{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "f32d156f",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ลักษณะของข้อมูลประเภท Array</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">Package Numpy เป็น package เสริมที่สร้างขึ้นมาเพื่อเสริมการทำงานให้กับโปรแกรมภาษา Python โดยสร้างชุดข้อมูลใหม่ขึ้นมาที่มีชื่อว่า numpy array หรือเราเรียกสั้น ๆ ว่า array โดยที่ array จะเป็นข้อมูลที่เป็น Block ที่มีขนาดเท่ากันเรียงต่อกันเพื่อให้เกิดประสิทธิภาพในการเข้าถึงข้อมูลมากที่สุด (จึงเป็นเหตุผลที่ว่าทำไมสมาชิกใน array จึงต้องเป็นข้อมูลชนิดเดียวกัน) และเป็นข้อมูลประเภท immutable คือไม่สามารถเพิ่มหรือลดสมาชิกได้ แต่สามารถจัดเรียงสมาชิกใหม่ได้</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ข้อมูล array จะมีส่วนที่เป็น header อยู่ที่รวบรวม attributes ของ array ไว้เพื่อให้ง่ายต่อการเข้าถึงดังที่แสดงในรูปด้านล่าง</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img width=500px src=\"https://indico.narit.or.th/event/229/images/1292-numpyarray.png\">\n",
    "    <figcaption>โครงสร้างของข้อมูลประเภท Numpy Array</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">การใช้งานหลักของ numpy array คือการสร้างวัตถุที่สามารถใช้แทนปริมาณ vector หรือ matrix ที่มักจะพบเจอบ่อย ๆ ในการใช้งานทางวิทยาศาสตร์ ในหัวข้อถัดไปจะเป็นตัวอย่างการใช้งาน numpy array</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a7c84cc",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ตัวอย่างการใช้งานข้อมูลประเภท Array</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในหัวข้อนี้เราจะทำการเปรียบเทียบข้อมูลประเภทลิสท์ (List) กับข้อมูลประเภท array ว่ามีความแตกต่างกันอย่างไร ดังตัวอย่าง</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ก่อนอื่นเราจะโหลด package numpy และตั้งชื่อใหม่ว่า np เพื่อเข้าถึงข้อมูลประเภท array</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3ce055b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a68874a7",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ส่วนข้อมูลประเภทลิสท์เป็นข้อมูลพื้นฐานที่มีอยู่แล้วในโปรแกรมภาษา Python</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e6d0be4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L = [[1, 2, 3], [4, 5, 6]]\n",
    "type(L)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ad78c27",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">หากเราพยายามที่จะคูณ <font face='Monaco' style=\"font-size:15px\">L</font> ด้วย <font face='Monaco' style=\"font-size:15px\">2</font> ผลลัพธ์ที่ได้จะไม่เหมือนกับการที่เรามอง <font face='Monaco' style=\"font-size:15px\">L</font> เป็นเมทริกซ์</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c1703f6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[1, 2, 3], [4, 5, 6], [1, 2, 3], [4, 5, 6]]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "L * 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f76a490",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">หากเราต้องการสร้างปริมาณเมทริกซ์ที่ให้มีสมาชิกเหมือนกับ <font face='Monaco' style=\"font-size:15px\">L</font> เราจำเป็นต้องใช้ฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">array</font> ใน numpy</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a2ee7107",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array(L)\n",
    "type(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53bcdf44",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ทีนี้หากเรานำสองมาคูณ <font face='Monaco' style=\"font-size:15px\">a</font> เราจะได้ผลลัพธ์เหมือนกับที่เราคาดหวังจากการคูณเมทริกซ์ทุกประการ</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "48c6cb82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2,  4,  6],\n",
       "       [ 8, 10, 12]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a * 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6ffe5d4",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">การเข้าถึงสมาชิกใน array สามารถทำได้เหมือนกับข้อมูลที่มีลำดับทุกประการ รวมถึงการสไลซ์ ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "296d9b9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "43513952",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "72936ce4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0, 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19be1d4a",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">การเข้าถึงข้อมูลระดับที่ลึก เช่น ดังเช่น <font face='Monaco' style=\"font-size:15px\">a[<font color=\"green\">0</font>, <font color=\"green\">0</font>]</font> ใช้ได้เฉพาะกับข้อมูล array เท่านั้น</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">การสร้าง array สามารถสร้างได้หลายวิธี อีกวิธีหนึ่งคือ การสร้างจากฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">arange</font> ซึ่งมีวิธีการใช้งานดังนี้</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9abf7969",
   "metadata": {},
   "source": [
    "<div><span face=\"Monaco\" style=\"font-family: Monaco; font-size:15px; padding-left: 20px;\">\n",
    "            arange(<i>m</i>, <i>n</i>, <i>d</i>)</span></div>\n",
    "            \n",
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยที่ <font face='Monaco' style=\"font-size:15px\"><i>m</i></font> <font face='Monaco' style=\"font-size:15px\"><i>n</i></font> และ <font face='Monaco' style=\"font-size:15px\"><i>d</i></font> แทนจำนวนเต็มซึ่งจะเป็นการสร้าง array ของจำนวนเต็มตั้ง <font face='Monaco' style=\"font-size:15px\"><i>m</i></font> ถึง <font face='Monaco' style=\"font-size:15px\"><i>n - 1</i></font> โดยเพิ่มทีละ <font face='Monaco' style=\"font-size:15px\"><i>d</i></font></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในบางกรณีเราสามารถล่ะ <font face='Monaco' style=\"font-size:15px\"><i>m</i></font> และ <font face='Monaco' style=\"font-size:15px\"><i>d</i></font> ได้โดยสื่อความหมายให้ <font face='Monaco' style=\"font-size:15px\"><i>m = 0</i></font> และ <font face='Monaco' style=\"font-size:15px\"><i>d = 1</i></font> (การใช้งานเหมือนกับคำสั่ง <font face='Monaco' style=\"font-size:15px\">range</font> ทุกประการแต่คืนค่าเป็น array) ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "57ec2a58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.arange(4)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0be84ba6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[0:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "050e72b1",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการสร้าง array และ กระบวนวิธีที่เกี่ยวข้องกับ array เราจะศึกษาในหัวข้อถัดไป</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9cad6722",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ลักษณะของ Object-oriented Programming</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">การเขียนโปรแกรมประเภท Objected-oriented Programming หรือ OOP ที่เรียกในชื่อภาษาไทยว่า การเขียนโปรแกรมเชิงวัตถุเป็นการมองข้อมูลที่ประกอบไปด้วย ลักษณะประจำ (attribute) และ กระบวนวิธี (method) ติดกับตัวข้อมูล โดยที่ attribute จะเป็นข้อมูลที่บอกคุณสมบัติของวัตถุนั้น ๆ ส่วน กระบวนวิธีเป็นฟังก์ชันที่วัตถุใช้เรียกตัวเอง ดังตัวอย่าง</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">สมมติว่าเรานิยามตัวแปร <font face='Monaco' style=\"font-size:15px\">a</font> โดยให้มีค่าเท่ากับ <font face='Monaco' style=\"font-size:15px\">1</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b40532d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = 1\n",
    "type(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57bedcae",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\"><font face='Monaco' style=\"font-size:15px\">a</font> เป็นวัตถุชนิด <font face='Monaco' style=\"font-size:15px\">int</font> ซึ่งเราสามารถเรียกลักษณะประจำ และ กระบวนวิธีของ <font face='Monaco' style=\"font-size:15px\">int</font> ได้ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "af8aedaf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.bit_length()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9d8acb1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "1f75e629",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.imag"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fe34827",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">จากตัวอย่างข้างต้นกระบวนวิธี <font face='Monaco' style=\"font-size:15px\">bit_length</font> คืนจำนวนบิตที่ใช้บรรจุข้อมูลของ <font face='Monaco' style=\"font-size:15px\">a</font> ส่วนลักษณะประจำ <font face='Monaco' style=\"font-size:15px\">real</font> และ <font face='Monaco' style=\"font-size:15px\">imag</font> ที่บันทึกค่าส่วนจริง และส่วนจินตภาพของ <font face='Monaco' style=\"font-size:15px\">a</font></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในโปรแกรมภาษา Python กระบวนวิธีเป็นฟังก์ชันดังนั้นจำเป็นต้องมีวงเล็บเสมอ ส่วนลักษณะประจำเปรียบเสมือนตัวแปรที่เรียกค่าได้โดยที่ไม่ต้องมีวงเล็บ สำหรับลักษณะประจำ และกระบวนวิธีของข้อมูลประเภทอื่น ๆ เราสามารถศึกษาได้จากแหล่งข้อมูลอ้างอิง</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "400a6519",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ตัวอย่างการใช้งานกระบวนวิธีพื้นฐานใน numpy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในหัวข้อนี้จะยกตัวอย่างกระบวนวิธีที่สำคัญของ numpy array ที่มีโอกาสได้ใช้บ่อยในการคำนวณทางวิทยาศาสตร์</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">กระบวนวิธี <font face='Monaco' style=\"font-size:15px\">reshape</font> เป็นกระบวนวิธีที่คืน array ที่จัดมิติการเรียงตัวของสมาชิกใหม่โดยยังคงมิติของ array เดิม</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5e847bce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2, 3, 4],\n",
       "       [5, 6, 7, 8, 9]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(10)\n",
    "a.reshape([2,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "267ec52e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10,)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54d571bb",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">attribute <font face='Monaco' style=\"font-size:15px\">shape</font> ของ array จะคืนค่ามิติของ array นั้น จะเห็นได้ว่ามิติของ array ยังคงเหมือนเดิม</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">หากเราต้องการเปลี่ยนมิติของ array อย่างถาวรเราต้องใช้กระบวนวิธี <font face='Monaco' style=\"font-size:15px\">resize</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c5afc0ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 5)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(10)\n",
    "a.resize((2,5))\n",
    "a.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "366549b1",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างกระบวนวิธีอื่น ๆ ที่น่าสนใจได้แก่</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "40716b5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 2, 3, 4],\n",
       "       [5, 6, 7, 8, 9]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6355005c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.argmin()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7d6808e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.argmax()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "637c1300",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.5"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d785b37d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 5],\n",
       "       [1, 6],\n",
       "       [2, 7],\n",
       "       [3, 8],\n",
       "       [4, 9]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be05e59a",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">argmin</font> และ <font face='Monaco' style=\"font-size:15px\">argmax</font> เป็นการหาสมาชิกที่น้อยที่สุด และมากที่สุดตามลำดับ กระบวนวิธี <font face='Monaco' style=\"font-size:15px\">mean</font> หาค่าเฉลี่ยของสมาชิกทั้งหมด และ <font face='Monaco' style=\"font-size:15px\">T</font> เป็นการหา tranpose ของ array</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da182285",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ตัวอย่างการคำนวณพีชคณิตเชิงเส้นด้วย Numpy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ให้หัวข้อนี้เราจะศึกษาการแก้ปัญหาพีชคณิตเชิงเส้นโดยใช้ Numpy</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">หากเราต้องการแก้สมการเชิงเส้น เราสามารถทำได้โดยการแปลงระบบสมการเชิงเส้นให้เป็นสมการเมทริกซ์</p>\n",
    "\\[\n",
    "    \\mathbf{A} \\cdot \\mathbf{x} = \\mathbf{b}\n",
    "\\]\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยที่ <font face=\"Times\" style=\"font-size:20px\"><b>A</b></font> แทน เมทริกซ์สัมประสิทธิ์ <font face=\"Times\" style=\"font-size:20px\"><b>x</b></font> แทน เมทริกซ์ของตัวแปร ส่วน <font face=\"Times\" style=\"font-size:20px\"><b>b</b></font> แทน เมทริกซ์ของค่าตัวเลข การแก้สมการสามารถทำได้โดย การหาเมทริกซ์ผกผันของ <font face=\"Times\" style=\"font-size:20px\"><b>A</b></font> แทน แล้วนำไปคูณทั้งสองฝั่งจะได้คำตอบของระบบสมการ</p>\n",
    "\\[\n",
    "      \\mathbf{x} = \\mathbf{A}^{-1} \\cdot \\mathbf{b}\n",
    "\\]\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ยกตัวอย่างเช่น เราต้องการแก้ระบบสมการนี้</p>\n",
    "\n",
    "\\begin{eqnarray}\n",
    "    2x - y + 2z &=& \\,\\,\\,\\,\\,\\,\\,6 \\\\\n",
    "    x - y + 3z &=& \\,\\,\\,\\,\\,\\,\\,8 \\\\\n",
    "    4x -y - 2z &=& -4 \\\\\n",
    "\\end{eqnarray}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราเริ่มต้นตัวการสร้างเมทริกซ์</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\mathbf{A} = \\left(\\begin{array}{ccr}\n",
    "            2 & -1 & 2\\\\\n",
    "            1 & -1 & 3\\\\\n",
    "            4 & -1 & -2 \n",
    "        \\end{array}\n",
    "        \\right)\n",
    "\\end{equation}\n",
    "\n",
    "และ\n",
    "\n",
    "\\begin{equation}\n",
    "    \\mathbf{b} = \\left(\\begin{array}{r}\n",
    "            6 \\\\\n",
    "            8 \\\\\n",
    "            -4  \n",
    "        \\end{array}\n",
    "        \\right)\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยการสร้างเมทริกซ์โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">array</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ae5d2691",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "A = np.array([[2, -1, 2], [1,-1, 3],[4,-1,-2]])\n",
    "b = np.array([6, 8,-4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b44258e8",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่งที่เราจะใช้ในการหาเมทริกซ์ผกผันจะอยู่ใน sub-module <font face='Monaco' style=\"font-size:15px\">linalg</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "039f1e8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3.])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ainv = np.linalg.inv(A)\n",
    "np.dot(Ainv,b)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c88d4aa",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะเห็นได้ว่าคำตอบของระบบสมการนี้คือ</p>\n",
    "\n",
    "\\begin{eqnarray}\n",
    "    x &=& 1\\\\\n",
    "    y &=& 2\\\\\n",
    "    z &=& 3\\\\\n",
    "\\end{eqnarray}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถตรวจสอบคำตอบได้โดยการคูณคำตอบที่ได้กับ <font face=\"Times\" style=\"font-size:20px\"><b>A</b></font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c7d07c7a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 6,  8, -4])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([1, 2, 3])\n",
    "A.dot(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "474e51d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.dot(x) == b"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dab90909",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">อีกคำสั่งหนึ่งที่เราสามารถใช้หาเมทริกซ์ผกผันได้ คือ <font face='Monaco' style=\"font-size:15px\">tensorinv</font> ใน sub-package <font face='Monaco' style=\"font-size:15px\">linalg</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b501b6bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3.])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Ainv = np.linalg.tensorinv(A, ind=1)\n",
