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How to use new_score method in hypothesis
Best Python code snippet using hypothesis
food_rs_webservice.py
Source:food_rs_webservice.py 
1from flask import Flask, request2from flask_restful import Resource, Api3from json import dumps4import pandas as pd5import numpy as np6app = Flask(__name__)7api = Api(app)8class Mood(Resource):9 def get(self):10 url_dataset_it = 'dataset.csv'11 url_dataset_en = 'dataset_en.csv'12 lang = request.args.get('lang')13 if lang == 'en':14 df = pd.read_csv(url_dataset_en)15 else:16 df = pd.read_csv(url_dataset_it)17 # print('dataset language: ', lang)18 # dfFromIngredient19 def dfFromIngredient(df, searchIngrendient):20 new_rows = []21 returnDf = pd.DataFrame()22 for index, row in df.iterrows():23 listIngredients = row.ingredients.strip("[ ]").split(", ")24 if any(not (ingredient.lower().find(searchIngrendient)) for ingredient in listIngredients):25 new_rows.append(row)26 return returnDf.append(pd.DataFrame(new_rows, columns=df.columns))27 def rescoreOverweight(row):28 new_score = row.score29 if row.calories < 133.35:30 new_score = new_score * 231 if row.calories >= 133.35 and row.calories <= 400.05:32 new_score = new_score * 1.233 if row.calories > 400.05:34 new_score = new_score * 0.135 if row.fat < 4.65:36 new_score = new_score * 237 if row.fat >= 4.65 and row.fat <= 13.95:38 new_score = new_score * 1.239 if row.fat > 13.95:40 new_score = new_score * 0.141 if row.carbohydrates >= 18 and row.carbohydrates <= 54:42 new_score = new_score * 1.243 if row.carbohydrates > 54:44 new_score = new_score * 1.545 if row.fibers < 1.65:46 new_score = new_score * 0.147 if row.fibers >= 1.65 and row.fibers <= 4.95:48 new_score = new_score * 1.249 if row.fibers > 4.95:50 new_score = new_score * 251 return new_score52 def rescoreObesity(row):53 new_score = row.score54 if row.calories < 133.35:55 new_score = new_score * 356 if row.calories >= 133.35 and row.calories <= 400.05:57 new_score = new_score * 1.258 if row.calories > 400.05:59 new_score = new_score * 0.0160 if row.fat < 4.65:61 new_score = new_score * 362 if row.fat >= 4.65 and row.fat <= 13.95:63 new_score = new_score * 164 if row.fat > 13.95:65 new_score = new_score * 0.0166 if row.carbohydrates >= 18 and row.carbohydrates <= 54:67 new_score = new_score * 168 if row.carbohydrates > 54:69 new_score = new_score * 2.570 if row.fibers < 1.65:71 new_score = new_score * 0.0172 if row.fibers >= 1.65 and row.fibers <= 4.95:73 new_score = new_score * 174 if row.fibers > 4.95:75 new_score = new_score * 376 return new_score77 def rescoreObesityPlus(row):78 new_score = row.score79 if row.calories < 133.35:80 new_score = new_score * 481 if row.calories >= 133.35 and row.calories <= 400.05:82 new_score = new_score * 0.983 if row.calories > 400.05:84 new_score = new_score * 0.00185 if row.fat < 4.65:86 new_score = new_score * 487 if row.fat >= 4.65 and row.fat <= 13.95:88 new_score = new_score * 0.989 if row.fat > 13.95:90 new_score = new_score * 0.00191 if row.carbohydrates >= 18 and row.carbohydrates <= 54:92 new_score = new_score * 0.993 if row.carbohydrates > 54:94 new_score = new_score * 3.595 if row.fibers < 1.65:96 new_score = new_score * 0.00197 if row.fibers >= 1.65 and row.fibers <= 4.95:98 new_score = new_score * 0.999 if row.fibers > 4.95:100 new_score = new_score * 4101 return new_score102 def rescoreUnderweight(row):103 new_score = row.score104 if row.calories < 133.35:105 new_score = new_score * 0.1106 if row.calories >= 133.35 and row.calories <= 400.05:107 new_score = new_score * 1.2108 if row.calories > 400.05:109 new_score = new_score * 2110 if row.carbohydrates < 18:111 new_score = new_score * 0.1112 if row.carbohydrates >= 18 and row.carbohydrates <= 54:113 new_score = new_score * 1.2114 if row.carbohydrates > 54:115 new_score = new_score * 2116 if row.proteins < 3.35:117 new_score = new_score * 0.1118 if row.proteins >= 3.35 and row.proteins <= 10.05:119 new_score = new_score * 1.2120 if row.proteins > 10.05:121 new_score = new_score * 2122 return new_score123 def rescoreActivityMedium(row):124 new_score = row.score125 if row.calories > 400.05:126 new_score = new_score * 1.5127 if row.calories >= 133.35 and row.calories <= 400.05:128 new_score = new_score * 1.2129 if row.calories < 133.35:130 new_score = new_score * 0.1131 if row.proteins > 10.05:132 new_score = new_score * 1.5133 if row.proteins >= 3.35 and row.proteins <= 10.05:134 new_score = new_score * 1.2135 if row.proteins < 3.35:136 new_score = new_score * 0.1137 if row.carbohydrates > 54:138 new_score = new_score * 1.5139 if row.carbohydrates >= 18 and row.carbohydrates <= 54:140 new_score = new_score * 1.2141 if row.carbohydrates < 18:142 new_score = new_score * 0.1143 return new_score144 def rescoreActivityHigh(row):145 new_score = row.score146 if row.calories > 400.05:147 new_score = new_score * 2148 if row.calories >= 133.35 and row.calories <= 400.05:149 new_score = new_score * 1.2150 if row.calories < 133.35:151 new_score = new_score * 0.1152 if row.proteins > 10.05:153 new_score = new_score * 2154 if row.proteins >= 3.35 and row.proteins <= 10.05:155 new_score = new_score * 1.2156 if row.proteins < 3.35:157 new_score = new_score * 0.1158 if row.carbohydrates > 54:159 new_score = new_score * 2160 if row.carbohydrates >= 18 and row.carbohydrates <= 54:161 new_score = new_score * 1.2162 if row.carbohydrates < 18:163 new_score = new_score * 0.1164 return new_score165 cibiAntistress = ['latte intero', 'riso', 'pollo', 'cereali integrali', 'manzo', 'fagioli', 'noci',166 'cioccolato', 'formaggio', 'broccoli']167 def isAntistress(ingredients):168 listIngredients = ingredients.strip("[ ]").split(", ")169 antistress = 0170 for elem in cibiAntistress:171 if any(elem in ingredient.lower() for ingredient in listIngredients):172 antistress += 1173 antiS = antistress / len(cibiAntistress)174 return (antiS)175 def rescoreStress(row):176 new_score = row.score177 if row.sodium < sodiumAvg - sodiumStd:178 new_score = new_score * 2179 if row.sodium >= sodiumAvg - sodiumStd and row.sodium <= sodiumAvg + sodiumStd:180 new_score = new_score * 1.2181 if row.sodium > sodiumAvg + sodiumStd:182 new_score = new_score * 0.1183 if row.antistress == 0.1:184 new_score = new_score * 10185 if row.antistress == 0.2:186 new_score = new_score * 20187 if row.antistress >= 0.3:188 new_score = new_score * 30189 return new_score190 def rescoreDepression(row):191 new_score = row.score192 if row.saturatedFat < 1.35:193 new_score = new_score * 2194 if row.saturatedFat >= 1.35 and row.saturatedFat <= 4.05:195 new_score = new_score * 1.2196 if row.saturatedFat > 4.05:197 new_score = new_score * 0.1198 if row.carbohydrates > 54:199 new_score = new_score * 2200 if row.carbohydrates >= 18 and row.carbohydrates <= 54:201 new_score = new_score * 1.2202 if row.carbohydrates < 18:203 new_score = new_score * 0.1204 if row.fibers >= 1.65 and row.fibers <= 4.95:205 new_score = new_score * 1.5206 if row.fibers > 4.95:207 new_score = new_score * 2208 return new_score209 def rescoreMoodBad(row):210 if row.sugars < 6:211 return row.score * 0.1212 if row.sugars >= 6 and row.sugars <= 18:213 return row.score * 1.2214 if row.sugars > 18:215 return row.score * 2216 def rescoreCoffe(row):217 listIngredients = row.ingredients.strip("[ ]").split(", ")218 if 'caffè' in listIngredients:219 return row.score * 0.5220 if 'Caffè' in listIngredients:221 return row.score * 0.5222 else:223 return row.score224 richMagnesium = ['crusca', 'mandorle', 'anacardi', 'cereali integrali', 'piselli', 'fagioli', 'datteri',225 'aneto', 'fichi', 'nocciole']226 def isRichMagnesium(ingredients):227 listIngredients = ingredients.strip("[ ]").split(", ")228 magnesium = 0229 for elem in richMagnesium:230 if any(elem in ingredient.lower() for ingredient in listIngredients):231 magnesium += 1232 mg = magnesium / len(richMagnesium)233 return (mg)234 def rescoreMagnesium(row):235 if row.magnesium == 0.1:236 return row.score * 10237 if row.magnesium == 0.2:238 return row.score * 20239 if row.magnesium == 0.3:240 return row.score * 30241 else:242 return row.score243 def rescoreSleep(row):244 new_score = row.score245 if row.fat > 13.95:246 new_score = new_score * 0.1247 return new_score248 def rescoreDifficulty(row, difficulty):249 new_score = row.score250 if difficulty == 1:251 if row.difficulty == 'Molto facile':252 new_score = new_score * 2253 if difficulty == 2:254 if row.difficulty == 'Facile':255 new_score = new_score * 2256 if row.difficulty == 'Molto facile':257 new_score = new_score * 1.5258 if difficulty == 3:259 if row.difficulty == 'Media':260 new_score = new_score * 2261 if row.difficulty == 'Facile':262 new_score = new_score * 1.5263 if row.difficulty == 'Molto facile':264 new_score = new_score * 1.5265 if difficulty == 4:266 if row.difficulty == 'Difficile':267 new_score = new_score * 2268 if row.difficulty == 'Media':269 new_score = new_score * 1.5270 if row.difficulty == 'Facile':271 new_score = new_score * 1.5272 if row.difficulty == 'Molto facile':273 new_score = new_score * 1.5274 if difficulty == 5:275 if row.difficulty == 'Molto difficile':276 new_score = new_score * 2277 if row.difficulty == 'Difficile':278 new_score = new_score * 1.5279 if row.difficulty == 'Media':280 new_score = new_score * 1.5281 if row.difficulty == 'Facile':282 new_score = new_score * 1.5283 if row.difficulty == 'Molto facile':284 new_score = new_score * 1.5285 return new_score286 def rescoreGoalPlus(row):287 new_score = row.score288 if row.calories < 133.35:289 new_score = new_score * 0.1290 if row.calories >= 133.35 and row.calories <= 400.05:291 new_score = new_score * 1.2292 if row.calories > 400.05:293 new_score = new_score * 2294 if row.carbohydrates > 54:295 new_score = new_score * 2296 if row.carbohydrates >= 18 and row.carbohydrates <= 54:297 new_score = new_score * 1.2298 if row.carbohydrates < 18:299 new_score = new_score * 0.1300 if row.proteins < 3.35:301 new_score = new_score * 0.1302 if row.proteins >= 3.35 and row.proteins <= 10.05:303 new_score = new_score * 1.2304 if row.proteins > 10.05:305 new_score = new_score * 2306 return new_score307 def rescoreGoalMinus(row):308 new_score = row.score309 if row.calories < 133.35:310 new_score = new_score * 2311 if row.calories >= 133.35 and row.calories <= 400.05:312 new_score = new_score * 1.2313 if row.calories > 400.05:314 new_score = new_score * 0.1315 if row.carbohydrates > 54:316 new_score = new_score * 1.4317 if row.carbohydrates >= 18 and row.carbohydrates <= 54:318 new_score = new_score * 1.2319 if row.fat < 4.65:320 new_score = new_score * 2321 if row.fat > 13.95:322 new_score = new_score * 0.1323 return new_score324 def rescoreCost(row, cost):325 new_score = row.score326 if cost == 1:327 if row.cost == 'Molto basso':328 new_score = new_score * 2329 else:330 new_score = new_score * 0.1331 if cost == 2:332 if row.cost == 'Basso':333 new_score = new_score * 2334 elif row.cost == 'Molto basso':335 new_score = new_score * 1.5336 else:337 new_score = new_score * 0.1338 if cost == 3:339 if row.cost == 'Medio':340 new_score = new_score * 2341 elif row.cost == 'Basso':342 new_score = new_score * 1.5343 elif row.cost == 'Molto basso':344 new_score = new_score * 1.5345 else:346 new_score = new_score * 0.1347 if cost == 4:348 if row.cost == 'Elevato':349 new_score = new_score * 2350 elif row.cost == 'Medio':351 new_score = new_score * 1.5352 elif row.cost == 'Basso':353 new_score = new_score * 1.5354 elif row.cost == 'Molto basso':355 new_score = new_score * 1.5356 return new_score357 def rescoreTime(row, time):358 new_score = row.score359 i = len(row.totalTime) - 2360 potenzaDieci = 1361 totalTime = 0362 while i >= 2:363 totalTime = totalTime + int(row.totalTime[i]) * potenzaDieci364 potenzaDieci = potenzaDieci * 10365 i -= 1366 if time == totalTime:367 new_score = new_score * 2368 elif time < totalTime:369 new_score = new_score * 0.1370 elif time > totalTime:371 