From 3e0e6db4303ccb9994b4c74cc97aface6ee2c03d Mon Sep 17 00:00:00 2001 From: betich Date: Sun, 20 Nov 2022 14:54:51 +0700 Subject: [PATCH] hw4 --- .DS_Store | Bin 8196 -> 8196 bytes grader/week11.ipynb | 241 +++ grader/week12.ipynb | 188 ++ hw/.DS_Store | Bin 6148 -> 6148 bytes hw/hw3/output_boom.txt | 1923 +++++++++++++++++ hw/hw3/test.ipynb | 39 + .../HW4_graph_social_network_toStudent.ipynb | 704 ++++++ hw/hw4/liked_pages.txt | 5 + hw/hw4/social_network.txt | 12 + hw/hw4/sol_social_network_0.txt | 1 + hw/hw4/sol_social_network_1.txt | 1 + hw/hw4/sol_social_network_2.txt | 1 + hw/hw4/sol_social_network_3.txt | 1 + hw/hw4/sol_social_network_4.txt | 1 + hw/hw4/sol_social_network_5.txt | 1 + hw/hw4/sol_social_network_6.txt | 1 + hw/hw4/sol_social_network_7.txt | 1 + hw/hw4/sol_social_network_8.txt | 1 + hw/hw4/sol_social_network_9.txt | 1 + hw/hw4/test_social_network_0.txt | 2 + hw/hw4/test_social_network_1.txt | 3 + hw/hw4/test_social_network_2.txt | 1 + hw/hw4/test_social_network_3.txt | 26 + hw/hw4/test_social_network_4.txt | 23 + hw/hw4/test_social_network_5.txt | 14 + hw/hw4/test_social_network_6.txt | 4 + hw/hw4/test_social_network_7.txt | 1 + hw/hw4/test_social_network_8.txt | 48 + hw/hw4/test_social_network_9.txt | 20 + result.txt | 0 ...340\270\232\340\270\262\340\270\224.ipynb" | 632 ++++++ 31 files changed, 3896 insertions(+) create mode 100644 grader/week11.ipynb create mode 100644 grader/week12.ipynb create mode 100644 hw/hw3/output_boom.txt create mode 100644 hw/hw4/HW4_graph_social_network_toStudent.ipynb create mode 100644 hw/hw4/liked_pages.txt create mode 100644 hw/hw4/social_network.txt create mode 100644 hw/hw4/sol_social_network_0.txt create mode 100644 hw/hw4/sol_social_network_1.txt create mode 100644 hw/hw4/sol_social_network_2.txt create mode 100644 hw/hw4/sol_social_network_3.txt create mode 100644 hw/hw4/sol_social_network_4.txt create mode 100644 hw/hw4/sol_social_network_5.txt create mode 100644 hw/hw4/sol_social_network_6.txt create mode 100644 hw/hw4/sol_social_network_7.txt create mode 100644 hw/hw4/sol_social_network_8.txt create mode 100644 hw/hw4/sol_social_network_9.txt create mode 100644 hw/hw4/test_social_network_0.txt create mode 100644 hw/hw4/test_social_network_1.txt create mode 100644 hw/hw4/test_social_network_2.txt create mode 100644 hw/hw4/test_social_network_3.txt create mode 100644 hw/hw4/test_social_network_4.txt create mode 100644 hw/hw4/test_social_network_5.txt create mode 100644 hw/hw4/test_social_network_6.txt create mode 100644 hw/hw4/test_social_network_7.txt create mode 100644 hw/hw4/test_social_network_8.txt create mode 100644 hw/hw4/test_social_network_9.txt delete mode 100644 result.txt create mode 100644 "thai/HW5_\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\243\340\270\260\340\270\232\340\270\262\340\270\224.ipynb" diff --git a/.DS_Store b/.DS_Store index af2e9dd871ba2c6e1dbfcae1fa343642d6d6ff88..8fca660a02d04580d3d80b49e90f67689c676bc1 100644 GIT binary patch delta 126 zcmZp1XmOa}&nUk!U^hRb{AM132-e9df(;yo#uhpX#+DY7dqt!tvkR$Ajux#DWnm~` i$Y4lh$Seyk%FD^mOJ`tUVBDDK&$yXgB9?T0K8yfu?jbS& delta 40 qcmZp1XmOa}&nUYwU^hRb>}DQ;2-e9aV)+|WO_(;bOT 0 else \"None\")\n", + "\n", + "exec(input().strip())\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## [10_NumPy_24] 11_NumPy_★★_Peak_Indexes" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "def peak_indexes(x):\n", + " # x is an array containing values\n", + " # return an array listing indexes of “peaks”\n", + " pass\n", + "\n", + "def main():\n", + " d = np.array([float(e) for e in input().split()])\n", + " pos = peak_indexes(np.array(d))\n", + " if len(pos) > 0:\n", + " print(\", \".join([str(e) for e in pos]))\n", + " else:\n", + " print(\"No peaks\")\n", + "\n", + "exec(input().strip()) # Don't remove this line\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.10 64-bit", + "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": "3.9.10" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/grader/week12.ipynb b/grader/week12.ipynb new file mode 100644 index 0000000..d4e2b52 --- /dev/null +++ b/grader/week12.ipynb @@ -0,0 +1,188 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## [12_Class_21] 12_Class-★★-Complex-Number" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3+4i\n" + ] + } + ], + "source": [ + "class Complex:\n", + " def __init__(self, a: int, b: int):\n", + " self.a = a\n", + " self.b = b\n", + "\n", + " def __str__(self):\n", + " real = self.a if self.a != 0 else ''\n", + " imag = f'{\"+\" if self.b > 0 else \"\"}{self.b}i' if self.b != 0 else ''\n", + " return \"{}{}\".format(real, imag)\n", + "\n", + " def __add__(self, rhs: 'Complex') -> 'Complex':\n", + " return Complex(self.a + rhs.a, self.b + rhs.b)\n", + "\n", + " def __mul__(self, rhs: 'Complex') -> 'Complex':\n", + " return Complex((self.a * rhs.a) - (self.b * rhs.b), (self.a * rhs.b) + (self.b * rhs.a))\n", + "\n", + " def __truediv__(self, rhs: 'Complex') -> 'Complex':\n", + " return Complex(((self.a * rhs.a) + (self.b * rhs.b)) / ((rhs.a ** 2) + (rhs.b ** 2)), ((self.b * rhs.a) - (self.a * rhs.b)) / ((rhs.a ** 2) + (rhs.b ** 2)))\n", + "\n", + "t,a,b,c,d = map(int, input().split())\n", + "# t,a,b,c,d = 1,3,4,5,6\n", + "# t,a,b,c,d = 2,3,4,5,6\n", + "# t,a,b,c,d = 1,-3,3,3,-3\n", + "# t,a,b,c,d = 3,3,4,5,6\n", + "# t,a,b,c,d = 4,3,1,2,1\n", + "# t,a,b,c,d = 5,3,1,2,1\n", + "\n", + "c1 = Complex(a,b)\n", + "c2 = Complex(c,d)\n", + "\n", + "if t == 1:\n", + " print(c1)\n", + "elif t == 2:\n", + " print(c2)\n", + "elif t == 3:\n", + " print(c1 + c2)\n", + "elif t == 4:\n", + " print(c1 * c2)\n", + "else:\n", + " print(c1 / c2)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## [12_Class_22] 12_Class-★★-Card" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "10\n", + "10\n", + "3\n", + "8\n", + "2\n", + "6\n", + "7\n", + "10\n", + "1\n", + "10\n", + "----------\n", + "0\n", + "3\n", + "1\n", + "0\n", + "8\n", + "3\n", + "7\n", + "1\n", + "1\n", + "----------\n", + "(3 heart)\n", + "(6 club)\n", + "(7 heart)\n", + "(8 heart)\n", + "(10 club)\n", + "(J diamond)\n", + "(K diamond)\n", + "(Q heart)\n", + "(A diamond)\n", + "(2 diamond)\n" + ] + } + ], + "source": [ + "class Card:\n", + " def __init__(self, value, suit):\n", + " self.value = value\n", + " self.suit = suit\n", + " def __str__(self):\n", + " return \"({} {})\".format(self.value, self.suit)\n", + " def getScore(self):\n", + " VALUES = (\"A\", \"2\", \"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\", \"10\", \"J\", \"Q\", \"K\") \n", + "\n", + " if self.value in \"JQK\":\n", + " return 10\n", + " else:\n", + " return VALUES.index(self.value)+1\n", + " def sum(self, other):\n", + " return (self.getScore() + other.getScore()) % 10\n", + " def __lt__(self, rhs):\n", + " SUITS = (\"club\", \"diamond\", \"heart\", \"spade\")\n", + " VALUES = (\"3\", \"4\", \"5\", \"6\", \"7\", \"8\", \"9\", \"10\", \"J\", \"Q\", \"K\", \"A\", \"2\")\n", + "\n", + " a_score = self.getScore()\n", + " b_score = rhs.getScore()\n", + "\n", + " if a_score == b_score:\n", + " return SUITS.index(self.suit) < SUITS.index(rhs.suit)\n", + " else:\n", + " return VALUES.index(self.value) < VALUES.index(rhs.value)\n", + "\n", + "n = int(input())\n", + "cards = []\n", + "for i in range(n):\n", + " value, suit = input().split()\n", + " cards.append(Card(value, suit))\n", + "for i in range(n):\n", + " print(cards[i].getScore())\n", + "print(\"----------\")\n", + "for i in range(n-1):\n", + " print(Card.sum(cards[i], cards[i+1]))\n", + "print(\"----------\")\n", + "cards.sort()\n", + "for i in range(n):\n", + " print(cards[i])" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.10 64-bit", + "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": "3.9.10" + }, + "orig_nbformat": 4, + "vscode": { + "interpreter": { + "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/hw/.DS_Store b/hw/.DS_Store index 28e5a5b3596879ebe9752c43582df7bf4315431d..59f3696dd260e59466a598f54b0008c6429b6f7e 100644 GIT binary patch delta 21 ccmZoMXffC@jgiC1&`3wY$k=l8JjOIJ07hR11poj5 delta 21 ccmZoMXffC@jgdpw!dyqe(9&%4JjOIJ07kh64gdfE diff --git a/hw/hw3/output_boom.txt b/hw/hw3/output_boom.txt new file mode 100644 index 0000000..ae0a91a --- /dev/null +++ b/hw/hw3/output_boom.txt @@ -0,0 +1,1923 @@ +923 +1 8 +2 8 +3 8 +4 8 +5 5 +6 8 +7 5 +8 5 +9 5 +10 5 +11 8 +12 5 +13 5 +14 5 +15 5 +16 5 +17 8 +18 8 +19 5 +20 5 +21 8 +22 5 +23 5 +24 5 +25 5 +26 5 +27 5 +28 5 +29 5 +30 5 +31 5 +32 5 +33 5 +34 5 +35 5 +36 5 +37 5 +38 5 +39 5 +40 5 +41 5 +42 5 +43 5 +44 5 +45 5 +46 5 +47 8 +48 5 +49 5 +50 5 +51 5 +52 5 +53 5 +54 5 +55 5 +56 5 +57 5 +58 5 +59 5 +60 5 +61 5 +62 5 +63 5 +64 5 +65 5 +66 5 +67 5 +68 5 +69 5 +70 5 +71 5 +72 5 +73 5 +74 5 +75 7 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+1140 8 +1141 8 +1 {'title': 'Guardians of the Galaxy', 'genre': 'Action', 'votes': 704613.0, 'rating': 8.1, 'release_year': 2014, 'plot': 'A group of intergalactic criminals must pull together to stop a fanatical warrior with plans to purge the universe.', 'poster': 'https://m.media-amazon.com/images/M/MV5BMTAwMjU5OTgxNjZeQTJeQWpwZ15BbWU4MDUxNDYxODEx._V1_SX300.jpg', 'ibmdb_id': 'tt2015381'} +2 {'title': 'Interstellar', 'genre': 'Adventure', 'votes': 961763.0, 'rating': 8.6, 'release_year': 2014, 'plot': "A team of explorers travel through a wormhole in space in an attempt to ensure humanity's survival.", 'poster': 'https://m.media-amazon.com/images/M/MV5BZjdkOTU3MDktN2IxOS00OGEyLWFmMjktY2FiMmZkNWIyODZiXkEyXkFqcGdeQXVyMTMxODk2OTU@._V1_SX300.jpg', 'ibmdb_id': 'tt0816692'} +3 {'title': 'The Grand Budapest Hotel', 'genre': 'Adventure', 'votes': 492158.0, 'rating': 8.1, 'release_year': 2014, 'plot': "A writer encounters the owner of an aging high-class hotel,who tells him of his early 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+Mystery 6 +N/A 18 +News 1 +Reality-TV 15 +Romance 2 +Short 35 +Sport 3 +Talk-Show 1 +Thriller 5 +Western 8 +Action [1, 6, 7, 9, 10, 12, 13, 15, 19, 20, 21, 22, 24, 25, 26, 27, 35, 36, 39, 41, 45, 48, 56, 57, 59, 60, 62, 63, 69, 74, 76, 80, 82, 99, 101, 104, 107, 108, 112, 113, 119, 120, 124, 129, 137, 140, 141, 142, 152, 161, 163, 168, 172, 173, 175, 180, 181, 195, 197, 198, 199, 201, 204, 208, 212, 214, 219, 220, 221, 222, 225, 226, 231, 232, 233, 238, 240, 248, 250, 252, 253, 256, 262, 264, 265, 267, 268, 272, 276, 278, 279, 280, 283, 284, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 301, 304, 309, 312, 316, 317, 319, 325, 328, 332, 334, 339, 341, 343, 344, 345, 348, 351, 354, 358, 360, 361, 364, 365, 372, 376, 379, 386, 390, 394, 397, 425, 473, 494, 527, 542, 581, 586, 590, 592, 648, 650, 666, 677, 697, 728, 731, 733, 737, 761, 783, 785, 797, 807, 831, 836, 892, 898, 900, 905, 915, 923, 932, 940, 961, 972, 980, 981, 982, 988, 1057, 1062, 1075, 1076, 1078, 1080, 1082, 1083, 1097, 1101, 1126, 1137] +Adventure [2, 3, 18, 29, 47, 89, 102, 109, 121, 144, 151, 166, 170, 171, 176, 207, 217, 223, 239, 244, 255, 305, 307, 310, 322, 338, 367, 369, 370, 392, 454, 466, 475, 482, 497, 498, 570, 582, 633, 637, 659, 771, 779, 893, 911, 916, 1112, 1115, 1127] +Animation [23, 42, 46, 127, 165, 178, 191, 200, 210, 218, 230, 257, 258, 271, 308, 313, 335, 353, 359, 374, 410, 412, 418, 436, 467, 471, 480, 481, 488, 501, 504, 601, 607, 611, 624, 625, 682, 812, 813, 931, 946, 1007, 1011, 1021, 1023, 1091] +Biography [5, 16, 50, 51, 88, 103, 106, 111, 114, 123, 128, 135, 145, 182, 183, 209, 224, 227, 243, 247, 261, 263, 274, 321, 340, 346, 479, 485, 492, 543, 698, 930, 1099, 1134] +Comedy [31, 34, 40, 43, 53, 54, 66, 67, 68, 71, 75, 77, 79, 81, 83, 87, 91, 98, 118, 136, 148, 149, 155, 159, 169, 177, 179, 185, 187, 189, 190, 193, 196, 205, 211, 213, 249, 251, 260, 266, 269, 273, 275, 298, 299, 318, 320, 323, 324, 326, 327, 331, 333, 350, 352, 363, 375, 378, 380, 381, 382, 389, 403, 408, 411, 413, 415, 421, 422, 424, 441, 445, 462, 464, 465, 469, 470, 474, 478, 484, 496, 505, 508, 510, 513, 522, 549, 551, 555, 561, 571, 574, 584, 593, 602, 604, 616, 622, 626, 631, 642, 652, 654, 656, 660, 662, 663, 665, 668, 671, 675, 683, 685, 686, 691, 695, 707, 716, 718, 721, 739, 741, 751, 763, 764, 765, 767, 770, 772, 773, 781, 786, 789, 791, 792, 798, 801, 802, 806, 814, 815, 818, 822, 830, 832, 863, 875, 880, 889, 904, 908, 909, 917, 920, 926, 947, 978, 1002, 1028, 1041, 1047, 1060, 1074, 1079, 1081, 1085, 1086, 1090, 1094, 1114, 1120, 1138] +Crime [4, 28, 37, 70, 85, 92, 95, 110, 134, 194, 203, 216, 236, 241, 246, 281, 311, 315, 342, 347, 393, 398, 400, 477, 506, 537, 587, 605, 643, 657, 661, 669, 676, 688, 689, 709, 736, 743, 749, 776, 847, 921, 1087, 1088, 1108, 1118, 1119, 1122, 1135] +Documentary [395, 434, 443, 459, 460, 540, 548, 558, 577, 579, 606, 609, 614, 620, 634, 646, 653, 655, 664, 670, 672, 673, 678, 719, 723, 725, 726, 727, 729, 735, 752, 769, 777, 780, 787, 799, 823, 827, 838, 844, 860, 861, 862, 870, 877, 886, 907, 910, 918, 922, 924, 936, 941, 974, 975, 983, 986, 996, 1020, 1025, 1026, 1031, 1044, 1049, 1051, 1059, 1070, 1093, 1096, 1102] +Drama [11, 17, 33, 38, 44, 49, 52, 58, 72, 86, 90, 93, 96, 97, 100, 115, 116, 117, 122, 125, 126, 131, 132, 133, 138, 139, 143, 147, 150, 153, 156, 157, 158, 160, 162, 164, 167, 184, 186, 188, 192, 202, 215, 234, 235, 237, 245, 254, 270, 277, 282, 297, 306, 314, 329, 368, 388, 391, 416, 419, 423, 428, 437, 440, 442, 444, 448, 452, 455, 472, 483, 487, 489, 490, 493, 495, 502, 503, 512, 514, 515, 520, 533, 546, 552, 556, 559, 560, 562, 572, 576, 588, 591, 612, 613, 615, 617, 619, 621, 627, 644, 667, 680, 681, 693, 694, 701, 706, 710, 713, 734, 758, 768, 778, 782, 800, 808, 821, 824, 835, 857, 873, 874, 883, 885, 902, 903, 906, 913, 914, 919, 927, 929, 937, 939, 942, 963, 965, 971, 976, 979, 1024, 1032, 1043, 1066, 1069, 1071, 1084, 1089, 1111, 1113, 1121, 1123, 1124, 1128, 1132, 1133, 1136, 1140, 1141] +Family [302, 456, 463, 486, 573, 594, 595, 597, 746, 997, 1010, 1052] +Fantasy [1139] +Game-Show [1037, 1045] +History [568, 878] +Horror [8, 14, 30, 32, 55, 61, 64, 73, 84, 94, 105, 146, 206, 228, 242, 259, 366, 371, 399, 476, 491, 519, 569, 585, 603, 618, 649, 760, 762, 897, 912, 925, 928] +Music [362, 658, 712, 722, 724, 775, 859, 876, 951, 1034, 1054] +Musical [600, 651] +Mystery [65, 174, 384, 387, 461, 623] +N/A [499, 526, 610, 700, 720, 804, 825, 849, 853, 858, 887, 952, 969, 970, 1016, 1068, 1104, 1110] +News [1000] +Reality-TV [674, 732, 784, 790, 934, 977, 984, 990, 1036, 1038, 1040, 1042, 1100, 1103, 1109] +Romance [553, 882] +Short [78, 417, 435, 450, 453, 468, 507, 516, 517, 518, 521, 525, 547, 557, 628, 629, 632, 638, 704, 829, 833, 834, 841, 856, 881, 935, 1005, 1006, 1008, 1012, 1015, 1030, 1033, 1092, 1125] +Sport [550, 955, 959] +Talk-Show [896] +Thriller [130, 154, 554, 989, 1116] +Western [229, 296, 528, 793, 888, 890, 894, 938] +Action {'num': 186, 'rating': 6.51, 'votes': 187336.3} +Adventure {'num': 49, 'rating': 6.62, 'votes': 145701.29} +Animation {'num': 46, 'rating': 7.12, 'votes': 58185.52} +Biography {'num': 34, 'rating': 7.22, 'votes': 80150.53} +Comedy {'num': 172, 'rating': 6.22, 'votes': 40237.16} +Crime {'num': 49, 'rating': 6.55, 'votes': 135958.43} +Documentary {'num': 70, 'rating': 7.26, 'votes': 376.87} +Drama {'num': 160, 'rating': 6.76, 'votes': 66104.36} +Family {'num': 12, 'rating': 6.55, 'votes': 29724.83} +Fantasy {'num': 1, 'rating': 8.8, 'votes': 1500090.0} +Game-Show {'num': 2, 'rating': 4.3, 'votes': 81.5} +History {'num': 2, 'rating': 7.65, 'votes': 23.5} +Horror {'num': 33, 'rating': 5.93, 'votes': 41901.18} +Music {'num': 11, 'rating': 7.71, 'votes': 182.0} +Musical {'num': 2, 'rating': 5.5, 'votes': 20.5} +Mystery {'num': 6, 'rating': 5.58, 'votes': 20790.0} +N/A {'num': 18, 'rating': 6.55, 'votes': 46.0} +News {'num': 1, 'rating': 6.1, 'votes': 39.0} +Reality-TV {'num': 15, 'rating': 5.3, 'votes': 515.93} +Romance {'num': 2, 'rating': 6.65, 'votes': 373.0} +Short {'num': 35, 'rating': 6.52, 'votes': 608.94} +Sport {'num': 3, 'rating': 7.87, 'votes': 19.0} +Talk-Show {'num': 1, 'rating': 7.0, 'votes': 5.0} +Thriller {'num': 5, 'rating': 6.0, 'votes': 5891.4} +Western {'num': 8, 'rating': 5.77, 'votes': 36223.75} \ No newline at end of file diff --git a/hw/hw3/test.ipynb b/hw/hw3/test.ipynb index 3f4a4f1..d100818 100644 --- a/hw/hw3/test.ipynb +++ b/hw/hw3/test.ipynb @@ -79,6 +79,45 @@ " print('Comparing {} and {}...'