    "np.dot(Ainv,b)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acafe98f",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ตัวอย่างการคำนวณโดยใช้ Numpy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในตัวอย่างนี้จะเป็นการประยุกต์ใช้คำสั่งใน Numpy ในการหาค่า eigen vectors และค่า eigen values ของเมทริกซ์</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ค่า eigen values และ eigen vectors ของเมทริกซ์ <font face=\"Times\" style=\"font-size:20px\"><b>A</b></font> สอดคล้องกับสมการ</p>\n",
    "\n",
    "\\begin{eqnarray}\n",
    "    \\mathbf{A}\\cdot\\mathbf{v} = \\lambda\\mathbf{v}. \n",
    "\\end{eqnarray}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยที่ <font face=\"Times\" style=\"font-size:20px\"><b>v</b></font> แทน eigen vector และ &lambda; แทน eigen value</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในตัวอย่างเราจะสมมติให้เราต้องการหาค่า eigen values และ eigen vectors ของเมทริกซ์</p>\n",
    "\n",
    "\\begin{eqnarray}\n",
    "   \\left(\\begin{array}{ccc}\n",
    "   1 & 2 & 3 \\\\\n",
    "   4 & 5 & 2 \\\\\n",
    "   7 & 6 & 5\n",
    "   \\end{array}\\right)\n",
    "\\end{eqnarray}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราเริ่มต้นปัญหาโดยการสร้างเมทริกซ์โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">array</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e5b56eeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "A = np.array([[1, 2, 3], [4, 5, 2], [7, 6, 5]])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e1fa79a",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่งที่ใช้ในการหาค่า eigen value คือคำสั่ง <font face='Monaco' style=\"font-size:15px\">eigvals</font> อยู่ใน sub-module linalg</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4ea6f3a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11.28041742, -1.83030721,  1.54988979])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linalg.eigvals(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80105765",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">eigvals</font> จะคืนค่า eigenvalue ออกมาซึ่งในที่นี่มีทั้งหมดสามค่า คือ 11.28, -1.83 และ 1.55</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">eigvals</font> จะคืนค่าเฉพาะค่า eigen value เท่านั้น หากเราต้องการค่า eigen vector ด้วยเราควรใช้คำสั่ <font face='Monaco' style=\"font-size:15px\">eig</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "ea50f56e",
   "metadata": {},
   "outputs": [],
   "source": [
    "values, vecs = np.linalg.eig(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f497d1c2",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Courier' style=\"font-size:15px\">eig</font> จะคืนค่ามาสองค่า คือ eigen values และ eigen vectors</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "dfc09fc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11.28041742, -1.83030721,  1.54988979])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "85f3e381",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.33031999,  0.78568336,  0.3607414 ],\n",
       "       [ 0.47088026, -0.3020298 , -0.7441554 ],\n",
       "       [ 0.8180223 , -0.53988856,  0.56222627]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vecs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaa032c3",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะตรวจสอบ eigen values และ eigen vectors ได้ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "446f338c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.72614741, 5.31172587, 9.22763301])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vecsT = vecs.transpose()\n",
    "A.dot(vecsT[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a11b45b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3.72614741, 5.31172587, 9.22763301])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values[0] * vecsT[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b166025",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะพบว่าค่าทั้งสองฝั่งของค่า eigenvalue ตัวแรกของสมการมีค่าใกล้เคียงกัน เมื่อเราตรวจสอบกับค่า eigen value ค่าอื่น ๆ จะพบว่าค่าที่ได้ใกล้เคียงกันเช่นกัน</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7c9b0662",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.43804192,  0.55280732,  0.98816192])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.dot(vecsT[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e57f3c21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-1.43804192,  0.55280732,  0.98816192])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values[1] * vecsT[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "61156c9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.55910941, -1.15335886,  0.87138876])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.dot(vecsT[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "acadadb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.55910941, -1.15335886,  0.87138876])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values[2] * vecsT[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "885efb70",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">โมดูลใน scipy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">Scipy เป็น Package ที่สร้างต่อยอดจาก Numpy เพื่อนำไปประยุกต์ใช้งานกับงานต่างที่แตกต่างกันในทางวิทยาศาสตร์โดยการแบ่งเป็น sub-Package ย่อย ๆ ดังนี้</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1293-scipy.png\">\n",
    "    <figcaption>Sub-Package ใน Scipy</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในหัวข้อถัดไปจะแนะนำวิธีการใช้งาน sub-Package ที่สำคัญและใช้งานบ่อยในทางวิทยาศาสตร์</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "33e73b08",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การใช้งาน Scipy พื้นฐาน</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เนื่องจาก Scipy เป็น package ที่ต่อยอดมาจาก Numpy ดังนั้นหากเราต้องการใช้คำสั่งที่อยู่ใน Numpy เราสามารถใช้ผ่าน Scipy ได้ทันที เช่นการสร้าง numpy array</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "63474f08",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da06f7d8",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ต่อไปเราจะสามารถศึกษาการใช้งาน sub-package ใน scipy กัน เช่น</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "579b9072",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.constants as consts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f0a95508",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.02214076e+23"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "consts.Avogadro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "323aef37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.618033988749895"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "consts.golden_ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "226d671b",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">sub-package ของ scipy เป็นการรวบรวมค่าคงที่ที่สำคัญในสาขาวิทยาศาสตร์ และคณิตศาสตร์เข้าด้วยกัน</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7c6429e",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การทำ interpolation โดย scipy</h1>\n",
    "\n",
    "<p　style=\"font-size: 16px; line-height:2.0;\">ในหัวข้อนี้เราจะศึกษาการทำการประมาณในช่วง (interpolation) โดยใช้ scipy ซึ่งเราจะใช้งานคำสั่ง <font face='Monaco' style=\"font-size:15px\">interp1d</font> ผ่าน sub-package interpolate</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "8fcbe659",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.interpolate import interp1d\n",
    "import scipy\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "809ac0e9",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">เราจะทำการสร้างฟังก์ชันที่เราจะใช้เป็นต้นแบบ</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "04d35e84",
   "metadata": {},
   "outputs": [],
   "source": [
    "def func(x):\n",
    "    return np.sin(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66763d4c",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">เราจะสร้าง sampling ของข้อมูลจริง กับ sampling ของข้อมูลดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "c1dcaee6",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * scipy.pi,100)\n",
    "xn = np.linspace(0, 2 * scipy.pi, 5)\n",
    "\n",
    "y = func(x)\n",
    "yn = func(xn)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ae94db8",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">โดยที่คู่อันดับ <font face='Monaco' style=\"font-size:15px\">(xn, yn)</font> แทนข้อมูลที่เราได้ เทียบกับฟังก์ชันต้นแบบ <font face='Monaco' style=\"font-size:15px\">(x, y)</font> เมื่อเราพลอตข้อมูลจะได้ดังนี้</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1294-fig6-1.png\">\n",
    "    <figcaption>พลอตข้อมูลที่เราได้เทียบกับฟังก์ชันจริง</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "<p　style=\"font-size: 16px; line-height:2.0;\">ในขั้นตอนต่อไปเราจะใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">interp1d</font> เพื่อสร้าง interpolating function ขึ้นมาโดยใส่ข้อมูลเข้าไป คำสั่ง <font face='Monaco' style=\"font-size:15px\">interp1d</font> เราสามารถกำหนดประเภทของการ interpolate ได้ หากเราไม่ระบุจะเป็นแบบ linear ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d9ad7121",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 2 * scipy.pi,100)\n",
    "xn = np.linspace(0, 2 * scipy.pi, 5)\n",
    "\n",
    "y = func(x)\n",
    "yn = func(xn)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e325607",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">โดยที่คู่อันดับ <font face='Monaco' style=\"font-size:15px\">(xn, yn)</font> แทนข้อมูลที่เราได้ เทียบกับฟังก์ชันต้นแบบ <font face='Monaco' style=\"font-size:15px\">(x, y)</font> เมื่อเราพลอตข้อมูลจะได้ดังนี้</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1294-fig6-1.png\">\n",
    "    <figcaption>พลอตข้อมูลที่เราได้เทียบกับฟังก์ชันจริง</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "<p　style=\"font-size: 16px; line-height:2.0;\">ในขั้นตอนต่อไปเราจะใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">interp1d</font> เพื่อสร้าง interpolating function ขึ้นมาโดยใส่ข้อมูลเข้าไป คำสั่ง <font face='Monaco' style=\"font-size:15px\">interp1d</font> เราสามารถกำหนดประเภทของการ interpolate ได้ หากเราไม่ระบุจะเป็นแบบ linear ดังตัวอย่าง</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "2af9bcc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "infunc1 = interp1d(xn,yn)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a11aff12",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">จากคำสั่งด้านบนเราได้ interpolating function <font face='Monaco' style=\"font-size:15px\">infunc1</font> ที่เราสามารถใส่ sampling points ใด ๆ แล้วคือการประมาณในช่วงได้ ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e4828d6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "y1 = infunc1(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0279c60",
   "metadata": {},
   "source": [
    "<p　style=\"font-size: 16px; line-height:2.0;\">หากเราเปรียบเทียบการทำ interpolation แบบ linear เมื่อเทียบกับข้อมูล</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1294-fig6-1.png\">\n",
    "    <figcaption>การทำ interpolation แบบ linear</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "<p　style=\"font-size: 16px; line-height:2.0;\">วิธีการ interpolate แบบอื่น ๆ ได้แก่ <font face='Monaco' style=\"font-size:15px\">'linear'</font>, <font face='Monaco' style=\"font-size:15px\">'nearest'</font>, <font face='Monaco' style=\"font-size:15px\">'zero'</font>, <font face='Monaco' style=\"font-size:15px\">'slinear'</font>, <font face='Monaco' style=\"font-size:15px\">'quadratic'</font>, <font face='Monaco' style=\"font-size:15px\">'cubic'</font>, <font face='Monaco' style=\"font-size:15px\">'previous'</font> และ <font face='Monaco' style=\"font-size:15px\">'next'</font> โดยการเพิ่ม arguments ลงไปดังตัวอย่าง</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "beecb445",
   "metadata": {},
   "outputs": [],
   "source": [
    "infunc2 = interp1d(xn,yn, kind='slinear')\n",
    "y2 = infunc2(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23015893",
   "metadata": {},
   "source": [
    "<!-- HTML6-3 -->\n",
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "\n",
    "<p　style=\"font-size: 16px; line-height:2.0;\">กราฟด้านล่างเป็นการเปรียบเทียบการทำ interpolation แบบต่าง ๆ ที่นิยมใช้กัน</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1296-fig6-3.png\">\n",
    "    <figcaption>การทำ interpolation แบบ linear</figcaption>\n",
    "  </center>\n",
    "</figure>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "808fd4cb",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การฟิตข้อมูลโดยใช้ scipy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการใช้ประยุกต์ที่มักจะได้พบเห็นบ่อย ๆ ในการคำนวณทางวิทยาศาสตร์ คือ การฟิตข้อมูล โดยการใช้ฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">curve_fit</font> ในอยู่ใน sub-package <font face='Monaco' style=\"font-size:15px\">optimize</font> ใน <font face='Monaco' style=\"font-size:15px\">scipy</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "da33dc50",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy\n",
    "from scipy.optimize import curve_fit"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d20c873e",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับการฟิตข้อมูลเราจะเทียบกับฟังก์ชันที่เราสร้างขึ้นมาเพื่อหาว่าพารามิเตอร์ของฟังก์ชันมีค่าเท่าใดถึงจะสอดคล้องกับข้อมูลที่เราได้มา สมมติว่าเราต้องการเท่ากับฟังก์ชันเชิงเส้น</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "b20815dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def func(x, a, b):\n",
    "    return a * x + b"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17f959ba",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ฟังก์ชันข้างต้นเป็นฟังก์ชันเชิงเส้นที่มี <font face='Monaco' style=\"font-size:15px\">x</font> เป็นตัวแปรมี <font face='Monaco' style=\"font-size:15px\">a</font> และ <font face='Monaco' style=\"font-size:15px\">b</font> เป็นพารามิเตอร์ที่เราต้องหาค่าจากข้อมูล</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะสร้างฟังก์ชันที่แทนความสัมพันธ์ ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "bb9ef3f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.linspace(0, 10, 100)\n",
    "y = func(x, 2, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d7f7a83",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ความสัมพันธ์ <font face='Monaco' style=\"font-size:15px\">y(x)</font> เป็นความสัมพันธ์โดยที่ <font face='Monaco' style=\"font-size:15px\">a = 2</font> และ <font face='Monaco' style=\"font-size:15px\">b = 1</font> ที่เราต้องหาจากข้อมูลที่ให้มา โดยมาข้อมูลที่เราวัดได้จะมีค่าความคลาดเคลื่อนดังนั้นเราจึงจำลองข้อมูลที่มีความคลาดเคลื่อนมาดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "cc2d31df",
   "metadata": {},
   "outputs": [],
   "source": [
    "yn = y + 0.9 * scipy.random.normal(size=len(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dad69a4e",
   "metadata": {},
   "source": [
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1297-fig6-4.png\">\n",