new_score = new_score * 1.5372 return new_score373 def rescoreU20(row):374 new_score = row.score375 if row.carbohydrates > 54:376 new_score = new_score * 2377 if row.carbohydrates >= 18 and row.carbohydrates <= 54:378 new_score = new_score * 1.2379 if row.carbohydrates < 18:380 new_score = new_score * 0.1381 if row.saturatedFat < 1.35:382 new_score = new_score * 2383 if row.saturatedFat >= 1.35 and row.saturatedFat <= 4.05:384 new_score = new_score * 1.2385 if row.saturatedFat > 4.05:386 new_score = new_score * 0.1387 if row.fibers < 1.65:388 new_score = new_score * 0.1389 if row.fibers >= 1.65 and row.fibers <= 4.95:390 new_score = new_score * 1.2391 if row.fibers > 4.95:392 new_score = new_score * 2393 return new_score394 def rescoreU30(row):395 new_score = row.score396 if row.carbohydrates > 54:397 new_score = new_score * 2398 if row.carbohydrates >= 18 and row.carbohydrates <= 54:399 new_score = new_score * 1.2400 if row.carbohydrates < 18:401 new_score = new_score * 0.1402 if row.proteins < 3.35:403 new_score = new_score * 0.1404 if row.proteins >= 3.35 and row.proteins <= 10.05:405 new_score = new_score * 1.2406 if row.proteins > 10.05:407 new_score = new_score * 2408 if row.fibers < 1.65:409 new_score = new_score * 0.1410 if row.fibers >= 1.65 and row.fibers <= 4.95:411 new_score = new_score * 1.2412 if row.fibers > 4.95:413 new_score = new_score * 2414 return new_score415 def rescoreU40(row):416 new_score = row.score417 if row.proteins < 3.35:418 new_score = new_score * 0.1419 if row.proteins >= 3.35 and row.proteins <= 10.05:420 new_score = new_score * 1.2421 if row.proteins > 10.05:422 new_score = new_score * 2423 if row.fat < 4.65:424 new_score = new_score * 2425 if row.fat >= 4.65 and row.fat <= 13.95:426 new_score = new_score * 1.2427 if row.fat > 13.95:428 new_score = new_score * 0.1429 return new_score430 def rescoreU60(row):431 new_score = row.score432 if row.fibers < 1.65:433 new_score = new_score * 0.1434 if row.fibers >= 1.65 and row.fibers <= 4.95:435 new_score = new_score * 1.2436 if row.fibers > 4.95:437 new_score = new_score * 2438 if row.fat < 4.65:439 new_score = new_score * 2440 if row.fat >= 4.65 and row.fat <= 13.95:441 new_score = new_score * 1.2442 if row.fat > 13.95:443 new_score = new_score * 0.1444 return new_score445 def rescoreO60(row):446 new_score = row.score447 if row.proteins < 3.35:448 new_score = new_score * 0.1449 if row.proteins >= 3.35 and row.proteins <= 10.05:450 new_score = new_score * 1.2451 if row.proteins > 10.05:452 new_score = new_score * 2453 if row.calories < 133.35:454 new_score = new_score * 0.1455 if row.calories >= 133.35 and row.calories <= 400.05:456 new_score = new_score * 1.2457 if row.calories > 400.05:458 new_score = new_score * 2459 return new_score460 def score(row):461 score = row.ratingValue * np.log10(row.ratingCount)462 return score463 df['score'] = df.apply(score, axis=1)464 # calcolo medie prima di 'tagliare' il DataFrame465 #sugarAvg = df.sugars.mean()466 #sugarStd = df.sugars.std()467 #proteinsAvg = df.proteins.mean()468 #proteinsStd = df.proteins.std()469 #caloriesAvg = df.calories.mean()470 #caloriesStd = df.calories.std()471 #fatAvg = df.fat.mean()472 #fatStd = df.fat.std()473 #sFatAvg = df.saturatedFat.mean()474 #sFatStd = df.saturatedFat.std()475 sodiumAvg = df.sodium.mean()476 sodiumStd = df.sodium.std()477 #carbsAvg = df.carbohydrates.mean()478 #carbsStd = df.carbohydrates.std()479 #fiberAvg = df.fibers.mean()480 #fiberStd = df.fibers.std()481 # accorgimenti parametri482 n = int(request.args.get('n')) if (request.args.get('n') != None) else -1483 recipeName = request.args.get('recipeName')484 ingredient = request.args.get('ingredient')485 category = request.args.get('category')486 cost = request.args.get('cost')487 isLowNickel = int(request.args.get('isLowNickel')) if (request.args.get('isLowNickel') != None) else ''488 isVegetarian = int(request.args.get('isVegetarian')) if (request.args.get('isVegetarian') != None) else ''489 isLactoseFree = int(request.args.get('isLactoseFree')) if (request.args.get('isLactoseFree') != None) else ''490 isGlutenFree = int(request.args.get('isGlutenFree')) if (request.args.get('isGlutenFree') != None) else ''491 isLight = int(request.args.get('isLight')) if (request.args.get('isLight') != None) else ''492 user_difficulty = int(request.args.get('difficulty')) if (request.args.get('difficulty') != None) else ''493 goal = int(request.args.get('goal')) if (request.args.get('goal') != None) else ''494 user_cost = int(request.args.get('user_cost')) if (request.args.get('user_cost') != None) else ''495 user_time = int(request.args.get('user_time')) if (request.args.get('user_time') != None) else ''496 # age = int(request.args.get('age')) if (request.args.get('age') != None) else ''497 age = request.args.get('age')498 # orario499 hour = request.args.get('hour')500 # mood501 mood = request.args.get('mood')502 activity = request.args.get('activity')503 stress = request.args.get('stress')504 sleep = request.args.get('sleep')505 depression = request.args.get('depression')506 # overweight = request.args.get('overweight')507 # underweight = request.args.get('underweight')508 #height = request.args.get('height')509 #weight = request.args.get('weight')510 #bmi = weight / (height * height)511 bmi = float(request.args.get('fatclass')) if (request.args.get('fatclass') != None) else ''512 healthy = request.args.get('healthy')513 # filtro il DF sulle ricette salutari514 # https://acmrecsys.github.io/rsss2019/Food-Recommender-ctrattner.pdf515 if healthy == 'high':516 # print("healthy: ", healthy)517 df = df[(df.sugars <= 5) & (df.fat <= 3) & (df.saturatedFat <= 1.5)]518 if healthy == 'medium':519 # print("healthy: ", healthy)520 df = df[(df.sugars >= 5) & (df.sugars <= 15) &521 (df.fat >= 3) & (df.fat <= 20) &522 (df.saturatedFat >= 1.5) & (df.saturatedFat <= 5)523 ]524 if healthy == 'low':525 # print("healthy: ", healthy)526 df = df[(df.sugars >= 15) & (df.fat >= 