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How to use representatives method in hypothesis
Best Python code snippet using hypothesis
legislator_spider.py
Source:legislator_spider.py 
1import scrapy2import logging, sys3from cand.items import CandItem4# This script contains spiders to crawl different page from ballotpedia.org5# Spider1: parse out state links6# Spider2: parse the majority of candidate (except: FL, NH for Senate)7# Spider3: parse only general election candidates (inconsistent table number)8# Spider4: (Senate Only) parse FL, NH as they have different html layout9# Note: NY senators have multiple party10# https://ballotpedia.org/United_States_Senate_election_in_New_York,_201611# This spider needs more work to actually output the JSON file - only prints to console now12class SenateSpider1(scrapy.Spider):13 name = "senate-StateURLs"14 # use the output for the start_urls for other Senate spiders15 allowed_domains = ["ballotpedia.org"]16 start_urls = ["https://ballotpedia.org/United_States_Congress_elections,_2016"]17 def parse(self, response):18 # grep 50 state's info19 for i, href in enumerate(response.xpath('//table[@class="infobox"]/descendant::node()/a[contains(@href, "United_States_Senate_election_in")]/@href').extract()):20 url = response.urljoin(href)21 print i+1, url 22class SenateSpider2(scrapy.Spider):23 name = "senate-AllCandidatesInfo"24 allowed_domains = ["ballotpedia.org"]25 #start_urls = ["https://ballotpedia.org/United_States_Senate_election_in_California,_2016"]26 start_urls = ["https://ballotpedia.org/United_States_Senate_election_in_Alabama,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Alaska,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Arizona,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Arkansas,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_California,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Colorado,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Connecticut,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Georgia,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Hawaii,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Idaho,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Illinois,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Indiana,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Iowa,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Kansas,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Kentucky,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Louisiana,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Maryland,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Missouri,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Nevada,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_New_York,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_North_Carolina,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_North_Dakota,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Ohio,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Oklahoma,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Oregon,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Pennsylvania,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_South_Carolina,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_South_Dakota,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Utah,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Vermont,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Washington,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Wisconsin,_2016"]27 def parse(self, response):28 i=129 for href in response.xpath('//a[contains(@href, "Independent") or contains(@href, "Libertarian") or contains(@href, "Republican_Party") or contains(@href, "Democratic_Party") or contains(@href, "Green_Party") or contains(@href, "Peace_and_Freedom_Party") or contains(@href, "Equality_Party") or contains(@href, "Working_Families_Party") or contains(@href, "Independence_Party_of_America") or contains(@href, "Conservative_Party") or contains(@href, "Reform_Party") or contains(@href, "Constitution_Party")]'):30 party = href.xpath('./@title').extract()[0]31 logging.info('Party: %s', party)32 ccurl = href.xpath('following-sibling::a/@href').extract()33 if len(ccurl) >= 1:34 logging.debug('candidates url found: %s', ccurl)35 curl = ccurl[0]36 else:37 logging.debug('no candidate found')38 continue39 logging.info("Processing person #%d", i)40 i+=141 name = curl.replace("_", " ")[1:] 42 cand_urls = response.urljoin(curl)43 logging.info('Candidate url: %s', cand_urls)44 item = CandItem()45 item['name'] = name46 item['url'] = cand_urls47 item['party'] = party #TODO: remove party as parse_cand now handle it48 item['chamber'] = 'S'49 yield scrapy.Request(cand_urls, callback=self.parse_cand, meta={'item':item}) 50 def parse_cand(self, response):51 item = response.meta['item']52 logging.debug('grab picure...')53 for p in response.xpath('//table[@class="infobox"]/descendant::node()/@src'):54 item['pic'] = response.urljoin(p.extract())55 logging.info('pic: %s', p.extract())56 break 57 # District number 0 for senators to match Sunlight candidate data58 if item['chamber'] == 'S':59 logging.debug('setting senate district 0')60 item['dist'] = '0'61 else:62 logging.info('grab house district...')63 # if there this person is running for64 pro = response.xpath('//*[@id="mw-content-text"]/table/tr[5]/td/text()').extract()65 if pro[0].split(',')[0] == 'Running for U.S. House':66 d = pro[0].split(',')[2]67 else:68 ln = response.xpath('//*[@id="mw-content-text"]/table/tr[4]/td/text()').extract()69 d = ln[0].split(',')[2]70 item['dist'] = d71 logging.info('dist: %s', d)72 logging.debug('grab party...')73 for l in