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cosine_esamodel_test.py

Source:cosine_esamodel_test.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3'''4The MIT License (MIT)5Copyright (c) 2012-2013 Karsten Jeschkies <jeskar@web.de>6Permission is hereby granted, free of charge, to any person obtaining a copy of 7this software and associated documentation files (the "Software"), to deal in 8the Software without restriction, including without limitation the rights to use, 9copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the 10Software, and to permit persons to whom the Software is furnished to do so, 11subject to the following conditions:12The above copyright notice and this permission notice shall be included in all 13copies or substantial portions of the Software.14THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, 15INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A 16PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT 17HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION 18OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE 19SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.20'''21'''22Created on 23.11.201223@author: karsten jeschkies <jeskar@web.de>24'''25from cosine_esamodel import CosineEsaModel, DocumentTitles26from feature_extractor.extractors import (EsaFeatureExtractor, 27                                          TfidfFeatureExtractor,28                                          LdaFeatureExtractor)29from gensim import utils, matutils30from gensim.corpora import Dictionary, MmCorpus31from gensim.models import tfidfmodel32import itertools33import logging34from models.mongodb_models import (Article, Features, User, UserModel, 35                                   RankedArticle, ReadArticleFeedback)36from mongoengine import *37import numpy as np38import unittest 39from utils.helper import load_config40from random import sample41from sets import Set42from smote import SMOTE, borderlineSMOTE43import sys44logger = logging.getLogger("unittesting")45# set up vars used in testing ("Deerwester" from the web tutorial)46texts = [['human', 'interface', 'computer'], #human interface47 ['survey', 'user', 'computer', 'system', 'response', 'time'], #computer systems48 ['eps', 'user', 'interface', 'system'], #eps49 ['system', 'human', 'system', 'eps'], #human systems50 ['user', 'response', 'time'], #response time51 ['trees'], #trees52 ['graph', 'trees'], #graph53 ['graph', 'minors', 'trees'], #minor tress54 ['graph', 'minors', 'survey']] #minors survey55dictionary = Dictionary(texts)56corpus = [dictionary.doc2bow(text) for text in texts]57concepts = ['human interface', 'computer systems', 'eps', 'human systems',58            'response time', 'tress', 'graph', 'minors tress', 'minors survey']59test_corpus_texts = [['graph', 'minors', 'eps'],60               ['human', 'system', 'computer'],61               ['user', 'system', 'human']62               ]63test_corpus = [dictionary.doc2bow(text) for text in test_corpus_texts]64UNREAD = 065READ = 166def get_features(article, extractor):67    '''68    Reaturns full features vector from article.69    Article should be a mongodb model70    '''71    #check if features of article are current version72    try:73        feature_version = article.features.version74    except AttributeError as e:75        if str(e) == 'features':76            logger.error("Article %s does not have any features." % 77                         article.id)78            #article seems not to exist anymore go on79            raise 80         81    if feature_version != extractor.get_version():82        clean_content = article.clean_content83            84        #get new features85        features = extractor.get_features(clean_content)86    else:87        features = article.features.data88    89    #sparse2full converts list of 2-tuples to numpy array90    article_features_as_full_vec = matutils.sparse2full(features, 91                                                        extractor.get_feature_number())92    93    return article_features_as_full_vec94def get_samples(extractor,95                read_article_ids, 96                unread_article_ids,97                p_synthetic_samples = 300,98                p_majority_samples = 500,99                k = 5):100    '''101    read_article_ids : Set102    unread_article_ids : Set103    n_synthetic_samples : Percentage of snythetic samples, 300 for 300%104    k : neighbourhood for k nearest neighbour, standard 5105    Returns106    -------107    array-like full vector samples, shape = [n_features, n_samples]108    array-like marks, shape = [n_samples]109    '''110    111    #Under-sample unread ids112    unread_article_ids = Set(sample(unread_article_ids, 113                                    min(p_majority_samples/100 * len(read_article_ids), 114                                        len(unread_article_ids))115                                    )116                             )117    118    #Create unread article vectors119    unread_marks = np.empty(len(unread_article_ids))120    unread_marks.fill(UNREAD)121    unread_articles = np.empty(shape=(len(unread_article_ids), 122                                         extractor.get_feature_number()))123    124    125    for i, article in enumerate(Article.objects(id__in = unread_article_ids)):126        try:127            article_features_as_full_vec = get_features(article, extractor)128            unread_articles[i,:] = article_features_as_full_vec[:]129        except AttributeError as e:130            logger.error("Article %s does not have attribute: %s." 131                         % (article.id, e))  132            133    #Create read article vectors134    read_marks = np.empty(len(read_article_ids))135    read_marks.fill(READ)  136    read_articles = np.empty(shape=(len(read_article_ids), 137                                         extractor.get_feature_number()))138    139    for i, article in enumerate(Article.objects(id__in = read_article_ids)):140        try:141            article_features_as_full_vec = get_features(article, extractor)142            read_articles[i,:] = article_features_as_full_vec[:]143        except AttributeError as e:144            logger.error("Article %s does not have attribute: %s." 145                         % (article.id, e))           146    147    #SMOTE sample minorities148    #synthetic_read_articles = SMOTE(read_articles, p_synthetic_samples, k) 149    150    #borderlineSMOTE sample minorites151    X = np.concatenate((read_articles, unread_articles)) 152    y = np.concatenate((read_marks, unread_marks))153    new_read_articles, synthetic_read_articles, danger_read_articles = borderlineSMOTE(X = X,154                                                                                    y = y,155                                                                                    minority_target = READ,156                                                                                    N = p_synthetic_samples, k = k)157    158    #Create synthetic read samples159    synthetic_marks = np.zeros(len(synthetic_read_articles))160    synthetic_marks.fill(READ)  161    162    read_marks = np.empty(len(new_read_articles))163    read_marks.fill(READ)  164    165    danger_read_marks = np.empty(len(danger_read_articles))166    danger_read_marks.fill(READ)   167    168    logger.info("Use %d read, %d unread, %d danger reads and %d synthetic samples." %169                (len(read_marks), len(unread_marks), 170                 len(danger_read_marks), len(synthetic_marks)))171    172    return (np.concatenate((new_read_articles, 173                              synthetic_read_articles, 174                              danger_read_articles,175                              unread_articles)),176            np.concatenate((read_marks, 177                              synthetic_marks, 178                              danger_read_marks,179                              unread_marks))180            )181class TestCosineESAModel(unittest.TestCase):182    def setUp(self):183        logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', 184                        level=logging.DEBUG)185        186        self.config_ = load_config(("/media/sdc1/Aptana Studio 3 Workspace/"187                                    "configs/config.yaml"), 188                                   logger, 189                                   exit_with_error = True)190        191        if self.config_ == None:192            logger.error("No config. Exit.")193            sys.exit(1)194    def tearDown(self):195        pass196    @unittest.skip("Skip small test")197    def test_constructor(self):198        #create tf-idf model199        tfidf_model = tfidfmodel.TfidfModel(corpus, normalize=True)200        201        #transform corpus202        tfidf_corpus = tfidf_model[corpus]203        204        #train esa model205        esa_model = CosineEsaModel(tfidf_corpus,206                                   document_titles = concepts,207                                   test_corpus = test_corpus, 208                                   test_corpus_targets = [1,2,2],209                                   num_test_corpus = 