20) & (df.saturatedFat > 5) & (df.sodium >= 1.5)]527 # filtro il DataFrame su nome della ricetta cercata528 if recipeName:529 # print("recipeName: " + recipeName)530 df = df[df.title.str.contains(recipeName, case=False)]531 # filtro il DataFrame su ingrediente della ricetta cercato532 if ingredient:533 # print("ingredient: " + ingredient)534 df = dfFromIngredient(df, ingredient)535 # categories = df.category.unique()536 # ['Dolci', 'Primi piatti', 'Lievitati', 'Salse e Sughi', 'Piatti Unici', 'Contorni', 'Antipasti', 'Secondi piatti', 'Torte salate', 'Bevande', 'Insalate', 'Marmellate e Conserve']537 if category:538 # print('category: ' + category)539 df = df[df.category == category]540 # cost = df.cost.unique()541 # ['Molto basso', 'Medio', 'Basso', 'None', 'Elevato', 'Molto elevata']542 if cost:543 # print("cost: " + cost)544 df = df[df.cost == cost]545 if isLowNickel:546 # print("isLowNickel: " + str(isLowNickel))547 df = df[df.isLowNickel == isLowNickel]548 if isVegetarian:549 # print("isVegetarian: " + str(isVegetarian))550 df = df[df.isVegetarian == isVegetarian]551 if isLactoseFree:552 # print("isLactoseFree: " + str(isLactoseFree))553 df = df[df.isLactoseFree == isLactoseFree]554 if isGlutenFree:555 # print("isGlutenFree: " + str(isGlutenFree))556 df = df[df.isGlutenFree == isGlutenFree]557 if isLight:558 # print("isLight: " + str(isLight))559 df = df[df.isLight == isLight]560 # if overweight:561 # print('overweight:', overweight)562 # df.score = df.apply(rescoreOverweight, axis=1)563 # df = df.sort_values('score', ascending=False)564 # print(df[['title', 'score']].head(10))565 # if underweight:566 # print('underweight: ', underweight)567 # df.score = df.apply(rescoreUnderweight, axis=1)568 # df = df.sort_values('score', ascending=False)569 # print(df[['title', 'score']].head(10))570 bmiWeight = 'normal'571 if bmi < 19:572 bmiWeight = 'under'573 df.score = df.apply(rescoreUnderweight, axis=1)574 elif bmi >= 25 and bmi < 30:575 bmiWeight = 'over'576 df.score = df.apply(rescoreOverweight, axis=1)577 elif bmi >= 30 and bmi < 35:578 bmiWeight = 'over'579 df.score = df.apply(rescoreObesity, axis=1)580 elif bmi >= 35:581 bmiWeight = 'over'582 df.score = df.apply(rescoreObesityPlus, axis=1)583 df = df.sort_values('score', ascending=False)584 if mood == 'bad':585 # print('mood: bad')586 # print("sugarAvg: " + str(sugarAvg))587 # df = df[df.sugar > sugarAvg]588 df.score = df.apply(rescoreMoodBad, axis=1)589 df = df.sort_values('score', ascending=False)590 # print(df[['title', 'score']].head(10))591 if activity == 'medium':592 df.score = df.apply(rescoreActivityMedium, axis=1)593 df = df.sort_values('score', ascending=False)594 if activity == 'high':595 # print('activity: high')596 # print("caloriesAvg: " + str(caloriesAvg))597 # print("proteinsAvg: " + str(proteinsAvg))598 # df = df[(df.calories > caloriesAvg) & (df.proteins > proteinsAvg)]599 df.score = df.apply(rescoreActivityHigh, axis=1)600 df = df.sort_values('score', ascending=False)601 # print(df[['title', 'score']].head(10))602 # stress => cibo salato (https://www.nutritestesso.it/it/lo-stretto-legame-cibo-ed-emozioni/)603 if stress == 'yes':604 # print('stress : ' + str(stress))605 # print("sodiumAvg: " + str(sodiumAvg))606 # df = df[df.sodium > sodiumAvg]607 df['antistress'] = df.ingredients.apply(isAntistress)608 df.score = df.apply(rescoreStress, axis=1)609 df.score = df.apply(rescoreCoffe, axis=1)610 df = df.sort_values('score', ascending=False)611 # print(df[['title', 'score']].head(10))612 # poco sonno => mangia magnesio613 if sleep == 'low':614 # print("sleep: " + sleep)615 # df = df[df.magnesium > 0]616 df['magnesium'] = df.ingredients.apply(isRichMagnesium)617 df.score = df.apply(rescoreMagnesium, axis=1)618 df.score = df.apply(rescoreCoffe, axis=1)619 df.score = df.apply(rescoreSleep, axis=1)620 # sera => ricalcolo il caffe621 if hour == 'evening':622 # print ("hour: " + hour)623 df.score = df.apply(rescoreCoffe, axis=1)624 # depressione => meno grassi625 if depression == 'yes':626 # print ("depression: " + depression)627 # print("fatAvg: " + str(fatAvg))628 # df = df[df.fat < fatAvg]629 df['magnesium'] = df.ingredients.apply(isRichMagnesium)630 df.score = df.apply(rescoreDepression, axis=1)631 df.score = df.apply(rescoreCoffe, axis=1)632 df.score = df.apply(rescoreMagnesium, axis=1)633 df = df.sort_values('score', ascending=False)634 # print(df[['title', 'score']].head(10))635 if user_difficulty != '':636 # print ('user_difficulty: ', user_difficulty)637 df.score = df.apply(rescoreDifficulty, difficulty=user_difficulty, axis=1)638 df = df.sort_values('score', ascending=False)639 # print(df[['title', 'score']].head(10))640 if goal != '':641 # print ('goal: ', goal)642 # se vuole prendere peso e non è sovrappeso643 if (bmiWeight != 'over' and goal == 1):644 # if((not(overweight)) and goal == 1):645 df.score = df.apply(rescoreGoalPlus, axis=1)646 # se vuole perdere peso e non è sottopeso647 if (bmiWeight != 'under' and goal == -1):648 df.score = df.apply(rescoreGoalMinus, axis=1)649 df = df.sort_values('score', ascending=False)650 if user_cost != '':651 # print ('user_cost: ', user_cost)652 df.score = df.apply(rescoreCost, cost=user_cost, axis=1)653 df = df.sort_values('score', ascending=False)654 if user_time != '':655 # print ('user_time: ', user_time)656 df.score = df.apply(rescoreTime, time=user_time, axis=1)657 df = df.sort_values('score', ascending=False)658 # print ('age: ', age)659 if age == 'U20':660 df.score = df.apply(rescoreU20, axis=1)661 elif age == 'U30':662 df.score = df.apply(rescoreU30, axis=1)663 elif age == 'U40':664 df.score = df.apply(rescoreU40, axis=1)665 elif age == 'U60':666 df.score = df.apply(rescoreU60, axis=1)667 elif age == 'O60':668 df.score = df.apply(rescoreO60, axis=1)669 df = df.sort_values('score', ascending=False)670 # print(len(df))671 return df.head(n).sample(frac=1).to_json(orient='split')672api.add_resource(Mood, '/mood/')673if __name__ == '__main__':...