.format(file1, file2))\n", " print(compare_csv(file1, file2))" ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def check_all():\n", + " with open('output_thee.txt', 'r') as t1, open('output_boom.txt', 'r') as t2:\n", + " fileone = t1.readlines()\n", + " filetwo = t2.readlines()\n", + "\n", + " if len(fileone) == len(filetwo):\n", + " for line1, line2 in zip(fileone, filetwo):\n", + " if line1 != line2:\n", + " print(line1, line2, sep=\"\\n===========\\n\")\n", + " else:\n", + " print('Files are not the same length')\n", + "\n", + "\n", + "def check_one_line(line_number):\n", + " line_number -= 1\n", + " with open('output_tee.txt', 'r') as t1, open('output_tee.txt', 'r') as t2:\n", + " fileone = t1.readlines()\n", + " filetwo = t2.readlines()\n", + "\n", + " if len(fileone) == len(filetwo):\n", + " print(fileone[line_number], filetwo[line_number])\n", + " for x, y in zip(fileone[line_number].split(','), filetwo[line_number].split(',')):\n", + " if x != y:\n", + " print(x, y, sep=\"\\n===========\\n\")\n", + " break\n", + " else:\n", + " print('Files are not the same length')\n", + "\n", + "\n", + "# check_one_line(1878)\n", + "check_all()" + ] } ], "metadata": { diff --git a/hw/hw4/HW4_graph_social_network_toStudent.ipynb b/hw/hw4/HW4_graph_social_network_toStudent.ipynb new file mode 100644 index 0000000..7e76ef8 --- /dev/null +++ b/hw/hw4/HW4_graph_social_network_toStudent.ipynb @@ -0,0 +1,704 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "xaO6ydwuTSae" + }, + "source": [ + "# Assignment #4: NumPy + A few tuples/lists\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tZly7h79NP4H" + }, + "source": [ + "### In this assignment, we will practice on NumPy, Tuple, Set, Dict using social network use case. \n", + "\n", + "**Please read the explanation in \"H4.docx\"**" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YAq-m9r53V0E" + }, + "source": [ + "# **Important**\n", + "- Do not delete or modify the first line in the given code cell.\n", + "- You work must be add in the provided area only. \n", + "- You must not change the declaration of the provided functions.\n", + "- You are allowed to add your own functions.\n", + "- If you want to write your own program to test, add new code cell at the very end of the file and add your code there.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "3-zuAAWzWzyu" + }, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "id": "i-ag1K690HGa" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(array([[0, 1, 0, 1, 1],\n", + " [1, 0, 0, 1, 0],\n", + " [0, 0, 0, 0, 1],\n", + " [1, 1, 0, 0, 1],\n", + " [1, 0, 1, 1, 0]]), ['A', 'B', 'C', 'D', 'E'])\n" + ] + } + ], + "source": [ + "# DO NOTE DELETE THIS CELL / WRITE YOUR CODE HERE\n", + "# Task#1\n", + "\n", + "def generate_adjacency_matrix(filename):\n", + " # write your code here\n", + " f = open(filename, 'r')\n", + " lines = f.readlines()\n", + " f.close()\n", + "\n", + " nodes = set()\n", + "\n", + " # get the number of nodes\n", + " for l in lines:\n", + " new_nodes = l.strip().split(',')\n", + " nodes.add(new_nodes[0])\n", + " nodes.add(new_nodes[1])\n", + "\n", + " person_names = sorted(list(nodes))\n", + " \n", + " # create the adjacency matrix\n", + " A = np.zeros((len(nodes), len(nodes)), dtype=int)\n", + " for l in lines:\n", + " new_nodes = l.strip().split(',')\n", + " first_node = person_names.index(new_nodes[0])\n", + " second_node = person_names.index(new_nodes[1])\n", + " A[first_node, second_node] = 1\n", + " A[second_node, first_node] = 1\n", + "\n", + " return A, person_names" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "xdRdI95_UnLu", + "outputId": "74409220-1a33-4525-f1ac-be9ca8f0c544" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0 1 0 1 1]\n", + " [1 0 0 1 0]\n", + " [0 0 0 0 1]\n", + " [1 1 0 0 1]\n", + " [1 0 1 1 0]]\n", + "['A', 'B', 'C', 'D', 'E']\n", + "False\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "from google.colab import files\n", + "uploaded = files.upload()\n", + "print('uploaded = ', uploaded)\n", + "\"\"\"\n", + "A, person_names = generate_adjacency_matrix(\"social_network.txt\")\n", + "print(A)\n", + "print(person_names)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test 0 passed\n", + "Test 1 passed\n", + "Test 2 passed\n", + "Test 3 passed\n", + "Test 4 passed\n", + "Test 5 passed\n", + "Test 6 passed\n", + "Test 7 passed\n", + "Test 8 passed\n", + "Test 9 passed\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import random\n", + "\n", + "def generate_graph(n: int) -> np.ndarray:\n", + " graph = np.zeros((n,n), dtype=int)\n", + " for i in range(n):\n", + " for j in range(n):\n", + " if i == j:\n", + " graph[i][j] = 0\n", + " else:\n", + " graph[i][j] = random.randint(0,1)\n", + " graph[j][i] = graph[i][j]\n", + "\n", + " # check if there is an entry at dimension n\n", + " if np.sum(graph[n-1]) == 0:\n", + " graph[n-1][n-1] = 1\n", + " return graph\n", + "\n", + "def generate_edges(graph: np.ndarray) -> list:\n", + " edges = []\n", + " for i in range(len(graph)):\n", + " for j in range(len(graph)):\n", + " if graph[i][j] == 1:\n", + " edges.append(str(i) + \",\" + str(j))\n", + " return edges\n", + "\n", + "def main():\n", + " # generate\n", + " for i in range(10):\n", + " n = random.randint(1,10)\n", + " graph = generate_graph(n)\n", + " edges = generate_edges(graph)\n", + " # write edges to file\n", + " f = open(\"test_social_network_{}.txt\".format(i), \"w\")\n", + " \n", + " for e in edges:\n", + " f.write(e + \"\\n\")\n", + " f.close()\n", + "\n", + " f2 = open(\"sol_social_network_{}.txt\".format(i), \"w\")\n", + " f2.write(str(graph.tolist()))\n", + " f2.close()\n", + "\n", + " # test\n", + " for i in range(10):\n", + " A, person_names = generate_adjacency_matrix(\"test_social_network_{}.txt\".format(i))\n", + " f = open(\"sol_social_network_{}.txt\".format(i), \"r\")\n", + " sol = np.array(eval(f.read().strip()))\n", + " f.close()\n", + " if np.array_equal(A, sol):\n", + " print(\"Test {} passed\".format(i))\n", + " else:\n", + " print(\"Test {} failed\".format(i))\n", + " print(\"A = \", A)\n", + " print(\"sol = \", sol)\n", + " \n", + "\n", + "if __name__ == \"__main__\":\n", + " main()" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "===\n", + "Test#0\n", + "===\n", + "[[0 0 1 1]\n", + " [0 0 1 1]\n", + " [1 1 0 1]\n", + " [1 1 1 0]]\n", + "['0', '1', '3', '4']\n", + "[[0 0 0 1 1]\n", + " [0 0 0 1 1]\n", + " [0 0 0 0 0]\n", + " [1 1 0 0 1]\n", + " [1 1 0 1 0]]\n", + "===\n", + "Test#1\n", + "===\n", + "[[0 1 0 0 1]\n", + " [1 0 1 0 0]\n", + " [0 1 0 1 1]\n", + " [0 0 1 0 1]\n", + " [1 0 1 1 0]]\n", + "['0', '1', '2', '3', '4']\n", + "[[0 1 0 0 1]\n", + " [1 0 1 0 0]\n", + " [0 1 0 1 1]\n", + " [0 0 1 0 1]\n", + " [1 0 1 1 0]]\n", + "===\n", + "Test#2\n", + "===\n", + "[[0 1 0 1 0]\n", + " [1 0 1 0 1]\n", + " [0 1 0 0 1]\n", + " [1 0 0 0 1]\n", + " [0 1 1 1 0]]\n", + "['0', '1', '2', '3', '4']\n", + "[[0 1 0 1 0]\n", + " [1 0 1 0 1]\n", + " [0 1 0 0 1]\n", + " [1 0 0 0 1]\n", + " [0 1 1 1 0]]\n", + "===\n", + "Test#3\n", + "===\n", + "[[0 1 0 0 0]\n", + " [1 0 0 0 1]\n", + " [0 0 0 1 1]\n", + " [0 0 1 0 1]\n", + " [0 1 1 1 0]]\n", + "['0', '1', '2', '3', '4']\n", + "[[0 1 0 0 0]\n", + " [1 0 0 0 1]\n", + " [0 0 0 1 1]\n", + " [0 0 1 0 1]\n", + " [0 1 1 1 0]]\n", + "===\n", + "Test#4\n", + "===\n", + "[[0 0 1 0]\n", + " [0 0 1 0]\n", + " [1 1 0 1]\n", + " [0 0 1 0]]\n", + "['0', '1', '3', '4']\n", + "[[0 0 0 1 0]\n", + " [0 0 0 1 0]\n", + " [0 0 0 0 0]\n", + " [1 1 0 0 1]\n", + " [0 0 0 1 0]]\n", + "===\n", + "Test#5\n", + "===\n", + "[[0 1 1 1]\n", + " [1 0 1 1]\n", + " [1 1 0 1]\n", + " [1 1 1 0]]\n", + "['0', '1', '2', '4']\n", + "[[0 1 1 0 1]\n", + " [1 0 1 0 1]\n", + " [1 1 0 0 1]\n", + " [0 0 0 0 0]\n", + " [1 1 1 0 0]]\n", + "===\n", + "Test#6\n", + "===\n", + "[[0 1 1 0]\n", + " [1 0 1 1]\n", + " [1 1 0 0]\n", + " [0 1 0 0]]\n", + "['0', '2', '3', '4']\n", + "[[0 0 1 1 0]\n", + " [0 0 0 0 0]\n", + " [1 0 0 1 1]\n", + " [1 0 1 0 0]\n", + " [0 0 1 0 0]]\n", + "===\n", + "Test#7\n", + "===\n", + "[[0 1 0]\n", + " [1 0 1]\n", + " [0 1 0]]\n", + "['0', '1', '4']\n", + "[[0 1 0 0 0]\n", + " [1 0 0 0 1]\n", + " [0 0 0 0 0]\n", + " [0 0 0 0 0]\n", + " [0 1 0 0 0]]\n", + "===\n", + "Test#8\n", + "===\n", + "[[0 0 1 0]\n", + " [0 0 1 1]\n", + " [1 1 0 1]\n", + " [0 1 1 0]]\n", + "['0', '2', '3', '4']\n", + "[[0 0 0 1 0]\n", + " [0 0 0 0 0]\n", + " [0 0 0 1 1]\n", + " [1 0 1 0 1]\n", + " [0 0 1 1 0]]\n", + "===\n", + "Test#9\n", + "===\n", + "[[0 1 1]\n", + " [1 0 0]\n", + " [1 0 0]]\n", + "['0', '1', '2']\n", + "[[0 1 1 0 0]\n", + " [1 0 0 0 0]\n", + " [1 0 0 0 0]\n", + " [0 0 0 0 0]\n", + " [0 0 0 0 0]]\n" + ] + } + ], + "source": [ + "import random\n", + "\n", + "def generate_graph(n):\n", + " graph = [[0 for i in range(n)] for j in range(n)]\n", + " edges = []\n", + " for i in range(n):\n", + " for j in range(i+1, n):\n", + " if random.randint(0, 1) == 1:\n", + " graph[i][j] = 1\n", + " graph[j][i] = 1\n", + " edges.append(str(i) + \",\" + str(j))\n", + "\n", + " return graph, edges\n", + "\n", + "\n", + "for i in range(10):\n", + " graph, edges = generate_graph(5)\n", + " # write edges to file\n", + " f = open(\"test_social_network_{}.txt\".format(i), \"w\")\n", + " for e in edges:\n", + " f.write(e + \"\\n\")\n", + " f.close()\n", + "\n", + " f2 = open(\"sol_social_network_{}.txt\".format(i), \"w\")\n", + " f2.write(str(graph))\n", + " f2.close()\n", + "\n", + "# Test\n", + "for i in range(10):\n", + " A, person_names = generate_adjacency_matrix(\"test_social_network_{}.txt\".format(i))\n", + " print(\"===\\nTest#{}\\n===\".format(i))\n", + " print(A)\n", + " print(person_names)\n", + "\n", + " f = open(\"sol_social_network_{}.txt\".format(i), \"r\")\n", + " sol = np.array(eval(f.read()))\n", + " f.close()\n", + " print(sol)\n", + "\n", + " # assert np.array_equal(A, sol)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "id": "_xds654Yw6Ff" + }, + "outputs": [], + "source": [ + "# DO NOTE DELETE THIS CELL / WRITE YOUR CODE HERE\n", + "# Task#2\n", + "\n", + "def get_degree_matrix(A):\n", + " # write your code here\n", + " D = np.zeros((A.shape[0], A.shape[1]), dtype=int)\n", + " for i in range(A.shape[0]):\n", + " D[i, i] = np.sum(A[i, :])\n", + " return D" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "27xLRQ13Yjb0", + "outputId": "bef98fb4-f6ff-4524-db3c-8f50f809fa17" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[3 0 0 0 0]\n", + " [0 2 0 0 0]\n", + " [0 0 1 0 0]\n", + " [0 0 0 3 0]\n", + " [0 0 0 0 3]]\n" + ] + } + ], + "source": [ + "D = get_degree_matrix(A)\n", + "print(D)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "id": "mZT3meYFZeXa" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('A', 0), ('D', 3), ('E', 4)]\n" + ] + } + ], + "source": [ + "# DO NOTE DELETE THIS CELL / WRITE YOUR CODE HERE\n", + "# Task#3\n", + "\n", + "def get_names_with_highest_number_of_friends(D, person_names):\n", + " # write your code here\n", + " max_count = np.max(D)\n", + " max_count_indices = np.where(D == max_count)[0]\n", + " \n", + " all_max = [(person_names[i], i) for i in max_count_indices]\n", + " return all_max\n", + "\n", + "print(get_names_with_highest_number_of_friends(D, person_names))" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9CuAUZ83bQDp", + "outputId": "a94b088e-c3a2-41fc-cfdd-86d3462e994b" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('A', 0), ('D', 3), ('E', 4)]\n" + ] + } + ], + "source": [ + "persons = get_names_with_highest_number_of_friends(D, person_names)\n", + "print(persons)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "id": "ePneg4VEe03b" + }, + "outputs": [], + "source": [ + "# HELPER FUNCTION\n", + "def get_liked_page_matrix(infile):\n", + " liked_pages = []\n", + " persons = []\n", + " fr = open(infile, 'r')\n", + " for line in fr:\n", + " name, bits = line.strip().split(',')\n", + " liked_page = [int(c) for c in bits]\n", + " liked_pages.append(liked_page)\n", + " persons.append(name)\n", + " liked_pages_array = np.array(liked_pages)\n", + " return liked_pages_array,persons" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "iW6zJIFyiNCM", + "outputId": "756fde61-f520-490f-fe77-1ad43f01adc2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0 1 0 1 1 1 0]\n", + " [1 0 0 1 0 1 1]\n", + " [0 0 0 0 1 0 1]\n", + " [1 1 0 0 1 0 0]\n", + " [0 1 1 1 0 1 0]]\n", + "['A', 'B', 'C', 'D', 'E']\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "from google.colab import files\n", + "uploaded = files.upload()\n", + "print('uploaded = ', uploaded)\n", + "\"\"\"\n", + "liked_pages, persons = get_liked_page_matrix('liked_pages.txt')\n", + "print(liked_pages)\n", + "print(persons)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "id": "-eBjntKTjiVn" + }, + "outputs": [], + "source": [ + "# DO NOTE DELETE THIS CELL / WRITE YOUR CODE HERE\n", + "# Task#4\n", + "\n", + "def get_distance_matrix(Lp):\n", + " # write your code here\n", + " \n", + " # calculate tanimoto distance\n", + " D = np.zeros((Lp.shape[0], Lp.shape[0]), dtype=float)\n", + " for i in range(Lp.shape[0]):\n", + " for j in range(Lp.shape[0]):\n", + " if i == j:\n", + " D[i, j] = 0\n", + " else:\n", + " c = np.sum(np.logical_and(Lp[i, :], Lp[j, :]))\n", + " a = np.sum(Lp[i, :])\n", + " b = np.sum(Lp[j, :])\n", + "\n", + " D[i, j] = c / (a + b - c)\n", + " \n", + " distance_matrix = D\n", + " return distance_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "NfCR8X3zjpvd", + "outputId": "375b039c-51ce-4583-b99f-27d296a54672" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[0. 0.33333333 0.2 0.4 0.6 ]\n", + " [0.33333333 0. 0.2 0.16666667 0.33333333]\n", + " [0.2 0.2 0. 0.25 0. ]\n", + " [0.4 0.16666667 0.25 0. 0.16666667]\n", + " [0.6 0.33333333 0. 0.16666667 0. ]]\n" + ] + } + ], + "source": [ + "Dt = get_distance_matrix(liked_pages)\n", + "print(Dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "id": "PkjAA2hw-I1i" + }, + "outputs": [], + "source": [ + "# DO NOTE DELETE THIS CELL / WRITE YOUR CODE HERE\n", + "# Task#5\n", + "\n", + "def get_all_most_similar_pairs(Dt, persons):\n", + " # write your code here\n", + " max_distance = np.max(Dt)\n", + " max_distance_indices = np.where(Dt == max_distance)\n", + " all_pairs = [(persons[i], persons[j]) for i, j in zip(max_distance_indices[0], max_distance_indices[1])]\n", + "\n", + " pairs = set()\n", + " for p in all_pairs:\n", + " if not tuple(sorted(p)) in pairs:\n", + " pairs.add(tuple(sorted(p)))\n", + " \n", + " return sorted(pairs)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "NuCfMjXb-Z_R", + "outputId": "6b820fcc-aac2-4663-9c65-9ec2f85a535f" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('A', 'E')]\n" + ] + } + ], + "source": [ + "pairs = get_all_most_similar_pairs(Dt, persons)\n", + "print(pairs)" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3.9.10 64-bit", + "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": "3.9.10" + }, + "vscode": { + "interpreter": { + "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e" + } + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/hw/hw4/liked_pages.txt b/hw/hw4/liked_pages.txt new file mode 100644 index 0000000..a947f29 --- /dev/null +++ b/hw/hw4/liked_pages.txt @@ -0,0 +1,5 @@ +A,0101110 +B,1001011 +C,0000101 +D,1100100 +E,0111010 \ No newline at end of file diff --git a/hw/hw4/social_network.txt b/hw/hw4/social_network.txt new file mode 100644 index 0000000..a5b40ed --- /dev/null +++ b/hw/hw4/social_network.txt @@ -0,0 +1,12 @@ +A,B +A,D +A,E +B,A +B,D +C,E +D,A +D,B +D,E +E,A +E,C +E,D \ No newline at end of file diff --git a/hw/hw4/sol_social_network_0.txt b/hw/hw4/sol_social_network_0.txt new file mode 100644 index 0000000..f48fb81 --- /dev/null +++ b/hw/hw4/sol_social_network_0.txt @@ -0,0 +1 @@ +[[0, 1], [1, 0]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_1.txt b/hw/hw4/sol_social_network_1.txt new file mode 100644 index 0000000..2c8752c --- /dev/null +++ b/hw/hw4/sol_social_network_1.txt @@ -0,0 +1 @@ +[[0, 1, 0], [1, 0, 0], [0, 0, 1]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_2.txt b/hw/hw4/sol_social_network_2.txt new file mode 100644 index 0000000..89d00ba --- /dev/null +++ b/hw/hw4/sol_social_network_2.txt @@ -0,0 +1 @@ +[[1]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_3.txt b/hw/hw4/sol_social_network_3.txt new file mode 100644 index 0000000..37f5589 --- /dev/null +++ b/hw/hw4/sol_social_network_3.txt @@ -0,0 +1 @@ +[[0, 0, 1, 0, 0, 0, 0, 1], [0, 0, 1, 1, 0, 1, 0, 0], [1, 1, 0, 0, 0, 0, 1, 1], [0, 1, 0, 0, 1, 1, 0, 1], [0, 0, 0, 1, 0, 0, 1, 1], [0, 1, 0, 1, 0, 0, 1, 0], [0, 0, 1, 0, 1, 1, 0, 0], [1, 0, 1, 1, 1, 0, 0, 0]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_4.txt b/hw/hw4/sol_social_network_4.txt new file mode 100644 index 0000000..a482d1b --- /dev/null +++ b/hw/hw4/sol_social_network_4.txt @@ -0,0 +1 @@ +[[0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 1, 1, 1, 0], [1, 1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 1, 0, 0], [0, 1, 1, 0, 1, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_5.txt b/hw/hw4/sol_social_network_5.txt new file mode 100644 index 0000000..2965ba9 --- /dev/null +++ b/hw/hw4/sol_social_network_5.txt @@ -0,0 +1 @@ +[[0, 0, 0, 0, 1, 1], [0, 0, 1, 0, 0, 0], [0, 1, 0, 1, 1, 0], [0, 0, 1, 0, 0, 1], [1, 0, 1, 0, 0, 1], [1, 0, 0, 1, 1, 0]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_6.txt b/hw/hw4/sol_social_network_6.txt new file mode 100644 index 0000000..98e2311 --- /dev/null +++ b/hw/hw4/sol_social_network_6.txt @@ -0,0 +1 @@ +[[0, 1, 1], [1, 0, 0], [1, 0, 0]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_7.txt b/hw/hw4/sol_social_network_7.txt new file mode 100644 index 0000000..89d00ba --- /dev/null +++ b/hw/hw4/sol_social_network_7.txt @@ -0,0 +1 @@ +[[1]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_8.txt b/hw/hw4/sol_social_network_8.txt new file mode 100644 index 0000000..9312aa8 --- /dev/null +++ b/hw/hw4/sol_social_network_8.txt @@ -0,0 +1 @@ +[[0, 0, 1, 1, 1, 1, 1, 0, 1, 1], [0, 0, 0, 1, 0, 0, 0, 1, 0, 0], [1, 0, 0, 0, 1, 0, 1, 0, 0, 1], [1, 1, 0, 0, 0, 0, 0, 1, 1, 1], [1, 0, 1, 0, 0, 0, 0, 0, 1, 0], [1, 0, 0, 0, 0, 0, 0, 1, 0, 1], [1, 0, 1, 0, 0, 0, 0, 1, 1, 1], [0, 1, 0, 1, 