   |   |   |   |--- feature_5 <= 6.50
-|   |   |   |   |   |   |   |   |   |   |--- class: 1
-|   |   |   |   |   |   |   |   |   |--- feature_5 >  6.50
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 <= 8.50
-|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3
-|   |   |   |   |   |   |   |   |   |   |--- feature_2 >  8.50
-|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4
-|   |   |--- feature_0 >  3.50
-|   |   |   |--- class: 1
+|   |   |   |   |   |--- feature_1 >  2.50
+|   |   |   |   |   |   |--- class: 0
+|   |   |   |--- feature_4 >  4.50
+|   |   |   |   |--- class: 0
+|   |   |--- feature_2 >  1.50
+|   |   |   |--- class: 0
+|--- feature_2 >  3.50
+|   |--- feature_1 <= 1.50
+|   |   |--- feature_4 <= 1.50
+|   |   |   |--- feature_2 <= 4.50
+|   |   |   |   |--- feature_3 <= 4.50
+|   |   |   |   |   |--- feature_0 <= 1.50
+|   |   |   |   |   |   |--- class: 0
+|   |   |   |   |   |--- feature_0 >  1.50
+|   |   |   |   |   |   |--- class: 1
+|   |   |   |   |--- feature_3 >  4.50
+|   |   |   |   |   |--- class: 0
+|   |   |   |--- feature_2 >  4.50
+|   |   |   |   |--- class: 0
+|   |   |--- feature_4 >  1.50
+|   |   |   |--- class: 0
+|   |--- feature_1 >  1.50
+|   |   |--- class: 0
diff --git a/decision_tree/tree_model b/decision_tree/tree_model
index ef984c8271342ae5cf51591f715e0fdd93474b7f..b28c9a370a1f75d6e941f38a4420a2c206a32645 100644
GIT binary patch
literal 5545
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diff --git a/game_objects/trashbin.py b/game_objects/trashbin.py
index 9b8ea8b..f6f37da 100644
--- a/game_objects/trashbin.py
+++ b/game_objects/trashbin.py
@@ -1,23 +1,23 @@
 import pygame as pg
 from enum import Enum
-
+from random import randrange
 from map.tile import Tile
-
-class Waste_Type(Enum):
-    BIO = 0
-    GLASS = 1
-    PLASTIC = 2
-    PAPER = 3
-    MIX = 4
-
-    def __int__(self):
-        return self.value
 class Trashbin(Tile):
-    def __init__(self, img, x, y, width, height, waste_type: Waste_Type):
+    def __init__(self, img, x, y, width, height, waste_type):
         super().__init__(img, x, y, width, height)
+        # dis_dump	dis_trash	mass	space	trash_mass	trash_space
+        self.x = x
+        self.y = y
         
-        self.waste_type = waste_type
-        self.days_after_pickup = 0
-        self.max_capacity = 100
-        self.used_capacity = 0
-        self.access = True
+        self.season = randrange(4)
+        self.trash_type = randrange(5)
+        self.mass = randrange(5)
+        self.space = randrange(5)
+        self.trash_mass = randrange(5)       
+
+
+    def get_coords(self):
+        return (self.x, self.y)
+
+    def get_attributes(self):
+        return (self.season, self.trash_type, self.mass, self.space, self.trash_mass) 
diff --git a/main.py b/main.py
index e7c2476..fe582db 100644
--- a/main.py
+++ b/main.py
@@ -13,17 +13,22 @@ from path_search_algorthms import a_star, a_star_utils
 from decision_tree import decisionTree
 
 from game_objects import aiPlayer
+import itertools
 
 
-def printTree():
+def getTree():
     tree = decisionTree.tree()
     decisionTree.tree_as_txt(tree)
-    decisionTree.tree_to_png(tree)
+    # decisionTree.tree_to_png(tree)
     decisionTree.tree_to_structure(tree)
     drzewo = decisionTree.tree_from_structure('./decision_tree/tree_model')
-    print("Dla losowych danych predykcja czy wziąć kosz to: ")
-    dec = decisionTree.decision(drzewo, 4, 2, 7, 4, 2, 3)
-    print(dec)
+    # print("Dla losowych danych predykcja czy wziąć kosz to: ")
+    # dec = decisionTree.decision(drzewo, *(4,1,1,1))
+    # print('---')
+    # print(f"decision is{dec}")
+    # print('---')
+
+    return drzewo
 
 
 class Game():
@@ -31,6 +36,7 @@ class Game():
     def __init__(self):
         pg.init()
         self.clock = pg.time.Clock()
+        self.dt = self.clock.tick(FPS) / 333.0
         self.screen = pg.display.set_mode((WIDTH, HEIGHT))
         pg.display.set_caption("Trashmaster")
         self.load_data()
@@ -38,8 +44,17 @@ class Game():
         # because dont work without data.txt
         # self.init_bfs()
         # self.init_a_star()
+        self.t = aiPlayer.aiPlayer(self.player, game=self)
 
