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Peter Norvig
GitHub
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@ -19,17 +19,19 @@
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"# Python 3.x Utility Functions\n",
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"\n",
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"%matplotlib inline\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"import re\n",
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"import numpy as np\n",
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"import math\n",
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"import random\n",
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"import urllib.request\n",
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"\n",
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"from collections import Counter, defaultdict, namedtuple, deque, abc, OrderedDict\n",
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"from functools import lru_cache\n",
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@ -40,6 +42,8 @@
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"identity = lambda x: x\n",
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"letters = 'abcdefghijklmnopqrstuvwxyz'\n",
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"\n",
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"cache = lru_cache(None)\n",
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"\n",
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"cat = ''.join\n",
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"\n",
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"Ø = frozenset() # Empty set\n",
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@ -161,6 +165,11 @@
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"def mapt(fn, *args): \n",
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" \"Do a map, and make the results into a tuple.\"\n",
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" return tuple(map(fn, *args))\n",
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"\n",
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"def most_common(seq):\n",
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" \"The item that appears most frequently in sequence.\"\n",
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" [(item, count)] = Counter(seq).most_common(1)\n",
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" return item\n",
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" \n",
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"################ Math Functions\n",
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" \n",
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@ -188,6 +197,13 @@
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" result *= n\n",
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" return result\n",
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"\n",
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"import operator as op\n",
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"\n",
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"operations = {'>': op.gt, '>=': op.ge, '==': op.eq,\n",
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" '<': op.lt, '<=': op.le, '!=': op.ne,\n",
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" '+': op.add, '-': op.sub, '*': op.mul, \n",
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" '/': op.truediv, '**': op.pow}\n",
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"\n",
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"################ 2-D points implemented using (x, y) tuples\n",
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"\n",
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"def X(point): x, y = point; return x\n",
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@ -264,7 +280,9 @@
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -359,7 +377,9 @@
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -388,7 +408,9 @@
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -450,7 +472,9 @@
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -477,7 +501,9 @@
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -543,7 +569,9 @@
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -598,7 +626,9 @@
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -618,7 +648,9 @@
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -663,7 +695,9 @@
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -690,7 +724,9 @@
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -719,7 +755,9 @@
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -750,7 +788,9 @@
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{
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"cell_type": "code",
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"execution_count": 17,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -775,7 +815,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It took me less than five minutes, and my preparation with `Input` and `canon` helped, but I was still too slow to score any points--the top 20 took less than two minutes each."
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"That was easy, but the leaders were three times faster than me."
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]
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},
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{