3,210                                   num_best_features = 2, 211                                   num_features = len(dictionary))212        213        test_doc = ['graph', 'minors', 'trees']#['user', 'computer', 'time']#214        tfidf_test_doc = tfidf_model[dictionary.doc2bow(test_doc)]215        216        #transform test doc to esa217        esa_test_doc = esa_model[tfidf_test_doc]218        219        print esa_test_doc220        #for concept_id, weight in sorted(esa_test_doc, key=lambda item: -item[1]):221        #    print "%s %.3f" % (esa_model.document_titles[concept_id], weight)222         223    #@unittest.skip("Skip bigger test") 224    def test_constructor_with_file_wikicorpus(self):225        226        #load tf-idf model227        tfidf_model = tfidfmodel.TfidfModel.load("/media/sdc1/test_dump/result/test_tfidf.model")228        extractor = TfidfFeatureExtractor("/media/sdc1/test_dump/result/test")229        230        #load tf-idf corpus231        tfidf_corpus = MmCorpus('/media/sdc1/test_dump/result/test_tfidf_corpus.mm')232        233        #load lda corpus234        #lda_corpus = MmCorpus('/media/sdc1/test_dump/result/test_lda_corpus.mm')235        236        #load dictionary237        id2token = Dictionary.load("/media/sdc1/test_dump/result/test_wordids.dict")238        239        #load article titles240        document_titles = DocumentTitles.load("/media/sdc1/test_dump/result/test_articles.txt")241        242        #Connect to mongo database243        connect(self.config_['database']['db-name'], 244                username= self.config_['database']['user'], 245                password= self.config_['database']['passwd'], 246                port = self.config_['database']['port'])247        248        #Load articles as test corpus249        user = User.objects(email=u"jeskar@web.de").first()250        251        ranked_article_ids = (a.article.id 252                              for a 253                              in RankedArticle.objects(user_id = user.id).only("article"))254        all_article_ids = Set(a.id 255                              for a 256                              in Article.objects(id__in = ranked_article_ids).only("id"))257        258        read_article_ids = Set(a.article.id 259                               for a 260                               in ReadArticleFeedback.objects(user_id = user.id).only("article"))261        262        unread_article_ids = all_article_ids - read_article_ids263        #sample test articles264        X, y = get_samples(extractor, read_article_ids, unread_article_ids)265        266        s,f = X.shape267        logger.debug("Traning with %d samples, %d features, %d marks" % 268                     (s,f, len(y)))269        #train esa model270        esa_model = CosineEsaModel(tfidf_corpus, 271                                   document_titles = document_titles,272                                   test_corpus = X, 273                                   test_corpus_targets = y, 274                                   num_test_corpus = len(y),275                                   num_best_features = 15,276                                   num_features = len(id2token))277        278        print esa_model279        280        esa_model.save('/media/sdc1/test_dump/result/test_cesa.model')281        282        tmp_esa = CosineEsaModel.load('/media/sdc1/test_dump/result/test_cesa.model') 283        print tmp_esa  284        285    @unittest.skip("too big")286    def test_constructor_with_big_file_wikicorpus(self):287        288        #load tf-idf corpus289        tfidf_corpus = MmCorpus('/media/sdc1/test_dump/result/wiki_tfidf_corpus.mm')290        291        #load lda corpus292        #lda_corpus = MmCorpus('/media/sdc1/test_dump/result/test_lda_corpus.mm')293        294        #load dictionary295        id2token = Dictionary.load("/media/sdc1/test_dump/result/wiki_wordids.dict")296        297        #load article titles298        document_titles = DocumentTitles.load("/media/sdc1/test_dump/result/wiki_articles.txt")299        #train esa model300        esa_model = EsaModel(tfidf_corpus, num_clusters = 15, 301                             document_titles = document_titles,302                             num_features = len(id2token))303        304        print esa_model305        306        esa_model.save('/media/sdc1/test_dump/result/wiki_cesa.model')307        308        tmp_esa = EsaModel.load('/media/sdc1/test_dump/result/wiki_cesa.model') 309        print tmp_esa  310        311        312if __name__ == "__main__":313    #import sys;sys.argv = ['', 'Test.testName']...

