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Diffstat (limited to 'expl.ipynb')
| -rw-r--r-- | expl.ipynb | 458 |
1 files changed, 458 insertions, 0 deletions
diff --git a/expl.ipynb b/expl.ipynb new file mode 100644 index 0000000..5352cf4 --- /dev/null +++ b/expl.ipynb @@ -0,0 +1,458 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Grenadine', 'Bourbon', 'White rum', 'Campari', 'Strawberry syrup', 'Angostura bitters', 'Gin', 'Lime juice', 'Vodka', 'Lillet Blonde', 'Sweet vermouth', 'Dry vermouth', 'Kirsch']\n" + ] + } + ], + "source": [ + "import json\n", + "skip = [\n", + " 'Lime juice',\n", + " 'Syrup',\n", + " 'Lemon juice',\n", + " 'Orange juice',\n", + " 'Cream',\n", + " 'Soda water',\n", + " 'Cola',\n", + " 'Hot coffee',\n", + " 'Egg yolk',\n", + " 'Coconut milk',\n", + " 'Ginger beer',\n", + " 'Pineapple juice',\n", + " 'Grapefruit juice',\n", + " 'Cranberry juice',\n", + " 'Tomato juice',\n", + " 'Olive juice',\n", + " 'Ginger Ale',\n", + "]\n", + "skip = []\n", + "recipesj = json.load(open('recipes-fix.json'))\n", + "ingredients = set()\n", + "for recipe in recipesj:\n", + " for ingredient in recipe['ingredients']:\n", + " if 'special' in ingredient:\n", + " continue\n", + " if ingredient['ingredient'] in skip:\n", + " continue\n", + " ingredients.add(ingredient['ingredient'])\n", + "ingredientsl = list(ingredients)\n", + "ingredientsm = dict(zip(ingredientsl, range(len(ingredientsl))))\n", + "recipes = []\n", + "for recipe in recipesj:\n", + " x = set()\n", + " for ingredient in recipe['ingredients']:\n", + " if 'special' in ingredient:\n", + " continue\n", + " if ingredient['ingredient'] in skip:\n", + " continue\n", + " y = ingredientsm[ingredient['ingredient']]\n", + " x.add(y)\n", + " recipes.append(x)\n", + "n_ingredients = len(ingredientsl)\n", + "print(ingredientsl)" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "13" + ] + }, + "execution_count": 213, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_ingredients" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 214, + "metadata": {}, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "[Errno 2] No such file or directory: 'sol.2'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m<ipython-input-214-5e2507ee49c6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlinesf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'sol.2'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlinesf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplitlines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mlinesf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0msol\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mseen\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'sol.2'" + ] + } + ], + "source": [ + "linesf = open('sol.2')\n", + "lines = linesf.read().splitlines()\n", + "linesf.close()\n", + "sol = []\n", + "seen = set()\n", + "batch = None\n", + "batches = []\n", + "oldstep = None\n", + "for line in lines:\n", + " if 'y' in line:\n", + " y = line.split()[1].split('_')[-1]\n", + " if int(y) in sol:\n", + " continue\n", + " sol.append(int(y))\n", + " if 'r' in line:\n", + " step, r = line.split()[1][1:].split('_')\n", + " step = int(step)\n", + " r = int(r)\n", + " if step != oldstep:\n", + " if batch is not None:\n", + " batches.append((oldstep, batch))\n", + " batch = []\n", + " oldstep = step\n", + " if r not in seen:\n", + " batch.append(r)\n", + " seen.add(r)\n", + "batches.append((oldstep, batch))\n", + "len(batches), len(sol)" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1. Vodka | Sea Breeze, Screwdriver, Bloody Mary, Moscow Mule\n", + "2. White rum | Mojito, Cuba Libre, Pina Colada, Daiquiri\n", + "3. Triple Sec | Lemon Drop Martini, Cosmopolitan, Kamikaze\n", + "4. Tequila | Margarita, Tommy's Margarita, Vampiro\n", + "5. Gin | Long Island Iced Tea, Gin Fizz, John Collins, White Lady\n", + "6. Cognac | Horse's Neck, Sidecar, Between the Sheets\n", + "7. Galliano | Yellow Bird, Golden Dream, Harvey Wallbanger\n", + "8. Grenadine | Bacardi, Tequila Sunrise\n", + "9. Cherry liqueur | Aviation, Mary Pickford, Hemingway Special\n", + "10. Bourbon | Whiskey Sour, Mint Julep\n", + "11. Champagne | Mimosa, French 75\n", + "12. Angostura bitters | Old Fashioned, Champagne Cocktail\n", + "13. Dry vermouth | Dirty Martini, Dry Martini\n", + "14. DiSaronno | God Mother, French Connection\n", + "15. Dark rum | Planter's Punch, Dark 'n' Stormy\n", + "16. Coffee liqueur | Espresso Martini, Black Russian\n", + "17. Créme de Menthe | Stinger\n", + "18. Créme de Cacao | Grasshopper, Alexander\n", + "19. Pisco | Pisco Sour\n", + "20. Créme de Cassis | Russian Spring Punch\n", + "21. Dry white wine | Kir\n", + "22. Cachaca | Caipirinha\n", + "23. Peach bitters | Derby\n", + "24. Peach schnapps | Sex on the Beach\n", + "25. Absinthe | Monkey Gland\n", + "26. Apricot brandy | Paradise\n", + "27. Prosecco | Barracuda\n", + "28. Raspberry syrup | Clover Club\n", + "29. Campari | \n", + "30. Sweet vermouth | Negroni, Americano\n", + "31. Rye | Manhattan\n", + "32. Red Port | Porto Flip\n", + "33. Blackberry liqueur | Bramble\n", + "34. Irish whiskey | Irish Coffee\n", + "35. Peach puree | Bellini\n", + "36. Orgeat | Mai-tai\n", + "37. Scotch | God Father\n", + "38. Orange bitters | Casino\n", + "39. Drambuie | Rusty Nail\n", + "40. Peychaud's bitters | Sazerac\n", + "41. Calvados | Angel Face\n", + "42. Aperol | Spritz Veneziano\n", + "43. DOM Bénédictine | Singapore Sling\n", + "44. Cream liqueur | B52\n", + "45. Lillet Blonde | Vesper\n", + "46. Maraschino | Tuxedo\n", + "47. Orange flower water | Ramos Fizz\n", + "48. Raspberry liqueur | French Martini\n", + "49. Strawberry syrup | \n", + "50. Kirsch | Rose\n" + ] + } + ], + "source": [ + "def pad(s, n):\n", + " return s + (n - len(s))*' '\n", + "for i, (y, (step, batch)) in enumerate(zip(sol, batches)):\n", + " drinks = [recipesj[r]['name'] for r in batch]\n", + " print(pad(str(i+1) + '. ' + ingredientsl[y], 23) + ' | ' + ', '.join(drinks))" + ] + }, + { + "cell_type": "code", + "execution_count": 169, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "White rum\n", + "Vodka\n", + "Triple Sec\n", + "Cognac\n", + "Gin\n", + "Tequila\n", + "Galliano\n", + "Grenadine\n", + "Cherry liqueur\n", + "Champagne\n", + "Bourbon\n", + "Angostura bitters\n", + "Dark rum\n", + "Coffee liqueur\n", + "DiSaronno\n", + "Dry vermouth\n", + "Lillet Blonde\n", + "Pisco\n", + "Raspberry syrup\n", + "Red Port\n", + "Cream liqueur\n", + "Créme de Menthe\n", + "Créme de Cacao\n", + "Blackberry liqueur\n", + "Raspberry liqueur\n", + "Orgeat\n", + "Prosecco\n", + "Peach puree\n", + "Aperol\n", + "Peach schnapps\n", + "Absinthe\n", + "Peach bitters\n", + "Irish whiskey\n", + "Peychaud's bitters\n", + "DOM Bénédictine\n", + "Apricot brandy\n", + "Calvados\n", + "Orange flower water\n", + "Créme de Cassis\n", + "Dry White Wine\n", + "Scotch\n", + "Drambuie\n", + "Orange Bitters\n", + "Maraschino\n", + "Cachaca\n", + "Campari\n", + "Sweet vermouth\n", + "Rye\n", + "Kirsch\n", + "Strawberry syrup\n" + ] + } + ], + "source": [ + "from collections import Counter\n", + "recipesc = recipes.copy()\n", + "greedysol = []\n", + "\n", + "for step in range(n_ingredients):\n", + " c = Counter()\n", + " for recipe in recipesc:\n", + " if len(recipe) == 1:\n", + " c.update([list(recipe)[0]])\n", + " ingrs = c.most_common()\n", + " if len(ingrs) == 0:\n", + " ingr = list(set.union(*recipesc))[0]\n", + " else:\n", + " ingr = ingrs[0][0]\n", + " greedysol.append(ingr)\n", + " for i, recipe in enumerate(recipesc):\n", + " recipesc[i] = recipe - {ingr}\n", + "for y in greedysol:\n", + " print(ingredientsl[y])" + ] + }, + { + "cell_type": "code", + "execution_count": 174, + "metadata": {}, + "outputs": [], + "source": [ + "def score(recipes, sol):\n", + " t = 0\n", + " recipesc = recipes.copy()\n", + " for i, y in enumerate(sol):\n", + " for recipe in recipesc:\n", + " if recipe == {y}:\n", + " t += (len(ingredientsl)-i)\n", + " for i, recipe in enumerate(recipesc):\n", + " recipesc[i] = recipe - {y}\n", + " return t" + ] + }, + { + "cell_type": "code", + "execution_count": 175, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2501, 2495)" + ] + }, + "execution_count": 175, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "score(recipes, sol), score(recipes, greedysol)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} |