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@ -790,7 +830,9 @@
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{
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"cell_type": "code",
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"execution_count": 18,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -821,7 +863,9 @@
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{
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"cell_type": "code",
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"execution_count": 19,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -860,7 +904,9 @@
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"name": "stdout",
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@ -914,7 +960,9 @@
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{
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"cell_type": "code",
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"execution_count": 21,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -955,7 +1003,9 @@
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"banks = vector('4\t10\t4\t1\t8\t4\t9\t14\t5\t1\t14\t15\t0\t15\t3\t5')\n",
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@ -983,7 +1033,9 @@
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{
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"cell_type": "code",
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"execution_count": 23,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -1003,7 +1055,9 @@
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{
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"cell_type": "code",
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"execution_count": 24,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -1030,7 +1084,9 @@
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{
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"cell_type": "code",
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"execution_count": 25,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -1057,7 +1113,9 @@
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{
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"cell_type": "code",
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"execution_count": 26,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -1086,7 +1144,9 @@
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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@ -1102,6 +1162,432 @@
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"source": [
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"realloc2(banks)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# [Day 7](https://adventofcode.com/2017/day/7): Memory Reallocation "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First I'll read the data into two dicts as follows: the input line:\n",
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"\n",
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" tcmdaji (40) -> wjbdxln, amtqhf\n",
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" \n",
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"creates:\n",
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"\n",
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" weight['tcmdaji'] = 40\n",
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" above['tcmdaji'] = ['wjbdxln', 'amtqhf']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def towers(lines):\n",
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" \"Return (weight, above) dicts.\"\n",
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" weight = {}\n",
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" above = {}\n",
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" for line in lines:\n",
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" name, w, *rest = re.findall(r'\\w+', line)\n",
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" weight[name] = int(w)\n",
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" above[name] = rest\n",
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" return weight, above\n",
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"\n",
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"weight, above = towers(Input(7))\n",
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"\n",
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"programs = set(above)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now the root progam is the one that is not above anything:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'wiapj'}"
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]
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},
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"execution_count": 29,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"programs - set(flatten(above.values()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Part Two:**\n",
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"\n",
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"A program is *wrong* if it is the bottom of a tower that is a different weight from all its sibling towers:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"def wrong(p): return tower_weight(p) not in map(tower_weight, siblings(p))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here we define `tower_weight`, `siblings`, and the `below` dict:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"def tower_weight(p): return weight[p] + sum(map(tower_weight, above[p]))\n",