response.xpath('//table[@class="infobox"]//a[contains(@href, "Independent") or contains(@href, "Libertarian") or contains(@href, "Republican") or contains(@href, "Democratic") or contains(@href, "Green") or contains(@href, "Peace_and_Freedom") or contains(@href, "Equality") or contains(@href, "Working_Families") or contains(@href, "Independence_of_America") or contains(@href, "Conservative") or contains(@href, "Reform") or contains(@href, "Constitution")]'):74 party = l.xpath('./@href').extract()[0]75 item['party'] = party[1:]76 logging.info('party: %s', party)77 break78 logging.debug('grab incumbent...')79 item['incumbent'] = 080 for l in response.xpath('//table[@class="infobox"]//td[contains(text(), "Incumbent")]'):81 item['incumbent'] = 182 logging.info('is Incumbent!')83 # inconsistent format too84 #for l in response.xpath('//*[@id="mw-content-text"]/table/tr[4]/td/text()').extract():85 # h = l.split(',')[1][1:]86 # item['state'] = h87 logging.debug('grab campaign website...')88 for l in response.xpath('//a[@class="external text" and contains(text() ,"Campaign")]/@href'):89 logging.info('camp: %s', l.extract())90 item['camp'] = l.extract()91 break92 logging.debug('grab twitter...')93 for l in response.xpath('//a[@class="external text" and text()="Twitter"]/@href'):94 logging.info('Twitter Feed: %s', l.extract())95 item['twtr'] = l.extract()96 break97 logging.debug('grab facebook...')98 for l in response.xpath('//a[@class="external text" and text()="Facebook"]/@href'):99 logging.info('Facebook Page: %s', l.extract())100 item['fb'] = l.extract()101 break102 logging.debug('grab youtube...')103 for y in response.xpath('//a[@class="external text" and text()="Youtube"]/@href'):104 logging.info('Youtube: %s', y.extract())105 item['youtube'] = y.extract()106 break107 yield item108class SenateSpider3(scrapy.Spider):109 name = "senate-GeneralElectionCandidatesInfo"110 allowed_domains = ["ballotpedia.org"]111 #start_urls = ["https://ballotpedia.org/United_States_Senate_election_in_Florida,_2016"]112 start_urls = ["https://ballotpedia.org/United_States_Senate_election_in_Florida,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Alabama,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Alaska,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Arizona,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Arkansas,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_California,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Colorado,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Connecticut,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Georgia,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Hawaii,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Idaho,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Illinois,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Indiana,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Iowa,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Kansas,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Kentucky,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Louisiana,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Maryland,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Missouri,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Nevada,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_New_York,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_North_Carolina,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_North_Dakota,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Ohio,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Oklahoma,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Oregon,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Pennsylvania,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_South_Carolina,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_South_Dakota,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Utah,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Vermont,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Washington,_2016" ,"https://ballotpedia.org/United_States_Senate_election_in_Wisconsin,_2016"]113 def __init__(self):114 self.S2 = SenateSpider2()115 def parse(self, response):116 i=1117 logging.info('url: %s', response.url)118 state = response.url.split('in_')[1].split(',')[0].replace('_', ' ')119 logging.info('state: %s', state)120 for h in response.xpath("//table[contains(tr/td[2]/p[1]/b/big, 'General election candidates')]//a[not(contains(@href, 'Party') or contains(@href, '#cite_note') or contains(@href, 'Independent'))]/@href").extract():121 url = response.urljoin(h)122 logging.info('candidate url: %s', url)123 name = h.replace("_", " ")[1:] 124 item = CandItem()125 item['name'] = name126 item['url'] = url127 item['chamber'] = 'S'128 item['state'] = state129 item['gen_election_candidate'] = 1 130 yield scrapy.Request(url, callback=self.S2.parse_cand, meta={'item':item}) 131# sameple urls132#start_urls=["https://ballotpedia.org/Patty_Murray" ,"https://ballotpedia.org/Chris_Vance" ,"https://ballotpedia.org/Phil_Cornell" ,"https://ballotpedia.org/Mohammad_Said" ,"https://ballotpedia.org/Thor_Amundson" ,"https://ballotpedia.org/Uncle_Mover" ,"https://ballotpedia.org/Eric_John_Makus" ,"https://ballotpedia.org/Scott_Nazarino" ,"https://ballotpedia.org/Mike_Luke" ,"https://ballotpedia.org/Sam_Wright_(Washington)" ,"https://ballotpedia.org/Zach_Haller" ,"https://ballotpedia.org/Donna_Rae_Lands" ,"https://ballotpedia.org/Alex_Tsimerman" ,"https://ballotpedia.org/Pano_Churchill" ,"https://ballotpedia.org/Ted_Cummings" ,"https://ballotpedia.org/Chuck_Jackson" ,"https://ballotpedia.org/Jeremy_Teuton"] 133# spider3 applies to FL & NH for Senate134# Different layout for FL, and NH. Had to hardcode the xpath here135class SenateSpider4(scrapy.Spider):136 name = "senate-Special_FL_NH"137 allowed_domains = ["ballotpedia.org"]138 start_urls = ["https://ballotpedia.org/United_States_Senate_election_in_New_Hampshire,_2016"]139 def __init__(self):140 self.S2 = SenateSpider2()141 def parse(self, response):142 logging.debug('grab Democratic_Party candidates...') 