16. Python OOPs Concepts.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7582ad99",
   "metadata": {},
   "source": [
    "# Python Object Oriented Programming"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "144e28b5",
   "metadata": {},
   "source": [
    "- Python is a multi-paradigm programming language. It supports different programming approaches.\n",
    "\n",
    "- One of the popular approaches to solve a programming problem is by creating objects. This is known as Object-Oriented Programming (OOP).\n",
    "\n",
    "**An object has two characteristics:**\n",
    "- attributes\n",
    "- behavior\n",
    "**Let's take an example:**\n",
    "\n",
    "- A parrot is an object, as it has the following properties:\n",
    "\n",
    "    - name, age, color as attributes\n",
    "    - singing, dancing as behavior\n",
    "**The concept of OOP in Python focuses on creating reusable code. This concept is also known as DRY (Don't Repeat Yourself).**\n",
    "\n",
    "***In Python, the concept of OOP follows some basic principles***\n",
    "- Class\n",
    "- Object"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d40d51e",
   "metadata": {},
   "source": [
    "# Class\n",
    "- A class is a blueprint for the object.\n",
    "\n",
    "We can think of class as a sketch of a parrot with labels. It contains all the details about the name, colors, size etc. Based on these descriptions, we can study about the parrot. Here, a parrot is an object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ac58d54b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#The example for class of parrot can be\n",
    "class Parrot:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "852a47c5",
   "metadata": {},
   "source": [
    "<b> In above example, we use the class keyword to define an empty class Parrot. From class, we construct instances. An instance is a specific object created from a particular class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "16184455",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "<function Person.greet at 0x0000023F651B2B80>\n",
      "This is a person class\n"
     ]
    }
   ],
   "source": [
    "class Person:\n",
    "    \"This is a person class\"\n",
    "    age = 10\n",
    "\n",
    "    def greet(self):\n",
    "        print('Hello')\n",
    "\n",
    "\n",
    "# Output: 10\n",
    "print(Person.age)\n",
    "\n",
    "# Output: <function Person.greet>\n",
    "print(Person.greet)\n",
    "\n",
    "# Output: \"This is a person class\"\n",
    "print(Person.__doc__)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcbf9af8",
   "metadata": {},
   "source": [
    "## Object\n",
    "- An object (instance) is an instantiation of a class. When class is defined, only the description for the object is defined. Therefore, no memory or storage is allocated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3918460a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Parrot object at 0x0000023F651D44F0>\n"
     ]
    }
   ],
   "source": [
    "#The example for object of parrot class can be\n",
    "obj = Parrot()\n",
    "print(obj) #object of class Parrot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4cbeb47",
   "metadata": {},
   "source": [
    "### Example 1: Creating Class and Object in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7bf6766e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Blu is a bird\n",
      "Woo is a bird\n",
      "Blu is 10 years old\n",
      "Woo is 15 years old\n"
     ]
    }
   ],
   "source": [
    "class Parrot:\n",
    "    \n",
    "    #class attribute\n",
    "    species = \"bird\"\n",
    "    \n",
    "    #instance attribute\n",
    "    def __init__(self,name,age):\n",
    "        self.name = name\n",
    "        self.age = age\n",
    "        \n",
    "# Instantiate the parrot class\n",
    "blu = Parrot(\"Blu\",10)\n",
    "woo = Parrot(\"Woo\",15)\n",
    "\n",
    "#access the class attributes\n",
    "print(\"Blu is a {}\".format(blu.__class__.species))\n",
    "print(\"Woo is a {}\".format(woo.__class__.species))\n",
    "\n",
    "#access the instance attributes\n",
    "print(\"{} is {} years old\".format(blu.name,blu.age))\n",
    "print(\"{} is {} years old\".format(woo.name,woo.age))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69eaea48",
   "metadata": {},
   "source": [
    "- In the above program, we created a class with the name Parrot. \n",
    "- Then, we define attributes. The attributes are a characteristic of an object.\n",
    "\n",
    "- These attributes are defined inside the __init__ method of the class. It is the initializer method that is first run as soon as the object is created.\n",
    "\n",
    "- Then, we create instances of the Parrot class. Here, blu and woo are references (value) to our new objects.\n",
    "\n",
    "- We can access the class attribute using __class__.species. Class attributes are the same for all instances of a class. \n",
    "- Similarly, we access the instance attributes using blu.name and blu.age. However, instance attributes are different for every instance of a class."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8abceccc",
   "metadata": {},
   "source": [
    "## Constructors in Python\n",
    "- Class functions that begin with double underscore __ are called special functions as they have special meaning.\n",
    "\n",
    "- Of one particular interest is the __init__() function. This special function gets called whenever a new object of that class is instantiated.\n",
    "\n",
    "- This type of function is also called constructors in Object Oriented Programming (OOP). We normally use it to initialize all the variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b5f35a3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2+3j\n",
      "(5, 0, 10)\n"
     ]
    },
    {
     "ename": "AttributeError",
     "evalue": "'ComplexNumber' object has no attribute 'attr'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-afa66228e4bc>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     25\u001b[0m \u001b[1;31m# but c1 object doesn't have attribute 'attr'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     26\u001b[0m \u001b[1;31m# AttributeError: 'ComplexNumber' object has no attribute 'attr'\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 27\u001b[1;33m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnum1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mattr\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: 'ComplexNumber' object has no attribute 'attr'"
     ]
    }
   ],
   "source": [
    "class ComplexNumber:\n",
    "    def __init__(self, r=0, i=0):\n",
    "        self.real = r\n",
    "        self.imag = i\n",
    "\n",
    "    def get_data(self):\n",
    "        print(f'{self.real}+{self.imag}j')\n",
    "\n",
    "\n",
    "# Create a new ComplexNumber object\n",
    "num1 = ComplexNumber(2, 3)\n",
    "\n",
    "# Call get_data() method\n",
    "# Output: 2+3j\n",
    "num1.get_data()\n",
    "\n",
    "# Create another ComplexNumber object\n",
    "# and create a new attribute 'attr'\n",
    "num2 = ComplexNumber(5)\n",
    "num2.attr = 10\n",
    "\n",
    "# Output: (5, 0, 10)\n",
    "print((num2.real, num2.imag, num2.attr))\n",
    "\n",
    "# but c1 object doesn't have attribute 'attr'\n",
    "# AttributeError: 'ComplexNumber' object has no attribute 'attr'\n",
    "print(num1.attr)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f65372a",
   "metadata": {},
   "source": [
    "- In the above example, we defined a new class to represent complex numbers. \n",
    "- It has two functions, __init__() to initialize the variables (defaults to zero) and get_data() to display the number properly.\n",
    "\n",
    "- An interesting thing to note in the above step is that attributes of an object can be created on the fly. We created a new attribute attr for object num2 and read it as well. But this does not create that attribute for object num1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eff3dc1",
   "metadata": {},
   "source": [
    "## Deleting Attributes and Objects\n",
    "Any attribute of an object can be deleted anytime, using the del statement. Try the following on the Python shell to see the output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9e336d99",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'ComplexNumber' object has no attribute 'imag'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-6-695a8bf3acc3>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mnum1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mComplexNumber\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdel\u001b[0m \u001b[0mnum1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mimag\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mnum1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-5-afa66228e4bc>\u001b[0m in \u001b[0;36mget_data\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      6\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 7\u001b[1;33m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34mf'{self.real}+{self.imag}j'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      8\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mAttributeError\u001b[0m: 'ComplexNumber' object has no attribute 'imag'"
     ]
    }
   ],
   "source": [
    "num1 = ComplexNumber(2,3)\n",
    "del num1.imag\n",
    "num1.get_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "904bec1c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'ComplexNumber' object has no attribute 'get_data'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-7-707187788474>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mdel\u001b[0m \u001b[0mComplexNumber\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mnum1\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_data\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m: 'ComplexNumber' object has no attribute 'get_data'"
     ]
    }
   ],
   "source": [
    "del ComplexNumber.get_data\n",
    "num1.get_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1655db95",
   "metadata": {},
   "source": [
    "<b> We can even delete the object itself, using the del statement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "06479b75",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'c1' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-8-85081af54bce>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mc1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mComplexNumber\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[1;32mdel\u001b[0m \u001b[0mc1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mc1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'c1' is not defined"
     ]
    }
   ],
   "source": [
    "c1 = ComplexNumber(1,3)\n",
    "del c1\n",
    "c1"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "bae21d28",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32395fbb",
   "metadata": {},
   "source": [
    "## Methods\n",