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"\n",
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"def siblings(p): \n",
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" \"The other programs at the same level as this one.\"\n",
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" return [] if p not in below else [s for s in above[below[p]] if s != p]\n",
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"\n",
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"below = {a: b for b in programs for a in above[b]}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 32,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'eionkb', 'lsire', 'wiapj', 'ycpcv'}"
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]
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},
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"execution_count": 32,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"set(filter(wrong, programs))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"So these four programs are wrong. Which one should we correct? The one that is wrong, and has no wrong program above it:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'eionkb'"
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]
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},
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"execution_count": 33,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def wrongest(programs):\n",
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" return first(p for p in programs\n",
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" if wrong(p) \n",
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" and not any(wrong(p2) for p2 in above[p]))\n",
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"\n",
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"wrongest(programs) "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now what should we correct it to? To the weight that makes it the same weight as sibling towers:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1072"
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]
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},
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"execution_count": 34,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"def correct(p):\n",
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" \"Return the weight that would make p's tower's weight the same as its sibling towers.\"\n",
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" delta = tower_weight(first(siblings(p))) - tower_weight(p) \n",
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" return weight[p] + delta\n",
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"\n",
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"correct(wrongest(programs))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# [Day 8](https://adventofcode.com/2017/day/8): Memory Reallocation \n",
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"\n",
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"This one looks easy: a simple interpreter for straight-line code where each instruction has 7 tokens. It is nice that my `array` function parses the whole program."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"6828"
|
||||
]
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},
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"execution_count": 35,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"program = array(Input(8))\n",
|
||||
"\n",
|
||||
"def run8(program):\n",
|
||||
" \"Run the program and return final value of registers.\"\n",
|
||||
" registers = defaultdict(int)\n",
|
||||
" for (r, inc, delta, _if, r2, cmp, amount) in program:\n",
|
||||
" if operations[cmp](registers[r2], amount):\n",
|
||||
" registers[r] += delta * (+1 if inc == 'inc' else -1)\n",
|
||||
" return registers\n",
|
||||
"\n",
|
||||
"max(run8(program).values())"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Part Two:**\n",
|
||||
"\n",
|
||||
"Here I modify the interpreter to keep track of the highest value of any register at any time."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 36,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"7234"
|
||||
]
|
||||
},
|
||||
"execution_count": 36,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"def run82(program):\n",
|
||||
" registers = defaultdict(int)\n",
|
||||
" highest = 0\n",
|
||||
" for r, inc, delta, _if, r2, cmp, amount in program:\n",
|
||||
" if operations[cmp](registers[r2], amount):\n",
|
||||
" registers[r] += delta * (+1 if inc == 'inc' else -1)\n",
|
||||
" highest = max(highest, registers[r])\n",
|
||||
" return highest\n",
|
||||
"\n",
|
||||
"run82(program)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# [Day 9](https://adventofcode.com/2017/day/9): Stream Processing\n",
|
||||
"\n",
|
||||