143 for h in response.xpath('//div[@id="bodyContent"]/table[3]/tr/td[1]/a/@href').extract():144 url = response.urljoin(h)145 logging.info('candidate url: %s', url)146 147 name = h.replace("_", " ")[1:] 148 item = CandItem()149 item['name'] = name150 item['url'] = url151 item['chamber'] = 'S'152 yield scrapy.Request(url, callback=self.S2.parse_cand, meta={'item':item}) 153 logging.debug('grab Republican_Party candidates...')154 for h in response.xpath('//*[@id="bodyContent"]/table[3]/tr/td[3]/a/@href').extract():155 url = response.urljoin(h)156 logging.info('candidate url: %s', url)157 name = h.replace("_", " ")[1:] 158 item = CandItem()159 item['name'] = name160 item['url'] = url161 item['chamber'] = 'S'162 yield scrapy.Request(url, callback=self.S2.parse_cand, meta={'item':item}) 163class HouseSpider1(scrapy.Spider):164 name = "house-StateURLs"165 allowed_domains = ["ballotpedia.org"]166 start_urls = ["https://ballotpedia.org/United_States_Congress_elections,_2016"]167 def parse(self, response):168 for i, href in enumerate(response.xpath('//table[@class="infobox"]/descendant::node()/a[contains(@href, "United_States_House_of_Representatives_elections_in")]/@href').extract()):169 url = response.urljoin(href)170 print i+1, url 171class HouseSpider3(scrapy.Spider):172 name = "house-GeneralElectionCandidatesInfo"173 allowed_domains = ["ballotpedia.org"]174 #start_urls = ["https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Washington,_2016"]175 start_urls = ["https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Alabama,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Alaska,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Arizona,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Arkansas,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_California,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Colorado,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Connecticut,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Delaware,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Florida,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Georgia,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Hawaii,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Idaho,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Illinois,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Indiana,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Iowa,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Kansas,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Kentucky,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Louisiana,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Maine,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Maryland,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Massachusetts,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Michigan,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Minnesota,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Mississippi,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Missouri,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Montana,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Nebraska,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Nevada,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_New_Hampshire,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_New_Jersey,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_New_Mexico,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_New_York,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_North_Carolina,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_North_Dakota,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Ohio,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Oklahoma,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Oregon,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Pennsylvania,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Rhode_Island,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_South_Carolina,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_South_Dakota,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Tennessee,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Texas,_2014", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Utah,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Vermont,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Virginia,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Washington,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_West_Virginia,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Wisconsin,_2016", "https://ballotpedia.org/United_States_House_of_Representatives_elections_in_Wyoming,_2016"]176 def __init__(self):177 self.S2 = SenateSpider2()178 def parse(self, response):179 i=1180 logging.info('url: %s', response.url)181 state = response.url.split('in_')[1].split(',')[0].replace('_', ' ')182 logging.info('state: %s', state)183 for h in response.xpath("//table[contains(tr/td[2]/p[1]/b/big, 'General election candidates')]//a[not(contains(@href, 'Party') or contains(@href, '#cite_note') or contains(@href, 'Independent'))]/@href").extract():184 url = response.urljoin(h)185 logging.info('candidate url: %s', url)186 name = h.replace("_", " ")[1:] 187 item = CandItem()188 item['name'] = name189 item['url'] = url190 item['chamber'] = 'H'191 item['state'] = state192 item['gen_election_candidate'] = 1 ...