    "- Methods are functions defined inside the body of a class. They are used to define the behaviors of an object"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b759959",
   "metadata": {},
   "source": [
    "### Example 2 : Creating Methods in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9b0386d1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Blu sings 'Happy'\n",
      "Blu is now dancing\n"
     ]
    }
   ],
   "source": [
    "class Parrot:\n",
    "    \n",
    "    #class attribute\n",
    "    species = \"bird\"\n",
    "    \n",
    "    #instance attribute\n",
    "    def __init__(self,name,age):\n",
    "        self.name = name\n",
    "        self.age = age\n",
    "        \n",
    "    #instance method\n",
    "    def sing(self,song):\n",
    "        return \"{} sings {}\".format(self.name,song)\n",
    "\n",
    "    def dance(self):\n",
    "        return \"{} is now dancing\".format(self.name)\n",
    "    \n",
    "# Instantiate the parrot class\n",
    "blu = Parrot(\"Blu\",10)\n",
    "\n",
    "#call our instance methods\n",
    "print(blu.sing(\"'Happy'\"))\n",
    "print(blu.dance())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b588fbfb",
   "metadata": {},
   "source": [
    "- In the above program, we define two methods i.e sing() and dance(). \n",
    "- These are called instance methods because they are called on an instance object i.e blu"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1357503d",
   "metadata": {},
   "source": [
    "## Inheritance\n",
    "- Inheritance is a way of creating a new class for using details of an existing class without modifying it. \n",
    "- The newly formed class is a derived class (or child class). Similarly, the existing class is a base class (or parent class)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8afe6694",
   "metadata": {},
   "source": [
    "**Syntax :**<br>\n",
    "class BaseClass:<br>\n",
    "&emsp;&emsp;  Body of base class<br>\n",
    "class DerivedClass(BaseClass):<br>\n",
    "&emsp;&emsp;  Body of derived class"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2e3cc57",
   "metadata": {},
   "source": [
    "### Example 3: Use of Inheritance in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e011a19f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#parent class\n",
    "class Bird:\n",
    "    \n",
    "    def __init__(self):\n",
    "        print(\"Bird is ready\")\n",
    "    \n",
    "    def whoisThis(self):\n",
    "        print(\"Bird\")\n",
    "    \n",
    "    def swim(self):\n",
    "        print(\"swim faster\")\n",
    "        \n",
    "\n",
    "#child class\n",
    "class Penguin(Bird):\n",
    "    \n",
    "    def __init__(self):\n",
    "        #call super function\n",
    "        super().__init__()\n",
    "        print(\"Penguin is ready\")\n",
    "        \n",
    "    def whoisThis(self):\n",
    "        print(\"Penguin\")\n",
    "        \n",
    "    def run(self):\n",
    "        print(\"Run Faster\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f81c9843",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bird is ready\n",
      "Penguin is ready\n"
     ]
    }
   ],
   "source": [
    "'''since child is inheriting base class, \n",
    "    - init function is exectuted for the base class as we are inheriting the init of base\n",
    "    - then child init function is executed '''\n",
    "peggy = Penguin() #creating object of child class\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "72296e70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Penguin\n"
     ]
    }
   ],
   "source": [
    "peggy.whoisThis() #accessing the child class method, though same name is in parent class but it is accessing child class as we created child class object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2059cbbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "swim faster\n"
     ]
    }
   ],
   "source": [
    "peggy.swim() #from child class object directly accessing base class methods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a8abc661",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Run Faster\n"
     ]
    }
   ],
   "source": [
    "peggy.run() #from child class object accessing child class method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea16f7eb",
   "metadata": {},
   "source": [
    "- we use the super() function inside the __init__() method. This allows us to run the __init__() method of the parent class inside the child class"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc59e462",
   "metadata": {},
   "source": [
    "### Example-4 Inheritance in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c22ef2b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Parent Class\n",
    "class Polygon:\n",
    "    def __init__(self, no_of_sides):\n",
    "        self.n = no_of_sides\n",
    "        self.sides = [0 for i in range(no_of_sides)]\n",
    "\n",
    "    def inputSides(self):\n",
    "        self.sides = [float(input(\"Enter side \"+str(i+1)+\" : \")) for i in range(self.n)]\n",
    "\n",
    "    def dispSides(self):\n",
    "        for i in range(self.n):\n",
    "            print(\"Side\",i+1,\"is\",self.sides[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "6dc3afc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Child Class\n",
    "class Triangle(Polygon):\n",
    "    def __init__(self):\n",
    "        Polygon.__init__(self,3) #Alternate way : super().__init__(3)\n",
    "    def findArea(self):\n",
    "        a, b, c = self.sides\n",
    "        # calculate the semi-perimeter\n",
    "        s = (a + b + c) / 2\n",
    "        area = (s*(s-a)*(s-b)*(s-c)) ** 0.5\n",
    "        print('The area of the triangle is %0.2f' %area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1a09ef23",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter side 1 : \n"
     ]
    },
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: ''",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-17-62ab463e5e26>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mt\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mTriangle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#creating the object\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minputSides\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Entering the sides\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m<ipython-input-15-04d09c7492c6>\u001b[0m in \u001b[0;36minputSides\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minputSides\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msides\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Enter side \"\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;34m\" : \"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdispSides\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-15-04d09c7492c6>\u001b[0m in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0minputSides\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msides\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Enter side \"\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;34m\" : \"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdispSides\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: could not convert string to float: ''"
     ]
    }
   ],
   "source": [
    "t = Triangle() #creating the object\n",
    "t.inputSides() #Entering the sides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "43916628",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Side 1 is 0\n",
      "Side 2 is 0\n",
      "Side 3 is 0\n"
     ]
    }
   ],
   "source": [
    "t.dispSides() #Displaying the entered sides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "66f47d42",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The area of the triangle is 0.00\n"
     ]
    }
   ],
   "source": [
    "t.findArea() #finding the area"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fbea995",
   "metadata": {},
   "source": [
    "## Encapsulation\n",
    "- Using OOP in Python, we can restrict access to methods and variables. \n",
    "- This prevents data from direct modification which is called encapsulation. \n",
    "- In Python, we denote private attributes using underscore as the prefix i.e single _ or double __."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "580389e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Computer:\n",
    "    \n",
    "    def __init__(self):\n",
    "        self.__maxprice = 900 #private attribute\n",
    "        self.costprice  = 100\n",
    "        \n",
    "    def sell(self):\n",
    "        print(\"Selling Price : {}\".format(self.__maxprice))\n",
    "    \n",
    "    def cp(self):\n",
    "        print(\"Cost Price : {}\".format(self.costprice))\n",
    "        \n",
    "    def setMaxPrice(self,price):\n",
    "        self.__maxprice = price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "01008c55",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selling Price : 900\n"
     ]
    }
   ],
   "source": [
    "c = Computer() #creating object of class\n",
    "c.sell() #calling the method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fe8fc8c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selling Price : 900\n"
     ]
    }
   ],
   "source": [
    "# change the sell price\n",
    "c.__maxprice = 1000 #not able to change as maxprice is private method\n",
    "c.sell()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f214f0d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Selling Price : 1000\n"
     ]
    }
   ],
   "source": [
    "# using setter function\n",
    "c.setMaxPrice(1000) #setting price via setter method\n",
    "c.sell()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5dbbb6b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost Price : 100\n"
     ]
    }
   ],
   "source": [
    "c.cp() #calling the costprice method "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "83c5efa1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost Price : 1000\n"
     ]
    }
   ],
   "source": [
    "# change the cost price\n",
    "c.costprice = 1000 #since costprice is public hence we are able to change/access it directly\n",
    "c.cp()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3f92d0a",
   "metadata": {},
   "source": [
    "## Polymorphism\n",
    "- Polymorphism is an ability (in OOP) to use a common interface for multiple forms (data types).\n",
    "\n",
    "- Suppose, we need to color a shape, there are multiple shape options (rectangle, square, circle). However we could use the same method to color any shape. This concept is called Polymorphism."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "3f5a1f32",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parrot can fly\n",
      "Penguin can't fly\n"
     ]
    }
   ],
   "source": [
    "class Parrot:\n",
    "    \n",
    "    def fly(self):\n",
    "        print(\"Parrot can fly\")\n",
    "        \n",
    "    def swim(self):\n",
    "        print(\"Parrot can't swim\")\n",
    "        \n",
    "        \n",
    "class Penguin:\n",
    "    \n",
    "    def fly(self):\n",