test_esa_model.py

Source:test_esa_model.py

1#!/usr/bin/env python2# -*- coding: utf-8 -*-3'''4The MIT License (MIT)5Copyright (c) 2012-2013 Karsten Jeschkies <jeskar@web.de>6Permission is hereby granted, free of charge, to any person obtaining a copy of 7this software and associated documentation files (the "Software"), to deal in 8the Software without restriction, including without limitation the rights to use, 9copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the 10Software, and to permit persons to whom the Software is furnished to do so, 11subject to the following conditions:12The above copyright notice and this permission notice shall be included in all 13copies or substantial portions of the Software.14THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, 15INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A 16PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT 17HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION 18OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE 19SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.20'''21'''22@author: Karsten Jeschkies <jeskar@web.de>23Unittests for the implementation of the ESA model.24The tests are not complete and were used for debugging.25'''26from esamodel import EsaModel, DocumentTitles27from gensim.corpora import Dictionary, MmCorpus28from gensim.models import tfidfmodel29import logging30import unittest 31logger = logging.getLogger("unittesting")32# set up vars used in testing ("Deerwester" from the web tutorial)33texts = [['human', 'interface', 'computer'], #human interface34 ['survey', 'user', 'computer', 'system', 'response', 'time'], #computer systems35 ['eps', 'user', 'interface', 'system'], #eps36 ['system', 'human', 'system', 'eps'], #human systems37 ['user', 'response', 'time'], #response time38 ['trees'], #trees39 ['graph', 'trees'], #graph40 ['graph', 'minors', 'trees'], #minor tress41 ['graph', 'minors', 'survey']] #minors survey42dictionary = Dictionary(texts)43corpus = [dictionary.doc2bow(text) for text in texts]44concepts = ['human interface', 'computer systems', 'eps', 'human systems',45            'response time', 'tress', 'graph', 'minors tress', 'minors survey']46class TestESAModel(unittest.TestCase):47    def setUp(self):48        logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', 49                        level=logging.DEBUG)50    def tearDown(self):51        pass52    @unittest.skip("Skip small test")53    def test_constructor(self):54        #create tf-idf model55        tfidf_model = tfidfmodel.TfidfModel(corpus, normalize=True)56        57        #transform corpus58        tfidf_corpus = tfidf_model[corpus]59        60        #train esa model61        esa_model = EsaModel(tfidf_corpus, num_clusters = 9, 62                             document_titles = concepts,63                             num_features = len(dictionary))64        65        print "%s\n" % str(esa_model)66        67        test_doc = ['user', 'computer', 'time']68        tfidf_test_doc = tfidf_model[dictionary.doc2bow(test_doc)]69        70        #transform test doc to esa71        esa_test_doc = esa_model[tfidf_test_doc]72        73        for concept_id, weight in sorted(esa_test_doc, key=lambda item: -item[1]):74            print "%s %.3f" % (esa_model.document_titles[concept_id], weight)75         76    #@unittest.skip("Skip bigger test") 77    def test_constructor_with_file_wikicorpus(self):78        79        #load tf-idf corpus80        tfidf_corpus = MmCorpus('/media/sdc1/test_dump/result/test_tfidf_corpus.mm')81        82        #load lda corpus83        #lda_corpus = MmCorpus('/media/sdc1/test_dump/result/test_lda_corpus.mm')84        85        #load dictionary86        id2token = Dictionary.load("/media/sdc1/test_dump/result/test_wordids.dict")87        88        #load article titles89        document_titles = DocumentTitles.load("/media/sdc1/test_dump/result/test_articles.txt")90        #train esa model91        esa_model = EsaModel(tfidf_corpus, num_clusters = 15, 92                             document_titles = document_titles,93                             num_features = len(id2token))94        95        print esa_model96        97        esa_model.save('/media/sdc1/test_dump/result/wiki_esa.model')98        99        tmp_esa = EsaModel.load('/media/sdc1/test_dump/result/wiki_esa.model') 100        print tmp_esa  101        102    @unittest.skip("too big")103    def test_constructor_with_big_file_wikicorpus(self):104        105        #load tf-idf corpus106        tfidf_corpus = MmCorpus('/media/sdc1/test_dump/result/wiki_tfidf_corpus.mm')107        108        #load lda corpus109        #lda_corpus = MmCorpus('/media/sdc1/test_dump/result/test_lda_corpus.mm')110        111        #load dictionary112        id2token = Dictionary.load("/media/sdc1/test_dump/result/wiki_wordids.dict")113        114        #load article titles115        document_titles = DocumentTitles.load("/media/sdc1/test_dump/result/wiki_articles.txt")116        #train esa model117        esa_model = EsaModel(tfidf_corpus, num_clusters = 15, 118                             document_titles = document_titles,119                             num_features = len(id2token))120        121        print esa_model122        123        esa_model.save('/media/sdc1/test_dump/result/wiki_esa.model')124        125        tmp_esa = EsaModel.load('/media/sdc1/test_dump/result/wiki_esa.model') 126        print tmp_esa  127        128        129if __name__ == "__main__":130    #import sys;sys.argv = ['', 'Test.testName']...