"For this problem I could have a complex finite-state machine that handles all the characters `'{<!>}'`, but I think it is easier to clean up the garbage first:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 37,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'{{{{{{{},},{{},}},{{{{}},{{{{{}}},{}},},{{{{},{,{{{}}}}},},{{{}},{{}}}}},{{,{}},{{},},{}}}},{{{{{}}},{}},{{{{},},{}},{{{}},{{{},},{}},{}},{{}}},{{,},{{{}},{{{{}},{{{},},{}}},{{{{},},{}}},{{{}},{{}}}}}}},{{{},{{}},{{{{},{}}},}},{{{}},{}},{{},{{},{}}},{{{}},{{}}}}},{{{{},{}}},{{},{{{{},{}},{{{},{{}}}}}},{{}}},{},{{{}}}},{{{{},{{{},{{},{}}}},{{{{},{}},{{}}}}}},{{{},{{{{}},{{},{}}},{{{,},{{}}},{{}},{{}}},{{}},{{{{},{},{{}}},{{{{}},{{{{{},{}}},{{}}},{,{}},{}},{}},{},{{{},{}}}},{{{{{},},{}},{,},{{}}},{,},{{{},},{{}}}},{{,},{{{{}},{}},{}},{{{},{}}}}},{{{},},{{},{{}}}},{},{{{{{},{}},{},{{}}},{,},{{},}},{{},{}},{{{}},{}}}}},{{{},},{{},{,{{,{}},}}}}},{},{{},{{},{}}},{{},{,},{,{}}}}},{{{{{{},{}}},{,{}},{{},{,{{}}}}},{{},{}}},{{{}},{{},{}},{{}}},{{{},{{},{}}},{{,}},{{,{}},{{{}},{}},{,{,{}}}}},{{{},{}}}},{{{{{}}},{}},{{{},{{{}},{}},{{},}},{{{},},{{,{}}},{{},{{},{}}}},{{{{}}}},{{{,},{}},{},{{},{{{},},{}}},{{{{{}},{{{},{{},}},}},{{},{}},{,{{},{}}}},{{,{}},{{,{}},}},{{,{}}}}}}}},{{{{{},},{{{{},{}}}}},{{{},},{{,{}},{{},{,{}}}}},{{{},{{{{}}},{}}},{{},{},{,}},{{},{{},}},{{{{}},{}},{{},{}},{{{{}}},{}}}},{{{}},{{},{}}}},{{{{{{},{}},{}},{{,},},{{,}}}},{},{},{{{,{}},{{},{}},{{{}},}},{{},{,},{}},{{{},{}}},{{{{}},},{{},},{{}}}}},{{{{{}},{,},{}},{{},{{{{{},},{{{},{}}}},{{},{{},}}},{},{{{{},{}},{}}}}}},{{},{{},{}}},{{{}},{{},},{,{{}}}}}},{{},{{{},{{}},{,{,}}},{{{}}},{{{{},{}},}}},{{{{,{}},{{,{}},{}}},{{{,{,}},{,}},{}},{{{{{},{}}},{{},{}},{{},{{{},}}}},{{{}}},{{{},{{},{}}}}},{}},{{}}},{{{,{{},{}}},{{},}},{{{}},{}},{{{},{}},{{{{}},{{},},{{{{}},{},{{{,{}},{}}}}}}},{,}},{{},{{{},{}},}}}},{{{{{{,{}},{{}},{{}}},{{{{{},{}},{{},{}},{{}}},{{}},{}},{{},},{,{}}},{{}},{{{}},{,},{,{}}}},{{{{}}},{{{,{}}},{{{}},{,}},{{},{{{}},{{},}},{{{}},{{},}},{{{,},{{{},{}},{}},{}},{{{}},{{},}},{{{{{{{},}}}},{{{,{{}}},{}},{,},{{{{}}},{{}}}},{{{}},{,{{},{}}}}}}}}},{{{}},{{},{}}},{{,},{,{,{}}}}},{{{}}},{{},{{}},{,}}},{{{{{{{},},{},{{{,{}},{}},}}},{},{{{}}}},{{,},{{,{}}},{{{},},}},{{{}},{{{,}},{}},{{}}}},{{},{,{}},{{},{{}}}},{{}},{{{},{{},},{}},{{}},{{},{}}}},{{{{}},{{},}},{{{{}},{{},{}}},{}},{{{{}},{},{{{{,{}}},{}}}},{{,{}},{{{{{},},{{{{}}},{,{}},{{}}}},{,},{}},{{}}},{{},}},{{{{},{{,{}},}},{{}},{{},}}},{{{},{{,{}}}},{{{},},},{{}}}}}},{{{{},},{{}}},{{{{{},{}}},{{,}}},{}},{{},{},{}}},{{{{{}},{{}},{}},{{},{{},{{{}},{{,},{{{},{}},{}},{{},}},{}},{{{{},{{{}},{{}}}}}},{{{},{,{{}}}},{{{,}}},{{{{{{},},{{{}},}},{}},{{}},{{{{}},{,{}}},}},{{{,}},{{{{}}},{},{{},}},{{{,{}},{,{}}},{{{}},{{{{},{}}},{{{{,},},}}},{{}}},{}}},{{},{{,{{},}},{{},}},{{{},{}},}},{{{},{}},{,{}},{,}}},{{{{},{{,{}}}}},{{}},{,}}}},{{,},{{},{}},{}},{{{{{{},{}},{}},{{{{},{}},{{}}},{,{{},{}}},{{},{,}}}},{{},{}}},{,},{{{},{}},{{},{}}}}},{{}},{{{{{{}},{{},{}},{{{},{{}}},{}}}},{{{{{},{{}}},{}}}},{{{}},{},{,{}}},{{{{}},{}},{{},{{{{},{{}}}}},{{{},{{}},{,{}}}}}}}}},{{{{{}},},{},{}},{}}},{{},{{{,{}},{,},{{}}},{}},{{,{}},{{{},},{}},{{{}},}},{{{{{}},},{{{,{}},},{,},{{{}},}},{}},{{{{}},{}},{{}}}}}},{{{{{,{}},{},{}},{{}}}},{{{,},{{{},{}}},{{{{},{{{},}}},{}},{{{},},{{,}}},{,{}}}},{{{{},{}},},{{,{{}}}},{{},{}}},{{{},}}},{},{{{{},},{{{}},{}},{{{{{}},{{}}},{}}}},{{{,},{{},{}}},{{},{{}}}},{{{},{{},{}}},{{{},}},{{{}},{},{,{}}},{{{},{{},{}},{,{}}}}}}}}\\n'"
|
||||
]
|
||||
},
|
||||
"execution_count": 37,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"text1 = Input(9).read() # Read text\n",
|
||||
"text2 = re.sub(r'!.', '', text1) # Delete canceled characters\n",
|
||||
"text3 = re.sub(r'<.*?>', '', text2) # Delete garbage\n",
|
||||
"text3"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Now I can deal with nested braces (which can't be handled with regular expressions):"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 38,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"9662"
|
||||
]
|
||||
},
|
||||
"execution_count": 38,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"def total_score(text):\n",
|
||||
" \"Total of group scores; each group scores one more than the group it is nested in.\"\n",
|
||||
" total = 0\n",
|
||||
" outer = [0] # Stack of scores of groups nested outside current group\n",
|
||||
" for c in text:\n",
|
||||
" if c == '{':\n",
|
||||
" score = outer[-1] + 1\n",
|
||||
" total += score\n",
|
||||
" outer.append(score)\n",
|
||||
" elif c == '}':\n",
|
||||
" outer.pop()\n",
|
||||
" return total\n",
|
||||
"\n",
|
||||
"total_score(text3)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"**Part Two:**\n",
|
||||
"\n",
|
||||
"At first I thought that the amount of garbage is just the difference in lengths of `text2` and `text3`:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 39,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"5989"
|
||||
]
|
||||
},
|
||||
"execution_count": 39,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"len(text2) - len(text3)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"But that turned out to be wrong; that counts all of `'<...>'`, whereas I'm not suppossed to count the opening and closing angle brackets, just the `'...'` in the middle. So that would be:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 41,
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"4903"
|
||||
]
|
||||
},
|
||||
"execution_count": 41,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"text4 = re.sub(r'<.*?>', '<>', text2) # Delete inner garbage\n",
|
||||
"\n",
|
||||
"len(text2) - len(text4)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
@ -1120,7 +1606,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.5.3"
|
||||
"version": "3.6.0"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
Loading…
Reference in New Issue
Block a user