minmax_play.py
Source:minmax_play.py
1#!/usr/bin/env python2# encoding: utf-83# from evaluate import evaluate_line4from table import TABLE,row,col, black, white,space5from copy import deepcopy6import random7import numpy as np8from value_function import NODE9import value_function10from vv import values11vv={'l2a': 90, 'l2c': 60, 'l2b': 75, 'l3b': 7500, 'd': 0, 'l3a': 8600, 'l4': 200000, 'w': 1000000, 'l1': 3, 'd4': 5000, 'd2': 5, 'd3': 100, 'd1': 1}12values[(1, 0, 0, 0, 1, 1, 0, 0, 1)]='l2a'13values[()]='d'14values[(1, 0, 0, 1, 1, 0, 0, 0, 1)]='l2a'15from newmethod import returnrowvalue16import pygame17count = 018fastScore = [0, 1, 10, 100, 1000, 99999]19def evaluate_line(line):20 status = 121 score = {1:[0, 0], -1:[0, 0]}22 for _ in range(2):23 for i in range(0, len(line)-4):24 tlist = line[i:i+5]25 if -status not in line[i:i+5]:26 tsum = list(tlist).count(status)27 score[status][0] += fastScore[tsum]28 if tsum >= 4:29 score[status][1] += 5030 status = -status31 return score32def evaluate(new_table, status):33 vecs = []34 # 1.1 '---' *1535 for i in xrange(0, row):36 vecs.append(new_table[i])37 # 1.2 '|' * 1538 for j in xrange(0, col):39 vecs.append([new_table[i][j] for i in range(0, row)])40 # 1.3 '\' *2141 vecs.append([new_table[x][x] for x in range(0, row)])42 for i in xrange(1, row - 4):43 vec = [new_table[x][x - i] for x in range(i, row)]44 vecs.append(vec)45 vec = [new_table[y - i][y] for y in range(i, col)]46 vecs.append(vec)47 # print [(y-i,y) for y in range(i, col)]48 # 1.4 '/'*2149 # vecs.append([new_tab;e[x][row-x-1] for x in range(0, row)])50 # print [(x, row-x-1) for x in xrange(0, row)]51 for i in xrange(4, row - 1):52 vec = [new_table[x][i - x] for x in xrange(i, -1, -1)]53 vecs.append(vec)54 vec = [new_table[x][col - x + row - i - 2] for x in xrange(row - i - 1, row)]55 vecs.append(vec)56 # print [(x,i-x) for x in xrange(i,-1,-1)]57 # print [(x,col-x+row-i-2) for x in xrange(row-i-1, row)]58 table_score = 059 for vec in vecs:60 score = evaluate_line(vec)61 if status == black:62 table_score += score[white][0] - score[black][0] - score[black][1]63 else:64 table_score += score[black][0] - score[white][0] - score[white][1]65 return table_score * (random.random() * 0.2 + 0.9)66def get_score2(current_table, status):67 '''68 score = 069 table_list = returnrowvalue(node.table.table, node.status)70 for key in table_list:71 score += vv[key] * table_list[key]72 another_list = returnrowvalue(node.table.table, -node.status)73 # for key in another_list:74 # score -= vv[key] * another_list[key]75 return score76 '''77 return - evaluate(current_table, status)78def get_score(current_table, status):79 score = 080 table_list = returnrowvalue(current_table, status)81 for key in table_list:82 score += vv[key] * table_list[key]83 another_list = returnrowvalue(current_table, status)84 for key in another_list:85 score -= vv[key] * another_list[key]86 return score87def generate_node(table, status, deep, temp, next_node, dist=2):88 # print "origin table", table89 if status == white:90 next_status = black91 else:92 next_status = white93 # print "1:", table[6]94 new_table = table + []95 # print "2:", table[6]96 x = next_node[0]97 y = next_node[1]98 new_table[x][y] = status99 # print "3:", table[6]100 new_deep = deep + 1101 new_temp = temp + []102 for k in range(max(x - dist, 0), min(x + dist + 1, 15)):103 for m in range(max(y - dist, 0), min(y + dist + 1, 15)):104 if new_table[k][m] == space and (k, m) not in new_temp:105 new_temp.append((k, m))106 if (x, y) in new_temp:107 new_temp.remove((x, y))108 # print "new_table1", new_table109 return new_table, new_deep, next_status, new_temp110def alphaBeta(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):111 global count112 count += 1113 if deep >= level_num:114 score = get_score2(table, status)115 # print score116 return score117 for next_node in temp:118 Cx = next_node[0]119 Cy = next_node[1]120 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size121 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size122 pygame.draw.circle(game.screen, (255-80*deep, 80*deep, 255-80*deep), [xx, yy], game.chessboard.grid_size // 6)123 pygame.display.update()124 ttable = [x + [] for x in table]125 # print ttable126 new_table, new_deep, new_status, new_temp = generate_node(ttable, status, deep, temp, next_node, dist)127 # print "new_table2", new_table128 new_score = -alphaBeta(new_table, new_status, new_deep, new_temp, level_num, game, dist, -beta, -alpha)129 if new_score > beta:130 return new_score131 if new_score > alpha:132 alpha = new_score133 pos_i = next_node[0]134 pos_j = next_node[1]135 if deep == 0:136 return pos_i, pos_j137 return alpha138def new_alphabeta(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):139 global count140 count += 1141 if deep >= level_num:142 score = get_score2(table, status)143 # print score144 return score145 print "deep0:", deep146 if deep == 0:147 num_remain = len(temp) / 2 + 1148 temp_dict = dict()149 small_score = 1000000150 small_index = -1000000151 print "temp0", temp152 for next_node in temp:153 print "next_node", next_node154 print "deep", deep155 Cx = next_node[0]156 Cy = next_node[1]157 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size158 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size159 pygame.draw.circle(game.screen, (255 - 80 * deep, 80 * deep, 255 - 80 * deep), [xx, yy],160 game.chessboard.grid_size // 6)161 pygame.display.update()162 ttable = [x + [] for x in table]163 # print ttable164 new_table, new_deep, new_status, new_temp = generate_node(ttable, status, deep, temp, next_node, dist)165 print "new temp", new_temp166 print "new deep", new_deep167 # print "new_table2", new_table168 new_score = -new_alphabeta(new_table, new_status, new_deep, new_temp, level_num, game, dist, -beta, -alpha)169 if new_score >= beta:170 return new_score171 if deep == 0:172 if len(temp_dict) < num_remain:173 temp_dict[next_node] = new_score174 if new_score < small_score:175 small_score = new_score176 small_index = next_node177 else:178 if new_score > small_score:179 temp_dict[next_node] = new_score180 temp_dict.pop(small_index)181 small_index, small_score = min(temp_dict.items(), key=lambda x: x[1])182 if new_score >= alpha:183 alpha = new_score184 pos_i = next_node[0]185 pos_j = next_node[1]186 print "bingo"187 if deep == 0:188 return list(temp_dict.keys())189 return alpha190def new_alphabeta_final(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):191 global count192 count += 1193 if deep >= level_num:194 score = get_score2(table, status)195 # print score196 return score197 print "deep0:", deep198 if deep == 0:199 num_remain = len(temp) / 2 + 1200 temp_dict = dict()201 small_score = 1000000202 small_index = -1000000203 print "temp0", temp204 for next_node in temp:205 print "next_node", next_node206 print "deep", deep207 Cx = next_node[0]208 Cy = next_node[1]209 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size210 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size211 