    "    <figcaption>ข้อมูลที่จำลองขึ้นมา (จุดสีน้ำเงิน) เทียบกับฟังก์ชันที่ใช้สร้างข้อมูลจำลอง (เส้นสีแดง)</figcaption>\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะสมมุติให้เราทราบค่าเฉพาะ <font face='Monaco' style=\"font-size:15px\">yn(x)</font> เท่านั้น และต้องการหาเส้นตรงที่สอดคล้องกับข้อมูลมากที่สุด (หาค่าพารามิเตอร์ <font face='Monaco' style=\"font-size:15px\">a</font> และ <font face='Monaco' style=\"font-size:15px\">b</font>) โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">curve_fit</font> ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "2cf0d0fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "params, cov = curve_fit(func, x, yn)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3174932",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">curve_fit</font> จะคืนค่ามาสองค่า ค่าแรกคือ array ที่เก็บค่าของพารามิเตอร์ ค่าที่สองคือ covariance matrix ของชุดพารามิเตอร์ ดังนั้นคำสั่ง <font face='Monaco' style=\"font-size:15px\">curve_fit</font> นอกจากจะคืนค่าประมาณพารามิเตอร์แล้วยังทำการประมาณความคลาดเคลื่อนของค่าพารามิเตอร์ให้เราทราบด้วย</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "3ce7a2fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2.02602851, 0.87141007])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "6e105c89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.03604833, 0.20865005])"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(cov.diagonal())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1c453d6",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">จากค่าที่คืนมาของคำสั่ง <font face='Monaco' style=\"font-size:15px\">curve_fit</font> จะได้ว่า</p>\n",
    "\\begin{eqnarray}\n",
    "    a &=& 1.99 \\pm 0.03 \\\\\n",
    "    b &=& 0.97 \\pm 0.20\n",
    "\\end{eqnarray}\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ซึ่งความพารามิเตอร์สอดคล้องกับที่ได้กำหนดไว้</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "449a51a9",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การอินทิเกรตโดยใช้ scipy</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการใช้ประยุกต์ที่มักจะได้พบเห็นบ่อย ๆ ในการคำนวณทางวิทยาศาสตร์ คือ การอินทิเกรตฟังก์ชัน ซึ่งเราสามารถทำได้โดยการใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">quad</font> สำหรับการอินทิเกรตหนึ่งชั้น <font face='Monaco' style=\"font-size:15px\">dblquad</font> สำหรับการอินทิเกรตสองชั้น และ <font face='Monaco' style=\"font-size:15px\">tplquad</font> สำหรับการอินทิเกรตสามชั้น ใน sub-package <font face='Monaco' style=\"font-size:15px\">integrate</font> ของ scipy</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "fbb9d859",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy\n",
    "from scipy.integrate import quad, dblquad, tplquad"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9fe612e",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">วิธีการใช้งานคำสั่ง <font face='Monaco' style=\"font-size:15px\">quad</font> มีลักษณะดังนี้</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bff83de",
   "metadata": {},
   "source": [
    "<span face=\"Monaco\" style=\"font-family: Monaco; font-size:15px; padding-left: 20px;\">quad(<i>f(x)</i>, <i>a</i>, <i>b</i>)</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a250eab",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับการอินทิเกรตฟังก์ชัน</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_a^b {\\rm d}x\\;f(x)\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะยกตัวอย่างการอินทิเกรตโดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">lambda</font> แทน function โดยสมมติให้เราต้องหาค่าของ</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_0^\\pi\\sin(x) {\\rm d}x\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "091e3ac4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.0, 2.220446049250313e-14)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "func = lambda x: np.sin(x)\n",
    "quad(func, 0, scipy.pi)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a318ab2",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">quad</font> จะคืนค่าออกมาสองค่าคือ ค่าการอินทิเกรต และค่าความคลาดเคลื่อน ดังนั้นจากการคำนวณ</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_0^\\pi\\sin(x) {\\rm d}x = 2.0\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่ง <font face='Monaco' style=\"font-size:15px\">dblquad</font> และ <font face='Monaco' style=\"font-size:15px\">tplquad</font> มีวิธีการใช้งานคล้ายคลึงกับ คำสั่ง <font face='Monaco' style=\"font-size:15px\">quad</font> ดังนี้</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9c93296",
   "metadata": {},
   "source": [
    "<span face=\"Monaco\" style=\"font-family: Monaco; font-size:15px; padding-left: 20px;\">dblquad(<i>f(y, x)</i>, <i>a</i>, <i>b</i>, <i>g(x)</i>, <i>h(x)</i>)</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8824dba0",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับการหา</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_a^b \\int_{g(x)}^{h(x)} f(y, x)\\; {\\rm d}y\\; {\\rm d}x.\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">และ</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d66a928f",
   "metadata": {},
   "source": [
    "<span face=\"Monaco\" style=\"font-family: Monaco; font-size:15px; padding-left: 20px;\">tplquad(<i>f(z, y, x)</i>, <i>a</i>, <i>b</i>, <i>g(x)</i>, <i>h(x)</i>, <i>q(y, x)</i>, <i>r(y, x)</i>)</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cebee59",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับการหา</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_a^b \\int_{g(x)}^{h(x)} \\int_{q(y, x)}^{r(y, x)} f(z, y, x)\\; {\\rm d}z \\; {\\rm d}y\\; {\\rm d}x.\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการใช้งานฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">dblquad</font> เช่นการหาค่าของ</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_0^1 {\\rm d}x \\int_0^{x^2} {\\rm d}y\\; (x \\cdot y)\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถเขียนคำสั่งได้ ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3f182bc1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.08333333333333334, 5.491107323698757e-15)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dblquad(lambda y, x: x * y, 0, 1, lambda y: 0, lambda x: x**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "608bd050",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการใช้งานฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">tplquad</font> เช่นการหาค่าของ</p>\n",
    "\n",
    "\\begin{equation}\n",
    "    \\int_0^1 {\\rm d}x \\int_0^x {\\rm d}y \\int_0^{x \\cdot y} {\\rm d}z\\;(x \\cdot y \\cdot z)\n",
    "\\end{equation}\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถเขียนคำสั่งได้ ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "6d3a2efd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.015625000000000003, 5.44356847645697e-15)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tplquad(lambda z, y, x: x*y*z, 0, 1, 0, lambda x: x, 0, lambda y, x: y*x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cb0ea96",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">เริ่มต้นการพลอตกราฟโดยใช้ Matplotlib</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">Matplotlib เป็น package ที่สำคัญของโปรแกรมภาษา Python ที่ใช้ในการพลอตกราฟซึ่ง matplotlib สามารถสร้างกราฟได้อย่างรูปแบบ</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะใช้คำสั่งในการโหลด package matplotlib ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "81dd2d1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d693d2ac",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยการโหลด module <font face='Monaco' style=\"font-size:15px\">matplotlib.pyplot</font> โดยตั้งชื่อใหม่เป็น <font face='Monaco' style=\"font-size:15px\">plt</font> เพื่อความสะดวกในการเรียกใช้ในภายหลัง ในบางกรณีเราจำเป็นต้องใช้คำสั่งของ Package Numpy เราจึงโหลดโมดูล Numpy โดยใช้คำสั่ง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "daf11ce8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f63a67e7",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการพลอตกราฟง่าย ๆ ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "ba245c7d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "func = lambda x: 2 * x + 1\n",
    "\n",
    "x = np.linspace(-1, 2, 100)\n",
    "y = func(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a918c86e",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">จากตัวอย่างข้างต้นเราใช้ฟังก์ชัน <font face='Monaco' style=\"font-size:15px\">linspace</font> ซึ่งย่อมาจาก <font face='Monaco' style=\"font-size:15px\">linear space</font> คือ ฟังก์ชันที่สร้างค่าเรียงลำดับโดยที่ผลต่างของสมาชิกถัดกันจะเท่าโดยการกำหนดค่าเริ่มต้น และค่าสุดท้าย คำสั่ง <font face='Monaco' style=\"font-size:15px\">np.linspace(-1, 2, 100)</font> ในตัวอย่างคือการสร้างลำดับ <font face='Monaco' style=\"font-size:15px\">array</font> จาก <font face='Monaco' style=\"font-size:15px\">-1</font> ถึง <font face='Monaco' style=\"font-size:15px\">2</font> โดยมีสมาชิกทั้งหมด <font face='Monaco' style=\"font-size:15px\">100</font> ตัว</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">หลังจากที่เราได้ค่า <font face='Monaco' style=\"font-size:15px\">x</font> และ <font face='Monaco' style=\"font-size:15px\">y</font> แล้วเราสามารถพลอตกราฟได้ ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "51b0a795",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3c103b0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d9e0520",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a70beea7",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">plot</font> ในการพลอตคู่อันดับ <font face='Monaco' style=\"font-size:15px\">x</font> และ <font face='Monaco' style=\"font-size:15px\">y</font> และ คำสั่ง <font face='Monaco' style=\"font-size:15px\">show</font> ในการแสดงพลอตออกมาใน <font face='Monaco' style=\"font-size:15px\">output</font> (ส่วนมากจะแสดงผ่านหน้าจอ) เมื่อรันโปรแกรมเราจะได้พลอตแบบนี้ออกมา</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img src=\"https://indico.narit.or.th/event/229/images/1298-figure7-1.png\">\n",
    "    <!--<figcaption>Guido van Rossum ผู้สร้างโปรแกรมภาษา Python</figcaption>-->\n",
    "  </center>\n",
    "</figure>\n",
    "<br />\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ซึ่งเป็นกราฟง่าย ๆ การใส่รายละเอียดของกราฟเราจะพูดในหัวข้อถัดไป</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ชุดคำสั่งอื่น ๆ ที่สามารถใช้พลอตกราฟได้แสดงไว้ในตารางต่อไปนี้</p>\n",
    "\n",
    "<div id=\"object-type\">\n",
    "<table>\n",
    "    <tbody>\n",
    "        <tr>\n",
    "            <td bgcolor=\"#B0B0B0\" align=\"center\" width=175px><span style=\"color:#000000;font-family:'Kanit'; font-size:20px\">คำสั่ง</span></td>\n",
    "            <td bgcolor=\"#B0B0B0\" align=\"center\" width=400px><span style=\"color:#000000;font-family:'Kanit'; font-size:20px\">การใช้งาน</span></td>\n",
    "        </tr>\n",
    "        <tr>\n",
    "            <td><span><font face=\"Monaco\" size=\"4\" style=\"padding-left: 15px\">plot(x, y)</font></span></td>\n",
    "            <td><span><font face=\"Helvatica\" size=\"4\" style=\"padding-left: 15px\">คำสั่งที่ใช้พลอตกราฟคู่อันดับ <font face='Monaco' style=\"font-size:15px\">(x ,y)</font> ทั่วไป</font></span></td>\n",
    "        </tr>\n",
    "        <tr>\n",
    "            <td><span><font face=\"Monaco\" size=\"4\" style=\"padding-left: 15px\">scatter(x, y)</font></span></td>\n",
    "            <td><span><font face=\"Helvatica\" size=\"4\" style=\"padding-left: 15px\">คำสั่งที่ใช้พลอตกราฟคู่อันดับ <font face='Monaco' style=\"font-size:15px\">(x ,y)</font> เฉพาะจุดเท่านั้น โดยไม่มีเส้น</font></span></td>\n",
    "        </tr>\n",
    "        <tr>\n",
    "            <td><span><font face=\"Monaco\" size=\"4\" style=\"padding-left: 15px\">errorbar(x, y, ye, xe)</font></span></td>\n",
    "            <td><span><font face=\"Helvatica\" size=\"4\" style=\"padding-left: 15px\">คำสั่งที่ใช้พลอตกราฟคู่อันดับ <font face='Monaco' style=\"font-size:15px\">(x ,y)</font> โดยมีค่าความคลาดเคลื่อนในแนวแกน <font face='Monaco' style=\"font-size:15px\">y</font> และ <font face='Monaco' style=\"font-size:15px\">x</font></font></span></td>\n",
    "        </tr>\n",
    "    </tbody>\n",
    "    <caption text-align=\"center\" caption-side=\"bottom\" vertical-align=\"bottom\">ชุดคำสั่งในการพลอตกราฟแบบต่าง ๆ ใน <font face='Monaco' style=\"font-size:15px\">matplotlib.pyplot</font><br /></caption>\n",
    "</table>\n",
    "</div>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการพลอตกราฟในรูปแบบที่ได้นำเสนอในหัวข้อนี้ สามารถศึกษาเพิ่มเติมได้ที่</p>\n",
    "\n",
    "<p><a href=\"https://matplotlib.org/gallery/index.html\" target=\"_blank\">https://matplotlib.org/gallery/index.html</a></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3fbf9ca",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">ตัวอย่างการกำหนดสี และเส้นของกราฟ</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถกำหนดสี และเส้นของกราฟได้โดยการระบุคุณสมบัติของสี และเส้นในคำสั่งที่ใช้ในการพลอต (<font face='Monaco' style=\"font-size:15px\">plot</font> <font face='Monaco' style=\"font-size:15px\">scatter</font> และ <font face='Monaco' style=\"font-size:15px\">errorbar</font> เป็นต้น)</p>\n",
    "\n",
    "<h2 style=\"color:#011993;font-family:'Kanit'; font-size:20px\">การกำหนดสีของกราฟ</h2>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถกำหนดสีของกราฟได้หลายวิธี โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">color</font> หรือ <font face='Monaco' style=\"font-size:15px\">c</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "241417ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.linspace(0,1,100)\n",
    "y1 = [i**2 for i in x]\n",
    "y2 = [0.75 * i**2 for i in x]\n",
    "y3 = [1.25 * i**2 for i in x]\n",
    "\n",
    "plt.plot(x, y1, 'r')\n",
    "plt.plot(x, y2, c='#4433ff')\n",
    "plt.plot(x, y3, color=(0.1,0.2,0.4))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8855b4f",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่งที่ใช้ในการเขียนรหัสสี สามารถศึกษาได้จาก</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/colors_api.html\" target=\"_blank\">https://matplotlib.org/stable/api/colors_api.html</a></p>\n",
    "\n",
