How to use _hidden_test method in green

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ssa_case_complex_no_sugar.py

Source:ssa_case_complex_no_sugar.py

1import os2import random3from collections import Counter, defaultdict4import random5from nltk.tag import StanfordNERTagger6from nltk.tokenize import word_tokenize7from nltk import pos_tag8from nltk.chunk import conlltags2tree9from nltk.tree import Tree10import pandas as pd11from htrc_features import FeatureReader12import geocoder13import folium14from pprint import pprint15from tqdm import tqdm16USERNAME = os.getenv('USERNAME')17st = StanfordNERTagger(18    '/usr/local/share/stanford-ner/classifiers/english.all.3class.distsim.crf.ser.gz'19    , '/usr/local/share/stanford-ner/stanford-ner.jar', encoding='utf-8')20def stanfordNE2BIO(tagged_sent):21    bio_tagged_sent = []22    prev_tag = 'O'23    for token, tag in tagged_sent:24        if tag == 'O':25            bio_tagged_sent.append((token, tag))26            prev_tag = tag27            continue28        if tag != 'O' and prev_tag == 'O':29            bio_tagged_sent.append((token, 'B-' + tag))30            prev_tag = tag31        elif prev_tag != 'O' and prev_tag == tag:32            bio_tagged_sent.append((token, 'I-' + tag))33            prev_tag = tag34        elif prev_tag != 'O' and prev_tag != tag:35            bio_tagged_sent.append((token, 'B-' + tag))36            prev_tag = tag37    return bio_tagged_sent38def stanfordNE2tree(ne_tagged_sent):39    bio_tagged_sent = stanfordNE2BIO(ne_tagged_sent)40    sent_tokens, sent_ne_tags = zip(*bio_tagged_sent)41    _hidden_sent_pos_tags = []42    for token, pos in pos_tag(sent_tokens):43        _hidden_sent_pos_tags.append(pos)44    sent_pos_tags = _hidden_sent_pos_tags45    _hidden_sent_conlltags = []46    for token, pos, ne in zip(sent_tokens, sent_pos_tags, sent_ne_tags):47        _hidden_sent_conlltags.append((token, pos, ne))48    sent_conlltags = _hidden_sent_conlltags49    ne_tree = conlltags2tree(sent_conlltags)50    return ne_tree51########### example52htid = 'wu.89079728994'53fr = FeatureReader(ids=[htid])54for vol in fr:55    tokens = vol.tokenlist()56temp = tokens.index.values.tolist()57########################58counts = pd.DataFrame.from_records(temp, columns=['page', 'section',59    'token', 'pos'])60counts['count'] = tokens['count'].tolist()61counts[:10]62_hidden_res_71_17 = zip(counts['token'].tolist(), counts['count'].tolist())63text_data = list(_hidden_res_71_17)64text_list = []65for w, c in text_data:66    for i in range(0, c):67        text_list.append(w)68random.shuffle(text_list)69text_reconstruction = ' '.join(text_list)70tokens = word_tokenize(text_reconstruction)71tagged_tokens = st.tag(tokens)72_hidden_tagged_tokens = []73for item in tagged_tokens:74    if item[0] != '':75        _hidden_tagged_tokens.append(item)76tagged_tokens = _hidden_tagged_tokens77ne_tree = stanfordNE2tree(tagged_tokens)78ne_in_sent = []79for subtree in ne_tree:80    if type(subtree) == Tree:81        ne_label = subtree.label()82        _hidden_res_88_29 = []83        for token, pos in subtree.leaves():84            _hidden_res_88_29.append(token)85        ne_string = ' '.join(_hidden_res_88_29)86        ne_in_sent.append((ne_string, ne_label))87_hidden_locations = []88for tag in ne_in_sent:89    if tag[1] == 'LOCATION':90        _hidden_locations.append(tag[0].title())91locations = _hidden_locations92print(locations)93most_common_locations = Counter(locations).most_common(10)94pprint(most_common_locations)95_hidden_places_list = []96for name, _ in most_common_locations:97    _hidden_places_list.append(name)98places_list = _hidden_places_list[:3]99most_common_locations = dict(most_common_locations)100geocoder_results = []101for place in places_list:102    results = geocoder.geonames(place, maxRows=5, key=USERNAME)103    jsons = []104    for result in results:105        jsons.append(result.json)106    geocoder_results.append(jsons)107countries = []108for results in geocoder_results:109    for item in results:110        if 'country' in item.keys():111            countries.append(item['country'])112top_country = sorted(Counter(countries))[0]113print(top_country)114coordinates = []115for i, results in enumerate(geocoder_results):116    for item in results:117        if item['country'] == top_country:118            coordinates.append((float(item['lat']), float(item['lng'])))119            break120print(places_list)121print(coordinates)122basemap = folium.Map(location=[37.97945, 23.71622], zoom_start=8, tiles=123    'cartodbpositron', width=960, height=512)124for i, c in enumerate(coordinates):125    folium.CircleMarker([c[0], c[1]], radius=most_common_locations[126        places_list[i]] * 0.25, color='#3186cc', fill=True, fill_opacity=127        0.5, fill_color='#3186cc', popup=128        '{} ({}, {}) appears {} times in book.'.format(places_list[i], c[0],129        c[1], most_common_locations[places_list[i]])).add_to(basemap)130print(131    'Map of relevant locations in Broneer et al.\'s "Ancient Corinth: A guide to the excavations," weighted by frequency.'132    )133basemap134page = 87135test = counts[counts['page'] == page]['token'].tolist()136print(test)137print(len(test))138from nltk.corpus import stopwords139_hidden_res_137_12 = stopwords.words('english')140stops = set(_hidden_res_137_12)141pns_list = []142for i in range(1, max(counts['page']) + 1):143    tokens = counts[counts['page'] == i]['token'].tolist()144    _hidden_tokens = []145    for token in tokens:146        if token.lower() not in stops and len(token) > 2:147            _hidden_tokens.append(token)148    tokens = _hidden_tokens149    _hidden_pns = []150    for token in tokens:151        if token[0].isupper():152            _hidden_pns.append(token)153    pns = _hidden_pns154    _hidden_combs = []155    for x, y in combinations(pns, 2):156        _hidden_combs.append(f'{x} {y}')157    combs = _hidden_combs158    pns_list.extend(combs)159print([x for x, y in Counter(pns_list).most_common(25)])160geocoder_results = []161for place in pns_list[:15]:162    results = geocoder.geonames(place, maxRows=5, key=USERNAME)163    jsons = []164    for result in results:165        jsons.append(result.json)166    geocoder_results.append(jsons)167geocoder_results168results = geocoder.geonames('Roman Forum', maxRows=5, key=USERNAME)169print(next(result.address for result in results))170g = geocoder.google('Al-Fayum')171print(g.latlng)172coordinates = [g.latlng]173basemap = folium.Map(location=[37.97945, 23.71622], zoom_start=8, tiles=174    'cartodbpositron', width=960, height=512)175for i, c in enumerate(coordinates):176    folium.CircleMarker([c[0], c[1]], radius=most_common_locations[177        places_list[i]] * 0.25, color='#3186cc', fill=True, fill_opacity=178        0.5, fill_color='#3186cc').add_to(basemap)179basemap180_hidden_test = []181for x, y in Counter(pns_list).most_common(10):182    _hidden_test.append(x)183test = _hidden_test184places = []185coordinates = []186for item in test:187    g = geocoder.google(item)188    if g:189        places.append(g.address)190        print(g.address)191        coordinates.append(g.latlng)192basemap = folium.Map(location=[37.97945, 23.71622], zoom_start=8, tiles=193    'cartodbpositron', width=960, height=512)194for i, c in enumerate(coordinates):195    folium.CircleMarker([c[0], c[1]], color='#3186cc', fill=True,196        fill_opacity=0.5, fill_color='#3186cc').add_to(basemap)...