0, 1, 1, 0, 1, 1], [1, 0, 0, 1, 1, 0, 1, 1, 0, 1], [1, 0, 1, 1, 0, 1, 1, 1, 1, 0]] \ No newline at end of file diff --git a/hw/hw4/sol_social_network_9.txt b/hw/hw4/sol_social_network_9.txt new file mode 100644 index 0000000..303ffe3 --- /dev/null +++ b/hw/hw4/sol_social_network_9.txt @@ -0,0 +1 @@ +[[0, 1, 0, 1, 1, 1], [1, 0, 1, 1, 1, 0], [0, 1, 0, 1, 0, 0], [1, 1, 1, 0, 1, 1], [1, 1, 0, 1, 0, 0], [1, 0, 0, 1, 0, 0]] \ No newline at end of file diff --git a/hw/hw4/test_social_network_0.txt b/hw/hw4/test_social_network_0.txt new file mode 100644 index 0000000..6dccc1e --- /dev/null +++ b/hw/hw4/test_social_network_0.txt @@ -0,0 +1,2 @@ +0,1 +1,0 diff --git a/hw/hw4/test_social_network_1.txt b/hw/hw4/test_social_network_1.txt new file mode 100644 index 0000000..ed428f2 --- /dev/null +++ b/hw/hw4/test_social_network_1.txt @@ -0,0 +1,3 @@ +0,1 +1,0 +2,2 diff --git a/hw/hw4/test_social_network_2.txt b/hw/hw4/test_social_network_2.txt new file mode 100644 index 0000000..15794e0 --- /dev/null +++ b/hw/hw4/test_social_network_2.txt @@ -0,0 +1 @@ +0,0 diff --git a/hw/hw4/test_social_network_3.txt b/hw/hw4/test_social_network_3.txt new file mode 100644 index 0000000..9a7b125 --- /dev/null +++ b/hw/hw4/test_social_network_3.txt @@ -0,0 +1,26 @@ +0,2 +0,7 +1,2 +1,3 +1,5 +2,0 +2,1 +2,6 +2,7 +3,1 +3,4 +3,5 +3,7 +4,3 +4,6 +4,7 +5,1 +5,3 +5,6 +6,2 +6,4 +6,5 +7,0 +7,2 +7,3 +7,4 diff --git a/hw/hw4/test_social_network_4.txt b/hw/hw4/test_social_network_4.txt new file mode 100644 index 0000000..5b49337 --- /dev/null +++ b/hw/hw4/test_social_network_4.txt @@ -0,0 +1,23 @@ +0,2 +0,3 +0,4 +1,3 +1,4 +1,5 +1,6 +2,0 +2,4 +2,5 +2,6 +3,0 +3,1 +4,0 +4,1 +4,2 +4,5 +5,1 +5,2 +5,4 +6,1 +6,2 +7,7 diff --git a/hw/hw4/test_social_network_5.txt b/hw/hw4/test_social_network_5.txt new file mode 100644 index 0000000..fda961d --- /dev/null +++ b/hw/hw4/test_social_network_5.txt @@ -0,0 +1,14 @@ +0,4 +0,5 +1,2 +2,1 +2,3 +2,4 +3,2 +3,5 +4,0 +4,2 +4,5 +5,0 +5,3 +5,4 diff --git a/hw/hw4/test_social_network_6.txt b/hw/hw4/test_social_network_6.txt new file mode 100644 index 0000000..9e43624 --- /dev/null +++ b/hw/hw4/test_social_network_6.txt @@ -0,0 +1,4 @@ +0,1 +0,2 +1,0 +2,0 diff --git a/hw/hw4/test_social_network_7.txt b/hw/hw4/test_social_network_7.txt new file mode 100644 index 0000000..15794e0 --- /dev/null +++ b/hw/hw4/test_social_network_7.txt @@ -0,0 +1 @@ +0,0 diff --git a/hw/hw4/test_social_network_8.txt b/hw/hw4/test_social_network_8.txt new file mode 100644 index 0000000..6567265 --- /dev/null +++ b/hw/hw4/test_social_network_8.txt @@ -0,0 +1,48 @@ +0,2 +0,3 +0,4 +0,5 +0,6 +0,8 +0,9 +1,3 +1,7 +2,0 +2,4 +2,6 +2,9 +3,0 +3,1 +3,7 +3,8 +3,9 +4,0 +4,2 +4,8 +5,0 +5,7 +5,9 +6,0 +6,2 +6,7 +6,8 +6,9 +7,1 +7,3 +7,5 +7,6 +7,8 +7,9 +8,0 +8,3 +8,4 +8,6 +8,7 +8,9 +9,0 +9,2 +9,3 +9,5 +9,6 +9,7 +9,8 diff --git a/hw/hw4/test_social_network_9.txt b/hw/hw4/test_social_network_9.txt new file mode 100644 index 0000000..a125258 --- /dev/null +++ b/hw/hw4/test_social_network_9.txt @@ -0,0 +1,20 @@ +0,1 +0,3 +0,4 +0,5 +1,0 +1,2 +1,3 +1,4 +2,1 +2,3 +3,0 +3,1 +3,2 +3,4 +3,5 +4,0 +4,1 +4,3 +5,0 +5,3 diff --git a/result.txt b/result.txt deleted file mode 100644 index e69de29..0000000 diff --git "a/thai/HW5_\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\243\340\270\260\340\270\232\340\270\262\340\270\224.ipynb" "b/thai/HW5_\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\243\340\270\260\340\270\232\340\270\262\340\270\224.ipynb" new file mode 100644 index 0000000..83889be --- /dev/null +++ "b/thai/HW5_\340\271\201\340\270\232\340\270\232\340\270\210\340\270\263\340\270\245\340\270\255\340\270\207\340\270\201\340\270\262\340\270\243\340\270\243\340\270\260\340\270\232\340\270\262\340\270\224.ipynb" @@ -0,0 +1,632 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "jL9Rk67Oz8DW" + }, + "source": [ + "การบ้านครั้งสุดท้ายนี้ให้เขียนโปรแกรมการจำลองการระบาด กำหนดให้ข้อมูลของคนหนึ่งคนเก็บใน dictionary ดังนี้ \n", + "\n", + "1. `id` เป็นจำนวนเต็มเก็บเลขประจำตัวของคน\n", + "2. `vaccinated` เป็นบูลีน แทนสถานะการรับฉีดวัคซีนว่าได้รับ (`True`) หรือยังไม่ได้รับ (`False`)\n", + "3. `coordinate` เป็นทูเปิลของจำนวนจริง 2 ค่า เก็บพิกัดในแนวแกน `x` และ `y` ของคนนั้น\n", + "\n", + "เช่น `{'id':20382921, 'vaccinated':False, 'coodinate': (204.368, 304.256)}` หมายถึง คนนี้มีเลขประจำตัว `20382921` ยังไม่ได้รับการฉีดวัคซีน และอยู่ที่พิกัด `x=204.368` และ `y=304.256`\n", + "\n", + "และเก็บข้อมูลประชากรเป็น list of dicts เช่น \n", + "\n", + "```\n", + "[{'id':20382921, 'vaccinated':False, 'coodinate': (204.368, 304.256)}, \n", + " {'id':20382952, 'vaccinated':True, 'coodinate': (201.280, 302.524)},\n", + " {'id':20482912, 'vaccinated':False, 'coodinate': (202.102, 301.129)}]\n", + " ```\n", + "\n", + "สั่ง run cell ข้างล่างนี้เพื่อสร้างข้อมูลประชากร (แบบสุ่ม) เก็บในตัวแปร `population` (`n` คือขนาดประชากร และ `vaccinated` คือเปอร์เซ็นต์ของประชากรที่ได้รับวัคซีน)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "cellView": "form", + "id": "ra1pJfZgTRuQ" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[(47442119, 85109525), (10790563, 96365445), (41224698, 96365445), (13880368, 96365445), (57738559, 84419781), (82184386, 84419781), (84419781, 95598806), (78471422, 84419781), (13065093, 29172927), (13065093, 95085939), (13065093, 81132241), (13065093, 20708071), (13065093, 60834413), (13065093, 66681034), (13065093, 59291581), (10790563, 41224698), (10790563, 13880368), (16734940, 87452375), (16158843, 74700954), (25697116, 74700954), (51410600, 74700954), (47882681, 74700954), (29172927, 95085939), (20708071, 29172927), (29172927, 60834413), (57738559, 95598806), (56847580, 88207856), (30293487, 83930383), (13880368, 41224698), (63923084, 86495463), (31690631, 86495463), (12501274, 23714842), (12501274, 41506211), (12501274, 47442119), (75343338, 78010143), (32734324, 78010143), (59088357, 78010143), (35515066, 78010143), (60505105, 78010143), (82184386, 87413218), (22134427, 87413218), (78471422, 87413218), (16158843, 25697116), (16158843, 51410600), (68854526, 94720095), (68854526, 78741153), (10573008, 68854526), (68854526, 97882755), (61701738, 68854526), (43490684, 68854526), (32445212, 94720095), (10573008, 94720095), (61701738, 94720095), (25697116, 51410600), (25697116, 75343338), (81132241, 95085939), (20708071, 95085939), (22134427, 82184386), (78471422, 82184386), (23714842, 51966002), (23714842, 41506211), (23714842, 52044980), (23714842, 40058187), (16239837, 24748497), (23787180, 33152311), (22134427, 78471422), (16146015, 81132241), (59291581, 81132241), (16146015, 16239837), (32734324, 75343338), (59088357, 75343338), (35515066, 75343338), (32734324, 59088357), (32734324, 35515066), (16954439, 47882681), (35515066, 59088357), (78741153, 97882755), (43490684, 78741153), (10573008, 97882755), (10573008, 61701738), (61701738, 97882755), (43490684, 97882755), (51966002, 52044980), (20708071, 60834413), (20708071, 66681034), (60834413, 66681034), (16146015, 43490684), (31690631, 63923084), (41506211, 52044980), (40058187, 41506211), (40058187, 52044980), (35515066, 60505105), (59291581, 66681034)]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#@title\n", + "n = 100 #@param {type:\"slider\", min:100, max:1000, step:1}\n", + "vaccinated_percent = 40 #@param {type:\"slider\", min:0, max:100, step:1}\n", + "\n", + "import random \n", + "random.seed(37)\n", + "population = [{'id':int(random.random()*(10**8-10**7))+10**7,\\\n", + " 'vaccinated': True if random.random() Download -> Download .ipynb\n", + " * ส่งไฟล์ที่ดาวน์โหลดได้ใน MyCourseVille ก่อนเวลา **23:59 น. วันที่ 8 พฤศจิกายน 2565** \n", + " * จะตรวจแฟ้ม .ipynb แฟ้มล่าสุดที่ส่งในระบบ MyCourseVille เท่านั้น\n", + "\n", + "