pygame.draw.circle(game.screen, (255 - 80 * deep, 80 * deep, 255 - 80 * deep), [xx, yy],212 game.chessboard.grid_size // 6)213 pygame.display.update()214 ttable = [x + [] for x in table]215 # print ttable216 new_table, new_deep, new_status, new_temp = generate_node(ttable, status, deep, temp, next_node, dist)217 print "new temp", new_temp218 print "new deep", new_deep219 # print "new_table2", new_table220 new_score = -new_alphabeta(new_table, new_status, new_deep, new_temp, level_num, game, dist, -beta, -alpha)221 if new_score >= beta:222 return new_score223 if deep == 0:224 if len(temp_dict) < num_remain:225 temp_dict[next_node] = new_score226 if new_score < small_score:227 small_score = new_score228 small_index = next_node229 else:230 if new_score > small_score:231 temp_dict[next_node] = new_score232 temp_dict.pop(small_index)233 small_index, small_score = min(temp_dict.items(), key=lambda x: x[1])234 if new_score >= alpha:235 alpha = new_score236 pos_i = next_node[0]237 pos_j = next_node[1]238 print "bingo"239 if deep == 0:240 return pos_i, pos_j241 return alpha242def alpha_beta_prunning(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):243 '''244 for i in range(1, level_num + 1):245 new_temp = new_alphabeta(table, status, deep, temp, i, game, dist, alpha=-1000000, beta=1000000)246 print "over", i247 temp = new_temp248 print temp249 '''250 new_temp = new_alphabeta(table, status, deep, temp, 2, game, dist, alpha=-1000000, beta=1000000)251 temp = new_temp252 print temp253 pos_i, pos_j = new_alphabeta_final(table, status, deep, temp, level_num, game, dist, alpha=-1000000, beta=1000000)254 return pos_i, pos_j255def new_negaScout(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):256 global count257 count += 1258 if deep >= level_num:259 score = get_score2(table, status)260 # print score261 return score262 # print "deep0:", deep263 if deep == 0:264 num_remain = len(temp) / 2 + 1265 temp_dict = dict()266 small_score = 1000000267 small_index = -1000000268 first_next_node = temp[0]269 Cx = first_next_node[0]270 Cy = first_next_node[1]271 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size272 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size273 pygame.draw.circle(game.screen, (100, 100, 100), [xx, yy],274 game.chessboard.grid_size // 6)275 pygame.display.update()276 ttable = [x + [] for x in table]277 first_table, first_deep, first_status, first_temp = generate_node(ttable, status, deep, temp, first_next_node, dist)278 first_value = -negaScout(first_table, first_status, first_deep, first_temp, level_num, game, dist, -beta, -alpha)279 if first_value >= beta:280 return first_value281 if deep == 0:282 temp_dict[first_next_node] = first_value283 if first_value > alpha:284 alpha = first_value285 pos_i = first_next_node[0]286 pos_j = first_next_node[1]287 for i in range(0, len(temp)):288 next_node = temp[i]289 Cx = next_node[0]290 Cy = next_node[1]291 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size292 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size293 pygame.draw.circle(game.screen, (255-80*deep, 80*deep, 255-80*deep), [xx, yy], game.chessboard.grid_size // 6)294 pygame.display.update()295 ttable = [x + [] for x in table]296 # print ttable297 new_table, new_deep, new_status, new_temp = generate_node(ttable, status, deep, temp, next_node, dist)298 # print "new_table2", new_table299 new_score = -negaScout(new_table, new_status, new_deep, new_temp, level_num, game, dist, -alpha - 1, -alpha)300 if new_score > alpha and new_score < beta:301 new_score = -negaScout(new_table, new_status, new_deep, new_temp, level_num, game, dist, -beta, -alpha - 1)302 if new_score >= beta:303 return new_score304 if deep == 0:305 if len(temp_dict) < num_remain:306 temp_dict[next_node] = new_score307 if new_score < small_score:308 small_score = new_score309 small_index = next_node310 else:311 if new_score > small_score:312 temp_dict[next_node] = new_score313 temp_dict.pop(small_index)314 small_index, small_score = min(temp_dict.items(), key=lambda x: x[1])315 if new_score > alpha:316 alpha = new_score317 pos_i = next_node[0]318 pos_j = next_node[1]319 if deep == 0:320 return list(temp_dict.keys())321 return alpha322def negaScout(table, status, deep, temp, level_num, game, dist=2, alpha=-1000000, beta=1000000):323 global count324 count += 1325 if deep >= level_num:326 score = get_score2(table, status)327 # print score328 return score329 first_next_node = temp[0]330 Cx = first_next_node[0]331 Cy = first_next_node[1]332 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size333 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size334 pygame.draw.circle(game.screen, (100, 100, 100), [xx, yy],335 game.chessboard.grid_size // 6)336 pygame.display.update()337 ttable = [x + [] for x in table]338 first_table, first_deep, first_status, first_temp = generate_node(ttable, status, deep, temp, first_next_node, dist)339 first_value = -negaScout(first_table, first_status, first_deep, first_temp, level_num, game, dist, -beta, -alpha)340 if first_value >= beta:341 return first_value342 if first_value > alpha:343 alpha = first_value344 pos_i = first_next_node[0]345 pos_j = first_next_node[1]346 for i in range(0, len(temp)):347 next_node = temp[i]348 Cx = next_node[0]349 Cy = next_node[1]350 xx = game.chessboard.start_x + Cy * game.chessboard.grid_size351 yy = game.chessboard.start_y + Cx * game.chessboard.grid_size352 pygame.draw.circle(game.screen, (255-80*deep, 80*deep, 255-80*deep), [xx, yy], game.chessboard.grid_size // 6)353 pygame.display.update()354 ttable = [x + [] for x in table]355 # print ttable356 new_table, new_deep, new_status, new_temp = generate_node(ttable, status, deep, temp, next_node, dist)357 # print "new_table2", new_table358 new_score = -negaScout(new_table, new_status, new_deep, new_temp, level_num, game, dist, -alpha - 1, -alpha)359 if new_score > alpha and new_score < beta:360 new_score = -negaScout(new_table, new_status, new_deep, new_temp, level_num, game, dist, -beta, -alpha - 1)361 if new_score >= beta:362 return new_score363 if new_score > alpha:364 alpha = new_score365 pos_i = next_node[0]366 pos_j = next_node[1]367 if deep == 0:368 return pos_i, pos_j369 return alpha370def negaScout_prunning(table, status, deep, temp, level_num, game, dist=2):371 new_temp = new_negaScout(table, status, deep, temp, 1, game, dist, alpha=-1000000, beta=1000000)372 temp = new_temp373 # print temp374 pos_i, pos_j = negaScout(table, status, deep, temp, level_num, game, dist, alpha=-1000000, beta=1000000)375 return pos_i, pos_j376def alpha_beta(node, level_num, game, dist=2):377 # print "hahha"378 # print node.table.table379 pos_i, pos_j = negaScout_prunning(node.table.table, node.status, node.deep, node.table.temp, level_num, game, dist)380 # pos_i, pos_j = negaScout(node.table.table, node.status, node.deep, node.table.temp, level_num, game, dist)381 node.pos_i = pos_i382 node.pos_j = pos_j383 # print count...