test_constructs.py

Source:test_constructs.py

1import copy2from neuralogic.core.constructs.relation import BaseRelation, WeightedRelation3from neuralogic.core import R, Activation, Aggregation, Metadata, ActivationAgg, V4from neuralogic.core.constructs.rule import Rule5def test_predicate_creation() -> None:6    """Test different ways of predicate creation"""7    relation = R.lorem_ipsum8    predicate = relation / 19    assert predicate.arity == 110    assert predicate.name == "lorem_ipsum"11    assert predicate.special is False12    assert predicate.hidden is False13    predicate = relation / 214    assert predicate.arity == 215    assert relation.predicate.arity == 016    assert relation.predicate.name == "lorem_ipsum"17    assert relation.predicate.special is False18    assert relation.predicate.hidden is False19    relation = R.special.lorem_ipsum20    predicate = relation / 121    assert predicate.special is True22    assert predicate.hidden is False23    assert relation.predicate.special is True24    assert relation.predicate.hidden is False25    relation = R.hidden.lorem_ipsum26    predicate = relation / 127    assert predicate.special is False28    assert predicate.hidden is True29    assert relation.predicate.special is False30    assert relation.predicate.hidden is True31    relation = R.special.hidden.lorem_ipsum32    predicate = relation / 133    assert predicate.special is True34    assert predicate.hidden is True35    assert relation.predicate.special is True36    assert relation.predicate.hidden is True37    relation = R.special._hidden_test38    predicate = relation / 139    assert predicate.hidden is True40    assert predicate.name == "hidden_test"41    assert predicate.special is True42    relation = R._hidden_test43    predicate = relation / 144    assert predicate.hidden is True45    assert predicate.special is False46    assert predicate.name == "hidden_test"47    relation = R.get("_hidden_test")48    predicate = relation / 149    assert predicate.hidden is True50    assert predicate.special is False51    assert predicate.name == "hidden_test"52    predicate_metadata = R.shortest / 2 | [Activation.SIGMOID]53    assert predicate_metadata.metadata is not None54    assert predicate_metadata.metadata.aggregation is None55    assert predicate_metadata.metadata.activation == Activation.SIGMOID56    predicate_metadata = R.shortest / 2 | [Activation.SIGMOID(ActivationAgg.MAX)]57    assert predicate_metadata.metadata is not None58    assert predicate_metadata.metadata.aggregation is None59    assert str(predicate_metadata.metadata.activation) == "max-sigmoid"60    predicate_metadata = R.shortest / 2 | [ActivationAgg.MIN]61    assert predicate_metadata.metadata is not None62    assert predicate_metadata.metadata.aggregation is None63    assert str(predicate_metadata.metadata.activation) == "min-identity"64    predicate_metadata = R.shortest / 2 | Metadata(activation=ActivationAgg.MAX(Activation.TANH))65    assert predicate_metadata.metadata is not None66    assert predicate_metadata.metadata.aggregation == None67    assert str(predicate_metadata.metadata.activation) == "max-tanh"68def test_relation_creation() -> None:69    """Test relation creation related operations and properties"""70    relation = R.my_atom71    assert len(relation.terms) == 072    assert isinstance(relation, BaseRelation)73    relation = relation("a", "b")74    assert len(relation.terms) == 275    assert isinstance(relation, BaseRelation)76    relation = relation[1, 2]77    assert len(relation.terms) == 278    assert isinstance(relation, WeightedRelation)79    assert relation.weight == (1, 2)80    relation = R.my_atom["abc":1, 2]81    assert len(relation.terms) == 082    assert isinstance(relation, WeightedRelation)83    assert relation.weight == (1, 2)84    assert relation.weight_name == "abc"85    relation = relation.fixed()86    assert relation.is_fixed is True87    relation = R.my_atom88    neg_relation = -relation89    assert neg_relation.function is Activation.REVERSE90    neg_relation = ~relation91    assert neg_relation.function is Activation.REVERSE92    # t_relation = relation.T93    # assert t_relation.function is Activation.TRANSP94def test_rule_metadata():95    rule = (R.a <= R.b) | [Activation.SIGMOID, Aggregation.AVG]96    assert rule.metadata is not None97    assert rule.metadata.aggregation == Aggregation.AVG98    assert rule.metadata.activation == Activation.SIGMOID99    rule = (R.a <= R.b) | Metadata(activation=Activation.IDENTITY, aggregation=Aggregation.MAX)100    assert rule.metadata is not None101    assert rule.metadata.aggregation == Aggregation.MAX102    assert rule.metadata.activation == Activation.IDENTITY103    rule = R.a <= R.b104    assert rule.metadata is None105    rule = (R.a <= R.b) | [ActivationAgg.MAX(Activation.SIGMOID), Aggregation.AVG]106    assert rule.metadata is not None107    assert rule.metadata.aggregation == Aggregation.AVG108    assert str(rule.metadata.activation) == "max-sigmoid"109def test_rules():110    my_rule: Rule = R.a(V.X) <= R.special.alldiff(...)111    assert len(my_rule.body[0].terms) == 1112    assert my_rule.body[0].terms[0] == V.X113    my_rule: Rule = R.a(V.X) <= (R.special.alldiff(...), R.b(V.Y, V.Z))114    assert len(my_rule.body[0].terms) == 3115    terms = sorted(my_rule.body[0].terms)116    assert terms[0] == V.X117    assert terms[1] == V.Y118    assert terms[2] == V.Z119    my_rule = R.a <= R.b120    assert len(my_rule.body) == 1...

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