\n", + "\n", + "## สำคัญ: อ่านตรงนี้ด้วย\n", + "- ข้อห้าม\n", + " - ห้าม import ใด ๆ \n", + " - ห้ามเปลี่ยนบรรทัด def ของฟังก์ชันที่ให้เขียน\n", + " - ในกรณีที่ฟังก์ชันมีการคืนค่า ฟังก์ชันต้องคืนข้อมูลและประเภทข้อมูลตามที่กำหนดเท่านั้น\n", + " - ห้ามเปลี่ยนบรรทัดแรกของ code cell\n", + "- ส่งแฟ้ม .ipynb กี่ครั้งก็ได้ แต่จะตรวจแฟ้ม .ipynb **แฟ้มล่าสุด** เท่านั้น\n", + "- ส่อทุจริต เช่น\n", + " - ส่งโปรแกรมที่ผู้ส่งไม่สามารถอธิบายได้ว่า ใช้หลักการและทำงานอย่างไร\n", + " - หรือ ส่งโปรแกรมที่คล้ายกับโปรแกรมของผู้อื่นมาก ๆ (ไม่ว่าจะเป็นผู้ให้หรือผู้รับ จะตั้งใจหรือไม่ก็ตาม)\n", + " - ฉะนั้น\n", + " - ให้แน่ใจว่า ไม่ดูโปรแกรมของคนอื่น\n", + " - ให้แน่ใจว่า ไม่ได้ให้คนอื่นดูโปรแกรมของตัวเอง\n", + "\n", + "- หากพบว่า งานที่ส่งส่อทุจริต จะได้นิสิตจะได้ $0$ ในการบ้านครั้งนี้ และการบ้านครั้งที่แล้ว ๆ\n", + "- จะตรวจให้คะแนน เมื่อ\n", + " - แฟ้มที่ส่งครั้งหลังสุดใน MyCourseVille เป็นแฟ้มที่ตั้งชื่อตามที่กำหนด และเป็นแฟ้มที่ได้จากการ File->Download->Download .ipynb เท่านั้น (ไม่ใช่แฟ้ม .py แล้วมา rename เป็น .ipynb)\n", + " - ฟังก์ชันที่เขียนส่งต้องอยู่ใน code cell สุดท้ายข้างล่างนี้\n", + " - บรรทัดแรกของ code cell ทุกอันต้องขึ้นต้นด้วย `# HW5_Infection_Analysis` ตามที่ให้ไป\n", + " - ไม่ทำในสิ่งที่ห้ามทำในข้อห้าม\n", + " - code cell ทุกอันสามารถทำงานได้ (ไม่มี error)\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "U0Ll9SeOpWQ2" + }, + "source": [ + "# งานที่ 1 (5 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `get_coordinates(population, vaccinated)` \n", + "- รับ `population` เป็น list of dicts ที่เก็บข้อมูลประชากร\n", + "- รับ `vaccinated` เป็นบูลีน เพื่อเลือกว่าจะคืนค่าเป็นประชากรที่ได้รับ (`True`) หรือไม่ได้รับวัคซีน (`False`)\n", + "- คืน dict ที่มีเลขประจำตัวเป็น key และพิกัดเป็น value \n", + "\n", + "เช่น\n", + "\n", + "```\n", + "population = [\n", + " {'id': 71380410,\n", + " 'vaccinated': True,\n", + " 'coordinate': (142.35632697722804, 233.67679618203823)},\n", + " {'id': 85109525,\n", + " 'vaccinated': False,\n", + " 'coordinate': (142.62075930591354, 214.76919336251675)},\n", + " {'id': 57521675,\n", + " 'vaccinated': False,\n", + " 'coordinate': (143.65899867666593, 224.0267344699912)},\n", + " {'id': 35373207,\n", + " 'vaccinated': False,\n", + " 'coordinate': (144.72263074267343, 217.75509778988294)},\n", + " {'id': 96365445,\n", + " 'vaccinated': False,\n", + " 'coordinate': (146.76725209497084, 203.64110005292503)}\n", + "]\n", + "```\n", + "```\n", + "get_coordinates(population, False) จะคืนค่า \n", + "{85109525: (142.62075930591354, 214.76919336251675),\n", + " 57521675: (143.65899867666593, 224.0267344699912),\n", + " 35373207: (144.72263074267343, 217.75509778988294),\n", + " 96365445: (146.76725209497084, 203.64110005292503)}\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "id": "ND70oKsVzzum" + }, + "outputs": [], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def get_coordinates(population, vaccinated):\n", + " coordinates = dict()\n", + "\n", + " for person in population:\n", + " # ตรวจสอบว่ารับวัคซีนหรือไม่\n", + " if person['vaccinated'] == vaccinated:\n", + " coordinates[person['id']] = person['coordinate']\n", + "\n", + " return coordinates\n", + "\n", + "# population = [\n", + "# {'id': 71380410,\n", + "# 'vaccinated': True,\n", + "# 'coordinate': (142.35632697722804, 233.67679618203823)},\n", + "# {'id': 85109525,\n", + "# 'vaccinated': False,\n", + "# 'coordinate': (142.62075930591354, 214.76919336251675)},\n", + "# {'id': 57521675,\n", + "# 'vaccinated': False,\n", + "# 'coordinate': (143.65899867666593, 224.0267344699912)},\n", + "# {'id': 35373207,\n", + "# 'vaccinated': False,\n", + "# 'coordinate': (144.72263074267343, 217.75509778988294)},\n", + "# {'id': 96365445,\n", + "# 'vaccinated': False,\n", + "# 'coordinate': (146.76725209497084, 203.64110005292503)}\n", + "# ]\n", + "\n", + "# def test(output, expected):\n", + "# if output == expected:\n", + "# print(\"Correct!\")\n", + "# else:\n", + "# print(\"Incorrect. Expected: {}, but got: {}\".format(expected, output))\n", + "\n", + "# expected = {85109525: (142.62075930591354, 214.76919336251675),\n", + "# 57521675: (143.65899867666593, 224.0267344699912),\n", + "# 35373207: (144.72263074267343, 217.75509778988294),\n", + "# 96365445: (146.76725209497084, 203.64110005292503)}\n", + "\n", + "# test(get_coordinates(population, False), expected)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "g9I1NOXl3U49" + }, + "source": [ + "# งานที่ 2 (5 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `get_all_unjabbed_pairs(population, radius)`\n", + "- รับ `population` เป็น list of dicts เก็บข้อมูลประชากร `radius` เป็น float เก็บรัศมีการระบาด \n", + "- คืน list of tuples (`id1`, `id2`) โดยที่ ทั้งสองเลขประจำตัวยังไม่ได้รับวัคซีน และอยู่ห่างกันไม่เกิน `radius`\n", + "- ให้เรียงลิสต์ที่คืนตามทูเปิลของเลขประจำตัวจากน้อยไปมาก โดยให้แต่ละทูเปิลเก็บเลขประจำตัวช่องซ้ายให้มีค่าน้อยกว่าช่องขวา\n", + "\n", + "เช่น\n", + "```\n", + "population = [\n", + " {'id': 71380410,\n", + " 'vaccinated': True,\n", + " 'coordinate': (142.35632697722804, 233.67679618203823)},\n", + " {'id': 85109525,\n", + " 'vaccinated': False,\n", + " 'coordinate': (142.62075930591354, 214.76919336251675)},\n", + " {'id': 57521675,\n", + " 'vaccinated': False,\n", + " 'coordinate': (143.65899867666593, 224.0267344699912)},\n", + " {'id': 35373207,\n", + " 'vaccinated': False,\n", + " 'coordinate': (144.72263074267343, 217.75509778988294)},\n", + " {'id': 96365445,\n", + " 'vaccinated': False,\n", + " 'coordinate': (146.76725209497084, 203.64110005292503)}\n", + "]\n", + "```\n", + "```\n", + "get_all_unjabbed_pairs(population, 10) จะคืนค่า\n", + "[(35373207, 57521675), (35373207, 85109525), (57521675, 85109525)]\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "id": "GiP4Z9gO3UcR" + }, + "outputs": [], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def get_all_unjabbed_pairs(population, radius):\n", + " unjabbed_pairs = []\n", + "\n", + " def distance(p1, p2):\n", + " return ((p1[0] - p2[0])**2 + (p1[1] - p2[1])**2)**0.5\n", + "\n", + " for person in population:\n", + " if not person['vaccinated']:\n", + " # คนอื่นที่เหลือ\n", + " for other_person in population:\n", + " if not other_person['vaccinated'] and person['id'] != other_person['id']:\n", + " # ตรวจสอบว่าอยู่ในรัศมีหรือไม่\n", + " if distance(person['coordinate'], other_person['coordinate']) <= radius:\n", + " # เพิ่มคู่\n", + " if (other_person['id'], person['id']) not in unjabbed_pairs:\n", + " unjabbed_pairs.append((person['id'], other_person['id']))\n", + "\n", + " # เรียงทั้ง tuple ทั้ง set\n", + " return sorted([tuple(sorted(l)) for l in unjabbed_pairs])\n", + "\n", + "# expected = [(35373207, 57521675), (35373207, 85109525), (57521675, 85109525)]\n", + "# test(get_all_unjabbed_pairs(population, 10), expected)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "7AwxB4Eix2kd" + }, + "source": [ + "# งานที่ 3 (10 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `first_hop(population, id, radius)` \n", + "- รับ `population` เป็น list of dicts เก็บข้อมูลประชากร `id` เป็นจำนวนเต็ม เก็บเลขประจำตัว และ`radius` เป็น float เก็บรัศมีการระบาด \n", + "- คืน list of เลขประจำตัวต่าง ๆ ที่ยังไม่ได้รับวัคซีน และอยู่ห่างจากคนที่เลขประจำตัว `id` ในระยะไม่เกิน `radius`\n", + "- โดยให้เรียงลิสต์ที่คืนตามเลขประจำตัวจากน้อยไปมาก (หากไม่มีข้อมูลอะไรคืนเลย ก็คืนลิสต์ว่าง)\n", + "\n", + "เช่น\n", + "```\n", + "population = [\n", + " {'id': 71380410,\n", + " 'vaccinated': True,\n", + " 'coordinate': (142.35632697722804, 233.67679618203823)},\n", + " {'id': 85109525,\n", + " 'vaccinated': False,\n", + " 'coordinate': (142.62075930591354, 214.76919336251675)},\n", + " {'id': 57521675,\n", + " 'vaccinated': False,\n", + " 'coordinate': (143.65899867666593, 224.0267344699912)},\n", + " {'id': 35373207,\n", + " 'vaccinated': False,\n", + " 'coordinate': (144.72263074267343, 217.75509778988294)},\n", + " {'id': 96365445,\n", + " 'vaccinated': False,\n", + " 'coordinate': (146.76725209497084, 203.64110005292503)}\n", + "]\n", + "```\n", + "```\n", + "first_hop(population, 85109525, 10) จะคืนค่า\n", + "[35373207, 57521675]\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "id": "RImqheX1qb_B" + }, + "outputs": [], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def first_hop(population, id, radius): \n", + " people_in_range = []\n", + "\n", + " for unjabbed in get_all_unjabbed_pairs(population, radius):\n", + " if id in unjabbed:\n", + " people_in_range.append(unjabbed[0] if unjabbed[1] == id else unjabbed[1])\n", + " \n", + " return people_in_range\n", + "\n", + "# expected = [35373207, 57521675]\n", + "# test(first_hop(population, 85109525, 10), expected)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-H3kLk2D6_L2" + }, + "source": [ + "# งานที่ 4 (10 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `get_adjacency_set(pairs)` \n", + "- รับ `pairs` เป็น list of tuples ซึ่งเก็บข้อมูลในรูปแบบเดียวกับผลที่ได้จากฟังก์ชัน `get_all_unjabbed_pairs` ในงานที่ 2\n", + "- คืน dict ที่มีเลขประจำตัวทุกหมายเลขใน `pairs` เป็น key โดยที่ value เป็น set ของเลขประจำตัวต่าง ๆ ที่อยู่ในทูเปิลเดียวกับค่า key เช่น\n", + "\n", + "\n", + "เช่น\n", + "```\n", + "pairs = [\n", + " (35373207, 57521675), \n", + " (35373207, 85109525), \n", + " (57521675, 85109525)\n", + "]\n", + "```\n", + "```\n", + "get_adjacency_set(pairs) จะคืนค่า \n", + "{35373207: {57521675, 85109525}, 57521675: {85109525, 35373207}, 85109525: {57521675, 35373207}}\n", + "```\n", + "\n", + "```\n", + "get_adjacency_set([(1,2),(1,3),(2,4),(4,5),(7,8)]) จะคืนค่า\n", + "{1: {2, 3}, 2: {1, 4}, 3: {1}, 4: {2, 5}, 5: {4}, 7: {8}, 8: {7}}\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "id": "e7oyZ2SF79-A" + }, + "outputs": [], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def get_adjacency_set(pairs):\n", + " adjacency_set = dict()\n", + " for pair in pairs:\n", + " if pair[0] not in adjacency_set:\n", + " adjacency_set[pair[0]] = set()\n", + " adjacency_set[pair[0]].add(pair[1])\n", + "\n", + " if pair[1] not in adjacency_set:\n", + " adjacency_set[pair[1]] = set()\n", + " adjacency_set[pair[1]].add(pair[0])\n", + "\n", + " return adjacency_set\n", + "\n", + "pairs = [\n", + " (35373207, 57521675),\n", + " (35373207, 85109525),\n", + " (57521675, 85109525)\n", + "]\n", + "\n", + "# test(get_adjacency_set(pairs), {35373207: {57521675, 85109525}, 57521675: {\n", + "# 85109525, 35373207}, 85109525: {57521675, 35373207}})\n", + "# test(get_adjacency_set([(1, 2), (1, 3), (2, 4), (4, 5), (7, 8)]), {\n", + "# 1: {2, 3}, 2: {1, 4}, 3: {1}, 4: {2, 5}, 5: {4}, 7: {8}, 8: {7}})\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZWuD2DxLHhPs" + }, + "source": [ + "# งานที่ 5 (15 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `get_infectable_ids(pairs, seed)` \n", + "- รับ `pairs` เป็น list of tuples ซึ่งเก็บข้อมูลในรูปแบบเดียวกับผลที่ได้จากฟังก์ชัน `get_all_unjabbed_pairs` ในงานที่ 2 และ `seed` เป็นจำนวนเต็มเก็บเลขประจำตัว\n", + "- คืน set ที่เก็บเลขประจำตัวต่าง ๆ ที่โรคสามารถระบาดไปถึงได้ ถ้า `seed` เป็นจุดเริ่มต้นของการระบาด\n", + "- ให้ใช้ flowchart ด้านล่างนี้เป็นแนวทางการทำงาน รวมถึงการใช้ฟังก์ชันก่อนหน้านี้มาช่วยในการเขียนฟังก์ชั้นนี้\n", + "\n", + "\n", + "\n", + "เช่น หากคู่เลขประจำตัวต่าง ๆ ที่ยังไม่ได้รับวัคซีน และสามารถแพร่เชื้อถึงกันได้ เป็นดังนี้ \n", + "```\n", + "pairs = [(1,2),(1,3),(2,4),(4,5),(7,8)]\n", + "```\n", + "\n", + "\n", + "เมื่อเรียก `get_adjacency_set(pairs)` จะได้ dict\n", + "```\n", + "{1: {2, 3}, 2: {1, 4}, 3: {1}, 4: {2, 5}, 5: {4}, 7: {8}, 8: {7}}\n", + "```\n", + "ที่ทำให้หาได้รวดเร็วว่า เลขประจำตัวใดบ้างที่สามารถรับเชื้อได้จากเลขประจำตัวที่เป็นคีย์ \n", + "\n", + "จะได้ว่า \n", + "```\n", + "get_infectable_ids(pairs, 2) จะคืนค่า {1, 2, 3, 4, 5}\n", + "```\n", + "\n", + "\n", + "หมายเหตุ: ตรงส่วนที่เขียนใน flowchart ว่า `append all adjacent ids, which is not in output, of p into f` หมายความว่า ให้ append เลขประจำตัวทั้งหมดที่เชื่อมกับ `p` ลงในลิสต์ `f` โดยต้องเป็นเลขประจำตัวที่ไม่อยู่ใน `output`\n", + "\n", + "เช่น ถ้า `p` เก็บค่า 2 ให้นำ 1 กับ 4 (เฉพาะหมายเลขที่ไม่มีมีใน output) ไปเพิ่มต่อท้ายใน `f` \n", + "\n", + "ผลลัพธ์ที่ได้จาก flowchart จะเป็นลิสต์ที่เก็บอยู่ในตัวแปร `output` " + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "id": "_A3rrpBSHP1F" + }, + "outputs": [], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def get_infectable_ids(pairs,seed):\n", + " output = set()\n", + " f = [seed]\n", + "\n", + " while len(f) > 0:\n", + " p = f.pop(0)\n", + " output.add(p)\n", + "\n", + " nearby = get_adjacency_set(pairs)[p]\n", + " \n", + " for n in nearby:\n", + " if n not in output:\n", + " f.append(n)\n", + " \n", + " return output\n", + "\n", + "# pairs = [(1,2),(1,3),(2,4),(4,5),(7,8)]\n", + "# test(get_infectable_ids(pairs, 2), {1, 2, 3, 4, 5})" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "0P8QNKGlPq-7" + }, + "source": [ + "# งานที่ 6 (15 คะแนน)\n", + "\n", + "เขียนฟังก์ชัน `get_all_clusters(pairs)` \n", + "- รับ `pairs` เป็น list of tuples ซึ่งเก็บข้อมูลในรูปแบบเดียวกับผลที่ได้จากฟังก์ชัน `get_all_unjabbed_pairs` ในงานที่ 2\n", + "- คืน list of sets แทนกลุ่มก้อนการระบาดในแต่ละกลุ่ม แต่ละ set แทนกลุ่มการระบาด \n", + "\n", + "ตัวอย่างเช่น \n", + "\n", + "หาก `pairs=[(1,2),(1,3),(2,4),(4,5),(7,8)]` \n", + "\n", + "`get_all_clusters(pairs)` จะคืนค่า `[{1, 2, 3, 4, 5}, {7, 8}]`\n" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "id": "k75zveo_OAEP" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Correct!\n" + ] + } + ], + "source": [ + "# HW5_Infection_Analysis\n", + "\n", + "def get_all_clusters(pairs):\n", + " clusters = []\n", + "\n", + " while len(pairs) > 0:\n", + " cluster = get_infectable_ids(pairs, pairs[0][0])\n", + " clusters.append(cluster)\n", + " for c in cluster:\n", + " for p in pairs:\n", + " if c in p:\n", + " pairs.remove(p)\n", + " \n", + " return clusters\n", + "\n", + "# pairs = [(1,2),(1,3),(2,4),(4,5),(7,8)]\n", + "# test(get_all_clusters(pairs), [{1, 2, 3, 4, 5}, {7, 8}])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VS6_4-Srwv-x" + }, + "source": [ + "### ลองเล่น ๆ ###\n", + "\n", + "หากเขียนฟังก์ชัน 1 และ 2 ถูกต้อง (ไม่เกี่ยวกับการเรียงลำดับ) เมื่อสั่ง run เซลล์ด้านล่างนี้ จะได้รูปที่แสดงเส้นเชื่อมของคู่คนที่ยังไม่ได้รับวัคซีน ดังตัวอย่างรูปด้านล่าง\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 265 + }, + "id": "4dH8aHB2p85F", + "outputId": "70cc4b5d-3f96-45b3-8e52-cb285c74db25" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[(47442119, 85109525), (10790563, 96365445), (41224698, 96365445), (13880368, 96365445), (57738559, 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aKOVOF+KElOjA3cR6+12dgn8JPdHpExi0DOJwOQIdisIsCT3RRSQgkcrdLoSZThXELCHEMSFEpRDiuhDiq57l/yiEuOIpUHdYCJHuWS6EED8SQtR61nt1fMlXw2EK/sMXDv/HcFsOi3D7Wv/dmwFHaaIIV4W7fQAKIYkvHP57gZekm3NArBAizVsBCyGUzkSIM6Nnuskc/kKIFuAJ3rvTZQAtE3Zr9Sy7/VhPCSFKhRCl3d0zywo0NhwWQiYzhQlMW3R3c/hLKbOA3+B2+E8bKeWLUsoSKWVJUtLMkggOjA7wH+X/wbnWczPaTyE4mJboPA7/N4DfSCnfnGST3wBjZV/agKwJ6zI9y7xGh6mDnpEeDtUcosvc5c1DK/iB6fRe7+rwn7DZuMMfeAv4tKcXuwYYlFJ2eDFm1Co167LWkRaVxv6q/Q9cEd4HHV84/A8Au4FaYAT4rDcDtjqsdJo7SY9KZ/e83VQYKzhaf5RV6au8nv5AwTf4wuEvgWfuM6670jzYDLg7E3q1nvcVvY8TTSe42H6RQesgG7M3Bjwlq8K9CakRCSkl/3L6X6gwViAQ7pKUqjC25m2lJL2E6t5q/ljzR6+nK1XwLiHjkQCQSC4ZL2F32BEI1Co1hfGFpBhSSDWksjF7I2dazrDv5j52Fe7yWQ0HhfsjpESnEiqeX/88b1x/A02YhqL4IixOC5c6LiGRCARhIoxrXdeo66tjbeZatuRtCclEOA8yISU6gFRDKjlxObQPtxOnj2Nt1lrsTjud5k46TZ0YTUYsTgtvVr7JLy79glc+/MqccXvNlm5zN39q+hM6te6On+LEYv+nCgs2IsMjxxP6XWy/yIKkBcToYsiMzhzPMFnVU0Vdfx3R2mgWpywOcMTBj0qoiNJGMWofpWekB4vDgtXpzqZenFjs9fOFnug0kQgEOTE5qIWaY43H2FO8Z7wJ7TJ3cbL5JIVxhRTFF4XEUNmQdYgh69A9K9f4koSIBHYW7Lxl2Vgaf18k+A65h51xb6aAtVlr6TJ3UWGsAMBkM/F27dsYNAa/pEe4X5wuJ+Ud5bx+/XVONp3EJV2BDmkclVDdV3nQexF6d7rwSCQSm8NGXlwe/ZZ+yjvKSY9K50zLGRwuB4/Pe5xOcyfg7vEGI61DrZxuPs2gdZCCuALWZq0N+j8SbxF6otNEAmB1WhEI1metp324nZ9c+AkZURm8b977iNPHjYsu2Bixj3Cm5Qz1/fXEaGPYXbQ7YM1qoAg50WnCNKiFmmHH8LhnM0GfQONAI/MS5o3XfBCTDqIEDpd0UdldycW2i7iki5L0EpamLJ2ToychJzoAXbgOq9ndu6rvr6dlqIU1mWuwOCy0DbWREf3e9L1g6Eh0mbs42XSS3tFesqKzWJ+9nmhtdKDDChgh+RARGR6JzWmjb7SP443HSYlM4fMrPk+sLpbjjcexOqx+r706GVaHlZNNJ9l3cx8Wh4Ud+Tt4rOixOS04CNU7nVqH2Wbmnfp30Ifr2VmwE61ay9a8rey7uY/TLafHn5MC0ZGQUlLdW835tvNYHVaWpCxhZVpwVlAMBCEpulHbKBfbL7IsdRkfmP+B8a59YkQiK9JWUNpeGrDXD32jfZxqPoXRZCQlMoWN8zbetVT5XCUkRfd23ds0DzZzvfs6R+qPkBSRRFJkEsmRySxMWkjzYDNl7WV3FOXwJXannbKOMq52XkWr1rI5ZzPzEuYFRTMfbISk6P72kb9lyDaEVqVFG6al09xJXX8d4O61atQarnZepWmwid2Fu33+DFXWXsZr118jOyabxSmLWZ2x+oEoC+ArQlJ0i5MX85EFH6F5sBm7y85HF7gLr3WPdNNt7qZ7pJtB6yA3em5Q01dDQYL3Sw2N4XA5ONNyBqvTyt7ivWTGzK13brNhOlUQs4CXgBTc3tYXpZQ/FEJ8D3g/YAPqgM9KKQc8NsUbQJXnEOeklF+488izRwhBTmwOCBi0DHKi6QTb87eTHZNNdkw2I/YRzracJTkimUfyHpn6gPdBaXspWrWW59Y9N+de8s6W+3H4HwEWSSmXANXANybsUyelXOb58argxkg1pCIQLElZQn1/PVc73yvEUWGswO6ysyxtmU8T/nWaOrnSeYUFSQsUwc2A6XgkOoAOz+dhIcSYw//whM3O4S656TfGiqmlGlIZtA5yrvUcSZFJGDQGKrsrSTOk+XTmsMPl4HjjcQwaAw9nKPP1ZsJ9Ofwn8CRwcML3PCHEJSHECSHExrsca9YOf4CkiCRUQoXRZGRL7haitdEcrT/KmZYzAOTE5Pj0Yb60vZRB6yCbczYr799myH05/D3Lv4W7Cf6NZ1EHkC2lXA48C/y3EOKO7uP9OPzBXYIoKSIJo8mIJkzDjoIdDFoGeavqLeYnzkcI4TPRjTWrDyU+dMuQm8L0uC+HvxDiM8DjwBNj1aullFYpZa/ncxnuToZPqrylGlLpHunG4XIQr48nWhvNsHUYh8uBxWHxyfOcw+XgRNMJd7OqTIOfFffj8N8FPA/skVKOTFieJIQI83zOx50yzCcW/FRDKi7pomekh/7RfkYdo2zI3kB1bzUtQy0+udOVtZcxYBlgc85mNGEarx9/LjCdO92Yw3+rJwFihRBiN+6S6VHAEc+yn3m23wRc8WQD+C3wBSmlT/J6jVWfNpqMlLaXognT8MSSJ4jTxfHmjTep7Kr0atXELnOX0qx6AV84/N/A3RT7HJ1aR6wulqqeKgatgyxKXsS1rmu0DrbSaerkcP1hdOE6cmNzKYgrICM6Y9azc8d6q5GaSKVZvU9CckRiIqmGVH5b+VtitDHjyxanLubYZ47hcrmoH6incaCR6t5qdGodebF5FMQXkGZIm9G46Fizurtot9Ks3ichL7qekR4utF1gY9ZGiuKLWJ62/Jb3c9mx2ThdTlqGWqjrq6Omr4YbPTeICI8YF2BKZMo9BTjWrM5PnK+8BPYCIS+6FakrWJ+1nmcefobc2NxJtwlThZEbm0tubC4Ol4PmwWbq+uq42XOT693XiQyPpCC+gPy4fJIjk2/Z1+lyjjer/ipNORvsTvu4X9XisNzyY3VYGbAM8P2z32dN1hq+s/U7AY015EWXG5fLC4++MO3t1So1+XH55MflY3faaRpsoq6vjmtd17jSeYUoTRQF8QUUxBWQEJFAWUdgmlWXdPHa9dcoji9GG67F4XJgdbwnqNvFda/5g06Xk5s9N+kZ7eFa5zW6zF13/HH5ExEMHoKSkhJZWloa0BisDiuNA43U9dfRNtSGRGKymbjaeZUnljzB9vztfo1n3419PHv4WVINqeTH5ROuCker1mLQGDBoDERro4nRxhCjjSFaF02cLo5obTQ6tQ6tWjueFqLL1MU7De8wYh/BOGzkYvtFHNLBax95jfiI2U8uFUKUSSlLZrNvyN/pvIVWraU4sZjixGIsDgtVPVW8cPYF2ofbKUmf1b/trHmr6i1ev/E62/K28cTiJ1CHqXE4HVidVkbsI5jtZkbsIzilkz5LH32WPhppRK1SExEegUFjIFwVzoGaAxhNRhIjEylOKGbQNki0zj045JCBqzikiG4StGFaOkwdbMrZxLa8bX5NOfZG5Rv87ubvWJC0gL9Z9zd3bdJd0uUWoM2M2W6+43enqZPDdYfJjM7k6ZKnyYrOoq6/jsvGy8Tp44jSRPntmm5HEd0kXO