    "<h2 style=\"color:#011993;font-family:'Kanit'; font-size:20px\">การกำหนดเส้นของกราฟ</h2>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราสามารถกำหนดลักษณะของเส้นได้ (เช่น เส้นทึบ เส้นประ) โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">linestyle</font> หรือ <font face='Monaco' style=\"font-size:15px\">ls</font> และ ความหนาของเส้นกราฟด้วยคำสั่ง <font face='Monaco' style=\"font-size:15px\">linewidth</font> หรือ <font face='Monaco' style=\"font-size:15px\">lw</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "1b3f899a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rXZYyPu5MH9nK9YtsndsFc0dA3Gk4uQGCQqBSU4dUJU/oQgiHmbl7Jm4mN9Y8ssZhs0G11nyz7hjPz9uTFeZVAryZ/3h714a51rBjJnzXzQhzgPRkmDcCkmJv+dGCsjr131Fk6r8QJZfWGqUUFm0hKiGKyv6O2Vg5w6J55/cDzNx8MutY/SB/Zj7amqDSXg6p0yapibD0edgzJ/fz9brDoDlgyv8zdWGn/gshhM3Co8Np+11bTl45iUmZHBbmyWkZPDV7Z44wb1OzLHP/3c61YX7pKEzrnHeYAxxecevzBSR96EIIu9l3YR+dfuiEm8mNlPQUh9VzJTGVf/0QxvaT17sueoZU4uOHm+Ll7sLZn/sXwOKnITXh1uXaPQVNHrZ79RLoQgi72HthL51+6ISH2YM1j6yhXrl6DqnnTEwij8zYxvGL17KOPdahJq/1bOC62Z/pKbDyNdg25dblPPyg72Ro1M8hzZBAF0IU2v7o/dz7/b14u3k79AXo3sgrPDYzjEsJ15/+X+vZgNEdHTd6xqrYkzD/UTi389blyjeAgT9CoOOWCpZAF0IUWtVSVbm7+t1M6jKJ2mVrO6SO1Ycu8OSsXSSlGXt/ephNfPxwU3o3dUwfvU0OLYWFYyEl7tblmgyEXp+Ch69DmyOBLoQosD1Re6hXrh4BXgEsGLjAYfX8+PdJ3lgcTuaoREp7uzN1RCita5Z1WJ02SYy5dZibPaD7hxD6mMNniYKMchFCFNC6k+u4c8adjFsxzmF1WCya95YeYPxv18O8ahlvfh3bzvVhDtB8GDQZlPu5MjVg1J/QapRTwhzkCV0IUQArj62k38/9qB5QnTfuecMhdSSlZvDc3N2sCI/KOta0ammmPdKK8v6eDqkz35SCXp8Ys0EvRVw/Xr+X8fLTO8CpzZEndCFEvvx++PeszSnWjVznkHHm0fHJDJryd44w79qwIj+PaVd0wvwfHr7w0Exw8waTu9HFMvAnp4c5yBO6ECIfktKS+Pfv/yakQggrh6+krLf9uz0iouJ5bOb2HEvfPtahJq/2bIC5qG5KUbEhPPA1lA6Gqi1d1gwJdCGEzbzdvVk5bCVVS1V1yLZxayKieXr2LhJS0gEwKXirTyOGt6th97qs0houRkCF+raVb/SAY9tjA+lyEUJYNXnbZMavHg9AowqN7B7mWmtmbjrBqJnbs8Lc18PMdyNbuSbMk2Jh/iPwbUeI2uf8+gtIAl0IkSetNe9veJ+nlj/F3ui9pFvS7V5HWoaF138L580lB7JGslQJ8OaXse259w7HbVGXp1N/wzcd4cBvkJFqTBpKvWb9c0WABLoQIldaa15e9TKvrn6VoSFD+eWhX+y+OUVcYhojZ2zjxy2nso41qxbAwifb06BSKbvWZVVGOqz5AGb2gLgz149fPgLL/8+5bSkgCXQhRK6eWf4MEzdPZGzoWH544Afcze52vf7xiwk88NUmNh29nHWsV5NK/DymLRX8XbBaYkIUbPkKtOXmc7t+hP2/Or9N+SQvRYUQuWpfrT3+nv68d997KDtPjNlw5CJPztrJ1eTrXTjPda7HM53q2L0um5WuakzP/3VU7ue3fweN+jttklBByBO6ECLLtdRrrD25FoDBIYN5v9P7dg1YrTUzNp1g5IztWWHu5W5i8pAWPNu5ruvC/B8hD0LTwTcfbz0Ghi0o0mEO8oQuhMgUkxRDz9k92RO1h+PPHifIL8iu109Nt/DG4v3M2Xa9f7piKU+mjgilSdUAu9ZVKD0mwektEHsCfMpB36/gju6ubpVNJNCFEERejaTbT904FnOMOQPm2D3ML8anMPanHYSdur4hRdNqAUwZ3pKKpVy4u1BuPP1hwHew7kPo8wX42/fXwpFs6nJRSnVXSkUopY4qpV7Oo8zDSqkDSqlwpdRs+zZTCOEohy4dov137Ym8GsmKYSt4oIF9J8jsi4yjz5cbc4R5v2aVmTumrXPD/PIxsGTYVrZqSxg6v1iFOdjwhK6UMgOTgS5AJLBdKbVYa30gW5m6wCtAB611rFLKBYNHhRAF8fP+n0nNSGXdyHU0C2pm12sv2nWW//t1LynpxsgRpeDl7vUZc1ct5/WXWyyw9RtY9Sbc+1+4c5xz6nUBpbW+dQGl2gFvaq27Zf78CoDW+oNsZSYCh7XW02ytODQ0VIeFhRWo0UKIwktMS8TH3QeLtnAh4QKV/CvZ7drpGRY+XH6IaRtPZB3z93Lji8HNuceZk4WunIFFY+HkBuNnkzuMWQNBIc5rg50ppXZorUNzO2dLl0sVINsoeyIzj2VXD6inlNqklNqilMr1DYJSaoxSKkwpFXbx4kVb2i6EcIDpu6ZT74t6nLxyEpMy2TXMY66l8siMbTnCvHZ5X357soPzwlxr2D0Hvm5/PcwBLGnw678gLdk57XAyew1bdAPqAvcAg4GpSqmAGwtpradorUO11qHly5e3U9VCCFtprXl3/buMWjyKRhUaEegTaNfr7z8bR+8vNuaYLNSlYUUWPdmBWuX97FpXnhIuwtxhsOhxSLl68/mLB2H1O85pi5PZEuhngWrZfq6aeSy7SGCx1jpNa30COIwR8EKIIiLdks7jvz/O+DXjGdZkGEsGL8HPw34h++uOSAZ8vTnHsrfPdqrLt8Na4u9l31mmeTqwGL5qA4d+v3W5HTON4C9hbBm2uB2oq5SqiRHkg4AhN5RZhPFkPkMpFYjRBXPcju0UQhTShI0TmLJzCq/c+YpdZ3+mplt4d+kBfvj7+nos/p5ufDqwGZ0bVrRLHVYlxsDyl2DffOtlq7aCB74Fv5LXS2A10LXW6Uqpp4A/ADMwXWsdrpR6GwjTWi/OPNdVKXUAyABe1FpfzvuqQghne7bts9QpW4eBjQfa7ZpRcck8MWsHO09fyTpWt4If3w5v6bwulojlsORZSLhw63ImN7jnFegwDswlcwqO1VEujiKjXIRwvIMXDzJ+zXhm9ptp1+4VgL+PXebpOTu5lJCadaxHSBATH2yKn6cTAjMpFpa/DHt/tl62fAPo/y1Uaur4djnYrUa5lMx/poQQrDu5jgfmPoCH2YPTcadpWL6hXa5rsWi+WX+Mj/6IyFq/3GxSvNy9PqM71nTO+PKI5bBknLFC4i0p6PAM3PsquBWxvUgdQAJdiBLoxz0/MmrxKGqXrc3yocupEVDDLteNS0rjP/P2sOrg9e6NQD8Pvhjcgna1y9mljltKjDHWJt83z3rZsrWg3zcQ3Mbx7SoiJNCFKGG+3v41Tyx7gvtq3scvD/1CGe8ydrnuvsg4npi9gzMx10exhFYvw+ShLZwzhT98ESx7Aa7ZMDql9b+h8xvg4evwZhUlEuhClDDd63RnXJtxTOgyAQ+zR6Gvp7Vm1tbTvL3kAKkZ1zd/GHVnTV6+vz7uZgevwh1/wQjyg4utlw0Ihr6ToeZdjm1TESWBLkQJEH0tmm/CvuG1u16jZpmafNr9U7tcNyElnVcX7uO33eeyjvl5ujHxwSb0CLHf7NJcaQ27Z8Mf/4XkK9bLtxoNnd80Vku8TUmgC1HMhUeH02tOL6ISonig/gOEVLTPOiUHz1/lyVk7OX7p+gbJDSqV4uuhLagR6OCujNiTxkvP42uslw2oDn2/vG2fyrOTQBeiGFt6eCmDfx2Mr4cv60eut0uYa62Zs+0Mby0Jz1olEWBQq2q82acRXu7mQteRJ0uGsTLi6nchLdF6+db/hk6vg6eTxrwXcRLoQhRTX2//mieXPUmzoGYsHryYqqWqFvqaV5PTeGXBPpbuPZ91zNfDzPv9Q+jb7MY1+ezs/F5Y8gyc22W9bNnaxlN59faObVMxI4EuRDHVoHwDBjYeyLTe0/C1w2iOvZFXeGr2Lk7HXH8yrh/kz+ShLajtyFmfqYnG7kCbvwRtZQMKZYL2TxszPt29HdemYkoCXYhi5ELCBVYcXcEjzR7hnhr3cE+Newp9TYtFM23jcSauiCDdcn3m+NA2wYzv1dCxXSxHVsHS5+HKKetlKzQynsqrtHBce4o5CXQhiomd53fS9+e+xCbF0rV2V7usYX4xPoX/zN/D+sPXx3b7e7rx4YAm9GziwFEs8Rfgj1dg/6/Wy5o94O6XoP2z4Fb4YZglmQS6EMXAnH1zGLV4FIE+gWx4dINdwnxNRDQvzt+TYy2WZtUC+HxQc4LL+RT6+rmyZMCOGbDqbUiJs14+uD30/gzK13NMe0oYCXQhirhX/3qV9ze+T8fgjsx/aD4V/Qq3JG1yWgYTVhxixqaTOY4/fndt/tO1nuMmCmWkw8wecGar9bKepaHLW9DiETA5eOJSCSKBLkQRV7VUVcaGjuV/3f9X6Jmfhy/E88ycXRyKis86Vt7fk08ebkrHug5eH9zsBlVCrQd6w75w/0TwD3Jse0ogCXQhiqA9UXuIvBpJz3o9GdtqbKGvp7Xm+80n+WD5oRxjyzvVr8DEB5tQzs9JKxHe+wqEL4T4czefK1UVekyC+j2c05YSSAJdiCJm9r7ZjF48muDSwXSr0w03U+H+mkZfTealX/eyNuL6i09PNxP/7dGAEe2qO2e526yK/eH+CTBv+PVjygRtnzCGIsoEoUKRQBeiiEjNSOWFlS/wxbYvsvrLCxvmK/af55UF+4hNTMs6Vj/In88HN6deRRetedKgN9TrDodXQJWW0OvTErHxRFEggS5EEZCUlkTnHzuz+cxmnmv7HBM6T8DdXPCNla8mp/HW4gP8ujMyx/HRd9bkxe534Olm57HlWsPJDbatp6KU0Udetwu0fBRMDhznfpuRQBeiCPB296ZNlTY80/qZQu/5ufnYJV6cv5ezV66vW165tBcfPdSU9nUCC9vUm0XtMzadOLUJhsyHel2tf6ZMdWN1RGFXEuhCuIhFW5i0aRLd6nSjWVAzPun2SaGul5SawcQ/bh6O2LdZZd7u25jS3gV/4s9VYgyseQ/CpoPOfNG6/CXjKd3dCRteiJtIoAvhAjFJMYxcNJIlh5dwKfESzYKaFep6O0/H8sK8PTmWug3wcee9fiGOmfF5fg/80NfYqDm72BPw95dw1wv2r1NYJYEuhJNtjdzKwF8Gci7+HJ93/5ynWj9V4GulpGfwv1VH+HbdMbItw8K9d5RnwoAmVHDU1nDl64NXwM2BDrD+I2gyEAKqOaZukSeZgiWEE204tYGOMzqilGLjYxt5us3TBR42uOfMFXp9vpGv114Pcz9PNyYMCGH6yFaOC3MAN0/o9n7u59KTYMvXjqtb5MmmQFdKdVdKRSiljiqlXr5FuQFKKa2UCrVfE4Uo/rQ2Erdt1ba81OEldo7ZSesqrQt0rX+m7j/w1SaORCdkHW9XqxwrxnVkYKtg54wtv+N+qHVvzmOepaDre8a0feF0VgNdKWUGJgP3Aw2BwUqphrmU8weeBWxYqEGI28fmM5vpML0DlxIv4W5259373qWMd5kCXWvHqVh6fr4hx1O5j4eZt/s2YtboNlQt46BFtXKjFHT/EFTmsMPmw+DpHdD+KSjEkEtRcLb0obcGjmqtjwMopX4G+gIHbij3DjABeNGuLRSimMqwZDBx00TGrxlPcOlgLiRcINCnYMMGE1PT+XjlYaZvOoHO1lfetlZZJg5oar/VEbWGw3+AJR0a9LJevkJ9I9SrtISqLe3TBlFgtgR6FeBMtp8jgTbZCyilWgDVtNZLlVJ5BrpSagwwBiA4ODj/rRWimDgXf47hC4ez+sRqBjYayLe9vqW0V+kCXWvjkUu8snAvZ2Kujyv39TDz8v31GdqmOiaTnbpXzu2CleONCUJ+QVDrHtum4rcZY5/6RaEVepSLUsoEfAKMtFZWaz0FmAIQGhqqrRQXoth66c+X2BK5he/6fMejzR4tUJ/2lcRU3lt6kPk7cs727Fg3kA/6h9iveyX2lLEp8755148lRMHmz+He/9qnDuEUtgT6WSD7+KOqmcf+4Q80BtZm/qENAhYrpfporcPs1VAhirrEtETiU+Kp6FeRT7p9wmt3vUb9wPr5vo7WmiV7z/P2kvAcm0+U9nbntZ4NeLBlVfu89EyMgY2fwNZvISP15vObPjfWIy/t4M2hhd3YEujbgbpKqZoYQT4IGPLPSa11HJDVMaiUWgu8IGEubid7ovYwZMEQAn0CWfvIWir4VqCCb4V8XycyNpHxi/azJtvKiAA9QyrxRp+GVPC3w1DEtCTY+g1s/BSSb7FrUHoS/PU29P+28HUKp7Aa6FrrdKXUU8AfgBmYrrUOV0q9DYRprRc7upFCFFUWbeHjzR/z6upXCfQJ5H/d/legp+e0DAszNp3g0z+PkJSWkXU8qJQXb/dtRNdGdtjsISMdds+CtR/mvh55bk7/DSnxxrK3osizqQ9da70MWHbDsdfzKHtP4ZslRNEXlRDF4F8Hs/bkWvo36M+UXlMo51Mu39fZeTqWVxfu5+D5q1nHlILhbavzYrc78Pcq5BBAreHgYvjrHbh8xLbPeJaGu/4Drf8t67IUIzL1X4gC8vPwIzYplul9pjOy2ch8P5lfSUxlwooIft5+OsdQxPpB/rz3QAgtqxdsrHoWreHYaqPb5Pxu2z5jcjdWQbzrRfDN/z9OwrUk0IXIh4vXLvLehvf4oNMH+Hn4sfPfOzGp/K2gYbFoft0ZyYfLD3H52vWXkV7uJsZ1rseoO2sWfqPm01uMJ/JTG23/TOMBcN94KFuzcHULl5FAF8JGvx74lbFLxxKXEkffO/pyb8178x3mB85d5fXf9hN2KueiVp3qV+DNPo2oVraQQxHP7jSWtD26yvbP1LwLOr8FVVoUrm7hchLoQlgRkxTD08ufZva+2bSo1ILV/VbTuELjfF0jLimNT/88zA9/n8yxKmLl0l680acRXRtWLNxQxPN7jZedEUtt/0xQiBHkte8zOu1FsSeBLoQVIxeNZPnR5bx1z1u8cucr+doazmLR/LIzkgk3dK+4mxWjO9bi6fvq4ONRiL+GF8KNID+Yj8FmZWvBfa9BwwfAJAuuliRKa9dM2AwNDdVhYTJUXRRNlxIvoVCU8ynHoUuHSE5PzvcmFLtOx/LmkgPsOXMlx/H2tcvxdt/G1KlQiB3uL4TDuglw4DfbP+NfyXjZ2WKELJ5VjCmldmitc13RVp7QhchGa8288Hk8vfxputbuyk/9f8r3bM/oq8l8uOIQC3aezXG8cmkvXuvVkPsbBxW8eyVqH6ybmL8ncu8ycOfz0Ppf4O5dsHpFsSCBLkSms1fP8sSyJ1gcsZhWlVvxfx3+L1+fT07L4LuNJ5i85iiJqdcnB3m4mRjTsRZP3Fu74N0r53bBukn56yP3LAXtn4Y2j4NXqYLVK4oVCXQhgD+P/cmD8x8kLSONj7p8xLi24zCbzDZ9VmvNsn1RfLD8IJGxSTnOdW1Ykdd6Niz48rant8L6SXD0T9s/4+4Lbf5thLlP2YLVK4olCXRxW7NoCyZlIqRiCJ1qdmJil4nUKVvH5s/vOh3Lu0sPsuOGYYj1Kvrxeq9G3Fm3AOufaw3H18CGT4ylbG3l7gOtx0D7Z2RS0G1KAl3clpLSknh/w/tsjtzMn8P/JMgviAUDF9j8+TMxiUz6I4LFe3KuiVLGx53nu97B4FbVcCvI5KATG+DP1+HcTts/4+5jzO5s/wz4lc9/naLEkEAXt51Vx1cxdulYjsYcZXiT4SSlJeHr4WvTZ+MS0/hyzRG+33yK1AxL1nF3s+KRdjV4+r66lPYpxAiSxMu2h7m7D7QaBe2flSAXgAS6uI3EJMXwxNInmBs+lzpl67Bq+Co61epk02eT0zL44e+TTF5zjLiktBzn7m8cxMv316d6Odv+UbilBr2hbG2IOZZ3GQ8/o2ul3ZPgW7At7UTJJIEubhvebt7svbCXt+55i5c6vISXm/VVBDMsmoW7zvLJygjOxSXnONc8OIBXezQgtIYdXzyazNDhWVjyzM3nvEpDm7HGC0952SlyIYEuSrT1p9bz0eaPmPvgXLzdvdk7di9uJut/7LXW/BF+gY9XRnAkOiHHuerlfHipW316hORzPHlijG1B3HQQrHnf2AYOwCcQ2o41xpEXcF9ScXuQQBcl0tmrZ3lp1UvM3jeb6qWrc+LKCRqWb2g1zLXWbDp6mY9WRrD7hhmegX4ePNOpLoNaBePhZuMLT63h6F/w95fGWPLnwq1vvOzmaXSnbP0WOjwDzYeDh532DxUlmgS6KFHSLelM2jSJ9za8R7olndc6vsYrHV/Bx916IO44FcOkPyLYcjwmx3E/TzdGd6zJ6I618PO08a9MaiLsnWts9Xbx0PXju2cZXSbWtB5jTAhy87CtPiGQQBcljFmZ+f3I73Sp3YWPu35MrTK1rH5m95krfPrnYdYdzrmPp4ebiRFtq/PEvXUo65vPYF36POyZc/PxvydD6CgwW/mrJ7sEiQKQQBfF3u6o3YxfM56pvacS5BfEymErbRqGuC8yjs/+Osyqg9E5jptNiodDq/H0fXWoHFDAtU9ajsw90K+cgkNLoNEDBbuuELcggS6KrXPx53ht9WvM3D2Tst5lOXjxIEF+QVbDPK8gVwr6Nq3MuM71qBFYyCGI1dpA5eZGv/mNNn0ODfvJGuTC7iTQRbGjtead9e8wYdME0i3pPN/ueV676zUCvAJu+bmdp2P54q8jrInI2bWiFPQMqcS4znWpU8GG3e0z0q13mShlDDFcOCbncZ9yUKczWNJlCVthdxLootj4Z90VpRQRlyPoWbcnH3b+8Jb95FprthyPYfKao2w8einHOaWgR0glnrmvLncEWQnyjDSIWA5h3xmh/OB06w1u9AD8OR4SLkDgHdDuCWgyUJawFQ5jU6ArpboDnwFmYJrW+sMbzj8PjAbSgYvAY1rrU3Zuq7hNaa1ZcHAB49eMZ86AOTQNasr3/b6/5RBErTWrD0Uzec1Rdp6+kuNcvoL8ymnY+YPxlXDBOGZyg/gL4F/x1p9184DuH4BXgGzzJpzCaqArpczAZKALEAlsV0ot1lofyFZsFxCqtU5USo0FJgIDHdFgcXv56/hfvPzXy4SdC6NBYAOupV0DyDPM0zIs/L73HN+uO86hqPgc58wmRd+mlXni3jq33i0oIw0Or4Ad32dutnzDrl6WdCPg737R+g00HmC9jBB2YssTemvgqNb6OIBS6megL5AV6FrrNdnKbwGG2bOR4vajtabvz31ZcngJ1UpVY0bfGQxvMjzPNcqvpaQzL+wM0zac4OyVnGuSe5hNDGhZlcfvrnXr9VYuHzOCevdsuBaddzmAHTPgzues96UL4US2/GmsApzJ9nMk0OYW5UcBy3M7oZQaA4wBCA4OtrGJ4nZy4OIBGgQ2QClFx+CO3FfzPh4PfTzPdVei45P5YfMpftxy6qZFs3w8zAxuHcy/OtYiqHQe47pTrxn7cu76CU5tsr2hV88aT/ENetn+GSEczK6PF0qpYUAocHdu57XWU4ApYGwSbc+6RfG2O2o3b659k98ifmPpkKX0qNuDFzvk3aVxKOoq3204wW+7z+VYxhagrK8Hj7avwfB21QnwyWVCkNZwajPsmQ3hiyA14eYy1vgEQnJc/j8nhAPZEuhngWrZfq6aeSwHpVRn4FXgbq11in2aJ0q6Xed38c76d1h4aCGlPUvz1j1v0aFah1zLWiyaNRHRzNh08qYRK2AsmjX6zpo82LIa3h65dM3EHIe984wJP7EnC9bg6ndC6KPGMrdungW7hhAOYkugbwfqKqVqYgT5IGBI9gJKqebAt0B3rbWVzkchDOmWdPr83If4lHhev+t1nmv3XK5jyeOT0/hlRyTfbz7JycuJN51vHhzAvzrWolujIMymG0aSJMbAgUWwZy6c2VKwhnqXhaaDoeUjUP6Ogl1DCCewGuha63Sl1FPAHxjDFqdrrcOVUm8DYVrrxcAkwA+Yn7mc6GmtdR8HtlsUQ1pr1p1ax9SdU5nRdwYeZg8WPLyAeuXqUTqXZWGPRifww98n+XVHJNdSM3KcMyno1iiI0R1r0bJ6mZwfTEuCw3/AvvnGfy05+9ZtVvMuaPEI1O8la6uIYsGmPnSt9TJg2Q3HXs/2fWc7t0uUIBZtYUnEEiZsmsDfkX9T0bciEZciCKkYQqsqrXKUTcuwsOrABX7ccorNxy7fdC1/LzcGtw5meNvqVCubbQXFjDQ4sQ72/QoHl0Bq/E2ftYl/JWg2BJoPg7LWF/YSoiiRMVfCoaISorjv+/s4eOkgNQJq8OX9X/JY88fwvmG2ZGRsInO3n2Hu9jNEx9/8CqZuBT9GtK9B/+ZV8P1nCVtLhvFyc/+vcHCxsR9nQZg94I77jXXHa99n7BokRDEkgS7sLiYphl3nd9GpVicq+lakeaXmjL9rPA81eijHhKC0DAurD0Xz87bTrD18EX3DuCeTgs4NKjKyfQ3a1S5n7A5kyYCTGyF8IRxYbH28+K1Ubg7NhhqTf2RLN1ECSKALu4m4FMFnWz/j+z3GtPzz/zmPj7sPs/rPylHuxKVrzA87w/wdkVzM5Wm8vL8ng1tVY3CbYCqV9ja6U46vMQL80O9w7eJNn7GZf2Vo8rCxzVuFBgW/jhBFkAS6KLQ9UXv47+r/suzIMjzNngwNGcqzbZ/NsUtQQko6y/ad55ewSLadjMn1Oh3rBjK0TTCdGlTE3Zxti7fTW+DHQqwf7lkKGvSBJg9BjY7SpSJKLAl0USBXkq+QmJZIZf/KWLSFned38ubdbzK21Vgq+FYAIMOi2XL8Mr/uiGT5/iiS0jJuuk55f08ealmVga2q5T0tP7idMXQwKfd/CHJl9oC6XSHkQajXXVY4FLcFCXSRL7ujdvPV9q+YtW8WDzV8iJn9ZtK8UnNOjzuNe+b63hFR8SzYFclvu84RdTX5pmuYTYp776jAwy2rcG8tb9x9Am5dqdkN6vcwpuffijJDrbuhUX9j4o+3lesKUcJIoAubzN0/l0+2fMK2s9vwdvNmSMgQnmj1RNb5C1fTWLLnNL/tPnvTKof/qFfRj4FNyzGg3AkCzsyGP1dCpaYwaFau5XNo0Cf3QFcmqN4BGvUzdgHyDSzYDQpRAkigi1xprdlxfgctKrXApExsPbuVhNQEPuv+GcObDKeMdxkuXE1m+sYT/L733E1rjv+jrK8HvZtUYlADT+pv/T/Upo2Qke1FaGIMpKdYn0Zf827w8DPWXVEmqHGnEfIN+4JfBfvduBDFmNI3jhVzktDQUB0WFuaSukXeohKimLV3FjP3zGR/9H5WDV9Fp1qdSE5PxtPsyYWrKSzff55l+84Tdir2pqGGAF7uJjo1qEj/5lW4q1554wVnRjpMrAUpuSxoNWwB1OlkvXEb/2d0o9TvJU/i4rallNqhtQ7N7Zw8oQsALiRcYPSS0Sw/spwMnUHrKq35puc3tKrSilOXr/FHeBQr9kfl8SSucTOZ6FAnkH7NK9OlYRB+njf80TK7Qa27jFmcNzr8h22Bfue4AtyZELcPCfTbVIYlg7Un1xKXEkf/Bv0p51OO8/HneaH9CwwPGUF6amX+PHCBh77aTcSFnH3inqTSTB2jnfkA3XwO41s2CL/hsynrm8tStdnV6ZxHoK+A+yfIFm1CFJIE+m3Eoi1sidzC3P1zmXdgHlEJUTQs35D+DfqTmg4f3rmUvw5d4NFp54iOP5H1OR+SaWE6QivTIdqaDtLcdAwPMhe8SgViT4GXKfdKs6udx1O4TzlIvgLeZXI/L4SwiQR6CWfRFhQKpRRPL3uar8K+wtPsSc+6Pbmv+gO4pbZkxPRtbDl+mdR0Y6OI8lyhu+kwrUwRtDRF0FidxE1Z8q4k5SpE7YEqLW/dmIBqEHgHxEdB7XuNceJ1OlvfbFkIYRMJ9BIoNSOVtSfXsvDgQhZFLOKvEX8ZT+L1h+CrGpKR2IKtx5KYtCsJdw7TUJ1ksOkYLdyP0EIdoZqpAFPrT6y3HugAQ+dDqSqyF6cQDiB/q0qQyKuRvLDyBZYfXc7VlKv4uPvQulInpm08yvFzseyLjKEG7jRRvzHKdJxmHsdoqE7iqdILX/mJDcamydaUqV74uoQQuZJAL6a01uy5sIflR5ZTPaA6Q0KG4KH8WHNiA/VLd8UjNRSfaF8aHomkoWk2A00naOhxCn+V5JgGXToMFguYbOhLF0I4hAR6MTM/fD6/H/mdlcdWEpUQBUDrsr0IX3UVj8sH+B8taRh/lDvUGrzcC7hTjy28AowZmjU6GDv7VGgkYS6Ei0mgF2ExSTGsP7WeiEsRPNf2RQ5FXeX9Pz/k6NVDhFCeRzPqMlAl0vTyemC9Y383fStA9XZGiAe3g4qNJcCFKGIk0IuYLZFb+HHPT/x1fB2HY8LRaMzKm6kr6pGe7sHr7mUYaTZjIhYcmaflG0C1VkZ4V2tjbMcm48SFKNIk0J1Na0iKJfXyMXafWsvGk5vZFL2fcZ4N+L3iuyw78TPh16bhaWlAKcsQvCwheFruIB1jJcOLltqYzNvt2yavAKgaClVCoWor43tZqVCIYkcC3QlS0lOIjk/kQpzmz8MbWLh5AHvIIDXzgbeSVjyrz7PwzHGS6Ug17kXl8ltTraw3ZQIaw7lCNMbdB4KaQJUWULmF8V95+haiRJBAtyYt2dhYITHG2IT4n69rl4yt0K5FQ0I0OuECSY2HEF77UZYeXsXu83s5HBvOuYRDXM04SUDqKEpl9CZdXaa6pzvPYKaNNtMWM1UxgYKq6iLHdWUAqgR406hyKRpXKU2TqqVpUjXAmFp/KRi+fM22tnuWMsK7UhPjv5WbQWA92bFHiBKqeAZ6SjykJRndF2hj42BLOugMY1U/S5qxD2VGqrE0a0aKEczpmV+piZB2zfhvaoJxvdQESL5qzHpMvgrJcZAUm3Op10wJaI5h4SgWIjK/2mCmzJq/+b8/63DGeygAZl0Od0sN/C398LTUA8BNV+R/lsa0Mh2+6bovtfbAP6QNDSqVyntdlDI1jN14MlKzHVTGU3bFRplfjSGoMQRUlydvIW4jNgW6Uqo78BlgBqZprT+84bwn8APQErgMDNRan7RvU7NZOR52zHDY5S9j4QyaSCxEojmFhYooxmGs2V2LBC6q6+vGVtaKqijuUFcw4UVQyiTcLFUx459VxtvdTM1AX+pU8KNUTC24eHOgd6+cDHWsLAtrdoMWj4CHD1RoCOXrG0/dHj63/pwQosSzGuhKKTMwGegCRALblVKLtdYHshUbBcRqresopQYBE4CB9m5sfHIaE1dE0OtMLG2slE1Hcw3jaToBTSoQgtHV8Dtp7MdCDJqLaKLRlEPxA8a+k91IZEe2tUvcNfTAjXGZP0/EEx+tqIOJepjww3gKDjddoX6QP9XK3kONcj7UCPSlellfapX3JaiUFyZT5tPyX43g4oqbGx1z4uZjuen5kW3lhBC3FVue0FsDR7XWxwGUUj8DfYHsgd4XeDPz+1+AL5VSStt594yUdAs/bjnFAY/thJsSsAAWNGkYN3Is84l4BEn8qHJOqqmoFVGZ56eRxm8qHU8N5VFUQFGO6/3Kb+BJioZqKKphoiIKM9e7LkaSe3dIQ/9EVoy7y/qNlK1tdJEEBBtdKAHVjf9WapqPXw0hhMjJlkCvApzJ9nMk3PSAnFVGa52ulIoDygGXshdSSo0BxgAEBwfnu7H/RGqA9qYZJkyZx9xReGUr1w836mgTfoAfCl8UZbOdn4E3nhp8yL1/uXfmEMF8t+/aRaM/39pLx+ZDjS8hhLAjp74U1VpPAaaAsQVdfj/v6+nGW30a0eZgS+qfOZpnuf640/8W1ymTR5DnSpmNdbp9yhrrdnuXBd9y4BNobIPmW8HY09KvAvhVNPa7FEIIF7Al0M8C1bL9XDXzWG5lIpVSbkBpjJejduXlbuaR9jUgsTLElAeUMYpDmY2nYmUCszuY3I2Xh2YPMHuCmwe4eRlf7t7GWGwPH3D3BQ9f8PQDD3/w9AevUsZwP6/SxuQaDz8ZKSKEKBZsCfTtQF2lVE2M4B4EDLmhzGLgEeBv4EFgtb37z3Po/KbxJYQQIovVQM/sE38K+ANj2OJ0rXW4UuptIExrvRj4DvhRKXUUiMEIfSGEEE5kUx+61noZsOyGY69n+z4ZeMi+TRNCCJEf8gZPCCFKCAl0IYQoISTQhRCihJBAF0KIEkI5cnThLStW6iJwqoAfD+SGWai3Abnn24Pc8+2hMPdcXWtdPrcTLgv0wlBKhWmtQ13dDmeSe749yD3fHhx1z9LlIoQQJYQEuhBClBDFNdCnuLoBLiD3fHuQe749OOSei2UfuhBCiJsV1yd0IYQQN5BAF0KIEqJIB7pSqrtSKkIpdVQp9XIu5z2VUnMzz29VStVwQTPtyoZ7fl4pdUAptVcp9ZdSqror2mlP1u45W7kBSimtlCr2Q9xsuWel1MOZv9fhSqnZzm6jvdnwZztYKbVGKbUr8893D1e0016UUtOVUtFKqf15nFdKqc8zfz32KqVaFLpSrXWR/MJYqvcYUAvwAPYADW8o8wTwTeb3g4C5rm63E+75XsAn8/uxt8M9Z5bzB9YDW4BQV7fbCb/PdYFdQJnMnyu4ut1OuOcpwNjM7xsCJ13d7kLe811AC2B/Hud7AMsxdtJsC2wtbJ1F+Qk9a3NqrXUq8M/m1Nn1Bb7P/P4XoJNSxXp7Iav3rLVeo7VOzPxxC8YOUsWZLb/PAO8AE4BkZzbOQWy5538Bk7XWsQBa62gnt9HebLlnDZTK/L40cM6J7bM7rfV6jP0h8tIX+EEbtgABSqlKhamzKAd6bptTV8mrjNY6Hfhnc+riypZ7zm4Uxr/wxZnVe878X9FqWuulzmyYA9ny+1wPqKeU2qSU2qKU6u601jmGLff8JjBMKRWJsf/C085pmsvk9++7VU7dJFrYj1JqGBAK3O3qtjiSUsoEfAKMdHFTnM0No9vlHoz/C1uvlArRWl9xZaMcbDAwU2v9sVKqHcYuaI211hZXN6y4KMpP6PnZnBpHbk7tRLbcM0qpzsCrQB+tdYqT2uYo1u7ZH2gMrFVKncToa1xczF+M2vL7HAks1lqnaa1PAIcxAr64suWeRwHzALTWfwNeGItYlVQ2/X3Pj6Ic6FmbUyulPDBeei6+ocw/m1ODMzandjyr96yUag58ixHmxb1fFazcs9Y6TmsdqLWuobWugfHeoI/WOsw1zbULW/5sL8J4OkcpFYjRBXPciW20N1vu+TTQCUAp1QAj0C86tZXOtRgYkTnapS0Qp7U+X6gruvpNsJW3xD0wnkyOAa9mHnsb4y80GL/h84GjwDaglqvb7IR7XgVcAHZnfi12dZsdfc83lF1LMR/lYuPvs8LoajoA7AMGubrNTrjnhsAmjBEwu4Gurm5zIe93DnAeSMP4P65RwOPA49l+jydn/nrss8efa5n6L4QQJURR7nIRQgiRDxLoQghRQkigCyFECSGBLoQQJYQEuhBClBAS6EIIUUJIoAshRAnx/+nR3kPar5NRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(x, y1, linestyle='solid', linewidth=3)\n",
    "plt.plot(x, y2, ls='-.', lw=6)\n",
    "plt.plot(x, y3, 'g--')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58d0aa4b",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่งที่ใช้ในการกำหนดลักษณะเส้น สามารถศึกษาได้จาก</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html\" target=\"_blank\">https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html</a></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">และ คำสั่งที่ใช้ในการกำหนดความหนาของเส้น สามารถศึกษาได้จาก</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html\" target=\"_blank\">https://matplotlib.org/stable/api/_as_gen/matplotlib.lines.Line2D.html</a></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff523e50",
   "metadata": {},
   "source": [
    "<h2 style=\"color:#011993;font-family:'Kanit'; font-size:20px\">การกำหนดจุดของกราฟ</h2>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">การกำหนดรูปแบบจุดของกราฟสามารถทำได้โดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">marker</font> ส่วนคำสั่งสำหรับการกำหนดขนาดของจุดในกราฟสามารถทำได้ด้วยคำสั่ง <font face='Monaco' style=\"font-size:15px\">makersize</font> หรือ <font face='Monaco' style=\"font-size:15px\">ms</font> ดังตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "98d1f981",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,1,20)\n",
    "y1 = [i**2 for i in x]\n",
    "y2 = [0.75 * i**2 for i in x]\n",
    "y3 = [1.25 * i**2 for i in x]\n",
    "\n",
    "plt.plot(x, y1, linestyle='None', marker='o', markersize=4)\n",
    "plt.plot(x, y2, ls='None', marker='^', ms=2)\n",