-        self.dt = self.clock.tick(FPS) / 1000.0
+        
+    def get_actions_by_coords(self,x,y):
+        pos = (x,y)
+        offset_x, offset_y = self.camera.offset()
+        clicked_coords = [math.floor(pos[0] / TILESIZE) - offset_x, math.floor(pos[1] / TILESIZE) - offset_y]
+        actions = a_star.search_path(math.floor(self.player.pos[0] / TILESIZE),
+                                        math.floor(self.player.pos[1] / TILESIZE), self.player.rotation(),
+                                        clicked_coords[0], clicked_coords[1], self.mapArray)
+        return actions
 
     def init_game(self):
         # initialize all variables and do all the setup for a new game
@@ -47,16 +62,15 @@ class Game():
         # sprite groups and map array for calculations
         (self.roadTiles, self.wallTiles, self.trashbinTiles), self.mapArray = map.get_tiles()
         self.agentSprites = pg.sprite.Group()
-
         # player obj
         self.player = Player(self, 32, 32)
-
         # camera obj
         self.camera = map_utils.Camera(MAP_WIDTH_PX, MAP_HEIGHT_PX)
 
         # other
         self.debug_mode = False
 
+        
     def init_bfs(self):
         start_node = (0, 0)
         target_node = (18, 18)
@@ -81,6 +95,38 @@ class Game():
         path = a_star.search_path(start_x, start_y, target_x, target_y, self.mapArray)
         print(path)
 
+    def init_decision_tree(self):
+         # logika pracy z drzewem
+        self.positive_decision = []
+        self.negative_decision = []
+
+        self.positive_actions = []
+        self.negative_actions = []
+        for i in self.trashbinTiles:
+            atrrs_container = i.get_attributes()
+            x, y = i.get_coords()
+            dec = decisionTree.decision(getTree(), *atrrs_container)
+            if dec[0] == 1:
+                self.positive_decision.append(i)
+                self.positive_actions.append(self.get_actions_by_coords(x, y))
+            else:
+                self.negative_decision.append(i)
+                self.negative_actions.append(i)
+        
+        # j = 0
+        # for i in self.positive_actions:
+            
+        #     print(f"step {j} actions is : {i}")
+        #     j+=1
+
+        # vec = pg.math.Vector2
+        # for i in self.positive_actions:
+        #     self.t.startAiController(i)
+        #     self.player.pos = vec(32, 32)
+        
+        self.t.startAiController(self.positive_actions[0])
+        
+
     def load_data(self):
         game_folder = path.dirname(__file__)
         img_folder = path.join(game_folder, 'resources/textures')
@@ -91,7 +137,7 @@ class Game():
     def run(self):
         # game loop - set self.playing = False to end the game 
         self.playing = True
-
+        self.init_decision_tree()
         while self.playing:
             self.dt = self.clock.tick(FPS) / 1000.0
             self.events()
@@ -142,24 +188,17 @@ class Game():
                 actions = a_star.search_path(math.floor(self.player.pos[0] / TILESIZE),
                                              math.floor(self.player.pos[1] / TILESIZE), self.player.rotation(),
                                              clicked_coords[0], clicked_coords[1], self.mapArray)
-                print(actions)
+                # print(actions)
+                
                 if (actions != None):
-                    t = aiPlayer.aiPlayer(self.player, game=self)
-                    t.startAiController(actions)
-
-    def show_start_screen(self):
-        pass
-
-    def show_go_screen(self):
-        pass
+                    self.t.startAiController(actions)
 
+                
 
 # create the game object
 
 if __name__ == "__main__":
     g = Game()
-    g.show_start_screen()
-    printTree()
-
+    
     g.run()
     g.show_go_screen()
\ No newline at end of file
diff --git a/map/map_utils.py b/map/map_utils.py
index 1a32047..1904528 100644
--- a/map/map_utils.py
+++ b/map/map_utils.py
@@ -21,13 +21,15 @@ def generate_map():
         map[y][x] = 1
 
     # generowanie smietnikow
-    for i in range(0, 5):
+    for i in range(0, 10):
         x = random.randint(0, MAP_WIDTH-1)
         y = random.randint(0, MAP_HEIGHT-1)
         map[y][x] = 2
 
     return map
 
+trashbins =[]
+
 # tworzenie grup sprite'ow
 def get_sprites(map, pattern):
     roadTiles = pg.sprite.Group()
@@ -54,6 +56,7 @@ def get_sprites(map, pattern):
                 trashbin = Trashbin(trashbin_pattern[trashbinId], offsetX, offsetY, 32, 30, trashbinId)
                 roadTiles.add(tile)
                 trashbinTiles.add(trashbin)
+                trashbins.append(trashbin)
 
     return roadTiles, wallTiles, trashbinTiles