test_league_rater.py
Source:test_league_rater.py
1import pytest2from service import config3from service.league_service.league_rater import LeagueRater4from service.league_service.typedefs import GameOutcome, LeagueScore5@pytest.fixture6def unplaced_player_score(example_league):7 return LeagueScore(8 division_id=None,9 score=None,10 game_count=example_league.placement_games - 1,11 returning_player=False12 )13def test_new_score_victory_no_boost(example_league):14 current_score = LeagueScore(15 division_id=2, score=5, game_count=30, returning_player=False16 )17 player_rating = (180.0, 0.0)18 new_score = LeagueRater.rate(19 example_league, current_score, GameOutcome.VICTORY, player_rating20 )21 assert new_score.division_id == current_score.division_id22 assert new_score.game_count == current_score.game_count + 123 assert new_score.score == current_score.score + config.SCORE_GAIN24 player_rating = (10.0, 0.0)25 new_score = LeagueRater.rate(26 example_league, current_score, GameOutcome.VICTORY, player_rating27 )28 assert new_score.division_id == current_score.division_id29 assert new_score.game_count == current_score.game_count + 130 assert new_score.score == current_score.score + config.SCORE_GAIN31def test_new_score_victory_boost(example_league):32 current_score = LeagueScore(33 division_id=2, score=5, game_count=30, returning_player=False34 )35 player_rating = (1800.0, 0.0)36 new_score = LeagueRater.rate(37 example_league, current_score, GameOutcome.VICTORY, player_rating38 )39 assert new_score.division_id == current_score.division_id40 assert new_score.game_count == current_score.game_count + 141 assert (42 new_score.score43 == current_score.score + config.SCORE_GAIN + config.POSITIVE_BOOST44 )45def test_new_score_defeat_no_boost(example_league):46 current_score = LeagueScore(47 division_id=2, score=5, game_count=30, returning_player=False48 )49 player_rating = (180.0, 0.0)50 new_score = LeagueRater.rate(51 example_league, current_score, GameOutcome.DEFEAT, player_rating52 )53 assert new_score.division_id == current_score.division_id54 assert new_score.game_count == current_score.game_count + 155 assert new_score.score == current_score.score - config.SCORE_GAIN56 player_rating = (1800.0, 0.0)57 new_score = LeagueRater.rate(58 example_league, current_score, GameOutcome.DEFEAT, player_rating59 )60 assert new_score.division_id == current_score.division_id61 assert new_score.game_count == current_score.game_count + 162 assert new_score.score == current_score.score - config.SCORE_GAIN63def test_new_score_defeat_boost(example_league):64 current_score = LeagueScore(65 division_id=2, score=5, game_count=30, returning_player=False66 )67 player_rating = (60.0, 0.0)68 new_score = LeagueRater.rate(69 example_league, current_score, GameOutcome.DEFEAT, player_rating70 )71 assert new_score.division_id == current_score.division_id72 assert new_score.game_count == current_score.game_count + 173 assert (74 new_score.score75 == current_score.score - config.SCORE_GAIN - config.NEGATIVE_BOOST76 )77def test_new_score_victory_highest_division_no_boost(example_league):78 current_score = LeagueScore(79 division_id=3, score=5, game_count=30, returning_player=False80 )81 player_rating = (240.0, 0.0)82 new_score = LeagueRater.rate(83 example_league, current_score, GameOutcome.VICTORY, player_rating84 )85 assert new_score.division_id == current_score.division_id86 assert new_score.game_count == current_score.game_count + 187 assert new_score.score == current_score.score + config.SCORE_GAIN88def test_new_score_victory_highest_division_boost(example_league):89 current_score = LeagueScore(90 division_id=3, score=5, game_count=30, returning_player=False91 )92 player_rating = (380.0, 0.0)93 new_score = LeagueRater.rate(94 example_league, current_score, GameOutcome.VICTORY, player_rating95 )96 assert new_score.division_id == current_score.division_id97 assert new_score.game_count == current_score.game_count + 198 assert (99 new_score.score100 == current_score.score + config.SCORE_GAIN + config.HIGHEST_DIVISION_BOOST101 )102def test_placement_after_enough_games(example_league, unplaced_player_score):103 # Neutralize the offset in the placement function so we can test the score independently of the config settings104 rating = (150.0 - config.RATING_MODIFIER_FOR_PLACEMENT, 0.0)105 new_score = LeagueRater.rate(106 example_league, unplaced_player_score, GameOutcome.DRAW, rating107 )108 assert new_score.division_id == example_league.divisions[1].id109 assert new_score.game_count == unplaced_player_score.game_count + 1110 assert new_score.score == 5111def test_placement_returning_player(example_league):112 current_score = LeagueScore(113 division_id=None,114 score=None,115 game_count=example_league.placement_games_returning_player - 1,116 returning_player=True117 )118 rating = (150.0 - config.RATING_MODIFIER_FOR_PLACEMENT, 0.0)119 new_score = LeagueRater.rate(120 example_league, current_score, GameOutcome.DRAW, rating121 )122 assert new_score.division_id == example_league.divisions[1].id123 assert new_score.game_count == current_score.game_count + 1124 assert new_score.score == 5125def test_replacement_at_invalid_player_division(example_league):126 current_score = LeagueScore(127 division_id=999,128 score=4,129 game_count=example_league.placement_games,130 returning_player=False131 )132 rating = (150.0 - config.RATING_MODIFIER_FOR_PLACEMENT, 0.0)133 new_score = LeagueRater.rate(134 example_league, current_score, GameOutcome.DRAW, rating135 )136 assert new_score.division_id == example_league.divisions[1].id137 assert new_score.game_count == current_score.game_count + 1138 assert new_score.score == 5139def test_replacement_at_null_division(example_league):140 current_score = LeagueScore(141 division_id=None,142 score=4,143 game_count=example_league.placement_games,144 returning_player=False145 )146 rating = (150.0 - config.RATING_MODIFIER_FOR_PLACEMENT, 0.0)147 new_score = LeagueRater.rate(148 example_league, current_score, GameOutcome.DRAW, rating149 )150 assert new_score.division_id == example_league.divisions[1].id151 assert new_score.game_count == current_score.game_count + 1152 assert new_score.score == 5153def test_replacement_at_null_score(example_league):154 expected_division_id = example_league.divisions[1].id155 current_score = LeagueScore(156 division_id=expected_division_id,157 score=None,158 game_count=example_league.placement_games,159 returning_player=False160 )161 rating = (150.0 - config.RATING_MODIFIER_FOR_PLACEMENT, 0.0)162 new_score = LeagueRater.rate(163 example_league, current_score, GameOutcome.DRAW, rating164 )165 assert new_score.division_id == expected_division_id166 assert new_score.game_count == current_score.game_count + 1167 assert new_score.score == 5168def test_placement(example_league, unplaced_player_score):169 # Neutralize the offset in the placement function so we can test the score independently of the config settings170 rating = 150 - config.RATING_MODIFIER_FOR_PLACEMENT171 new_score = LeagueRater._do_placement(example_league, unplaced_player_score, rating)172 assert new_score.division_id == example_league.divisions[1].id173 assert new_score.game_count == unplaced_player_score.game_count + 1174 assert new_score.score == 5175def test_placement_high_rating(example_league, unplaced_player_score):176 rating = 1500 - config.RATING_MODIFIER_FOR_PLACEMENT177 new_score = LeagueRater._do_placement(example_league, unplaced_player_score, rating)178 assert new_score.division_id == example_league.divisions[-1].id179 assert new_score.game_count == unplaced_player_score.game_count + 1180 assert new_score.score == 10181def test_placement_low_rating(example_league, unplaced_player_score):182 rating = -500 - config.RATING_MODIFIER_FOR_PLACEMENT183 new_score = LeagueRater._do_placement(example_league, unplaced_player_score, rating)184 assert new_score.division_id == example_league.divisions[0].id185 assert new_score.game_count == unplaced_player_score.game_count + 1186 assert new_score.score == 0187def test_new_player(example_league):188 current_score = LeagueScore(189 division_id=None, score=None, game_count=0, returning_player=False190 )191 player_rating = (380.0, 0.0)192 new_score = LeagueRater.rate(193 example_league, current_score, GameOutcome.VICTORY, player_rating194 )195 assert new_score.division_id is None196 assert new_score.game_count == 1197 assert new_score.score is None198def test_placement_games(example_league):199 current_score = LeagueScore(200 division_id=None, score=None, game_count=5, returning_player=False201 )202 player_rating = (380.0, 0.0)203 new_score = LeagueRater.rate(204 example_league, current_score, GameOutcome.VICTORY, player_rating205 )206 assert new_score.division_id is None207 assert new_score.game_count == current_score.game_count + 1208 assert new_score.score is None209def test_promote(example_league):210 current_score = LeagueScore(211 division_id=2, score=10, game_count=30, returning_player=False212 )213 player_rating = (380.0, 0.0)214 new_score = LeagueRater.rate(215 example_league, current_score, GameOutcome.VICTORY, player_rating216 )217 assert new_score.division_id == 3218 assert new_score.game_count == current_score.game_count + 1219 assert new_score.score == config.POINT_BUFFER_AFTER_DIVISION_CHANGE220def test_demote(example_league):221 current_score = LeagueScore(222 division_id=2, score=0, game_count=30, returning_player=False223 )224 player_rating = (380.0, 0.0)225 new_score = LeagueRater.rate(226 example_league, current_score, GameOutcome.DEFEAT, player_rating227 )228 assert new_score.division_id == 1229 assert new_score.game_count == current_score.game_count + 1230 assert new_score.score == 10 - config.POINT_BUFFER_AFTER_DIVISION_CHANGE231def test_promote_in_highest_division(example_league):232 current_score = LeagueScore(233 division_id=3, score=10, game_count=30, returning_player=False234 )235 player_rating = (380.0, 0.0)236 new_score = LeagueRater.rate(237 example_league, current_score, GameOutcome.VICTORY, player_rating238 )239 assert new_score.division_id == current_score.division_id240 assert new_score.game_count == current_score.game_count + 1241 assert new_score.score == 10242def test_demote_in_lowest_division(example_league):243 current_score = LeagueScore(244 division_id=1, score=0, game_count=30, returning_player=False245 )246 player_rating = (380.0, 0.0)247 new_score = LeagueRater.rate(248 example_league, current_score, GameOutcome.DEFEAT, player_rating249 )250 assert new_score.division_id == current_score.division_id251 assert new_score.game_count == current_score.game_count + 1252 assert new_score.score == 0253def test_score_too_high(example_league):254 current_score = LeagueScore(255 division_id=2, score=14, game_count=30, returning_player=False256 )257 player_rating = (380.0, 0.0)258 new_score = LeagueRater.rate(259 example_league, current_score, GameOutcome.VICTORY, player_rating260 )261 assert new_score.division_id == 3262 assert new_score.game_count == current_score.game_count + 1263 assert new_score.score == config.POINT_BUFFER_AFTER_DIVISION_CHANGE264def test_score_too_low(example_league):265 current_score = LeagueScore(266 division_id=2, score=-14, game_count=30, returning_player=False267 )268 player_rating = (380.0, 0.0)269 new_score = LeagueRater.rate(270 example_league, current_score, GameOutcome.VICTORY, player_rating271 )272 assert new_score.division_id == 1273 assert new_score.game_count == current_score.game_count + 1274 assert new_score.score == 10 - config.POINT_BUFFER_AFTER_DIVISION_CHANGE275def test_other_game_outcomes(example_league):276 current_score = LeagueScore(277 division_id=2, score=4, game_count=30, returning_player=False278 )279 player_rating = (180.0, 0.0)280 new_score = LeagueRater.rate(281 example_league, current_score, GameOutcome.DRAW, player_rating282 )283 assert new_score.division_id == current_score.division_id284 assert new_score.game_count == current_score.game_count + 1285 assert new_score.score == current_score.score286 new_score = LeagueRater.rate(287 example_league, current_score, GameOutcome.MUTUAL_DRAW, player_rating288 )289 assert new_score.division_id == current_score.division_id290 assert new_score.game_count == current_score.game_count + 1291 assert new_score.score == current_score.score292 new_score = LeagueRater.rate(293 example_league, current_score, GameOutcome.UNKNOWN, player_rating294 )295 assert new_score.division_id == current_score.division_id296 assert new_score.game_count == current_score.game_count + 1297 assert new_score.score == current_score.score298 new_score = LeagueRater.rate(299 example_league, current_score, GameOutcome.CONFLICTING, player_rating300 )301 assert new_score.division_id == current_score.division_id302 assert new_score.game_count == current_score.game_count + 1...
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