68TPNgM+uz1pMXl+eXc0opeeXqKxyoPcCSlCU8u+ZZ1GF3/+9RCdV4U3s3UqNSaRxoZH3WerRqLf2WfmxOG1LKgGY+CEkLoi9pH27nYttFCuIKWJi80C/nlFLyq4pfcaD2ACvTVk4puOmyIs1dIWssEbherUcicbgcAc2boohuAiP2Ed6pf4cYXQybcjb55Zw2h40fnv8h7zS8w9rMtXx1zVe9Ijhwu+NidbHU9NUAoA/XIxDjd7tAoYjOg0u6OFp/FLvLzo78HX6ZI+eSLr7+ztd57fprrMtaxxdXfdHrSXSK4oswmoyYbCb0ardV0+6yK81rMHCh7QJGk5FNOZuI08f55Zy/KP8F7cPtvH/e+/lCyRd8krWpML4QgNq+WvThelRChd1pV5rXQNM40DjudRj7T/I1v674NSeaTrAldwtf3/B1n6UJi9JGkRKZQm1frdsHLMDmtCmiCySDlkGONx4nKSKJtZlr/XLO5sFm3m14l4czH+bplU/73JBdGF9I32gfZpvZfadz2QP6TDenX5k4XA6O1B9BINhRsMNvabuyY7L59qZvUxBX4JcMAAXxBZxpOUNdfx16td5dQVJ5pgsMp5tP0zfax9a8rfd83+ULihKKUKn888+vU+vIismitq8WbZhWeaYLFFU9VVT1VrEibQVZMVlT7xDiFMYXYrKZsDltAW9ep+ORyBJCHBNCVAohrgshvupZ/j0hxE0hxBUhxO+EELET9vmGEKJWCFElhHjUh/HPit6RXk41nyIjKoOVaSsDHY5fyI3NRa1SM2AZcL+nC/LmdUYOf8+6jwMLgV3AT8eMOsGAzWnjSP0RdGodW/O2zpmsSmqVmtzYXAYsA1gd1uBuXqWUHVLKcs/nYdx5SjKklIelHJ+qcA53MWFw13591WNFbMBdgnO190OfOX2jfTzzx2eo7a1le/52n6WsD1aK4otAwLBtGKvDGrA4ZtR7ncLh/z+ezxm4RThGq2fZ7cd6CngKIDs7eyZhzIhByyANAw009DdQ3lHOOw3vsLNgZ0AnMQaKjOgMojRRmGwmRu2jAYtj2qKbgcN/WkgpXwReBPckzpnsOxV9o3009DfQMNBA36jb/ZgUkcTWvK2YbWYSIxMp6yjz+zy5QKMSKvJi8zhcd5hB62DA4piW6Kbh8N8m3+sOtQETu4OZnmU+pdvcTcNAA/X99QxZ3X8TqYZU1mauJS8uD4PGQNtQG/OT5pOoT6S8o5zkyOTxEgBzheKEYiSShv4G1mb552X47UwnP91UDv/NEx3+wFu485f8K5CO2+F/watRe7hsvMwLZ19gS84WHNKBQJARncHSlKXkxObckf51rMjahpwNnGo+xbsN7/Khhz40p7Kdr0hfwf/d8X9Znhq40vPTudONOfyvelz7AN8EfgRocTv8wZP8UEp5XQjxGlCJu9l9RkrpPZu9B4vDwsuXX+ZU8ymS9Ek8veppcmJy7pm/ZOzhOTI8kh35O3jzxpscqTvC3vl7fVJ4LRjRqXVszJk0kZbf8LrD37PPd4Hv3kdc98TisPDH6j+SGZPJY4WPER8Rz6BlEG3CvRPmjN3ptGotapWaR/Ie4VDtIU41n2JL7hZfhatwGyE3ImFxWPhD9R8YsAywp3gPS1OXkhaVxiXjJW5037jnvlaHFZVQjd/VsmOyWZG2gure6in3VfAeIdWmjAlu0DLIo4WPkhmdiTZMS15cHmabmVPNp4jURN61c2B1WtGG3Xo3XJm2km5zN6dbTpMYkUhS5Mxz5SnMjJC5000U3K7CXePpHaK0UZhtZrbnbychIoGj9UfpGemZ9Bg2p+2OZz4hBI/kPUJEeARH6o9gcVh8fi1znZAQ3Y3uG3zit5+gfbidXYW7bknTFaWJYtg2THhYOLsKd6FT6zhUe4hh6/Adx7E67rzTgfvhemfBTkbto7zb8G5QFLF7kAkJ0R2sOUhFZwWnmk9xyXiJmt4aHC73CFyU1v2GHSAiPILHCh/D4XJwsPbgHUM9Vqf1rr3bxIhE1mevp3WolbKOMt9e0BwnJET37LpneXLZk4zYR7jWdY1jjcf4f1f+H6ebT+NwOXC4HOPDOnH6OB4teJQh6xCH6w7fkhTR6rDeMx/J/MT5FCcUU95RTvNgs8+va64SEqID+Nqar1EQV0DbUBsbszeSHZPNzZ6bnGo+RXlHOaXtpdicNgDSotLYkruFDlMHxxuPjzeXVqd1ypSw67PXkxiRyLsN746PbCh4l5ARnUFr4MnlT2KymThQc4BNOZv45JJPsinb7U/9U9OfePnyyxxrOEbHcAeF8YWszlhNXX8dF9svIqXE5rRNmXlJrVKzI38HAsGRuiPjzbiC9wgZ0QEsTV3KtrxtXOm8wuG6w2jVWlZlrGJF2grWZa2jOLGYpsEm9lfv53+uuSe95MflU2Gs4LLxMsCkHYnbidJG8UjeI/SO9nKk7ohX8xYrhNh7OoAPPvRBavpq+GP1H8mPzWd+0nx0ah3hYeFsyN7Amsw11PfXc7PnJhfaLiClpGe0h99X/R6VUKFVa3G6nIw6Rhm1j076eywxTXl7Of916b9oH27ncys+F+hLf2AIOdFFaiL580V/zr9d/Dder3ydL636EgaNYfwViVqlZl7CPOYlzGPAMkBVTxU3um/w68u/5nzbea51XWNb/rZJjx2uCkcfrsdkNVE/UI9BY2B99vqgzsAZioSc6ADmJ81na95WDtYcZH/1fpIjkhm23fleLlYXy4q0FZhsJrRhWvRqPVq1lkXJi4jXx6NX69GH68d/m21mzraeZcg6xLLUZazLWqfkGPYBISk6gB0FO2gaaKK8o5yCuIJJLYRGk5Hjjccpay9jefpy/mn7P1HeUU7vSC9rMteMu+rtTjtl7WVc7bqKWqVmbeZaFiYv9Jnrfq4TsqIzaAzsLNzJq9depaa3hviIeEbto+jD9biki9L2Ui4bL2O2mUk2JLM5ZzPL05Zj0Bg41niMc63nWJu5ltq+Ws63nWfEPkJxQjGrM1bPOe+EvwlZ0QE8lPgQq9JXsb96PzV9NdT115ERlcG7De/SO9pLVnQWbUNtJEUmjU9Nz47JJsOQwatXX+XVa6+yKHkRyZHJc9Y3EQhCWnRCCDbnbqamr4bDdYf51aVfkReXh1qlZmHyQsray+gd6SXZkMy+m/voNHXSOtQ6XtbJhYsvlnxxvGqign+4H7P1Rz3fXUKIkgnb5wohRifUEfvZ3Y9+/0Rro1mdvpprXdf43c3f8Xbd29icNvZX7edi+0V0ah31/fVc6bxCw0ADapWajdkb+ddH/5WjnzrKQ0kPBURwVT1VuFyB854Gkunc6cbM1uVCiCigTAhxBLgGfAj4+ST71Ekpl3kvzHuzIm0F8fp4IsMj0aq1WJ1W1Co1y1OWE6uPxSmdpEelMy9hHoXxhX7PW3I7FcYKXjjzAotTFrOzYCfzEubd4ed4kLmfcupHgKBoliI0EVz54hWqe6v5wdkf8GLZiyxIWsCe4j3j7+yC5Xmtureacy3n2JC9gRRDChfaLnCx7SLZMdnMT5xPVkzWA99r9pbZ+nbyhBCXgCHg21LKk7MLb2bMS5jH/9r8v2gcaOTpkqfZmb/Tb+m/psON7hucbD5Jdmw2Owt2olapGbQMUtVbRXVvNU11TUSERzAvYR7zE+c/sC61aVfM8ZitTwDfvc37ehx4TkpZ6vmuBQxSyl4hxEpgH7BwokHbs91Eh//Kpqam+7+aIOZa1zXOtJwhOyabHfl35sJzSRctgy3c7LlJ82AzEsnCpIWsz14foIjvjc8r5tzNbD0ZUkorYPV8LhNCjJVTL71tO585/IONCmMFF9oukBebx7b8bZM2nyqhIic2h5zYHMw2M9W91X4tmuJPZm22vsf2SUCflNLp63LqoUBZexllHWUUxheyJXfLtJ7XIjWRLE8LnBna19yP2VoL/BhIAv4ohKiQUj6Ku5z6Pwgh7IALH5ZTD3YutF2gwljBvIR5bM7ZHBSdrmDgfszWAL+bZHu/lVMPZs62nOVq11UWJC1gfdZ6RXATCOkRiWBESsnpltNUdleyKHkR67LWBTqkoEMRnReRUnKi6QTVvdUsS13G6oygyAUZdCii8xLd5m5+cekXaMI0bM7ZzMr0uZHLeDY82K++/cgl4yV+d/N3pBhSFMFNgSI6L5EelU5WdBYFsQWBDiXoUUTnJdQqNTq1Dqf3U/E9cCii8xLhKnepTsUnOzWK6LzE2FiqcqebGkV0XmIs0aJizJ4aRXReQi3colOa16lRROcl1GGK6KaLIjovoRIqBEJpXqeBIjovIRCohErpSEwDRXReQgiP6JQ73ZQE5dhrZXclVzqvEKONIUYXQ4w2hpzYnIC7uO6FQCCEwCGVZ7qpCErRGTQGEiMSGbIOYewxYnfZidPHBbfohCBMhCkdiWkQlKLLjsm+pRbEiH1kWskMA43SvE4Przv8Peu8Wk49IjwiqKyEkzHevCp3uinxusP/tnLq6cBRIcQ8XxSlCzQu6aJ3pBejyUh5Rzn7q/djc9j4/MrPBzq0oMYXDv/xcupAgxBirJz6WW8GHghsThudpk46zZ0YTUa6zF3v3dmk+47sknMzP8lM8IXDf1rl1IMdu9OOxWHBaDLSae6kfbid3pFeXNKFRBKriyU9Kp3EiETi9fGEq8L5z/L/pNPcGejQg577Lqc+W25z+N/v4bzK9a7rfOXgV4jRxRCliUIIQZQmavx7tDaaEfsIzYPNtxQ5aR1upW3Y50W8Qx6vO/yZZjn1YHb4Z0RlkB+fj9PlZFX6KkrSSwhThaFWqcdLd97+O0yE8fr11x/45DfewOsOf/xYTt1XxOpj+dn7fsaxxmPU99cjkaxIWzHlfkmRSUoVxWngdYe/v8qp+5owVRjb8rahU+uoMFYwah9lY87Ge97J1Cr1AzP2anFYqO+vHy+R4E287vD37OPTcur+QgjBhuwN6NV6yjrKsDgsbMvfNj5h83bCVeEh/XLY7rTTNNhEbV8trUOtuKSLnJgc/4tOAVamr0Sn1nG65TQHag6wq3DXpDXG1Cp1SL4c7hnp4UrnFRoHGnG4HBg0BhYnL6YwvpCEiASvn08R3TRZmLwQnVrHscZj7K/az2NFj92RsjVU73Qj9hFah1rH0+OmRKb4NPeKIroZUBBfgFat5XDdYd6qeovdRbtvyZYZpgrDJV04Xc6gH7abSGZ0Jp9c8km/9byV/v0MyYzO5PF5j2Nz2vj9zd/TO9I7vi48LNwtuhDrTKiEyq+vehTRzYLkyGT2FO8hTBXG/ur9dAx3AKBRaXBKZ0g2sf5EEd0sidXFsqd4DxHhERyoOUDjQOO4OUd5V3dvFNHdBwaNgT3Fe0iISOBI3REGRgcARXRToYjuPtGpdTw+73EyojNoHGikf7Qfk80U6LCCGkV0XkCtUrOrcBcGjYEucxc3um8EOqSgRnll4iVUQsWq9FUMWAdYnalk4LwXyp3Oi4Srw8mNzSUxIjHQoQQ1iui8iM1pG5/qpHB3QvJfp6y9jFHHKKmGVFIiU4jSRgU6JMAtusnGZBVuJSRFZ7abqeuro7K7EnB7E1INqeMiTIhICMhkSpvTRnhYuN/PG2qEpOg25WxiY/ZG+kb7xj0MRpOR+n53NSi1Ss38xPl+r+HwcMbD2Jw2v54zFAlJ0YF7rltCRAIJEQksZCEAZpt5XIQx2hi/x/Ro4X1bfOcEISu6yYjURFIQX0BBvJLhPJi5H4d/vBDiiBCixvM7zrN8ixBiUAhR4fn5376+CIXQYjpP22MO/wXAGuAZj4v/68A7Usoi4B3P9zFOSimXeX7+wetRK4Q0U4pOStkhpSz3fB4GbuA2T+8Ffu3Z7NfAB3wUo8IDxozeK9zm8E/xpJwAMAIpEzZdK4S4LIQ4KIRYeJdjPSWEKBVClHZ3d88idIVQZdqiu5fDX0opgTHDdDmQI6VcituiuG+y40kpX5RSlkgpS5KSkmYTu8I96DR1YnME5+ubaYnuLg7/TiFEmmd9GtAFIKUcklKaPJ8PAOFCCGUw0o/YnDae+sNTPPnWk/SP9gc6nDuYTu/1bg7/t4C/8Hz+C+D3nu1TPfsghFjtOUcvCn5DE6ZhV8Eu6vrqePL3T3Kz+2agQ7qF6dzpxhz+Wye8BtkN/DOwQwhRA2z3fAf4CHBNCHEZ+BHwcU/zq+BHvrjqizy79ln6Lf38zZG/4VDtoaDxbohg0ENJSYksLS0NdBgPJPur9vPzsp8jhGBv8V4+uuCjxOjuf7RGCFEmpSyZess7UaY2PeA8Pu9xnln1DFGaKPbf3M83jn6D6t7qgMb0QA2DKdyJEIJHCx/F6XLyw/M/5GDtQQZtgzyx+Al25O8IyKwYRXRzAJVQ8VjRY1gcFn5Z8Us6TZ28fPllKrsr+fSST5NsSPZvPH49m0LACFOFsWf+Hj615FNkRGWgCdNwresaf3/i7znZdBJ/PtsroptDaMI0fPChD7IpZxNhqjDmxc9DF67jxbIX+cG5HzBsHfZLHIro5hg6tY4/W/RnLElZQk1/Desy17GjYAflHeV8Zt9n2Hdjn89jUEQ3BzFoDHxm2WfIi83jYO1BCuML+ebGbzJiH+FCm+8z9Sqim6PE6mL50qovEa+P51cVv0IlVHx59ZdZmDLp/AyvoohuDpMYkchfrf4rwlXh/Pj8j9GoNJhtZp/7PBTRzXGyYrL4ysNfweKw8Nubv8XisNBt9u1UM0V0ChQnFvNUyVOYrWaO1h+lfbjdp+dTRKcAwOqM1Xxy6SfpH+3nl+W/9Om5lBEJhXF2Fe6itL2UMOHbfMmK6BRu4dubvu3zcyjNq4LfUUSn4HcU0Sn4HV84/IUQ4kdCiFohxBUhxNTlAxXmFL5w+D+Gu9xmEe4iwv/u9agVQhpfOPz3Ai9JN+eA2DGrooIC+MbhnwG0TNit1bPs9mMpDv85ii8c/tNCcfjPXab1cvheDn8pZcdEhz/QBmRN2D3Ts+yulJWV9QghmiYsSgR6phNbiPAgXk/ObHeeUnTTcPj/MxMc/p7lXxZCvAo8DAxOaIYnRUp5y61OCFE6W09lMPKAXk/ubPefzp1uzOF/VQhR4Vn2Tdxie00I8TmgCfiYZ90BYDdQC4wAn51tcAoPJlOKTkp5CrhbmeNtk2wvgWfuMy6FB5hgHZF4MdABeBnleiYQFLlMFOYWwXqnU3iAUUSn4HcCIjohxC+FEF1CiGsTlv2jZ4JAhRDisBAi3bM86CcQTHY9E9b9tRBCjmUjDdXrEUL8nRCi7bYchWPrvuG5niohxNQVXKSUfv8BNgErgGsTlkVP+PwV4Geez7uBg7h70GuA84GIeabX41meBbyN+5VSYihfD/B3wHOTbLsAuAxogTygDgi71/EDcqeTUv4J6Ltt2cShtUjeG1YL+gkEk12Ph+8Dz3PrEGEoX89k7AVelVJapZQNuN/P3rPKclA90wkhviuEaAGeAMYq7UxrAkGwIYTYC7RJKS/ftiokr8fDlz2PBL8cmz/JLK4nqEQnpfyWlDIL+A3w5UDHM1uEEBG4R20epBJV/w4UAMuADuCF2R4oqEQ3gd8AH/Z8nvEEgiCgAPfzzWUhRCPumMuFEKmE5vUgpeyUUjqllC7gP3ivCZ3x9QSN6IQQRRO+7gXG8tC/BXza0+tbwzQmEAQaKeVVKWWylDJXugfGW4EVUkojIXg9MF4rZIwPAmM927eAjwshtEKIPNwzxu+d+ilAvaNXcN+i7bj/Qz6He+rUNeAKsB/I8GwrgH/D3Su6CpQEunc3neu5bX0j7/VeQ/J6gJc98V7xCC1twvbf8lxPFfDYVMdXhsEU/E7QNK8KcwdFdAp+RxGdgt9RRKfgdxTRKfgdRXQKfkcRnYLf+f/HXdCTDWukRwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#@title\n", + "n = 100 #@param {type:\"slider\", min:100, max:1000, step:1}\n", + "vaccinated_percent = 40 #@param {type:\"slider\", min:0, max:100, step:1}\n", + "\n", + "import random \n", + "random.seed(37)\n", + "import matplotlib.pyplot as plt \n", + "\n", + "def show_data(pairs,population_ids):\n", + " fig,ax=plt.subplots()\n", + " for pair in pairs:\n", + " plt.plot([population_ids[pair[0]][0],population_ids[pair[1]][0]],\n", + " [population_ids[pair[0]][1],population_ids[pair[1]][1]],'g',alpha=0.4)\n", + " ax.set_aspect('equal', 'box')\n", + " plt.show()\n", + "\n", + "population = [{'id':int(random.random()*(10**8-10**7))+10**7,\\\n", + " 'vaccinated': True if random.random()