    "plt.plot(x, y3, ls='None', marker='d', ms=6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a4cc575",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">จากตัวอย่างเราได้ปรับจำนวนจุดในน้อยลงเพื่อให้มองเห็นจุดได้ง่ายขึ้น</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่งที่ใช้ในการเขียนลักษณะของจุด สามารถศึกษาได้จาก</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/markers_api.html\" target=\"_blank\">https://matplotlib.org/stable/api/markers_api.html</a></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53b78076",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การปรับแต่งแกนข้อมูลโดย Matplotlib</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในหัวข้อนี้เราจะศึกษาคำสั่งที่ใช้ในการเขียนคำบรรยายใต้ภาพ และ การปรับพิสัยของแกน <font face='Monaco' style=\"font-size:15px\">x</font> และ <font face='Monaco' style=\"font-size:15px\">y</font> ดังตาราง</p>\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img width=600 src=\"https://indico.narit.or.th/event/229/images/1299-table-1.png\">\n",
    "    <figcaption>คำสั่งที่ใช้การปรับแกน</figcaption>\n",
    "  </center>\n",
    "</figure><br />\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">title</font> ใช้ในการเขียนคำบรรยายกราฟ คำสั่ง <font face='Monaco' style=\"font-size:15px\">xtitle</font> และ <font face='Monaco' style=\"font-size:15px\">ytitle</font> ใช้ในการเขียนคำบรรยายแกน <font face='Monaco' style=\"font-size:15px\">x</font> และ <font face='Monaco' style=\"font-size:15px\">y</font> ตามลำดับ ส่วนพิสัยของแกน <font face='Monaco' style=\"font-size:15px\">x</font> และ แกน <font face='Monaco' style=\"font-size:15px\">y</font> สามารถทำได้โดยผ่านคำสั่ง <font face='Monaco' style=\"font-size:15px\">xlim</font> และ <font face='Monaco' style=\"font-size:15px\">ylim</font></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างการใช้งานคำสั่งที่เกี่ยวข้องกับแกน</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "135cc57d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0,1,100)\n",
    "y1 = [i**2 for i in x]\n",
    "y2 = [0.75 * i**2 for i in x]\n",
    "y3 = [1.25 * i**2 for i in x]\n",
    "\n",
    "plt.plot(x, y1, label='x**2')\n",
    "plt.plot(x, y2, label='0.75 * x**2')\n",
    "plt.plot(x, y3, label='1.25 * x**2')\n",
    "plt.title('Title')\n",
    "plt.xlabel('x')\n",
    "plt.xlabel('f(x)')\n",
    "plt.xlim([0, 1.5])\n",
    "plt.ylim([0, 1.5])\n",
    "plt.legend(loc=0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9970683",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">legend</font> เป็นคำสั่งที่เราสามารถแทรกคำอธิบายกราฟในตารางได้โดยดึงข้อความที่เราใส่ไว้ใน <font face='Monaco' style=\"font-size:15px\">label</font> ของกราฟแต่ละตัวมาแสดง โดยที่เราสามารถเลือกตำแหน่งในการว่าง <font face='Monaco' style=\"font-size:15px\">legend</font> โดยกำหนดค่า  <font face='Monaco' style=\"font-size:15px\">loc</font> โดยที่ค่าของ <font face='Monaco' style=\"font-size:15px\">loc</font> แทนจำนวนเต็มตั้งแต่ 0 ถึง 10</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่ง <font face='Monaco' style=\"font-size:15px\">legend</font> สามารถศึกษาเพิ่มเติมได้ที่</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/legend_api.html\" target=\"_blank\">https://matplotlib.org/stable/api/legend_api.html</a></p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9ed370b",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การสร้างกราฟสองมิติ และ color map โดย Matplotlib</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในข้อหัวนี้เราศึกษาการสร้างกราฟสองมิติ คือ เป็นฟังก์ชันสองตัวแปร ที่เราสามารถเขียนในรูปของแผนภาพสี (color map) โดยที่คำสั่งที่สามารถใช้ได้มีดังนี้</p><br />"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a57f871c",
   "metadata": {},
   "source": [
    "<figure>\n",
    "  <center>\n",
    "    <img width=600 src=\"https://indico.narit.or.th/event/229/images/1300-table-2.png\">\n",
    "    <figcaption>คำสั่งที่ใช้ในการพลอตกราฟสองมิติ</figcaption>\n",
    "  </center>\n",
    "</figure><br />"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5e90027",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">โดยที่ คำสั่ง <font face='Monaco' style=\"font-size:15px\">imshow</font> เป็นคำสั่งที่ใช้พลอตแผนภาพสี ส่วน <font face='Monaco' style=\"font-size:15px\">colorbar</font> เป็นคำสั่งที่ใช้แสดงแถบสี ตัวอย่าง</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "514d0124",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.imshow(np.random.random((100, 100)))\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbab0df3",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">จากตัวอย่างเราสุ่มค่าในตาราง 2 x 2 มิติแล้วนำค่าที่ได้มาสร้างเป็นแผนภาพสี โดยผ่านคำสั่ง <font face='Monaco' style=\"font-size:15px\">random</font> ในสับโมดุล <font face='Monaco' style=\"font-size:15px\">random</font> ของ <font face='Monaco' style=\"font-size:15px\">numpy</font></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับคำสั่ง <font face='Monaco' style=\"font-size:15px\">colorbar</font> สามารถศึกษาเพิ่มเติมได้ที่</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/api/colorbar_api.html\" target=\"_blank\">https://matplotlib.org/stable/api/colorbar_api.html</a></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในตัวอย่างถัดไปเราจะใช้ keyword <font face='Monaco' style=\"font-size:15px\">cmap</font> ในการเปลี่ยน colormap</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "286b97c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(np.random.random((100, 100)), cmap='Blues')\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65084197",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">สำหรับ <font face='Monaco' style=\"font-size:15px\">colormap</font> ที่เราสามารถใช้ได้ทันที สามารถศึกษาเพิ่มเติมได้ที่</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\"><a href=\"https://matplotlib.org/stable/gallery/color/colormap_reference.html\" target=\"_blank\">https://matplotlib.org/stable/gallery/color/colormap_reference.html</a></p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ในตัวอย่างต่อไป เราจะพลอตฟังก์ชันสองตัวแปรโดยพลอตเป็นแผนภาพสี โดยการใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">mgrid</font> และ <font face='Monaco' style=\"font-size:15px\">meshgrid</font> (ตัวอย่างการใช้งานศึกษาได้ในสื่อวิดีทัศน์) ดังนี้</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "07085a81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = y = np.linspace(0, 2*np.pi, 50)\n",
    "X, Y = np.meshgrid(x, y)\n",
    "Z = (np.cos(X*2) + np.sin(Y*3))\n",
    "\n",
    "plt.imshow(Z, cmap='cool', interpolation='quadric')\n",
    "\n",
    "locs, labels = plt.xticks()\n",
    "plt.xticks(locs[1:], [' 0', ' 2$\\pi$/5', ' 4$\\pi$/5', ' 6$\\pi$/5', ' 8$\\pi$/5', ' 2$\\pi$'])\n",
    "\n",
    "locs, labels = plt.yticks()\n",
    "plt.yticks(locs[1:], [' 0', ' 2$\\pi$/5', ' 4$\\pi$/5', ' 6$\\pi$/5', ' 8$\\pi$/5', ' 2$\\pi$'])\n",
    "\n",
    "plt.colorbar()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "061b0dcc",
   "metadata": {},
   "source": [
    "<link href=\"https://fonts.googleapis.com/css?family=Athiti|Bai+Jamjuree|Chakra+Petch|Kanit|Open+Sans|Prompt|Sarabun\" rel=\"stylesheet\">\n",
    "\n",
    "<h1 style=\"color:#011993;font-family:'Kanit'; font-size:30px\">การสร้างกราฟย่อยโดย Matplotlib</h1>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่งต่อไปนี้จะเป็นคำสั่งในการสร้างกราฟย่อย รวมถึงคำสั่งที่เกี่ยวข้อง</p><br />\n",
    "\n",
    "<figure>\n",
    "  <center>\n",
    "    <img width=600 src=\"https://indico.narit.or.th/event/229/images/1301-table-3.png\">\n",
    "    <figcaption>คำสั่งที่ใช้ในการสร้างกราฟย่อย</figcaption>\n",
    "  </center>\n",
    "</figure><br />\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">เราจะใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">subplots</font> ในการสร้างแกนของแต่ละกราฟย่อย โดยที่คำสั่ง <font face='Monaco' style=\"font-size:15px\">subplots</font> เราจะระบุจำนวนกราฟย่อยเป็นจำนวนแถว (<font face='Monaco' style=\"font-size:15px\">nrows</font>) กับ จำนวนคอลัมน์ (<font face='Monaco' style=\"font-size:15px\">ncols</font>)</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างต่อไปนี้จะเป็นการสร้างกราฟย่อยโดยใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">subplots</font></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "d566f581",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x = np.linspace(0,1,100)\n",
    "y1 = [i**2 for i in x]\n",
    "y2 = [0.75 * i**2 for i in x]\n",
    "y3 = [1.25 * i**2 for i in x]\n",
    "\n",
    "fig, (ax0, ax1, ax2) = plt.subplots(ncols=3, figsize=(12, 4))\n",
    "fig.set_facecolor('#ffffff')\n",
    "ax0.plot(x,y1)\n",
    "ax1.plot(x,y2)\n",
    "ax2.plot(x,y3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdab3efd",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">subplots</font> จะคืนค่ามาสองค่า คือ object ที่ใช้แทนกราฟใหญ่ และตารางที่เก็บแกนของกราฟย่อย ในตัวอย่างเราจะเก็บ object ที่แทนกราฟใหญ่ไว้ที่ <font face='Monaco' style=\"font-size:15px\">fig</font> ส่วนแกนกราฟย่อยที่เหลือจะไปแทนใน <font face='Monaco' style=\"font-size:15px\">ax0</font> <font face='Monaco' style=\"font-size:15px\">ax1</font> และ <font face='Monaco' style=\"font-size:15px\">ax2</font> ซึ่งอยู่ใน Tuple ที่มีมิติเดียวกับการวางกราฟย่อย ในตัวอย่างนี้เราตั้งจำนวนแถวเท่ากับ 3</p>\n",
    "\n",
    "<p style=\"font-size: 16px; line-height:2.0;\">คำสั่ง <font face='Monaco' style=\"font-size:15px\">figsize</font> เป็นการตั้งขนาดของกราฟ ส่วนคำสั่ง <font face='Monaco' style=\"font-size:15px\">set_facecolor</font> เป็นการตั้งค่าสีพื้นของกราฟ (ในตัวอย่างเป็นสีขาว)</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "dd269fad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5cgXV1dW8WkFECv3wVwauFVRi0RNeXLauhTSlZj/11FM4evQoAKCgoADJyclwcXERIS0RaZJzWcXYdT4XM/s5w8HSROw4LUJp3zwGBgZYu3YtQkJC4OnpibFjx8Lb2xuLFy9GTEwMAODzzz/Hd999h+7du2P8+PHYuHEjZ9ET0QPll9fgy0MpGORhjUFdOYmtpTSlZoeEhMDS0hJeXl4YNGgQPv30U1haat4OYkSkOnK5gPdiEmDTthXmDdLcZev+SyIIgiB2iOYICAiAVCoVOwYRiWTBzkv4+VwO9r/aHy7WbcSO02y6VsN07XyJ6G47pNl4Y+clrBzbHaP97cSO02yN1TDe+yQijXE5pxTbz2Zjel8njWyeiYh0SXl1HT6OvQo/e3M85Wer+AUaRGkbqRARtSRBELAkJh6WpkZ4cYib2HGIiEiBtYdTUVBRg3VTA6Cn4cvW/RevQBORRvjlfC7OZZXgzeFdNXr3KiIiXZCWX4Hv/0zHsz3t4GdvLnacFscGmojUXkVNPZbvS0J3OzOM0cAxdEREukQQBLz3WyKMDfTx5vCuYsdRCjbQRKT21hxOQX55DZaGeWvdbUAiIm1z6Mr/Nroa6gbrttq50RUbaCJSa9fyK/D9H3duA/ZwsBA7DhERPUB1nQzv706Eq00bTO3jJHYcpWEDTURqSxAELP3fbcA3hnuIHYeIiBRYd+IasoqqsGSUFwz1tbfN1N4zIyKNtz/xFo4n5+OVYe6waWssdhwiInqAnOIqrD2SihE+HdHPTbt3lmYDTURqqbpOhvd/S4R7hzaY0ttR7DhERKTAh3uuAADeGekpchLlYwNNRGrpm6NpyC25jffCfLT6NiARkTY4kZKPffE3MW+gK+wsTMSOo3T8ViIitZNVWIVvjqVhVPfO6N3FUuw4RET0ALX1ciyNSYCjpQlm93cRO45KsIEmIrXz/u4EGOhJsDBUO9cPJSLSJt//mY60/EosGeUFY0N9seOoBBtoIlIrBxNv4eCVPLw8xA2dzFqLHYeIiB7gesltfHkoBUM9O2Bw1w5ix1EZNtBEpDaq62R4b3cCXG3aYHpfZ7HjEBGRAh/uuQKZXMCSUV5iR1EpNtBEpDa+OZqG7KLbeD/MG0YGLE9EROrsREo+9ly+gXmDXGHfXvsnDv4bv6GISC1kFFTim2NpeMK3E/q4Wokdh4iIHqCmXoYl0XcmDkboyMTBfzMQOwARkSAIWBKTACN9PSx6QrduAxIRaaLvjl/DtYJKbJgeqDMTB/+NV6CJSHS/J9zEseR8vDrMHR3accdBIiJ1ll1UhTWH7+w4OMjDRuw4omADTUSiqqypx3u/JaJrx7aYyh0HiYjU3nu/JUBfT6LTdwzZQBORqL48lIIbpdX48GkfGHDHQSIitXbgX0uNdjbX3aVG+W1FRKJJulmG9X+kY1yAPXo6thc7DhERPUBVbT2WxiTAvUMbzHhMt5ca5SRCIhKFXC7g3V/i0dbYAG+N4I6DRETqbvWhFOSW3Mb253rDUMfvGOr22RORaHaczYY0sxgLQz1hYWokdhwiInqAqzfLsf5EOsYG2KGXM+8YsoEmIpUrqqzF8n1J6OXUHmN62okdh4iIHkAuF/Dur5fRxtgAb43wFDuOWmADTUQq99HeK6iorseyp30gkUjEjkNERA+w82wOzmQU4+0RXdGedwwBsIEmIhU7mVaInWdzENHfBe4d2oodh4iIHqCwogYf7buCXk7t8WxPe7HjqA020ESkMjX1Mrzz62XYt2+NFwe7iR2HiIgU+HDvFVTW1OPDp32gp8c7hn9jA01EKvN/x67hWn4lPnjSB62NdG/rV3UXGxsLDw8PuLq6YsWKFfc8v3HjRlhbW8PPzw9+fn5Yt26dCCmJSFX+SivArnO5eK5/F7jxjuFduIwdEalEekEl1h5JxRO+nTBQR7d+VWcymQzz5s3DgQMHYGdnh8DAQISFhcHL6+6dxsaNG4e1a9eKlJKIVKW6ToZ3f4mHo6UJXhjsKnYctcMr0ESkdIIgYOGuy2hloIfFOrz1qzqLi4uDq6srXFxcYGRkhPDwcERHR4sdi4hE8vXRNFwruHPH0NiQdwz/iw00ESndzrM5OHmtEG+P8IRNO2Ox49B95Obmwt7+nwlCdnZ2yM3Nvee4n3/+Gb6+vhgzZgyys7Pv+16RkZEICAhAQEAA8vPzlZaZiJQj5VY5vjmaiqd72KK/u7XYcdQSG2giUqrCihp8uPcKAhwtEB7IGdyabNSoUcjIyMClS5cwbNgwTJ069b7HRUREQCqVQiqVwtqaX75EmkQuF7Dwl8swbWWAd0dyzefGsIEmIqVatufODO7lo7txBrcas7W1veuKck5ODmxtbe86xtLSEq1atQIAzJo1C2fPnlVpRiJSvqgz2TiTUYx3Qj1h2aaV2HHUFhtoIlKa48n5+OV8Lp4fwBnc6i4wMBApKSlIT09HbW0toqKiEBYWdtcxN27caPh1TEwMPD15dYpIm+SVVWP5vivo7WLJXWIV4CocRKQUVbX1WPjLZbhYm2LuIM7gVncGBgZYu3YtQkJCIJPJMGPGDHh7e2Px4sUICAhAWFgYvvzyS8TExMDAwADt27fHxo0bxY5NRC1oSUwCaurl+Gh0N+4Sq0CTGuiioiIAQPv27ZUahoi0x8r9ycgpvo3tz/XmDG4NERoaitDQ0Lt+9v777zf8evny5Vi+fLmqYxGRCvyecBP74m/izeEecLYyFTuO2mt0CEdWVhbCw8NhbW2NoKAg9OrVCzY2NggPD0dGRoYKIxKRprmUU4Lv/0zHhCAH9HLmP7zVQbdu3cSOQERqqqy6Douj4+HZqR1m93MRO45GaPQK9Lhx4/DKK69gy5Yt0Ne/c/VIJpNhx44dCA8Px6lTp1QWkog0R51MjgU/X4ZVm1Z4a0RXsePolF27dt3354Ig4ObNmypOQ0Sa4uN9Scgvr0Hk5AAY6nN6XFM02kAXFBRg3Lhxd/1MX18f4eHhWLRokdKDEZFmijx+DVdulOH/JvdEO2NDsePolHHjxmHixIn3HbtYXV0tQiIiUnenrhViy+kszHzMGd3tzcWOozEabaB79uyJuXPnYurUqQ2L62dnZ+OHH35Ajx49VBaQiDRHal4FVh9KwchunRDi3VHsODrH19cXr7/+Onx8fO557uDBgyIkIiJ1Vl0nw9u7LsOhvQlee9xd7DgapdEGetOmTVi/fj2WLFnSsBuVnZ0dRo0ahZkzZ6osIBFpBrlcwFs/X0JrQ30sDfMWO45OWrVqFdq1a3ff53755RcVpyEidbfqYArSCyqxZVYQTIy4MFtzNPq7ZWRkhOeffx7PP/+8KvMQkYbafDoT0sxifPZsd1i35eL7YujXr1+jzwUEBKgwCRGpu/jcUnx34hrGBdijr6uV2HE0DkeKE9Ejyy6qwop9SejnZoVn/G0Vv4CIiERTWy/H6zsuwtLUCAtDuSHSw+D1eiJ6JIIgYOEvlyEBsJyL7xMRqb1vj6Uh6WY5vpsSADMTTvZ+GEq9Ah0bGwsPDw+4urpixYoV9z1m+/bt8PLygre3NyZMmKDMOESkBDvO5uBESgHeGtEVdhYmYschIqIHuHqzHGsOp2BU984Y5tVB7DgaS2EDvXr1apSVlUEQBMycORP+/v7Yv3+/wjeWyWSYN28e9u3bh8TERGzbtg2JiYl3HZOSkoLly5fjzz//REJCAlatWvXQJ0JEqnerrBof7E5EL+f2mBjkKHYc+p+HrdtEpN3qZXK8ufMi2hobYukoL7HjaDSFDfT333+Pdu3aYf/+/SguLsaPP/6It956S+Ebx8XFwdXVFS4uLjAyMkJ4eDiio6PvOua7777DvHnzYGFhAQCwsbF5yNMgIlUTBAHv/HIZtfVyfPyML/T0OHRDXTxs3SYi7bbuj3RczCnF0jBvWLbhZO9HobCBFgQBALB3715MnjwZ3t7eDT97kNzc3Ib1o4E7S+D9vRze35KTk5GcnIy+ffsiODgYsbGxzc1PRCL59UIuDl7JwxshHnC2MhU7Dv3Lw9ZtItJeqXnlWHkgGSHeHTDKt5PYcTSewkmEPXv2xOOPP4709HQsX74c5eXl0NNrmaHT9fX1SElJwdGjR5GTk4P+/fvj8uXLMDc3v+u4yMhIREZGAgDy8/Nb5LOJ6OHllVVjaUwiejpaYHpfZ7Hj0H8os24TkeaRyQW8vuMSTIz0sewpTvZuCQob6PXr1+PChQtwcXGBiYkJCgsLsWHDBoVvbGtri+zs7IbHOTk5sLW9e3krOzs7BAUFwdDQEM7OznB3d0dKSgoCAwPvOi4iIgIREREAuJYpkdjurLoRj+o6GT4Z4wt9Dt1QOw9bt4lIO63/4xouZJdgdbgf1+lvIY1ekkhKSgIAXLhwAQBw7do1nDt3DpmZmaivr1f4xoGBgUhJSUF6ejpqa2sRFRWFsLCwu4556qmncPToUQBAQUEBkpOT4eLi8pCnQkSqEH3hOg5euYXXH/dAF+s2Ysehf3nUuk1E2ic1rwKf7U/G414dENa9s9hxtEajV6BXrlyJyMhIvPbaa/c8J5FIcPjw4Qe/sYEB1q5di5CQEMhkMsyYMQPe3t5YvHgxAgICEBYWhpCQEOzfvx9eXl7Q19fHp59+CktLy0c/KyJSiltl1VgSkwB/B3PMeIxDN9TNo9ZtItIu9TI5Xttx8c7Qjad9OHSjBUkEDZtZEhAQAKlUKnYMIp0jCAJm/SDFH6kF2PdyP7jw6vND0bUapmvnS6ROvjmaho9jk/Dl+B68+vyQGqthCmeVLFq0CDKZrOFxWVkZpk+f3rLpiEjt7Tybg0NJeXhzeFc2z2qOdZuIrt4sxxcHkjHCpyNX3VAChQ10fX09evXqhUuXLuHAgQMIDAxEz549VZGNiNTE9ZLbeH93Ino5tcf0Pk5ixyEFWLeJdFudTI7Xd1xEW2MDLHuKQzeUQeEqHMuXL8fQoUMRFBQECwsLHD9+HK6urqrIRkRqQBAEvLnzEmRyAZ8+yw1TNAHrNpFu++pIKi7nluKbif7cMEVJFF6BPn78OF566SUsXrwYAwcOxIsvvojr16+rIhsRqYHNpzLxR2oBFoZ6wtGSG6ZoAtZtIt11OacUaw+n4im/zhjRjUM3lEXhFejXX38dO3bsgJfXnT3Td+3ahcGDBzcsl0RE2iujoBIf7U1CPzcrTAxyEDsONRHrNpFuqq6TYf72C7BsY4T3wnzEjqPVFDbQJ0+ehL6+fsPj0aNHY8CAAUoNRUTik8kFvLbjIgz0JfhkjC/H0GkQ1m0i3fTFgWSk5FVg4/RAmJkYih1HqylsoPX19bFnzx4kJCSgurq64eeLFy9WajAiEtf/HU/D2cxifDGuOzqZtRY7DjUD6zaR7jl9rRCRJ65hQpADBnrYiB1H6ykcAz1nzhz89NNPWLNmDQRBwI4dO5CZmamKbEQkkoTrpfjiQDJCu3XEU362YsehZmLdJtIt5dV1eG3HRTi0N8E7oZ5ix9EJChvov/76C5s2bYKFhQWWLFmCkydPIjk5WRXZiEgE1XUyvPrTBZibGOHDp7px6IYGYt0m0i3v/5aI6yW3sXKsH0xbKRxcQC1AYQPduvWdW7cmJia4fv06DA0NcePGDaUHIyJxfL7/KpJvVeCTMb6wMDUSOw49hIet27GxsfDw8ICrqytWrFjR6HE///wzJBIJdxgkUgP7E25ix9kcPD+wC3o6WogdR2co/GfKE088gZKSErzxxhvw9/eHRCLB7NmzVZGNiFTsr7QCrPsjHRODHDCIY+g01sPUbZlMhnnz5uHAgQOws7NDYGAgwsLCGlby+Ft5eTlWr16NoKAgZZ4CETVBXnk13tp1GV6d2uHlIe5ix9EpChvoRYsWAQCeeeYZPPHEE6iuroaZmZnSgxGRapVW1eG17RfhZGmKd0ZyDJ0me5i6HRcXB1dXV7i4uAAAwsPDER0dfU8DvWjRIixYsACffvqpcsITUZMIgoAFOy+hsqYeq8P9YGSgcFABtaBm/W63atWKzTORlloUHY+88hqsGucHEyOOodMWTa3bubm5sLe3b3hsZ2eH3Nzcu445d+4csrOzMXLkyBbPSUTNs/l0Fo5czcfbI7rCrUNbsePoHH5LEhGiL+Qi5uJ1zB/mju725mLHITUkl8sxf/58bNy4UeGxkZGRiIyMBADk5+crORmR7knLr8CHexLRz80KU3o7iR1HJz3wCrQgCMjOzlZVFiISQU5xFd79JR7+DuaYO7CL2HHoET1s3ba1tb3rdTk5ObC1/WcJw/LycsTHx2PgwIFwcnLCqVOnEBYWdt+JhBEREZBKpZBKpbC2tn64EyGi+6qtl+PlqPMwNtTHZ892h54eV0oSwwMbaIlEgtDQUFVlISIVk8kFzP/pIgQAq8b1gIE+x9Bpuoet24GBgUhJSUF6ejpqa2sRFRWFsLCwhufNzMxQUFCAjIwMZGRkIDg4GDExMQgICGjJ+ESkwMoDyYjPLcOK0b7o0M5Y7Dg6S+G3pb+/P86cOaOKLESkYt8eS0NcRhHef9IbDpYmYsehFvIwddvAwABr165FSEgIPD09MXbsWHh7e2Px4sWIiYlRUlIiao6/0grwf8fTML6XPYb7dBQ7jk6TCIIgPOiArl27IjU1FY6OjjA1NYUgCJBIJLh06ZKqMt4lICCAa48StYCL2SV45pu/MNynI9aM78ENU1REFTVMneo2azZRyyipqsWI1SfQ2lAfu196jJO9VaSxGqbwd//3339XSiAiEk9FTT1eijoPm7atuNugFmLdJtIugiDgrZ8vI7+8Brvm9mHzrAYU/gk4Ojri4sWLOHHiBACgX79+6N69u9KDEZHyLI6OR3ZRFX56rjfMTAzFjkMtjHWbSLtEnclGbMJNvD2iK3ztzMWOQ2jCGOjVq1dj4sSJyMvLQ15eHiZNmoQ1a9aoIhsRKUH0hVzsOpeLFwe7IdCpvdhxSAlYt4m0R2peOd77LQGPuVphdj8XsePQ/ygcA+3r64uTJ0/C1NQUAFBZWYnevXtzDDSRBsoqrMLIL0/Ao2NbREUEc9UNEaiihqlT3WbNJnp41XUyPP31X7hVVo3Yl/vBhqtuqNxDj4EWBAH6+voNj/X19aGg5yYiNVQnk+PFqPOQSIBV4X5snrUY6zaRdlixLwlXbpRh/dQANs9qRmEDPX36dAQFBeHpp58GAPz666+YOXOm0oMRUcv6bP9VXMwuwTcT/WFnwSXrtBnrNpHmO5B4Cxv/ysCMvs4Y4tlB7Dj0H4020Onp6XB2dsb8+fMxcOBA/PHHHwCADRs2oEePHioLSESP7lhyPv7v2DVMCHLAiG6dxI5DSsK6TaQdbpTexhs7L8K7czssGOEhdhy6j0Yb6DFjxuDs2bMYMmQIDh06BH9/f1XmIqIWkldejde2X4BHh7ZY/ISX2HFIiVi3iTRfvUyOl6MuoLZejjXje6CVgb7iF5HKNdpAy+VyfPTRR0hOTsbKlSvveX7+/PlKDUZEj04mF/BK1AVU1NRj6+xgGBuyEGsz1m0izffloRTEpRdh5djucLFuI3YcakSjs4iioqKgr6+P+vp6lJeX3/MfEam/r4+k4q+0Qrwf5gP3Dm3FjkNKxrpNpNn+TC3AmiOpGNPTDqP97cSOQw/Q6BVoDw8PLFiwAL6+vhgxYoQqMxFRCzh9rRBfHEzGU36d8WwAC7EuYN0m0lz55TV45acLcLEyxftPeosdhxRQuAoHizCR5imsqMFLUefhaGmKZU9zq25dw7pNpFlkcgGv/nQBZbfr8OPMXtyqWwPwT4hIy8jlAl7dfhHFVXX4flog2rTiX3MiInW29nAq/kgtwIrR3dC1Yzux41ATcCcFIi3z9dFUHE/Ox9JR3vDubCZ2HCIieoC/Uguw6lAynu5hi3GB9mLHoSZq9NLUrl27HvjC0aNHt3gYIno0J9MKsfJAMp7064zxvViIdQ3rNpFmySuvxktRd8Y9L3vKh8PtNEijDfRvv/3W6IskEgkLMZGaySurxovbzsPJyhQfctyzTmLdJtIc9TI5Xtx6HhU1ddgyKwimHG6nURr909qwYYMqcxDRI6iXyfHitn8KMcc96ybWbSLNsfJAMk7/b71nj45cZlTTKBwDfevWLcycObNhVndiYiLWr1+v9GBE1HR/F+IPn+rGQkys20Rq7tCVW/j6aBrG97Lnes8aSmEDPW3aNISEhOD69esAAHd3d6xatUrZuYioif5diJ/pyUJMrNtE6iy7qArzt1+Ed+d2WDKK6z1rKoUNdEFBAcaOHQs9vTuHGhgYQF+f2wETqYOswiq88tMFFmK6C+s2kXqqrpPh+S1nIRcEfD3RH8aG/HupqRQOlDQ1NUVhYWHDhKRTp07BzIxLYxGJrbpOhjmbz0JPIsG3k3qyEFMD1m0i9bQ0JgHxuWVYNyUAjpamYsehR6CwgV65ciXCwsKQlpaGvn37Ij8/Hzt37lRFNiJqhCAIWPRrPK7cLMP3UwNh395E7EikRli3idTP9jPZiDqTjXmDumCoVwex49AjUthA+/v749ixY7h69SoEQYCHhwcMDQ1VkY2IGrEtLhs7zubgpSFuGNTVRuw4pGZYt4nUy+WcUrwbHY++rpaYP8xD7DjUAhQ20NXV1fj666/xxx9/QCKRoF+/fpgzZw6MjY1VkY+I/uNcVjGWxMRjoIc1Xh7iJnYcUkOs20Tqo6iyFnM2n4V1m1b4MrwH9PW4Rr82UNhAT5kyBW3btsWLL74IANi6dSsmT56MHTt2KD0cEd0tv7wGczefQ0czY6wa58dCTPfFuk2kHmRyAS9tO4/8ihrsnNMblm1aiR2JWojCBjo+Ph6JiYkNjwcNGgQvLy+lhiKie9XJ5Hhh6zkUV9Vi19w+MDcxEjsSqSnWbSL18OnvV/FHagE+ecYXvnbmYsehFqRwGTt/f3+cOnWq4fHp06cREBCg1FBEdK8P91zB6fQirHimG7w7c0UFahzrNpH4dl+6jm+PpWFCkAPGBtqLHYdaWKMNdLdu3eDr64uzZ8+iT58+cHJygrOzM3r37g2pVNqkN4+NjYWHhwdcXV2xYsWKRo/7+eefIZFImvy+RLpmhzQbG//KwIy+zni6BzdLoft71LqtqGZ/++236NatG/z8/PDYY4/ddZWbiP5x5UYZ3thxCT0dLbCUa/RrpUaHcOzevfuR3lgmk2HevHk4cOAA7OzsEBgYiLCwsHtuI5aXl2P16tUICgp6pM8j0laXckrwzq/x6O1iiYWhXcWOQ2rsUep2U2r2hAkTMGfOHABATEwM5s+fj9jY2EfOTaRNSqpq8dyPZ9GutQG+megPIwOFN/tJAzX6p+ro6HjXf61bt4ZEImn4T5G4uDi4urrCxcUFRkZGCA8PR3R09D3HLVq0CAsWLODscKL7yCuvxnM/3pm9vXZCDxjosxBT4x6lbjelZrdr167h15WVlU36LiDSJfUyOV7cdh43Sm/jm0k9YdOOvY22UvhtHBMTAzc3Nzg7O2PAgAFwcnLCiBEjFL5xbm4u7O3/GfNjZ2eH3Nzcu445d+4csrOzMXLkyIeITqTdaupleH7znUmDkVN6cvY2NdnD1O2m1GwA+Oqrr9ClSxe8+eab+PLLL1s8O5EmW7EvCSdSCvDhU93g72AhdhxSIoUN9KJFi3Dq1Cm4u7sjPT0dhw4dQnBw8CN/sFwux/z58/H5558rPDYyMhIBAQEICAhAfn7+I382kboTBAFLohNwNrMYnz3bnZMGqVmUVbcBYN68eUhLS8PHH3+MZcuW3fcY1mzSRT+fzcG6P9IxrY8TJw3qAIUNtKGhISwtLSGXyyGXyzFo0KAmTUaxtbVFdnZ2w+OcnBzY2to2PC4vL0d8fDwGDhwIJycnnDp1CmFhYfd974iICEilUkilUlhbWzf13Ig01o+nMhu2fH3Ct7PYcUjDPEzdVlSz/ys8PBy//vrrfZ9jzSZdcz6rGG//chl9uljinZGeYschFVC4DrS5uTkqKirQv39/TJw4ETY2NjA1NVX4xoGBgUhJSUF6ejpsbW0RFRWFrVu3NjxvZmaGgoKChscDBw7EZ599xqWWSOf9mVqA935LxFBPG7zGLV/pITxM3VZUswEgJSUFbm53dr/cs2dPw6+JdNmN0tuI+PEsOrYzxlcT/GHIuSo6QeGfcnR0NFq3bo0vvvgCw4cPR5cuXfDbb78pfGMDAwOsXbsWISEh8PT0xNixY+Ht7Y3FixcjJiamRcITaZv0gkrM3XIOrtZtsCq8B/S40yA9hIep202p2WvXroW3tzf8/PywcuVK/PDDD6o4HSK1dbtWhohNZ3G7VoZ1UwNgYcoNrnSFRBAEQewQzREQEMD1okkrlVXX4emv/kRRZS1iXngM9u1NxI5ESqBrNUzXzpd0hyAIeHHbeey5fAPrpgRgiGcHsSOREjRWwxodwtG2bdv7LlEkCAIkEgnKyspaNiGRDquXyTFvyzlkFlZh86wgNs/0UFi3iVRn9aEU7L50A2+N6MrmWQc12kCXl5erMgeRTvtgdyJOpBTg42e6IdjFUuw4pKFYt4lUI+bidaw6mIJn/O3wXH8XseOQCDjSnUhkP57MwA8nMzG7nzPGBTqIHYeIiB7gfFYxXt9xEb2c2uOj0T7cUEhHsYEmEtGx5Hws/S0Rg7va4K0RXPqIiEid5RRXYfams+jQrhW+ndwTrQz0xY5EIlG4jB0RKcfVm+WYt+Uc3Du0xZfje0CfK24QEamtsuo6zNwoRU29DFERQWjPFTd0msIr0GvWrEFxcbEqshDpjLzyaszYeAYmRvr4floA2rTiv2Wp5bBuE7WsepkcL2w9j7T8Cnw7qSdcbdqKHYlEprCBvnXrFgIDAzF27FjExsZCw1a9I1I7t2tlmP2DFEWVtVg/NRCdzFqLHYm0DOs2UcsRBAFLYhJwPDkfHzzlg76uVmJHIjWgsIFetmwZUlJSMHPmTGzcuBFubm5YuHAh0tLSVJGPSKvI5AJejjqPS7mlWB3uh252ZmJHIi3Euk3Ucr47cQ1bTmfhuQEuGN+LE73pjiZNIpRIJOjYsSM6duwIAwMDFBcXY8yYMXjzzTeVnY9Iq3y45wr2J97Ckie88Lh3R7HjkBZj3SZ6dHsu3cBHe5Mw0rcTFoR0FTsOqRGFAy9Xr16NTZs2wcrKCrNmzcKnn34KQ0NDyOVyuLm54ZNPPlFFTiKNt+HPdHz/Zzpm9HXGtL7OYschLca6TfTozmYW4dXtFxDgaIHPn+0OPU70pn9R2EAXFRVh165dcHR0vOvnenp62L17t9KCEWmTfZdv4P3diXjcqwPeGcnl6ki5WLeJHk1afgVm/iCFrXlrRE4JgLEhl6ujuylsoN97771Gn/P0ZCNApIg0owgv/3QBPezNuVwdqQTrNtHDyyuvxtTv42CgJ8EP03txuTq6L66dRaREqXkVmLVJCjvz1lg/NZBXMYiI1FhFTT1mbDyDwopa/PRcMBwsTcSORGqKDTSRktwq+/sqhh5+mNELFryKQUSktmrr5Xh+81lcuVGO76b0hK+dudiRSI1xK28iJSi9XYep38ehpKoWG6cHwr49r2IQEakruVzAmzsv4kRKAZaP7obBXTuIHYnUHK9AE7Ww6joZIjZJkZZfge+nBcLHlms9ExGps49jk/Drhet4I8QDYwPsxY5DGoANNFEL+nujlNPpRVgd7od+btZiRyIiogeIPJ6G/zt+DVN6O2LuwC5ixyENwSEcRC1EEAS8++tl/J5wC4uf8MKTfrZiRyIiogfYIc3GR3uT8IRvJywZ5Q2JhKskUdOwgSZqIZ/vT8a2uGy8MMgVMx7jRilEROrsYOItvLXrMvq5WWHlWD8uMUrNwgaaqAWsO3ENa4+kYnwve7z2uLvYcYiI6AFOXSvEvK3n4NO5Hb6d1BNGBmyHqHn4fwzRI9p+JhvL9lzByG6dsOypbrwFSESkxi7nlGLWD1I4tDfBhum9YNqK08Go+dhAEz2C2PgbeGvXJfR3t8YX43gLkIhInaXmVWDqhjiYtTbEjzODuMsgPTQ20EQP6ejVPLy47Tx6OFjg20n+vAVIRKTGsouqMGndaehJJNgyKwgdzYzFjkQajN/4RA/h1LVCPPfjWbh3aIvvpwXCxIi3AImI1NXN0mpMWHcKt+tk2DyrF5ysTMWORBqODTRRM13ILsHMjWdg394Em2b0gllrQ7EjERFRIworajBx3SkUV9Zh04xe6NqxndiRSAuwgSZqhoTrpZiy/jTatzHC5plBsGzTSuxIRETUiJKqWkxaH4fckttYPzUA3e3NxY5EWoL3nYma6OrNckxadxptWhlg66xgjp8jIlJjZdV1mPJ9HNLyK7B+agCCXCzFjkRahFegiZogLb8CE9edhqG+HrbODoZ9exOxIxG1uNjYWHh4eMDV1RUrVqy45/mVK1fCy8sLvr6+GDJkCDIzM0VISaRYRU09pm84gys3yvDNRH/0c7MWOxJpGTbQRAqkF1RifOQpAAK2zg7i5BPSSjKZDPPmzcO+ffuQmJiIbdu2ITEx8a5jevToAalUikuXLmHMmDF48803RUpL1LjKmnrM2HAGF7JLsGZ8Dwzx7CB2JNJCbKCJHiCz8E7zXC8XsGVWMFxt2oodiUgp4uLi4OrqChcXFxgZGSE8PBzR0dF3HTNo0CCYmNy5+xIcHIycnBwxohI1qqq2HjM2noE0swirw/0w3KeT2JFIS7GBJmpEVmEVxkeeQk29DFtmBcGjI5tn0l65ubmwt7dveGxnZ4fc3NxGj1+/fj1GjBihimhETXK7VoaZG6U4k1GEL8b54QnfzmJHIi3GSYRE9/H3leequjvNs2cnLntE9LfNmzdDKpXi2LFj930+MjISkZGRAID8/HxVRiMdVVVbj5kbpTiVXojPn+2OJ/1sxY5EWo5XoIn+I6OgEuGRdxbc3zorGN6dzcSORKR0tra2yM7Obnick5MDW9t7m5CDBw/iww8/RExMDFq1uv8yjhEREZBKpZBKpbC25uQtUq6q2jsTBk+nF2Ll2O4Y7W8ndiTSAWygif7lWn4FwiNPoaZejq2zg+HVmVeeSTcEBgYiJSUF6enpqK2tRVRUFMLCwu465vz583juuecQExMDGxsbkZIS/aOiph7TNpxpGLbxdA82z6QabKCJ/iflVjnGRZ5CnUyOrbM5bIN0i4GBAdauXYuQkBB4enpi7Nix8Pb2xuLFixETEwMAeOONN1BRUYFnn30Wfn5+9zTYRKpUVl2HKetP42xmMVaF9+CwDVIpjoEmApB0swwTvzsNPT0JoiKC4daBEwZJ94SGhiI0NPSun73//vsNvz548KCqIxHdV2lVHaZ8fxoJ18uwdnwPjOjG1TZItdhAk867lFOCKd/HwdhAH1tnB8HFuo3YkYiIqBEFFTWYvD4OaXkV+HZSTwz14jrPpHpsoEmnnckowvQNZ2BhaogtM4PhYMkdBomI1NXN0mpMXHcKuSW38d3UAAxw5yRVEgcbaNJZf6QUYPYmKTqZG2PLrCB0MmstdiQiImpEdlEVJq47jcKKGvwwvReCXCzFjkQ6jA006aTY+Bt4adsFuFib4seZQbBue//luIiISHwpt8oxaf1pVNfJsWV2MPzszcWORDqODTTpnB3SbCz4+RL87M2xYVovmJkYih2JiIgacTG7BNM2xMFAXw8/PReMrh25QhKJjw006ZR1J65h2Z4r6Odmhf+b3BMmRvwrQESkrv5KvTPUrn0bI2yeGQRHS1OxIxEBYANNOkIQBHzy+1V8czQNod064otxfmhloC92LCIiasS+yzfwctQFOFmZYNOMIHQ0MxY7ElEDNtCk9eplcrzzSzx+kmZjYpAD3n/SB/p6ErFjERFRI7aczsS7v8bD38EC66cGwNzESOxIRHdhA01a7XatDC9sPYdDSXl4aYgbXh3qBomEzTMRkToSBAGrDqZg9aEUDPKwxtcTe6K1Ee8WkvpR6lbesbGx8PDwgKurK1asWHHP8ytXroSXlxd8fX0xZMgQZGZmKjMO6ZiiylpMWHcKh6/m4YOnfDB/mDubZyIiNVUvk2PhL5ex+lAKxvS0Q+SUADbPpLaU1kDLZDLMmzcP+/btQ2JiIrZt24bExMS7junRowekUikuXbqEMWPG4M0331RWHNIxWYVVGPPtX0i4XoZvJvbE5GBHsSMREVEjqmrrMWfzWWyLy8YLg1zx6RhfGOor9Rof0SNR2v+dcXFxcHV1hYuLC4yMjBAeHo7o6Oi7jhk0aBBMTO7s/BYcHIycnBxlxSEdcjG7BKO/+ROFFbXYMisIw306ih2JiIgakV9eg/DIUziclIcPnvTG6yEevFtIak9pY6Bzc3Nhb2/f8NjOzg6nT59u9Pj169djxIgRyopDOuJg4i28uO08rNoa4afpvdDFuo3YkYiIqBGpeRWYtiEOhRW1iJwcgKFeHcSORNQkajGJcPPmzZBKpTh27Nh9n4+MjERkZCQAID8/X5XRSEMIgoANf2Zg2Z5EdLM1w7qpgdxdkIhIjf2VVoA5P56FkYEeoiKC0Z27C5IGUVoDbWtri+zs7IbHOTk5sLW1vee4gwcP4sMPP8SxY8fQqtX9G56IiAhEREQAAAICApQTmDRWvUyO93cnYtPJTIR4d8CqcT048YSISI3tkGbj7V2X4Wxliu+nBcK+vYnYkYiaRWkNdGBgIFJSUpCeng5bW1tERUVh69atdx1z/vx5PPfcc4iNjYWNjY2yopAWK6uuw0vbzuPo1XxE9HfBW8O7Qo9rPBMRqSW5XMBn+6/i66NpeMzVCl9N9IdZa0OxYxE1m9IaaAMDA6xduxYhISGQyWSYMWMGvL29sXjxYgQEBCAsLAxvvPEGKioq8OyzzwIAHBwcEBMTo6xIpGUyCysx8wcpMgoq8dHT3TAhyEHsSERE1IjKmnq8+tMF7E+8hfG9HPD+k95caYM0llLHQIeGhiI0NPSun73//vsNvz548KAyP5602KlrhXh+81nIBWDTzF7o08VK7EhERNSI3JLbmP2DFEk3y7BklBem9XHiShuk0dRiEiFRc/x4KhPvxSTAwdIE66cGwtnKVOxIRETUiLj0Ijy/+SxqZXJ8Py0QAz04ZJM0Hxto0hi19XIs/S0BW09nYZCHNVaP74F2xhw7R0SkrraezsLi6Hg4tDfBd1MDuLQoaQ020KQR8sqrMXfzOUgzi/HcABe8GdIV+pwsSESklmrqZVgak4htcVkY4G6NL8f34GRB0ipsoEntncsqxvObz6Lsdj2+HN8DYd07ix2JiIgacausGnM2n8X5rBLMHdgFrz3uwQsepHXYQJPaEgQBm09l4v3diehk1hq75vaCZ6d2YsciIqJGnLpWiBe2nkdVbT2+nuiP0G6dxI5EpBRsoEkt3a6VYeEvl/HL+VwM8rDGF+P8YG5iJHYsIiK6D0EQsO5EOlbEJsGxvQm2zg6Ce4e2YsciUho20KR20vIrMG/LOVy9VY75w9zxwiBXbo5CRKSmSm/XYcHOS4hNuIkRPh3xyRhftOUEb9JybKBJrcRcvI63f76EVob62Di9Fwa4W4sdiYiIGhGfW4q5W87hesltvDvSEzMfc+b6zqQT2ECTWqiuk+H93YnYejoLAY4WWDOhBzqZtRY7FhER3YcgCPjxVCaW7b4CyzZG+Om53ujpaCF2LCKV4R6aJLrUvHI89dWf2Ho6C8/1d8G2iGA2z0QiiI2NhYeHB1xdXbFixYp7nj9+/Dj8/f1hYGCAnTt3ipCQ1EFpVR3mbD6LxdEJ6ONqiT0v9WPzTDqHV6BJNIIgYLs0G0tjEmFipI+N07lDFZFYZDIZ5s2bhwMHDsDOzg6BgYEICwuDl5dXwzEODg7YuHEjPvvsMxGTkpikGUV4OeoCbpVV453QO0M2OEeFdBEbaBJFaVUd3v7lEvZevok+XSzxxTg/dGhnLHYsIp0VFxcHV1dXuLi4AADCw8MRHR19VwPt5OQEANDT481LXVMvk2PN4VSsOZwCOwsT7Hy+D/zszcWORSQaNtCkcn+lFeD17ReRV16Dt0d0xex+LryCQSSy3Nxc2NvbNzy2s7PD6dOnRUxE6iKrsAqvbr+As5nFGO1vi/fCvLnKBuk8NtCkMtV1Mny+/yrW/ZEOJ0tT/Px8H3TnFQwirRMZGYnIyEgAQH5+vshp6GEJgoAd0hy891sC9PQkWB3uhyf9bMWORaQW2ECTSsTnluK17Rdx9VY5JgU7YGGoJ0yM+L8fkbqwtbVFdnZ2w+OcnBzY2j5csxQREYGIiAgAQEBAQIvkI9XKL6/Bwl8u40DiLQS7tMfnY/1ga87J3UR/YwdDSlUnk+PrI2lYczgF7U2NsGFaIAZ15URBInUTGBiIlJQUpKenw9bWFlFRUdi6davYsUgEey7dwLu/XkZlrYwTBYkawQaalObKjTK8sfMi4nPL8KRfZ7wX5s3tuInUlIGBAdauXYuQkBDIZDLMmDED3t7eWLx4MQICAhAWFoYzZ87g6aefRnFxMX777TcsWbIECQkJYkenFlJYUYPFMQnYc+kGfO3MsHJsd7jacDtuovthA00t7u+rzmuPpMCstSG+meiPEd06iR2LiBQIDQ1FaGjoXT97//33G34dGBiInJwcVcciJRMEAbsv3cCSmASUV9fh9cfdMWdAFxjoc7UVosawgaYWdT6rGG/vuoykm+V40q8zlozyRntTXnUmIlJHN0pvY9GvCTh45Ra625nh02eD4d6BV52JFGEDTS2ioqYen++/io1/ZaBDW2N8NyUAw7w6iB2LiIjuQy4XsOV0Jj6OvYp6uRwLQ7tiRl9nXnUmaiI20PRIBEHA7wm38N5vCbhRWo3JwY54c7gH1wglIlJTidfLsPCXy7iQXYLHXK3w0dPd4GBpInYsIo3CBpoeWnZRFd77LQEHr+Sha8e2WDvBHz0dLcSORURE91FRU49VB5Kx4a8MmLc2xBfjuuMpP1tIJFxhg6i52EBTs1XXyfB/x67h66Op0NeTYGFoV0zv6wxD3vojIlI7giAg5uJ1fLjnCvIrahAeaI8Fw7tyVSSiR8AGmppMEAQcSLyFZXuuIKuoCiN9O+HdkZ7oZMbF9YmI1FHi9TK891sCTqcXoZutGf5vck/0cOCdQqJHxQaamiT5Vjk+2J2IEykFcLNpg80zg/CYm5XYsYiI6D4KK2rw+YFkRMVlway1IT582gfhgQ7Q54YoRC2CDTQ9UEFFDb44kIxtcVlo08oAS0d5YVKwI2dqExGpoeo6GX74KwNrD6eiqk6GqX2c8MoQd5iZcGI3UUtiA033VVVbjw1/ZuCbo2morpNhSm8nvDzEDRZc05mISO3I5QJ+u3Qdn+2/iuyi2xjS1QZvh3blToJESsIGmu5SL5Njx9kcfHEgGXnlNRjm1QFvjeiKLtZtxI5GRET/IQgC/kwtxIrYK4jPLYNnp3bYPNOXQ+yIlIwNNAH45+rFFweSkVFYhZ6OFvh6oj8CnNqLHY2IiO7jbGYRPv39Kk5dK4KteWt8Ma47nuxuCz2OcyZSOjbQOk4uF7A/8SZWHUxB0s1ydO3YFt9NCcBQTxuuDUpEpIYuZpdg1cFkHLmaD6s2RlgyygsTghzQykBf7GhEOoMNtI76b+PsYmWK1eF+GOXbmVcviIjU0MXsEnx5KAWHkvJgbmKIN0I8ML2vE0yM+FVOpGr8W6dj6mVy7Ll8A2sPpyIlrwLOVqb4Ylx3jPLtzJU1iIjUUFx6EdYcTsGJlAKYtTbE64+7Y2ofJ7Q15soaRGJhA60jbtfKsPNsNr47kY6soiq4d2iD1eF+GNmtExtnIiI1I5cLOJSUh2+PpeFsZjGs2hjhrRFdMSnYEW1a8aubSGz8W6jl8strsPlUJn48lYmiylr42ZvjnZGeGObZgUM1iIjUTHWdDL+cz8X6P9KRmlcBO4vWWDrKC+MCHdDaiGOcidQFG2gtlXi9DBv/Ssev56+jVibHkK42eG5AFwQ6WXByIBGRmrlZWo0tpzOx5XQWiipr4d25He8SEqkxNtBapLZejt8TbmLTyQycyShGa0N9jA20w/S+zlzHmYhIzQiCgLj0Imw6lYnf429CJggY0rUDZvVzRpBze17sIFJjbKC1QGZhJbbFZWPn2WwUVNTC0dIE7470xLM97bl9KxGRmimpqsWuc7nYGpeF1LwKmLU2xIzHnDEpyBEOliZixyOiJmADraFu18qwL/4GtkuzcepaEfT1JBjS1QYTghzQ382a45uJiNSITC7gz9QCbJdmY3/CLdTK5PCzN8enY3zxhG9njm8m0jBsoDWITC7g9LVC7Dqfi32Xb6CyVgZHSxO8EeKBZ/zt0NHMWOyIRET0L1dvlmPX+Rz8ej4Xt8pqYG5iiAlBDhgbYA+vzu3EjkdED4kNtJoTBAHns0uw++IN7Ll8HbfKatCmlQFG+nbCaH87jpMjIlIzGQWV2H3pOn67eANXb5XDQE+CAe7WWPSELYZ6doCxIa82E2k6NtBqqF4mx9nMYuyLv4nfE27iRmk1jAz0MNDdGqO6d8YwLxZgIiJ1IQgCUvIqEBt/E/vib+LKjTIAQKCTBd4L88YTvp1g2aaVyCmJqCWxgVYTpbfr8GdqAQ5euYUjSXkorqqDkYEe+rtZ4/XHPTDMuwPacdcpIiK1UFMvgzSjGIeT8nAg8RayiqoAAD0dLfDuSE+M6NYJtuatRU5JRMrCBlok9TI5LueW4s/UAhxPLsDZrGLI5ALMWhticFcbDPG0wUAPG+44RUSkBgRBwLWCyoaa/VdaAapqZTAy0EPfLpZ4boALhnp2QId2nItCpAvYnalInUyOxOtlOJ1eiNPXihCXUYTy6noAgHfndpgzwAUDPWzQw96ci+YTEYns74Y5Lr0Ip68V4nR6EW6UVgMA7CxaY7S/LQa626B3F0uY8kIHkc7h33olEAQB10urcSm7BBdzSnE+qxgXc0pQXScHALhYmeIJ307o62qF3i6WHBtHRCSykqpaXMopxaWcEpzPKsG5rGIUV9UBAKzatEKQS3v07WKFx1ytuFYzESm3gY6NjcXLL78MmUyGWbNm4a233rrr+ZqaGkyZMgVnz56FpaUlfvrpJzg5OSkzUou7XStDWn4Fkm+V4+rNciTeKEPi9TIUVtYCAAz0JPDu3A7jezmgp6MFejm1hw1v8RGRGtKFml0nkyOzsAopt8px9VY5Eq+XIfFGGXKKbzcc42JtimFeHeDvYIFA5/ZwsTLlakdEdBelNdAymQzz5s3DgQMHYGdnh8DAQISFhcHLy6vhmPXr18PCwgKpqamIiorCggUL8NNPPykr0kORywUUVNbgZmk1copvI6e4CllFVcgoqEJ6QSWul96GINw51khfD+4d22CIpw28O5vB184Mnp3accUMIlJ72lKzBUFA6e063CyrRm7xbeQU30Z2URUyCiuRXlCJrKIq1MnuFG2JBHC2MoWfvTkmBDmgu505fGzNYNaaE7aJ6MGU1kDHxcXB1dUVLi4uAIDw8HBER0ffVYyjo6OxdOlSAMCYMWPwwgsvQBCEFv+X/tWb5SiuqoVcECCX37kCUVMvR029DFW1MlTW1KOiph4lVXUou12HoqpaFFbUoqCiBvnlNaiXC3e9n1lrQzhZmiDQyQLOVvZw69AG7h3awNHSFIYcv0xEGkidanZuyW3kFFVBJggQhH9qdm29HLdrZaioqUdlTT3KqutQUlWH4qo6FFbWNNTsv4fL/c3YUA9OlqZws2mLYV4d4WbTBu4d2qKLjSlMjDiSkYiaT2mVIzc3F/b29g2P7ezscPr06UaPMTAwgJmZGQoLC2FlZdWiWT7cewXHk/MVHte2lQHMTAxhbmIIqzat4NGxLazbtkJnM2N0aGcMW4vWsLMw4dUJItI66lSzfzmXg8/2Jys8rrWhPsxNDGHW+k7NdnAwgXWbVuhoZoxOZq3RydwY9hYmsGpjxCEYRNSiNOKf3pGRkYiMjAQA5OcrboT/680QD8zp7wI9PQn0JBIY6kvQykAfRgZ6MG2lD9NWBjA1MoC+HgssEdGjetSa/aSfLfwdLCCRSKCvd+e/VgZ6aGWgh9ZG+mjTygAmRgYwMuAdPyISh9IaaFtbW2RnZzc8zsnJga2t7X2PsbOzQ319PUpLS2FpaXnPe0VERCAiIgIAEBAQ0OwsPrZmzX4NEZEuUaeabd/eBPbtudIFEakvpf3zPTAwECkpKUhPT0dtbS2ioqIQFhZ21zFhYWH44YcfAAA7d+7E4MGDeZuNiEgErNlERE2ntCvQBgYGWLt2LUJCQiCTyTBjxgx4e3tj8eLFCAgIQFhYGGbOnInJkyfD1dUV7du3R1RUlLLiEBHRA7BmExE1nUQQBEHxYeojICAAUqlU7BhERA9F12qYrp0vEWmXxmoYZ2AQERERETUDG2giIiIiomZgA01ERERE1AxsoImIiIiImoENNBERERFRM7CBJiIiIiJqBjbQRERERETNwAaaiIiIiKgZNG4jFSsrKzg5OTX7dfn5+bC2tm75QGpAm88N0O7z47lproc9v4yMDBQUFCghkXpizb4/bT4/npvm0ubza+marXEN9MPS5t2wtPncAO0+P56b5tL28xObtv/+avP58dw0lzafX0ufG4dwEBERERE1AxtoIiIiIqJm0JkGOiIiQuwISqPN5wZo9/nx3DSXtp+f2LT991ebz4/nprm0+fxa+tx0Zgw0EREREVFL0Jkr0ERERERELYENNBERERFRM2hdAx0bGwsPDw+4urpixYoV9zxfU1ODcePGwdXVFUFBQcjIyFB9yIek6NxWrlwJLy8v+Pr6YsiQIcjMzBQh5cNRdG5/+/nnnyGRSDRumZ2mnN/27dvh5eUFb29vTJgwQcUJH56ic8vKysKgQYPQo0cP+Pr6Yu/evSKkfDgzZsyAjY0NfHx87vu8IAh46aWX4OrqCl9fX5w7d07FCTUfa7Zm1mxAu+s2azZrtkKCFqmvrxdcXFyEtLQ0oaamRvD19RUSEhLuOuarr74SnnvuOUEQBGHbtm3C2LFjxYjabE05t8OHDwuVlZWCIAjC119/rVXnJgiCUFZWJvTr108ICgoSzpw5I0LSh9OU80tOThb8/PyEoqIiQRAE4datW2JEbbamnNvs2bOFr7/+WhAEQUhISBAcHR1FSPpwjh07Jpw9e1bw9va+7/N79uwRhg8fLsjlcuHkyZNCr169VJxQs7Fma2bNFgTtrtus2azZTaFVV6Dj4uLg6uoKFxcXGBkZITw8HNHR0XcdEx0djalTpwIAxowZg0OHDkHQgHmUTTm3QYMGwcTEBAAQHByMnJwcMaI2W1PODQAWLVqEBQsWwNjYWISUD68p5/fdd99h3rx5sLCwAADY2NiIEbXZmnJuEokEZWVlAIDS0lJ07txZjKgPpX///mjfvn2jz0dHR2PKlCmQSCQIDg5GSUkJbty4ocKEmo01WzNrNqDddZs1mzW7KbSqgc7NzYW9vX3DYzs7O+Tm5jZ6jIGBAczMzFBYWKjSnA+jKef2b+vXr8eIESNUEe2RNeXczp07h+zsbIwcOVLV8R5ZU84vOTkZycnJ6Nu3L4KDgxEbG6vqmA+lKee2dOlSbN68GXZ2dggNDcWaNWtUHVNpmvv3ku7Gmv0PTarZgHbXbdZs1uymMGipUKQ+Nm/eDKlUimPHjokdpUXI5XLMnz8fGzduFDuK0tTX1yMlJQVHjx5FTk4O+vfvj8uXL8Pc3FzsaI9s27ZtmDZtGl577TWcPHkSkydPRnx8PPT0tOrf70QPTdtqNqD9dZs1m7Tqd8PW1hbZ2dkNj3NycmBra9voMfX19SgtLYWlpaVKcz6MppwbABw8eBAffvghYmJi0KpVK1VGfGiKzq28vBzx8fEYOHAgnJyccOrUKYSFhWnMhJSm/NnZ2dkhLCwMhoaGcHZ2hru7O1JSUlQdtdmacm7r16/H2LFjAQC9e/dGdXU1CgoKVJpTWZr695LujzVbM2s2