coop_evol.py
Source:coop_evol.py
1# This file is part of DEAP.2#3# DEAP is free software: you can redistribute it and/or modify4# it under the terms of the GNU Lesser General Public License as5# published by the Free Software Foundation, either version 3 of6# the License, or (at your option) any later version.7#8# DEAP is distributed in the hope that it will be useful,9# but WITHOUT ANY WARRANTY; without even the implied warranty of10# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the11# GNU Lesser General Public License for more details.12#13# You should have received a copy of the GNU Lesser General Public14# License along with DEAP. If not, see <http://www.gnu.org/licenses/>.15"""This example contains the evolving test from *Potter, M. and De Jong, K.,162001, Cooperative Coevolution: An Architecture for Evolving Co-adapted17Subcomponents.* section 4.2.4. The number of species is evolved by adding and18removing species as stagnation occurs.19"""20import random21try:22 import matplotlib.pyplot as plt23 plt.figure()24except:25 plt = False26import numpy27from deap import algorithms28from deap import tools29import coop_base30IND_SIZE = coop_base.IND_SIZE31SPECIES_SIZE = coop_base.SPECIES_SIZE32NUM_SPECIES = 133TARGET_SIZE = 3034IMPROVMENT_TRESHOLD = 0.535IMPROVMENT_LENGTH = 536EXTINCTION_TRESHOLD = 5.037noise = "*##*###*###*****##*##****#*##*###*#****##******##*#**#*#**######"38schematas = ("1##1###1###11111##1##1111#1##1###1#1111##111111##1#11#1#11######",39 "1##1###1###11111##1##1000#0##0###0#0000##000000##0#00#0#00######",40 "0##0###0###00000##0##0000#0##0###0#0000##001111##1#11#1#11######")41toolbox = coop_base.toolbox42toolbox.register("evaluateContribution", coop_base.matchSetContribution)43def main(extended=True, verbose=True):44 target_set = []45 species = []46 47 stats = tools.Statistics(lambda ind: ind.fitness.values)48 stats.register("avg", numpy.mean)49 stats.register("std", numpy.std)50 stats.register("min", numpy.min)51 stats.register("max", numpy.max)52 53 logbook = tools.Logbook()54 logbook.header = "gen", "species", "evals", "std", "min", "avg", "max"55 56 ngen = 30057 g = 058 59 for i in range(len(schematas)):60 size = int(TARGET_SIZE/len(schematas))61 target_set.extend(toolbox.target_set(schematas[i], size))62 63 species = [toolbox.species() for _ in range(NUM_SPECIES)]64 species_index = list(range(NUM_SPECIES))65 last_index_added = species_index[-1]66 67 # Init with random a representative for each species68 representatives = [random.choice(species[i]) for i in range(NUM_SPECIES)]69 best_fitness_history = [None] * IMPROVMENT_LENGTH70 71 if plt and extended:72 contribs = [[]]73 stag_gen = []74 collab = []75 76 while g < ngen:77 # Initialize a container for the next generation representatives78 next_repr = [None] * len(species)79 for (i, s), j in zip(enumerate(species), species_index):80 # Vary the species individuals81 s = algorithms.varAnd(s, toolbox, 0.6, 1.0)82 83 # Get the representatives excluding the current species84 r = representatives[:i] + representatives[i+1:]85 for ind in s:86 # Evaluate and set the individual fitness87 ind.fitness.values = toolbox.evaluate([ind] + r, target_set)88 89 record = stats.compile(s)90 logbook.record(gen=g, species=j, evals=len(s), **record)91 92 if verbose: 93 print(logbook.stream)94 95 # Select the individuals96 species[i] = toolbox.select(s, len(s)) # Tournament selection97 next_repr[i] = toolbox.get_best(s)[0] # Best selection98 99 if plt and extended:100 # Book keeping of the collaborative fitness101 collab.append(next_repr[i].fitness.values[0])102 103 g += 1104 105 representatives = next_repr106 107 # Keep representatives fitness for stagnation detection108 best_fitness_history.pop(0)109 best_fitness_history.append(representatives[0].fitness.values[0])110 111 try:112 diff = best_fitness_history[-1] - best_fitness_history[0]113 except TypeError:114 diff = float("inf")115 116 if plt and extended:117 for (i, rep), j in zip(enumerate(representatives), species_index):118 contribs[j].append((toolbox.evaluateContribution(representatives,119 target_set, i)[0], g-1))120 121 if diff < IMPROVMENT_TRESHOLD:122 if len(species) > 1:123 contributions = []124 for i in range(len(species)):125 contributions.append(toolbox.evaluateContribution(representatives, target_set, i)[0])126 127 for i in reversed(range(len(species))):128 if contributions[i] < EXTINCTION_TRESHOLD:129 species.pop(i)130 species_index.pop(i)131 representatives.pop(i)132 133 last_index_added += 1134 best_fitness_history = [None] * IMPROVMENT_LENGTH135 species.append(toolbox.species())136 species_index.append(last_index_added)137 representatives.append(random.choice(species[-1]))138 if extended and plt:139 stag_gen.append(g-1)140 contribs.append([])141 if extended:142 for r in representatives:143 # print final representatives without noise144 print("".join(str(x) for x, y in zip(r, noise) if y == "*"))145 146 if extended and plt: # Ploting of the evolution147 line1, = plt.plot(collab, "--", color="k")148 149 for con in contribs:150 try:151 con, g = zip(*con)152 line2, = plt.plot(g, con, "-", color="k")153 except ValueError:154 pass155 156 axis = plt.axis("tight")157 158 for s in stag_gen:159 plt.plot([s, s], [0, axis[-1]], "--", color="k")160 161 plt.legend((line1, line2), ("Collaboration", "Contribution"), loc="center right")162 plt.xlabel("Generations")163 plt.ylabel("Fitness")164 plt.show()165 166if __name__ == "__main__":...