    "        print(\"Penguin can't fly\")\n",
    "        \n",
    "    def swim(self):\n",
    "        print(\"Penguin can sim\")\n",
    "        \n",
    "#common interface\n",
    "def flying_test(bird):\n",
    "    bird.fly()\n",
    "    \n",
    "#Instantiate objects\n",
    "blu = Parrot()\n",
    "peggy = Penguin()\n",
    "\n",
    "#passing the object\n",
    "flying_test(blu)\n",
    "flying_test(peggy)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f12ad3b",
   "metadata": {},
   "source": [
    "### Key Points :\n",
    "- Object-Oriented Programming makes the program easy to understand as well as efficient.\n",
    "- Since the class is sharable, the code can be reused.\n",
    "- Data is safe and secure with data abstraction.\n",
    "- Polymorphism allows the same interface for different objects, so programmers can write efficient code."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d04b5c5a",
   "metadata": {},
   "source": [
    "## Multiple inheritance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eea093bd",
   "metadata": {},
   "source": [
    "- A class can be derived from more than one base class in Python, similar to C++. This is called multiple inheritance.\n",
    "\n",
    "- In multiple inheritance, the features of all the base classes are inherited into the derived class. The syntax for multiple inheritance is similar to single inheritance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "efc57d99",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Base1:\n",
    "    pass\n",
    "\n",
    "class Base2:\n",
    "    pass\n",
    "\n",
    "class MultiDerived(Base1, Base2):\n",
    "    pass"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "8e348751",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2b3457e",
   "metadata": {},
   "source": [
    "## Multilevel Inheritance\n",
    "- We can also inherit from a derived class. This is called multilevel inheritance. It can be of any depth in Python.\n",
    "\n",
    "- In multilevel inheritance, features of the base class and the derived class are inherited into the new derived class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2ad587ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Base:\n",
    "    pass\n",
    "\n",
    "class Derived1(Base):\n",
    "    pass\n",
    "\n",
    "class Derived2(Derived1):\n",
    "    pass"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "cb41332d",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbcb3277",
   "metadata": {},
   "source": [
    "## Method Resolution Order in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5e69151",
   "metadata": {},
   "source": [
    "- Every class in Python is derived from the object class. It is the most base type in Python.\n",
    "\n",
    "- So technically, all other classes, either built-in or user-defined, are derived classes and all objects are instances of the object class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "6c3da88c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# Output: True\n",
    "print(issubclass(list,object))\n",
    "\n",
    "# Output: True\n",
    "print(isinstance(5.5,object))\n",
    "\n",
    "# Output: True\n",
    "print(isinstance(\"Hello\",object))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33174260",
   "metadata": {},
   "source": [
    "- In the multiple inheritance scenario, any specified attribute is searched first in the current class. \n",
    "- If not found, the search continues into parent classes in depth-first, left-right fashion without searching the same class twice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0c0f3b6",
   "metadata": {},
   "source": [
    "So, in the above example of MultiDerived class the search order is [MultiDerived, Base1, Base2, object]. This order is also called linearization of MultiDerived class and the set of rules used to find this order is called Method Resolution Order (MRO)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5242224d",
   "metadata": {},
   "source": [
    "- MRO must prevent local precedence ordering and also provide monotonicity. \n",
    "- It ensures that a class always appears before its parents. \n",
    "- In case of multiple parents, the order is the same as tuples of base classes."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e4b6d96",
   "metadata": {},
   "source": [
    "MRO of a class can be viewed as the __mro__ attribute or the mro() method. The former returns a tuple while the latter returns a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8e706493",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(__main__.MultiDerived, __main__.Base1, __main__.Base2, object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MultiDerived.__mro__ #it returns tuples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "7b21c7aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[__main__.MultiDerived, __main__.Base1, __main__.Base2, object]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MultiDerived.mro() #it returns list"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "ae2e5577",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "fe4e5909",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Demonstration of MRO\n",
    "\n",
    "class X:\n",
    "    pass\n",
    "\n",
    "\n",
    "class Y:\n",
    "    pass\n",
    "\n",
    "\n",
    "class Z:\n",
    "    pass\n",
    "\n",
    "\n",
    "class A(X, Y):\n",
    "    pass\n",
    "\n",
    "\n",
    "class B(Y, Z):\n",
    "    pass\n",
    "\n",
    "\n",
    "class M(B, A, Z):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "6d710872",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<class '__main__.M'>, <class '__main__.B'>, <class '__main__.A'>, <class '__main__.X'>, <class '__main__.Y'>, <class '__main__.Z'>, <class 'object'>]\n"
     ]
    }
   ],
   "source": [
    "print(M.mro()) #printing MRO of class M"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ceb8505a",
   "metadata": {},
   "source": [
    "## Operator Overloading"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9661bc8",
   "metadata": {},
   "source": [
    "- Python operators work for built-in classes. But the same operator behaves differently with different types. For example, the + operator will perform arithmetic addition on two numbers, merge two lists, or concatenate two strings.\n",
    "\n",
    "- This feature in Python that allows the same operator to have different meaning according to the context is called operator overloading."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1cca043",
   "metadata": {},
   "source": [
    "what happens when we use them with objects of a user-defined class? Let us consider the following class, which tries to simulate a point in 2-D coordinate system"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ff1078b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Point:\n",
    "    def __init__(self, x=0, y=0):\n",
    "        self.x = x\n",
    "        self.y = y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "be15c6eb",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for +: 'Point' and 'Point'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-35-29f760c7677d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mp1\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPoint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0mp2\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mPoint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mp1\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mp2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for +: 'Point' and 'Point'"
     ]
    }
   ],
   "source": [
    "p1 = Point(1, 2)\n",
    "p2 = Point(2, 3)\n",
    "print(p1+p2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "331b0746",
   "metadata": {},
   "source": [
    "- we can see that a TypeError was raised, since Python didn't know how to add two Point objects together.\n",
    "\n",
    "- However, we can achieve this task in Python through operator overloading."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76e3cc6d",
   "metadata": {},
   "source": [
    "## Python Special Functions\n",
    "- Class functions that begin with double underscore __ are called special functions in Python.\n",
    "\n",
    "- These functions are not the typical functions that we define for a class. \n",
    "- The __init__() function we defined above is one of them. It gets called every time we create a new object of that class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "7b7348cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Point object at 0x0000023F651D1280>\n"
     ]
    }
   ],
   "source": [
    "# Using special functions, we can make our class compatible with built-in functions\n",
    "p1 = Point(2,3)\n",
    "print(p1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4179cab5",
   "metadata": {},
   "source": [
    "Suppose we want the print() function to print the coordinates of the Point object instead of what we got. We can define a __str__() method in our class that controls how the object gets printed. Let's look at how we can achieve this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "a80fc1de",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Point:\n",
    "    def __init__(self, x = 0, y = 0):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "    \n",
    "    def __str__(self):\n",
    "        return \"({0},{1})\".format(self.x,self.y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8320c5b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2,3)\n"
     ]
    }
   ],
   "source": [
    "#Now, let us try to print function again\n",
    "p1 = Point(2, 3)\n",
    "print(p1) #we have overridden print function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "0225dddc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'(2,3)'"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(p1) #would also return the same output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "6e2e8c1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'(2,3)'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format(p1) #would also return the same output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c05b88a5",
   "metadata": {},
   "source": [
    "So, when you use str(p1) or format(p1), Python internally calls the p1.__str__() method. Hence the name, special functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "580bf0b2",
   "metadata": {},
   "source": [
    "## Overloading the + Operator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ae00eac",
   "metadata": {},
   "source": [
    "- To overload the + operator, we will need to implement __add__() function in the class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "939fbb29",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Point:\n",
    "    def __init__(self, x=0, y=0):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "\n",
    "    def __str__(self):\n",
    "        return \"({0},{1})\".format(self.x, self.y)\n",
    "    \n",
    "    def __add__(self,other):\n",
    "        x = self.x + other.x\n",