oN11mzWbNbtJHnr0tBqqq6sTnJ2dhWvXrjUMjo+Pj7/rmLVr1941IeXZZ58VI2qzNeXczp07J7i4uAjJyckipXw4TTm3fxswYIDGTEYRhKad3759+4QpU6YIgiAI+fn5gp2dnVBQUCBG3GZpyrkNHz5c2LBhgyAIgpCYmCh06tRJkMvlIqR9OOnp6Y1OSNm9e/ddE1ICAwNVnE6zsWZrZs0WBO2u26zZrNlNoVUNtCDcmWHp5uYmuLi4CMuWLRMEQRAWLVokREdHC4IgCLdv3xbGjBkjdOnSRQgMDBTS0tLEjNssis5tyJAhgo2NjdC9e3ehe/fuwqhRo8SM2yyKzu3fNKkQ/03R+cnlcuHVV18VPD09BR8fH2Hbtm1ixm0WReeWkJAg9OnTR/D19RW6d+8u/P7772LGbZbw8HChY8eOgoGBgWBrayusW7dO+Oabb4RvvvlGEIQ7f25z584VXFxcBB8fH437/1IdsGZrZs0WBO2u26zZrNmKcCtvIiIiIqJm0Kox0EREREREysYGmoiIiIioGdhAExERERE1AxtoIiIiIqJmYANNRERERNQMbKBJ7bRp0+aBz2dkZMDHx6dZ7zlt2jTs3Lnznp8nJSXBz88PPXr0QFpaWrPe82HNmjULiYmJTTq2pqYG48aNg6urK4KCgpCRkaHccEREzcSa/Y/jx4/D398fBgYG981P2oMNNOm0X3/9FWPGjMH58+fRpUsXhccLggC5XP5In7lu3Tp4eXk16dj169fDwsICqampePXVV7FgwYJH+mwiIk2m7jXbwcEBGzduxIQJEx7pM0n9sYEmlTlz5gx8fX1RXV2NyspKeHt7Iz4+vtHjKyoqMGTIEPj7+6Nbt26Ijo5ueK6+vh4TJ06Ep6cnxowZg6qqKgDA2bNnMWDAAPTs2RMhISG4ceNGo++/d+9erFq1Ct988w0GDRoEAFi5ciV8fHzg4+ODVatWAbhz9cTDwwNTpkyBj4/PXduAAsD777+PwMBA+Pj4ICIiAoIgoL6+HoGBgTh69CgA4O2338Y777wDABg4cCCkUilkMhmmTZsGHx8fdOvWDV988cU9GaOjozF16lQAwJgxY3Do0CFw6XYiUgXW7ObXbCcnJ/j6+kJPj+2V1nvkbV+ImuGdd94RXnvtNWHu3LnCRx99dN9jTE1NBUG4s+VoaWmpIAh3tkrt0qWLIJfLhfT0dAGA8McffwiCIAjTp08XPv30U6G2tlbo3bu3kJeXJwiCIERFRQnTp08XBEEQpk6dKuzYseOez1qyZInw6aefCoIgCFKpVPDx8REqKiqE8vJywcvLSzh37pyQnp4uSCQS4eTJk/fNW1hY2PDrSZMmCTExMYIgCEJ8fLzQtWtX4cCBA4Kfn59QU1MjCMI/O3JJpVJh6NChDa8tLi6+5729vb2F7OzshscuLi5Cfn7+fXMQEbU01uzm1ey/NZaftIeB2A086ZbFixcjMDAQxsbG+PLLLx94rCAIWLhwIY4fPw49PT3k5ubi1q1bAAB7e3v07dsXADBp0iR8+eWXGD58OOLj4zFs2DAAgEwmQ6dOnZqc7Y8//sDTTz8NU1NTAMDo0aNx4sQJhIWFwdHREcHBwfd93ZEjR/DJJ5+gqqoKRUVF8Pb2xqhRo+Dt7Y3JkyfjiSeewMmTJ2FkZHTX61xcXHDt2jW8+OKLGDlyJB5//PEmZyUiUgXW7H+wZtO/sYEmlSosLERFRQXq6upQXV3dUPjuZ8uWLcjPz8fZs2dhaGgIJycnVFdXAwAkEsldx0okEgiCAG9vb5w8ebLFczeWs7q6GnPnzoVUKoW9vT2WLl3akBEALl++DHNzc+Tl5d3zWgsLC1y8eBG///47vv32W2zfvh3ff//9XcfY2toiOzsbdnZ2qK+vR2lpKSwtLVv25IiIGsGa/Y+m1GzSHRykQyr13HPP4YMPPsDEiRMVTogrLS2FjY0NDA0NceTIEWRmZjY8l5WV1VB0t27disceewweHh7Iz89v+HldXR0SEhKanK1fv3749ddfUVVVhcrKSvzyyy/o16/fA1/zd+G1srJCRUXFXbOud+3ahaKiIhw/fhwvvvgiSkpK7nptQUEB5HI5nnnmGSxbtgznzp275/3DwsLwww8/AAB27tyJwYMH3/NFRESkLKzZ/2hKzSbdwSvQpDKbNm2CoaEhJkyYAJlMhj59+uDw4cMYPHjwfY+fOHEiRo0ahW7duiEgIABdu3ZteM7DwwNfffUVZsyYAS8vLzz//PMwMjLCzp078dJLL6G0tBT19fV45ZVX4O3t3aR8/v7+mDZtGnr16gXgztJFPXr0eODScebm5pg9ezZ8fHzQsWNHBAYGArhTaN966y0cOnQI9vb2eOGFF/Dyyy83NMMAkJubi+nTpzfMEF++fPk97z9z5kxMnjwZrq6uaN++PaKiopp0LkREj4o1u/k1+8yZM3j66adRXFyM3377DUuWLGnWPwpIc0gEgVP6iYiIiIiaikM4iIiIiIiagQ00EREREVEzsIEmIiIiImoGNtBERERERM3ABpqIiIiIqBnYQBMRERERNQMbaCIiIiKiZmADTURERETUDGygiYiIiIiagQ00EREREVEzsIEmIiIiImoGNtBERERERM3ABpqIiIiIqBnYQBMRERERNQMbaCIiIiKiZmADTURERETUDGygiYiIiIiagQ00EREREVEzsIEmIiIiImoGNtBERERERM3ABpqIiIiIqBnYQBMRERERNQMbaCIiIiKiZmADTURERETUDGygiYiIiIiagQ00EREREVEzsIEmIiIiImoGNtBERERERM1gIHaA5rKysoKTk5PYMYiIHkpGRgYKCgrEjqEyrNlEpMkaq9ka10A7OTlBKpWKHYOI6KEEBASIHUGlWLOJSJM1VrM5hIOIiIiIqBnYQBMRERERNQMbaCIiIiKiZmADTURERETUDGygiYiIiIiagQ00EREREVEzsIEmIiIiImoGNtBERERERM3ABpqIiIiIqBnYQBMRERERNQMbaCKiZiqurBU7AhERNVFJVS0EQWjR92QDTUTUDGXVdRj8+VF8dSRV7ChERNQEz28+hxkbz7Toe7KBJiJqhu//SEdxVR36u1mLHYWIiBT4K7UAJ68Vor97y9ZsNtBERE1UXFmL9SfSMdy7I7rZmYkdh4iIHkAQBHy2/yo6mRljfC+HFn1vNtBERE0UeeIaKmrr8eowd7GjEBGRAkev5uNcVgleHOwGY0P9Fn1vNtBERE2QX16DjX9mYJRvZ3h0bCt2HCIieoC/rz47tDfBswF2Lf7+bKCJiJrgm6NpqKmX4ZWhbmJHISIiBWLjbyLhehleHuIGQ/2Wb3fZQBMRKXCj9DY2n87EM/52cLFuI3YcIiJ6AJlcwOcHktHF2hRP9bBVymewgSYiUuDLQ6kQBAEvDeHVZyIidRd9IRepeRWYP8wD+noSpXyG0hroGTNmwMbGBj4+Pvd9fsuWLfD19UW3bt3Qp08fXLx4UVlRiIgeWkZBJXZIszGhlwPs25uIHUepWLeJSNPV1sux6mAKvDu3wwifjkr7HKU10NOmTUNsbGyjzzs7O+PYsWO4fPkyFi1ahIiICGVFISJ6aKsOJsNAX4J5g13FjqJ0rNtEpOm2S7ORVVSF1x/3gJ6Srj4DgIGy3rh///7IyMho9Pk+ffo0/Do4OBg5OTnKikJE9FCu3ixH9MXreK5/F9i0NRY7jtKxbhORJquuk2HN4RQEOFpgoIdyN7tSizHQ69evx4gRI8SOQUR0l8/3X0UbIwPMGeAidhS1w7pNROrmx5OZuFVWg9dDPCCRKO/qM6DEK9BNdeTIEaxfvx5//PFHo8dERkYiMjISAJCfn6+qaESkw85nFWN/4i3MH+YOcxMjseOoFUV1mzWbiFStvLoOXx9NRT83KwS7WCr980S9An3p0iXMmjUL0dHRsLRs/GQjIiIglUohlUphba3cS/JERADw6e9XYWlqhBmPOYsdRa00pW6zZhORqq07kY7iqjq8GdJVJZ8nWgOdlZWF0aNH48cff4S7O7fFJSL18UdKAf5KK8S8Qa5o00r0G3Vqg3WbiNRRYUUN1p24htBuHdHNzkwln6m0b4bx48fj6NGjKCgogJ2dHd577z3U1dUBAObMmYP3338fhYWFmDt37p0gBgaQSqXKikNE1CSCIODT35Nga94aE4MdxI6jUqzbRKSJvj6ahtt1Mswf5qGyz1RaA71t27YHPr9u3TqsW7dOWR9PRPRQfk+4iYs5pfhkjC9aGeiLHUelWLeJSNNcL7mNH09lYkxPO7jaqG6nWLVYhYOISB3Uy+T49Per6GJtitFK2v6ViIhazqqDyYAAvDxUtcPK2EATEf3PrnO5SMuvxBshHjDQZ3kkIlJnqXnl2Hk2B5N7O8LWvLVKP5vfEEREuLMA/xcHk9Hd3hwh3srb/pWIiFrGZ78nw8TIAPMGqX6nWDbQREQANp/KxI3SaiwYrvwF+ImI6NFcyC5BbMJNRPR3QXtT1a/VzwaaiHReWXUdvjpyZwH+Pl2sxI5DREQPIAgCPt6XBEtTI8wUaa1+NtBEpPMij11T6QL8RET08I6nFODktUK8ONgVpiKt1c8Gmoh0Wl5ZNdb/kY5R3TurbAF+IiJ6OHL5navP9u1bY0KQo2g52EATkU5bfSgFdTI5Xn+cO+sREam73y5dR+KNMrz+uAeMDMRrY9lAE5HOupZfgagz2ZgQ5ABHS1Ox4xAR0QPU1svx2f6r8OrUDqN8O4uahQ00Eemsz/cno5WBHl4c7CZ2FCIiUmDr6UxkF93GghFdoacn7mpJbKCJSCddyC7Bnss3MKufC6zbthI7DhERPUB5dR2+PJyK3i6W6O8m/mpJbKCJSOcIgoDle6/Aqo0RIvq7iB2HiIgUiDx+DUWVtXg7tKtarNXPBpqIdM6Rq3k4nV6El4a4oY1ISyAREVHT5JVVY92JdDzh2wm+duZixwHABpqIdIxMLuDjfVfhZGmC8b0cxI5DREQKfHEwBfVyOd4I8RA7SgM20ESkU34+l4Ort8rx5vCuMNRnCSQiUmepeRXYLs3GxCBHtVotid8eRKQzbtfKsHJ/Mrrbm2OET0ex4xARkQIfxyahtaE+XhzsKnaUu7CBJiKd8f2f6bhZVo13Qj3VYhIKERE1Li69CAcSb+H5gV1g2Ua9VktiA01EOqGwogbfHE3DMK8O6OXcXuw4RET0AIIg4MO9V9CxnTFm9HUWO8492EATkU748lAKbtfJsGB4V7GjEBGRAnsu38DF7BLMf9wdrY30xY5zDzbQRKT1ruVXYMvpLIQH2sPVpo3YcYiI6AFq6mX4JPYqunZsi2f87cSOc19soIlI630SexVGBnp4Zai72FGIiEiBzaeykFVUhbdGdIW+yFt2N4YNNBFptTMZRYhNuIk5A7pwy24iIjVXWlWHLw+loJ+bFQa4W4sdp1FsoIlIawmCgGV7rqBDu1aY3Y9bdhMRqbu1R1JQVl2HhWq+WhIbaCLSWrsv3ZmE8vrjHmo5CYWIiP6RVViFH/7KxLM97eDZqZ3YcR6IDTQRaaWaehk+jk2CZ6d2GK2mk1CIiOgfn/yeBH09CeYPU58tuxvDBpqItNIPf2Ugp/g2Foaq7yQUIiK641xWMXZfuoHZ/ZzR0cxY7DgKsYEmIq1TVFmLNYdTMcjDGv3c1HcSChER3Zmv8sHuRFi3bYXnBnQRO06TsIEmIq2z+mAyqmplWBjqKXYUIiJSYM/lGzifVYI3HveAaSsDseM0CRtoItIqqXkV2Hw6CxN6OcCtQ1ux4xAR0QNU18mwYt+d+SrP9NSc+Sqa0eYTETXRin1XYGKoj1eGuokdhYiIFNj4v/kqW2b5atR8FV6BJiKt8WdqAQ5eycO8wa6wbMNNU4iI1FlBRQ2+OpyKIV1t0NfVSuw4zcIGmoi0gkx+ZxKKffvWmNbHSew4RESkwMoDybhdJ8PbGjhfhQ00EWmFn85kI+lmOd4e4QljQ26aQkSkzpJuliEqLguTgh3hatNG7DjNxgaaiDReeXUdVh64il5O7THCp6PYcYiI6AEEQcCy3VfQ1thQY+erKK2BnjFjBmxsbODj43Pf5wVBwEsvvQRXV1f4+vri3LlzyopCRFruqyNpKKysxaInvCCRaM4kFHXDuk1EqnA4KQ9/pBbglaFuMDcxEjvOQ1FaAz1t2jTExsY2+vy+ffuQkpKClJQUREZG4vnnn1dWFCLSYlmFVfj+j3SM7mGHbnZmYsfRaKzbRKRstfVyfLjnClysTTEp2FHsOA9NaQ10//790b59+0afj46OxpQpUyCRSBAcHIySkhLcuHFDWXGISEt9uDcRBvoSvDncQ+woGo91m4iUbdPJDFwrqMS7Iz1hqK+5I4lFS56bmwt7e/uGx3Z2dsjNzRUrDhFpoL/SCvB7wi3MHdgFHdoZix1H67FuE9GjKKyowepDKejvbo1BHjZix3kkGrGRSmRkJCIjIwEA+fn5IqchInUgkwt4/7dE2Jq3xqx+LmLHoX9hzSai+/n8QDKqamVYNNJT4+eriHYF2tbWFtnZ2Q2Pc3JyYGtre99jIyIiIJVKIZVKYW1traqIRKTGos5kIelmORaGctk6VWlq3WbNJqL/unLjzrJ1k4Md4dahrdhxHploDXRYWBg2bdoEQRBw6tQpmJmZoVOnTmLFISINUnq7Dp/vT0Yv5/YI7cZl61SFdZuIHoYg3Llj2K615i5b919KG8Ixfvx4HD16FAUFBbCzs8N7772Huro6AMCcOXMQGhqKvXv3wtXVFSYmJtiwYYOyohCRlll9MAUlVbVYMorL1rUk1m0iUobY+Js4ea0QHzzprbHL1v2X0hrobdu2PfB5iUSCr776SlkfT0RaKjWvHJtOZiC8lwO8O3PZupbEuk1ELa26ToYP915B145tMb6Xg9hxWozmrh9CRDpHEAS8v/sKWhvp47Vh7mLHISIiBb47fg05xbexeJQXDDR42br/0p4zISKtd+hKHo4n5+PVoe6wbNNK7DhERPQAN0pv4+ujaRjh0xF9uliJHadFsYEmIo1QUy/DB3sS4WrTBpN7a+7uVUREumL53iTIBAELQz3FjtLi2EATkUZYdyIdmYVVWDLKS6N3ryIi0gWnrxUi5uJ1zBnQBfbtTcSO0+L4LUREau9G6W2sPZyKEO8O6OfGdYWJiNRZvUyOJTEJsDVvjecHdBE7jlKwgSYitff3bcB3R3qJHYWIiBTYFndno6t3RnqitZF2bnTFBpqI1FpcetGd24D9XbTyNiARkTYprqzFZ/uT0dvFEiN8tHejKzbQRKS26mVyLI6OR2czYzw/0FXsOEREpMCn+6+ioqYeS8O8tXqjKzbQRKS2tpy+cxtw0RNeWnsbkIhIW1zOKcW2uCxM7e0Ej45txY6jVGygiUgtFVTU4PP9V/GYqxWGa/FtQCIibSCXC1gcEw9LUyO8MsxN7DhKxwaaiNTSp7FXUVUrw9IwL62+DUhEpA1+PpeD81kleGuEJ9oZG4odR+nYQBOR2jmfVYyfpNmY8ZgzXG20+zYgEZGmK71dh49jk+DvYI7RPWzFjqMSBmIHICL6N5lcwKLoeHRo1wovDdH+24BERJpu5f6rKKqsxcbpvaCnpxt3DHkFmojUyta4LMTnluGdkV5o04r/xiciUmfxuaX48VQmJgU7wsfWTOw4KsMGmojURmFFDT6NTUJvF0uM8u0kdhwiInoAuVzA4uh4WJgY4bVhHmLHUSk20ESkNj6OTUJVrQzvP6nd64cSEWmDnedycC6rBG+N6AozE+2fOPhvbKCJSC2czSzCdmkOZjzmDLcOnDhIRKTOSqpqsWJfEno6WuAZfzux46gcG2giEl29TI53folHJzNjvMyJg0REau+T36+i9HYdlj3lozMTB/+NDTQRie6Hk5lIulmOJaO8YMqJg0REau1CdknDjoOendqJHUcUbKCJSFS3yqrxxYFkDPSwRog3dxwkIlJnMrmAd3+9DOs2rfCqDuw42Bg20EQkqg92J6JWJsd7YZw4SESk7jafykR8bhkWPeGFtjqw42Bj2EATkWiOJ+dj96UbmDfQFY6WpmLHISKiB8grq8Znv1/FY65WeELHlxplA01Eoqiuk2FxdDxcrEwxZ6CL2HGIiEiBZXuuoEYmxwdP+ej8HUM20EQkim+OpiGjsAofPOWDVgb6YschIqIHOJGSj5iL1zF3YBc4W/GOIRtoIlK5a/kV+OZoGp7064y+rlZixyEioge4c8cwAU6WJpgzoIvYcdQC14siIpUSBAGLouPRylAP74z0FDsOEREp8O2xNKQXVOLHmb1gbMg7hgCvQBORiv16IRd/phZiwfCusGlrLHYcIiJ6gLT8Cnx95M4dw35u1mLHURtsoIlIZUqqarFs9xX0cDDHhF4OYschIqIHEAQB7/xyGcaGenh3pJfYcdQKh3AQkcqs2JeEktt12Px0N53c+pWISJPsOpeLU9eK8NHT3WDdtpXYcdQKr0ATkUrEpRch6kw2Zj3mrLNbvxIRaYqiylp8uPcKejpaIDzQXuw4aocNNBEpXU29DG/vugRb89Z4eajubv1KRKQpPtxzBWW36/Dh0z68Y3gfbKCJSOm+PXoNafmVWPa0D0yMOHKMiEid/ZVagJ/P5eC5AS7o2pF3DO+HDTQRKVVqXgW+OpKKsO6dMcjDRuw4RET0ANV1Miz85TKcLE3w4mDeMWwMLwURkdIIgoCF/5vBvegJzuAmIlJ3aw6nIKOwCltmBXHN5wfgFWgiUpqfzmQjLr0IC0M9OYObiEjNJd0sw/8du4bR/rbcJVYBpTbQsbGx8PDwgKurK1asWHHP81lZWRg0aBB69OgBX19f7N27V5lxiEiF8sqq8eHeKwh2aY9xnMGtEViziXSXTC5gwc+XYdbaEIu45rNCSmugZTIZ5s2bh3379iExMRHbtm1DYmLiXccsW7YMY8eOxfnz5xEVFYW5c+cqKw4RqdiSmATU1MuxfLQvJBLO4FZ3rNlEuu2HvzJwMbsEi0d5wcLUSOw4aq/RBjo7Oxvh4eHo168fPvroI9TV1TU899RTTyl847i4OLi6usLFxQVGRkYIDw9HdHT0XcdIJBKUlZUBAEpLS9G5c+eHPA0iUie/J9zEvvibeHmIG5ytTMWOoxOSkpIwYsQIjBw5EmlpaZg2bRrMzc3Rq1cvXLlyReHrWbOJdFdOcRU+238VAz2sEdadf6+botEGesaMGRg4cCDWrFmDGzduYMCAASgsLAQAZGZmKnzj3Nxc2Nv/c9vWzs4Oubm5dx2zdOlSbN68GXZ2dggNDcWaNWvu+16RkZEICAhAQEAA8vPzm3RiRCSOsuo6LI6OR9eObRHR30XsODojIiICc+fOxaRJkzB48GAMHz4cxcXFWLRoEV544QWFr2fNJtJNgiDg3V/jAQDLnvLhHcMmarSBzs/Px5w5c+Dn54c1a9Zg7ty56N+/P9LS0lrsN3fbtm2YNm0acnJysHfvXkyePBlyufye4yIiIiCVSiGVSmFtbd0in01EyrF8bxLyy2vw8TO+MNTnPGVVKS8vx6hRozB+/HgYGhoiPDwcEokEo0aNQnFxcYt8Bms2kfb59UIujl7NxxshHrCzMBE7jsZodBm7uro6VFdXw9jYGAAwadIkdOzYESEhIaisrFT4xra2tsjOzm54nJOTA1tb27uOWb9+PWJjYwEAvXv3RnV1NQoKCmBjw7ViiTTRX2kF2BaXhYj+Luhuby52HJ0ik8kafj1//vy7nqutrVX4etZsIt1TUFGD935LhL+DOab0dhI7jkZp9PLQrFmzcPr06bt+NnToUOzYsQM+Pj4K3zgwMBApKSlIT09HbW0toqKiEBYWdtcxDg4OOHToEADgypUrqK6u5tUKIg11u1aGt3ddhqOlCV4d6i52HJ0zb948VFRUAMBdk/tSU1MxdOhQha9nzSbSPUtjElBVI8PHz/hCn9t1N0ujV6BfffXV+/68R48eOHDggOI3NjDA2rVrERISAplMhhkzZsDb2xuLFy9GQEAAwsLC8Pnnn2P27Nn44osvIJFIsHHjRo69IdJQXxxMRmZhFbbODkJrIy6+r2rPPffcfX/u6uqKVatWKXw9azaRbjmQeAu7L93A/GHucOvQVuw4GkciCIIgdojmCAgIgFQqFTsGEf3LxewSPP31nxgXaI/lo33FjqPWdK2G6dr5EmmC0tt1GLbyGNqbGiHmhcdgZMD5Ko1prIZxK28ieiQ19TK8sfMibNoa4+1QT7HjEBGRAh/uSURhZS3WTw1k8/yQ+LtGRI/kqyNpSL5VgY9G+6CdsaHYcYiI6AGOJ+djuzQHEf1d0M3OTOw4GkthA7169WqUlZVBEATMnDkT/v7+2L9/vyqyEZGau3KjDF8fScXoHrYY3LWD2HEIrNlE1LiKmnq8vesyXKxN8fIQN7HjaDSFDfT333+Pdu3aYf/+/SguLsaPP/6It956SxXZiEiN1cnkeH3HRZibGGLRE15ix6H/Yc0mosas2HcF10tv49MxvjA25GTvR6Gwgf57juHfi+Z7e3tDw+YdEpESfHs0DQnXy7DsqW6wMDUSOw79D2s2Ed3PX6kF2HwqCzP6OqOnY3ux42g8hQ10z5498fjjj2Pv3r0ICQlBeXk59PQ4dJpIlyXdLMOXh1MwqntnDPfpKHYc+hfWbCL6r8qaerz58yU4W5ni9cc9xI6jFRSuwrF+/XpcuHABLi4uMDExQWFhITZs2KCKbESkhv4eutHO2BDvhXmLHYf+gzWbiP7r49gk5JbcxvbnenOd/hbSaAOdlJSErl274sKFCwCAa9euqSoTEamx/zuWhvjcMnwz0R/tOXRDbbBmE9H9/JVWgE0nMzGjrzMCnTh0o6U02kCvXLkSkZGReO211+55TiKR4PDhw0oNRkTq58qNMqw+dGfoxohuncSOQ//Cmk1E/1VRU483d94ZuvFGCIdutKRGG+jIyEgAwJEjR1QWhojUV229HK9tvwiz1kZ4n0M31A5rNhH910d7ryC35DZ2zuHQjZamcGbJokWLIJPJGh6XlZVh+vTpSg1FROrnqyOpSLxRho+e9uGqG2qMNZuIgDsbpmw9nYXZ/Vy46oYSKGyg6+vr0atXL1y6dAkHDhxAYGAgevbsqYpsRKQmLueU4qsjqXi6hy0e9+aqG+qMNZuIyqrr8NbPl9DF2hTzh7mLHUcrKVyFY/ny5Rg6dCiCgoJgYWGB48ePw9XVVRXZiEgNVNfJMH/7BVi2McLSURy6oe5Ys4novZhE3Cqvwc/P9+GGKUqi8Ar08ePH8dJLL2Hx4sUYOHAgXnzxRVy/fl0V2YhIDaw8kIyUvAp8/IwvzEwMxY5DCrBmE+m2/Qk38fO5HMwd2AV+9uZix9FaCq9Av/7669ixYwe8vO5s1btr1y4MHjwYSUlJSg9HROI6k1GE705cw4QgBwz0sBE7DjUBazaR7iqqrMXCXy7Dq1M7vDjYTew4Wk1hA33y5Eno6/9z+X/06NEYMGCAUkMRkfgqa+rx2vaLsLNojYWhnmLHoSZizSbSTYIg4J1fLqPsdj02z+oOIwPuQKpMChtofX197NmzBwkJCaiurm74+eLFi5UajIjEtWxPIrKLq/BTRG+0aaWwVJCaYM0m0k2/nM/FvvibeGtEV3Tt2E7sOFpP4T9P5syZg59++glr1qyBIAjYsWMHMjMzVZGNiERy6MotbIvLRkR/F/Ry5vJHmoQ1m0j35JbcxpLoBAQ6WWB2Pxex4+gEhQ30X3/9hU2bNsHCwgJLlizByZMnkZycrIpsRCSCwooaLPj5Mrp2bMvljzQQazaRbpHLBby+/SLkgoDPn/WDvp5E7Eg6QWED3bp1awCAiYkJrl+/DkNDQ9y4cUPpwYhI9e6MoYtH2e06fDHOD60MuPyRpmHNJtItG/7KwMlrhVj0hBccLE3EjqMzFA5sfOKJJ1BSUoI33ngD/v7+kEgkmD17tiqyEZGK7Tybg9iEm3h7RFd4duIYOk3Emk2kO67eLMfHsUkY6mmDcYH2YsfRKRJBEISmHlxTU4Pq6mqYmZkpM9MDBQQEQCqVivb5RNoqq7AKI1YfRzc7M2yZFczbgEqiyhrGmk2kvWrqZXhy7Z8oqKhB7Cv9YdWmldiRtFJjNaxZU+tbtWqFVq34B0SkbeplcszffgF6ehJ8PpZj6LQFazaR9lq5PxlJN8vx/bQANs8i4NpURIRvj6VBmlmMVeP8YGveWuw4RET0AH+lFSDyf5tcDe7aQew4OumBkwgFQUB2draqshCRCC5kl+CLgykY1b0znvTrLHYcegSs2UTar6SqFvN/ughnS1O8O5KbXInlgQ20RCJBaGioqrIQkYpV1tTjlajz6NjOGMue8oFEwqEbmow1m0i7CYKAhb9cRkFFDVaH94CJEQcSiEXhMnb+/v44c+aMKrIQkYq9/1siMouqsHJsd5i1NhQ7DrUA1mwi7bXzbA72Xr6J1x73QDc78SYHUxPGQJ8+fRpbtmyBo6MjTE1NIQgCJBIJLl26pIp8RKQk+y7fwE/SbMwb1AVBLpZix6EWwppNpJ0yCiqxNCYBwS7tEdGfuw2KTWED/fvvv6siBxGp0PWS21jw8yV0tzPDK0O526A2Yc0m0j619XK8FHUeBvp6WMmVktSCwgba0dERFy9exIkTJwAA/fr1Q/fu3ZUejIiUQyYX8MpPFyCTC/hyfA8Y6iscyUUahDWbSPusPJCMSzml+HaSPzpzpSS1oPCbc/Xq1Zg4cSLy8vKQl5eHSZMmYc2aNarIRkRK8NWRVMSlF+GDp3zgaGkqdhxqYazZRNrlz9QC/N/xNIzv5YDhPp3EjkP/o/AK9Pr163H69GmYmt75ol2wYAF69+6NF198UenhiKhlSTOKsPpQCp7064yne9iKHYeUgDWbSHsUVtTg1Z8uwMXKFIue4JJ16kRhAy0IAvT19Rse6+vroxm7fxORmiitqsPLURdga94aH3DJOq3Fmk2kHQRBwBs7L6Hkdh02TA/kknVqRuGfxvTp0xEUFISnn34aAPDrr79i5syZSg9GRC1HEAQs+PkSbpVVY+fzfdDOmEvWaSvWbCLt8P2fGTiclIf3wrzh3ZlL1qmbRsdAp6enAwDmz5+PDRs2oH379mjfvj02bNiAV155pUlvHhsbCw8PD7i6umLFihX3PWb79u3w8vKCt7c3JkyY0PwzICKFtpzOQmzCTbwR4gE/e3Ox45ASsGYTaY/43FKs2HcFw7w6YEpvR7Hj0H00egV6zJgxOHv2LIYMGYJDhw7B39+/WW8sk8kwb948HDhwAHZ2dggMDERYWBi8vLwajklJScHy5cvx559/wsLCAnl5eQ9/JkR0X1dulOGD3Yno726N2f24dqi2Ys0m0g4VNfV4Yes5WJq2wifP+HK4nZpqtIGWy+X46KOPkJycjJUrV97z/Pz58x/4xnFxcXB1dYWLy50v7PDwcERHR99VjL/77jvMmzcPFhYWAAAbG5uHOgkiur/K/xXidq0NsXJsd+hx7VCtxZpNpPkEQcDCXZeRVVSFqIjesDA1EjsSNaLRIRxRUVHQ19dHfX09ysvL7/lPkdzcXNjb2zc8trOzQ25u7l3HJCcnIzk5GX379kVwcDBiY2Pv+16RkZEICAhAQEAA8vPzm3puRDpvcXQCrhVUYnW4H6zatBI7DikRazaR5vvpTDZiLl7H/GHu6OXcXuw49ACNXoH28PDAggUL4OvrixEjRijlw+vr65GSkoKjR48iJycH/fv3x+XLl2Fubn7XcREREYiIiAAABAQEKCULkbb5+WwOfj6Xg5eHuKFPFyux45CSsWYTabarN8uxJCYBj7la4fmBrmLHIQUUbqTysIXY1tYW2dnZDY9zcnJga3v3urN2dnYICwuDoaEhnJ2d4e7ujpSUlIf6PCL6R8qtcrz7azyCnNvjpSFuYschFWLNJtI8lTX1mLvlLNoaG2LluO7cqlsDKG0P38DAQKSkpCA9PR21tbWIiopCWFjYXcc89dRTOHr0KACgoKAAycnJDePviOjhVNXWY+6WczBtpY8143uwEFOTsGYTiUMQBLz7azzSCyrxZbgfbNoaix2JmkBpDbSBgQHWrl2LkJAQeHp6YuzYsfD29sbixYsRExMDAAgJCYGlpSW8vLwwaNAgfPrpp7C0tFRWJCKdsDg6Aan5FVg1rgds2rEQU9OwZhOJY7s0G7+cz8XLQ9zRx5XD7TSFRGhki6pdu3Y98IWjR49WSiBFAgICIJVKRflsInW3XZqNN3dewktD3DB/mLvYceg+lFXDWLOJNM+VG2V46qs/EejUHj/M6MU7hmqosRrW6CTC3377rdE3k0gkohVjIrq/xOtlWPRrPPp0scTLHPesc1iziTRLeXUd5m45B7PWhvhinB+bZw3TaAO9YcMGVeYgokdQXl2HeVvvFOLV4Rz3rItYs4k0hyAIWPDzJWQVVWHb7GBYt+Uyo5pG4RjoW7duYebMmQ0zuxMTE7F+/XqlByOipvl3IV47wZ+FWMexZhOpvw1/ZmDv5Zt4M8SD6z1rKIUN9LRp0xASEoLr168DANzd3bFq1Spl5yKiJlr/Rzr2Xr6JN1iICazZROrubGYRPtp7BcO8OiCiP1ex0VQKG+iCggKMHTsWenp3DjUwMIC+vr7SgxGRYnHpRVi+LwmPe3XAcyzEBNZsInWWX16DuVvOwdaiNT57tjskEg6301SNjoH+m6mpKQoLCxv+kE+dOgUzMzOlByOiB8srr8YLW8/B3qI1PhvLQkx3sGYTqad6mRwvbTuPkqo6/DK3F8xaG4odiR6BwgZ65cqVCAsLQ1paGvr27Yv8/Hzs3LlTFdmIqBH1Mjle3HoeZdV1+GFGL7QzZiGmO1izidTTZ/uTcfJaIT57tju8OrcTOw49IoUNtL+/P44dO4arV69CEAR4eHjA0JBf1kRiWrEvCafTi/DFuO7w7MRCTP9gzSZSP/su38C3x9IwvpcDxvS0EzsOtQCFDXR1dTW+/vpr/PHHH5BIJOjXrx/mzJkDY2PucEYkhpiL17Huj3RM6+OEp3uwENPdWLOJ1EtqXjle33ER3e3NsTTMS+w41EIUNtBTpkxB27Zt8eKLLwIAtm7dismTJ2PHjh1KD0dEd0u6WYYFOy8hwNECC0M9xY5Daog1m0h9lFfX4bkfz8LYUB/fTvJHKwNO6NUWChvo+Ph4JCYmNjweNGgQvLz4LygiVSutqsOcH8+ijbEBvp7oDyMDhYvokA5izSZSD3K5gNd3XERGYRU2zwxCJ7PWYkeiFqTwG9jf3x+nTp1qeHz69GkEBAQoNRQR3U0mF/BS1HnkltzGNxP9YdOOt+Pp/lizidTDV0dS8XvCLbw9oit6d7EUOw61sEavQHfr1g0SiQR1dXXo06cPHBwcIJFIkJmZia5du6oyI5HO+3z/VRxLzseyp3wQ4MTNUuherNlE6uNw0i2sPJiMp/w6Y+ZjzmLHISVotIHevXu3KnMQUSP2Xr6Br4+mITzQHhODHMSOQ2qKNZtIPVzLr8DL2y7Aq1M7LB/tyzX6tVSjDbSjo+Ndj/Py8lBdXa30QET0jys3yvDa9ovo4WCO9570ZiGmRrFmE4mvrLoOszdJYaAvwbeTeqK1EScNaiuFY6BjYmLg5uYGZ2dnDBgwAE5OThgxYoQqshHptKLKWszeJEW71gb4v0k9OXubmoQ1m0gcMrmAV6IuILOwCl9P7An79iZiRyIlUthAL1q0CKdOnYK7uzvS09Nx6NAhBAcHqyIbkc6qk8kxb8s55JXX4P8mB3DSIDUZazaROFYeuIrDSXlYMsqLkwZ1gMIG2tDQEJaWlpDL5ZDL5Rg0aBCkUqkqshHprGW7E3HyWiGWP90NfvbmYschDcKaTaR6MRev46sjaRjfyx6Tgh0Vv4A0nsJ1oM3NzVFRUYH+/ftj4sSJsLGxgampqSqyEemkLacz8cPJTMx6zBnPcMtXaibWbCLVupRTgjd2XESgkwWWhnGuiq5QeAU6OjoarVu3xhdffIHhw4ejS5cu+O2331SRjUjnnEwrxJLoBAz0sMbb3GmQHgJrNpHq3CqrxuxNUli1aYVvOFdFpyi8Av3vKxdTp05VahgiXZZVWIXnt5yFo6UJvhzfA/p6vIpBzceaTaQa1XUyRPx4FuXV9fj5+T6watNK7EikQo020G3btr3vbQhBECCRSFBWVqbUYES6pKy6DjN+OANBANZPDUQ7Y0OxI5GGYc0mUh1BEPDGzku4lFOCbyf1hGendmJHIhVrtIEuLy9XZQ4inVX/vxU3Mgoq8ePMIDhZcbwqNR9rNpHqrD6Ugt8uXseC4V0R4t1R7DgkAoVDOIhIuZbtuYITKQVYMboblz4iIlJzv128jlUHU/CMvx3mDHAROw6JROEkQiJSnh/+ysDGvzIw6zFnhPfiNt1EROrsbGYxXvvfihsfjfbhihs6jA00kUiOJOXhvd8SMNSzA1fcICJSc9lFVYjYJEUnM2P83+QArrih4xQ20GvWrEFxcbEqshDpjMTrZXhh6zl4dmqHL8f7ccUNajGs2UQtr/R2HaZvPIN6uYDvpwWivamR2JFIZAob6Fu3biEwMBBjx45FbGwsBEFQRS4irXWztBozfziDtsaGWD81ECZGnIpALYc1m6hl1db/M9H720k90cW6jdiRSA0obKCXLVuGlJQUzJw5Exs3boSbmxsWLlyItLQ0VeQj0ioVNfWYvvEMym7X4ftpgehoZix2JNIyrNlELUcQBCz85TL+SC3Aimd8OdGbGjRpDLREIkHHjh3RsWNHGBgYoLi4GGPGjMGbb76p7HxEWuPv5eqSb5Xjq4n+8OrMdUNJOViziVrGmsOp2Hk2By8PccOYnnZixyE1ovDe8erVq7Fp0yZYWVlh1qxZ+PTTT2FoaAi5XA43Nzd88sknqshJpNEEQcCi6AQcS87H8tHdMNDDRuxIpKVYs4laxq5zOVh5IBmj/W3xylA3seOQmlHYQBcVFWHXrl1wdHS86+d6enrYvXu30oIRaZOvjqRiW1wW5g7sgvFcro6UiDWb6NGdSMnHmzsvoU8XS6wY7cvl6ugeChvo9957r9HnPD259BaRIjvP5uCz/ckY3cMWb4R4iB2HtBxrNtGjSbxehuc3n4OrTRt8O7knjAy44i/di/9XECnRiZR8vPXzJfR1tcSKZ3gVg4hIneUUV2H6xji0NTbAhumBaGdsKHYkUlNKbaBjY2Ph4eEBV1dXrFixotHjfv75Z0gkEkilUmXGIVKpyzmlmPPjWbjatME3k3gVg9QfazbpsuLKWkz9Pg5VtTJsnN4Lncxaix2J1JjSvtFlMhnmzZuHffv2ITExEdu2bUNiYuI9x5WXl2P16tUICgpSVhQilcssrMT0jXEwNzHCphm9eBWD1B5rNumy27UyzPzhDLKLb2PdlAB4dGwrdiRSc0proOPi4uDq6goXFxcYGRkhPDwc0dHR9xy3aNEiLFiwAMbGXA+XtEN+eQ2mfB8HmVzAppm9YNOO/2+T+mPNJl1VL5PjxW3ncD67BF+G+yHIhWs9k2JKa6Bzc3Nhb2/f8NjOzg65ubl3HXPu3DlkZ2dj5MiRD3yvyMhIBAQEICAgAPn5+UrJS9QSyqrrMPX7OOSV1WD9tEDuWEUagzWbdJEgCHhr12UcvJKH95/0wXCfTmJHIg0h2qBMuVyO+fPn4/PPP1d4bEREBKRSKaRSKaytrVWQjqj5qutkmP2DFMm3yvHNJH/4O1iIHYmoxbBmkzZavi8JO8/m4JWhbpgc7Kj4BUT/o7QG2tbWFtnZ2Q2Pc3JyYGtr2/C4vLwc8fHxGDhwIJycnHDq1CmEhYVxUgpppHqZHC9Hncfp9CJ8PrY7N0ohjcOaTbrm22NpiDx+DVN6O+LlIdwohZpHaQ10YGAgUlJSkJ6ejtraWkRFRSEsLKzheTMzMxQUFCAjIwMZGRkIDg5GTEwMAgIClBWJSCnk8ju3AH9PuIUlo7zwpJ+t4hcRqRnWbNIl2+KysGJfEp7w7YSlo7y5xCg1m9IaaAMDA6xduxYhISHw9PTE2LFj4e3tjcWLFyMmJkZZH0ukUoIg4MO9V7DzbA5eHuKG6X2dxY5E9FBYs0lX7Ll0Awt/uYyBHtZYOdYPenpsnqn5JIIgCGKHaI6AgADeMiS18eWhFKw8kIxpfZywZJQXr2KQQrpWw3TtfEm9HUvOx6wfzsDP3hybZgShtZG+2JFIzTVWw7izw/+3d+dhUdbr/8Dfwy6g7AgCCgOIwMiibKXmgpVlclrQSHPD7aSVnTppy8k8J+vU6fxarTymFYZLZha0aOWGqbgMuIEbIsiSsu/DMsvn94dF+VV0BoFZeL+uq+sS5pnhvlFu3j3zeZ4PUSet3VeAt34+h4eGeWPZfQzPRESG7NCFKiz4XI5A975YMzOa4ZluCQM0USdsOlyEV747hXtkHnjjoaF8C5CIyIAdL67FnBQ5vBz74PM5MXDow82t6NYwQBPpKO1YKZ7/+iRGD3bDu0mRsDDnjxERkaE6c7keMz45DCc7S6yfGwcXe2t9l0QmgL/5iXSw7eQlPL35OGJ8nbHq0eGwsuCPEBGRoTpf3ohpHx9CH0tzrJ8TBw8H7qBJXYO//Ym0tPN0GZ7cdBTh3g5YO4vr54iIDFlhZROmfnwQEokE6+fFYqCLrb5LIhPCAE2khb3nKvBYajaGePTDZ8kxsLe20HdJRETUgeJqBaatOQSlWoP1c2Ph72av75LIxDAFEN3EvrxKzFsnh9TNDuuSY9DPhhefEBEZqpIaBZJWH0Rjqwrr58YiyKOvvksiE8Qz0EQ3cCC/EnPXHYGfqx02zIuDk52VvksiIqIO/FrbjEc+Poj6FiVS58RC5uWg75LIRDFAE3UgM78Kcz6TY6CzLdbPjYUzwzMRkcH6PTzXNl0Jz0O9GZ6p+zBAE13HgfxKzP7sMLyd+vC2R0REBq60thlJqw+iurENKXNiEO7jqO+SyMRxDTTR/3HgfCWSU478duY5Dm59GZ6JiAzVlfCcidomJdbNiUHkQCd9l0S9AAM00Z/8kleBeevkGORsh/XzYuHKM89ERAaruFqBRz4+iLpmJT6fG4sInnmmHsIATfSb3WfKsSA1C/5u9kidE8NlG0REBuz3+zw3tamxfm4swrwd9V0S9SIM0EQAfsq9jEUbrtzn+fM5MXC05QWDRESG6nx5I6Z+fBAqjcCGebEIHcALBqlnMUBTr5d2rBRPbz6OoV4OSEmOgUMf3ueZiMhQnb5Uj0fXHIJEAmycF8f7PJNeMEBTr7b5SDGWbj2BGF9nrJ0VzR0GiYgM2LHiWsz85DBsrcyxfm4spNxhkPSEaYF6rU/3F+Cf357C6MFuWPXocPSxMtd3SURE1IGDF6owN0UOZzsrrJ8bCx9nW32XRL0YAzT1OkIIvLszD+/syMOEUA+8+0gErC0YnomIDNXO02VYuD4bPs62SJ0TCw8HG32XRL0cAzT1KhqNwIrvT+OT/QVIHO6N1x8cCgtz7idERGSo0o6V4pnNxxHs2Q8pyTHcFZYMAgM09RpKtQbPfXUSX2WXYPYIX7w0MQRmZhJ9l0VERB1Yl1mIl9NzEePrjDUzo9DXhhd5k2FggKZeoblNjcc3ZGPnmXL8bfxgPBkfAImE4ZmIyBAJIfD2jjy8tzMP44P7Y+XUSNhYcqkdGQ4GaDJ5dQol5qQcQVZRDVbcL8OjcYP0XRIREXVArRF4OT0HqQeLuNSODBYDNJm0X2ubMfOTw7hYpcDKR4ZhYpinvksiIqIOtCjVeGrTMWzPvYwFo6V4bsIQvltIBokBmkzWmcv1mPXJETS1qpCSHIPb/F30XRIREXWgVtGGeevkkF+swbL7QpA80k/fJRF1iAGaTNKB/Eos+DwLtlbm2PzX2xDs2U/fJRERUQdKahSY9ekRFFUp8P4jkbgvbIC+SyK6IQZoMjnfHC3Fs1uOw9fFDp8lx8DLsY++SyIiog7klNZh9mdH0KJU891CMhoM0GQyhBD4cE8+3vzxLOKkzvjf9Cg49OEtj4iIDNXuM+VYtCEbTrZXdhcc3L+vvksi0goDNJmENpUGL3x9EluySnB/xAC8kRjG3QWJiAzYusxCLE/PRbBnP3wyKxr9+3F3QTIeDNBk9OoUSvw1NQuZF6rw1PhALI4P5FXbREQGSq0RePW3HWHHB7vj3aRI2FkzjpBx4b9YMmoXKhoxN0WOkppmvP1wOB6I9NZ3SURE1IGGFiWe3HgUu89WIHmEH16cGAxz7ghLRogBmozW/vOVeCw1CxbmZkidG4sYP2d9l0RERB0orlZgTsoR5Fc04ZX7ZZjOTa3IiDFAk9ERQiD14EUs//YU/N3ssHZmNHycbfVdFhERdeDQhSo8tj4bKrUG65JjMCLAVd8lEd0SBmgyKm0qDV5Oz8XGw0UYN8Qd7yZFoK8N77RBRGSo1h+6iJfTcjHQxRZrZkRB6mav75KIbhkDNBmNioZWLFqfjcOF1XhsjD/+flcQ184RERmoNpUG//ouF6kHizAmyA3vPRKJfjzhQSbCrDtffPv27QgKCkJAQABef/31ax5/6623EBISgrCwMMTHx+PixYvdWQ4ZsePFtUhYuQ8nSmvxblIElk4YwvBM1MU4s6mrlDe0YOrHB5F6sAgL7pBi7cxohmcyKd0WoNVqNRYtWoRt27bh1KlT2LhxI06dOnXVMZGRkZDL5Thx4gQSExOxZMmS7iqHjNhmeTEm/y8T5mYSfPXY7fhLhJe+SyIyOZzZ1FWyi2ow6f19yP21Hu8/Eonn7+WdNsj0dFuAPnz4MAICAiCVSmFlZYWkpCSkpaVddczYsWNha3vl4q+4uDiUlJR0VzlkhFqUajy/9QSWbDmBGF9nfPv4SIQOcNB3WUQmiTObbpUQAusyC/Hw/zJhbWGOrQtvx6TwAfoui6hbdNsa6NLSUvj4+LR/7O3tjUOHDnV4/Nq1a3HPPfdc97HVq1dj9erVAICKioquLZQMUnG1AgvXZ+NkaR0WjvHHM1zvTNStOLPpVijaVHhh60l8c+xXjBvijrenRMDBlks2yHQZxEWEqampkMvlyMjIuO7j8+fPx/z58wEAUVFRPVka6cHO02V4evNxaDQCq6cPx12hHvouiYj+hDOb/ux8eQMWrs9GXnkjnrlzMBaNDYAZT3iQieu2AO3l5YXi4uL2j0tKSuDlde3a1R07duDVV19FRkYGrK2tu6scMgIqtQb//ekcVmXkI8SzHz6cNgy+rnb6LouoV+DMps745mgpXvj6JPpYmmNdcgxGBbrpuySiHtFtATo6Ohp5eXkoKCiAl5cXNm3ahA0bNlx1zNGjR7FgwQJs374d7u7u3VUKGYHS2mYs3ngU8os1mBo7EMvuC4GNpbm+yyLqNTizSRfNbWr889tcbDpSjGhfJ7z/yDB4ONjouyyiHtNtAdrCwgIrV67E3XffDbVajeTkZISGhmLZsmWIiopCQkICnn32WTQ2NmLy5MkAgIEDByI9Pb27SiID9fOpMvz9y+NQqTV4NymCd9kg0gPObNLWubIGPL7hypKNhWP88fSdg2Fh3q13xSUyOBIhhNB3EbqIioqCXC7XdxnUBVqUavz7h9NIybwImVc/rHyESzbI9PW2Gdbb+jVlQgisP1SEFd+fgr21Bd5+OIJLNsjkdTTDDOIiQup9zl5uwJMbj+JsWQPmjPTDkglBsLbgkg0iIkNU3dSGpV+dwM+nyjAq0BX/b0o43PtyyQb1XgzQ1KM0GoHPDhTi9e1n0M/GEinJMRg9mGcwiIgM1d5zFfj7l8dRq1DiHxODkTzCj3fZoF6PAZp6zKW6Zjz75QnsO1+J+CHueCMxDK72vIqfiMgQtSjVeH3bGXx2oBCB7vb4dHY0N7Mi+g0DNHU7IQS+OVaKl9NyoVQL/PvBoUiK9oFEwjMYRESG6FhxLZ7ZfAz5FU2YPcIXSycM4Z2RiP6EAZq6VWVjK/7xdQ62517G8EFO+O/kcPjxQkEiIoPUptLg3Z3n8NGefHj0s0HqnFiMDHTVd1lEBocBmrqFEALfnriE5em5aGxR4YV7h2DOSCm34yYiMlAnSmrx7JcncLasAZOHe+OlSSHoZ8PtuImuhwGaulx5fQv+8U0OfjpVhnAfR/w3MQyB/fvquywiIrqOFqUa7+zIw+q9+XDra421M6MQH9xf32URGTQGaOoyGo3AF/JivPbDabSqNHj+niGYM9KPN9gnIjJQBy9U4fmtJ1FQ2YSHo3zwwsRgOPThWWeim2GApi6RX9GIF7aexKGCasRJnfHaA0MhdbPXd1lERHQdtYo2vL7tDDYdKcZAZ1uudSbSEQM03ZIWpRof7j6PVRkXYGNphjceGoopUbzDBhGRIfr9rkgrvjuN2mYl5t8hxd/GD0YfK95hg0gXDNDUaXvOlmN5ei4KqxS4P2IAXpwYAre+vK8zEZEhOl/egJfTc7H/fBUifBzx+QNDETKgn77LIjJKDNCks9LaZrzy7Slsz70Mqasd3/ojIjJgTa0qvLcrD2t/KYCtlTleuV+GqTEDeVckolvAAE1aa25T439787EqIx8SSLBkQhDmjPSDtQXf+iMiMjQajUDa8VK8vu0MyupbMSXKG0snDIELd4AlumUM0HRTv9/T+Y1tZ1Ba24z7wjzx/L3B8HLso+/SiIjoOo4V1+Kf3+biaFEtwr0d8NGjwzFsoJO+yyIyGQzQdENZF2uw4vtTOFpUixDPfnhrSjhipS76LouIiK6jpEaB/2w/i/Tjv8LV3hpvJobhoWHeMONyDaIuxQBN13WhohH//eksfjh5Ge59rfGf34Yw18wRERmeOoUSH+45j08PFEIC4IlxAVgw2h/21vw1T9Qd+JNFVymvb8F7u/Kw8XAxrC3MsDg+EPPvkMKOQ5iIyOC0KNVIOVCID3afR0OrCg9EeuHvdwVhAJfYEXUrpiICANQ0tWHV3nykHCiESi0wLXYgnhgXyNvSEREZoDaVBl8cKcL7u86jvKEVY4LcsHTCEAR78rZ0RD2BAbqXq1MosXbfBXyyvxBNbSrcH+GFp8YHYpCLnb5LIyKi/0Op1uCrrBKs3H0eJTXNiPZ1wvuPRPLaFKIexgDdS9U0teHT/QX4dH8hGlpVuHeoBxbHD0aQR199l0ZERP9Hm0qDrdl/BOdwbwe8cr8MYwa7cedXIj1ggO5lyutbsGZfAVIPXoSiTY0JoR5YPD6Qb/sRERmg5jY1Nh0pwuq9F3CpruVKcP6LDGOCGJyJ9IkBupfIr2jEx3svYGt2KVQaDRLCB2Dh2AAM7s8zzkREhqamqQ0pmYVIOVCIGoUSMX7OeOOhMIwKdGVwJjIADNAmTAiBQwXVWLuvADtOl8HS3AyTo7wxb5QUvq5c40xEZGguVDTi0/2F2JJVgmalGvFD3LFgtD9i/Jz1XRoR/QkDtAlqUarx3YlL+OxAAXJK6+Fka4nHxwZgxm2+vKsGEZGB0WgE9p2vRMqBQuw6Ww5LMzP8JWIA5t0h5buERAaKAdqEFFUpsOFwEb44UoQahRKB7vZ47YGheHCYF2wszfVdHhER/UmdQomvskuQevAiLlQ2wdXeCk+MC8T0uEE82UFk4BigjVybSoNdZ8qw4XAxfsmrgATA+OD+mHW7L27zd+FaOSIiAyKEQHZRDTYeLsa3x39Fq0qDCB9HvPNwBO4Z6gFrC57sIDIGDNBG6szlemyRl+Dro6WoamqDp4MNFscH4uFoH3g6cAcqIiJDUlbfgq+PlmKzvBgXKppgZ2WOh4Z7Y2rMQMi8HPRdHhHpiAHaiFyua8G3x3/F1qOlOH2pHpbmEowP7o8pUT4YFegKC3MzfZdIRES/aWxV4afcy/j6aCn2n6+ERgBRg5zw14f8MTHME3bW/BVMZKz402vgKhpa8WPuZXx7/FccLqyGEEC4twOWTwrBpPABcLHnOjkiIkOhaFMh42wFvj3xK3aeLkerSgMf5z54fGwA7o/0gtTNXt8lElEXYIA2QMXVCuw4XYZtOZdx5LfQ7O9mh6fiB+O+cE/4cwATERmMWkUb9pytwPacy9hzrhwtSg1c7a2QFO2DSeEDMHyQE69HITIxDNAGQKXW4GhxLfacLcfO0+U4c7kBADC4vz2eGBeIe2QeGOLRlwOYiMgACCGQV96IPWfLsetMOY4U1kCtEXDva40pUT6YIPNAjK8zl9URmTAGaD0QQqCoWoFf8iqx//yV/+pbVDA3k2D4ICf8Y2Iw4oP7w4+bnRARGYSqxlbsz6/C/rxK7DtfidLaZgBAUP+++OtoKcYH90e4tyPMzHiig6g3YIDuARqNQH5FI+QXa3DoQhUOFVTjUl0LAMDTwQZ3h3pgTJA7Rga6wqGPpZ6rJSKiX2ubkXWxBocLqnGooArnyhoBAH1tLHC7vwsWjQ3A6CA3eDnyrkdEvREDdBcTQqC8oRUnSupwoqQWx0vqcKyoBvUtKgCAq701YqXOiPNzxogAV/i52nFpBhGRHtU1K5H7a1373D5aVNt+ksPOyhzDfZ3xlwgvjAhwhWxAPy7NIKLuDdDbt2/H4sWLoVarMXfuXDz33HNXPd7a2ooZM2YgKysLLi4u+OKLL+Dr69udJXWpOoUS+ZWNyCtrwLmyRpy93IBTl+pR3dQGADA3kyDQ3R4TwwZg2EBHDB/kxMBMRAbL1Gd2c5saBZVNyCtvQF5ZI86WNeD0pXqU1DS3H+Pj3AdRvs4YPtARwwY5IcSTgZmIrtVtAVqtVmPRokX4+eef4e3tjejoaCQkJCAkJKT9mLVr18LJyQnnz5/Hpk2bsHTpUnzxxRfdVZJONBqB2mYlyhtacKmuBZfrWlBSo0BJTTOKqhUorGxCjULZfryNpRkC3fvizuD+CPbsC5mXA0IHOKCPFXeVIiLDZ+wzWwiBhlYVKhpaUVZ3ZW6X1jajpEaB4upmFFY1tZ9VBq6c4PB1sUWEjyOmxg5EiGc/hHk7wtnOSo9dEJGx6LYAffjwYQQEBEAqlQIAkpKSkJaWdtUwTktLw/LlywEAiYmJePzxxyGE6PIztD/lXkZxTTOEEFBrBJRqDdpUGrSoNFC0qdDUqkZjqwp1CiXqmpWoVrShuqkNao246nXMzSTwdLCBj5MtJsg84OdqBz9Xewzubw9vJ1uY8+IRIjJShjSzjxfXIutiDTRCQCMElGqBVtWVud3cpkJjqxpNrSrUtyhRq1CiVtGGyqY2tKk017yWW19r+Dj1wW1SF/i62sHX1Q6D+9vDz9WO22YTUad1W4AuLS2Fj49P+8fe3t44dOhQh8dYWFjAwcEBVVVVcHV1veq41atXY/Xq1QCAiooKnWtZf6gIGeeufp5EAliZm8HO2gK2Vuawt7aAQx9L+LraIqKPI1z7WsHFzhpufa0xwNEG/fvZwKOfDd/KIyKTZEgz+5e8Cvz3p3PXfN7K3Ax9rMxhZ2UOu99mtqeDDYZ49oWbvTVc7K3gam8NDwcbeDr0gaeDDWwsGZKJqOsZxUWE8+fPx/z58wEAUVFROj9/5dRIaDSAmRlgJpHA0twMluYSrkUmIuoGtzqz54yUYnqcLyRmgLlEAnMzCazMzXiLOCIyGN0WoL28vFBcXNz+cUlJCby8vK57jLe3N1QqFerq6uDi4tLltfS14a3hiIhuxJBmdh8rc14/QkQGrdvWI0RHRyMvLw8FBQVoa2vDpk2bkJCQcNUxCQkJSElJAQBs2bIF48aN41lhIiI94MwmItJet52BtrCwwMqVK3H33XdDrVYjOTkZoaGhWLZsGaKiopCQkIA5c+Zg+vTpCAgIgLOzMzZt2tRd5RAR0Q1wZhMRaU8ihBA3P8xwREVFQS6X67sMIqJO6W0zrLf1S0SmpaMZxltKEBERERHpgAGaiIiIiEgHDNBERERERDpggCYiIiIi0gEDNBERERGRDhigiYiIiIh0wABNRERERKQDBmgiIiIiIh0Y3UYqrq6u8PX11fl5FRUVcHNz6/qCDIAp9waYdn/szXh1tr/CwkJUVlZ2Q0WGiTP7+ky5P/ZmvEy5v66e2UYXoDvLlHfDMuXeANPuj70ZL1PvT99M/ftryv2xN+Nlyv11dW9cwkFEREREpAMGaCIiIiIiHfSaAD1//nx9l9BtTLk3wLT7Y2/Gy9T70zdT//6acn/szXiZcn9d3VuvWQNNRERERNQVes0ZaCIiIiKirsAATURERESkA5ML0Nu3b0dQUBACAgLw+uuvX/N4a2srHn74YQQEBCA2NhaFhYU9X2Qn3ay3t956CyEhIQgLC0N8fDwuXryohyo752a9/e6rr76CRCIxutvsaNPf5s2bERISgtDQUEydOrWHK+y8m/VWVFSEsWPHIjIyEmFhYfjhhx/0UGXnJCcnw93dHTKZ7LqPCyHw5JNPIiAgAGFhYcjOzu7hCo0fZ7ZxzmzAtOc2ZzZn9k0JE6JSqYRUKhX5+fmitbVVhIWFidzc3KuO+eCDD8SCBQuEEEJs3LhRTJkyRR+l6kyb3nbt2iWampqEEEJ8+OGHJtWbEELU19eLUaNGidjYWHHkyBE9VNo52vR37tw5ERERIaqrq4UQQpSVlemjVJ1p09u8efPEhx9+KIQQIjc3VwwaNEgPlXZORkaGyMrKEqGhodd9/PvvvxcTJkwQGo1GZGZmipiYmB6u0LhxZhvnzBbCtOc2ZzZntjZM6gz04cOHERAQAKlUCisrKyQlJSEtLe2qY9LS0jBz5kwAQGJiInbu3AlhBNdRatPb2LFjYWtrCwCIi4tDSUmJPkrVmTa9AcBLL72EpUuXwsbGRg9Vdp42/X388cdYtGgRnJycAADu7u76KFVn2vQmkUhQX18PAKirq8OAAQP0UWqn3HHHHXB2du7w8bS0NMyYMQMSiQRxcXGora3FpUuXerBC48aZbZwzGzDtuc2ZzZmtDZMK0KWlpfDx8Wn/2NvbG6WlpR0eY2FhAQcHB1RVVfVonZ2hTW9/tnbtWtxzzz09Udot06a37OxsFBcXY+LEiT1d3i3Tpr9z587h3LlzGDFiBOLi4rB9+/aeLrNTtOlt+fLlSE1Nhbe3N+699168//77PV1mt9H155Kuxpn9B2Oa2YBpz23ObM5sbVh0VVFkOFJTUyGXy5GRkaHvUrqERqPB008/jc8++0zfpXQblUqFvLw87NmzByUlJbjjjjtw8uRJODo66ru0W7Zx40bMmjULzzzzDDIzMzF9+nTk5OTAzMyk/v+dqNNMbWYDpj+3ObPJpL4bXl5eKC4ubv+4pKQEXl5eHR6jUqlQV1cHFxeXHq2zM7TpDQB27NiBV199Fenp6bC2tu7JEjvtZr01NDQgJycHY8aMga+vLw4ePIiEhASjuSBFm787b29vJCQkwNLSEn5+fhg8eDDy8vJ6ulSdadPb2rVrMWXKFADAbbfdhpaWFlRWVvZond1F259Luj7ObOOc2YBpz23ObM5srXR69bQBUiqVws/PT1y4cKF9cXxOTs5Vx6xcufKqC1ImT56sj1J1pk1v2dnZQiqVinPnzumpys7Rprc/Gz16tNFcjCKEdv1t27ZNzJgxQwghREVFhfD29haVlZX6KFcn2vQ2YcIE8emnnwohhDh16pTw9PQUGo1GD9V2TkFBQYcXpHz33XdXXZASHR3dw9UZN85s45zZQpj23ObM5szWhkkFaCGuXGEZGBgopFKpWLFihRBCiJdeekmkpaUJIYRobm4WiYmJwt/fX0RHR4v8/Hx9lquTm/UWHx8v3N3dRXh4uAgPDxeTJk3SZ7k6uVlvf2ZMg/h3N+tPo9GIv/3tbyI4OFjIZDKxceNGfZark5v1lpubK26//XYRFhYmwsPDxY8//qjPcnWSlJQkPDw8hIWFhfDy8hJr1qwRH330kfjoo4+EEFf+3hYuXCikUqmQyWRG9+/SEHBmG+fMFsK05zZnNmf2zXArbyIiIiIiHZjUGmgiIiIiou7GAE1EREREpAMGaCIiIiIiHTBAExERERHpgAGaiIiIiEgHDNBkcOzt7W/4eGFhIWQymU6vOWvWLGzZsuWaz585cwYRERGIjIxEfn6+Tq/ZWXPnzsWpU6e0Ovatt95CSEgIwsLCEB8fj4sXL3ZzdUREuuHM/sOqVaswdOhQREREYOTIkVo/j4wPAzT1at988w0SExNx9OhR+Pv73/R4IQQ0Gs0tfc01a9YgJCREq2MjIyMhl8tx4sQJJCYmYsmSJbf0tYmIjJmhz+ypU6fi5MmTOHbsGJYsWYKnn376lr42GS4GaOoxR44cQVhYGFpaWtDU1ITQ0FDk5OR0eHxjYyPi4+MxbNgwDB06FGlpae2PqVQqTJs2DcHBwUhMTIRCoQAAZGVlYfTo0Rg+fDjuvvtuXLp0qcPX/+GHH/DOO+/go48+wtixYwFcOeMrk8kgk8nwzjvvALhy9iQoKAgzZsyATCa7ahtQAPjXv/6F6OhoyGQyzJ8/H0IIqFQqREdHY8+ePQCA559/Hi+++CIAYMyYMZDL5VCr1Zg1axZkMhmGDh2Kt99++5oax44dC1tbWwBAXFwcSkpKbvJdJiLqGpzZus/sfv36tf+5qakJEonkBt9hMmq3vu8LkfZefPFF8cwzz4iFCxeK11577brH2NnZCSGubDlaV1cnhLiyVaq/v7/QaDSioKBAABD79u0TQggxe/Zs8eabb4q2tjZx2223ifLyciGEEJs2bRKzZ88WQggxc+ZM8eWXX17ztV5++WXx5ptvCiGEkMvlQiaTicbGRtHQ0CBCQkJEdna2KCgoEBKJRGRmZl633qqqqvY/P/rooyI9PV0IIUROTo4YMmSI+Pnnn0VERIRobW0VQvyxI5dcLhfjx49vf25NTc0Nv3eLFi0Sr7zyyg2PISLqSpzZus/slStXCqlUKry9vY1ym3bSjoW+Azz1LsuWLUN0dDRsbGzw3nvv3fBYIQReeOEF7N27F2ZmZigtLUVZWRkAwMfHByNGjAAAPProo3jvvfcwYcIE5OTk4M477wQAqNVqeHp6al3bvn378MADD8DOzg4A8OCDD+KXX35BQkICBg0ahLi4uOs+b/fu3fjPf/4DhUKB6upqhIaGYtKkSQgNDcX06dNx3333ITMzE1ZWVlc9TyqV4sKFC3jiiScwceJE3HXXXR3WlpqaCrlcjoyMDK37ISK6VZzZf9B2Zi9atAiLFi3Chg0bsGLFCqSkpGjdExkPBmjqUVVVVWhsbIRSqURLS0v74Lue9evXo6KiAllZWbC0tISvry9aWloA4Jq3xSQSCYQQCA0NRWZmZpfX3VGdLS0tWLhwIeRyOXx8fLB8+fL2GgHg5MmTcHR0RHl5+TXPdXJywvHjx/Hjjz9i1apV2Lx5Mz755JNrjtuxYwdeffVVZGRkwNrauuuaIiK6Cc7sP2g7s3+XlJSExx577NabIYPENdDUoxYsWIBXXnkF06ZNw9KlS294bF1dHdzd3WFpaYndu3dfdQeKoqKi9qG7YcMGjBw5EkFBQaioqGj/vFKpRG5urta1jRo1Ct988w0UCgWamprw9ddfY9SoUTd8zu+D19XVFY2NjVddNb5161ZUV1dj7969eOKJJ1BbW3vVcysrK6HRaPDQQw9hxYoVyM7Ovub1jx49igULFiA9PR3u7u5a90JE1BU4s/+gzczOy8tr//P333+PwMBArfsh48Iz0NRj1q1bB0tLS0ydOhVqtRq33347du3ahXHjxl33+GnTpmHSpEkYOnQooqKiMGTIkPbHgoKC8MEHHyA5ORkhISF47LHHYGVlhS1btuDJJ59EXV0dVCoVnnrqKYSGhmpV37BhwzBr1izExMQAuHLrosjISBQWFnb4HEdHR8ybNw8ymQweHh6Ijo4GcGXQPvfcc9i5cyd8fHzw+OOPY/HixVe9lVdaWorZs2e3XyH+73//+5rXf/bZZ9HY2IjJkycDAAYOHIj09HSt+iEiuhWc2brP7JUrV2LHjh2wtLSEk5MTl2+YMIkQQui7CCIiIiIiY8ElHEREREREOmCAJiIiIiLSAQM0EREREZEOGKCJiIiIiHTAAE1EREREpAMGaCIiIiIiHTBAExERERHp4P8DSlPMv6lxyOQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x864 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2, figsize=(12, 12))\n",
    "fig.set_facecolor('#ffffff')\n",
    "ax0.plot(x,y1)\n",
    "ax1.plot(x,y2)\n",
    "ax2.plot(x,y3)\n",
    "ax3.plot(x,y3)\n",
    "\n",
    "ax0.set_xlabel('x label for axis 0')\n",
    "ax1.set_xlabel('x label for axis 1')\n",
    "ax2.set_xlabel('x label for axis 2')\n",
    "ax3.set_xlabel('x label for axis 3')\n",
    "\n",
    "ax0.set_ylabel('y label for axis 0')\n",
    "ax1.set_ylabel('y label for axis 1')\n",
    "ax2.set_ylabel('y label for axis 2')\n",
    "ax3.set_ylabel('y label for axis 3')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c07b79f6",
   "metadata": {},
   "source": [
    "<p style=\"font-size: 16px; line-height:2.0;\">ตัวอย่างข้างต้นเป็นการใช้คำสั่ง <font face='Monaco' style=\"font-size:15px\">set_xlabel</font> และ <font face='Monaco' style=\"font-size:15px\">set_ylabel</font> ในการเขียนคำบรรยายแกน <font face='Monaco' style=\"font-size:15px\">x</font> และ <font face='Monaco' style=\"font-size:15px\">y</font> ตามลำดับ</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4b588fc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}