solver15.py
Source:solver15.py
...24 words = [re.sub("[^а-ÑÑ]+", "0", word.strip(punctuation)) for word in text.split() if ")" in word25 and any([n in word for n in placeholders])]26 n_number = text.split(".")[0].split()[-1].lower()27 return text, words, n_number28 def get_representatives(self, word, representatives, threshold=70):29 representatives = [rep for rep in representatives if fuzz.ratio(word, rep) >= threshold]30 return representatives31 def get_similarity(self, x, representatives):32 y = [self.representatives["n"][rep] if rep in self.representatives["n"]33 else self.representatives["nn"][rep] for rep in representatives]34 similarity = max([cosine_similarity(x, y_.reshape(1, -1))[0][0] for y_ in y])35 return similarity36 37 def parse_representatives(self, task):38 text, words, n_number = self.process_task(task)39 solution = self.get_target(task)40 if len(n_number) == 1:41 n_words = [re.sub("[^а-ÑÑ]+", "н", word.strip(punctuation)) for word in text.split()42 if any([d in word for d in solution]) and ")" in word]43 for word in n_words:44 if word not in self.representatives["n"]:45 self.representatives["n"][word] = self.token_embedding([word])46 for word in words:47 n_replacement = word.replace("0", "н")48 nn_replacement = word.replace("0", "нн")49 if n_replacement not in n_words and nn_replacement not in self.representatives["nn"]:50 self.representatives["nn"][nn_replacement] = self.token_embedding([nn_replacement])51 elif len(n_number) == 2:52 nn_words = [re.sub("[^а-ÑÑ]+", "нн", word.strip(punctuation)) for word in text.split()53 if any([d in word for d in solution]) and ")" in word]54 for word in nn_words:55 if word not in self.representatives["nn"]:56 self.representatives["nn"][word] = self.token_embedding([word]) 57 for word in words:58 n_replacement = word.replace("0", "н")59 nn_replacement = word.replace("0", "нн")60 if nn_replacement not in nn_words and n_replacement not in self.representatives["n"]:61 self.representatives["n"][n_replacement] = self.token_embedding([n_replacement])62 def fit(self, tasks):63 for task in tasks:64 self.parse_representatives(task)65 66 def save(self, path="data/models/solver15.pkl"):67 with open(path, "wb") as f:68 pickle.dump(self.representatives, f)69 70 def load(self, path="data/models/solver15.pkl"):71 with open(path, "rb") as f:72 self.representatives = pickle.load(f)73 def predict_from_model(self, task):74 prediction = []75 text, words, n_number = self.process_task(task)76 for i, word in enumerate([word.replace("0", "н") for word in words]):77 representatives = {}78 x = self.token_embedding([word]).reshape(1, -1)79 c1 = self.get_representatives(word, self.representatives["n"])80 c2 = self.get_representatives(word, self.representatives["nn"])81 if c1:82 representatives["н"] = self.get_similarity(x, c1)83 if c2:84 representatives["нн"] = self.get_similarity(x, c2)85 if representatives:86 answer = max(representatives.items(), key=itemgetter(1))[0]87 if answer == n_number:88 prediction.append(str(i + 1))...
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