    "        y = self.y + other.y\n",
    "        return Point(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "607b3403",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3,5)\n"
     ]
    }
   ],
   "source": [
    "#Now let's try the addition operation again\n",
    "p1 = Point(1, 2)\n",
    "p2 = Point(2, 3)\n",
    "\n",
    "print(p1+p2) #adding two objects"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1dbb4276",
   "metadata": {},
   "source": [
    "What actually happens is that, when you use p1 + p2, Python calls p1.__add__(p2) which in turn is Point.__add__(p1,p2). After this, the addition operation is carried out the way we specified."
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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"
    },
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"
    }
   },
   "cell_type": "markdown",
   "id": "e041e42a",
   "metadata": {},
   "source": [
    "### Operators which can be overloaded\n",
    "![image.png](attachment:image.png)\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5e957a5",
   "metadata": {},
   "source": [
    "## Overloading Comparison Operators\n",
    "- Python does not limit operator overloading to arithmetic operators only. We can overload comparison operators as well.\n",
    "\n",
    "- Suppose we wanted to implement the less than symbol < symbol in our Point class.\n",
    "\n",
    "- Let us compare the magnitude of these points from the origin and return the result for this purpose. It can be implemented as follows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "0bc3dfa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# overloading the less than operator\n",
    "class Point:\n",
    "    def __init__(self, x=0, y=0):\n",
    "        self.x = x\n",
    "        self.y = y\n",
    "\n",
    "    def __str__(self):\n",
    "        return \"({0},{1})\".format(self.x, self.y)\n",
    "\n",
    "    def __lt__(self,other):\n",
    "        self_mag = (self.x ** 2) + (self.y ** 2)\n",
    "        other_mag = (other.x ** 2) + (other.y ** 2)\n",
    "        return self_mag < other_mag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "a217e5bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "False\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "p1 = Point(1,1)\n",
    "p2 = Point(-2,-3)\n",
    "p3 = Point(1,-1)\n",
    "# use less than\n",
    "print(p1<p2)\n",
    "print(p2<p3)\n",
    "print(p1<p3)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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H3kIfRxkAgOC+DAWOnMriVD41JkG0Vxc1vn7uzrTXZ5I+cxVbUvbwfMoengfaBQ9g4iPjeGj8gCq9RntM+iNLUxfxZNyPrF34GmsXAh38iZownodiozDV6NdfPVDn1Mfhtzmoj70MtKkjBJEbJrwXtzpKgNb2f96R8vaxmSfDYuvcvErCoiykgbfUeeqQPg7KPK+a3xPKy5q+3WsO46mkXf/+9Oew3WRug/QawUNjPuXJ7SlsSpzGsDH+JZ+nJfJeMtAjioei/K/3LCJSSfNJhAQPIKrHpxw5dZjPvjrLmHqPebWxb9cerIAxuj8hzozJZOLxejQU+9fVIBIREWnprJcr9dgs5PiPBWB3bpAm0Jj6uUcYL241Ebt/L59vSyLhv3/kuOUwaxceZlPceNb//X76l32T8uxM1KJ32PuImS8+T2T7rsPss+SSsHo9CZuTeGrdQmJD1EVdxLm6M2bmAHrWtVn/9k0RTBPzJyo2ih7bd5CwcgdHRk2lv6eNfdsSOAWEz4xUb20RJ2s+iRD6MnFmX5YtzCD5lVVsGWp/vG511m838fKGkrdTj0cPsZMN/pH04zbo4ajBksXh/QA+3HpLSYOuU5/eGMnAGhLB47PtHbORunanvw8kO5jUtdyFY+xvaG8QgE7d6VOf4185y8ljALfQp7Y3VSIiIgBXzrJl/pustUCfsFsg5UeSFy5iWZ8lzHHUbXz/jxy3Qg9Hlaglg/0APbrTo56z/113/ezpQ5+wKOaERTEHyE9LYPHT69ny7TaWbY+oMfFou2ATE2ebmDgbuJDBljff4fm4H1n89h5+ZW/Cx/JAVR+L1Ft5+/gWxv72QcKd1vBuvPKyJiOLcwxw+H89/8iR6+8NUiY0ksfDd/B8cgJx+++nf48Elm0omeQ5dowmRRZxtmYzRwhAp/EzeTEcKMzg+Znr2VfHREvWY9tKV2CBPg/PJNZBd5CN/0xwuMytdf9O1qYBPe4i/LbSD0P6M9EH2LyDzx0t01WYwZbl61m2fA9H6j1A9zaGRhuADNZ+bGfJ3lLHt+8kob6HrMzzNsLLjv+h4+Of276R904BpjCGabChiIjUqhDzW4t4/itbyeSoq/7CikUlk3y+9+ymWpaSTWGjw6VhC9n38Q6OAD2ih9C/vqE0sn62njrMvhQz+47lVtm0XWgUC+aHAZB8vDRW61nMKWb2pfxYdSLSDn2Z+OwMpgEkZ9uf3LSM6mORBihrH9deZhyJW8+y5evZnu54iVynKStrkrc5XpL3ShafbTjsxJN25lczwjBiY+Mne0jeXjKBrOn340tXuhIRZ2pWiRA8OzNx0RymBQOWBB6LfI7F2zM4V70FUZjFvlXPcU/0pyQXls5a/wfHk5GRvIlZr6dwrloyJD99G0/O3sMpDITPrtTlzDiE2Pl9gQyen7mK5DPVjncliy0LX+X5VQl8bu1c+xjoKgwMe2Qq4T5wfNWbPLnhR/KrxXRq+zKefKXmjNHlymJMTiGpRius0vFX2z/+ua9W8egzJbNgx867S5MuiYi4ocuFheRfcPxjrVR3nIorXUIyOIr3SydHLZ881ZLAo/Mdv2xIfmERL39V7YvNlUKObFjC79YVgk9f5kb3rX/gja2fTyTxu9++yWN/3FYjcXPuTEl8xvK6/Ec+//2bPPbbJbz7bfWNz3ISoM4RQaqPRaqoq/06437CcVBmAKfilvHowgTei4cewU0wLM04hMcXliZ8f/sqG9OrlQWly+e+bHbyaYeOZ54J2LWeWcsLgQH8Zozm7hO5EZrR0JhSnYaw4J9/pscf32Rxyo+snb+ItUC74M709AHOXay0vJ+B/pMeZenCsFpmrYeJD0dxaPUq7olbR/8wE+E9CjEnH2afpeQ4fR7+I0urzWzfI3ouK44tZNaGFGZFHqBP2ADCTZ3h1GE+T8ziXCEY7xjN0lqWDbSraxRLV2UzeUYCya88xz0fdCb8bhN9yCL5q2McOWOjz8NRTFydwBa79+dOJo7ZRPL2DJ4f9RhrQ9tjvFJA+IKVzLmj4vgPziw5/ohV/vS/YwBDfbLYvz+r9N4ZiHplIU+5amy3iIi41L5XnmPEK45+25cXExcysStYv13PrIWlS0i+NJWKVS19MP1hIS9anuH5r9Yz663ufDSven04hNiHj7F29lNs6VpS1/UoPEbyf//I8QtQMuHqPMY0cEhIY+pn49D7WXD3AZ7/KoHpow4zZtwAevqU9BTZEp8F+PN4VOnqD8YhxD7Tly0LM1g7Yy6Hxo1gWA8DFJ5lX7wZM9Dnt2HUuWqm6mORCnW1X3uM5i8rf+TRJ1LYOPspPgu+hfDw2+jJWfbtOoz5jA18bmHOm/djaqLeEZ3GzeP9o08zfXUGL0+ay3sht3Hv3d3hmJkvUs5yrtCf2IeHsHb1AeedtHQlmpfNJT1Nesy+nzENWUBCROqt+SVCANoNIHbVSqL2b+Od5TvYbraRbzlbaQyegU53j+BPs6cypvq63vYOd8+DfPirbixbtImNiSnlxzF27cvUhY/y1N12Mq2e/oQ/8yr/ZdrE4iV7SU4xczyl9Hc+PoTPnslffmuqMst8fRnveJCP4rqx5IVNbDSfJWFz6UCYDrcQ+/qjzBlTwLLVjgbH+BP1wkJebLeKxZuzOJ52FjAQVSkO4x0P8lH8/8/atzbxbnwWR8qv2UCnu++q930TERE3diqhdPipgfBFC2vOBeLZmYmv/5HjU15j7eo3ebLPK9Xm2GjPvX94lV/1Wcdf30ypqOtK6/C/zH+E8F6NiKsx9bNnZya+/Qo9/r6Kpz/IYPu6ip6Xxq59eerNeVWG1/aIXsjOwE0892wCyfF7KH/p6+ND+Lw5vDajfr1YVB+LlKm7/dopfCYfxfVn2dub2PTVj2y3/Fj6GwOd7h7NqwunMqxJ59LxwTTvVf6rzzqeezMFc/phNqaXJCjahd3Fa/OnMib/U9audu5Z2w0dTBSHSaA7sWMa0GNORBrE49Lla9dcHUSdrIXkV+qR1sbPB2M9EhDmJbFMXw2x69by1B2lHxYWkm8FvAy0a1f/rnXW/EIuFwMYaNfBiV3yyuJpzHGv2MjPo/b9rtjIzyvtQePjQzuNMRQRkRvqMIsHvsZaovgw9cHynhPWC4VcBqfXRQ2unyvXi0Yf2tWRh3Ba/a/6WKREfdqvldr+9W3332jlZVg9yo3rcXzDM/z6lSyMMXP4+hknLtogIlU0zx4h1Rmd2GDwaVzhZWznc2MKokbGA4CngXZ1dZfzdHLiRkREpBGMHW5MPdrg+rmB9aLT6n/VxyIl6tN+dWbb30luVBlWhfUAm94uHa5ndzVMEXGW5jVZqoiIiIiIiBs6t30HGwuBUfczzcFqmCLiHEqEiIiIiIiIuNKVDLasygB8iI0ZQTtXxyPSyikRIiIiIiIi4kL5Cdt47xRgGs+0OzSMTuRGaxmTpYqIiIiIiIiIOIF6hIiIiIiIiIiI21AiRERERERERETchhIhIiIiIiIiIuI2lAgREREREREREbehRIiIiIiIiIiIuA0lQkRERERERETEbSgRIiIiIiIiIiJuQ4kQEREREREREXEbSoSIiIiIiIiIiNtQIkRERERERERE3IYSISIiIiIiIiLiNpQIERERERERERG3oUSIiIiIiIiIiLgNJUJERERERERExG0oESIiIiIiIiIibkOJEBERERERERFxG0qEiIiIiIiIiIjbUCJERERERERERNyGEiEiIiIiIiIi4jaUCBERERERERERt6FEiIiIiIiIiIi4DSVCRERERERERMRtKBEiIiIiIiIiIm7DKzs7y9UxiIiIiIiIiIg0CfUIERERERERERG34XHp8rVrrg5CRERERERERKQpqEeIiIiIiIiIiLgNJUJERERERERExG0oESIiIiIiIiIibkOJEBERERERERFxG0qEiIiIiIiIiIjbUCJERERERERERNyGEiEiIiIiIiIi4jaUCBERERERERERt6FEiIiIiIiIiIi4DSVCRERERERERMRtKBEiIiIiIiIiIm5DiRARERERERERcRtKhIiIiIiIiIiI21AiRERERERERETchhIhIiIiIiIiIuI2lAgREREREREREbehRIiIiIiIiIiIuA0lQkRERERERETEbXi5OgARERFxjQt5BeQXFnHZVsy1a9dcHY7b8PDwoI3Bi3Y+3nTw83V1OCK1UjkhLYHKVWkoj0uXVaKJiIi4E1vxFbLPXaCNwQv/tj7c3MaAh4eHq8NyG9euXePSZRu5Pxdy2VZMt04dMHh5ujoskSpUTkhLonJVGkqJEBERETdz4vQ52vl606Gd3pq52oX8AvILiugV2MnVoYhUoXJCWiqVq1IfmiNERETEjVzIK6CNwUtfbpqJDu18aWPw4kJegatDESmnckJaMpWrUh9KhIiIiLiR/MIi/Nv6uDoMqcS/rQ/5hUWuDkOknMoJaelUrkpdlAgRERFxI5dtxdzcxuDqMKSSm9sYuGwrdnUYIuVUTkhLp3JV6qJESLORSdzspcyevRuLq0MREZFW69q1a5rwsJnx8PDQahzSrKickJZO5arUpXktn/v9bmYvNQMm5i0fSbCr4xERERERERGRVqV5JUJatQJOp/9EHr4EhXTB29XhiIiIiIhII+SSsuIDNhyu9NGAkbw8y4Sfy2ISkYZQIqTJnCdl+VYS1dtFRERauZwD8fx9YwYnb3WfLwZ56XvZkpBKWnoBRXjh16Mbd0Xfy6gQf1eHJtIstexywp8h02MIzCrAxk8kLd/LofruetHMymdzuK+5fh8oshD/1mfsJpQn/jCSfk56e9uYMjLn6028tDGPIY9OIeYXKkvFuZQIEREREee4ep4Dm7ayYW8uNlfH0lRs2SS++wlx6cUY2ncj7L6+eGPl5DcZxC9fx3cTJvF0VDdXRynSfLSScsLg14VgPwAv0hqwX5HFQhp+3HeD4rou1kziFpe+uJ0/kmCjE455HWVkwC+n8qznJl56fx1502fwxHAlQ8R5Wl0ixPazlWIAT0+8vetxeTYrRdaSP3r5GDHUNn1sQ7Z1hvLzeeLdtv6PqvweGI14N3TC76vFFBVeAZroGkVEpFWwnTHz0Xu7SbnYhXHzR1P4+g4SXR1UUzB0pE/vzkTeNZro2ys10u/NJO71T0jc+jUHhk9iSFvXhSjSXLhtOVFJ5nELYHJ1GDVdzSVl9VYSL3YjZoGTkiBw3WVkwPBo5p5ey5IPNxPXOZboW50VmLi71pEIuZrL0V07WJOQTZ614mND+27cN320/S5XeRZ2/XMHO1OtFdlooz9hD4xl8vAuGBq7bTWWrUtZklD5EzNLZpvL/xY6/ZGa2c2r5znwcTybk89Tvvq1b0ciHhjH5CEdHdyDAo7u/oItOyycLL8HXvQcPJiJ948g8PAmFnyYXeN8ZfFFPvkkERd2sObjdCwFFfsHh9/DQw8MJEAJERERN1E69r3rBJZHd+Tori/46KtMTheAd+9g7ht/L5H9fGvsZWjfEb/OA3ni9/cS6pdJXFOHXXSetK+TOH3rBCIb3d+8MdduJHjs1Jpd3I1B3DnMSOK2TDLPoESItDIttJxwkaLvDxK/28zRjFxOF0D17wPg4DtBE8rbv4MNqcWETh9NWICjrVxRRhoJ/tVoRv37E3b982sGPT2SYK3sLE7Q8hMh1kzi39zKrlPF4OvLoKF96eoLRdkZ/MucTfzydaSOn8Tc/9WtImFxNZtdb28l/gx4h4QwdkgQPucy2POlhZQPN5NHpa5XDdnWnrb+9OwFUEzOiZIxcYG9fMtvvJ+x+iM4z561GzhwEPx6BHHn7b7kfZfBoTPnSVqzgZyrM3hiaPXESS4p761jQ2ox4EVgSBChvX3J/cFC2sF9vJN6gsgRV2q9jTlJW3npoAXa+zMovDd+eRn8y1yAJfkLXrpwhRdntrSxmyIicl1OZhD3Xjp7fw5iRLgJE1YsyenEvfMBR2fYqasKITMAACAASURBVIuMQYybGdT0cf6czYGE3WxO+Ikio5Fxs51wzIZeuwNexpsBa53bibRYLaWccDGv9l0YFH4Pg8ILSNv2BYkngoiePZjKd8LQuWbiqMnYMkncng0dBzOuPuVbU5eRhiCiRgexa42ZLd8MYl64gxfDIg3QwhMhVtK2liRBAoffyxO/qdxzYSTRWfv4x5K9pG2LZ+dtjzAuuPRyfzzCzjNA7wienj2YkqTnQMLu3MeSRXtJ+3gvRwePpp+hgdvaERz1CE9HAWQSN/sTEgklZn5tkyNlcuCgL5FzY4nuV9r1a2zZZEHZpG0+iGXISILLr7MYy/bNJUmQriE8MWc0oe0rHa4ok10rtxL/ZXGtd/LQQQuBUROYNz4Y75tK7t/kswdZ+WoSaalJJH5vIvrWWg8hIiKtybFUDt0zgZdnBle8SLg3hLi/biVx816O/sJx3dcUbDkWkj5PYuf+8xT5diFy+iQihwbh54wejE659gJOZuQC3Qh0+HZVpIVr5uVEc2EICKJfAEAuObsBOtInJLjZTJZqO5pK4nno+cBAetanDHVBGeltGkSEMZOklGOcDh9GYD3CFKlNyx7wcDaVncnF0NFEzJSawzcM3Yfx0LQgoIBdu9MrhpmU8fGqOqyl6zDmvjGLN14cSbDndWx7nYIfmFSRBCkVEDaSsb0AazpHsyr94qyZLTsLwNiNh6onQQC8gxj1u9FE1DWcrvcIHitPgpTqPJjoX/kDxRz6PrvR1yMiIi2RP5H/EVy17jMGExbpD9Z0Dh2tPcF+oxSdSWfXqhXMf34rn53y577/jOWNV2KIHu6kJAjglGs/k8qe78AweBCDqtfNIq1G8ywnpGFOHssAjPzi1vr2tHBBGWnoTehQ4EQGlpx6hilSixadCMmzHMMCBPxHf4djxbxNg4gA+C6D/ynLhPTsRZgROJzEitV7STuTi+1qya8M3ka821aaJLQh2zpFF0YMtFMI3dSFoFsBrBRW6kFWdg8M4b9kiKNCxNiXEVG1Z0L6hYUQaOc6AnuWdNrLKVRFJiLiXoII7Fzz08CevQFIO3W2acMpymTX8mX8adEOEopvI2b+4yx9ZgKRt3esmsR3iuu8dmsmce/txWLsxuTxIThp9UmRZqiZlRPSCLmczioGgunZtb77uKKM9CIg0B/4idMX6xuniGMtemhMTlZJL4WcbZuYva2urS+VrMDiDRj6Ev37wWS+fRDLwX2sPLgP8MKvTxCR90YQcXvHigxnQ7Z1Csfdwwx2ep6U3YN+gbXP4NG1VzCQ7vD3QYEOxvJ5Orm7i4iItBCe9hP97f3pBxxt1Qny67j2spUXzvgS+WR0LZMOirQG7lxOtBZ5nPsewIhPvb/UuKaM9DH6ALmcPpsLt2opXbk+LToRUiZg4ECG9KzrC7s/gZU6RRh6RTDvDRMnv01n73dpHErPJe+4hbh3LaQMH83c6SHlk4M2ZFsREZFWrbiYQlec1zuIUbPnEHEmnaS43Wx4PZUNPYIZOzaCEaE3oleIHXVeuxXLts1sSIXQ6VO0zKO4L1eVE+JaKiOlBWnRiZCA7t2AbLz7D2bcXY2YPfgmf3oOGcbkIcOYfLWYnKNJrPm7Gcs3X5AYFlJ1ctCGbNuEyu7B0dN5gOPM6JkTliaLSUREWgMrhTao0e3x5wJOAgE+rmlCeHcNYdTMEEZdzCRp127i311LnG8XIqMjnDdZaqOu3crpPXG8k2Cl530TeMyFy2CKNJ3mWU5IQ/jR6VbgsINnaZdryshCa0maJbCzyle5fi16jhC/4NsIBk4mHuSoo5WXcjJI/Gw38bst5JV+VJRl4Wi6BUtOpW5bN3kREDKSmPElk4OePpvb4G1doewe2JK/5oCj8XLWDPYmaPk+ERFpCAsn7cyTffrkDwCE9rAzQLwptQ8iYkosb7w6lYfCYO+Hn7DgTyvY5ZS8f8OvPeebOF77OJuAqAnMGxvk5GGzIs1VMy8nmq0r5XMOup4/AV0BLJw8U999XFFGFpNzOhfoQqAmoBYnaKaJECuFP1spquXHdhXoPJBx9xjhfCorV+/jZPVlYYosxL+3g7idZk76dCwfvlL4fRLvLN/KOx+nkXO16nnzzl0q+eNNXg3eti5eRoB0DjnM2jRCZxMT7/MFazZrlu0grXoypCiTXX/bQZLyICIi0iBWdm43V637rBZSEnPBGMKgfs3kTW/bbgyZEMMbb8TyxOjuTurq2rBrz0vbwcoPSxv445UEEXfShOXExVTWPLuM2fM+IC6twHnHbVJlSYdjWE66OpYKwSEhgJVUy/l67uGCMtL2A2n7gY5BBGnuJXGCZtKKqS6dlU87ntgTuhHz0lTC2hvpN3YSk89u5qPUvbz67EF6hgQT2s1IUXYG/zIXUAQEDh/N5KEVXagCho4k8qtPSEzdzUvPHSFseBe8gaKT6aSkWkuWfxrg2+BtaxfEL0b5smtbAYnvvMe/evji51lMp4gp19l91ovgMVOIObmODanprHw2g8CQIEJ7+5L7g4W09AKKjN2IvOcKiV/+dB3nERERt9KrG6EXknjpNQsRt/vhZc3j6H4LlgIvQmeMoF9z+