test_pg2ogr.py

Source:test_pg2ogr.py

1import os2import shutil3import tempfile4import unittest5import fiona6import pgdata7URL = 'postgresql://postgres:postgres@localhost:5432/pgdata'8DB = pgdata.connect(URL)9DB.execute('CREATE SCHEMA IF NOT EXISTS pgdata')10DATA_1 = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')11AIRPORTS = os.path.join(DATA_1, 'bc_airports.json')12# also test a path with spaces13DATA_2 = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data space')14AIRPORTS_2 = os.path.join(DATA_2, 'bc_airports_one.json')15class ogrpg(unittest.TestCase):16    def setUp(self):17        self.tempdir = tempfile.mkdtemp()18        self.spaced_dir = tempfile.mkdtemp("spa ced")19    def test_ogr2pg(self):20        db = DB21        db.ogr2pg(AIRPORTS, in_layer='bc_airports', out_layer='bc_airports',22                  schema='pgdata')23        airports = db['pgdata.bc_airports']24        assert 'physical_address' in airports.columns25        assert sum(1 for _ in airports.all()) == 42526    def test_ogr2pg_noindex(self):27        db = DB28        db.ogr2pg(AIRPORTS, in_layer='bc_airports', out_layer='bc_airports_noindex', schema='pgdata', index=False)29        airports = db['pgdata.bc_airports_noindex']30        assert len(airports.indexes) == 031    def test_ogr2pg_sql(self):32        db = DB33        db.ogr2pg(AIRPORTS, in_layer='bc_airports', out_layer='bc_airports_sql', schema='pgdata', sql="AIRPORT_NAME='Terrace (Northwest Regional) Airport'")34        airports = db['pgdata.bc_airports_sql']35        assert 'physical_address' in airports.columns36        assert sum(1 for _ in airports.all()) == 137    def test_ogr2pg_spaces(self):38        db = DB39        db.ogr2pg(AIRPORTS_2, in_layer='bc_airports', out_layer='bc_airports_spaced',40                  schema='pgdata')41        airports = db['pgdata.bc_airports_spaced']42        assert 'physical_address' in airports.columns43        assert sum(1 for _ in airports.all()) == 144    def test_pg2ogr_spaces(self):45        db = DB46        db.pg2ogr(sql='SELECT * from pgdata.bc_airports_spaced', driver='GeoJSON', outfile=os.path.join(self.spaced_dir, 'test_dump_spaced.json'))47        c = fiona.open(os.path.join(self.spaced_dir, 'test_dump_spaced.json'), 'r')48        assert len(c) == 149    def test_pg2geojson(self):50        db = DB51        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GeoJSON',52                  outfile=os.path.join(self.tempdir, 'test_dump.json'))53        c = fiona.open(os.path.join(self.tempdir, 'test_dump.json'), 'r')54        assert len(c) == 1055    def test_pg2gpkg(self):56        db = DB57        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GPKG',58                  outfile=os.path.join(self.tempdir, 'test_dump.gpkg'),59                  outlayer='bc_airports')60        c = fiona.open(os.path.join(self.tempdir, 'test_dump.gpkg'), 'r')61        assert len(c) == 1062    def test_pg2gpkg_update(self):63        db = DB64        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GPKG',65                  outfile=os.path.join(self.tempdir, 'test_dump.gpkg'),66                  outlayer='bc_airports')67        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GPKG',68                  outfile=os.path.join(self.tempdir, 'test_dump.gpkg'),69                  outlayer='bc_airports_2')70        layers = fiona.listlayers(os.path.join(self.tempdir, 'test_dump.gpkg'))71        assert len(layers) == 272    def test_pg2ogr_append(self):73        db = DB74        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GPKG',75                  outfile=os.path.join(self.tempdir, 'test_dump.gpkg'),76                  outlayer='bc_airports')77        db.pg2ogr(sql='SELECT * FROM pgdata.bc_airports LIMIT 10', driver='GPKG',78                  outfile=os.path.join(self.tempdir, 'test_dump.gpkg'),79                  outlayer='bc_airports', append=True)80        c = fiona.open(os.path.join(self.tempdir, 'test_dump.gpkg'), 'r')81        assert len(c) == 2082    def tearDown(self):83        shutil.rmtree(self.tempdir)84        shutil.rmtree(self.spaced_dir)85def test_tearDown():...

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