7bv3ZHQqAmEOuNYDbn2rL28szKd0/gz5CYLCdvtdUnpzoixIajtLq1OE5YTtlOZHLhYDOSSeOw80aH1aX/fILZcTn5/vnQ+jJ/IAfj5J46mW0pevBp8CezVBT871x98h4nAL83E/20t2UODCDACXKHNLSMYdbtrrsnQ7zYijOkkfZHKyV9G0LOuV+UuKCOLzIdIskLwhIH0bPglitTQTBMhDWDsQsTjjxC4+wviv7BgMadz0lz6O9+ORESPZtzQLlUnUTMGEf1UDIHbdrAlOZuknRV9u7x7hxATO5pBbRuxbR16RsUw90o8axKyyTuVSx5edPJywiO4yZ+wxx8hYFfJsU+nWzidDuBFz8HDmHj/CAIPbyLx+s8kIiLu4kQXIpeMZNCOJHYmmzldAN69g4l+9F4i+7nwC0hTaMi1F13iNAC5HPg/ZjsHKzFQiRBpjZqwnDD0CGJI+wwOFPkSeVsj5gZ0oryDO3j1w2pjQ06ksmZ5avlfQ6c/whN2XnYagkcyd+7NbPnsEOYvzdgA767+3HmLC7+WGfpy3wPdSPrQTIJ5MA/9oo5n19RlpC2ThB2Z0NHExOGuffbSenhcunztmquDcCbbz1aKATw98fauR4FytZiiwislfzYa8a4tc92QbesRJz5G+0tPXQ8nxigiIq3PsRPZ3NarWy1b5JKy4gM2HDYxb/lIgpsssubAddde93MRaToqJ9zQ1VxS3lvHhmOdiVkw1cGytq547lYsW9eyJAEin4xt0EozKlelNs10jpDGM7Q14t3WWL8kCMBNXiXbt61H0qAh29YjTqcnQcCpMYqIiIiIiBu4yZ+whycQ2T6bDSt2Y2km8wvmfFOy0oyW2xVna/lDY0RERERExI2V9VRowC42T/y4Ql5DXhwOGMnLs0zlCzDcEN/vZvZSx0NIairmwk02Olz1bsA+ZfMtVvvYGET0UxPweusz3vmbF/N+F0FPF+Yecr75hFc/zGPIQzHEDNGSueJcSoSIiIi4EQ8PD65du4aHh4erQ5FSeh7S3LS8csKXfqMnMHdkA3YpvkQBN+PbkG9Dxo40JN3QKF0HMnd2QwadXOFi7mXa+zckMi8CHE0D4h3MuGfmMK4BR7tRAoZP4o3hjdu3Zf37FVdQIkRERMSNtDF4cemyDW9jG1eHIqUuXbbRxqAmmTQfLa+c8CIgOLh1TEjctgv9QlwdRMunclXq0uomSxURERHHLuQVYLXZCAyo3idaXOV0zkWMBgMd/Fr5ajzSYqickJZO5arUpdVNlioiIiKOdfDz5bKtmAv5Ba4ORYAL+QVcthWrsS7NisoJaclUrkp9qEeIiIiIm7EVXyH73AXaGLzwb+vDzW0MGkvdhK5du8alyzZyfy7ksq2Ybp06YPDydHVYIlWonJCWROWqNJQSISIiIm7qQl4B+YVFXLYVc03NgSbj4eFBG4MX7Xy89cZSmj2VE9ISqFyVhlIiRERERERERETchuYIERERERERERG3oUSIiIiIiIiIiLgNJUJERERERERExG0oESIiIiIiIiIibkOJEBERERERERFxG0qEiIiIiIiIiIjbUCJERERERERERNyGEiEiIiIiIiIi4jaUCBERERERERERt6FEiIiIiIiIiIi4DSVCRERERERERMRtKBEiIiIiIiIiIm5DiRARERERERERcRtKhIiIiIiIiIiI21AiRERERERERETchhIhIiIiIiIiIuI2lAgREREREREREbehRIiIiIiIiIiIuA0lQkRERERERETEbXhlZ2e5OgYRERERERERkSbhcenytWuuDkJEREREREREpCloaIyIiIiIiIiIuA0lQkRERERERETEbSgRIiIiIiIiIiJuQ4kQEREREREREXEbSoSIiIiIiIiIiNtQIkRERERERERE3IYSISIiIiIiIiLiNpQIERERERERERG3oUSIiIiIiIiIiLgNJUJERERERERExG0oESIiIiIiIiIibkOJEBERERERERFxG0qEiIiIiIiIiIjbUCJERERERERERNyGEiEiIiIiIiIi4jaUCBERERERERERt6FEiIiIiIiIiIi4DSVCRERERERERMRtKBEiIiIiIiIiIm7Dy9UBiIiIiGtcyCsgv7CIy7Zirl275upwpBYeHh60MXjRzsebDn6+rg5H3IjKCWkJVEZKQ3lcuqwSTURExJ3Yiq+Qfe4CbQxe+Lf14eY2Bjw8PFwdltTi2rVrXLpsI/fnQi7biunWqQMGL09XhyWtmMoJaUlURkpDKREiIiLiZk6cPkc7X286tNNbs5boQn4B+QVF9Ars5OpQpBVTOSEtlcpIqQ/NESIiIuJGLuQV0MbgpS83LViHdr60MXhxIa/A1aFIK6VyQloylZFSH0qEiIiIuJH8wiL82/q4Ogy5Tv5tfcgvLHJ1GNJKqZyQlk5lpNRFiZBmI5O42UuZPXs3FleHIs3PRTMrZy9l9gozea6ORURatMu2Ym5uY3B1GHKdbm5j4LKt2NVhSCulckJaOpWRUpfmtWrM97uZvdQMmJi3fCTBro5HRESklbl27ZomPGwFPDw8tIKH3DAqJ6SlUxkpdWleiZBWrYDT6T+Rhy9BIV3wdnU40uoVZVnIzAO/nsEEtnV1NCIiIiKtRS4pKz5gw+FKHw0YycuzTPi5LCYRaQglQprMeVKWbyVRvV2kiZzev5V3EiDyySeJViJERJpQzoF4/r4xg5O36ouBQ1etnPw2iZ1fHCPtlBUbXgSG9CVywkjCehpdHZ3IDdeyywl/hkyPITCrABs/kbR8L4dcHZKzFFmIf+szdhPKE38YST8nvb3NS9/LloRU0tILKMILvx7duCv6XkaF+DvcJ+frTby0MY8hj04h5heOtxNpDCVCRERExDmunufApq1s2JuLzdWxNGcX09mw8gtSThXj3TuYiPv88LLmcXR/OhtezeD4bx8hxqTVOqSVaiXlhMGvC8F+AF6kuToYZ7FmEre49MXt/JEEOyMna8sm8d1PiEsvxtC+G2H39cUbKye/ySB++Tq+mzCJp6O62d014JdTedZzEy+9v4686TN4YriSIeI8rS4RYvvZSjGApyfe3vW4PJuVImvJH718jBhqmz62Ids6Q/n5PPFuW/9HVX4PjEa8GzrP1dViigqvAM65RluRleIr0NBrKI/F5oV3Qwrhxj6jRt7r6+KKc9biup6ViLg92xkzH723m5SLXRg3fzSFr+8g0dVBNVd+3egTGETQg6OJqNz7424zK1/eTcqnB7nr9gh6akp7aWVUTjRjV3NJWb2VxIvdiFngpCQIgKEjfXp3JvKu0UTfXimRcW8mca9/QuLWrzkwfBJDHPReDhgezdzTa1ny4WbiOscSfat6zIlztI5vO1dzObprB2sSssmzVnxsaN+N+6aPtt/lKs/Crn/uYGeqtSIbbfQn7IGxTB7eBUNjt63GsnUpSxIqf2JmyWxz+d9Cpz9SM7t59TwHPo5nc/J5yhd98u1IxAPjmDyko4N7UMDR3V+wZYeFk+X3wIuegwcz8f4RBB7exIIPs2ucryy+yCefJOLCDtZ8nI6loGL/4PB7eOiBgQQ0pDFW2t03fms6aRcrzdZsNBIaNZqYUcH4VT/eRTMrn91N2oCRvDwziKPl19+NmJemEta+9lMWnTQTvymJpB8qzw7tRXB4BFPGm+jpoFufLSuVz7Z8SWJ6pf18uxD5wL2MHWLls9mf1BzOVDapb9Qklk8IqnnQst87GCvaqHPWV/mEwxUSly6taGRUj6kxz0pEWrnSse9dJ7A8uiNHd33BR19lcroAvHsHc9/4e4nsV7O3gqF9R/w6D+SJ399LqF8mcU0ddtF50r5O4vStE4hsyvGn3+9m9tJsYl6MYVCRmfiPvibluBWb0UhoeATRowcSWL3dfpM/YQ9PqHmsgBDCBu4m7WAWmXnQs466T8R1Wmg54WpFP3FgVxI7U0rulaG9P6G/vIfJzaC9lbd/BxtSiwmdPpqwAEdbNea5GwkeO7Vmm9YYxJ3DjCRuyyTzDA4TIWAk+FejGfXvT9j1z68Z9PRIgrWgkThBy0+EWDOJf3Mru04Vg68vg4b2pasvFGVn8C9zNvHL15E6fhJz/1e3ioTF1Wx2vb2V+DPgHRLC2CFB+JzLYM+XFlI+3EwelbpeNWRbe9r607MXQDE5J0rGxAX28i2/8X7G6o/gPHvWbuDAQfDrEcSdt/uS910Gh86cJ2nNBnKuzuCJodUTJ7mkvLeODanFgBeBIUGE9vYl9wcLaQf38U7qCSJHXKn1NuYkbeWlgxZo78+g8N745WXwL3MBluQveOnCFV6cWc+xm1dzObB6HWu+K4nFr0cX+vXrSPH3mfzPiQLSPt/K84dMzP2jo0xzLilrk4g/WP/lrnL2f8Kr6zJLxhv2CebOfqVdjL/LxJK8m1ePnuCxWeMYVK1Qt32/m9eWmjlNaUV0e2+6cp60f2eTuGYDaSdNTp/L5Yaf86ab6dmr5N9HcU5uScXU1Z+Asnvd3rNi2+t+ViLSqp3MIO69dPb+HMSIcBMmrFiS04l75wOOzrBTFxmDGDfTTnL4Rvs5mwMJu9mc8BNFRiPjZjd9CPATx5N3k5icTsDQEEb2g+KzP5CU8AUv/fsn5tW74e6JwedGxyriRC2lnGgOctLZsGIHKWe86BduwuQLxecz2fv5VhYccOJQlMawZZK4PRs6DmZc9WdmT0OfuwNexpsBa53bYQgianQQu9aY2fLNIOaFO3gxLNIALTwRYiVta0kSJHD4vTzxm8o9F0YSnbWPfyzZS9q2eHbe9gjjgksv98cj7DwD9I7g6dmDKfl+PJCwO/exZNFe0j7ey9HBo+lnaOC2dgRHPcLTUQCZxM3+hERCiZlf25v+TA4c9CVybizR/UpLw7FlkwVlk7b5IJYhIwkuv85iLNs3lyRBuobwxJzRhFZ+g1SUya6VW4n/svbEwqGDFgKjJjBvfDDeN5Xcv8lnD7Ly1STSUpNI/N5E9K21HqI8ljXfOYrlJ5LWbuajVDPvrA7g2cdNNXuafG9mJ75E/uf9Fd3nrtZyyjP7WLMukyJjF8bNnsSoyjVIdAFpn25g5Z4M1n5spk/lZM5FM/9YYeY0XoQ+MIWHwruUXjeMm1IygdfKNWZS6rrkhmiKcwaP4On5I4CK3j4jfvOInWfnhGclIq3bsVQO3TOBl2cGV7xIuDeEuL9uJXHzXo7+wnHd1xRsORaSPk9i5/7zFPl2IXL6JCKHBlV5q5r3TUlvyNo5ZxLzlISfiHlxVpU3qRH9NvH8xgY03K+e5WQaYOxCYMuaOVLcVTMvJ5qPXA58/AUpF7sR8/xUwjpX/GbsL0tekq3ZcRvPTgiqtaf5jWI7mkrieej5wMD6DclzynMv4GRGLtCNQIc9UCp4mwYRYcwkKeUYp8OHEViPMEVq07K/2pxNZWdyMXQ0ETOl5vANQ/dhPDQtCChg1+70imEmZXy8qhY2XYcx941ZvPHiSII9r2Pb6xT8wKSKJEipgLCRjO0FWNM5mlXpF2fNbNlZAMZuPFT9yyyAdxCjfjeaiLoyzL1H8Fh5EqRU58FE/8ofKObQ93U1JKvGEjPLXixdiHh0AqO6gi01icSjdpIzVjBNn1J1DKHDf6XFHE3ajwUIfWBs1SQIwE2+hN4/jnEdwZb6NSknKu33RRJpVgi8bwKP3dWl6nUDAUPG8dgDzsw2u+KctXDGsxKRVs6fyP8Irlr3GYMJi/QHazqHXFQuFJ1JZ9eqFcx/fiufnfLnvv+M5Y1XYogeHlSja7mh822Mus9Ux09356xWET6EIdUa8wFDhxABWFKOcboeh7AdOcTO8xA4qn+lFx4izVnzLCeanZNm4lOLCYi6q0oSBMBw62Aib4Oc5GOcrO3l340M71gGYOQXt9a3HeqE534mlT3fgWHwIAbVZxigoTehQ4ETGVhy6hmmSC1adDWbZzmGBQj4j/4Ou5x6mwYRAfBdBv9Tlgnp2YswI3A4iRWr95J2JhdbacFj8Dbi3bbSJJsN2dYpujBioJ1C6KYuBN0KYKWwUg+ysntgCP8lQxwVIsa+jIiqPRPSLyyEQDvXEdizpPtiTmHdBVre9xWxOBxbWNq1DYpJSsu0s0Ff7hxY35nys/mfb4qBYMJMDrrg3dQNU6Q/YGVvena1/boR+R+OM++BgwczqJ6R1D/WpjynY855ViLSugUR2Lnmp4E9ewOQdups04ZTlMmu5cv406IdJBTfRsz8x1n6zAQib+9YI7FcxvvWwYwbO7KOnxDq8TKyTv16dq5Zths6EzQAOJHN6RpvY6rJMfOPD9KxdTURc5f9FRREmp9mVk40U3kns8gBQnvZuVn4E3gLYP2J03lNHBgAuZzOKmlP9+xa332u87lbM4l7by8WYzcmjw+hfiv0ehEQ6A/8xOmL9Y1TxLEWPTQmJ6vki23Otk3M3lbX1pdKVujwBgx9if79YDLfPojl4D5WHtwHeOHXJ4jIeyOIuL1jRWOmIds6hePuYQY7PU/K7kG/OvrQdu0VDKQ7/H1QoINEgmf9u7vknK5fLN4BHTGQie1MHnlQ9U3cgO4E1feGXjxfOjGshX/8aWnd8ZUlc8r360JgbRnott3p1wsOnahlm/pyxTlr4ZRnJSKtnKf9RH97f/oBR+uRIHcn9upo8CegK3C4UhvEHmsmcSt2k0Y3YmZpXiZpSVRO1EfOuZLEQNLKZSQ53Oo8eT8DTT5Jch7nvgcw4lPvLzXX8dzLVqc540vkk9G1TMxak4/RB8jl9NlcuFVL6cr1adGJkDIBAwcypGddX9j9q8zabugVwbw3TJz8Np2936VxKD2XvOMW4t61kDJ8NHOnh5R/6WvItuIKHRlyX1Ddb/SC6tvTREREHCouptAV5/UOYtTsOUScSScpbjcbXk9lQ49gxo6NYESo/V4hRd8fJOFIbh0H7s4IJ/UKqakYW13fA6/jS4FIs+WqcqK5Ki4pCIKHmuhXy+iTri09CVrnc7di2baZDakQOn2KlsIVl2rRiZCA7t2AbLz7D2bcXY2YW+Emf3oOGcbkIcOYfLWYnKNJrPm7Gcs3X5AYFlJ1gsmGbNuEyu7B0dN5gOPM6JkTlhsfS2D9YinKOV+yDHFXv+tLILXvSE8jpFm7cOeokYTWN4tdvl9J17pgR5n3n7M42oieGUV5dvo13uBzNlSTPysRaYGsFNqgRrfHnws4CQT4uKYJ4d01hFEzQxh1MZOkXbuJf3ctcb5diIyOqDFZqu3sMXbtrHuOq4FOSITkWu2tzlZAXg7AzXjba+9fLSDt05IvBYNm6EuBtETNs5xobsraXX2Gj2RcP1dHU50fnW4FDjt4lnY15rlbOb0njncSrPS8bwKP1bbqpgOF1pI0S2Bn9QaR69ei5wjxC76NYOBk4kGOOlp5KSeDxM92E7/bQtnX06IsC0fTLVhyKr2mucmLgJCRxIwvmRz09NncBm/rCmX3wJb8NQccjZezZrA3oR5LU11vLLdWxJLiaBIjWyYJOzIBLyJCr3f5tG78f8O9gHSS9jt6BlZOfrOb+M92c+BkcbX9skn878ySL/p2nD54kEP2fnFTabl/NMvO5HcFpH1rL+l0ned0sqZ/ViLS8lg4aSeHcPrkDwCE9rA31r0JtQ8iYkosb7w6lYfCYO+Hn7DgTyvYVakI9hs+leXLn6zj5/pXjAE4mZFVc1J221kyDwO9uhFYY1iMFcu2DazcYyV0+gweq+dykyLNSzMvJ5oJv57dCYD6LT7Q5EqH8GHh5Jn67tPw557zTRyvfZxNQNQE5o1tzOo4xeSczqXOYeYi9dRMEyFWCn+2UlTLj+0q0Hkg4+4xwvlUVq7ex8nqLZAiC/Hv7SBup5mTPh3L32gXfp/EO8u38s7HaeRcrXrevHOXSv54k1eDt62LlxEgnUMOszaN0NnExPt8wZrNmmU7SKueDCnKZNffdpB04/MgVWLZsMJeLD+R9P5Wdp0Bw8AIIvtd71sCL/qNHEEokLZxMx/9u2YyJOebeN7+0Myu/RDQ1ativ3sjCDXC6Z1b+ceenyiqNkt3zoF4/vHxefunLZtA98R+4r6pfE4rp/fEs+E7B7Fezzkbw6vkeg8dstRMvDT5sxKRlsfKzu3mqnWf1UJKYi4YQxjUXMqFtt0YMiGGN96I5YnR3V3X1fW7vez8vmplm7P/AElAcNht1ZZ6rHgzGjothica8WZUpHlownLiYiprnl3G7HkfEJdW4LzjNoWeJsYN9CLn8z0kZtlvlOdddN01BYeEAFZSLfVthzbsueel7WDlh6VJkPGNXCLY9gNp+4GOQQRpCKE4QTNpxVSXzsqnHU/sCd2IeWkqYe2NNFCJPAAAIABJREFU9Bs7iclnN/NR6l5effYgPUOCCe1mpCg7g3+ZCygCAoePZnKlNy0BQ0cS+dUnJKbu5qXnjhA2vAveQNHJdFJSrSXLPw3wbfC2tQviF6N82bWtgMR33uNfPXzx8yymU8SURnUNq+BF8JgpxJxcx4bUdFY+m0FgSBChvX3J/cFCWnoBRcZuRN5zhcQvf7qO89Q/lofOrGPNdyWx+PXoSL9+HSn+PpP/OVHyPAw9TMx92FRjueNGCRhMzBM/8c7KdJLe/YB/de1C6IBuBJDH0e8ysVwsBmMXxj32y6orC7U38disHF5baibt4w0s+MKf0Nt705XzpP07m5MXiwmMMhGWYCal+jkNfYl8oBspH2aT9uE6FuwN4s5b4Ph3mVguQujAbqSl2kmTX885GyF4kInAnQc5/eVW5n/nT1c/KA4YzNxHTfi54ln9P/buPijKO833/xvttm0xoBAVDHjsqAyTNgUeGaNmxQnoKLuagox52MGTp8lujVnH3RznzGZzsjVnTmVzkuz6c36uq2fdTMakZCYxTqA0E3UCzAR/EWNwY9eAwyCmU4LSakC7FdqmW/j9AShC89A8dbf9eVVZpU3ffV/dN15939f9/V5fEQkvsxKxXi7jldftZN4fg8Hjoua4HXuzAeuTS0kZ2U7hw2eOw7oiF2uQdm9dEMfRrbuoW2bFEt3tPGFGGo8svn36rtv2W15/vwHvXdOJv3ySAx/6ecHYeaxYljzI1RREgmQM84T3XB0VV3yAk5LTTeRZg9j7zeuk/kxTZz+MizQCXLtITbW948arMZqEWdOJufn+Y8l4Jpe6N/ZR+OouTi5KJSWuo7+hr6mBqqqLOJasY3tucN6TMWUemaZqyj6upP7BTJIGOu8L5LifP8q2ndU4iCVjnJ3ij/yNnB64V5PbdpIyD1hy55MU+FsU6SVECyEBME0n86+fJaH0Yw58bMduq6be1vmz6Dgy83JYu2j67U3UTMnk/SifhP0H+eBIA2Xd5g+bZ6eS/1QO6ZOH8NwBJK3IZ9ONA+wubsB1zokLA3cbRuAQjItlyV8/S/zhjtd2VNtxVAMYSFr4AI98dykJp96lZPh7GlQsGc/8NQlpZRwoqqbq3EUqznUWYKLjyFiZySNZltvmcA9XjDWHv38pmQ/3l1FWeZGKC10FHwMx8xfy9BOZpPgZQmeck8XfvxRP4S/LKPvKyckjnb840dPJfnolazI8fFhs670hEL84j7/nt+x+v5b6L+2UfAmYYlmyfg2PTavkBX+FkGHuM2BJmWzaBAXv2Ki64qT+ChjjuzUVDsKxEpEwcnY62VuySD9YxqEjNhzNYJ5tIe/7K8lOUfPpXqwr+cdlVXzw4UlKv/TgNZmwrlhJXs58EnpcDHrdzR0j9a5epOxQHzcp7otnuQohEurGME8Y70kmY0otFe5osucNoTfgCHKdOMhre3qc652tZPf2ypv/tK5/9vbRXqZk8v7ns1hLf8eh8moOH++Ysm2eEcs3/utS8h6cPhah+2ecy+pHEynbY6PYtpCnFwxw7AI57u7rnVPJnVT8tu9z3H57NXVN147rXVgWGaqo663t7cEOYiR5r3nwAYwfj9k8iCJDmw93S2eDM5MJc3+V60CeO4g4mWTyv/TUcIxgjCPB6/bguwEwHvPkMai7eT0dSxQChkA+X48Htxduj7OOwo37KCGNzX3NIe/2eQe0vz73OUo8Htzj+v99GPNjJSJBcfpsA/NmJfbzDCflO96i4FQ/uU9uOVPKxq223hc9Y2DgYykyNMoTEajNSfmudyg4PY38l57oYwWrYBx3D/ait9lSDNkvPBVQU2nlSOnPHXe1Y5xsCmze2TjD4C/6AnnuAIyTR6kz/AjGOBKM5gCPx7B3OMTij8nkv6P/QIbzeQ91n0Pd1wBPGfNjJSIiIiKhYVwsS57JxfHGPgp2lJLw4ywsIbCQVeOxzn5K65/UyloyokLnillERERERCRgXSMVAtjEO54YbuAK5C7QfVm8+nzazQUYRkXnKLPB83F5nJepbYFMpOvqt9jjYVMyeT/KxfCzD9n2bwY2/00mSUGsPTQe28dre1xkPJ1PfoaaSsvIUiFERERERETCWDQpOblsygpgE991mplIdCBXQ6a40e/bM2M+mzYGMunkBlecrUyJDSQyA/F9tQExW1j7Dz9kbQCvNlriF6/jnxcHOwq5U6kQIiIiEkGioqJob28nKioq2KHIMOgYymgKvzxhIN5i6XfVkbAxeTopqcEOIvyF1++vBMMd1yxVRERE+nbW8TXTpsZgNk0IdigyDG5PK5cuu5iVcHewQ5E7kPKEhDvlSBmIFsYUERGJIHdNMuO81hLsMGSYnNdauGuSFteV0aE8IeFOOVIGokKIiIhIBJkaE02r18flq83BDkWG6PLVZlq9PqbG9DXJX2R4lCcknClHymBoaoyIiEiE8fpu0PD1ZSYYDcROnsTECUbNpQ5x7e3tXG/14rzWQqvXR+LdUzEaxgc7LLmDKU9IOFGOlECpECIiIhKhLruaudriptXro12nAyEtKiqKCUYDd00y6y6njCnlCQkHypESKBVCRERERERERCRiqEeIiIiIiIiIiEQMFUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhFDhRARERERERERiRgqhIiIiIiIiIhIxFAhREREREREREQihgohIiIiIiIiIhIxVAgRERERERERkYihQoiIiIiIiIiIRAwVQkREREREREQkYhgaGs4HOwYRERERERERkTGhESEiIiIiIiIiEjGirre2twc7CBERERERERGRsaARISIiIiIiIiISMVQIEREREREREZGIoUKIiIiIiIiIiEQMFUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhFDhRARERERERERiRgqhIiIiIiIiIhIxFAhREREREREREQihgohIiIiIiIiIhIxVAgRERERERERkYhhCHYAIiIiEhyXXc1cbXHT6vXR3t4e7HCkH1FRUUwwGrhrkpmpMdHBDkciiPKEhAPlSAlU1PVWZTQREZFI4vXdoOHry0wwGoidPImJE4xERUUFOyzpR3t7O9dbvTivtdDq9ZF491SMhvHBDkvuYMoTEk6UIyVQKoSIiIhEmLOOr7kr2szUu3TXLBxdvtrM1WY3sxLuDnYocgdTnpBwpRwpg6EeISIiIhHksquZCUaDLm7C2NS7oplgNHDZ1RzsUOQOpTwh4Uw5UgZDhRAREZEIcrXFTezkScEOQ4YpdvIkrra4gx2G3KGUJyTcKUfKQFQIERERiSCtXh8TJxiDHYYM08QJRlq9vmCHIXco5QkJd8qRMhAVQsaY69i7bNy4lZ3HnMEORUREIlB7e7saHt4BoqKitIKHjBrlCQl3ypEykNBaPvdMKRu32gZ+3op1bM9NHv14REREREREROSOohEhIa8ZR7WdmuqLaJabiIiIiIiIyPCE1oiQm9LYvD0LS7DDCAlNlG8vokSfiYiIhInGigP8x69qqZ+TxavPpxET7IBCUZuH+v8s49DHp6k658GLgYTUuWTnZrEkyRTs6ERGnfJEiHLbOfCzDynFyoa/yyLFPDIv66o+ygfFlVRVN+PGQMw9iSzPW8mq1Ng+t2n89F1e+ZWLjO8/Tv6Cvp8nMhQhWggRERGRsNPWRMW7RRQcdeINdiyh7Eo1BTs/pvycD/NsC5mrYzB4XNQcr6bgtVq+/KtnyU/TsqVyh1KeCF2eOgr/pfMG7I+zsIxETdbbQMm/76Ow2odxSiJLVs/FjIf6Y7Uc2P4OX+Su48UViX43jX/wCV4e/y6v/PwdXOufZMNiFUNk5NxxhRCv24PvBmA0YR6jGyrB2Gef2ny4W250/D0U4hERkYjgvWBj765Syq9MZ+2Pc2h54yAlwQ4qVMUkcm9CMsn/LYfM7qM/vm1j56ullP/6BMvvzyRJE5jlDqM8EcLanJT/ooiSK4nkvzRCRRAAYxz3zp5G9vIc8u7vVshYWUfhG/soKfqUisXryJjsf/P4xXlscrzNlj3vUTjtKfLm6OJGRsYdUgjx4KgoY+/7ldQ033rUnDqfxx/JJMP9aUcT1h5NVu1FW9lSDNkvvEDenN6v2vVz6/pn/VQgh7bPwera9y02tmy81Ui2V0zui1QcLuWDIw24PLceNk5JZPX6nH6HnYmIiNzipHzHWxTMyGV7Xhw1hz9m7+/rcDSDebaF1Q+vJDul92gF45Q4YqbNZ8PfrsQaU0dhECIPijOlbNzaQP5P80l32ziw91PKv/TgNZmwLsskL2c+CT3P28fFsuSZ3N6vFZ/KkvmlVJ04T50LkqaMyTsQGQLlCeic7vHRSWxfDm56m/e8jcJ3b+UIy6IHefzhNAzH3+KV92cHdRq86/hBCip9WNfnsCS+r2cN5bibsKx5ovf7MiXzrQdMlOyvo+4CfRZCwITlL3JY9Yd9HP7lp6S/mIVFKzvLCLgDCiEe7EVvs6W4GTrnm6XfHwcNX3GyupLdr9qp62O4VUjvc3IsSbMAfDSe7ZhLlzAr+uYBizF1O3SNNt58o5STzYDJRFLqTL4xzcefahqov9DQMexsdS6b1ySjvCEiIoNSX0vhrmqOXktm6bI00vBgP1JN4ba3qHnySTYs6lFgNyWz9geRuqLbRb48UkrJkWriF6WSlQK+S19RVvwxr/zhIpsHfeI+HuOk0Y5VZARFbJ7wUP/bfWzZfxHu6Zze1jndo+C1Wk76mcbhPVPK61ttOEyxZDyUSrzpBo3VZbz2L+fJnOkM0vvoCq6Oko8aIG4ha3seM38CPe59MJgmAp4Bn4cxmRU5yRzebeODY+lsXhY3qNcX6U+IFkKqKHjjK7/BfevRZ8nuVlJ0HS9kW3EzmBJ57IW824aYPtbWRMUv97G7uHZEoxuLfVpWPMuLKwDqKNy4jxKs5P/YT5XYW8eBHR1FkITlOWz6biox3YbSuus/Y/fWo1QdKuLNuzW3TkREBul0JScfyuXVH1huFdFXplL4T0WUvHeUmgU5pIxldf2KjZ0vl1I1wNO6j/J0HXuXl/Y0DLDFyDQjLy++SP5Pn7/tTmpmyrv85FcBnLi3XaK+CjBNJ0GdIyUchFqeGCNe+6fs3n+R+BW5bH7Ygrnr3PvPnZTveoeCPQcpT32CJTdHdTVRXmjDQSL5Lz1xK0+syWR50ds9RoGPPW9NJSVNkPTo/MFNyRuR495Mfa0TSCShzxEot5jT0sk01VFWfhrHsgdIGESYIv0J0UKID8dZ/5XRb7R1+4e3lkPvNeAlmlUb15GZ1OPtjIsj43vraHG8zd6vRii0YOyzH43HSjl8AYzzs9jQowgCYE56gOc2NvP6FhtV7x+lZuGd+YUkIiIjLZbsP7PcPpLQZGFJdiwl71dzsmYlKdYxPI0wxWFdnUbSAE9L7lZAME6bx6rV0wfYYubIrFaxLIOMHifz8YsyyPzVgUGfuHv/eJJDTZDw8DexqD+IhIUQyxNjwkPV7204SObpFd2KINAx7S0rlYLKSk5WO1nSdQOyvpKSr8C4vGeeMGH59gNYiwcu8o6m+tO1gIkFcwY70mIEjvuFSj75AowL00kfzDRA42ysi6DsSC32xgcGVTwR6U+IZqZk8jYuxN/AuZgZ3f5Rf5ZyD3DfAyy39PFWxsXxrW8ns3d33ciEFox99slJzR+aAAOZK9OI7+OkyWh5gNULbOz+opoqew4pKaMcloiI3AGSSZjW+9GEpNmAjapzl8A60lNP+2FOJnNNYEPqzXMWstZPD7DRkJI0rff0U+M0ku8DTjXgcENCf8tQNtp4861qvDPSyF8+hp+ryLCEWJ4YExexnwBmJZPkr6/F9OlYgSqHC+gohLjOn6cRsP6XxN55YkocSSaoGsQMkdHhxHHeB8wlacaAT+40zOPuqaNw11HspkTyH05lcCv0GohPiAUu4rgCqBAiwxSihZA47k21DDhM1XXhYseyWzPj+r2bY05OJok66kcgsmDss59ocJwCmDZAVTSa+BkGwIejyUlXUhYREenbeIz+CuxTYkkBalp8Yx1QSDOO9/doLPEzgFPXcXugz7N9Tx2FO0qpIpH850dwtQaRUReBecLVhAPg7FFe2Xi07+ddbsZN53/7zhHtCfH+lsWO4e45wKkRjnPQXHx9BsDEpEGPGh/Gce9aneZCNNkv5PXTmLW3SaZJgBPHJSfM0fWMDE+IFkJEREQkJPl8tARjv+46ykpOM1BLweQHskjvvFPpPnOC4j8OtMVMlq5JHaWbiz68A10HDuOiQCRkBStPjIWuafpxiWQumt73aIZYf0WPO9yAx92Dff97FFSCdf3jWgpXgiqsCyExM6ZjpAHv+SZcJPc5QsNdN5SRGR6cl8d6n4GKIeE+4NQlHI1An/Prmmm80HEmlhCn6qmIiAyGhxYv9BrHfa2ZeiB+0hifQniaqDpkG7hZ6jdvFUK8l05z+NBAzVJh/ggUQpyeG34ebcbVCDARs7/z/bZmqn7dcVGQ/qQuCiQchVieGAtT4kgAquLnkb1m4eByR+foCUdjM8zpWSBpweUY2RAD0zUipY9j6ddQjrsHxyeFbCv2kLQ6l+eGsIBDi6ejzJIwTdczMnzhnZ2SZrHEZKPs1Gd8Yrey1l/PjrYmPv99H706DB3TRf5U3wQ9mwNdO03FiVHY54iKJeX+ODjVRNnHNjIt/vuEeO2fcegLwJSKNViLk4uISJixU98A1lm3P+qo7+gEbr3HzwTx0TQljQ3b0wLaJGbxE2xfPErx9FBfex738rjb7w57L1F3CpiV6Kc/iAf7/gJ2fuLBuv5JnhvkcpMioSXE8sSYmI5lIXDCjv3aQuL99QnpIWbmTOJpoOZ8E9CjEHKtkbqm0YhzsLqm8NmpvwDWgTpSA0M57o3HCnn9/QbiV6xj85rkwdVbbuOj0eEEppMwmOaqIgMI0Z7kHlqueXD39aermZBxLqsfT8RIM4e376OsvkeXoc6lbPtavSVp7lyMQP3+31Le2H33Fynb8ztO+ttomPscCoMJoJqTNb27KMUvzmLVDPBWlrLz19W42m7/ubv+M97cbsOBAeujS7VijIiIDJKHQx/ZaOz+veKxU17iBFMq6SnhfS9lxH1xlENnbv+ebjxeQRlgWTKvx4oxt+6MWv8yX0vbSxgbwzxxpZLdL/8rGze/RWFV88i9bsBMWL+dRgJ1HPhN73NvANxOXN5u/545j6UzwHvk09uvOQDH8RP+rznGkCU1FfBQaR9sRSaw4+6qOsjOPQ2dyw0PpQgCeL+i6jgQl0yyphDKCAjRs5hqdr5Y3fePV6xje25H5/iYRXlsOv82W4ob2PvaLg7dk0j6/XHQ8BUnq524PNFkr5hLSXFtr5cxpizlsfm1FFQ2UPDqDo6mzeNezvO5rQkXiVjva6DKT+Oi4ewzcMksWBXN4f3NlGzbxef3RBMz3sfdmY93DCkzJrP2+SwuvFHKyU8O8tKxUpIsM/nGNB9/qmmg/oIPMAx5CJqIiESoWYlYL5fxyut2Mu+PweBxUXPcjr3ZgPVJFdZ7si6I4+jWXdQts2KJBnd9NeWVHpiRxiOLbx916rb9ltffb8B713TiL5/kwId+XjB2HiuWJQ9yNQWRIBnDPOE9V0fFFR/gpOR0E3nW4PXgMFqy2LD+Iq/sOchP/nCSJYu7eoV4uPAHO1Xn4njslSdY0jVyYVwiWd9L4/OtNgpefYs/LZ1NvKkzT1yaSca8JipOB+3tYEyZR6apmrKPK6l/MJOkgW6VB3Lczx9l285qHMSSMc5O8Ud2Py84cK8mt+0kZR6w5M4fcBl1kcEI0UJIIExYcp/i5YRSCgqrsZ+ro+xcx7QUc+p8nn4kkwz3p5QU+9l0XCxLnnkcfv0he486sR+vxA4Y75lL/lPfIeH4Dr+FkGHtcwiSVuSz6cYBdhc34DrnxIWBuw3dDl18Gs/9r0QqDpfywZEG6qvt1HfWkcyzLaxe8xDZqSqCiIhIAM5OJ3tLFukHyzh0xIajueM7Je/7K8lOicAmgAOxruQfl1XxwYcnKf3Sg9dkwrpiJXk580nocTHodTd3rEB39SJlhy76f7374lmuQoiEujHME8Z7ksmYUkuFO5rseXEDbzDK4hc/watJlRw6eJzPf2fD5QFMJpIsM8lavxBrj0aCxjlZbH4xngN7P6X8dza8JhOWRQ+y+anZ1P3CTkVQ3kVXcHNZ/WgiZXtsFNsW8vSCAY5dIMfdfb1jlR2cVPzW1udL9turyVtH8cE6iOtdWBYZqqjrre3twQ5iJHmvefABGE23GpOdKWXjVtttI0l6b9g55Wb8eMzmwOpDfvc5SrzXPDDJ5H/JKoA2H+6WzoZtYxCPiIiEl9NnG5g3K7GfZzgp3/EWBafS2Lw9a8Cl7CNe5zmGdf2zYz7FZeBjKTI0yhNjKUQ+yzYn5bveoeD0NPJfeqKPFayCEasHe9HbbCmG7BeeCqiptHKk9CdEe4QMnXGyCfPkIRQAjJ3bBVgEGdY+h8A4uZ8iCMA4Q0csYxSPiIiIiIiEuXGxLHkml+wpDRTsKMXeuzVhUDQe6+ynpOV2ZYTdAVNjREREREQkcnWNVAhgE+94YriBK5A+Jvdl8erzacQM/Myh6xrJPmg+Lo/zMrUtkIl0ieR372HSxZRM3o9yMfzsQ7b9m4HNf5NJUhBrD43H9vHaHhcZT+eTn6Fp/jKyVAgRERGJIFFRUbS3txMVFRXsUGQYdAxlNIVfnogmJSeXTVkBbOK7TjMTiQ7kasgUN/p9e2bMZ9PGQCad3OCKs5UpsYFEZiC+rzYgZgtr/+GHrA3g1UZL/OJ1/PMQl0APr99fCQYVQkRERCLIBKOB661ezKYJwQ5FhuF6q5cJRp3GyegIvzxhIN5i6XfVkbAxeTopqcEOIvwpR8pA7rhmqSIiItK3y65mPF4vCfE9x0RLOHE0XsFkNDI1Riv4yMhTnpBwpxwpA7njmqWKiIhI36bGRNPq9XH5anOwQ5Ehuny1mVavTyf4MmqUJyScKUfKYGhEiIiISITx+m7Q8PVlJhgNxE6exMQJRs2lDnHt7e1cb/XivNZCq9dH4t1TMRrGBzssuYMpT0g4UY6UQKkQIiIiEqEuu5q52uKm1eujXacDIS0qKooJRgN3TTLrLqeMKeUJCQfKkRIoFUJEREREREREJGKoR4iIiIiIiIiIRAwVQkREREREREQkYqgQIiIiIiIiIiIRQ4UQEREREREREYkYKoSIiIiIiIiISMRQIUREREREREREIoYKISIiIiIiIiISMVQIEREREREREZGIoUKIiIiIiIiIiEQMFUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhHD0NBwPtgxiIiIiIiIiIiMiajrre3twQ5CRERERERERGQsaGqMiIiIiIiIiEQMFUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhFDhRARERERERERiRgqhIiIiIiIiIhIxFAhREREREREREQihgohIiIiIiIiIhIxVAgRERERERERkYihQoiIiIiIiIiIRAwVQkREREREREQkYqgQIiIiIiIiIiIRwxDsAERERCQ4LruaudriptXro729PdjhSD+ioqKYYDRw1yQzU2Oigx2ORBDlCQkHypESqKjrrcpoIiIikcTru0HD15eZYDQQO3kSEycYiYqKCnZY0o/29naut3pxXmuh1esj8e6pGA3jgx2W3MGUJyScKEdKoFQIERERiTBnHV9zV7SZqXfprlk4uny1mavNbmYl3B3sUOQOpjwh4Uo5UgZDPUJEREQiyGVXMxOMBl3chLGpd0UzwWjgsqs52KHIHUp5QsKZcqQMhgohIiIiEeRqi5vYyZOCHYYMU+zkSVxtcQc7DLlDKU9IuFOOlIGoECKBu2Jj58atbNxhwxXsWEREJCCtXh8TJxiDHYYM08QJRlq9vmCHIXco5QkJd8qRMpDQWjXmTCkbt9rAlEj+S0+wJH6gDeoo3LiPEiD7hRfImzMGMYqIiISx9vZ2NTy8A0RFRWkFDxk1yhMS7pQjZSChOSLE00DBLz7D0Rak/Xud2Kvt1NideIMUwp2lGUe1nZrqi2iAmoiIiIiIiARTaI0I6e6ro7y5fyZ/n5vMmA/Ma/6KQ9tLqbovi1efTxv7/d9xmijfXkQJaWzenoUl2OGIiMioaqw4wH/8qpb6OR3fozGjsA/XsXd5aU8D3Dd6+xhVbR7q/7OMQx+fpuqcBy8GElLnkp2bxZIkU7CjExl1Y5EnZAjcdg787ENKsbLh77JIMY/My7qqj/JBcSVV1c24MRBzTyLL81ayKjW2z20aP32XV37lIuP7j5O/oO/niQxFiBZCDBhNPhzFRbyZ8CQbFusXX0REJOS1NVHxbhEFR0d/RKXRNLHjLzPjwu8C6ko1BTs/pvycD/NsC5mrYzB4XNQcr6bgtVq+/KtnyU/Tah1yhxrDPCEB8tRR+C+dNy9/nIVlJGpRqh++AAAgAElEQVSy3gZK/n0fhdU+jFMSWbJ6LmY81B+r5cD2d/gidx0vrkj0u2n8g0/w8vh3eeXn7+Bar2tCGVkhWgixkr/eRcHP7VTtKaLM8hSZM4b3il63B98NgPGYJ4/N2x7qPm9uZzRhHqObQsHYZ5/afLhbbnT8PRTiERGRAXkv2Ni7q5TyK9NZ++McWt44SMko7s8cE3blj1tiErk3IZnk/5ZDZvfRH9+2sfPVUsp/fYLl92eSFJoTmEWGbKzzhASgzUn5L4oouZJI/ksjVAQBMMZx7+xpZC/PIe/+boWMlXUUvrGPkqJPqVi8jozJ/jePX5zHJsfbbNnzHoXTniJvji4MZGSEaCEE4hfksGnF22wpbmLvrlKSh1KV7Bx2eqComqor3boGm0xYV+SQv8pCzM2TDCflO96i4FS37U+V8tLG0pv/HFRD1jYP9cdLea+wGnv3pauj48jMy2HtoumY/Z7YeHBUlLH3/Upqum1nTp3P449kkuH+tKOR7Ip1bM9Nvvlze9FWthT3HVvXz63rn/VTRR3aPgera9+32Niy0XbzX71icl+k4nApHxxpwOW59bBxSiKr1+f0O3RORERGSuf34YxctufFUXP4Y/b+vg5HM5hnW1j98EqyU3qPVjBOiSNm2nw2/O1KrDF1FAYh8qA4U8rGrQ3k/zSfdLeNA3s/pfxLD16TCeuyTPJy5pPQ8/xlXCxLnsnt/VrxqSyZX0rVifPUuSBpypi8A5EhiOQ80fd7Jzqa9CWZ5D2cSry/8333RSoOl3GovOP5ximxWB98iMduuyYJDtfxgxRU+rCuz+lnwYqhHHcTljVP9J4ab0rmWw+YKNlfR90F+iyEgAnLX+Sw6g/7OPzLT0l/MQuL+hbICAjZQgiYsDz8OPmOdyiotLHtF/G8/Ndp/pOKP21OKn7xDru/8AEGYu6ZTkpKHL4zdfzpbDNVvyniJyfT2PTfuwosBsxTYkmaBdy4zoVzHScxSTMm3nzJARNU932aTFgWzSMlbjy+pjo+tzVRtqeAmtocNnyvZ3L0YC96my3FzZ2xJpJ+fxw0fMXJ6kp2v2qnro8hY0M3Bvuc3Pl54qPxbMd8wIRZ0Td/6WJM3X79Gm28+UYpJ5sBk4mk1Jl8Y5qPP9U0UH+hoWPo3OpcNq8JQs8YEZFIVF9L4a5qjl5LZumyNNLwYD9STeG2t6h58kk2LOpRnDYls/YHgRfNhyt+UiicylzkyyOllBypJn5RKlkp4Lv0FWXFH/PKHy6yedAn7uMxThrtWEVGUJjkiVHR+d5L7DFkLEojzXSDxupqKooPUuXw8NMf9Oh70lhNwY6DlF8wkLIsjbRo8DXVcfQ3RbxUMYJTUYbCW0fJRw0Qt5C1PY+ZP4Ee9z4YTBMBz4DPw5jMipxkDu+28cGxdDYvixvU64v0JxTOHvo2LpYlz6zB8U9FlFSWsrN4Oi9/ZzAX5z7sH73XUZCYkcqGH+Zg7X5XxX2RsrffY+9tBZZo0r/3LOkAV2zsfLmUqjkP8nwAzZscR4rY/YUP470L2bQhE0u35kJ5rlr2/r8HKDv2MXtTEm9LEK7jhWwrbgZTIo+9kHfbMNnH2pqo+OU+dhfXDjKKwRmLfVpWPMuLK+DWMsdW8n/sp1mqt44DOzqKIAnLc9j03dTbik7u+s/YvfUoVYeKePNuzQ8UERkTpys5+VAur/7AcqsAvTKVwn8qouS9o9QsyCElmJXp+HisADF9Vw5uNlTt18g08i4vvkj+T5+/7U5qZsq7/ORXAZy4t12ivgowTSchjGf+SAQJ9Twxmk5XUnJfJj/9Pwtv3eD880V84/++RUHlp5TXp7EqqevJTire/5jyK4nk/+QJlky79TJrHizl9a02dh+cx8vBWCQC8NZUUtIESY/OH9yUvBE57s3U1zqBRBL6HIFyizktnUxTHWXlp3Ese4CEQYQp0p/Qn31qsrDmqTQSAMf+AxSeGUTV8JKNDw51XOTnP9+jCAJgnk7m93NZNQO8lWWU1Pj8vkxAvLWU7W8CEnns2duLIADEzOWxpxYSj4+qD23Ut93a7tB7DXiJZtXGdbfPFQYYF0fG99bx2Ozhh9g91jHfZz8aj5Vy+AIY52exoUcRBMCc9ADPbUwjAR9V7x+lRp21RETGQCzZf2a5/aTcZGFJdix4qjk5Et+do8w4bR6rVqcN8GfmyDRbXZZBRo+T+fhFGWQC9vLTOAbxEt4/nuRQEySs+iaW0D9DE+FOyBNDZyB71cLbR3mPiyV9iQXw8OX5bvPO620cqPQRv2L5bUUQAOOchWTPg8Yjp29dH4yx+tO1gIkFcwY70mIEjvuFSj75AowL00kfzDRA42ysi4CztdgbBxmmSD/C4mvWOCeLDesTMdJMyY5Cygf45XedOY0dMC57sO85bp1DrMBHWVXd8IOsP0u5B+jvP/Os+WTPApoqqTrfY7v7HmC5pY8BOuPi+Na3R3AYYTD22ScnNX9oAgxkrux76pPR8gCrFwCeaqrsYxCWiEjESyZhWu9HE5I6quRV5y6NcTyBM89ZyNo1WQP8SWUQNyMHlJI0rfedXOM0ku8DzjbgcA/wAo023nyrGu+MNPKXj/R0WJHREv55YuiSsczs/ejNRs5tt4oBrvrzNALWWX4+LGJJ+C+A5yIO12jEORAnjvM+wELSoBenGOZx99RRuOsodlMijz2cyuBW6DUQnxALXMRxZbBxivQttKfGdHOzY3BxAwU7SknoZ75to6NjGGzKAONKzfFxGKnDe8GFC4Z1R8h14WLHEmAnDvI/Thwc4NkeWjw9thtg+T9zcjJJ1FE/jBh7xTqG++wnGhynAKYNMCwumvgZBsCHo8kJaHqMiMjoGo/RX3F6SiwpQE1LkO/0mkyYgdhpofF9YBzv79FY4mcAp67j9kCfZ/ueOgp3lFJFIvnPB7FPgEjAQjxPjKoYYgd3BU/j1x2FgbKd/0pZn89qwnUNGPMmyS6+PgNgYtKg5+UM47h3rU5zIZrsF/L6acza2yTTJMCJ45IT5oRG7pfwFTaFEDBhyckh+w/7KLlgo+A38/h7Pw3Xg262hVWpA5dUkjX3V0REwpHPR0uwYwAwRw9YEnefOUHxH50DPGsmS0doVEhvPrwDXQcO46JAJGSFSp4IFb6ORGBZlEZKP7NPZoR7EXTA4+7Bvv89CirBuv5xLYUrQRVGhRDAlEze81k4Xi2lqriINxOW+m2UE5+QCDRQ43DR38gBd2NTx8iIGTHDnh8cM2M6RhrwJs9n9Zq5g250dHO78024SO4zDnfdUEZmeHBeHut9BiqGhPuAU5dwNNJPFbyZxgsdXyIJcaoAi4iMPg8tXuj1hXatmXpCZbWW/nkvnebwoYGapcL8ESiEOD03/DzajKsRYCJmf+f7bc1U/brjoiD9SV0USDgK/zwxFrquTe5dnMXalGBH01MMd88BTvVxLP0aynH34PikkG3FHpJW5/LcEBY/aPF0lFkSQmQkoIS38MtO8Wk893wjr2+1UbWnjCo/T4mZMw8LDdiPfEr5sif8313x1lF8sA4wkGkdgV4YSbNYYrJRdqSCihVz/e/T00D5x3/ka6azYNV8kozdtjv1GZ/Yraz117OjrYnPf99HHxNDx3SRP9U3Qc8GR9dOU3Gin1iHus8RFUvK/XFwqomyj21kWvz3CfHaP+PQF4ApFetwW/uLiMgg2KlvAOus2x911H8FgPUef3Pdx1Iyedtf6PcZMYufYPvisYmmvvY87uVxt89+8V6i7hQwK5GEXkPoPdj3F7DzEw/W9U/y3CCXmxQJLaGeJ0JDTNJM4mng5JkG8lJCrQdQ1xQ+O/UXwJo04AYM5bg3Hivk9fcbiF+xjs1rhrI6jo9GhxOYTsKYTx+SO1FYNEvtyTgnk/zV0X0/YVoaj6yOBk8DBTsOUtWzoY77ImU/L+pcqSST7JQehYCuT+XUH6kabFdi41yyH+mo9vrdZ1sT5Xv2UXDIRoUvlhnGW9utfryjEezh7fsoq/f02q7il/vY+5X/3SbN7Rh9Ur//t7c3kfVcpGzP7zjZR6zD2edQGEwA1Zys6b3qT/zirM4VfErZ+etqXD06ZrvrP+PN7TYcGLA+uvTOXYZNRCSkeDj0kY3G7jnZY6e8xAmmVNJ7fneOMW/9Z7z5xlu8WdpASCwm9sVRDvVY2a7xeAVlgGXJvB4jWG/dGbX+Zb6WhZcwNoZ54kolu1/+VzZufovCquaBnx9KktJYO99A428+oeS8/xUwXVeC954sqamAh0p70yC3COy4u6oOsnNPA/Erctn88BCXCPZ+RdVxIC6ZZE0hlBEQfiNCADBg+fPHya9/h4JKf5NvO37+9IV32P1FNTtfriXmnjhSUuLwnanjT2ebcQPGe9LY9IyfEQgxc1mysIyqEw0U/ORfKZkVjeHGdayPPc/aOX1HFb9kLRvOF7Dzk459JqQmY50dA011fG5rwuUB470L+auc2xNAzKI8Np3vaAS797VdHLonkfT746DhK05WO3F5osleMZeS4tpe+zSmLOWx+bUUVDZQ8OoOjqbN417Od+yPRKz3NVB1qnesw9ln4JJZsCqaw/ubKdm2i8/viSZmvI+7Mx/vGBZnTGbt81lceKOUk58c5KVjpSRZZvKNaT7+VNNA/QUfYBjyMDoRERmCWYlYL5fxyut2Mu+PweBxUXPcjr3ZgPXJ4Bel6yuOcvIscOGPZGclEuzBgtYFcRzduou6ZVYs0eCur6a80gMz0nhk8e0jNt223/L6+w1475pO/OWTHPjQzwvGzmPFsuRBrqYgEiRjmCe85+qouOIDnJScbiLP2s9N0ZATS8YzudS9sY/CV3dxclEqKXEdHZZ9TQ1UVV3EsWQd23OD856MKfPINFVT9nEl9Q9mkjTQrfJAjvv5o2zbWY2DWDLG2Sn+yN/yjwP3anLbTlLmAUvufAY1aEVkAGFaCAHGxbLkmVwcb+yj5IL/n2c889ckpJVxoKiaqnMXqTh3seNn0XFkrMzkkSwLMX7/o0eT/r3HyZ90kA+ONOE46wQMLBgoKYyLxvroU7xsKaOwqJqqajuO6s6fmUxY/yKH/FX+9mnCkvsULyeUUlBYjf1cHWXnOqalmFPn8/QjmWS4P6WkuK/P4XH49YfsPerEfryyY+nge+aS/9R3SDi+w28hZFj7HIKkFflsunGA3cUNuM45cWHgbkO3X7/4NJ77X4lUHC7lgyMN1Ffbqe/87MyzLaxe8xDZqSqCiIiMmbPTyd6SRfrBMg4dseFo7sjHed9fSXZK8C9AEixzMfMV8SvmhcZJsXUl/7isig8+PEnplx68JhPWFSvJy5lPQo+LQa+7uWMUy9WLlB266P/17otnuQohEurGME8Y70kmY0otFe5osuf103E0VJmSyfufz2It/R2Hyqs5fLzjZq55Rizf+K9LyXtwevBiM85l9aOJlO2xUWxbyNMLBjh2gRx393UcADip+K2tz5fst1dTV0uDuN6FZZGhirre2t4e7CDGgtftwXcDYDzmyQHUf9p8uFsIbJth7tN7zYMPwGi61VztTCkbt9pgxTq25/bR08Tr6Vieb/x4zObA4vW7z1HiveaBSSb/y25B52fe2XRuDOIREYkkp882MG9Wf3PUnZTveIuCU2ls3p4V9JEWIa/z+9m6/tkxn+Iy8LEUGRrliQjU5qR81zsUnJ5G/kt99FgMynH3YC96my3FkP3CUwE1lVaOlP6EZY+QoTCaTZgnmwIvaIwzDKkIMpx9Gid3bhdoAcDYuV2ARZBh7XMIjJP7KYJA52c+dvGIiIiIiES0ztH22VMaKNhRit1/K5Mx13iss5+SltuVERa+U2NERERERERujlQIYBPveGK4gSuQPib3ZfHq82nEBBpeILpGgQ+aj8vjvExtC2QiXSL5rzzBkp6rr5iSyftRLoaffci2fzOw+W8ySQpi7aHx2D5e2+Mi4+l88jM0RV5GlgohIiIiIiISxqJJycllU1YAm/iu08xEogO5GjLFjX7fnhnz2bQxkEknN7jibGVKbCCRGYjvqw2I2cLaf/ghawN4tdESv3gd/zxGS6BL5FEhREREJIJERUXR3t5OVFRUsEORYdAxlNEUfnnCQLzF0u+qI2Fj8nRSUoMdRPgLr99fCYaIaZYqIiIicNbxNdOmxmA2TQh2KDIMbk8rly67mJVwd7BDkTuQ8oSEO+VIGUjENEsVERERuGuSGee1lmCHIcPkvNbCXZO0uK6MDuUJCXfKkTIQFUJEREQiyNSYaFq9Pi5fbQ52KDJEl6820+r1MTWmr0n+IsOjPCHhTDlSBkNTY0RERCKM13eDhq8vM8FoIHbyJCZOMGoudYhrb2/neqsX57UWWr0+Eu+eitEwPthhyR1MeULCiXKkBEqFEBERkQh12dXM1RY3rV4f7TodCGlRUVFMMBq4a5JZdzllTClPSDhQjpRAqRAiIiIiIiIiIhFDPUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhFDhRARERERERERiRgqhIiIiIiIiIhIxFAhREREREREREQihgohIiIiIiIiIhIxVAgRERERERERkYihQoiIiIiIiIiIRAwVQkREREREREQkYqgQIiIiIiIiIiIRw9DQcD7YMYiIiIiIiIiIjAmNCBERERERERGRiBF1vbW9PdhBiIiIiIiIiIiMBY0IEREREREREZGIoUKIiIiIiIiIiEQMFUJEREREREREJGKoECIiIiIiIiIiEUOFEBERERERERGJGCqEiIiIiIiIiEjEUCFERERERERERCKGCiEiIiIiIiIiEjFUCBERERERERGRiKFCiIiIiIiIiIhEDBVCRERERERERCRiqBAiIiIiIiIiIhFDhRARERERERERiRgqhIiIiIiIiIhIxFAhREREREREREQihgohIiIiIiIiIhIxVAgRERERERERkYihQoiIiIiIiIiIRAxDsAMQERGR4LjsauZqi5tWr4/29vZghxMxoqKimGA0cNckM1NjooMdjki/lCckHCivSqCirrcqo4mIiEQSr+8GDV9fZoLRQOzkSUycYCQqKirYYUWM9vZ2rrd6cV5rodXrI/HuqRgN44MdlshtlCcknCivSqBUCBEREYkwZx1fc1e0mal36a5ZsF2+2szVZjezEu4Odigit1GekHClvCqDoR4hIiIiEeSyq5kJRoMubkLE1LuimWA0cNnVHOxQRG5SnpBwprwqg6FCiIiISAS52uImdvKkYIch3cROnsTVFnewwxC5SXlCwp3yqgxEhRAREZEI0ur1MXGCMdhhSDcTJxhp9fqCHYbITcoTEu6UV2Ug4VEI8XhwX2qgproOxxUPbm+wA4o0dRRu3MrGjaXYgx2KiIgMS3t7uxoehpioqCitxiEhRXlCwp3yqgwkdJfPbfNQ/59lHCiqpupK72qeebaF1WseIjs1NgjBiYiIiIiIiEg4Cs1CiKuWwn87SMm5rgKIgZh7ookZD9y4zoVzHtxf2SncbufQgkw2r19IgimYAQfGfd5OnQtikiwkTA52NIDXif1ME15THBZLLBoIKSIiIiIiIneq0CuENNp4841STjYD0dNZu34lmdbpmLtP4vE6sR8r472iWuq/KOOV8042/zgLS5gUQxzHi9hWDNkvvEBeKBRCmr/i0PZSqu7L4tXn01QIERGRYWmsOMB//KqW+jkd3ysxwQ5oDLiqj/JBcSVV1c24MRBzTyLL81aySiNXRfyKxDwBwBUbO19uZPX2LCzBjsUft50DP/uQUqxs+LssUswj87JDyZGNn77LK79ykfH9x8lfoFwqIyu0eoS0NXB4R0cRxHjvQl783/msur9HEQTAGItl2Vpe/MlaMmcAF2xs+2U16gssIiISRG1NVPzyLV7ZXUu9J9jBjBFvAyXb/5WXtn+GzRHDt1ansWr1XJKbGziw/R1eK24IdoQioSUS80Q3brudqmAH0RdPHYX/UsRhn5VN/32EiiDDyJHxDz7By+tjqPj5O+w85hyBYERuCakRIa7jn3DgAmBK5bm/ySRpoBEeMXN57JmF1Lx2AseJUsqyU1k1q/9NvG4fRrP/t+295sEHMH485j6e0+92JhPmURhOMdS4APB48BpNGEe65OX14PYAjMc8eZAxtflwt9wAwDBpCDENd3sRERk13gs29u4qpfzKdNb+OIeWNw5SEuygxoIxjntnTyN7eQ5593e7Y7myjsI39lFS9CkVi9eREQojQEWCLGLzRDd1X9qBtGCH0Vubk/JfFFFyJZH8l0ZwpP0wc2T84jw2Od5my573KJz2FHlzwmQKgIS8ECqENFD+UUdFMP0vM7EO9nc8KZOXt2f6+UEdhRv3UUIam7c9CKWF/MfBBlyezikpczqf1uak5vBBdhd3/KyLcUoiq9fn9D1cq62ZmtKP+eCgvVs120DSwoU88t2lJJx6l5f2NGBd/ywbFsfCmVI2brXd9hIlW7feSv739RgWOIS47EVb2dI55Wb1uKPs/vmJjkazK9axPTe5x7OdlO94i4JT3R46VcpLG0tv/vO2z+lmXE1UvH+A94403RqBEx1H5qNreSwjzv9n5bJT8uvf8eEJJzcX/DHFkpHzEI9kxVH1f9+i4FQi+a88wZIp/t9P5uWD7H6/Gntz108NWJY9xNOPzideBRERkRHU+f0wI5fteXHUHP6Yvb+vw9Hc2aj84ZVkp0T32so4JY6YafPZ8LcrscbUUTjSYV2xUVDYzLceXkRK/GidvgzlvZuwrHmi9xB3UzLfesBEyf466i6gQojcYUI0T4ylNic1pb/jwO/rsPtZ2AHS2Nw5/cV95gQHSm3U1DpxNAPY2LLx9uuCm9cMQeI6fpCCSh/W9Tksie/rWcHIkSYsf5HDqj/s4/AvPyX9xSwsmscvIyB0CiGN5/lTE4CFDGvvxDl0N6gpfpsD+5t7/8hTx4H/p4jD53wQHU36ornMiAZ3Qy2f2zqGa1U+vI5N30m8vW9Gm5PyXe9QUOkDDCSkJmOdHY3zKztVJz5jW+VZspfeuH1f4yaSNKsjufkaO5KgeUYs8V0Fnynjhx9XlzNlbNl/Ake/n4sB85RYkmZxswGt12QiacbEm8+I6VVgaOKTtwuoOAEx9yTzrfujcX1Ry8kLTZTtLqCx7Uk2LOqRwBtt7Hy1lCoPEB1NitWCJboZ+6k6KoqKsNWmkTnAcsiNZUW8csIOU2JJXzabGFctn9uasR/5mFcu3+CnP4igeaUiImOlvpbCXdUcvZbM0mVppOHBfqSawm1vUfOkn3xvSmbtD3oW3UeQKRrjmTK2/eQEMfNTeeTPl5IxayTPF7oJ9L33wWCaCETg2H+JHKGWJ8aMk4pd77C70kR67kNsSorGe6WWQ+9XYvfEser732HpvGl01RMMU6aTvuwh0pc1U7X/Y0rOJpO3cSHdPwnjtFHKZ4PhraPkowaIW8jaweS3sc6RxmRW5CRzeLeND46ls3lZHzdfRQIQOoWQK05qAGYlktDHfDR78Vu895/9vUgqj/94aY+KYzWHDkP64/nkP9jZb6QNwENVUUexIWHxSjZ8r/vIgizyzn/Gm1uOUrX/AIfmPctaS9dH5cP+0XsdRZAZqWz4YQ7WbqMYcNdxeGcRB37XozJsWcqLP17a8T46Rzos/d6zvUdcDDmuW8oO2zAsyOTF7y0kydz1fnuKJv17z5IOnU2bSqma8yDP99usqo6KE9Fkb3qKvJTOCs6arkZGDVS9dwJ7RhaWrni9dRzY0VEESView6bvpt4qrnwX3PYydmw/QckA+e/kCTsJK3LZ/LCls19MFo9dOsHO18qoqiyj5Eyan89RRESG5XQlJx/K5dUfWG4V3VemUvhPRZS8d5SaBTmkjOVdOfNcHvvfG8i22ygpPMruNyp5b3Yqa/OWkjlnhO+ijsh7b6a+1gkkktDn3VWRMBdqeWKsnDlBQaUPy6P5PLe866Lcwr0GJ/9jdx313hjiu00dN8YnkxIP4KSxFCCOe1MtIdMs1VtTSUkTJD06n6TBjLQOQo40p6WTaaqjrPw0jmUPkDCIMEX6E3qTCiZPZFJfP7vmpP5sf3+u+9nIR/yqdTy3rFvT1XHApUoOHfFBXBr5j/eeXmGc+QBP/2Uy0Mzh0m6NWC/Z+OBQM5gSebpnEQTAnMyqv8khc6jT14YaVzfeKWn87TOdRZCu9ztCLI+uu1UE6RS/JIs1swBPNTXnbz3eeKyUwxfAOD+LTY+m9hphYrZksunZ1IFXqZm9lOduFkE6TVtI3l/EAj5OnlEjOhGRkRdL9p9Zbs/RJgtLsmPBU83JGn9DwUfZOAPxcxby2I9+yD//Yw4rJtsp3PoWL/yfIkr+0ITbb+F/KEbgvV+o5JMvwLgwnfSe5woid4wQzBNjwHXpIl7g3qTbRyaY587DClSdbwpKXENVf7oWMLFgzmBHWgQhRxpnY10EnK3F3jjIMEX6ETojQrpcu04L+B2VkLAol02pfn5w/gTbPqgDv8WHWDLTEns96rKfxg7E/9k3+5xnZk5LJ5M6yr6o5U/u+aSbb21nXPYgGX39pzXNZekKE2W/CXw47FDj6i4pc5DV3IBNZ+l8Pwly3HSS5wBnPbTcfMvN2KuaAAOZK/seZWL8Zjqr46o50M/3RcqSVBL8vJ+EpGTASWPLnfklKyISXMkkTOv9aELSbMBG1blLYO39/TpWzDNSWfWDVFZdqaP892V88O9vUxg9nfwf5bPET9yBGeZ799RRuOsodlMi+Q+nMkKrT4qEoNDOEzIYThznfcBckmYMdptg5EgD8QmxwEUcVwCNtJNhCp1CyJRYUoCasw043PidHmOeaY0zPmoAACAASURBVCFlZu/HXVc+6/jLvHg//ydmk+znP3Xj+Y5RBI3732Xj/oGCu96xQor51nYpCf13pZgxywJUD/TCIxZXd99IGq15c30PXTOO7/lIE3WVANP6H+42bhpJVuBI309JTuhjyPP4XjsVEZERM97/6lxd39chWIQ29v4yGqJhvPeulRcuRJP9Ql4/TQdF7gThlydGgnlKLEYa+PJ8E3QbReE9d54awDrAdUJocfH1GQATkwY9jSk4OXKSaRLgxHHJCSM9JVIiTugUQuItpM8qo+asnXKbk/RBd01u4uT/11E8sFiTA26aGT9/PhlJA504xZIwxis1hWpcIiIS4Xw+WoIdA+C+UE1ZYSmHKj1wj4U1G58lMyV2dJdWH/C9e7Dvf4+CSrCuf1zLPErkCpE8MVqMKUt5bH4tBUVFFPAQ2ffH4qut5IP3q/HOSGP1wgi9SFeOlDASOoUQ4kjPTGTvngaq3v8dJ+fnkj6Ipea8VZ9R+BVAMssXDH4kRPzMRKAB8zcXsnZ54NvVOFxA30nuwln7oF9zJOIKPXEkzwcqL+FoBPqaRtR2ifqqMQxLREQGyUOLF3o1crrWTD0QPykIpxBtPho7m6WWfeXDPDuVvBdGoVnqkN67B8cnhWwr/v/bu//opus83+PPQkIMxRYb6Q9sGSLQ6dh6WreIgGtdWxhgBjwUEV3r9QfjegeHYdbDjOt63eude1yuziyXvQwju67roMfOyo+xHHGn7dDWMaxUsV3JmZbplGJYWmkBW9pKCSGhvX+k0NKmP9KGJiWvxzmco02++b6/+STvfL/v7+eHi8SlK3kqiMtgioydEMwTY2FCNAueXMlX/7CH4p17Kd+Jd6XHBYt5fkkaieNqgtgobp4FHBmgLX0KTo487/KWWeKnKb/K6IXUZKlR877NmpmAy8EbW8qo9TUTaC/uk5/yxps1uIH4++8eZP1pH/uyzsEKNJRWUjvQVB7NdZR+UMa+MgftfbZzH/iYitYBtnPVcbBkZMvljTSu0BOJNTUG8GDbbx8wTvcfD1M0vuaTEhEJEw4afMxF3dRwHIDUW0Y9EYd/nHXs+p/beWnLQQ5PSWfd3z3Nz3+87BoUQWAkx978SQGv7m7EsmglG5cnDe9aQmTcC7E8MWY8OPYXUtyZzsbNz7Jt27Nse/VpnlqZ1rNYwaAu4Q7Y5M6jFY0lDsBBw6nhbhOMHOmhuakNiCVeE1BLAIRUIYQJMWQ9uYwFccApO1tfzKegopF2d5/nuVqoLdnDq5sOUu3yrkqybpGfEzFNS2PFfSZoqWL7rz6loW/Rxelg3+uFFBTZaZgc0zPkZlo6q5ZGgquRHb8opLpvMcRZT/EvC7ENVgcxeKukhw876HtoI45rNC5/Co78keoAzsJsmZ/NkjhwV5WxdXcN7X0SvtNhY2t3IUtEREKNi6Lf2mnunbtdDspL28CUQkbyGN/pdXXgnpXJhp+uY9P3s0iNi7yWO/Pr2NurC9n+TvcJ/v0qgkg4GcM80VrFjhd/wfqNb1JQ3RG41x2RM9Qe6ABLNFF+feEvFx2O4mi4NpGNhDUlBXBR5Rju3ckg5Ej3caoPATFJJGnuJQmA0OuvZkkh70cmot74gOIvTlO6411KAXNcNBYT0N5BQ2vPBDzx8xez7pH+y8wOzUTy8tWsObOTXVUHeeXFShJTrKQmmHA21vGZvQMnED9/GWvm9b7bZMD6nYfIa3ib/Koatr9YR3xKEqkzI2k77qC6pgOnKYGc+y5R+uFpn3u2ZqQTX1RJ04d7ee7zaOKiwGPJZMP30okacVyjEDWbBZk2qisbyX/pF5TOiMRw6QKpa55hxaxRvK4xiRXPZNOwqYzqjwp5ocJGcqoVa2QHjiP11J7yYExLJ8dlp/RoYA5FREQCZEYCqWdtvPyqg6zbozC42qk95MDRYSD1sYUkj/XV/tR08p4co335c+wnD7J1ew1NRDN3goOS3/oaGjudhctTtMiBXH/GME+4v6ynotUDtFF6tIXc1GtZDB1KAnMfSKLkbRsvbbBd9Yg5LpY7Fy8md36szwt+65+lE/+hnX2/fIvGeUne6xsuMekbC1lye3COyZg8hyxTDbb9VTTcnTX06pNByJFO+2FsLrCuTCPR/0MU6Sf0CiEAUVZW/PXT3FldSVFxJRXHPThPtdFTODUQlZbCqu8sZO6MUSQMUyxZT68lvmw/+/Y7cNhraLB3PxYZQ1buMlbMi8XcNxlMiGbB02uxFO9jR0kjTTUOmmq8cSVm3sWqBxYSf8RbwPEpMYsNGyD/bTvVrW00tILR0mti1JHGNWKRZDzyEHmTC3nvQAtNJ9oAA3cE4vUt6ax7KYriXxdSVNVB7aEqagFM0cxdeR+rsmOo/if7UK8iIiJj7UQsOZuzySi0UXTATlMHmGdayf3eYnKSg3kBMgb8OXbnBZoAaKPidwP/nqWpECLXozHME8Zbkpg7tY4KZyQ5c4I7j157rY383zRiyUwjdVrvxQ0u0VxTg+2dnTRPeIx1Pm5aGq3ZbNhwA+99cBj7h3bceG/43vmNIF6WGWez9MEEbO/YKbFn8sQdQ7TdWOdIdz0lhfUQk86q+eN5DkUJJREXLnZ1BTuIIbld3mViuxkmm67JrPDucy48ABMnYjYPMxl1enCev+T9b5MJs7+Vb5cL54TBtxtRXCPV6cF5HsxTrsF+erXjtWpDEREZ3NETjcyZMdhw0jbKX3uT/CPpbNyWjXXMIgsFwTv2odtFZOwoTwziTCWbf2rDvSqP57Nj+z/eWU/BT/ZQOiubTc+kB2YY+1jobKP89bfJPzqNvBceHmBZ22C0uwvH3rfYXAI5zz7u10ozyqsymPFxKWo0YZ7S8+9aXUAbL+/Dn2LDBENPbCPp/jeM4smI4hqpCYZrUwSBq9pRRRARERERGW+cDfU4gG9+w0cRBGBCZPc8IONM90o4OVMbyX+tDMfI1n0IuOZPvCvNaLldCbTQHBojIiIiIiIyLJd7KvixiXsiUVyi3Z8bmbdls2lJFEbgi4YWmNV/mIazppLSE2D5buzIeoMcK2P9Fn+GjXs4O8HNTZ3DWq6mWwJ5Lz/Mgr6rr5iSyP3xSgz/+AFbf2lg4w+ySAxi7aH5kz288k47c5/II2+ulsyVwFIhREREJIxERETQ1dVFREREsEORbmoPCTXjL09EkrxsJRuy/djEc4EObiDSn6shUwzmb8Sy/JZqCnbns/m/UshITiJpqoemuka+qD2K/QsX7rh0NmaPcEhGXBob1vsz6OQSrW0XmRrtTyHEgGWgaUDMVlb87Q9Z4cerXSuW+av5+fyRbTu+Pr8SDCqEiIiIhJFJRgMXLroxmyYFOxTpduGim0lGnZJJ6Bh/ecKAxWodowmJo8n5m8dIKvuQovIaCg5Vef9sMpFonU72o5ncOy+JqJEOA58SS3JKwIINW8qrMpTxMVmqiIiIBMTZ9g5cbjfxlr59oiVYmppbMRmN3BR1na/GI+OG8oSMd8qrMhRNWSkiIhJGboqK5KLbw9mvO4IdigBnv+7gotujk3UJKcoTMp4pr8pwqEeIiIhImHF7LtH41VkmGQ1ET5nMDZOMGks9hrq6urhw0U3bufNcdHtIuPkmjIaJwQ5L5CrKEzKeKK+Kv1QIERERCVNn2zv4+ryTi24PXTodGDMRERFMMhq4cbJZdywl5ClPyHigvCr+UiFERERERERERMKG5ggRERERERERkbChQoiIiIiIiIiIhA0VQkREREREREQkbKgQIiIiIiIiIiJhQ4UQEREREREREQkbKoSIiIiIiIiISNhQIUREREREREREwoYKISIiIiIiIiISNlQIEREREREREZGwoUKIiIiIiIiIiIQNFUJEREREREREJGyoECIiIiIiIiIiYUOFEBEREREREREJGyqEiIiIiIiIiEjYUCFERERERERERMKGCiEiIiIiIiIiEjZUCBERERERERGRsKFCiIiIiIiIiIiEDRVCRERERERERCRsGBobTwY7BhERERERERGRMRFx4WJXV7CDEBEREREREREZCxoaIyIiIiIiIiJhQ4UQEREREREREQkbKoSIiIiIiIiISNhQIUREREREREREwoYKISIiIiIiIiISNlQIEREREREREZGwoUKIiIiIiIiIiIQNFUJEREREREREJGyoECIiIiIiIiIiYUOFEBEREREREREJGyqEiIiIiIiIiEjYUCFERERERERERMKGCiEiIiIiIiIiEjZUCBERERERERGRsKFCiIiIiIiIiIiEDRVCRERERERERCRsqBAiIiIiIiIiImFDhRARERERERERCRsqhIiIiIiIiIhI2DAEOwAREREJjrPtHXx93slFt4eurq5ghyODiIiIYJLRwI2TzdwUFRnscCSMKE/IeKAcKf6KuHBRGU1ERCScuD2XaPzqLJOMBqKnTOaGSUYiIiKCHZYMoquriwsX3bSdO89Ft4eEm2/CaJgY7LDkOqY8IeOJcqT4S4UQERGRMHOi6StujDRz0426azYenf26g687nMyIvznYoch1THlCxivlSBkOzREiIiISRs62dzDJaNDFzTh2042RTDIaONveEexQ5DqlPCHjmXKkDIcKISIiImHk6/NOoqdMDnYYMkrRUybz9XlnsMOQ65TyhIx3ypEylPFRCHG5cJ5ppLamnqZWF053sAMKN/UUrN/C+vVlOIIdioSeVjvb129h/Wt22oMdi4gM6aLbww2TjMEOQ0bphklGLro9wQ5DrlPKEzLeKUfKUEJ31ZhOFw3/aWPf3hqqW/t/iM0zrSxdfh85KdFBCE5ERGR86urq0oSH14GIiAit4CHXjPKEjHfKkTKU0CyEtNdR8MtCSr+8XAAxEHVLJFETgUsXOPWlC+dxBwXbHBTdkcXGRzOJNwUzYP84Tzqob4eoRCvxU4IdDeBuw3GsBbcpBqs1GtX/5drqoKnmNO1EkpQSiznY4YiIiIiISFgJvUJIs503flbG4Q4gMpYVjy4mKzUWc+9BPO42HJ/Y2Lm3jobPbbx8so2Nz2VjHSfFkKZDe9laAjnPPktuKBRCOo5TtK2M6tuy2fRMugohco21UL5tL6Wks3FbNtZghyMiAddcsY9/+bc6GmZ5f1eigh1QKOru+Vq0/yjVX7pwYyA+ZTY5K7NZkDhOTmhERkF5IkQ5Hez7xw8oI5V1f51NcoDuWLXXHOS9kiqqazpwYiDqlgTuzV3MkkF69zd//C4v/1s7c7/3EHl3aBSABFZoFUI6Gyl+zVsEMd6aycYfZOHzXMAYjfWeFTyfXseu/7cP2yk7W389nU1PpujusoiISLB0tlDx7l7yD7ah6bwG0VpD/vb9lH/pwTzTStbSKAyudmoP1ZD/Sh1f/NVa8tK1Wodcp5QnQpernoJ/6L5ZFaibzO5GSv95DwU1HoxTE1iwdDZmXDR8Use+bW/z+crVPL8oweemlrsf5sWJ7/Lyv75N+6OPsW6+iiESOCFVCGk/9BH7TgGmFJ4aqAjSW9Rs1jyZSe0rlTRVlmHLSWHJjME3cTs9GM2+D9t9zoUHYOJEzAM8Z9DtTCbM16A7xUjjAsDlwm00YQz0tLhuF04XwETMU4YZU6cH5/lLABgmjyCm0W4/wGthNGH2N9F3enC6DX5t53a68FwCv96z3tuNJM4RCsY+BzTathKRMeE+ZWfX62WUt8ay4rllnP9ZIaXBDipURSVwa3wSSf9tGVm9T3b+ws72TWWU/6aSe2/PInF8TGkvMmzKEyGss43yX+2ltDWBvBcC2NPeGMOtM6eRc+8ycm/vVchYXE/Bz/ZQuvdjKuavZu4AveQt83PZ0PQWm9/ZScG0x8mdpRNBCYwQKoQ0Uv7bRgAy/jKL1OF+xhOzeHFblo8H6ilYv8db0dx6N5QV8C+FjbS7uoekzOp+WmcbtcWF7CjxPnaZcWoCSx9dNnB3rc4Oasv2816hg4Yr2xlIzMxk1QMLiT/yLi+800jqo2u91ctjZazfYr/qJUq3bOlJ/rf16RY4grgce7ewuXvIzdIJB9nxr5XeiWYXrWbbyqQ+z26j/LU3yT/S609HynhhfdmV/73qfboSVwsVu/ex80ALVxakiowh68EVrJkb4/u9andQ+psP+aCyV+XfFM3cZfexKjuG6n96k/wjCeS9/DALpvo+nqyzhezYXYPjynLgBqz33McTD6Zh8edE0XmaiuIy3jvgR3u32tn+YvfQoe8nUXvl+PvH3E+ni4ZDZews6B073vcsdxkr5vUZ9nWFi6YKG7t2V1HbaztzShoPrcpirvNj7+epT9v2fs/6tV2vx698LgOwz+G6vO8edjav7/lO9ItpJG0lIgHQ/fsQt5JtuTHUFu9n1+/raeronqj8/sXkJPfvrWCcGkPUtDTW/WgxqVH1FAQ6rFY7+QUd3Hn/PJItIXT6cqyM9VsayftpHhlOO/t2fUz5Fy7cJhOp92SRuyyt/zxmE6JZ8OTK/q9lSWFBWhnVlSepb4fEwX5fRIIqRPPEWOpso7bsQ/b9vh6Hj4Ud8DUE2HmaimIbReXe98o4NZrUu+9jzRIrUUEufLYfKiS/ykPqo8tYYBnoWSNpdxPW5Q/3HwptSuLOu0yUvl9P/SkGLISACet3l7HkD3so/vXHZDyfjVXj+CUAQudMovkkf2oBsDI3NZDdQS9RW/IW+97v6P+Qq559/3cvxV96IDKSjHmziYsEZ2Mdn9kb2bftbaruX82GbydcPW9GZxvlr79NfpUHMBCfkkTqzEjajjuorvyUrVUnyFl46ep9TbiBxBneCzdPc5s3YcRFY7l8cjR14ujjuuyYjc3vV9I06PtiwDw1msQZXJmA1m0ykRh3w5Vn9E/ILXz0Vj4VlRB1SxJ33h5J++d1HD7Vgm1HPs2dj7FuXp+L02bv3a1qFxAZSXKqFWtkB44j9VTs3Yu9Lp2sIfpFNtv28nKlA6ZGk3HPTKLa6/jM3oHjwH5ePnuJn35/mONKe88/YzKRmDKdb07z8KfaRhpOed/Xz5euZOPypAHmSWmj/C0b+yqHuRRXZxsVv3qbHZ97wGTCOm8OyTET8bTU85m9Bds7+dTWLWPdIyl9ijkuHHvfYnNJB3SPocy4PQYaj3O4poodmxzUD9CFcOTGYJ9Tuj9veGg+4R0fGj8j8koSijL1SkejbisRGbWGOgper+HguSQW3pNOOi4cB2oo2PomtY/5yPemJFZ83/8i6bCZIjEes7H1pUqi0lJY9Z2FzJ0RKsNHTvPFgTJKD9RgmZdCdjJ4zhzHVrKfl/9wmo3DPnGfiHHytY5VJIBCLU+MmTYqXn+bHVUmMlbex4bESNytdRTtrsLhimHJ977NwjnTuKqe0FxD/muFlJ8ykHxPOumR4Gmp5+C/7+WFigAORRkJdz2lv22EmExW9G0zX/xt9wEYTDcAriGfhzGJRcuSKN5h571PMth4zwA3X0X8EDqFkNY2agFmJBA/wEQfjpI32fmfg71ICg89t7BPxbGGomLIeCiPvLu77753Ario3ustNsTPX8y6R3r3LMgm9+SnvLH5INXv76NozlpWWC+/VR4cv93pLYLEpbDuh8tI7X3HxllP8fa97Puwz8WydSHPP7fQexzdd8YXPrLWx137kcbVw1Zsx3BHFs8/kkmi+fLx9hVJxiNryYCeHg+z7uaZQSerqqeiMpKcDY+Tm9ydqZdfnsiokeqdlTjmZmO9HK+7nn2veYsg8fcuY8MDKT3FlQfA6bDx2rZKSofIf4crHcQvWsnG+63dvSeyWXOmku2v2KiuslF6LN1n74erdMdyuMNHLICz4VN2bDlIddFe3rh5gDGIx+wUEUnOf3+gp2ufz/fWq+nAXnZ87sF4ayYb1mVh7fW5zm3vnt/mk/3sSk646gej/VABW0s6wJTAmmdzr+o2vaazhYpf72FHSd0QB+yfsdinddFanl8EPb21Usl7zsdkqYFoKxEZvaNVHL5vJZu+b+0pOC5OoeDv91K68yC1dywjeSwrkebZrPnf68hx2CktOMiOn1Wxc2YKK3IXkjXLdx5o/8TbO3NwgZm4ubzkNHk/feaqO6lZye/y0r/5ceLeeYaGasAUS7xmjpTxINTyxFg5Vkl+lQfrg3k8de/l77aVWw1t/GRHPQ3uKCxXDYNuo2L3fspbE8h76WEWTOt5ZPndZby6xc6Owjm8uDI4N3jctVWUtkDig2nDG5IXkHbvoKGuDUggfsAeKD3M6RlkmeqxlR+l6Z67iB9GmCKDCb3Rp1NuYMCbIefaaDgx2L8LPjbyYFmymqfu6TUEYQJwpoqiAx6ISSfvof7DK4zT7+KJv0wCOiguq+kZBnLGzntF3gvGJ/oWQQDMSSz5wTKyRlrRHWlcvbinpvOjJ7uLIJePN0CsD67uKYJ0syzIZvkMwFVD7cmevzd/UkbxKTCmZbPhwZR+PUzM1iw2rE0ZOuHPXMhTV4og3aZlkvvdaMDD4WNDneReHcu6B3zEkngXT61PJx4P1bsPUuurl4oL0h996OrxjQO9t+46bO+3AAmsWXt1EQTwzm/zeCYWPFR/YKehs2e7op2NuIlkyfrVV48dB5gQw9xHVrNm5pCHPHzB2OcgAtJWIhIA0eT8ufXqHG2ysiAnGlw1HK4dZu+4QJpgwDIrkzU//iE//7tlLJrioGDLmzz7f/ZS+ocWnH2K08Zpc1iyNH2If9MDs1rFPXOZ2+dk3jJvLlmAo/zoEL00vdx/PExRC8Qv+VbPTQWRkBaCeWIMtJ85jRu4NfHqAqd59hxSgeqTLVdv0GBnX5UHy6J7ryqCABhnZZIzB5oPHO05HxxjDUfrABN3zBpuT4sAtPupKj76HIyZGWQMZxigcSap84ATdTiahxmmyCBCp0fIZecucB58npTEz1vJhhQfD5ysZOt79eCz+BBNVnr/Lv3tjqM4AMuff2vA7qrm9AyyqMf2eR1/cqaRYe7ZznjP3cwd6Etrms3CRSZs/z6Mrl4Biqu3xKxhVnP9FsvCNB8JckIsSbOAEy7OXznkDhzVLYCBrMUD9zIxfiuDpTE17GsZ4AlA8oIU4n0cT3xiEtBG8/mhkm0btX/oiWWgOUWM1rtYeoedHZ/XUO1YRnJy32fM5s60YXbDbjhBuQsYLLnPSCNnRiW7TlRRfTKLxMRe2912F/f66O0DwIQY7vyLJHbtqB9eLMONdSz3OaBAtZWIjF4S8dP6/zU+cSZgp/rLM5Aa6GF6w2eOS2HJ91NY0lpP+e9tvPfPb1EQGUvej/OuXGiYZ2WyYqgegwGSnDitf2HfOI2k24AjjTQ5GbDHK+AdEvhmDe64dPLuDd77KuKf0M4ToaK94STNQNYMH28W0cR/Azh6mqZ2sI753EBtNJ30ALNJjBvuNqNsd1c9Ba8fxGFKIO/+4a76acASHw2cpqkVGEYvEpHBhE4hZGo0yUDtiYFPFszTrSRP7//39tZPvf8xx+LjOzGTJB9f6uaT3l4Eze+/y/r3hwrugneFFHPPdslD9FmNm2EFaoZ64YDF1ds3E6/VuLmBu64ZJ/b9Swv1VQDTBu/uNmEaianAgYGfkhQ/wNCHif12OoB2mo4MIxYiscQZAA9NLW1An/3eNp2kYfZXbD/lvVNAZSE/qSwc4tk9BaQr202PGfQOpTkpiUTqaRheOMOLdQz3OUg0gWkrEQmAib5X57r8ez1kEXrsGfv/GI3dvn3uOhpLHHDE9+/1Fa56Cl4ro5oE8p4J4jwBIn4bf3kiEMxTozHSyBcnW6BXLwr3lyepBVL7XCc0f3UGANv2X2Ab8FVbaD8HjHkhpJ2vjgGYmDzscTmjaPfLq9OciiTn2dxBJmbtb7JpMtBG05k2GGBIpMhwhU4hxGIlY4aN2hMOyu1tZAx73H8Lh//DWzywpib53b3VkpbG3MShTpyi+8/4fo2Falzip5lWlqQM/alM0lhwERkvPB7OBzsGwHmqBltBGUVVLrjFyvL1a8lKjr7q5Nx5rJKSP7YN8UrTWbg85RrdXPTgHuo6cBQXBSIhK0TyxLViTF7ImrQ68vfuJZ/7yLk9Gk9dFe/t9vbqWprZ5zrG400E1nnpJA9yvzJuvJ/XD9nuLhzv7yS/ClIffUhL4UpQhU4hhBgyshLY9U4j1bs/5HDaSjIGXEaph7v6UwqOAyRx7x3D7wlhmZ4ANGL+ViYr7vV/u9qmdga7C33qhGPYrxmIuEJPDElpQNUZmpoZuLp9eWK4ayqK+NuAI0PEQgfNp7w/VPExo6syR8XFYqQRd1IaS5fPHvbEV1e2O9lCOwMX9pz1I+mZ4aLt7Fjv019j31YiMhAX593QL4Gd66ABsEwOwilEp4fm7slSbcc9mGemkPvswJOlus8cpbho6Hmk0gJQCGlzXfLx1w7amwFuwOzrfL+zg+rfeC8KMh7TRYGMRyGYJ8ZC9xLYX/3DHop37qV8J96VHhcs5vklaST2eT8s8d7z+1vnZ7Mi5IbzRnHzLODIAG3p00ja3UXTRwVsLXGRuHQlT41gsvvzLm+ZJX6azv1k9EIqO0XN+zZr/uMtdh138MaWMjb8OJvkQQaNuU9+6h1PC8Tff/cg60/72Jd1DlYacZRWUjt/Mcm+zj2a6ygtP8H5yVbuzbYS1Xu7Ax9T8RcP+54nxFXHwRL/5wcZTVyhJxJragxUtWDbbydnlu95Qi5PDHdtRZN8ewwc8caSZfU994Tb8SlFnwOmFFJHu3xA4gwWmOzYDlRQsWi27zt8rkbK9/+Rr4jljss/mpe3O/IpHzlSfa4KRGcLn/1+gLk6DN7hIn9quLqrJgDnjlJROUisI91nQAWhrURkAA4aGiF1xtV/bWo4DkDqLb7Gul9Dzjp2/X0htlaISktn3d9lkho3+LxNUfMfZtv8sQmvoe4kzntjrh794j5D/REGWBHPheP9fLZ/5CL10cd4apjLTYqElhDLE2PGg2N/WBsu0AAACvRJREFUIcWd6WzcPPRwtqjE6Vho5PCxRnKTQ23OlMtD+Bw0nILUxOFs43+7N39SwKu7G7EsWs3G5SNZHcdDc1MbEEv8mA8fkutRaM1JPiGGrCeXsSAOOGVn64v5FFQ00t53VQhXC7Ule3h100GqXd2rSyzyM6lMS2PFfSZoqWL7rz6loe/yK04H+14vpKDITsPkXnMnTEtn1dJIcDWy4xeFVLf23a6e4l8WYhusDmLwXmgePuyg34IXI41rNC5/Co78keoAzsJsmZ/NkjhwV5WxdXcN7X1mwnY6bGztLmRda71j2f4bH7E0fMob2+w0YSD1wYWjX+rNOJucVd7qf/5rPj4nnS2Uv7OH/CI7FZ5o4ow92y19KAEjHRRv24OtwdVvu4pf72HXcd+7TZzt7X3S8P7vKO/dlq7T2N75kMMDxDqafY6EwQRQw+Ha/l+UMW8rERmAi6Lf2mnu/R10OSgvbQNTChnJY3wvxdWBe1YmG366jk3fzxqyCDLmPj9I0bGrc1rzoQpsgHXBnD5LPfbcGU39yzwtAy7j2BjmidYqdrz4C9ZvfJOC6o7Ave6InKH2QAdYookaznlIYjor0gw0//tHlJ70fZHQ3hq8Y7KmpAAuqhzDvTvpX7u3Vxey/Z1GLItWsvH+ES4R7D5O9SEgJokkDSGUAAipHiEAWFLI+5GJqDc+oPiL05TueJdSwBwXjcUEtHfQ0Noz4DZ+/mLWPdJ/mdmhmUhevpo1Z3ayq+ogr7xYSWKKldQEE87GOj6zd+AE4ucvY81Vd2kMWL/zEHkNb5NfVcP2F+uIT0kidWYkbccdVNd04DQlkHPfJUo/PO1zz9aMdOKLKmn6cC/PfR5NXBR4LJls+F46USOOaxSiZrMg00Z1ZSP5L/2C0hmRGC5dIHXNM6Obbd+YxIpnsmnYVEb1R4W8UGEjOdWKNbIDx5F6ak95MKalk+OyU3o0MIcyVCynflbG4Y8KeeGTMhKt0/nmNA9/qm2k4ZQHMIy4q54vlgUrWHcyn+0f9f6cREFLPZ/ZW2h3gfHWTP5q2dU/CFHzctlw8i02lzSy65XXKbolgYzbY6DxOIdr2mh3RZKzaDalJXX9D/PymNWqRvI3vcbB9Dncyknv/kgg9bZGqo/0j3U0+/RfEncsiaT4/Q5Kt77OZ7dEEjXRw81ZD3nf+yC0lYj4MCOB1LM2Xn7VQdbtURhc7dQecuDoMJD6WBCKkFPTyXtyjPfph9Q7Yji45XXq70nFGgnOhhrKq1wQl86q+Vf30HPaf8eruxtx3xiL5exh9n3g4wWj57DonqRhrqYgEiRjmCfcX9ZT0eoB2ig92kJuajCLoQnMfSCJkrdtvLTh6ulPzXGx3Ll4MbnzY3ud30Uz98mV1P9sDwWbXufwvBSSY7xzAXpaGqmuPk3TgtVsWxmcYzImzyHLVINtfxUNd2cNvfqkP+1+8iBbt9fQRDRzJzgo+a2v6QOGnqvJaT+MzQXWlWkMq9OKyBBCrxACEGVlxV8/zZ3VlRQVV1Jx3IPzVFuv+QkMRKWlsOo7C5k7YxQJwxRL1tNriS/bz779Dhz2Ghrs3Y9FxpCVu4wV82Ix900GE6JZ8PRaLMX72FHSSFONg6Yab1yJmXex6oGFxB/xFnB8SsxiwwbIf9tOdWsbDa1gtPSaGHWkcY1YJBmPPETe5ELeO9BC04k2wMAdgXh9SzrrXoqi+NeFFFV1UHuoiloAUzRzV97HquwYqv/JPtSrBIYlnaf+VwIVxWW8d6CRhhoHDd0L+5hnWlm6/D5yUgJ4YT0hktQHH+dFq42CvTVUX/mcACYTqd9dRt4SK1H93mcT1pWP82J8GfkFNTi+rMf2pXdYijkljSdWZTHX+TGlJb72Gc2CJx+C33zAroNtOA5VeZd7vmU2eY9/m/hDr/kshIxqnyOQuCiPDZe835/2L9tox8DNhl7paKzbSkT6OxFLzuZsMgptFB2w09Th/f7lfm8xOckh1hsjFKQu5u/uqea9Dw5T9oULt8lE6qLF5C5LI77PxaDb2eHtDfn1aWxFvm+acJuFe1UIkVA3hnnCeEsSc6fWUeGMJGdOcOfRa6+1kf+bRiyZaaRO6724wSWaa2qwvbOT5gmPsa73TUtTErn/Yy2pZR9SVF5D8SHvjV1zXDTf/LOF5N4dO7YH0ZtxNksfTMD2jp0SeyZP3DFE2/nT7s4LNAHQRsXvBj7nH3SuJnc9JYX1ENO/sCwyUhEXLnZ1BTuIIbld3mXnuhkmm3wv2TTa3Zxz4QGYOBGzeZg1ok4PzvPdE6SZTJj9rXy7XDgnDL7diOIaqU4PzvNgnnIN9tOrHa9VGw5b73YzmnxPYhdgbqcLzyWAiX69v1fav3ecx8pYv8UOi1azbWXSABt2v98j+Nz43Oc14j7ngsE+D0FoK5Hr2dETjcyZMdhw0jbKX3uT/CPpbNyWjabhGUJ3Pk59dO2YD3EZui1FRkZ5YhBnKtn8UxvuVXk8n+2jeNFZT8FP9lA6K5tNz/ieIy8kdbZR/vrb5B+dRt4LDw+wglUw2t2FY+9bbC6BnGcf92tSaeVIGUxo9gjpyziCAsNIdjPF5P+YtQmG0RUNTKYh7/aMKK6RmmDA7Meks34Zo3YcltG22wgYzSNrxxG3/yje77H8zBmnDPGDFoS2EhEREfHF2VCPA8j5xgA9OCZEeicfHW+6V8Jp+tke8l8rI/65oSeBHQvNn3TPp/ToY1pZSwJKVxciIiIiIjKOXe6p4Mcm7olEcYl2f+783JbNpiVRGIEvfK3QBzhrKik9AZbvxo6sN8jlXr/D5uHsBDc3dfozkC6BvJcfZkHf1VdMSeT+eCWGf/yArb80sPEHWSQGsfbQ/MkeXnmnnblP5JE3V0OiJbBUCBERERERkXEskuRlK9mQ7ccmngt0cAOR/lwNmWIwfyOW5bdUU7A7n83/lUJGchJJUz001TXyRe1R7F+4cMelszF7hEMy4tLYsN6fQSeXaG27yNRofwohBiwDTQNitrLib3/ICj9e7VqxzF/Nz8doCXQJPyqEiIiIhJGIiAi6urqIiIgIdigyCmpDuZbGX54wYLFaB111JHCiyfmbx0jqnvS04FCV988mE4nW6WQ/msm985J8TIY/TFNiSU4JWLBha3x9fiUYxsdkqSIiIhIQJ5q+YtpNUZhNk4IdioyC03WRM2fbmRF/c7BDkeuQ8oSMd8qRMpRgrtshIiIiY+zGyWbazp0PdhgySm3nznPjZC2uK9eG8oSMd8qRMhQVQkRERMLITVGRXHR7OPt1R7BDkRE6+3UHF90ebooaaJC/yOgoT8h4phwpw6GhMSIiImHG7blE41dnmWQ0ED1lMjdMMmosdYjr6uriwkU3befOc9HtIeHmmzAaJgY7LLmOKU/IeKIcKf5SIURERCRMnW3v4OvzTi66PXTpdCCkRUREMMlo4MbJZt3llDGlPCHjgXKk+EuFEBEREREREREJG5ojRERERERERETChgohIiIiIiIiIhI2VAgRERERERERkbChQoiIiIiIiIiIhA0VQkREREREREQkbKgQIiIiIiIiIiJhQ4UQEREREREREQkbKoSIiIiIiIiISNhQIUREREREREREwoYKISIiIiIiIiISNlQIEREREREREZGwoUKIiIiIiIiIiIQNFUJEREREREREJGyoECIiIiIiIiIiYaGrq0uFEBEREREREREJD+cvuFQIEREREREREZHrX1dXFyfPnOX/A4rg1fZSCjN5AAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "c190751a",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e09ceb1e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}